1849731454 lifecycle

Life-Cycle Analysis of Energy SystemsFrom Methodology to Applications

Bent Sørensen

Life-Cycle Analysis of Energy SystemsFrom Methodology to Applications

Other books by the author

A History of Energy – A North European case study from Stone Age topresent, 2011

Renewable Energy Reference Book Set (ed., four volumes of reprints), 2011Renewable Energy – Physics, engineering, environmental impacts,economics and planning, 4th edn., 2010 (previous editions 1979, 2000and 2004)

Renewable Energy Focus Handbook (with Breeze, Storvick, Yang,Rosa, Gupta, Doble, Maegaard, Pistoia and Kalogirou), 2008

Renewable Energy Conversion, Transmission and Storage, 2007Hydrogen and Fuel Cells, 2005 (2nd edn. planned for 2011)Life-Cycle Analysis of Energy Systems (with Kuemmel and Nielsen), 1997Blegdamsvej 17, 1989Superstrenge, 1987Fred og frihed, 1985Fundamentals of Energy Storage (with Jensen), 1984Energi for fremtiden (with Hvelplund, Illum, Jensen, Meyer andNørgard), 1983

Energikriser og Udviklingsperspektiver (with Danielsen), 1983Skitse til alternativ energiplan for Danmark (with Blegaa, Hvelplund,Jensen, Josephsen, Linderoth, Meyer and Balling), 1976

Life-Cycle Analysis ofEnergy SystemsFrom Methodology to Applications

Bent Sørensen

Department of Environmental, Social and Spatial Change,Roskilde University, Denmark

ISBN: 978-1-84973-145-4

A catalogue record for this book is available from the British Library

r Bent Sørensen 2011

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Preface

Life-cycle analysis has grown out of its infancy during recent years as a toolfor analysing the complex impacts of product life cycles and increasingly inthe energy field as a tool for analysing different solutions, both for specificinstallations and in the process of systems planning.

This book is an introduction to this field of science and assessment,providing basic methodology and practical experience through a range ofexamples. By carrying life-cycle analysis from the narrow field characterizingconventional product assessment to the much broader field of systems assess-ment, a number of new challenges are encountered, both regarding the impactsto include in the study and also with respect to the technical approach tofollow. The book attempts to give a systematic overview of these problems andtheir solution, both with the aim of serving as a textbook at university level andalso as a reference work for engineers, economists or environmental scientistsand administrators, whether on a local or a national level, in need of life-cycleassessment insights as a part of their work.

For classroom use the methodology chapters may form the basis for lectures,while the chapters dealing with case studies may be used as discussion papersand material for exercises suited for treatment in study groups, which could befocused on construction of one or more local scenarios.

The basis drawn upon for the presentation has two components: on themethodological side, work performed for the OECD (Organisation forEconomic Co-operation and Development) and its sister organisation IEA(International Energy Agency) has been used, together with material derivedfrom projects performed for various United Nations organisations (the envir-onmental programme, UNEP, and the Intergovernmental Panel on ClimateChange, IPCC). On the application side, projects have been carried out for the12th Directorate of the European Commission (the project Externalities ofEnergy of the JOULE Programme and a scenario project under the APAS/RENA programme), and last but not least for the Danish Energy Agency’sEnergy Research Programme, which financed a life-cycle analysis of both

Life-Cycle Analysis of Energy Systems

By Bent Sørensen


Published by the Royal Society of Chemistry, www.rsc.org

v

current and future Danish energy systems. Participants in all the projects arethanked for interesting discussions over the years.

The present book constitutes a complete rewriting of an earlier account byBernd Kuemmel, Stefan Kruger Nielsen and Bent Sørensen, furnishing heredetailed discussion of a wealth of new applications based on work from therecent decade. The methodology chapters of course have many sections onlylightly updated from the earlier version. After all, theory is not supposed tochange too much with time.

At the end of the book there is a Glossary of words and concepts, givingexplanations of important terms, followed by references, units and conversionfactors, and an index.

Bent SørensenGilleleje, Denmark, 2010

vi Preface

Contents

Chapter 1 Introduction 1

1.1 History 11.2 ISO-Based Implementations 91.3 The Present Approach 16References 19

Part I Methodology

Chapter 2 Life-Cycle Analysis 25

2.1 LCA Basics 262.1.1 Defining the Purpose and Scope of LCA 272.1.2 Treatment of Import and Export 32

2.2 What to Include in a LCA? 342.2.1 Qualitative or Quantitative Estimates of

Impacts 402.2.2 Treatment of Risk-related Impacts and

Accidents in LCA 402.3 Choosing the Context 41

2.3.1 Social Context 422.4 Aggregation Issues 442.5 Chain Calculations 472.6 Matrix Calculations 51

2.6.1 Marginal versus Systemic Change 532.7 Inventory Building 54References 63


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vii

Chapter 3 From Life-Cycle Analysis to Life-Cycle Assessment 67

3.1 Communicating with Decision Makers 673.2 Monetising Issues 69

3.2.1 Statistical Value of Life 713.2.2 Depreciation 73

3.3 Multivariate Presentation 74References 78

Chapter 4 Energy System Definition 79

4.1 Energy Demand and Supply 824.1.1 Basic and Derived Energy Demands 824.1.2 Energy Production, Conversion and End Use 90

4.2 Scenario Techniques 984.2.1 Why Use Scenario Techniques? 984.2.2 Methodology and Short History of

Scenario Construction 1004.2.3 Sociological and Geopolitical Basis

for Scenarios 101References 104

Part II Applications

Chapter 5 Life-Cycle Analysis of Particular Substances and

Common Issues 109

5.1 LCA of Greenhouse Gases 1095.1.1 Food Production and Silviculture 1255.1.2 Extreme Events 1275.1.3 Direct Health Impacts of Climate Change 1365.1.4 Vector-borne Diseases 1485.1.5 Ecosystem Impacts 1555.1.6 Choice of Impact Valuation Methodology 1565.1.7 Overall Valuation of Greenhouse

Warming Impacts 1595.2 LCA of Combustion Pollutants 1655.3 LCA of Radioactive Substances and Accidents 173References 181

Chapter 6 Life-Cycle Analysis of Primary and Intermediate Energy

Conversion 191

6.1 Power Production from Fossil Fuels 192

viii Contents

6.1.1 LCA of Coal-fired Power Stations 1946.1.2 LCA of Power Stations Using Natural

Gas or Fuel Oil 2046.2 Power from Nuclear Schemes 2066.3 Renewable Energy Chains 211

6.3.1 LCA of Wind Power Plants 2116.3.2 LCA of Photovoltaic and other Solar

Energy Systems 2206.3.3 LCA of Hydropower and Geothermal Energy 2276.3.4 LCA of Hydrogen Production and Large-scale

Fuel Cell Plants 2296.3.5 LCA of Food Provision 2346.3.6 LCA of Gaseous and Liquid Biofuels 238

References 247

Chapter 7 Life-Cycle Analysis of End-Use Energy Conversion 255

7.1 LCA of Road Traffic 2557.1.1 Conventional Gasoline Otto-engine

Passenger Car 2557.1.2 Fuel Cell Passenger Car Compared with

Conventional Car 2597.1.3 Other Transport Modes 270

7.2 LCA of Buildings and Space Conditioning 2727.2.1 Heat Transfer through the Building Shell 2727.2.2 Building Heating and Hybrid

Energy Systems 2787.3 LCA of Home and Work Activities 284References 289

Chapter 8 Life-Cycle Analysis on a System-Wide Level 295

8.1 LCA in National Energy-System Planning 2958.1.1 LCA of Selected Scenarios for Future

Danish Energy Systems 2968.2 Assessing Future Directions in a Global Context 3018.3 Wrapping Up 309References 311

Glossary of Words and Concepts 313

Units and Conversion Factors 317

Subject Index 321

ixContents

CHAPTER 1

Introduction

1.1 History

Life-cycle analysis and subsequent assessment are techniques that have theirorigin long before these names became used. In economic theory, everythingnot included in the analysis used to be called ‘‘externalities’’. Reasons for notincluding certain items in economic analyses were either that they did not lendthemselves easily to the monetising considered necessary by the theoreticalmethodologies used in the past, or that they were inconvenient to includebecause of their indirect and often uncertain nature. However, at an early stagethere were some such externalities that had to be considered in certain contexts,including the risk of severe accidents associated with a range of technologicalsystems, or the supply security for resources physically available only at specificlocations. Although the limitation of economic theory to direct costs led to thefrequent omission of such ‘‘indirect economies’’, there were instances wherethey could not be neglected.

An early use of techniques later to become incorporated into the life-cycleanalysis (LCA) methodology was in the field of risk analysis. Engineers havealways included estimates of risk in their design procedures and at first dealtwith such risks by adding safety margins in the design, e.g. by increasing thedimensions of structural beams by a heuristic ‘‘safety factor’’, often quite large.In a few cases it turned out that such safety factors did not avert the risk,because for some materials the thickness is not the proper factor to consider inorder to avoid breakage. In other cases there were systemic considerationsaffecting the risk pattern that could not be dealt with by simple safety factors.Contemporary engineering designs are characterised by more holistic designstrategies, but also by reducing costs by keeping safety margins small. Riskanalysis is a peculiar business, as it deals with accidents which normally arequite rare, but which in some cases can have very large negative consequences.Average calculations are therefore insufficient, or more precisely, their role in


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risk assessment has to be discussed and compared to other approaches, such as‘‘worst case’’ appraisal.

During the late 1960s it was pointed out, notably by Chauncey Starr (1969),that risk analysis could be expanded to include more factors of what we todaycall externalities. His view on risk assessment was the restrictive one that onlyaverage risk counted, that is the direct product of the probability of a givenevent and the damage it caused. This was a provocative proposition forsocieties that were accustomed to accepting daily car accidents, but less happyabout large airplane accidents and not happy at all about catastrophic nuclearaccidents that could make capitals and seats of administration deserted foryears, even if the probability was exceedingly small. Indeed, the nuclearaccident issue played an important role in the advancement of methodologiesto be used in risk assessment [see overview by Sørensen (1979a) and referencesgiven therein].

An even more important initiating event for life-cycle analysis and assess-ment was the new approach to environmental management spurred by RachelCarson’s book ‘‘Silent Spring’’ (1962). It brought knowledge of the threatcaused by persistent pesticides to the public, making up with the old approachof keeping ‘‘externality’’ problems away from general attention, to be dealtwith by civil servants and expert advisors sworn to professional silence.

From economists came the suggestion that risks and their associated prob-ability of damage should always be seen in relation to the benefits accomplishedby the activity in question. The central analysis tool in this ‘‘rational’’ approachwas therefore cost–benefit analysis. In principle, such calculations could beperformed for impacts other than those expressed in the term of risk, rangingfrom the factors traditionally incorporated into economic analysis to some ofthe externalities influencing, for example, the impact of a technological changeon society (Rowe, 1974; Pearce, 1974). One could even start to challenge theview that the future could be discounted away simply by applying any positiveinterest rate to a plan for postponing the clean-up of negative impacts to farinto the future. This use of private investor discounting principles to decisionmaking on a national or international scale, rather than distinguishing betweencommercial interest rates, social interest rates and intergenerational interestrates, was criticised as a ‘‘time-displaced irresponsibility’’ (Sørensen, 1974).Such issues were to occupy an important place in the subsequent theoreticaldiscussion of ingredients to include in a life-cycle analysis and of the best way todeal with positive and negative impacts happening at different points in time.

The notion that damage costs had to be balanced with benefits (or thatbenefits were required to exceed damage by a specified amount) had beenchallenged already by Starr (1969). His observation was that people werewilling to accept much higher voluntary risks than risks imposed upon theminvoluntarily, e.g. by a commercial airline or a power plant operator. Thisraises the important issue of perceived versus physical risk that was to play animportant role in extending life-cycle analysis to socially orientated views of thefull impacts of complex activities. It should be added that the peculiar risk-perception involved in the voluntary choice of risky activities such as

2 Chapter 1

mountain-climbing or motorcar racing for Starr was not an argument againstusing straight cost–benefit comparisons for purely technical issues such aschoosing between two types of power plant. The mixture of objective andsubjective factors in the political assessment of given activities is recognised bymost recent accounts of risk analysis methodology (e.g. Sprent, 1988).

During the 1970s, components of what constituted the ‘‘indirect econom-ics’’ were gradually identified. These included resource depletion, environ-mental impact, lifetime energy inputs, type of interest rate (see above) used ineconomic evaluations, economy of scale and degree of decentralisation,impact on foreign payments balance and on employment, and questions ofglobal equity (Sørensen, 1979b). It became clear that such precursor life-cycleanalyses could be made for individual products, for generic technologies andfor entire regional systems such as energy supply chains. Lists of concerns tobe investigated were produced and the first attempts at quantifying positiveand negative impacts were made, leaving subjective estimations of suitable‘‘indicators’’ as an option in cases where uncertainty or poorly definedquantities made concrete numbers less meaningful. A checklist of concerns,with which a system’s compatibility or lack of compatibility could beestimated, could look like this (Sørensen, 1981, 1982):

1. Satisfaction of basic biological needs2. Acceptable health risks3. Ensuring individual security4. Facilitating meaningful social relations5. Facilitating meaningful work activities6. Acceptable accident risks7. Small impacts on the physical environment, specifically

7a. Impacts on climate7b. Impacts on air, water and soil7c. Impact of availability of mineral resources7d. Impacts on biota and ecosystems

8. Positive contribution to work and mental environments9. Compatible with agreed goals of society, for instance

9a. A competitive society9b. A society based on equity9c. A society based on solidarity9d. A highly stratified type of society9e. A highly traditional society9f. A highly pluralistic society

10. Encouraging democratic participation in technology choice11. Avoiding redundant institutionalisation and infrastructure12. Avoiding formation of monopolies and power concentration13. Contributing to high material standards14. Encouraging high non-material standards15. The system having an acceptable share in the overall economy16. Having acceptable cost uncertainties

3Introduction

17. The system being resilient to changing conditions18. The system being resilient to legal and political changes19. Keeping future options open20. Minimising the risk of conflicts and war21. Improving international relations22. Not restricting development options for the poor world23. Being insensitive to uncertainty of the impact analysis

One purpose of lists such as this was to make decision makers aware ofthe many non-technical aspects of technology choices, and to suggest thateven if they could not be quantified, they still had to be somehow included inthe decision process. As an intermediary method between quantitative andqualitative analysis, the use of indicators was proposed as a less pretentioussemi-quantification of qualitative considerations, e.g. on a course scale from–1 to þ1 (in relation to the list above meaning non-compatibility to com-patibility). An example of using this idea is given in Section 3.1.

The 1980s saw increasing use of components of life-cycle analysis, such as the‘‘total energy analysis’’ aimed at including the energy spent in raw materialsand manufacture of energy conversion equipment, the operational energy useand finally the energy used at final disposal or recycling of decommissionedequipment. This constituted a complete life cycle (‘‘cradle-to-grave’’), but onlyenergy usage (i.e. conversion to lower quality) was counted, not other impactssuch as environmental damage. The purpose of such calculations was to be ableto make a fair comparison between ‘‘energy pay-back times’’ for different kindsof energy, in other words the time that the energy production of the equipmenttakes to match the initial outlays of energy in establishing the system. Withoutsuch an effort, the comparison between renewable energy, nuclear and fossilfuel-based systems could not be meaningful, as noted already in the 1970s(Roberts, 1978).

The environmental dimension was included in many of the studies carriedout during the 1980s and 1990s, using at first names such as ‘‘integrated impactassessment’’ or ‘‘full cycle analysis’’, and later the ‘‘cradle-to-grave’’ or ‘‘life-cycle analysis’’ terminology. The Environmental Impact Assessment methodol-ogy developed by the US Environmental Protection Agency (US EPA, 1978)was soon copied and made a legal requirement in several countries, under thename of ‘‘Environmental Impact Statement’’. Some of the studies includedmore than energy and environmental impacts, typically also occupational orair-pollution induced health impacts. United Nations organisations were cen-tral in these developments, with UNEP sponsoring several early environmentalstudies (see e.g. El-Hinnawi and Biswas, 1981) and IAEA looking specificallyinto health impacts (see e.g. IAEA, 1982). UNEP published an entire series ofEnvironmental Impact Reports (1979–86), mixing casual data from differentsources in a little convincing way. For example, the volume on environmentalimpacts from fossil energy use managed to forget about greenhouse gases andglobal warming (El-Hinnawi, 1981).

4 Chapter 1

The state of California was the first to require a life-cycle analysis andassessment as a part of the approval process for new industrial productsand facilities. Indeed, both the proposing party and the administration woulddesignate a consultant to make life-cycle impact reports, and the final decisionwould be using both. In several cases, there were orders of magnitude differ-ences between the two reports. Not just because one was representing theindustry involved and the other a public entity, but in most cases due to seriousdisagreement on the principles of performing life-cycle analyses. The consultingbusiness organisations saw this as a serious impediment for what otherwisecould be a very profitable business area. Early LCA studies dealt with recyclingof soft drink bottles and selling milk in bottles or cardboard boxes (see e.g.Tellus, 1992). A pressure followed for establishing standards for performinglife-cycle analyses, e.g. through organisations such as SETAC (1993; see alsoFava et al., 1992; Consoli et al., 1993) or the US EPA (1995), and subsequentlythrough the international standardisation procedures (norms for performingLCA first published in 1997; latest update in ISO, 2006). As a result, guidelineswere procured that would make the reports of different consultants rathersimilar. This, however, does not guarantee that the common results are thecorrect ones, as already demonstrated by the benchmark studies on nuclearaccident probabilities that flourished during the late 1980s, in the wake of theChernobyl accident (Sørensen, 1987). Concern over this state of affairs wasduly expressed, e.g. by Ayres (1994) and by Krozer and Vis (1998).

It is always a problem when science is turned into pseudo-science in order tosatisfy some prescribed commercial or political purpose. One wonders if the USenergy industry could have influenced a large government-supported extern-ality study of different energy supply options that came out with the surprisingconclusion that externalities were minute and unnecessary to consider (ORNL/RfF, 1992–95). To arrive at this conclusion, items like long-range transport ofatmospheric emissions from coal-fired power plants were omitted, despite theirearly identification as key causes of negative impacts (Rodhe et al., 1972),highlighted at the UN Environment Conference in Stockholm in 1972 andincidentally giving rise to the formation of UNEP. The European Commis-sion’s Framework Programme saw an interest in transferring these results toEurope and established a joint US–EU collaborative research project. How-ever, the EU side of the externality project, called ExternE, soon found that realexternalities, especially for coal-fired power plants, were far greater than foundby the US side of the study (see ETSU/IER, 1995; European Commission,1995). Because fossil externalities in the operating phase were so dominant,suggestions to extend ExternE to complete life-cycle analyses were neverwhole-heartedly followed, and the French project executioner decided to freezethe methodology and conduct a large number of country implementationsusing the fixed methodology (e.g. Curtiss et al., 1995; Schleisner and Nielsen,1997). Quite recently, the European Commission is trying again to becomeactive in the externality and life-cycle area, through a database projectperformed in collaboration with European industry, but with the restrictedISO-type interpretation of life-cycle inventories and assessment (EC/JRC, 2010a).

5Introduction

SETAC and UNEP have recently joined forces, cautiously and with lots ofdisclaimers (see e.g.UNEP, 2009) and the European Union is trying to expandits life-cycle database project to global applicability. Still, most of the marketfor performing run-of-the-mill environmental life-cycle assessments hasalready been captured by private consultants, notably the software enterprisesGaBi (2010) and Pre (2010). What they offer is easy-to-use software producingfinal reports more or less in agreement with the ISO standards, based on inputregarding the user’s product or installation, but falling back on a genericimpact database if no specific data are supplied by each user. Commercialgeneric databases are available (e.g. Ecoinvent, 2010) and although notencouraged by the ISO prescriptions, the software packages tend to offer toperform a weighting of the individual (and often incommensurable) impactresults, so that the decision maker is faced with a clear ranking of the solutionsstudied, e.g. based on ‘‘eco-points’’ (that is, indicators equivalent to monetisedimpact values, $, h, etc., translated from physical impacts in different unitsby the software company, often in a little transparent way). Faced with a graphof the type shown in Figure 1.1, the decision maker or politically electedparliamentarian would appear quite superfluous. The message is that policydecisions can safely be left to bureaucrats in possession of the right commercialsoftware.

From a scientific point of view, the life-cycle assessment proceduresproposed by ISO norms and most consultants are only a small subset of thecontent that should go into such an assessment. Mostly, only environmentalimpacts are included, and the suggested approach is to build an inventory ofprocess steps and flows involving emissions and then to assess their impacts onhuman health and selected parts of the environment. The scientific approachdistinguishes more clearly between the two phases of the work: the largelyfactual life-cycle analysis (for which the abbreviation LCA will be used in thefollowing) and then a life-cycle assessment based on such analysis, with roomfor explicit incorporation of normative and political weights (OECD/IEA,1993; Kuemmel et al., 1997). Furthermore, all types of impact should be

Figure 1.1 Result taken from commercial software comparing two technologicalsolutions to a given problem. Do we need a decision maker to make thechoice?

6 Chapter 1

considered, whether positive or negative, and whether they can be quantified orhave to be expressed in qualitative terms.

Another problem inherent in most commercial LCA software is that impactpathways from materials and processes to damage are not modelled dynami-cally, but taken from a database fixed in time and place. Some software allowsthe place to be selected differently for different parts of the analysis, butsimulation of realistic patterns are usually not feasible. Present globalisation inmanufacture implies that a given component, say of a piece of equipment, mayhave travelled back forth between, for example, Europe and SE Asia severaltimes in order to manufacture and assemble devices, adding microchips,welding and painting. This pattern is due to two current characteristics of theworld market:

� At current energy prices, transportation costs are negligible for manytypes of components and goods.

� Labour cost savings can be substantial by transferring manufacture toother parts of the world, and differences in workforce social legislationallow the employer to save additional costs.

Neither of these conditions may persist forever, but even if the existenceof regions backward in economic development but still with a reasonablyeducated workforce should cease to exist, there is still the possibility ofmaintaining poorly paid segments of a national population that on average isrich, as seen for example in the US.

The other neglect in current LCA software is in the treatment of time, despitethe importance accorded to time already through the terminology of ‘‘life-cyclesomething’’. The databases used in commercial LCA software describe asituation at a fixed point in time, and only in a few cases does one find relations,say between use of a given technology in a particular step of the ‘‘cradle-to-grave’’ chain and the impacts ensuing. This enables certain LCA properties ofemerging technologies to be estimated, assuming them to come on line X yearsinto the future, but hardly allows one to follow the changes in impacts for atechnology continuously producing impacts over several decades (or centuriesfor technologies such as nuclear reactors). To do this, continuous changesin the surrounding technological regime, such as in sources of energy andmaterials, and in efficiency (inputs used to obtain a certain output), as well ascause–effect relations in the database, would have to be quantified along atime-axis and included into the modelling. A related issue is whether futurecosts should be discounted by introduction of a positive interest rate. This isoften done for costs in monetary units, but not always for indicators.

Most current methodologies use a division of the processes involved in agiven LCA chain into background and foreground processes, proposing to usegeneric data for the background processes and site- and time-specific data onlyfor the foreground processes. If the impacts caused by use of energy areimportant, the energy mix of the country where the processes take place isspecified. This would today be a mix of coal, oil, gas, hydro, wind and nuclear

7Introduction

sources and technologies, used in many LCA studies to assess the impacts fromproduction of, say, photovoltaic (PV) panels. In case these energy inputs areimportant contributors to overall health and environmental impacts, the resultsmay indicate that PV can never become a viable technology. The picture wouldchange completely if future energy supplies are assumed increasingly andeventually totally to be derived from renewable sources. In this case, theintroduction of PV would change the ‘‘background’’ system, and in order to bemeaningful the advice that life-cycle assessment should give to the decisionmaker should be based on the future situation where the proposed technology(PV) in itself is contributing to altering the background energy mix. Thecost incurred during the transition period would require a full dynamic LCAcalculation and may furnish important information, such as whether a highintermediate-period impact barrier has to be crossed to reach the benignend-point (as illustrated schematically in Figure 1.2). Predicting the futureLCA impact by use of data valid for the current background situation is calleda marginal appraisal. It can clearly be very misleading.

The issues raised above will be treated in more detail in Chapters 2 and 3.This chapter will provide a brief illustration of the approach of the consultingbusiness, by discussing highlights from implementations of the ISO normprescriptions. Companies can (at a cost) be certified to the ISO 14040 standard,while the ISO 14044 norms are not for certification (as their precursors ISO14041–3). The norm descriptions are sold commercially and a certificationinvolves substantial payment to the ISO organisation. Establishing the norms

Figure 1.2 Difference between marginal appraisal of life-cycle costs using currentbackground data, scenario appraisal aiming at a given point in the future,and the true dynamical development, for a hypothetical system requiring atransition period to become viable (Kuemmel et al., 1997).

8 Chapter 1

was done by working groups formed by interested industry and commerce.Like in the case of other standardisation organisations, anyone who can affordthe travel and professional time spent may join the working groups.

1.2 ISO-Based Implementations

A number of recent implementations of the ISO prescriptions have beensurveyed by the European Commission (EC/JRC, 2010b). The guidelines arerestricted to environmental (and some health) effects, and most of theimplementations even treat only a subset of these. One fairly complete one isthe ‘‘ReCiPe’’ approach funded by the Dutch government and worked out byuniversities and people from Pre Consultants. The interest of the privateconsultant would be to have an alternative to the Swiss database fromEcoinvent (2010) currently employed.

Figure 1.3 shows an outline of the ReCiPe database structure. Theinventory contains mainly emissions to the air, a few to waterways andfinally land use, fossil energy and mineral resource use. The amounts

Figure 1.3 Dutch implementation of a scheme for product life-cycle analysis andassessment, restricted to environmental impacts according to the ISOprescriptions (Goedkoop et al., 2008; diagram from EC/JRC, 2010b, withgeneral permission). Abbreviations used in diagram: LCI, life-cycleinventory; DALY, disability-adjusted shortening of life (years); PDF,potential disappearing fraction of species.

9Introduction

(concentrations, doses) reaching, or in the case of resource depletion beingdrawn from, specific reservoirs are called midpoint indicators, while thedamage to humans, to the environment or to the mineral resource base iscalled endpoint indicators. The assessment consists in choosing betweenthree angles of view, defining the weight factors turning the impact into asingle number. The three perspectives are:

� Individual willingness to adapt to change, positive or negative.� Political perspective with time outlook to next election.� Ethical view based on a precautionary principle.

The insistence on merging highly incommensurable quantities such as humandisease and death, depletion of certain resources and ecosystem diversity into asingle number does appear far-fetched. The reason is disclosed by user com-ments posted on the project website (ReCiPe, 2010), where at least one userdemands that the software takes no time or effort to run and immediately givesa clear decision ready for the manager to carry out, without having to reflectfurther. The methodology has been applied to midpoint effects of certainchemical substances (Huijbregts et al., 2005; Zelm et al., 2008; Geelen et al.,2009). End-point normalization factors, that is quoting LCA outputs asfractions of those for a reference situation, are discussed by Stranddorfet al. (2005) and by Sleeswijk et al. (2008).

The European Commission study proceeds rather similarly to the Dutchone, but spends a lot more time on ensuring a consistent reporting formatthan on putting meaningful numbers into its database, justified by the ISOprescription’s similar emphasis. The initial overview of the work process is,however, quite transparent. First, the ISO overview diagram is reproduced(Figure 1.4) and later a detailed path of work progression steps is presented(Figure 1.5).

The life-cycle assessment prescription first demands that the user has a clearview of why the assessment is performed: for refining a product, for marketing,for longer-range business planning or for regulatory purposes. Then the scopeof the analysis must be defined, in terms of what to include and what to neglect.The following step is the analysis, which is confined to identifying the materialsand processes involved during the life cycle of the product, and finally theassessment would typically be running some software transforming the inven-tory list into an impact list, with standard or specific data on cause–effectrelations. Weight factors could be added already as part of the assessment, or inthe final step of interpretation. As Figure 1.4 suggests, these steps are nottraversed sequentially, but are open to iterative processes, which could involverefining calculations that turn out important, or changing processes leading toan unacceptable final interpretation.

The more detailed Figure 1.5 introduces a number of procedures com-mon in the practical implementation of the ISO specifications. Alreadymentioned is the possible division of the data inventory into a backgroundpart taken from generic sources and a foreground part requiring new data

10 Chapter 1

Figure 1.5 Detailed flow diagram of LCA process (EC/JRC, 2010b).

Figure 1.4 Overview of LCA effort according to ISO (EC/JRC, 2010b).

11Introduction

collection for the steps required to manufacture the specific product con-sidered. Figure 1.5 introduces the further possibility of aggregation, whereparticularly for background data it may be feasible (or necessary) to lump alarge number of processes or similar materials together in fewer categories.The scheme further includes one or more cycles of critical reviews, even-tually leading to iteration of parts of the whole analysis and assessmenteffort. It follows that detailed interim reporting is required for each roundof iteration, in order that the reviewers can perform their job, and not justat the end of the project.

In Figure 1.6 the assessment ingredients of a typical ISO-style process arespelled out, with the impact pathway considered for each emission or otherinitiating offence, through health or ecology impact categories to final aggregatedendpoints. The impact categories included stand out as fairly arbitrary, com-pared with a total impact analysis: even for health, environment and resourceangles of view it is easy to point at other impacts of considerable importance.

On a more detailed level, some doubts on the quality of the ISO-baseddatabases may be expressed. Consider an entry drawn randomly from theEC/JRC (2010b) database. Its name is fe1c3d03-072b-4da7-8fff-3505f9b01efc_02.01.000.xlm and it contains data on a wind turbine. The naming conventionreminds one of the software company Microsoft’s attempts to prevent usersfrom assessing or understanding update files. In the European project, a smallprogram is available for reading the database entries, and a search facility onthe internet can come up with database files containing specific search words.The typical entry selected is a four-page account of the data followed by sevenpages listing life-cycle emissions or other primary offences by manufacturing,using and disposing of the wind turbine. The data collection is commissionedby the European Commission from a German consultant. This consultantacquires the wind turbine LCA data from an American consultant and uses aFrench consultant to check the data for conformity and consistency, accordingto the data description.

Figure 1.6 Environmental impact assessment, ISO style (EC/JRC, 2010b).

12 Chapter 1

The alternating current electricity-producing wind turbine is described as ahorizontal-axis, three-bladed machine placed at a coastal site with an annualaverage wind speed 7.5 m s–1, an annual power output of 4700 MWh and anefficiency of 0.4. The data sheet states that the data pertain to the year 2002 andare partly from industry and partly from secondary literature (none of whichare further identified) and that the overall data quality is good. The purpose ofthe wind turbine is stated as delivering low-voltage electricity to a final con-sumer who does not have his own generator or transformer but uses electricitydirectly from the wind power plant.

This description raises a number of questions. Although calculation ofannual power production is not possibly from an average wind speed alone(actual variations or at least a power duration curve pertaining to the actualhub-height is required), one would estimate that the wind turbine has a ratedpower tag in the neighbourhood of 1 MW. To my knowledge, all commercialwind turbines of this size are made for grid connection, often with the gridserving to stabilize frequency and voltage. Off-grid machines for directly ser-ving the power needs of a single customer are much smaller and usuallycombined with batteries and/or a diesel generator, in contract to the descriptiongiven in the datasheet. One also wonders what the efficiency is used for. Is it thefraction of the power in the wind that is converted and is then treated as energyresource usage with some price tag on it? The input table of the datasheet listsinputs of air, nitrogen and carbon dioxide, but no corresponding outputs. Thisis clearly false: none of these resources are used. Then the input table lists aninput of wind amounting to 2.7 times the electricity output, plus a five orders ofmagnitude lower input of solar energy (!). The extra wind energy is again absentfrom the output table and appears to have been ‘‘used’’. In actuality, the windsystem is replenished behind with turbines (Sørensen, 2010) by a chain ofprocesses ultimately making up for the energy extracted by additional con-version of solar energy to winds. Thus a different efficiency could have beendefined as the amount of solar energy required to restore the wind flow patternin the atmosphere, but in any case the LCA table of EC/JRC (2010b) listsresource usage that simply should not be there. The emissions listed in theoutput table are said to derive from some selected European mix of backgroundsources for energy and other inputs to the manufacture, operation anddecommissioning of the turbine. This mix represents some past situation andthe question of whether that is consistent with the intended purpose of the LCAeffort is not considered as a problem.

One must conclude that the consultants providing the database file contenthave a very limited knowledge of wind turbine technology, and that the formalagreement with ISO formats does not provide any clue as to the validity of thedata. In other words, ISO certification of the consultant’s life-cycle work doesnot ensure quality of the data, which could equally well have consisted ofrandom numbers thrown into the database, which still would have received theapproval stamp, if only the correct ISO format is maintained.

With respect to the ISO-inspired format itself, one may note that its layoutis known from many failed database projects to increase the likelihood of

13Introduction

errors: unintelligible file names, 15-digit numbers independent of accuracy,some quantities given without units, no clear scientific references for checkingvalidity and lack of transparency allowing the user to select the appropriate oneamong related process files.

The database example critically appraised above only covers the initialinventory establishment. This is subsequently used to follow the ‘‘cradle-to-grave’’ succession of flows and processes constituting the life cycle. Sideproducts, such as waste and emissions, have their own life cycles, and so doinputs such as those needed for operation and maintenance of the primaryproduct or service-creating process. The set-up of the ‘‘cradle-to-grave’’ chainand the side chains entering or leaving it will be discussed in Chapter 2. Oneemerging issue, which has been incorporated into some of the commerciallife-cycle software, is the fact that activities in side chains may re-enter the mainor still other chains at several places and thereby create cyclic dependencies.This is a well-known issue in economic input–output models, and the remedy isto use matrix calculations to determine the solution to the equations describingthe system, rather than sequential (spreadsheet) calculations.

Once the magnitude of each substance or other assault component in therange of impact categories considered has been determined, with the help of theinventory database, then the appraisal of damage can be attempted. Requiredknowledge is a set of ‘‘dose–effect’’ relations, where for instance a givenemission of an adverse substance to the atmosphere has to be followed throughits dispersal with wind patterns over time (general circulation modelling), inorder to determine its concentration in breathing height as function of placeand time. Additionally, its eventual deposition on surfaces and entrance intohuman bodies through channels other than breathing has to be considered.Once the exposure and ingestion has been estimated, medical insights may beable to predict the health consequences, from acute to delayed diseases andinconveniences to premature death. In this example, the impact will be in theform of the number of deaths as a function of time after exposure, plus anumber of (work or leisure) days lost as the result of disease, and possibly otherforms of life quality deterioration.

It is a general feature that the impacts thus estimated will appear in differentunits. Some are easily quantifiable, like number of deaths, while other ones aremore elusive, such as measuring the inconvenience from, for example, chroniccoughs. If impacts are kept in separate units, the analysis is termed a multi-variate life-cycle assessment. During the late 20th century, most commercialLCA software producers put a lot of effort into translating incommensurablequantities, such as the ones given in the health example above, to a commoncurrency. Some used monetary values, but after critique such as ‘‘one cannotput a dollar-value on life’’ the currency was changed to ‘‘ecopoints’’. This isclearly a cheat, since the ecopoints are no different from monetary currenciesexcept that the ‘‘exchange rates’’ are known only to the consultants writing thesoftware (perhaps with some explanation given in a manual, but anyway basedon subjective judgement). Of course, a decision maker having to choosebetween different systems delivering the same product or service will have to

14 Chapter 1

make a weighting of the different impacts, but the question is the extent towhich one should leave this to the final political process or if the consultantshould try to influence the decision by providing her/his analysis in the form ofweighted numbers. Presenting the decision maker with weighted impacts is astatement that the consultant thinks him- or herself more qualified to make theweighting than the decision maker (e.g. enterprise manager or politically electedmember of a government). The common name for this view is bureaucracy:believing that the ‘‘experts’’ should exert their influence on the less qualifiedpeople in charge of making decisions, to ensure the ‘‘right’’ outcome.

To the credit of the teams formulating the ISO norms, they did not endorsesuch bureaucracy. They advise against merging impacts by the use of weightfactors, and the commercial consultants have had to play down this procedureas well as the use of artificial currencies such as ecopoints. However, theconsultants still think that decision makers are incapable of weighting incom-mensurable impacts against each other, and as mentioned some decisionmakers support this view by demanding to be presented with final weighted andmerged impact totals. A compromise suggested by the Dutch consultingcompany Pre (2008) is to reduce the multivariate impact categories to three, bygrouping similar impacts as illustrated in Figure 1.7. There is also a tendency in

Figure 1.7 Example of impact list for a given product or system, brought on acommon scale by the use of ‘‘ecopoints’’, translated from physical units orfrom qualitative descriptions by the consultant and then weighed intothree aggregated categories (based on examples given in Pre, 2006).

15Introduction

newer versions of the software to replace ecopoints by more physical units, orat least to give the user the option of choosing between different sets ofassessment units. Still, there is considerable arbitrariness in selecting impacts asbeing similar. Referring to Figure 1.7, one may ask, for example, why climateimpacts are included in ‘‘Human health’’ and not ‘‘Ecosystem quality’’. Bothare clearly influenced.

Another requirement of the ISO 14044 norm is that no important impactshould be left out. Of course, there are non-environmental impacts (see Chapter2), which may be important for some systems and not for others. These areanyway omitted in the ISO-based life-cycle assessments. However, the appear-ance of many partial life-cycle analyses in the literature (e.g. considering onlyhealth impacts or only energy impacts) makes the warning very relevant. Theproblem is just that in order to find out whether an impact is important or not, itreally has to be more or less fully assessed. There may be exceptions where thegut feeling of the analyst can be used to exclude components unlikely to have asignificant influence on the assessment, but the ISO prescription is anywayvague. Probably it should be taken just as a warning not to leave out parts of theanalysis without at least reflecting over the consequences of doing so.

1.3 The Present Approach

The promise of life-cycle analysis and assessment is to enable the incorporationof environmental and social impacts into decision-making processes. The chal-lenge is to do it on the basis of the always incomplete and uncertain dataavailable, in a way that is sufficiently transparent to avoid the modeller intro-ducing any particular bias into the decision process, by the way of selecting andtreating the incomplete data.

As a reference for evaluating future solutions, the decision maker needs toknow the impacts of current systems. Therefore to perform a LCA of importantexisting systems is the first task facing the modeller. Ideally, the data for doingthis should all be available, although in practice that is not always the case. Atleast, since the system exists, there is always the option to go out and measurethe impacts. Clearly, this at least theoretically makes an analysis of the existingsystem much more reliable than an analysis of alternatives for contemplatedfuture products and systems, from individual components to planning theentire future system, e.g. for energy usage in society.

Performing an LCA for subsequent use in decision making regardingalternative future energy systems implies that the objects of the investigationare not yet implemented (although some may already be present in othersocieties or on a smaller scale), and that more than one option appears to bepossible, either with differences in the technology used or differences in the waya given technology is produced and used. However, as it takes time to introducenew systems, the alternative scenarios being contemplated would be for asituation often several decades into the future. The reason for using a 30–50year planning horizon in the energy sector is a reflection on the time needed for

16 Chapter 1

a smooth transition to an energy system based on sources different from theones used today, with implied differences all the way through the conversionand end-use system. This takes time not only due to the requirements of thephysical implementation, but also because it is assumed that no component ofthe existing system is prematurely decommissioned. By ‘‘prematurely’’ is meantthat a component should normally not be discarded before the capital costoutlays have been recuperated, or the maintenance costs start to exceed rev-enues. More specifically, a component should not be scrapped unless there is aclear total-assessment advantage in doing so. This could happen at an earlystage, if the cost of operating the system becomes very high compared to theinitial capital cost. An example is when the fuel prices jumped up in 1973/4 (andagain in 1979), making some existing energy solutions untenable.

Apart from such discontinuities in development, most equipment is betterleft operating until the end of its economic depreciation period, and in somecases until the (likely longer) physical lifetime is exhausted, provided that non-economic life-cycle traits do not advice against it. Typical lifetimes of currentlyused energy conversion equipment are 10–20 years for most industrial equip-ment, cars, electronics and appliances, 25–30 years for power plants and certainindustrial equipment and 50–100 years for basic building structures (althoughrenovation may have to take place during the lifetime). The choice of a 30–50year scenario horizon thus ensures that most energy handling equipment can beassumed to be replaced (with what the scenario prefers) in a natural processwithout additional retirement costs. Only certain buildings will have to betreated separately, with either premature retirement or acceptance of sub-standard performance (despite retrofits) as a choice depending on a fullassessment including non-energy qualities of the building.

As a preparation for performing life-cycle analyses and assessments of entirescenario systems, a number of evaluations need to be performed for individualcomponents of the future system. Examples of such calculations will be given inChapters 5–7, followed in Chapter 8 by a discussion of system-wide studies andevaluation of complete scenarios of future systems. The use of scenarios is likelyto yield a more interesting input to the political energy debate than consideringonly those changes that may evolve by successive, marginal changes of thepresent system (cf. Figure 1.2). In fact, it is by no means certain that marginaloptimisation (which may be performed by using the same LCA methodology asfor conventional product assessments, with reliance on historical backgrounddata) will ever lead to the solutions that are optimal in the long run. Strictlyspeaking, however, there is no guarantee that the scenario method will do soeither, because in principle there are infinitely many possible future scenariosand just a few can be selected for analysis. It is therefore important that thescenarios selected for closer inspection should not just be based on the pre-ferences of the modeller, but should reflect trends visible in the social debates ofthe society in question. If the scenario work includes the main visions held in agiven society, then it is also relevant to assess the impacts of this limited set ofscenarios. A scenario will in this framework only be selected if it has beenalready identified and if there is social support for it, so construction of more

17Introduction

exotic scenarios by a researcher would only be meaningful if the advantages areso convincing that an interest can be created and the necessary social supportbe forthcoming. One may say that the energy scenarios based on renewableenergy sources were once in this category, as they were identified by a minoritygroup (of scientists and other individuals) and successfully brought to theattention of the wider public debate during the 1970s, notably in connectionwith the anti-nuclear sentiment (see e.g. Sørensen, 1975). In any case, it shouldbe kept in mind that no claim of having identified the optimum solution can bemade after having assessed a finite number of scenarios.

The methodology presentation given in Chapter 2 goes stepwise through theingredients that from a scientific point of view need to be included in ameaningful assessment and hence must be studied in the preceding life-cycleanalysis. This will include a discussion of some caveats in applying the meth-odology, such as problems of loop effects and double-counting. One importantissue is the handling of import and export, both of energy and other com-modities. Here are really two different ways of proceeding, both of which havebeen used in the literature: either to calculate all impacts in the country wherethey occur, taking into account any difference in practice and in prevailingconditions including those set by nature as well as politically imposedrequirements, or to calculate the impacts of imported products and componentsas if they had been produced locally (because the analyst may have better datapertaining to local conditions). Both approaches raise moral questions such asthose associated with exporting the components of highest negative impacts tocountries far away that may care less about these impacts. There is noscientifically right way to treat different valuation of the same impact indifferent societies. Legal compensation in the case of death in an industrialaccident may be extremely high in one country and extremely low in another.Whether to use the actual value valid in the country where the accident occursor to take a high value arising from a moral consensus arrived at in anothersociety is a question for the political assessment, not for the scientific analysis.Some of the challenges facing the decision maker are discussed in Chapter 3,covering the translation of the scientific life-cycle analysis into a decision tool.

Topics included in the life-cycle analysis and assessment include several thatare absent in the commercial, ISO-based implementations of LCA. The ISOprescription singled out noise as an impact that needs to be considered in allLCA evaluations, and it has subsequently been added to the commercialsoftware packages that missed it earlier. The analogue issue of visual intrusion,the assessment of which presently is routinely made in the EnvironmentalImpact Statements required in several countries, is not included in some of theprescriptions and current software. Other issues are accident risks and securityimpacts, and Chapters 2 and 3 add concerns for system resilience and com-patibility with the general goals of a given society.

Because the topic of this book is the application of life-cycle analysis andassessment in the energy field, Chapter 4 is devoted to defining what constitutesan energy system. The subsequent chapters go through a selection of LCAapplications, starting with a number of generic issues, including those

18 Chapter 1

associated with greenhouse gases and the induced global warming (Chapter 5)and moving on firstly to primary energy supply and intermediate energyconversion chains (Chapter 6) and then to end-use equipment providing energyservices to the final users (Chapter 7). Finally, Chapter 8 discusses life-cycleanalysis of entire energy systems, on a national, regional or global scale,and ends with a brief discussion of questions outstanding and suggestions forfurther development of the life-cycle methodology.

The energy planning concepts of top-down or bottom-up identification ofdemands also spill over into the LCA work. If categories are aggregated, it maybe easier to arrive at reasonable impact estimations in cases of poor data, andone can hope that the uncertainty of the results is smaller than if specific, veryuncertain processes are subjected to detailed evaluation. On the other hand, thebottom-up approach makes it more likely that important contributions tooverall life-cycle impacts are not forgotten. Existing software appears to beaiming at bottom-up calculations, with inventory data for quite detailedprocesses. However, in practice the actual process data needed often do notexist in the inventory and the recommendation is here to use some ‘‘similar’’process. This assumes a kind of top-down view where the precise underlyingprocesses are not so important. However, it may constitute a poorer solution touse another detailed process than the correct one, using, for example, powerinput mix from a particular country different from the one that should havebeen used. Working on specific cases in any case promotes the effort to identifyprocesses overlooked and to procure missing data.

References

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Carson, R. (1962). Silent Spring. Houghton Mifflin, Boston, MA.Consoli, F., et al. (eds.) (1993). Guidelines for life-cycle assessment: a code of

practice. SETAC, Pensacola, FL.Curtiss, P., Hernandez, B., Pons, A., Rabl, A., Dreicer, M., Tort, V., Margerie,

H., Landrieu, G., Desaigues, B., Proult, D. (1995). Environmental impactsand their costs: the nuclear and fossil fuel cycles. JOU2-CT92-0236 FinalReport, ARMINES – Ecole des Mines, Paris.

EC/JRC (2010a). Life cycle thinking and assessment. European Commission –Joint Research Centre, Inst. Environment and Sustainability, http://lct.jrc.ec.europa.eu/assessment/data.

EC/JRC (2010b). Analysis of existing Environmental Impact Assessmentmethodologies for use in Life Cycle Assessments. ILCD handbook.European Commission – Joint Research Centre, Inst. Environment andSustainability; available from http://lct.jrc.ec.europa.eu/assessment/data.

Ecoinvent (2010). Commercial emissions database. Swiss LCA Centre.Dubendorf, http://www.ecoinvent.org.

19Introduction

El-Hinnawi, E. (1981). The Environmental Impacts of Production and Useof Energy. An Assessment Prepared by the United Nations EnvironmentProgramme. Tycooly Press, Dublin.

El-Hinnawi, E., Biswas, A. (eds.) (1981). Renewable Sources of Energy and theEnvironment. Tycooly Press, Dublin.

ETSU/IER (1995). ExternE. Externalities of Energy. Vol. 3: Coal and lignite.Vol. 4: Oil and gas. Prepared by ETSU, Harwell, UK and IER, University ofStuttgart, Germany. EUR 16522/3 EN, part of a series of five volumes, seeEuropean Commission (1995).

European Commission (1995). ExternE: Externalities of Energy. Five-volumeproject report from DG XII, Luxembourg, ISBN 92-827-5212-7.

Fava, J., Denison, R., Mohin, T., Parrish, R. (1992). Life cycle assessment dataquality: a conceptual framework. Interim peer-review framework. Internalpapers, SETAC LCA Advisory Group.

GaBi (2010). ISO 14040/44 inspired commercial software. PE International,http://www.gabi-software.com.

Geelen, L., Huijbregts, M., Hollander, H., Ragas, A., Jaarsveld, H., Zwart, D.(2009). Confronting environmental pressure, environmental quality andhuman health impact indicators of priority air emissions. Atmos. Environ.43, 1613–1621.

Goedkoop, M., Heijungs, R., Huijbregts, M., Schryver, A., Struijs, J., Zelm, R.(2009). ReCiPe 2008: A life cycle impact assessment method which comprisesharmonised category indicators at the midpoint and the endpoint level.Report I. Dutch Environmental Ministry VROM, The Hague.

Huijbregts, M., Rombouts, L., Ragas, A., Meent, D. (2005). Human-toxicological effect and damage factors of carcinogenic and noncarcinogenicchemicals for life cycle assessment. Integr. Environ. Assess.Manage. 1, 181–244.

IAEA (1982). Health impacts of different sources of energy. InternationalAtomic Energy Agency, STI/PUB/594, Vienna.

ISO (2006). Environmental management – Life cycle assessment –Principles and framework (ISO 14040), Requirements and guidelines(ISO 14044). International Organization for Standardization, Geneva.

Krozer, J., Vis, J. (1998). How to get LCA in the right direction? J. Clean. Prod.6, 53–61.

Kuemmel, B., Sørensen, B. (1997). Life-cycle analysis of the total Danishenergy system. Text No. 334 from IMFUFA, Roskilde University, ISSN0106-6242.

Kuemmel, B., Nielsen, S., Sørensen, B. (1997). Life-Cycle Analysisof Energy Systems. Roskilde University Press, Frederiksberg.

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ORNL/RfF (1992–95). US–EC fuel cycle study. Estimating fuel cycle extern-alities. Reports 1–8. Oak Ridge National Laboratory and Resources for theFuture. ORNL/M 2500 (vol. 1) and McGraw-Hill/Utility Data Institute,Washington, DC.

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Pearce, D. (1974). Social cost–benefit analysis and nuclear futures. In EnergyRisk Management (Goodman, G., Rowe, W., eds.), pp. 253–267. AcademicPress, London.

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Energy Risk Management (Goodman, G., Rowe, W., eds.), pp. 327–344.Academic Press, London.

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21Introduction

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22 Chapter 1

Part I

METHODOLOGY

CHAPTER 2

Life-Cycle Analysis

The life-cycle approach starts with an analysis that defines the flows andprocesses involved during the life cycle of the object studied and collectsnecessary data on quantities of materials, time spent on different tasks andtransfer or transport of parts or work between regions, all focusing on thepathways most important for the object studied, but at least identifying theconnectivity with other potentially contributing pathways, for which one maybe so lucky to have independent life-cycle studies to draw from.

In addition to the data relevant for the particular object (product or system)being studied, an inventory may exist, or be created, of the general relationsbetween causes (emissions, waste streams, labour requirements, stressful work,and so on) and the exposure imposed on human beings, on society and on theenvironment, whether manmade or ‘‘natural’’. However, there may be parts ofthe exposure database that do depend on the specific circumstance of theinitiating activity, say where dispersal (e.g. through waterways or the atmo-sphere) has to be studied in order to arrive at the relevant exposures (such ashuman intake of toxic substances, amounts of acid rain falling onto a particularecosystem, etc.).

A seconddatabase of a general nature (i.e. not associated justwith the particularproduct or system under investigation), but likely time and location dependent,would contain relationships between exposures and the impacts (of positive ornegative kinds) being implied, including time sequences of delayed effects.

These prerequisites for an assessment will be described in more detail below,with a central part being devoted to the provision of a list of important effectsto be evaluated as part of a serious life-cycle study. Although such a list isnecessarily open-ended, it is important to indicate some obvious areas to whichto pay attention, so much more because some of them are often forgotten inmany of the studies currently presented as life-cycle assessments. The additionalconcerns cannot be dismissed as fantasies of the present author: many of themhave played an important role in historical cases and in arriving at politicaldecisions based on such assessments. Because life-cycle assessment is used as an


By Bent Sørensen



25

instrument for regulation, there will necessarily be agents trying to pull theteeth out of the method, by restricting its scope and by watering down itscritique of ongoing or contemplated industrial practices. If companies are to beallowed to use green LCA certificates in their marketing of products and ser-vices, the political overseers should at least make sure that there is a realcontent behind the green labels.

2.1 LCA Basics

A growing understanding has been forthcoming over recent decades that anykind of public assessment work performed in our societies, from consumer-aimed product evaluation to long-term planning decisions, should take intoaccount a broad range of environmental as well as social impacts. This focuseson the sometimes huge difference from earlier decisions based only on directcost and the full cost assessment, where the word ‘‘cost’’ must now be taken toinclude all conceivable impacts happening during the full life-cycle of the objectsubjected to public assessment. By ‘‘public assessment’’ is meant assessmentmade on a societal level, whether by governments, consumer organisations,businesses or industries. The contrast is personal assessments made by anindividual. It may well use tools similar to that of public assessment, but there isno point in making prescriptions for the reflections made by individual persons.

Some life-cycle impacts may be described by the economic concept ofexternalities (defined as social costs that are not incorporated in market prices).Some externalities can be quantified and expressed in monetary terms, whileothers are qualitative or normatively defined. There are impacts exhibiting avery complex structure. For example, the labour required for a given processstep has an impact on the employment situation and will therefore depend onwhether the society in question has a situation with full employment or onewith massive unemployment. Work requirements would in the first case be seenas a negative impact, in the second as a positive impact. In this example ittherefore also matters if the employment is created in the society benefitingfrom the product or service created, or in other countries without such benefits,but perhaps interested in the employment for its own sake.

It is the role of societies (through government legislative or other initiatives)to make sure that the indirect costs are not neglected in consumer choices or indecision-making processes related to planning for the society or for entitieswithin it. The way externalities are included will depend on the political pre-ferences. Possible avenues range from taxation to regulative measures.

Life-cycle analysis is a tool suited as input for assisting planners and decisionmakers in performing the necessary assessments related to external costs. TheLCA method in principle can address all direct and indirect impacts of atechnology, whether a product, an industrial plant, a system or an entire sectorof society. Proper LCA incorporates impacts over time, including impactsderiving from materials or facilities used to manufacture tools and equipmentfor the process under study, all operational impacts, and it includes final

26 Chapter 2

disposal of equipment and materials, whether involving reuse, recycling orwaste disposal. The two important characteristics of LCA can be stated as:

� Inclusion of ‘‘cradle-to-grave’’ impacts, wherever they occur.� Inclusion of indirect impacts imbedded in materials and equipment.

Gathering of data relevant for LCA work has been ongoing for a con-siderable duration of time, and although there are still many gaps in dataavailability, it has in many cases become possible to perform credible LCAinvestigations. Still, routine incorporation of LCA methods in public decisionprocesses is still far from advisable, and the role of LCA should primarily beseen as one of raising the level of debate and improving the informationavailable to decision makers.

2.1.1 Defining the Purpose and Scope of LCA

The first consideration in formulating a life-cycle assessment strategy is toformulate the purpose of the analysis. It may serve several purposes (Kuemmelet al., 1997):

(a) To determine impacts from different ways of producing the sameproduct.

(b) To determine impacts from different products serving the same purpose.(c) To determine all impacts from a technical system, such as an off-shore

wind-power array with associated power transmission to land.(d) To determine all impacts from a sector of the economy, such as the

energy sector.(e) To determine all impacts from an entire socio-economic system and the

activities within it.

In the two first cases, a or b, the analysis is usually called a product LCA,whereas an analysis with the purposes c, d or e define a systems-level LCA. Thepresent book focuses on energy and the products considered are equipment forenergy production, conversion or use. The energy system studies dealt withwould usually fall into categories c or d. Many impact assessments and otherkinds of life-cycle work made in the past were confined to a single chain ofenergy conversions, often based on site- and technology-specific componentsand falling into category c. Figure 2.1 shows a generic energy chain of the typeused in such calculations.

The scope of analysis would ideally be in one of the following forms:

A: Chain analysis with inclusion of side chains.B: System-level analysis.

where in case B a full matrix calculation allowing two-way interaction betweenany compartments in the model is called for, but where simplified approx-imations are often used.

27Life-Cycle Analysis

In a chain analysis (A), impacts include those of the main chain (Figure 2.1)as well as impacts caused by processes taking place in connection with sidelineinputs or outputs (Figure 2.2). Some sideline processes may have otherpurposes besides creating flows into or from the studied life-cycle chain.Finding out what should be allocated to the chain investigated can thereforebe a complex task. A simple example of dealing with such a situation is if theequipment used in a given chain step, say representing an oil refinery, isprovided by a manufacturer who sells 20% of his production to the oilrefinery and 80% to other customers. In this case, one would simply allocate20% of each of this manufacturer’s impacts (environmental, social) to the oilrefinery life-cycle.

In general terms, each physical component of the chain can be considered asgoing through a number of life-cycle phases, from construction activitiesthrough a period of operation and concurrent maintenance, evolving intostages of major repairs or dismantling as part of final decommissioning. Eachstage has inputs of materials, energy and labour, and outputs of both damage-causing agents (e.g. air pollution) and useful components. Impacts may thus bepositive or negative: the positive impacts are often the intended benefits of theactivity, for energy chains the products or services associated with energyservices to the end-user, although positive impacts (such as employment ifdesired) could also appear in side chains. The negative impacts are a range ofenvironmental and social impacts, coming from both the main chain and sidechains. The magnitude of impacts depends not only on the technologies used,but also on skills of operators, management and maintenance quality, as well as

Figure 2.1 Generic energy chain.

28 Chapter 2

on the structure of the surrounding society receiving the impacts but possiblyalso being able to influence their magnitude.

Moving now to energy systems, defined as complete systems for generatingenergy from primary sources, transmitting and distributing the energy andsupplying it to a range of end-users, defined by some domain of demand, e.g.specified by type, by geographical coverage or by recipient profile. Figure 2.3shows a recent global energy system in an highly aggregated form. Of course, inphysical terms this is part of an even larger system describing the energy flowson our planet, as indicated in Figure 2.4. Physically, the system componentswould be facilities for extracting or collecting energy, for importing orexporting energy, for converting energy from one form to another, for trans-porting and distributing energy, and finally for transforming the energy intoa useful product or service, as indicated in Figure 2.1. Products and services arethe demanded quantities, as seen from human society. They obviously changewith time and according to the development stage of a given society (cf.Chapter 4).

Looking a moment at the global energy system in Figure 2.3, it is strikingthat the overall efficiency is as low as 12%. That 47% of the energy is lost incentralised conversions between energy forms (in refineries, gas treatment

Figure 2.2 Input and output streams for a particular life-cycle step.


plants, power plants, etc.) is well known, but going to the conversions takingplace at the end-user, it is perhaps less known how substantial the losses are.The end-use efficiency is calculated as the actual delivered energy over thetheoretical minimum, or if that is not available, relative to the energy used if thebest currently known technology had been employed. ‘‘Energy used’’ means

Figure 2.3 The global energy system in 2007, from primary energy sources to finalenergy services (units GWy per year). Each compartment shows input andoutput (IEA, 2009). Energy services are rough estimates.

Figure 2.4 Physical structure of the Earth’s energy system (adapted from Sørensen,1979b).

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converted to low-grade heat – energy itself is a conserved quantity! The global2007 end-use efficiency in transportation is in this way estimated as 14%, upfrom 5% in 1990. The average road vehicle fuel-to-wheel efficiency has between1990 and 2010 increased from under 15% to over 20% (best vehicle 27%;Sørensen, 2005) and the rolling and air resistance losses have similarly declined,but are still higher than for a theoretical ‘‘best technology’’ (say magneticlevitation track bullet vehicle). Similar remarks can be made for other types ofenergy, such as the transition from incandescent light bulbs to more advancedelectricity-to-light converters.

A system-level analysis may be performed by calculating the impacts fromeach device in the system separately and then summing up the individualresults. For example, the direct impacts from running an oil refinery are cal-culated, the direct impacts of the equipment manufacturer likewise, as well asany inputs received from other sources, and at the end the sum of all the cal-culated impacts will provide a true total without double counting.

The cases presented in this book to illustrate the life-cycle method will rangefrom chain calculations (A) for specific energy equipment (such as photovoltaicpanels) to partial or complete systems (B), in which the energy sector has to betreated in detail but other sectors of the economy in most cases indirectly, usingaggregated and generic data.

A double counting problem could arise in this type of analysis if impactsfrom the energy system are not only calculated directly but are also containedin some of the generic data for the background system. It may be difficult toexclude energy impacts from generic data pertaining to processes outside theenergy sector. In many cases, but not all, it will be straightforward to make thedistinction, because the impacts found in the literature are normally dividedinto sectors of the economy. A general solution to the problem is to use matrixcalculations including all sectors, and the problem only arises when simplifi-cation of the LCA calculation is attempted.

Figure 2.5 illustrates the double-counting problem: if a chain LCAanalysis is made for each chain identified in Figure 2.5b, there will be doublecounting of both some direct and some indirect impacts. For the directimpacts, a solution would be to calculate impacts for each of the compartmentsin Figure 2.5a and then sum them up; as regards the indirect impacts, one has tomake sure that there is no hidden double counting. This could be accomplishedby including only the fraction of indirect impacts in side chains that do notinvolve the processes of the primary system. In other words, if the entire energysystem is included in the primary part of the analysis, one should simply omitenergy-related impacts from the indirect side-chains. If only a partial energysystem is being analysed, one would still have to include some impacts fromother parts not explicitly included within the system.

Most system-level life-cycle assessments made so far do not follow suchprescriptions for avoiding double counting. In particular, the use of matrixcalculation is rare, for obvious reasons of computation magnitude. Theimportant thing in such cases is to discuss the possible impact of not beingtotally consistent. In many cases, the error can be argued to be small.


2.1.2 Treatment of Import and Export

Many of the available data sources include indirect impacts based on anassumed mix of materials and labour input, taking into account the specificlocation of production units, mines, refineries, etc. This means that an attempthas been made to trace back the origin of all ingredients in a specific product(such as electricity) using a bottom-up approach, which is suitable for com-parison of current ways of furnishing the product in question (e.g. wind, coal ornuclear electricity). Ideally, the selection of regions to import from shoulddepend on a life-cycle assessment of the impacts associated with each con-templated supplier.

In the case of the analysis of an entire energy system, using data for specificsites and technology, and for specific countries from which import is currentlyin effect, may not be the best option. Especially for future energy supply sce-narios, it seems improper to use data based on selected current locations ofmines, refineries and other installations. One may of course average over manydifferent sets of data, in order to obtain average or ‘‘generic’’ data, but theselection of future energy systems should not depend sensitively on where, forexample, utilities presently choose to purchase their fossil fuels in a particularyear, and therefore a different approach has to be found.

One consistent methodology is to consider the energy system in each countrybeing studied as a part of the national economy of that country, such that if thecountry chooses to produce more energy than needed domestically in order toexport it, this constitutes an economic activity no different from, say, Denmarkproducing more Lego blocks than can be used by Danish children. Exports are

Figure 2.5 Energy system (a) with forward chains indicated (b).

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an integral part of the economy of a small country such as Denmark, because itis not possible or practical to produce every item needed within the society. Thecountry must thus export some goods in order to be able to import other onesneeded. Seen in this way, it is ‘‘Denmark’s own fault’’ if manufacturing goodsfor export turn out to have more environmental side-effects in Denmark thanDanish imports have in their countries of origin, and the total evaluation ofimpacts should simply include those generated as part of the economy of thecountry investigated, whether for domestic consumption or export. Likewise,the impacts of goods imported should be excluded from the evaluation for theimporting country, except of course for impacts arising during the operation oruse of the imported items in the country (e.g. burning imported coal).

A consistent methodology is thus to include all impacts of energy productionand use within the country considered, but to exclude impacts inherent inimported materials and energy. This is illustrated in Figure 2.6B. The alter-native shown in Figure 2.6A is count impacts imbedded in imports, but toexclude those of exports because they would be counted in the country thatimports them.

Looking at the assessment of future systems based on renewable energyconversion, some countries would have to import much of the conversion

Figure 2.6 Two consistent ways of treating imports and exports in LCA.


equipment. If a high fraction of the impacts are coming from materials such asconcrete, metals or composites, then it becomes important whether or not thesematerials have to be imported. The best method would certainly be that of case(A) in Figure 2.6. One argument against case (B), confining externality calcu-lations to impacts originating within the country, is that this could lead topurchasing the most environmentally problematic parts of the system fromcountries paying less attention to the environment than the importing country.Countries in the early stages of industrial development have, at least histori-cally, had a tendency to pay less attention to environmental degradation,making room for what is negatively termed ‘‘export of polluting activities to thethird world’’. The counter argument is that this may be better for the countriesinvolved than no development, and that when the countries reach a certain levelof industrialisation they will start to concern themselves with the environmentalimpacts (quoting examples such as Singapore or Hong Kong). Unfortunately,this confidence in a positive course of development does not seem universallyvalid.

It is also important to take into account the transport of pollutants acrossborders, which in many cases makes it impossible to defend calculations con-sidering only impacts within the boundaries of a particular country. Impactsfrom trans-border pollution basically invalidate both approaches of Figure 2.6.However, it may still be methodologically meaningful to start with calculationsof impacts country by country, provided that trans-boundary impacts (airpollution, climate changes) are then considered and included in the total impactassessment.

In many life-cycle studies, the difficulty in obtaining data from some of thecountries actually involved has forced the investigators to use generic data ordata from a different region. For example, the ‘‘ExternE’’ coal externality studyof the European Union mentioned in Chapter 1 (ETSU/IER, 1995) uses coalmined in Germany or England, based on the impacts of mining in thesecountries, rather than the less known impacts associated with coal mining inmajor coal exporting countries, from where the coal is or will be imported.

For countries where imports and exports are a small fraction of the GNP(e.g. USA), the problem is of much smaller proportions than, for example,for Denmark. Calculating LCA impacts using scheme (B), only including theeconomy in question is similar to conventional economic input–output calcu-lations. Scheme (A), on the other hand, focuses on questions of global equity.The mentioned ExternE study contains an important statement on this, bymeasuring lives lost (by accidents or impact-induced disease) according toEuropean life-insurance standards, rather than according to the compensationspaid in the countries where the lives are lost. This will be further discussed inSection 3.2 of Chapter 3.

2.2 What to Include in a LCA?

The history of life-cycle work has taken two distinct paths. One is associatedwith the energy life-cycle analyses being developed from chain analysis without

34 Chapter 2

imbedded impacts to analysis including such effects, both as regards environ-mental and social impacts. The basic scope of energy LCA was described inSørensen (1993, 1996, 1997), based on the precursors mentioned in Chapter 1.The main ingredients suggested for inclusion in an energy LCA are listed below.The other path is associated with consumer product LCA and has been pushedby the food and chemical industries and by consultants, again as discussed inChapter 1.

The experience accumulated since the early enthusiasm about the possiblerole of life-cycle assessment work has been replaced by a more realistic position:LCA is not and cannot be made a routine screening method for products orenergy systems, but has to remain an attempt to furnish more information tothe political decision maker than has previously been available. The decisionprocess will be of a higher quality if these broader impacts are considered, butthe technique is never going to become a computerised decision tool capable ofreplacing the political debate leading to a decision. This is already evident fromthe incommensurability of different impacts, which cannot always be mean-ingfully brought to a common scale of units: it is in the light of the above viewon the scope of LCA that a list of impacts to consider is established, withoutclaiming it to be inclusive or complete.

The types of impacts that may be contemplated for assessment reflect tosome extent issues that at a given moment in time have been identified asimportant in a given society. It is therefore possible that the list will be modifiedwith time, and that some societies will add new concerns to the list. However,the following groups of impacts, a summary of which is given in Table 2.1,constitute a fairly comprehensive list of impacts that have been considered in atleast some of the studies made (Sørensen, 1993).

� Economic impacts such as impacts on owner’s economy and on nationaleconomy, including questions of foreign payments balance and employment

This group of impacts includes those of the direct economy reflected inmarket prices and costs. All other impacts can be said to constitute indirect

Table 2.1 Impacts to be considered in life-cycle analysis of energy systems.

Economic impacts such as impacts on owner’s economy and on national economy,including questions of foreign payments balance and employment

Environmental impacts, e.g. land use, noise, visual impact, local, regional and globalpollution of soil, water, air and biota, impacts on climate

Social impacts, related to satisfaction of needs, impacts on health and workenvironment, risk, impact of large accidents

Security and resilience, including supply security, safety against misuse, terror actions aswell as sensitivity to system failures, planning uncertainties and changes in futurecriteria for impact assessment

Development and political impacts, such as degree of consistency with goals of a givensociety, impacts of control requirements and institutions, openness to decentralisationand democratic participation


costs or externalities, the latter if they are not included in prices through, forexample, environmental taxes. Economy is basically a way of allocating scarceresources. In applying economic assessment to an energy system, the differenttimes at which different expenses have to be paid must be taken into account,e.g. by discounting individual costs to present values. This again gives rise todifferent economic evaluations for an individual, an enterprise, a nation andsome imaginary global stakeholder. One possible way of dealing with theseissues is to apply different sets of interest rates for the above types of actors, andin some cases a different interest rate for short-term costs and for long-term,intergenerational costs, even for the same actor.

The national economy evaluation includes additional factors such as theimport fraction (showing up in the balance of foreign payments), theemployment impact (affected by the distribution between labour and non-labour costs, which may involve a choice even for the same technology) andmore subtle components such as regional economic impacts. Impact evalua-tions must pay particular attention to imports and exports, for the reasonsgiven in Section 2.1.

� Environmental impacts, e.g. land use, noise, visual impact, local pollution ofsoil, water, air and biota, regional and global pollution and other impacts onthe Earth–atmosphere system, such as climatic change

Environmental impacts include a very wide range of impacts on the naturalenvironment, including atmosphere, hydrosphere, lithosphere and biosphere,but usually with the human society left out (but later included under theheading of social impacts). Impacts may be classified as local, regional andglobal. At the resource extraction stage there is the impact of resource deple-tion, in addition to the impacts associated with extraction processes.

The efficiency of resource extraction is a quantity that is often difficult totreat in a meaningful way. If the resource is a fossil fuel, there are losses intreatment and refining, which are straightforward to estimate, but there can bemore elusive losses in the extraction process itself. Oil and natural gas extrac-tion has historically been able to recover about a third of the fuel estimated tobe in place in the geological formation (Sørensen, 2005, Chapter 7.4). Someadditional extraction is possible by enhanced recovery, e.g. pumping a gasthrough the borehole or operating at an elevated temperature. The energy spentin heating and pressure formation is less than the energy in the additional oil ornatural gas extracted. The efficiency calculation should include all processlosses, but should the efficiency be taken relative to the total fuel in situ orrelative to the maximum considered recoverable? If it is possible to go back andextract the rest, it should not be counted as a loss.

Similar questions arise in the case of renewable energy extraction. A state-of-the-art free-stream wind turbine currently on average extracts some 50% of itsnameplate rating and around 34% of the power in the wind, again averagedover a substantial period, say a year. However, is the wind energy not capturedto be regarded as a loss? It is required that the turbine recovers only a fraction

36 Chapter 2

of the wind swept, because the air cannot be brought to a standstill behind theturbine, for reasons of momentum continuity, and the energy extracted willunder these conditions be replenished by conversion of temperature andpressure differences to air motion somewhere else in the atmosphere (Sørensen,2010). Like in the fossil case, it is thus suggested to include only the energyactually extracted into the life-cycle analysis.

In the past, calculations for various energy conversion chains have beenperformed, keeping track only of energy inputs and outputs. Such net-energyassessments are typically expressed as an energy payback time, which is areasonable parameter to monitor for a system created with the purpose ofproducing energy where it would be unacceptable if energy inputs to be paid forexceeded energy outputs. The issue is complex, as the recent example of ethanolas a gasoline replacement in Brazil shows: to avoid a negative balance ofpayments due to imported oil products, a fuel for transportation has beengenerated from indigenous sources, even if the net energy in the beginning wasnegative (which is no longer the case, as long as solar energy inputs are notincluded; see Goldenberg et al., 2008). The example underlines the role of theenergy payback time as being only a secondary indicator, which should not beincluded in a life-cycle assessment if all the primary indicators of positive andnegative impacts are already sufficiently well estimated.

The life-cycle impacts affecting the natural ecosystems are in some cases alsothe ones that affect human well-being or health, possibly with a time delay.Although human societies are strictly speaking part of the natural ecosystem, itis convenient and sometimes necessary to treat impacts on human societies asseparate entities, as will be done below. However, the calculations needed areoften connected, as one may be dealing with a pollutant first injected into thenatural environment and later finding its way to humans after having beentransported, undergoing change of form and possibly becoming diluted, until itfinally ends up in the human body by inhalation or through food and water.The steps through such pathways have to be calculated in order.

� Social impacts, related to satisfaction of needs, impacts on health and workenvironment, risks, impact of large accidents

Social impacts include the impacts from using the energy that is provided,which means the positive impacts derived from services and products arisingfrom the energy use (usually with other inputs as well) and the negative impactsassociated with the energy end-use conversion, or otherwise reaching humansociety, such as environmental impacts with origins not covered in the envir-onmental category. Indeed, social impacts derive from each step in the energyproduction, conversion and transmission chain. Examples are health impacts,work environment, job satisfaction and risk, including the risk of large acci-dents. It is often useful to distinguish between occupational impacts andimpacts to the general public. If the impacts involve the transfer of pollutantsfrom the general environment to human society, a detailed investigation of themechanisms of such a transfer may be required. This is true both for releases


during normal operation of the facilities in question, e.g. power plants, and foraccidents. Clearly, the accident part is a fundamental risk problem that involvesestimating probabilities of accidental events of increasing magnitude.

Work environment has become a major issue in those societies seeking toimprove life quality for its citizens. By removing not only conditions causinghealth injuries (unsafe scaffold work, hard repetitive labour damaging parti-cular parts of the human body, handling toxic substances, etc.) but alsostressing and degrading work circumstances associated with command-basedmanagement (replacing it by proper information with clear reasons given forany change in working conditions, or by negotiated changes), the stage is set forimproving job satisfaction and making employees and workers not see their jobjust as a chore needed only for earning salaries that allow them to do what theyconsider meaningful, outside working hours. Clearly, if work can becomeconsidered as a meaningful activity for those performing it, their lives areeffectively prolonged by about 33%. Several of the impacts mentioned here willbe difficult to quantify, although are not less important because of that.

� Security impacts, including both supply security and also safety againstmisuse, terror actions, etc.

Security can be understood in different ways. One is supply security andanother is the security of energy installations and materials against theft, sabo-tage and hostage situations. Both are relevant in a life-cycle analysis of an energysystem. Supply security is a particularly important issue for energy systemsdepending on fuels that are unevenly spread over the planet. Indeed, some of themost threatening crises in energy supply have been related to supply security(1973/74, oil supply withdrawal; 1991, Gulf War; 2003, invasion of Iraq).

Problems of terrorism have come up repeatedly during the past century(1914, Sarajevo assassinations; 1933, Parliament House burning in Berlin; 1972,massacre at the Munich Olympics; 1988, Lockerbie plane blow-up; 2001, air-planes flown into World Trade Center high-rise buildings and Pentagon, tomention some spectacular ones). Similar assaults on energy installations havebeen constantly feared and several studies have been made of the possibleimpacts of such types of terrorism, which are primarily directed at installationsusing nuclear technologies in the energy sector. Concerns range from terroristsstealing weapons-grade fissile material to inducing nuclear accidents of Cher-nobyl magnitude (Gregory, 2007; Battacharjee, 2010; Bunn, 2010). Some earlystudies found it unthinkable that anyone would purposely fly a plane into anuclear reactor (Silver and Sorensen, 1978; see also Sørensen, 1979a). Unfor-tunately, gentlemanly rules are no longer the name of the game.

� Resilience, i.e. sensitivity to system failures, planning uncertainties andfuture changes in criteria for impact assessment

Resilience is also a concept with two interpretations: one is the technicalresilience, including fault resistance and parallelism, e.g. in providing more

38 Chapter 2

than one transmission route between important energy suppliers and energy uselocations. Another is a more broadly defined resilience against planning errors(e.g. resulting from a misjudgement of resources, fuel price developments orfuture demand development). A more tricky, self-referencing issue is resilienceagainst errors in impact assessment, assuming that the impact assessment isused to make energy policy choices. All the resilience issues are connected tocertain features of the system choice and layout, including modularity, unit sizeand transmission strategy.

The resilience questions may often be formulated in terms of risk, whereuncertainties are assigned to various factors that might influence system sta-bility. The planning uncertainty has a further component associated with futurechanges in human or societal values, manifesting themselves by alterations inthe criteria that will be used to determine viability and acceptability, here ofenergy system solutions.

� Development impacts (e.g. consistency of a product or a technology with thegoals of a given society)

Energy systems may exert an influence on the direction of development asociety will take, or rather may be more compatible with one developmentgoal than with another. These could be goals of decentralisation, goals ofconcentration on knowledge business rather than heavy industry, etc. For so-called developing countries, goals should include satisfying basic needs, fur-thering education, improving equitable distribution of wealth and raisingstandards. Goals of the most wealthy nations are often more difficult toidentify, because many members of society are frequently being swayed bywaves of ethically dubious advertising (for products as well as for behaviouror political views). People forget to ask what is wrong with a product since itneeds advertising. Does it not fulfil any need? Work that was once seen as away of being able to acquire things needed has become a goal in itself. Effi-cient solutions are avoided because they are seen as increasing unemployment,rather than allowing reduction in laborious chores and sharing the remainingtasks. Most nations have adopted an economic system that encourages suchwaste, indeed any kind of waste. The well-being of a nation is measured interms of the gross national product (GNP), which is basically a measure ofinefficiency: lowering the efficiency so that it takes three times as much effort(activity) to do a certain thing is counted as a wonderful three-fold growth. Inmost of the world, half the current GNP is generated by financial transac-tions, rather than by the creation of any physical product or service. Suchsystems regularly crash, but the minority groups gaining from maintainingthis 18th century British economic paradigm has so far been able to apply thenecessary advertisement and persuasion to make the majority forget thefinancial crises within a year or two.

� Political impacts include, for example, impacts of control requirements andon openness to decentralisation in both physical and decision-making terms


There is a geopolitical dimension to the above issues: development orpolitical goals calling for import of fuels for energy may imply increasedcompetition for scarce resources, an impact which may be evaluated in terms ofincreasing cost expectations or in terms of increasing political unrest. Fuelimporting countries may shy away from criticising human rights violations inthe exporting country, or may unduly interfere with internal politics in theexporting country in order to secure its fuel supply. Disagreements may at theextreme lead to ‘‘energy wars’’. The political issue also has a local component,pertaining to the freedom or lack of freedom of local societies to choose theirown solutions democratically, if the solutions disagree with those of the energyexporting industry and the interests of their foreign clients.

2.2.1 Qualitative or Quantitative Estimates of Impacts

There is a consensus that one should try to quantify as much as possible in anyimpact assessment. However, items for discussion arise in the handling of thoseimpacts that cannot be quantified (and later for those quantifiable impacts thatprove to be hard to monetise or otherwise make comparable to other impacts).One historically common approach is to ignore impacts that cannot bequantified. Alternatively, one may clearly mark the presence of such impactsand in any quantitative summary add a warning that the numbers given forimpacts cannot be summed up to a total, as some impacts are missing. AsOttinger (1991) points out, the danger is that policy makers will still ignore thewarnings and use the partial sums as if they were totals. Hopefully this is anunderestimation of the capacities of decision makers, as their task is precisely tomake decisions in areas where only part of the consequences are known atany given time and where most quantitative data are uncertain. If this were notthe case, there would be no need for decision makers, as the calculated totalimpact values would directly point to the best alternative. Unfortunately,the inappropriate summing of partial results is often made precisely by thoseconsultants that should have fairly prepared the data for the decision makers.I shall return to some of these issues in Chapter 3, where I discuss ways ofpresenting the results of life-cycle analyses.

2.2.2 Treatment of Risk-related Impacts and Accidents in LCA

Of the impacts listed above, some involve, as noted, an element of risk. Riskmay be defined as a possible impact occurring or causing damage only with afinite probability, less than 100% for each exposed individual (for example, therisk of being hit by a meteor or developing lung diseases as a result of airpollution). The insurance industry often uses a more narrow definition that alsorequires the event to be ‘‘sudden’’, i.e. excluding the damage caused by generalair pollution. In LCA, all types of impacts have to be considered, but the waydifferent impacts are treated may depend on whether they are ‘‘certain’’ or‘‘stochastic’’ of nature, and in the latter case whether they are insurance-typerisks or not.

40 Chapter 2

As regards the health impacts associated with dispersal of air pollutants fol-lowed by ingestion and application of dose–response functions describing pro-cesses in the human body (possibly leading to illness or death), one can usealready established probabilistic relationships, provided population densities anddistributions are such that the use of statistical data is appropriate. A similarapproach can be taken for the risk of accidents occurring fairly frequently, suchas motorcar accidents, but a different situation occurs for low-probability acci-dents with high levels of possible associated damage (e.g. nuclear accidents).

The treatment of high-damage, low-probability accident risks needs addi-tional considerations. The standard risk assessment used, for example, in theairplane industry consists in applying fault tree analysis or event tree analysis totrace accident probabilities forward from initiating events or backward fromfinal outcomes. The idea is that each step in the evaluation is a known failuretype associated with a concrete piece of equipment, and that the probability forfailure of such a component should be known from experience. The combinedprobability is thus the sum of products of partial event probabilities for eachstep along a series of identified pathways. It is important to realise that thepurpose of this evaluation is to improve design, by pointing out the areas whereimproved design is likely to pay off.

Clearly, unanticipated event chains cannot be included. In areas such asairplane safety, one is aware that the total accident probability consists of onepart made up by anticipated event trees, for which impact-reducing measureshave been implemented, and one made up by unanticipated events. Thepurpose of the design efforts is clearly to make those accidents that can bepredicted by the fault tree analysis (and thus may be said to constitute ‘‘built-in’’ weaknesses of design) small compared with the unanticipated accidents, forwhich no defence is possible, except to learn from actual experiences andhopefully move event chains including, for example, common mode failuresfrom the ‘‘unanticipated’’ category into the ‘‘anticipated’’, where engineeringdesign efforts may be addressed. This procedure has led to overall decliningairplane accident rates, while the ratio between unanticipated and anticipatedevents has stayed at approximately a value of ten.

It must further be emphasized that the term ‘‘probability’’ is often used in aloose manner, as there is no proof of a common, underlying statistical dis-tribution (Sørensen, 1979a), due to constant technological change, making theempirical data different from the outcome of a large number of identicalexperiments. This is equally true if we go to the cases of oil spills or nuclearaccidents, for which the empirical data are necessarily weak, owing to the lowfrequency of catastrophic events (albeit compounded with potentially largeconsequences). Here the term ‘‘probability’’ is really out of place and if usedshould be interpreted as meaning just ‘‘a frequency indicator’’.

2.3 Choosing the Context

When the purpose of the LCA is to proceed to generic energy technology andsystems evaluations (e.g. as inputs into planning and policy debates), one would


try to avoid using data depending too strongly on the specific site selected forthe installation. Still, available studies may depend strongly on location (e.g.special dispersal features, such as in a mountainous terrain) or a specificpopulation distribution (presence of particular high-density settlementsdownstream relative to emissions from the energy installation studied). Forpolicy uses, these special situations should if possible be replaced by suitableaverage inputs and should leave for a later detailed plant location phase toeliminate unsuited sites. This is not normally a problem, if the total planningarea is sufficiently diverse and generic or representative data do exist.

Pure emission data are often dependent only on the physical characteristicsof a given facility (power plant stack heights, quality of electrostatic filters,sulfate scrubbers, nitrogen oxide treatment facilities, etc.) and not on the site.However, the dispersion models are of course site dependent, but generalconcentration versus distance relations can usually be derived in model calcu-lations avoiding any special features of sites. As regards the dose commitment,it will necessarily depend on population distribution, while the dose–responserelationship should not depend on this. As a result, a generic assessment can inmany cases be performed with only a few adjustable parameters left in thecalculation, such as the population density distribution, which may be replacedwith average densities for an extended region.

The approach outlined above will only serve as a template for assessing newenergy systems where the technology can be specified and usually would involvea comparison between different new state-of-the-art solutions. If the impacts ofan existing energy system in a given nation or region have to be evaluated, theinventory of technologies actually in place should be included in the analysis,which would ideally have to proceed as a site- and technology-specific analysisfor each piece of equipment in the total installation.

In generic assessments, not only technology and population distributionsshould be taken as fixed, according to assumptions made, but also a number offeatures characterizing the surrounding society will have to be assumed, if theyinfluence the valuation of the calculated impacts. In some cases, social factorsmay even influence the physical part of the evaluation, say exposure estimates,e.g. through society’s preparedness for handling major accidents, which mayhave a bearing on both exposure and subsequent impact assessment.

2.3.1 Social Context

The social context in which a given energy system is placed may have profoundconsequences for a life-cycle assessment of the energy system. The social con-text influences both the nature and the magnitude of impacts to be considered.Key aspects of describing the social context of an energy system are the naturalsetting, the social setting and the human setting.

The natural setting has to do with geography and demography. Geographymay force people to settle in definite patterns, which again may influence theimpact of, for example, pollution of air, waterways and soils. In other words,these impacts will not be the same for the same type of energy equipment placed

42 Chapter 2

in different geographical settings. The patterns of releases and dispersal aredifferent and the chance of affecting the populations is also different, say foremissions reaching a city placed in a narrow valley compared with one situatedon an extended plain.

The social setting includes many features of a society: its stage of develop-ment, the scale and diversity of the society, its institutional infrastructure andtype of government. Many of the social factors are important determinants forthe selection of an energy system for a particular society, and they are equallyimportant for determining the way that operation of the system is conducted, aswell as the way in which society deals with various impacts. This may pertain tothe distribution of positive implications of the energy system, but it may alsorelate to the actions taken in the case of negative impacts (e.g. the way societydeals with a major accident in the energy sector, such as an oil spill).

The human setting involves the values and attitudes of individual membersof society. They are important for the decisions made by citizens, e.g. in relationto choices between different types of end-use technology, and of course also tothe opinion of people regarding the energy planning and energy future that theywould like their society to move towards. In democratic societies, the role ofattitudes is to influence the political debate, either by making certain techno-logical choices attractive to decision makers, or by protesting against choicesabout to be made by governments or political assemblies, and therebyexpressing the lack of public support for such decisions. Examples of bothkinds of political influence are numerous.

The processes are further complicated by feedback mechanisms, such as onesformed by media attention and interest groups attempting to influence attitudesin the general population, and lobby groups trying to coerce decision makers toforego public opinions in the decisions they make.

Data related to social setting should be used in the impact calculation.Health impacts of energy systems depend on the age and health distribution inthe particular society in question; social impacts depend on the social structure;and environmental impacts may depend on the settlement type, geography andclimate of the region in question.

Most countries have statistics pertaining to these kind of issues, but it is rareto see them fully used in connection with energy impact analyses. It is thereforelikely that an effort is required in order to gain acceptance for the need tojuxtapose all the relevant types of data, but in principle it can be done withlargely available tools.

More difficult is the question of incorporating values and attitudes of themembers of a given society in the assessment. Available studies are often madedifferently in different societies, and in any case it is unlikely that the impactsassociated with such traits of a society can be expressed in terms of numbers thatcan be compared to economic figures and other data characterising the energysystem.

In other words, one would have to accept that impacts must be described indifferent phrases or units and that not all of them can be numerically compared.This should not imply that some impacts a priori be given a smaller weight.


In fact, what the social evaluation is all about is to discuss in political terms thoseissues that do not lend themselves to a straightforward numerical evaluation andthus determine how much weight they should be given in the final decision.

The influence of media coverage, which in many societies plays an importantrole in shaping political perceptions and their feedback on values and attitudes,has been previously studied, e.g. by Stolwijk and Canny (1991), and that ofprotest movements and public hearings by Falk (1982), Gerlach (1987) andGale (1987) (cf. also the general introductory chapter in Shubik, 1991). The roleof institutions has been studied by Lau (1987), Hooker and van Hulst (1980)and by Wynne (1984).

2.4 Aggregation Issues

Because of the importance of aggregation issues, both for data definition andfor calculation of impacts, we shall discuss this topic in a little more detail.There are at least four dimensions of aggregation that play a role in impactassessments:

� Aggregation over technologies� Aggregation over sites� Aggregation over time� Aggregation over social settings

The most disaggregated studies done today are termed ‘‘bottom-up’’ studies.They deal with a specific technology located at a specific site. Since the impactswill continue over the lifetime of the installation, and possibly longer (radio-active contamination), there is certainly an aggregation over time involved instating the impacts in any compact form. The better studies attempt to displayimpacts as function of time, e.g. as short-, medium- and long-term effects.However, even this approach may not catch important concerns, as it willtypically aggregate over social settings, implicitly assuming them to be inert asfunction of time. This is of course never the case in reality, and in recent cen-turies the development with time of societies has been very rapid, entailing alsorapid changes in social perceptions of a given impact. For example, theimportance presently accorded to environmental damage was absent not somany decades ago, and there are bound to be issues over the next decades thatsociety will be concerned about, but which currently are just considered asmarginal by wide sections of society.

Aggregation over social settings also has a precise meaning at a giveninstance. For example, the impacts of a nuclear accident will greatly depend onthe response of the society. Will there be heroic firemen as in Chernobyl, whowill sacrifice their own lives in order to diminish the consequences of theaccident? Has the population been properly informed about what to do incase of an accident (going indoors, closing and opening windows at appropriatetimes, etc.). Have there been drills of evacuation procedures? For theChernobyl accident in 1986 the answer was no; in countries such as Sweden

44 Chapter 2

the answer today would largely be yes. A study making assumptions on acci-dent mitigation effects must be in accordance with the makeup of the society forwhich the analysis is being performed. Again the uncertainty in estimatingchanges in social context over time stands out in cases such as the nuclear onewhere delayed effects are important.

Aggregation over sites implies that peculiarities in topography (leadingperhaps to irregular dispersal of airborne pollutants) have not been treated inthe LCA calculations performed and that variations in population densityaround the energy installation studied will be disregarded in assessing damage.This may be a sensible approach in a planning phase, where the actual locationof the installation may not yet have been selected. It also gives more weight tothe technologies themselves, making this approach suitable for generic planningchoices between classes of technology (e.g. nuclear, fossil, renewable). Ofcourse, once actual installations are to be built, new site-specific analyses willhave to be invoked, e.g. in order to determine the best location.

As regards aggregation over technologies, this would in most cases not makesense. However, there will be exceptions, e.g. if an existing stock of, forexample, power plants in a region is to be assessed. In such cases, some level oftechnology aggregation may be relevant. For example, one might use averagetechnology for the impact analysis, rather than performing multiple calcula-tions for specific installations involving both the most advanced and the mostoutdated technology. In order to asses the total impact of an existing energysystem, one might aggregate over coal-fired power stations built at differenttimes, with differences in efficiency and cleaning technologies being averagedover. On the other hand, if the purpose is to make cost–benefit analyses ofvarious sulfur and nitrogen cleaning technologies, each plant would have to betreated separately.

In a strict sense, aggregation is clearly not allowed in any case, because theimpacts that play a role never depend linearly or in simple ways on assumptionsof technology, topography, population distribution, and so on. One should inprinciple treat all installations individually and make the desired sums on thebasis of the actual data. This may sound obvious, but in most cases it is alsounachievable, because available data are always incomplete and so is the char-acterization of social settings over the time periods needed for a completeassessment. As regards the preferences and concerns of future societies, or theimpacts of current releases in the future (such as climate impacts), one will alwayshave to do some indirect analysis, involving aggregation and assumptions onfuture societies (e.g. using the scenario method to be described in Chapter 4).

One may thus conclude that some aggregation is in practice always required,but that the level of aggregation must depend on the purpose of the assessment.In line with the general characterization given in Section 2.1.1, one may discernthe following specific purposes for conducting an LCA:

� Licensing of a particular installation� Energy system assessment� Assistance to energy planning and policy efforts


For licensing of a particular installation being part of an energy chain orconstituting the entire energy system, clearly a site- and technology-specificanalysis has to be performed, making use of actual data for physical pathwaysand populations at risk (as well as corresponding data for impacts on ecosystems,etc.). For the assessment of a particular energy system, the full chain from miningor extraction over refining, treatment plants and transportation to power plants,transmission and final use must be considered separately, as they would typicallyinvolve different locations. A complication in this respect is that for a fuel-basedsystem, for example, it is highly probable that over the lifetime of the installationthe fuel would be purchased from different vendors and the fuel would oftencome frommany geographical areas with widely different extraction methods andimpacts (e.g. Middle East versus North Sea oil or gas, German or Bolivian deepcoal mines, open-pit coal extraction in Australia, and so on). Future prices andenvironmental regulations will determine the change in fuel mix over the lifetimeof the installation, and any specific assumptions may soon turn out to be invalid.

For the planning type of assessment, it would in most industrialized nationsbe normal to consider only state-of-the-art technology, although even in someadvanced countries there is a reluctance to apply known and available envir-onmental cleaning options (currently for particle, SO2 and NOx emissions andin the future probably also for CO2 sequestering or other removal of green-house gases). In developing countries there is even more the tendency to ignoreavailable but costly environmental impact mitigation options. In some cases thelevel of sophistication selected for a given technology may depend on theintended site (e.g. near to or away from population centres). Another issue ismaintenance policies. The lifetime impacts of a given installation depend sen-sitively on the willingness to spend money on maintenance, and the level ofspending opted for is a matter to be considered in the planning decisions.

The following list enumerates some of the issues involved (Sørensen, 1993):

Technology and organisation

� Type and scale of technology� Age of technology� Maintenance state and policy� Matching technology with the level of skills available� Management and control setup

Natural setting

� Topography, vegetation, location of waterways, ground water tables, etc.� Climatic regime: temperature, solar radiation, wind conditions, water

currents (if applicable), cloud cover, precipitation patterns, air stability,atmospheric particle content

Social setting

� Scale and diversity of society� Development stage and goals� Types of government, institutions and infrastructure

46 Chapter 2

Human setting

� Values and attitudes, goals of individuals� Level of participation and of decentralisation of decision making

Impact assessments suitable for addressing these issues involve the con-struction of scenarios for future society that can serve as a reference frame fordiscussing social impacts. Because the scenario method has normative com-ponents, it would in most cases be best to consider more than one scenario,spanning important positions in the social debate of the societies involved.

Another issue is the emergence of new technologies that may play a role overthe planning period considered. Most scenarios of future societies do involvesome assumption regarding new technologies coming into place, assumptionsusually based on current research and development. However, the actualdevelopment is likely to involve new technologies not anticipated at the time ofmaking the assessment. It is possible to some extent to analyse scenarios forsensitivity to such new technologies, as well as to possible errors in other sce-nario assumptions. This makes it possible to distinguish between those futurescenarios that are resilient, i.e. do not become totally invalidated by changes inassumptions, as distinct from those that depend strongly on the assumptionsmade.

In the case of energy technologies, it is also important to consider theuncertainty of demand assumptions and in assumptions on primary energysupply technologies. The demand may vary according to social preferences, aswell as due to the emergence of new end-use technologies that may provide thesame or better services with less energy input. It is therefore essential thatthe entire energy chain is looked at, down to not just the energy delivered but tothe non-energy service derived with use of the delivered energy. No onedemands energy per se, but citizens in human societies demand transportation,air conditioning, computing, entertainment and so on.

The discussion of aggregation issues clearly points to the dilemma of impactanalyses: Those answers that would be most useful in the political context oftenare answers that can be given only with large uncertainty. This places the finalresponsibility in the hands of the political decision maker, who has to weigh theimpacts associated with different solutions, and in that process to take theuncertainties into account (e.g. choosing a more expensive solution because ithas less uncertainty). However, as already stated, this is of course preciselywhat decision making is about!

2.5 Chain Calculations

An important application of LCA is performing what in Section 2.1.1 wastermed a chain calculation. It consists in following the chain of conversionsteps leading to a given energy output, as illustrated in Figure 2.1, butconsidering input from and outputs to side chains, as exemplified in Figure2.2 for a particular step. The performance of such chain LCAs in the energy


sector is the equivalent of similar usage in conventional product LCAs andusually involves specific assumptions on the technology used in each stepalong the chain. The immediate LCA outcomes may for instance be emis-sions and waste from particular devices in the chain. However, before sucheffluent data can be translated into actual damage figures, one has to followtheir trajectories through the environment and their uptake by humanbeings, as well as the processes in the human body possibly leading tohealth damage. The method generally applied to this problem is called thepathway method.

The pathway method consists of calculating, for each step in the life cycle,the emissions and other impacts directly imposed during or caused by that life-cycle step, and then to trace the fate of the direct impacts through the naturaland human ecosystems, e.g. by applying a dispersion model to the emissions inorder to determine the concentration of pollutants in space and time. The finalstep is to determine the impacts on humans, on society or on the ecosystem,using for instance dose–response relationships between intake of harmfulsubstances and health effects that may already have been established elsewhere,or which can be calculated in connection with the LCA study at hand for theparticular substances emerging from the actual processes being studied. Thestructure of a pathway is indicated in Figure 2.7.

Consider the example of electricity produced by a coal-fired power station(Figure 2.8). The first step would be mining of the coal, which may emit dustand cause health problems for miners. Then follows cleaning, drying andtransportation of the coal, spending energy such as oil for transporting the coalby ship to a final usage destination (here the impacts from using oil have to beincorporated, e.g. taken from a separate oil chain study).

The next step is storage and combustion of the coal in the boiler of a powerstation, leading to partial releases of particulate matter, sulfur dioxide andnitrogen oxides through the stack. These emissions would then have to betraced by a dispersion model, calculating air concentrations in different

Figure 2.7 Illustration of pathway method (Sørensen, 1996).

48 Chapter 2

distances and directions away from the stack. Based upon these concentrations,inhalation amounts and the health effects caused by the substances identified inthe human body are obtained by using an existing or specifically establishedrelation between dose (exposure) and effect, if possible taken from some otherstudy or World Health Organisation databases. Pathways other than atmo-spheric dispersal may also have to be considered, for instance pollutantswashed out and deposited by rain and subsequently taken up by plants such asvegetables and cereals. They may later find their way to humans and causehealth problems.

For each life-cycle step the indirect impacts associated with the chain ofequipment used to produce any necessary installation, the equipment used toproduce the factories producing the primary equipment, and so on, have to beassessed, together with the stream of impacts occurring during operation of theequipment both for the life-cycle step itself and its predecessors (cf. Figure 2.2).

Figure 2.8 Coal-based electricity chain (Sørensen, 1993). Modern plants wouldreduce power plant emissions by the use of filters.


The same is true for the equipment used to handle the technology employed inthe life-cycle step after it has been decommissioned, in another chain of dis-carding, recycling and reusing the materials involved.

In the coal power example, the costs of respiratory diseases associated withparticulates inhaled may be established from hospitalisation and lost work-daystatistics, and the cancers induced by sulfur and nitrogen oxides may be simi-larly monetised, e.g. using insurance payments as a proxy for deaths caused bythese agents.

Generally, the initiating step in calculating chain impacts may be in the formof emissions (e.g. of chemical or radioactive substances) from the systeminstallations to the atmosphere, releases of similar substances to other envir-onmental reservoirs, visual impacts or noise. Other impacts would be frominputs to the fuel cycle step (water, energy, materials such as chalk for scrub-bers). As regards basic emission data, these are at present routinely beingcollected for many power plants, whereas the data for other conversion stepsare often more difficult to obtain. Emission data from road vehicles, forexample, may be available in some form, but not always distributed overdriving modes and location (at release) in the way one would need in mostassessment work.

Once having identified releases, the next step in calculating the dispersal inthe ecosphere may exploit available atmospheric or aquatic dispersion models.In the case of radioactivity, decay and transformation also have to be con-sidered. For airborne pollutants the concentration in the atmosphere is used tocalculate deposition (using dry deposition models, deposition by precipitationscavenging or after adsorption or absorption of the pollutants by water dro-plets). As a result, the distribution of pollutants (possibly transformed fromtheir original form, e.g. sulfur dioxide to sulfate aerosols) in the air and on theground, or in water bodies, will become established, normally expressed asfunction of time, because further physical processes may move the pollutants,e.g. down through the soil (eventually reaching ground water or aquifers) oragain into the atmosphere (e.g. as dust).

Given the concentration of dispersed pollutants as a function of place andtime, the next step along the pathway is to establish the impact on humansociety, such as human ingestion of the pollutant. Quite extended areas mayhave to be considered, both for fossil fuel power-plant normal releases and fornuclear plant accidents (typically covering a distance from the energy instal-lation of 1000 kilometres or more, cf. ETSU/IER, 1995). Along with thenegative impacts there is of course the positive impact derived from the energydelivered. In the end, these are the ones that will have to be weighed againsteach other. Finally, one may attempt to assist the comparison by translating thedose–response values (primarily given as the number of cancers, deaths,workdays lost, and so on) into monetary values. This translation of many unitsinto one should, as mentioned, only be done if the additional uncertaintyintroduced by monetising is not so large that the comparison is weakened(Figure 2.9). In any case, some impacts are likely to remain which cannotmeaningfully be expressed in monetary terms.

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The impacts pertaining to a given step in the chain of energy conversions ortransport may be divided into those characterising normal operation and thosearising in the case of accidents. In reality, the borderline between oftenoccurring problems during routine operation, mishaps of varying degrees ofseriousness and accidents of different size is fairly hazy and may be described interms of declining frequency for various magnitudes of problems. The path-ways of impact development are to a considerable extent similar for routine andaccidental situations, involving injuries and other local effects, e.g. connectedwith ingestion or inhalation of pollutants, and as regards public impacts therelease and dispersal of substances causing nuisance where they reach inhabitedareas, croplands or recreational areas. The analysis of these transfers involvesidentifying all the important pathways from the responsible component of theenergy system to the final recipient of the impact, such as a person developingillness or dying, possibly with delays of considerable lapses of time in cases suchas late cancers.

2.6 Matrix Calculations

A problem often encountered with LCA chain calculations is that output fromthe chain, e.g. such as an energy product, may appear as input into a precedingchain element or more likely into one of the side-chains. In such cases, thecalculation cannot be performed sequentially along the chain and instead thefull system has to be treated in one step, similar to what is done in the matrixcalculations of an economic input–output model.

Such a full systemic LCA calculation proceeds by the same steps as the chaincalculations, but for each compartment, without indirect impact contributions

Figure 2.9 Multivariate versus monetised presentation of LCA results.


from side-chains, and thus in many cases as a relative calculation because theabsolute magnitudes of the inputs are not known. A consistent determinationof the relevant levels of required input and output from each compartment isthen made in a matrix calculation. This is the analogy to economic input–output analyses.

Some compartments may serve other purposes not related to the systembeing studied and therefore only the appropriate fraction of their impactsshould be counted here. Other impacts from these compartments may beincluded in LCA evaluations of the other products or services they deliver to. Inthis way, the summed matrix calculation impacts will be properly scaled anddouble counting avoided.

There would be mixed situations where the impacts from a device in thesystem can be taken from a previous chain study and inserted as a component(without side-chains), provided that this collapsing of a part of the real matrixdoes not omit flows between the collapsed compartment and some other of thecompartments that are included. The collapsed component could represent amaterial input to the process studied, where this material is not used in any ofthe other processes within the system studied.

Particular issues arise in cases when LCA evaluations are made for systemsconsidered for future implementation. There may be possible substitutionsbetween human labour and machinery, linking the analysis to models ofemployment and reproductive activities. In order to find all the impacts, vitalparts of the economic transactions of society have to be studied. The totalenergy system comprises conversion equipment, transmission lines or trans-portation, as well as end-use devices converting energy to the desired services orproducts. The demand modelling involves consideration of the development ofand future preferences and values of society beyond the energy sector.

More factual is the precise relation between inputs and outputs of a givendevice, which may be highly non-linear but in most cases given by a deterministicrelationship. Exceptions are, for instance, combined heat-and-power plants,where the same fuel input may produce a range of different proportions betweenheat and electricity. This gives rise to an optimisation problem for the operatorof the plant (who will have to consider fluctuating demands along with differentdispatch options involving different costs). A strategy for operation is in this caserequired, before the system LCA evaluation can proceed. However, once theactual mode of operation is identified, the determination of inputs and outputs isof course unique. The impact assessment then has to trace where the inputs camefrom, and keep track of where the outputs are going, in order to determine whichdevices need to be included in the analysis. For each device, total impacts have tobe determined, and the cases where successive transfers may lead back to deviceselsewhere in the system can again be dealt with by setting up a matrix of alltransfers between devices belonging to the energy system.

Once this is done, the subsequent impact assessment involves summation ofimpacts over all devices in the system, as well as integration over time andspace, or just a determination of the distribution of impacts over type, time andspace. This can be a substantial effort, as it has to be done for each device in the

52 Chapter 2

system, or at least for each category of devices (an example of strong aggre-gation is shown in Figure 2.3).

Like in the chain analysis, once emissions have been determined, theatmospheric dispersion should be determined from a meteorological model,typically using emissions from point sources or area sources as input (for eachdevice in the system) and then calculating air concentration and land or seadeposition as a function of place and time. An early example is the RAINSmodel used to calculate SO2 dispersal on the basis of long-term averagemeteorological data, aggregated with the help of a large number of trajectorycalculations (Alcamo et al., 1990; Hordijk, 1991; Amann and Dhoondia, 1994).

Ingestion rates and other uptake routes are then used in a traditional way tocalculate human intake of pollutants identified by the dispersion model throughbreathing air, skin, etc., followed by a model calculation of subsequent dis-position in the human body, with emphasis of accumulating organs and rates ofexcretion. The resulting exposure for each substance and its relevant depositoryorgans is finally via a dose–response function used to calculate the morbidity andmortality arising from the human uptake of pollution. It is customary to use alinear dose–response function extending down to (0,0) in cases where measure-ments only give information on the effects for high doses. The alternative ofassuming a threshold, below which there is no effect, is often used in regulatoryschemes, usually as a result of industry pressure rather than scientific evidence.

System-wide calculations are sometimes restricted to comprising only thosecomponents that are directly related to energy conversion. Sometimes such arestriction cannot be made, e.g. for transportation vehicles that give rise totraffic and thus links to all the problems of the entire transportation infra-structure. A general approach would be to treat all components of the energysystem proper according to the system approach, but to treat links into thelarger societal institutions and transactions as in the chain LCA. In this way theoverwhelming prospect of a detailed modelling all of society is avoided and yetthe double-counting problem is minimized because energy loops do not occur(although loops of other materials may exist in the chains extending outside theenergy sector).

2.6.1 Marginal versus Systemic Change

Many energy LCA projects make the assumption that the energy installationsconsidered are marginal additions to an existing system. For instance, oneparticular coal-fired power plant is added to a system otherwise unchanged.This implies that in calculating indirect impact the whole fabric of society andits industrial capacity is the already existing one. Such an approach would notbe valid in a systemic study of scenarios for future systems. A scenario for thefuture energy system will be imbedded into a society that may be very differentfrom the present, both as regards energy demands and flows, industry structureand social goals and habits. In studying the future impacts from manufactur-ing, e.g. photovoltaic panels, the process energy input will not come from thepresent mix of mainly fossil power plants but will have to reflect the future


energy system mix, with perhaps wind, photovoltaic or fusion power as theavailable inputs.

Evidently, a systemic approach taking into account the future structureof society will give results very different from those emerging from treatingthe same future energy system as the result of a series of marginal changesfrom the present. The determination of an optimum system configurationshould thus take into account all LCA impacts at the time when they occur,and not substitute impacts caused by the present background system. If,for example, the energy inputs to a future renewable energy installation arehigher than that of a competing fossil installation, then a marginal evaluationbased on current fossil power supply may deem the system less favourablethan one based on the true future scenario of non-fossil energy supply forenergy inputs.

One workable alternative to the marginal assumption, in case different formsof energy supply have to be compared to each other without being part of anoverall scenario, is to artificially consider each system as autonomous, i.e. forthe photovoltaic power plant to assume that the energy for manufacture comesfrom similar photovoltaic plants. This makes the impact evaluation for dif-ferent contemplated system alternatives self-contained, and the assumption isgenerally fair and perhaps even realistic, e.g. if the power for site-specific workmostly comes from nearby installations rather than from the national averagesystem. Because many renewable energy systems like wind turbines and solarplants are of smaller unit size than coal or nuclear power plants, the gradualestablishment of a sizeable capacity could indeed be seen as involving energyuse based on the already installed plants of the same kind. This situation maynot always apply, e.g. for energy inputs in forms different from the one asso-ciated with the installation studied.

2.7 Inventory Building

The large number of processes that can appear as part of a life-cycle analysismakes it inviting to build up a database of the processes most often used. Infact, several entries should be expected for each process because of the differenttechnologies that may apply in different circumstances, depending on thelocation of the installation studied and on the time period in which it will befunctioning (existing, to be built now or entering some future energy system).Many commercial LCA programs contain such databases, suggesting that theybe used as background material in cases where a dedicated study of the pre-cursor, side or downstream chains of the system studied is not available and theinvestigator does not want to go into such detail as performing the studiesher- or himself (at least not for processes other than those most central to thestudy). The danger is, of course, that the user may fall back on such back-ground inventories even in cases where they are inappropriate, e.g. by per-taining to a technology level different from the one relevant for the actual study(cf. the wind energy example given in Chapter 1).

54 Chapter 2

The structure of the inventory databases may be illustrated by the processexample given in Tables 2.2–2.11, for steam produced in Slovenia from naturalgas, by the chain shown schematically in Figure 2.10.

Table 2.2 Annual average emission data (in kg TJ�1 fuel input) for variouspower plants entering into the Slovenian power generation mix, asused in the steam from the natural gas example (EC/JRC, 2010).

Energy-specificpower plant

Naturalgas Biogas

Heavyfuel oil

Hardcoal

Browncoal Biomass

CO2 55 989 127 577 79 657 94 559 101 134 101 777CO 20 276.1 20 32.5 33.1 958.1SO2 0.4 11 486.9 669.4 2450 15.3NOx 130 460.2 190 270 230 184.8

Table 2.3 Material resources from air, sediment and water used as input todirect or indirect processes associated with a Slovenian plantproducing steam by use of natural gas, normalised to 1 MJ of steam(EC/JRC, 2010).

Resource Value (kg) Resource Value (kg)

Air 4.61E-01 Kaolin 5.14E-11Carbon dioxide from air 2.03E-06 Magnesite 4.93E-11Nitrogen from air 2.04E-12 Dolomite 3.89E-11

Colemanite 3.84E-11Inert rock 3.38E-03 Potassium chloride 2.55E-11Natural aggregate 1.37E-04 Talc 2.11E-11Baryte 1.31E-04 Phosphorus 2.11E-11Calcium carbonate 1.18E-04 Raw pumice 4.99E-12Bentonite 5.44E-05 Sulfur 1.29E-12Soil 3.28E-05 Sodium sulfate 7.93E-14Iron 2.92E-05 Platinum 1.38E-15Quartz sand 2.10E-05 Molybdenum 4.82E-16Clay 1.75E-05 Palladium 1.15E-16Gypsum 2.49E-06 Calcium chloride 5.22E-17Magnesium chloride 2.02E-06 Rhodium 3.83E-18Lead 1.15E-06 Barium sulfate 5.10E-19Zinc 2.23E-07 Slate 4.60E-20Manganese 1.88E-07 Olivine 2.74E-20Bauxite 8.86E-08 Tin 4.42E-23Copper 6.02E-08Titanium 5.18E-08 Surface water 2.22E-03Basalt 3.36E-08 Water 9.08E-05Nickel 2.35E-08 Groundwater 3.14E-05Sodium chloride 1.30E-08 Seawater –3.76E-05Chromium 1.35E-10 River water –1.77E-03Fluorspar 8.76E-11


The inventory is divided into inputs and outputs, but aims to include allindirect life-cycle branches ‘‘from cradle-to-grave’’. The data descriptionstates that Slovenian-specific fuel supply and Slovenian-specific energycarrier properties underlie the data in Table 2.2. Furthermore, specificSlovenian technology standards of heat plants regarding efficiency, firingtechnology, flue-gas desulfurisation, NOx removal and de-dusting are con-sidered. The data set considers the whole supply chain from explorationover extraction and preparation to transport of fuels to the heat plant. Thedata set further includes the infrastructure as well as end-of-life fate of theplant. The background system is addressed as follows. All relevant andknown transportation processes used are included. Overseas transportationincludes rail and truck transport to and from major ports for internationaltrading. Further, relevant transportation of gas or oil by pipeline or tankeris included. The energy carriers used in the side-chains include coal, crudeoil, natural gas and uranium and they are modelled according to the actualimport situation. For example, refinery products such as diesel, gasoline,technical gases, fuel oils, basic oils and residues such as bitumen are mod-elled via a country-specific, parameterised model. The refinery modelrepresents the current technology standard in each country, as regards

Table 2.4 Energy resources from air, biosphere, sediment and water used asinput to direct or indirect processes associated with a Slovenianplant producing steam by use of natural gas, normalised to 1 MJ ofsteam (EC/JRC, 2010).

Energy resource InputValue(MJ)

Renewable energy from air primary energy from solar energy 1.97E-05Renewable energy from air primary energy from wind power 1.14E-05Renewable energy from biosphere wood; 14.7 MJ kg–1 9.45E-07Non-renewable energy from sediment natural gas; 44.1 MJ kg–1 1.26E+00Non-renewable energy from sediment crude oil; 42.3 MJ kg–1 6.53E-03Non-renewable energy from sediment uranium 8.13E-04Non-renewable energy from sediment hard coal; 26.3 MJ kg–1 7.93E-04Non-renewable energy from sediment brown coal; 11.9 MJ kg–1 6.63E-04Non-renewable energy from sediment peat; 8.4 MJ kg–1 5.94E-07Renewable energy from sediment primary energy from geothermics 2.15E-07Renewable energy from water primary energy from hydro power 1.75E-04

Table 2.5 Energy amounts constituting output from direct or indirect pro-cesses associated with a Slovenian plant producing steam by use ofnatural gas, normalised to 1 MJ of steam (EC/JRC, 2010).

Output Value (MJ)

Process steam from natural gas; plant output 1.00Eþ00Waste heat to air 1.41E-01Waste heat to waterways 1.78E-04

56 Chapter 2

Table 2.6 Materials constituting output emissions to air from direct orindirect processes associated with a Slovenian plant producingsteam by use of natural gas, normalised to 1 MJ of steam(EC/JRC, 2010).

Material Value (kg) Material Value (kg)

Used air 3.71E-01 Polycyclic aromatichydrocarbons

1.32E-10

Carbon dioxide 7.01E-02 Zinc 1.09E-10Water vapour 4.96E-02 Phenanthrene 8.58E-11Methane 3.16E-04 Helium 7.55E-11Nitrogen dioxide 1.65E-04 Nickel 6.81E-11Sulfur dioxide 4.78E-05 Ethanol 5.78E-11Carbon monoxide 3.74E-05 Methanol 5.10E-11Ethane 1.29E-05 Propene 4.92E-11Nitrogen 1.18E-05 Selenium 3.66E-11Propane 9.40E-06 Copper 3.59E-11n-Butane 4.30E-06 Fluorene 2.69E-11Pentane 2.72E-06 Iron 2.09E-11Non-methane volatileorganic compounds

2.23E-06 Chromium 1.84E-11

Oxygen 1.51E-06Acrolein 1.84E-11

Particles (PM2.5) 7.54E-07Tin 1.44E-11

Formaldehyde 6.66E-07Benzo[a]pyrene 1.17E-11

Particles (PM2.5–PM10) 2.89E-07CFC-114 1.05E-11

Nitrous oxide 2.75E-07CFC-11 1.02E-11

Benzene 2.56E-07Arsenic 1.01E-11

Hydrogen sulfide 2.22E-07Sulfate 9.08E-12

Particles (PM10) 1.07E-07Fluoranthene 8.47E-12

Acetic acid 9.52E-08Mercury 8.29E-12

Barium 8.28E-08Cyanide 6.11E-12

Hydrogen 5.35E-08Acid (as H+) 5.87E-12

Volatile organic compounds 2.61E-08Cobalt 5.36E-12

Hydrogen chloride 2.40E-08Chrysene 3.21E-12

Acetaldehyde 5.19E-09Hydrocyanic acid 2.80E-12

Acetone 4.00E-09Anthracene 2.60E-12

Xylene (all isomers) 3.59E-09HCFC-22 2.40E-12

Toluene 1.85E-09Benzo[k]fluoranthene 2.34E-12

Ammonia 1.29E-09Cadmium 2.27E-12

Ethylbenzene 1.28E-09CFC-12 2.20E-12

Ethylene 1.26E-09Chromium(III) 1.94E-12

Hydrogen fluoride 1.23E-09Thallium 1.92E-12

Boron 5.82E-10Antimony 1.76E-12

Hexane 4.83E-10CFC-13 1.38E-12

Lead 4.79E-10Polychlorinated biphenyls 1.33E-12

Vanadium 4.27E-10Benzo[a]anthracene 1.31E-12

Vinyl chloride 3.84E-10Molybdenum 1.25E-12

Heptane 3.24E-10Benzo[ghi]perylene 1.17E-12

Chloride 3.00E-10Indeno[1,2,3-cd]pyrene 8.69E-13

Naphthalene 2.73E-10FC-14 8.13E-13

Fluoride 1.86E-10Beryllium 7.84E-13

Octane 1.78E-10Dibenzo[a,h]anthracene 7.28E-13

Bromine 1.62E-10Hydrogen arsenide 6.05E-13

Manganese 1.61E-10Nitrogen monoxide 4.88E-13Phenol 4.97E-16


emissions and process efficiency, and takes into account the different mix ofoutputs in different countries (EC/JRC, 2010).

The main data source cited is the OECD/IEA 2004 energy statistics series,and the quality of the data in the database is described as ‘‘good’’ by theconsultants providing the dataset (PE-International and GaBi, both inGermany) and performing the data validation and check of compliance withthe ISO norms (done by the same two consultants plus a third, Ecobilan inFrance). The inventory of inputs is divided into materials (given by mass) andenergy flows (given in energy units, all for a 1 MJ steam output; Tables 2.3and 2.4), and the inventory of outputs is divided into materials, energy and

Table 2.6 (Continued )


Tellurium 2.58E-13Titanium 2.45E-13

Phosphine 3.17E-16

Hydrogen bromide 1.59E-13Styrene 1.74E-16

Cyclohexane 1.57E-13Hydrogen iodide 1.73E-16

Strontium 7.69E-142,3,7,8-Tetra-chlorodibenzo-p-dioxin

1.60E-16

Fluorine 6.59E-14 Lead dioxide 7.57E-17Propionic acid 2.15E-14 1,3,5-Trimethylbenzene 6.41E-17Chlorine 1.12E-14 Hexamethylenediamine 4.02E-17Arsenic trioxide 7.29E-15 Zinc oxide 1.32E-17Carbon disulfide 6.87E-15 Tin oxide 6.58E-18Sulfur hexafluoride 5.18E-15 Diethylamine 5.64E-20Ammonium 3.21E-15 Dichloromethane 2.02E-20Particles (4PM10) 2.43E-15 Silver 7.25E-21Scandium 2.06E-15 Palladium 1.44E-21Butadiene 6.84E-16 Rhodium 1.39E-21

Table 2.7 Materials constituting output emissions to non-agricultural soilfrom direct or indirect processes associated with a Slovenian plantproducing steam by use of natural gas, normalised to 1 MJ ofsteam (EC/JRC, 2010).


Ammonia 3.49E-06 Bromide 1.04E-09Strontium 2.20E-06 Zinc 7.55E-10Phosphate 1.99E-06 Cobalt 1.21E-10Chloride 1.21E-06 Decane 1.02E-10Potassium 8.79E-07 Calcium 1.00E-10Sulfide 6.63E-07 Copper 6.97E-11Sulfate 1.11E-07 Magnesium 2.50E-11Fluoride 3.46E-08 Cadmium 2.45E-11Iron 9.94E-09 Sodium 6.87E-12Aluminium 7.65E-09 Arsenic 2.71E-12Chromium 6.79E-09 Lead 1.83E-12Nickel 1.96E-09 Mercury 1.38E-13Manganese 1.42E-09 Chromium(III) 1.82E-14

58 Chapter 2

Table 2.8 Materials constituting output emissions to fresh water bodies fromdirect or indirect processes associated with a Slovenian plant pro-ducing steam by use of natural gas, normalised to 1 MJ of steam(EC/JRC, 2010).


Particles (4PM10) 1.33E-04 Hydroxide 5.37E-11Chloride 1.04E-05 Mercury 5.04E-11Sodium 3.45E-06 Polycyclic aromatic

hydrocarbons3.62E-11

Chemical oxygen demand 1.81E-06Boron 3.15E-11Sulfate 3.88E-07Molybdenum 2.97E-11Total organic carbon 3.40E-07Hydrocarbons(unspecified)

2.91E-11Biological oxygen demand 1.67E-07

Hydrogen fluoride 1.57E-11Ammonia 1.56E-07

Bromine 1.25E-11Iron 1.13E-07

Vanadium 1.15E-11Phosphate 9.61E-08

Sulfite 9.43E-12Carbonate 5.86E-08

Naphthalene 9.04E-12Adsorbable organichalogen compounds

3.86E-08

Cobalt 7.30E-12Chromium 2.74E-08Titanium 7.28E-12Strontium 1.71E-08Anthracene 7.10E-12Sulfide 1.47E-08Selenium 6.59E-12Fluoride 1.45E-08Acenaphthene 3.24E-12Copper 9.27E-09Chromium(III) 3.01E-12Calcium 8.73E-09R-40 2.68E-12Decane 7.89E-09Fluoranthene 2.28E-12Potassium 5.34E-09Hydrogen chloride 1.95E-12Nickel 2.56E-09Cyanide 1.83E-12Lead 2.34E-09Acenaphthylene 8.17E-13Nitrogen 1.98E-09Thallium 2.55E-13Chlorine 1.92E-09Sulfur 1.15E-13Zinc 1.87E-09Silver 1.06E-13Volatile organic

compounds1.67E-09

Chrysene 7.75E-14Aluminium 1.02E-09 Benzo[a]anthracene 6.74E-14Benzene 1.00E-09 Particles (PM10) 3.89E-14Nitrate 9.75E-10 Beryllium 3.72E-14Barium 9.33E-10 Tin 5.08E-15Cadmium 5.48E-10 Cresol 2.99E-15Toluene 5.26E-10 Acrylonitrile 2.36E-15Phenol 3.93E-10 Benzo[k]fluoranthene 1.13E-15Xylene (all isomers) 3.34E-10 Hexane 3.31E-16Acid (as H+) 3.00E-10 Magnesium 1.00E-16Arsenic 2.78E-10 1,2-Dibromoethane 3.70E-17Manganese 2.31E-10 Antimony 1.25E-17Methanol 1.56E-10 Chromium(VI) 1.07E-18Fluorine 8.02E-11 1,2-Dichloropropane 3.23E-20Acetic acid 7.30E-11 2,3,7,8-Tetrachlorodibenzo-

p-dioxin4.84E-26

Ethylbenzene 5.59E-11


radioactivity, the latter deriving from nuclear electricity used in the energy mixfor some of the chain or side-chain processes considered, and possibly frommining activities. The energy output flows (including the primary steam pro-duction) are given in Table 2.5, the material emissions to various recipients inTables 2.6–2.9, and the radioactive substances in mass units and in radio-activity units in Tables 2.10 and 2.11. In each category, effluents are listed in anorder of declining magnitude (of the amounts as expressed in the different unitsof mass, energy or radioactivity).

Among the largest life-cycle emissions, according to Table 2.6, one findscarbon dioxide and methane. The methane emission is of course natural gasescaping during extraction from onshore or offshore gas-fields or duringhandling and pipeline transport along the process chain, or unburned gasemissions, say from the steam plant itself. Comparing Table 2.6 and Table 2.4,one sees that the life-cycle natural gas emissions to the atmosphere constitute1.13% of the natural gas input to the Slovakian steam plant. This is an inter-esting figure, considering the debate that has taken place over the magnitude of

Table 2.9 Materials constituting output emissions to seawater bodies fromdirect or indirect processes associated with a Slovenian plant pro-ducing steam by use of natural gas, normalised to 1 MJ of steam(EC/JRC, 2010).


Chloride 6.78E-06 Vanadium 2.37E-11Carbonate 8.59E-08 Calcium 1.81E-11Particles (4PM10) 5.41E-08 Magnesium 1.62E-11Sulfate 3.62E-08 Strontium 1.41E-11Sulfide 1.56E-08 Lead 7.76E-12Chemical oxygen demand 7.28E-09 Acetic acid 4.46E-12Decane 2.59E-09 Beryllium 1.98E-12Barium 1.37E-09 Chrysene 1.81E-12Sodium 1.36E-09 Acenaphthene 1.42E-12Zinc 6.92E-10 Volatile organic compounds 6.80E-13Phenol 6.02E-10 Acenaphthylene 5.42E-13Iron 4.25E-10 Fluoranthene 3.73E-13Benzene 2.74E-10 Anthracene 3.67E-13Xylene (all isomers) 1.86E-10 Benzo[k]fluoranthene 3.55E-13Toluene 1.50E-10 Benzo[a]anthracene 3.20E-13Nitrate 1.11E-10 Ammonia 3.05E-13Biological oxygen demand 6.80E-11 Mercury 2.59E-13Total organic carbon 6.80E-11 Boron 1.66E-13Cadmium 5.89E-11 Sulfur 8.88E-14Naphthalene 4.67E-11 Aluminium 1.03E-14Manganese 4.45E-11 Tin 3.13E-15Copper 3.90E-11 Silver 2.61E-15Chromium 3.88E-11 Cresol 2.30E-15Cobalt 3.46E-11 Molybdenum 8.81E-16Ethyl Benzene 3.35E-11 Titanium 3.19E-16Nickel 2.78E-11 Hexane 2.51E-16Arsenic 2.44E-11

60 Chapter 2

natural gas losses from the extended European–Asian natural gas pipelinenetwork. Early Russian estimates based on leak rates measured at a selectedfew of the pressure upgrading stations, required at regular distances along apipeline, showed a high loss, reaching as much as 5% of the gas flowingthrough the line. Follow-up measurements at two compressor stations inSiberia, compared to production data and gas arriving at the German buyerRuhrgas AG, were made based upon data from the Russian gas companyGazprom (summary by Dedikov et al., 1999). This study arrived at a loss ofabout 1% of the gas. In the USA, government agency measurements of leaksfrom the gas network there found an average leak rate of between 1% and 2%(US EPA, 1996; Kirschgessner et al., 1997). The German gas company (nowE.ON Ruhrgas AG) commissioned a further study from the German Wup-pertal Institute for Climate, Environment and Energy (known for its socialscience work on energy policy) and the Max-Planck-Institute for Chemistry,based on five compressor stations selected by Gazprom, along the pipelines forexportation from Russia to Germany (Lechtenbohmer et al., 2005, 2007). Theestimated total average leak rate here was 0.7% (95% model confidenceinterval 0.5–1.5%). Measurements were made only during one week andoccasional mishaps and special circumstances found in the earlier studies toinfluence the long-term totals strongly were presumably not included. Becausemost of the loss is found to take place at the compressor stations, it is also

Table 2.10 Waste materials from mining, construction and operational activ-ities of direct or indirect processes associated with a Slovenian plantproducing steam by use of natural gas, normalised to 1 MJ of steam(EC/JRC, 2010).

Waste material Value (kg)

Adsorbable organic halogen compounds 6.17E-17Demolition waste (unspecified) 1.30E-04Mining wastes: overburden (unspecified) 2.85E-03Mining wastes: spoil (unspecified) 9.40E-05Mining wastes: slag (unspecified) 1.43E-09Radioactive tailings; reactor fuel assembly supply; production mix,at plant

2.09E-07

Uranium depleted; reactor fuel assembly supply; production mix,at plant

8.16E-10

Slag (uranium conversion); reactor fuel assembly supply; productionmix, at plant

7.89E-10

Unspecified radioactive waste; reactor fuel assembly supply;production mix, at plant

7.07E-10

Medium and low radioactive wastes; reactor fuel assembly supply;production mix, at plant

4.22E-10

Highly radioactive waste; reactor fuel assembly supply; productionmix, at plant

3.55E-10

Calcium fluoride; reactor fuel assembly supply; production mix,at plant; low radioactive

1.19E-10

Plutonium as residual product; reactor fuel assembly reprocessing;production mix, at plant

7.07E-13


possible or likely that the control of leakage at these facilities has beenimproved between the previous and this study.

The cause for concern over methane emissions to the atmosphere is ofcourse that it is a greenhouse gas, estimated by the Intergovernmental ClimatePanel (Forster et al., 2007) to produce on average 21 times more absorption ofsolar radiation than CO2. This places a particular focus on the natural gashandling companies and even more on cattle farmers all over the world,

Table 2.11 Radioactive emissions to air and waterways (see column 1) fromdirect or indirect processes associated with a Slovenian plantproducing steam by use of natural gas, normalised to 1 MJ ofsteam (EC/JRC, 2010).

Air or water IsotopeValue(kBq) Air or water Isotope

Value(kBq)

Air krypton-85 6.40E-02 Air uranium-235 1.56E-08Fresh water hydrogen-3 2.52E-03 Fresh water plutonium 6.89E-09Air radon-222 9.28E-04 Air uranium-234 4.04E-09Fresh water radium-226 2.81E-05 Air iodine-129 3.70E-09Air xenon-133 8.51E-06 Fresh water curium 2.26E-09Air hydrogen-3 7.34E-06 Fresh water ruthenium-106 1.70E-09Air argon-41 3.77E-06 Fresh water americium-241 1.70E-09Air xenon-135 2.81E-06 Air cesium-137 9.67E-10Air carbon-14 1.73E-06 Air xenon-137 7.37E-10Fresh water cesium-137 8.01E-07 Fresh water cobalt-58 6.63E-10Fresh water uranium-238 4.98E-07 Air iodine-131 5.55E-10Fresh water cobalt-60 3.71E-07 Air cesium-134 4.73E-10Fresh water iodine-129 2.48E-07 Air cobalt-60 7.52E-11Air xenon-138 9.51E-08 Fresh water antimony-124 1.78E-11Fresh water cesium-134 9.21E-08 Fresh water iodine-131 1.27E-11Fresh water carbon-14 8.67E-08 Fresh water antimony-125 1.21E-11Fresh water strontium-90 8.47E-08 Air cobalt-58 2.97E-12Fresh water manganese-54 5.76E-08 Fresh water silver-110 2.60E-12Air xenon-131 5.20E-08 Air plutonium 1.75E-12Air uranium-238 2.22E-08 Air antimony-124 5.98E-13

Figure 2.10 Example of Slovenian natural gas-fired steam plant, based on severalimport sources for the gas, followed by national transportation of the gasmixture to the steam plant (EC/JRC, 2010; general permission given).

62 Chapter 2

because of the large quantities of methane released to air during digestion byruminants.

Turning to the carbon dioxide emissions, Table 2.2 contains data for thepower sources entering into the electricity supply mix for the steam plantupstream and downstream LCA chains, and for side chains, excluding nuclearenergy. Both conventional fossil power plants and biomass plain combustion orbiogas combustion are seen to be associated with large CO2 emissions. Thehighest value relative to the energy in the feedstock is for biogas, reflecting thatbiogas is roughly 50%methane and 50%CO2, but only the first half contributesto the energy count. The fact that carbon dioxide assimilated during the growthof the biomass involved in the two biomass columns is not included means thatthe analysis using the inventory based on Table 2.2 will have to explicitly includethe assimilation process happening maybe one year before combustion of thebioenergy (manure from grazing livestock) or maybe 100 years earlier (forestresidues). In other studies, biomass is sometimes considered ‘‘CO2 neutral’’,which may be correct if the time between assimilation and release is short, but isnot necessarily correct when the time development in atmospheric CO2 releasesand accumulation is aimed for. Because the data in the Ispra Joint ResearchCentre of the European Commission database are recommended for use asgeneric background LCA data, lumping together emissions at different times(and different locations), it is surprising that the aggregation is not extendedback to include the CO2 assimilation. It would be quite easy for a user to forgetthe balancing CO2 contribution for biomass, because all other flows in thedatabase are being presented as aggregated over the entire relevant period oftime between resource extraction and end-of-life disposal. In any case, theadequate treatment of time distributions of assimilation and release of green-house gases from plant material is a central issue in evaluating the role of bio-mass in future energy systems (e.g. see discussion in Sørensen, 2010).

The use of inventories based upon concrete, existing installations becomesincreasingly invalid the larger the distance in time, technology and naturalsetting of the object of investigation is from the one forming the basis for theinventory. The most operational inventories would offer a range of technicalsolutions covering known and emerging technologies, and would allow the userto select a succession of background scenarios for the indirect impacts that spanthe range of options considered relevant for installations throughout theoperational life of the object studied. Because energy facilities often have a longlifetime, changes in the background system may cause impacts to vary quitesubstantially (say during the transition from fossil-based to renewable energysupply). To take this into account, inventories need to consist of fairly small‘‘building blocks’’ and to avoid aggregating impacts based on a particularhistorical system surrounding the facility studied.

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Wynne, B., 1984. The institutional context of science, models, and policy.Policy Sci. 17, 277–320.


CHAPTER 3

From Life-Cycle Analysis toLife-Cycle Assessment

The life-cycle analysis constitutes the technical calculations of the pathwaysfrom initial events (such as emissions or noise creation) to impacts on humansociety, the natural environment and other systems that may be affected.Often, such analysis has created a large amount of impact data, and a sub-sequent assessment trying to draw conclusions of how all the impacts affectthe world is needed. If existing facilities or systems are analysed, the assess-ment may be aimed at making corrections that will reduce the negativeimpacts, and if a new system is contemplated, the assessment should enabledecision makers to make their choices of future systems based on as full alevel of information as possible. This points to a need for someone (notnecessarily the same as the one making the life-cycle analysis in the firstplace) to prepare the assessment components in a way that, on the one hand,facilitates the job of the decision maker by presenting different impacts in aclear way, but, on the other hand, does not distort the information or bias ittowards particular choices. Some issues are already touched upon duringthe analysis work: how much aggregation is permissible in time, over geo-graphical locations or over technologies. The following sections will gofurther into a range of problems that have been raised in connection withprevious use of life-cycle techniques.

3.1 Communicating with Decision Makers

Using LCA to facilitate decision making on various levels, some thoughtshould be given to the way in which the results of an analysis are presentedto the target group. For example, this brings about the issue of monetisingimpacts, because it is believed that decision makers understand monetary


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impacts better than physical ones, and that qualitative impact descriptionshave little power to sway policy. From a scientific point of view, thedividing line goes between qualitative and quantitative impact statements.That the quantifiable impacts cannot all be expressed in the same unit isintuitively clear: numbers of cancer deaths, loss of agricultural crops, acidrain damage to Greek temples and traffic noise are fundamentally expressedin ‘‘different units’’. The translation into common units, whether monetaryor other ‘‘indicators’’, is tantamount to losing part of the message. Thisis the reason that the discussion in connection with Figure 2.9 concludedthat monetising should be used only if it does not significantly increaseuncertainty, meaning that the decision makers should not be exposed to themonetising simplification unless it preserves their possibility for making afair assessment.

The use of aggregation as part of preparing a case for assessment is certainlynot always a bad thing, if the confusion of hundreds of impacts (such as thosein Tables 2.4–2.11) can be avoided by presenting reasonable summations forfurther assessment, but aggregating all impacts into a single indicator, withsums over time, place and any other sign of diversity, will make assessmentpointless. The consultant’s efforts to construct such a single number are equallymisguided, whether the number is a monetary figure or an indicator. However,if the impacts can be divided into a modest number of categories, the situationis different and indicators may acquire a legitimate role as an alternative tocurrencies, because it is possible to use separate indicators for each of theimpact categories that are difficult to quantify or monetise. For instance, energysupply security may not be directly quantifiable but could be attributed anindicator value between zero and one that could meaningfully influence thedecision-maker’s choice. However, energy supply security could not be forcedto use common units with, say, the amount of local labour required or with thetoll of lung diseases caused by a measure of pollutant emissions. Adding upindicators for such disparate categories would be counterproductive, but pre-senting each of a modest number of separate indicators covering well-definedcategories can be very helpful in the assessment process. These ideas are furtherdeveloped below in Section 3.3.

In communication between life-cycle analysts and decision makers, all theusual issues of communication techniques, style, honesty and abuse are ofcourse in play. The current political use of spin doctors as intermediariesmakes it even more difficult to get objective input across to the target groupsupposed on behalf of their constituency to make the decisions that embracemajority political positions through the weighting of different impact typesand categories. It may be even more difficult to persuade the decision makersto reveal their selection of weight to public scrutiny. Many decisionmakers prefer to hide behind professionals, pretending that the choices theymake have a scientific foundation. This is where the practitioners of life-cycleanalysis readying the analysis for assessment have a serious responsibility tomake it crystal clear where the objectivity stops and the value-based choices ofweight factors begin.

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3.2 Monetising Issues

The desire to use well-known common units for as many impacts as possible ina life-cycle analysis is of course aimed at facilitating the subsequent job of adecision maker in comparing different solutions. However, it is important thatthis procedure does not further marginalize those impacts that cannot bequantified, or which seem to resist the monetising efforts. The basic question isreally whether or not the further uncertainty introduced by monetising offsetsthe benefit of being able to use common units.

I have already replaced the phrase ‘‘translation into common units’’ by‘‘monetising’’. This is done after a careful reflection of the meaning ofcommon units and assessment of some currently proposed common unitssuch as the ‘‘eco-points’’. I have not found any difference or advantage intranslating the effects of radiation exposure, the inhalation of air pollutants,the loss of biodiversity or other impacts into the currency of eco-pointsrather than into euros or dollars. Clearly, the translations of impacts notoriginally in monetary form into any common unit will entail a valuationeffort by the human being doing the assessment, or at best by groups insociety trying to agree on the most suitable translation. The common unitcould as well be taken as ‘‘number of sick days imposed’’. This would makeimpacts of this form exact but may make translation of other impacts moredifficult. Because we already use monetary values as a common expression ofseveral types of value, this would seem easier to accept than a new unknowncurrency. I have noted two possible reasons behind the proposed pointsystems. One is the debate over the statistical value of life and its negativeconnotations when monetary units are employed. The other is that replacinga well-known assessment unit of dollars or euros by a new currency, wherethe translation of different types of impact into points is done by consultantsand hidden deeply within the software documentation, may make somedecision makers fail to question the reasons for the choices and just use thepoints as if they were handed down by a higher authority. Of course,translating the same types of impact into monetary values involves essen-tially the same human agent considerations as translating into points, butthe process appears more transparent precisely because the user has muchmore familiarity with money than with eco-points. In any case, the relativerating of impacts of different types can show large variations and this is akey feature to scrutinize when comparing different approaches to life-cycleanalysis and assessment.

There is more than one way of arriving at a common unit such as a mone-tised value for a given impact. One may express damage, say from air pollution,in monetary terms, but another approach would be to estimate the cost ofreducing the emissions to some threshold value considered safe (this would beavoidance cost as opposed to damage cost). Estimating damage costs involvesdetermining the relation between exposure or other initiating event from thelife-cycle analysis and the various impacts subsequently caused: health impactsby counting hospitalisation and workday salaries lost, the replanting cost of

69From Life-Cycle Analysis to Life-Cycle Assessment

dead forests, the cost of restoration for historic buildings damaged by acid rain,and so on. Accidental human death may for instance be replaced by the lifeinsurance cost. Which method to use for such translations is the expected resultof analytical work combined with value-based input (ideally from the realdecision makers rather than from the scientists and consultants that shape thecalculation framework) that has to be performed in order to arrive at the finaloutcome of a life-cycle assessment.

Unavailability of data pertinent to monetising has led to alternative philo-sophies, such as interviewing cross sections of the affected population on theamount of money they would be willing to pay to avoid a specific impact, or tomonitor their actual investments (these are called contingency evaluations andinclude hedonic pricing, revealed preferences or willingness to pay*). Suchmeasures may change from day to day, depending on exposure to random bitsof information (whether true or false), and they also depend strongly on theincome at the respondent’s disposal, as well as on competing expenses ofperhaps more tangible nature. Neither interview studies nor contingencyevaluations can be made for impacts on nature as seen from an ecosphere pointof view. Only the valuation of nature by human beings is amenable to the use ofsuch techniques.

Very serious questions arise in discussing evaluation techniques such asthe ones discussed above: should the monetised value of losing a human life (the‘‘statistical value of life’’, SVL, discussed below) be reduced to reflect that onlya fraction of people actually take out life insurance, and should it be allowed totake different values in societies of different affluence?

All of the monetising methods mentioned are clearly deficient: the damagecost by not including a (political) weighing of different issues (e.g. weighingimmediate impacts against impacts occurring in the future), the contingencyevaluation by doing so on a wrong basis (influenced by people’s arbitraryknowledge of the issues, by their accessible assets determining willingness topay, etc.). The best alternative may be to avoid common units or monetisingentirely, which would amount to using a multivariate analysis, as discussedbelow in Section 3.3 by presenting an entire impact profile to decision makers,in the original units and with a time-sequence indicating when each impact isbelieved to occur, and then to invite a true political debate on the properweighing of the different issues. However, the use of monetary values to discussalternative policies is so common in current societies that it may seem a pity notto use this established framework wherever possible. It is also a fact that manyimpacts can indeed meaningfully be described in monetary terms, so thechallenge is to make sure that the remaining ones are treated adequately and donot ‘‘drop out’’ of the decision process.

The translation of impacts from physical terms (number of health effects,amount of building damage, number of people affected by noise, etc.) tomonetary terms (US$/PJ, DKK/kWh, etc.) is an investigation of costs. It is

*Definitions of concepts are collected in the Glossary of words and concepts placed near the end ofthe book.

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therefore important to agree whether one talks about cost to individual citizensor of cost to society. For example, the use of an affected population’swillingness to pay (WTP) for avoiding the impacts (e.g. as done by ETSU/Metronomica, 1995) means that the study is not estimating the cost to society,but rather the sum of costs inflicted on individual citizens. The concept ofWTP, introduced by Starr (1969), has a number of inherent problems, some ofwhich are:

� Interview studies may lead people to quote higher amounts than theywould pay in an actual case.

� The resulting WTPs will depend on disposable income.� The resulting WTPs will depend on the level of people’s knowledge of the

mechanism by which the impacts in question work.

The outcome of an actual development ensuing from policy action based onthe WTP principle may be inconsistent with agreed social goals of equity andfairness, as it may lead to polluting installations being built in the sociallypoorest areas.

The accidental deaths associated with energy provision turns out in manylife-cycle studies of individual energy supply chains to be the most significantimpact, fairly independent of details in the monetising procedure selected.Therefore, a discussion on the choice of the monetised value of an additionaldeath caused by the energy system will be dealt with in a little more detailbelow. Generally, working with a monetised damage reflecting the full LCAcost of energy to society, rather than the cost to selected individual citizens,would seem the most appropriate methodology, because society is more thanthe sum of its inhabitants at any particular point in time. Societies are supposedto have a longer lifetime than a human life and thus have to considerintergeneration questions of inheriting assets and structural organisation, butalso of inheriting wastes and environmental degradation, handling such issuesin a way that ensures equitable considerations for all generations of societymembers (cf. Pan and Kao, 2009). They also have to consider relations to othersocieties, including questions of peaceful coexistence, equity and the exchangeof goods and ideas.

3.2.1 Statistical Value of Life

One of the highest values for the loss of a human life used systematically incalculating externalities is the value of 2.6 million ECU or eurow (about 3.1million US$), used by the ExternE Group (ETSU/IER, 1995) in its European

wThe European Commission’s ExternE study originally presented its results in terms of theEuropean Currency Unit (ECU), which in 1995 when the study was completed equalled 1.2 US$.The exchange rate has since moved, mostly upwards. The ECU was a weighted average ofEuropean currencies and thus supposedly more stable than a national currency. It has since beenreplaced by a new ‘‘federal’’ European currency, the euro, used by a group of European Unionmember states, but not all. The examples given in this book generally assume 1 h¼ 1.3 US$.


study of externalities of selected energy chains. This value is based on a surveyof three types of data:

� Willingness to accept a higher risk of death, as revealed by salary increasesin risky jobs as compared with similar jobs with small risk.

� Contingency valuation studies, i.e. interviews aimed at getting statementsof WTP associated with risks of death.

� Actual expenditures paid to reduce risk of loss of life (e.g. purchase ofautomobile airbags, anti-smoking medication, etc.).

Compensations paid by European governments to families of civil servantsdying in connection with their job were also considered by the ExternE group.The scatter in data reviewed ranged from 0.3 to 16 million h per death. For useoutside Western Europe, the ExternE project group proposed to use purchaseparity translation of the SVL used in the European case studies (i.e. samepurchasing power).

A feeling for the statistical value of life (SVL) can be obtained by consideringthe salary lost by accidental death. Assuming that the death on average occurs inthemiddle of the working life and calculating the total salary thatwould have beenearned during the remaining time to retirement, e.g. in Denmark one would get alittle over 20 years multiplied by the average salary for the high seniority part of awork career, amounting to at least 400 000 DKK per year, or more than 8 millionDKK (some 1.35 million US$ or 1.05 million h). If this was paid to an individual,it should be corrected for interest earned by giving the present value of all theannual payments, amounting to about 70 000 h per year over 20 years. However,as a cost to society, it may be argued that no discounting should take place,because society does not set money aside for future salary or other payments.

Two other arguments might be considered. One is that in times of unem-ployment the social value of a person fit to work may be less than the potentialsalary. Accepting this kind of argument implies that the outcome of technologychoices in a society would depend on the ability of that society to distribute theavailable amount of work fairly (the total amount of salaries involved is notfixed, because salaries are influenced by various factors including the level ofunemployment).

The other argument is that the members of a society have a value to thatsociety above their ability to work. If this were not the case, a society would notprovide health services that prolong people’s lives beyond retirement age. Ajudgement on the merits of these arguments would lead us to conclude that theSVL as seen by society would most likely be above the million h average salaryloss, but it does not tell how much more. One could say that the ExternE valueof 2.6 million h represents a fairly generous estimate of non-tangible values tosociety of its members, and that a lower value might be easier to defend.However, as stated above, the ExternE estimate has an entirely different basis,representing an individual SVL rather than one seen from the point of view ofsociety. The conclusion may rather be that it is reassuring that two so differentapproaches do not lead to values more different.

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One further consideration is that not all deaths associated with, say, acountry’s use of energy take place in the same country. If coal used in Europe isimported from Bolivia, coal-mining deaths would occur there, and the questionarises if a different (smaller?) value of life should be used in such a case,reflecting the lower average salary earnings in Bolivia (and perhaps a smallerconcern by society). This would easily be stamped as a colonial view, which iswhy the study of the European Commission opted to use the same SVL nomatter where in the World the death occurs (in practise, this may be achievedby assuming that, for example, all coal comes from mines in Germany orPoland or the UK, even though in reality Europe imports coal from manydifferent parts of the world).

The global equity problem is one reason that the concept of SVL has beenattacked. Another is the ethical problem of putting a monetary value on a humanlife. The reply to the latter may be that SVL is just a poorly chosen name selectedto describe the attempt to give the political decision-process a clear signalregarding the importance of including the consideration of accidental death indecisions on energy system choice and location. This debate over the use of SVLcaused a debate in the journal Nature, in connection with the greenhousewarming issue (Grubb, 1996), using arguments similar to those given above.

If the discussion so far should be summarised, it may be to express the beliefthat if the 2.6 million h SVL is on the high side, it is probably so by at most afactor of two.

3.2.2 Depreciation

Since impacts from energy devices occur throughout the lifetime of the equip-ment and possibly after decommissioning, one point to discuss is whetherexpenses occurring in the future should be discounted. If a positive discount rateis used, it will effectively make any impact acceptable only if it occurs sufficientlyfar into the future. Until recently, many studies have used discount rates ofabout 10% annually, which effectively makes all long-term impacts unim-portant. The 10% value used would reflect discount rates encountered in 1990personal bank transactions. In social contexts it should be corrected for inflation,because inflation affects all the monetary values considered, including those ofmonetised impacts. The real interest rate, i.e. market interest rate corrected forinflation and averaged over the past century, has been just over 3% p.a., and is atpresent in most places even lower. It increased strongly during the oil crisisperiod of 1974–1984, but has since approached the long-term average or passedbelow it. The role of the discount rate is to provide a tool that allows individualsto allot their finite resources to competing investments with different timedistribution, and for this reason a different discussion is required for the sociallong-term interest rate to be used in connection with life-cycle analysis.

Short-term discounting does not take into account the role played byproblems of intergenerational equity, an issue that becomes relevant for manyimpacts from energy systems due to delays between cause and effect, particu-larly but not exclusively in the case of nuclear energy. Using a positive discount


rate in life-cycle studies expresses the preference for suffering a given damagelater rather than sooner. While this preference is evident for individuals with afinite lifespan, looking at total societies then items like the value of a human lifeshould remain at least the same with time. For a national economy the questionarises if assets left to future generations might not become exploited in a betterway than present technology allows. The same may be true for liabilities, suchas nuclear waste, which might be stored for later processing, whereas for airpollution the impacts are of course already committed at the time of ingestion.Most people would prefer a cancer occurring 20 years into the future to onenow, but the question becomes more subtle if continuous suffering is involved.

The intergenerational interest rate used in studies attempting to reflect theviews of a whole society rather than those of a single individual should basicallybe zero, placing the same value on the future as on the present. However, somewould argue that we build up a stock of amenities for the future, which togetherwith the technological progress enabling cheaper handling of deferred problemswould permit use of a positive discount rate for society. On the other hand,knowledge regarding health and environmental impacts are likely to grow withtime, e.g. making environmental standards become more stringent in the future(continuing their development over the past several decades). Also new con-cerns are likely to emerge, which are not known today, all of which points to anegative discount rate. Because there is no way of telling precisely what thefuture societies will be concerned about, and much less possibility of translatingthe concerns into precise discount rates, the most reasonable choice for anintergenerational discount rate may well be zero.

3.3 Multivariate Presentation

If those impacts that can be quantified are kept in different units, the questionarises of how they can be presented to the decision maker in a form facilitatingtheir use. The common answer is to use a multivariate approach, of which anexample is indicated in the left side of Figure 2.9, mentioning each category ofimpact and presenting it in its own units (right-hand side). Figure 3.1 expandson one methodology for multivariate presentation (cf. the list given in Section1.1 and Sørensen, 1993a), suggesting the use of what may be called an impactprofile. The idea of the profile is that each particular type of impact is evaluatedin the same way for different systems. Therefore, the magnitudes indicatedby the profile may be compared across technologies and they are no moresubjective than the monetised values, although they cannot be summed acrossimpact categories. Clearly those impacts that can be meaningfully monetisedshould be so, but the impact profile actually gives much more informationbecause it tells the decision maker if two energy solutions have the same type(i.e. the same profile) of impacts, or if the profiles are different and thus makes itnecessary for the decision maker to assign subjective or politically basedweights to different kinds of impacts (e.g. comparing greenhouse warmingimpacts of fossil systems with noise impacts of wind turbines). The assignment

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of weights to different impact categories is the central political input into thedecision process.

The impact profile approach further makes it a little easier to handlequalitative impacts that may only allow a description in words, because suchimpacts can often be characterized vaguely as ‘‘small’’, ‘‘medium’’ or ‘‘large’’, aclassification that can be rendered in the profiles and compared for differentenergy systems. Hence the advantage of the profile method is that the decisionmaker sees both the bars representing monetised values and at the same timeadjacent bars describing the outcome of qualitative assessments. Thus thechance of overlooking important impacts is diminished.

In any case, the multivariate profile approach does give the decision makermore information than a single monetary value. A further point that may playa role in decision making is the possible presence of value systems thatmake certain impacts ‘‘unconditionally acceptable’’ or ‘‘unconditionallyunacceptable’’. Such absolute constraints can be accommodated in theassignment of weights (zero or infinite) as indicated in Figure 3.1. Figure 3.2

Figure 3.1 Layout of multivariate impact assessment scheme (with use of Sørensen,1982, 1993a).


shows an example of a profile of the impacts from two energy installations,including both positive and negative impacts (derived from Sørensen, 1994).

Tabular presentations of both monetised and qualitative life-cycle impactswill be illustrated in several examples in Part II of this book, both for individualinstallations (e.g. using chain calculations) and for entire systems (e.g. basedupon present and future scenarios).

It is common in life-cycle studies to present summary tables includingstatements of uncertainty, of whether the impacts are local, regional or global,and whether they are short-term or long-term. In addition, there may bewarnings against summing up to arrive at totals, in case there are impacts notquantified and omission is considered to significantly affect the totals. Someimpacts that often fall in this category are local impacts of global greenhousewarming, the effects of large nuclear accidents, and of proliferation and nuclearwaste that will affect future societies in ways difficult to foresee.

It is evident that although the derivation of each single impact figure mayhave required a large effort, the results could still involve substantial uncer-tainty. The analyses to be presented in Part II will also show that the largestuncertainties are often associated with the most important impacts, such as thementioned nuclear accidents or greenhouse warming. Clearly there is a generalneed to improve data at all levels, by collecting information pertinent to each

Figure 3.2 LCA impact profiles for coal and wind power chains (Sørensen, 1994).

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type of analysis required. This need is probably best met by doing site- andtechnology-specific studies. As regards indirect inputs, national input–outputdata are often based upon statistical aggregation choices failing to align withthe needs of characterising transactions relevant for the energy sector. Inaddition, there are often gaps in data availability. One conclusion from theseobservations is that there is a need to be able to present qualitative andquantitative impacts to a decision maker in such a way that the magnitude andimportance of each item become clear, despite uncertainties and possiblydifferent units used. The multivariate presentation tools invite the decisionmaker to employ multi-criteria assessment.

The difficulties encountered in presenting the results of externality studiesand life-cycle analyses in a form suited for the political decision-making processmay be partly offset by the advantages of bringing into the debate the manyimpacts often disregarded (which is of course the core definition of ‘‘external-ities’’, meaning issues not included in the market prices). It may be fair to saythat use of life-cycle analysis and the imbedded risk assessments will hardly everbecome routine methods of computerised assessment, but that it may still servea very useful purpose by focusing and sharpening the debate involved in anydecision-making process and hopefully loop back to help increase the quality ofthe basic information upon which a final decision is taken, whether on startingto manufacture a given new product, use a new energy technology or to arrangea sector of society (such as the energy sector) in a novel way.

There is further the question of public participation in decision making,which in democratic societies is taking place not only through elected repre-sentatives, but also in media, meetings and manifestations involving largersegments of the public. Life-cycle analysis should not forget to present itself in a

Figure 3.3 The actor triangle: a model of democratic planning, decision making andcontinued assessment (Sørensen, 1993b).


way that allows actors with different backgrounds and different insights tomake use of the results as input in any public debates contributing to demo-cratic decision making.

Figure 3.3 is meant to remind us of the broader landscape of actors in thedebates on life-cycle impact valuation and use for policy making, and also thatdecision making is a continuous process, involving planning, implementationand assessment in a cyclic fashion, with the assessment of actual experiencesleading to adjustments of plans, or in some cases to entirely new planning.

References

ETSU/Metronomica (1995). ExternE: Externalities of Energy. Vol. 2: Metho-dology. European Commission DGXII: Science, Research & Development,Report EUR 16521 EN, Luxembourg.

ETSU/IER (1995). ExternE. Externalities of Energy. Vol. 3: Coal and lignite.Vol. 4: Oil and gas. Prepared by ETSU, Harwell, UK and IER, University ofStuttgart, Germany. EUR 16522/3 EN, part of a series of five volumes, seeEuropean Commission (1995).


Grubb, M. (1996). Purpose and function of IPCC, Nature 379, 108; response tonews items in Nature 378, 322 (1995) and Nature 378, 119 (1995).

Pan, T.-C., Kao, J.-J. (2009). Inter-generational equity index for assessingenvironmental sustainability: An example on global warming. Ecol. Indic.9, 725–731.

Sørensen, B. (1982). Comparative risk assessment of total energy systems. InHealth Impacts of Different Sources of Energy, pp. 455–471. IAEA Publ.SM-254/105, Vienna.

Sørensen, B. (1993a). What is life-cycle analysis? In Life-Cycle Analysis ofEnergy Systems, pp. 21–53. Workshop Proceedings, OECD Publications,Paris.

Sørensen, B. (1993b). Technology change: the actor triangle. Philos. Soc. Action19, 7–12.

Sørensen, B. (1994). Life-cycle analysis of renewable energy systems. Renew.Energy 5, part II, 1270–1277.

Starr, C. (1969). Social benefit versus technological risk. Science 165,1232–1238.

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CHAPTER 4

Energy System Definition

The energy system of a country or a region has a number of components,with more components for a decentralised system than for a centralised one.The end-use components are usually decentralised and operated by a numberof users from the private or public sector. It is therefore customary to reservethe words ‘‘centralised’’ and ‘‘decentralised’’ to describe the nature of theenergy supply part of the system. During the mid-20th century, most coun-tries experienced a move towards a higher degree of centralisation, withsmall municipal power or district heating systems being replaced by units ofover 500 MW size, clustered at particular sites and serving several commu-nities. Towards the end of the 20th century the trend reversed in many coun-tries, first with a large number of combined heat and power stations beingbuilt in smaller cities and later with wind power and solar panels servingindividual farms or urban houses. The early 21st century has seen the windturbines grow to several megawatt size and being placed in groups, and solarenergy being utilized by large panel arrays delivering district heat and powerserving many customers. Still, the solar technologies are continuing to caterto building-integrated solutions, and because of the cost of land, centralisedsolar solutions may not become economically competitive except for place-ment on marginal land such as deserts (Sørensen, 2010a).

The installations making up an energy system must cover the entire chainstructure from energy extraction (fuels) or recovery (renewable sources) overtransmission, conversion, possibly energy storage, and distribution to the facil-ities employed by the users of energy, as illustrated for a single chain in Figure2.1. However, the energy system in its entirety is not chain-like but more in theshape of a matrix of components that may have more than one energy input andmore than one energy output (such as the heat and electricity of a co-generatingpower plant). A simplified version of such a system is shown in Figure 4.1 for aconventional fuel-based system (of the type existing in most countries) and inFigure 4.2 for a possible future system based on fossil fuels but avoiding CO2

emissions by technologies such as the use of hydrogen as an energy carrier.


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Other types of energy systems proposed are based on nuclear or renewableenergy penetrations much higher than today. These systems are often alsoconsidered to require hydrogen as a new energy carrier in order to reachcomplete independence of fossil fuels. In reality, there are other solutions, usinghydropower and biofuels, which can handle the intermittent nature of some

Figure 4.1 Overview of a conventional fuel-based energy system, based upon theglobal energy system in 1990 (Sørensen, 1996).

Figure 4.2 Overview of a future energy system based upon fossil fuels with the use of‘‘clean’’ conversion technologies, based on one out of four global energyscenarios constructed for 2030 (Sørensen, 1996).

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renewable sources, and the stationary nature of current nuclear technologies(Sørensen, 2005, 2010a). Figures 4.3 and 4.4 illustrate basic global scenarios forsuch systems.

Figure 4.3 Overview of a future energy system based upon nuclear fuels and aimed tohave higher safety than present variants (Sørensen, 1996).

Figure 4.4 Overview of a future energy system based upon renewable energy withemphasis on centralised photovoltaic installations (Sørensen, 1996).

81Energy System Definition

The global nuclear scenario assumes advanced accelerator-breeder technol-ogies to be developed during the 50-year time horizon considered and used inconjunction with a thorium fuel-cycle. The global renewable energy scenario inFigure 4.4 assumes a large part of the energy to come from photovoltaicinstallations placed on marginal land, assuming these to become viable withinthe next 50 years, along with the long-distance transmission networks required.More details of energy scenario construction and various strategies fordetermining the best mix of energy sources are discussed in Section 4.2 andChapter 8.

4.1 Energy Demand and Supply

4.1.1 Basic and Derived Energy Demands

Energy demand futures are sometimes discussed in terms of changes relative tocurrent patterns. This is of course a suitable basis for assessing marginalchanges, while for changes over a time horizon of 50 years it is un likely tocapture the important issues. Another approach is offered by looking at humanneeds, desires and goals and building up first the material demands required forsatisfying these, then the energy required under certain technology assump-tions. This is called a bottom-up approach. It is based on the view that certainhuman needs are basic needs, i.e. non-negotiable, while others are secondaryneeds that depend on cultural factors and stages of development and knowl-edge and could turn out differently for different societies, subgroups or indi-viduals within a society. The basic needs include those of adequate food,shelter, security and human relations, and there is a continuous transition tomore negotiable needs that incorporate material possessions, art, culture andhuman interactions and leisure. Energy demand is associated with satisfyingseveral of these needs, including manufacturing and constructing the equip-ment and products required for fulfilling the needs and for procuring thematerials required along the chain of activities and products.

In normative models with emphasis on environmental sustainability, thenatural approach to energy demand is to translate needs and goal satisfactioninto energy requirements by methods of conversion consistent with environ-mental sustainability. For market-driven scenarios, basic needs and humangoals may play an equally important role, but secondary goals are more likelyto be influenced by commercial interest rather than by personal motives. It isinteresting that the basic needs approach is usually taken in discussions of thedevelopment of societies with low economic activity, but rarely in discussions ofhighly industrialized countries.

The methodology used here is first to identify needs and demands, commonlydenoted human goals, and then to discuss the energy required to satisfy them ina chain of steps backwards from the goal-satisfying activity or product to anyrequired manufacture, and then further back to materials. This should be doneon a per capita basis (involving averaging over differences within a population),but separate for different geographical and social settings, as required for the

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construction of local, regional and global scenarios such as those considered inChapters 6 and 8.

The primary energy demand analysis assumes a 100% goal satisfaction, fromwhich energy demands in societies that have not reached this can later bedetermined. The underlying assumption is that it is meaningful to specify theenergy expenditure at the end-use level without caring about the rest of the systemresponsible for delivering the energy. This is only approximately true. In realitythere may be couplings between the supply system and the final energy use, andthe end-use energy demand therefore in some cases becomes dependent on theoverall system choice. For example, a society rich in resources may take uponitself to produce large quantities of resource-intensive products for export, while asociety with less resources may instead focus on knowledge-based production,both doing this in the interest of balancing imports and exports in an economyproviding satisfaction of the goals of their populations, but possibly with quitedifferent implications for energy demand. The end-use energy demands will bedistributed on energy qualities, which may be categorized as follows:

1. Cooling and refrigeration 0–50 1C below ambient temperature2. Space heating and hot water 0–50 1C above ambient3. Process heat below 100 1C4. Process heat in the range 100–500 1C5. Process heat above 500 1C6. Stationary mechanical energy7. Electrical energy (no simple substitution possible)8. Energy for transportation (mobile mechanical energy)9. Food energy

The goal categories used to describe the basic and derived needs have beenchosen as follows:

A: Biologically acceptable surroundingsB: Food and waterC: SecurityD: HealthE: Relations and leisureF: Activities

f1: Agriculturef2: Constructionf3: Manufacturing industryf4: Raw materials and energy industryf5: Trade, service and distributionf6: Educationf7: Commuting

Here, categories A–E refer to direct goal satisfaction, f1–f4 to primaryderived requirements for fulfilling the needs and finally f5–f7 to indirect


requirements for carrying out the various manipulations stipulated. The esti-mated energy requirements for satisfying needs identified by present societiesare summarized in Figure 4.5, where individual entries are estimated asdescribed in the following. The central assumption is that the average tech-nology available some 30–60 years into the future will have an energy efficiencyequal to that of the best technology in each category available today.

4.1.1.1 Biologically Acceptable Surroundings

Suitable breathing air and shelter against wind and cold temperatures, or hotones, may require energy services, indirectly to manufacture clothes andstructures and directly to provide active supply or removal of heat. Insulationby clothing makes it possible to stay in cold surroundings with a modestincrease in food intake (the heat from which serves to heat the layer between thebody and the clothing). The main heating and cooling demands occur inextended spaces (buildings and sheltered walkways, etc.) intended for humanoccupation without the inconvenience of heavy clothing that would impede, forexample, manual activities.

Figure 4.5 Estimate of global end-use energy demand based upon bottom-up analysisof needs and goal satisfaction in different parts of the world, using bestcurrently available technologies (Sørensen et al., 1994; Sørensen, 1994;unit of average energy flows is W cap.�1). The table probably under-estimates the speed of the transition to an ‘‘information society’’, byoverestimating process heat and underestimating dedicated electricitydemands in the year 2030.

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Rather arbitrarily, it is assumed that a fulfilment of the goals related toshelter on average requires a space of 40 m2 times a height of 2.3 m to be at thedisposal of each individual in society, and that this space should be maintainedat a temperature of 18–22 1C, independent of outside temperatures and otherrelevant conditions. As a ‘‘practical’’ standard of housing technology we shallfurther use a rate of heat loss P from this space of the approximate formP¼C�DT, where DT is the temperature difference between the desired indoortemperature and the outside one (e.g. see Sørensen, 1979, 2010a). The constantC consists of a contribution from heat losses through the external surfaces ofthe space, plus a contribution from exchanging indoor air with outside air at aminimum rate of about once every two hours. Half of the surfaces of the‘‘person space’’ are considered as external, the other half being assumed to faceanother heated or cooled space. Best current technology solutions would sug-gest that the heat loss and ventilation values of C¼ 14 (heat loss)þ 17 (airexchange)¼ 31 W per 1C can be attained. The precise value of course dependson building design and particularly on window area. The air exchange part canbe brought down by use of heat exchangers, but there is often no room for thesein existing buildings, so for the present situation the full 31 W per 1C seemsappropriate, whereas for a future situation where most of the existing buildingswould have been replaced, a considerably lower value should apply.

Now the energy requirements for heating and cooling, averaged over theyear, can be calculated with the use of climate tables giving the ambient tem-perature, e.g. hour by hour, for a typical year. If there are periods when thetemperature does not exceed the 18 1C limit for indoor comfort, the heatingload can be determined from the average temperature difference alone.

A few examples. For Irkutsk in Siberia, the annual average temperature of–3 1C gives an average energy requirement for heating of 651 W (per capita, asthe space allocated to one person was considered). For Darwin in Australia, noheating is needed. These two values are taken as approximate extremes forhuman habitats in the summary table. A very few people worldwide live inharsher climates, such as that of Verkhoyansk (also in Siberia, average tem-perature –17 1C, heating need 1085 W per cap.). Other examples are P¼ 225 Wper cap. (New York City), P¼ 298W per cap. (Copenhagen) and PE0 for HongKong. Cooling needs are zero for Irkutsk and Copenhagen, while for Darwin,with an annual average temperature of 29 1C, there is a cooling energyrequirement of –P¼ 209W per cap., assuming that temperatures above 22 1C areunacceptable. The range of cooling energy demands is assumed to be roughlygiven by these extremes, implying that –P¼ 0 to 200 W per cap. For New YorkCity the annual average cooling requirement is 10 W per cap. (typicallyconcentrated within a few months) and for Hong Kong it is 78 W per cap.

4.1.1.2 Food and Water

Energy-wise, the food intake corresponding to full satisfaction of food needs isabout 120 W per capita (Sørensen, 1979, 2010a). To store the food adequately,the use of short- and long-term refrigeration is assumed to take place.


The weight of the average per capita food intake is of the order of 2� 10–5 kg s–1,of which 0.8� 10–5 kg s–1 is assumed to have spent five days in a refrigerator at atemperature DT¼ 15 1C below the surrounding room temperature, and 0.4� 10–5

kg s–1 is assumed to have spent two months in a freezer at DT¼ 40 1C belowroom temperature. The heat loss rate through the insulated walls of the refrig-erator or freezer is taken as 2 � 10–2 W per 1C per kg of stored food. The energyrequirement then becomes

PE0:8� 10�5� 5� 24� 3600� 2� 10�2 � 15¼ 1:04W per cap: refrigeratorð Þ

PE0:4� l0�5 � 2� 720� 3600� 2� 10�2� 40¼ 16:6W per cap: freezerð Þ

plus the energy needed to bring the food down to the storage temperatures,PE 0.72þ2.12¼2.84W per cap. (assuming a heat capacity of 6000 J kg–1 per 1Cabove 0 1C and half that value below the freezing point, and a phase changeenergy of 350 kJ kg–1). The energy is assumed to be delivered at the storagetemperatures. Some energy could he regained when melting frozen food.

Cooking the food requires further energy: assume that 40% of the food intakeis boiled at DT¼ 70 1C above room temperature and that 20% of the food intakeis fried at DT¼ 200 1C above room temperature. The energy needed to bring thefood up to the cooking temperatures is PE 3.36þ 4.80¼ 8.16W per cap., and theenergy required for keeping the food cooking is PE 1.45þ 2.08¼ 3.53 W percap., assuming daily cooking times of 30 minutes for boiling and 15 minutes forfrying (some food cultures use more), and heat losses from the pot/pan/ovenaveraging 1 W per 1C for the quantities of food cooked per person per day.

Provision of water involves pumping and cleaning or purification. Thepumping energy needs are important but negligible on a per capita basis andthe treatment energy needs are also small. Both are assumed included in theindustry sector estimates considered below.

4.1.1.3 Security

Heating and cooling of buildings used by courts, police, military and othersecurity-related institutions are included as part of the 40 m2 floor area accordedeach person. The remaining energy use for personal and national security wouldbe for transportation and energy depreciation of materials and would hardlyamount to more than 1 W per cap., except for very belligerent nations.

4.1.1.4 Health

Hot water for personal hygiene is taken as 50 litres per day per capita atT¼ 40 1C above the waterworks¼ supply temperature, implying a rate ofenergy use averaging roughly P¼ 97 W per cap. Some of this could be recycled.Clothes washing and drying may amount to treatment of about 1 kg of clothesper day per capita. Washing requirements are assumed to be 5 kg water per kgclothes, at T¼ 60 1C (in practice, often more water at different temperatures,

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some of which are closer to inlet temperature), or an average energy of P¼ 15W per cap. For drying it is assumed that 1 kg of water has to be evaporated(heat of evaporation about 2.3� 106 J kg–1) per day per capita, at an effectivetemperature elevation of 80 1C (the actual temperature is usually lower, butmechanical energy is then used to enhance evaporation by blowing air throughrotating clothes containers). Local air humidity plays a considerable role indetermining the precise figure. Condensing driers recover part of the eva-poration heat, typically around 50%. The energy use for the case considered isthen 17 W per cap.

Hospitals and other buildings in the health sector use energy for spaceconditioning and equipment. These are included in the household energy use(where they contribute 1–2%).

4.1.1.5 Relations

Full goal satisfaction in the area of human relations involves a number ofactivities, which are not independent from cultural traditions, habitats andindividual preferences. One possible combination of energy services in thissector will be used to quantify energy demands.

The need for lighting depends on climate and habits regarding the temporalplacement of light-requiring activities. Taking 40 W of present ‘‘state of theart’’ commercial light sources (at about or above 50 lumen per watt) per capitafor 6 hours a day entails an average energy demand of 10 W per cap. Still, theradiant energy from the light sources represents some ten times less energy, andmore efficient light sources are likely to become available in the future.

Audio and video equipment, telecommunications and other tasks currentlybased on microelectronics in stationary mobile computer-based apparatus take anaverage of some 50–200 W per cap. for around six hours a day, or an averageenergy flux of 12–50 W per cap. Earlier, the associated equipment was based onless- or non-computerised electronics and used several times more energy perdevice. However, the more efficient miniaturised phones and other devices usingmicroprocessors are more than compensated for by larger number of unitsoperated during more hours by each user. Flat screens for television or computerdisplays use 5–10 times less energy than cathode-ray tube screens, but the preferredsizes of the screens have increased to nearly offset the energy-efficiency advantage.

Other leisure-related appliances, most of which we may not be able toimagine today, will in the future add to this. Past problems such as highstandby power use for equipment performing unattended services, e.g. reg-ulation of indoor environment, satellite recording or internet downloading,have been minimised by ‘‘smart controls’’ (Sørensen, 1991). The future addi-tional energy expenditure may (as in Figure 4.5) be taken as some 30 W per cap.Social and cultural activities taking place in public buildings are assumed to beincluded in the above estimates, as far as electric energy is concerned, and to bepart of the floor area allocated to each person in regard to space conditioning.

Recreation and social visits entail a need for transportation, by surface or bysea or air. A range of 25– 133 W per cap. is taken to be indicative of full goal


satisfaction. The upper figure corresponds to travelling 11000 km y–1 in a road-based vehicle occupied by two persons and using for this purpose 100 litres ofgasoline equivalent per year per person. This amount of travel could be com-posed of 100 km weekly spent on short trips, plus two 500 km trips and one5000 km trip a year. Depending or habitat and where friends and relatives live,the shorter trips could be reduced or made on bicycle, and whether a yearlylong trip is considered necessary for experiencing goal satisfaction also variesamong cultures and individuals. Hence the lower limit is some 5–6 times lessthan the upper limit. Transportation energy use has grown strongly duringrecent years and the needs in the planning outlooks of many countries areassumed to continue to rise, despite the fact that few citizens want to spendmore time in traffic queues than they already do. Slowly it is being realised thatbuilding more roads does not solve the congestion problem.

4.1.1.6 Activities

Education (understood as current activities plus lifelong continued educationrequired in a changing world) is assumed to entail building-energy needs cor-responding to 10% of the residential one, i.e. an energy flux of 0–20 W per cap.for cooling and 0–65 W per cap. for heating.

Construction is evaluated on the basis of 1% of structures being replaced peryear. It would be higher in periods of population increase. Measuring structuresin units of the one-person space as defined in the biologically acceptable sur-roundings section above, it is assumed that there are about 1.5 such structuresper person (including residential, cultural, service and work spaces). This leadsto an estimate of the rate of energy spending for construction amounting to30–60 W per cap. of stationary mechanical energy and a further 7–15 W percap. for transportation of materials to the building site. The energy hidden inmaterials is deferred to industrial manufacture and the raw materials industry.

Agriculture, including fishing, lumber industry and food processing, in someclimates requires energy for food-crop drying (0–6 W per cap.), for waterpumping, irrigation and other mechanical work (about 3 W per cap.), electricappliances (about 1 W per cap.) and for transport (tractors and mobile farmmachinery, about 6 W per cap.).

The distribution and service (e.g. repair or retail) sector is assumed,depending on location, to use 0–80 W per cap. of energy for refrigeration,0–150 W per cap. for heating of commerce or business related buildings, about20 W per cap. of electric energy for telecommunications and other electricappliances, and about 5 W per cap. of stationary mechanical energy for repairand maintenance service. Transportation energy needs in the distribution andservice sectors, as well as energy for commuting between home and workingplaces outside home, depend strongly on the physical location of activities andon the amount of planning that has been made to optimise such travel, which isnot in itself of any benefit. A suggestion for using energy related to commutingmore efficiently is to let home-to-work transportation be the responsibility ofthe employer, such that the employer covers the cost and the time used (to be

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counted as working time for the employed). A compensating salary cut couldbe negotiated at the time of introducing this scheme.

Estimated total transportation energy spending is in the range of 30–100 Wper cap., depending on the factors listed above. All the energy estimates hereare based on actual energy use in present societies, supplemented with reduc-tion factors pertaining to the replacement of existing equipment by technicallymore efficient types, according to the ‘‘best available and practical technology’’criterion, accompanied by an evaluation of the required energy quality for eachapplication. A reduction could take place if the work arrangements are alteredto make it possible to carry out more work from home. This would be parti-cularly important in a transition from emphasis on heavy industry to less- ornon-material intensive job activities.

In the same way, the energy use of the manufacturing industry can bededuced by departing from the present data, once the volume of production isknown. Assuming the global possession of material goods to correspond to thepresent level in the USA or in Scandinavia, and a replacement rate of 5% peryear, one is lead to a rate of energy use in the neighbourhood of 300 W per cap.Less materialistically minded societies would use less. Spelled out in terms ofenergy qualities, there would be 0–40 W per cap. for cooling and 0–150 W percap. for heating and maintaining comfort in factory buildings, 7–15 W per cap.for internal transportation and 20–40 W per cap. for electrical appliances. Mostof the electric energy would be used in the production processes, for computersand for lighting, along with another 20–40 W per cap. used for stationarymechanical energy. Finally, the process heat requirement would comprise10–100 W per cap. below 100 1C , 20–70 W per cap. at 100–500 1C and 12–30 Wper cap. above 500 1C, all measured as average rates of energy supply overindustries very different in regard to energy intensity. Some consideration isgiven to heat cascading and reuse at lower temperatures, in that the energyrequirements at lower temperatures have been reduced by what corresponds toabout 70% of the reject heat from the processes in the next higher temperatureinterval. As indicated in the caption to Figure 4.5, a more radical transitionfrom the present industrial pattern to a less work and energy intensive one ispossible and likely to be preferred on a global scale.

Very difficult to estimate is the future energy needs of the resource industry.This is for two reasons: one is that the resource industry includes the energyindustry, and thus would be very different depending on which supply option orsupply mix is chosen (cf. the global scenarios of supply sketched in Figures 4.2–4.4). The second factor is the future need for primary materials: will it be basedon new resource extraction, as it is largely the case today, or will recyclingincrease to near 100%, for environmental and economic reasons connectedwith the depletion of mineral resources?

As a concrete example, let us assume that renewable energy sources are used.The extraction of energy by a mining and an oil & gas industry as we know ittoday will disappear and the energy needs for providing energy will take a quitedifferent form, related to renewable energy conversion equipment which inmost cases is more comparable to present utility services (power plants, etc.)


than to a resource industry. This means that the energy equipment manufacturebecomes the dominant energy requiring activity.

For other materials, the ratios of process heat, stationary mechanical energyand electricity use depend on whether mining or recycling is the dominant modeof furnishing new raw materials, so in the ranges given, not all the maxima arelikely to become realized simultaneously, and neither all minima. The numbersare assumed to comprise both those of the energy industry and for all materialprovision industries. The basis assumption is high recycling, but for the upperlimits not quite 100% and adding new materials for a growing world popula-tion. The assumed ranges are 0–30 W per cap. for process heat below 100 1C,the same for the interval 100–500 1C, 0–250 W per cap. above 500 1C, 0–170 Wper cap. of stationary mechanical energy, 0–30 W per cap. of electrical energyand 0–20 W per cap. of transportation energy.

4.1.1.7 Summary of Energy Requirements

Figure 4.5 summarizes the estimates of energy requirements for 100% satis-faction of the specified goals, distributed on energy qualities. The range indi-cations reflect differences in climate, in habitat and physical layout and alsodifferences in ways and means of production and type of goods produced.

There is an obvious lack of accuracy in any such estimate of future energydemands, such that it could be both too low and too high: new activities involvingenergy usage will emerge and may exceed the largely unqualified guesses made,and in the other direction the efficiency of energy use by novel technology mayincrease more than assumed. Yet it is reassuring that the global energy demandsassociated with full goal satisfaction (for a choice of goals not in any wayrestrictive) can indeed be limited to values allowing the entire world population,including underdeveloped and growing regions, to be brought up to a level of nearfull goal satisfaction. There are no technical reasons that this may not happen, butof course poor performance of the global political and financial systemmay derailthe goal-fulfilment development, as it has indeed until the present.

4.1.2 Energy Production, Conversion and End Use

Figures 4.2 to 4.4 have already pointed to fossil, nuclear and renewable sourcesas the main candidates for energy supply. Each of these has been studied indetail and the reader interested in technical details is referred to Sørensen(2010a) for renewable energy and Sørensen (2005) for fossil and nuclear optionsintegrated into hydrogen-based delivery to end users. Here, only a shortintroduction to the technologies involved will be made, aimed at providing thenecessary background for following the life-cycle studies of equipment andsystems based on such technologies.

4.1.2.1 Clean Fossil Technologies

Fossil resources are biomass that has undergone transformations over periodsof millions of years. A discussion of fossil resources and their geographical

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distribution may employ a simple version of the standard distinction betweenreserves and other resources, employing the following three categories (Sørensenet al., 1999): (1) proven reserves are deposits identified and considered economicto exploit with current price levels; (2) additional reserves are deposits that existand are economic, with a probability over 50%; (3) new and unconventionalresources are all other types of deposits, typically inferred from geological mod-elling or identified but not presently being considered economic to exploit.

The sum of all known and inferred (with reasonable probability) resourceswithout consideration of economy of extraction is the resource base. The levelof investigation is uneven among regions and therefore additional amountsmay be discovered, particularly in areas not well studied today. However, therate of finding new deposits has diminished over the last 50 years. Becauseextraction methods vary with time, new techniques (e.g. enhanced oil recovery)may alter the amount of reserves assigned to a given physical resource.

Estimates of fossil resources and reserves are abundant. A standard appraisalmay be found in Sørensen (2005). For oil, the reserves are more than 50%depleted and the period in which reliance on this resource can be continued maybe very short, depending on the pace of exploitation, e.g. by rapidly indus-trializing parts of the world. Figure 4.6 gives an impression of the span ofpossible outcomes and the prices likely to be associated with the depletion path.

Figure 4.6 Oil consumption during resource depletion, sketched on the basis of his-torical data and discovery rates (Sørensen, 2005), with price curves aimedat showing the volatility of the oil market. The lower, bell-like con-sumption curve is that of the King Hubbart depletion model assumingavailability of substitution energy at low additional cost (Hubbart, 1962).


The oil price is primarily market driven, due to the low extraction costs in theMiddle East regions where most of the remaining reserves are located. At the100 US $ per barrel level, several alternatives to oil become economically viable.

Fossil fuels are burned in conventional Carnot cycles, oil in vehicles, ships andaircraft, natural gas in furnaces and turbines for heat and electricity, and coalsimilarly in Rankine cycles, including various combined heat and power schemesas well as staged combustion. The purpose of the more elaborate schemes is toreach higher conversion efficiencies. This could imply lower emissions, but isoften used as an excuse for increasing demand. In any case, the fuels combustedwill lead to emissions and concerns in proportion to the magnitude of usage.

Because the environmental worries over fossil fuels are in part due to pol-lutants (such as SO2, NOx and particles), for which the emissions can bereduced at a modest cost, and in part CO2, which is difficult to reduce becauseof its quantity, the technologies included in claims of providing ‘‘clean fossilfuels’’ are mostly directed at removal of CO2. They are illustrated in Figure 4.7.The substantial range of dispersal for components such as SO2, causing healthproblems and destruction of historical monuments, is further discussed in thelife-cycle analysis presented in Section 6.1. Removal of CO2 after conventionalcombustion may be achieved by absorbing CO2 from the flue gas stream (e.g.using reversible absorption into ethanol amines), by membrane techniques orby cryogenic processes leading to the formation of solid CO2. These techniqueshave the disadvantage of requiring substantial energy inputs, and the mostaccessible techniques (absorption) further only lead to a partial capture of CO2

(Meisen and Shuai, 1997; Rubin et al., 2005). However, there is hope to achieveabout 90% recovery, which would be quite acceptable for greenhouse gas

Figure 4.7 Various routes proposed for carbon capture (Rubin et al., 2005).

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mitigation, and the energy requirements may be reduced to around 10% (of thepower generated) for natural gas-fired units and 17% for coal-fired ones(Mimura et al., 1997).

An alternative ‘‘after combustion’’ type of CO2 removal is to convertatmospheric CO2 to methanol by a catalytic process at elevated temperatureand pressure. The catalysts may be based on Cu and ZnO, and laboratorydemonstrations used a temperature of 150 1C and a pressure of 5 MPa (Saitoet al., 1997). Additional reaction products are CO and water. Other optionsconsidered include carbon sequestering by enhanced biomass growth, whereincreasing forest areas can provide a long time interval between carbonassimilation and subsequent decay and release (Schlamadinger and Marland,1997). A general overview is provided by Rubin et al. (2005), cf. Figure 4.7.

The most promising option for avoiding CO2 is possibly to transform thefossil fuels to hydrogen and then use this fuel for subsequent conversions.Currently, hydrogen is produced from natural gas by steam reforming withwater vapour. The process, which typically takes place at 850 1C and 2.5 MPa(Sørensen et al., 1999), is given by:

CH4 þH2O! COþ 3H2

followed by the catalytic shift reaction:

COþH2O! CO2 þH2

The CO2 is removed by absorption or membrane separation. The conversionefficiency is about 70% (Wagner et al., 1998). If the initial fossil fuel is coal, agasification process is employed (partial oxidation):

2CþO2 ! 2CO

followed by the shift reaction as above (Jensen and Sørensen, 1984). Nitrogenfrom the air is used to blow oxygen through the gasifier, and impurities in thecrude gas (called producer gas) are removed. With impurities removed, thehydrogen fuel is now of pipeline quality, ready to be transported to the pointsof use. The overall conversion efficiency is about 60%. The quantities of CO2 tobe disposed of following the processes above are huge, and storage in aquifersor abandoned wells may be insufficient (capacity less than 100 Gt of coalaccording to Haugen and Eide, 1996). This leaves ocean disposal of CO2 as theonly serious option. Storage here would be by dissolving liquefied CO2 inseawater at depths of 1000–4000 metres through special pipelines from land orfrom ships, or by converting the CO2 to dry-ice form and simply dropping itfrom a ship into the ocean (Koide et al., 1997; Fujioka et al., 1997; Rubin et al.,2005). The CO2 is supposed to subsequently dissolve into the seawater, andif suitable sites are selected it may stay in cavities or on the ocean floor inde-finitely, due to its higher density. The ocean disposal processes are summarisedin Figure 4.8.


The cost includes that of liquefaction or dry-ice formation, plus operationalcosts and pipelines if used. Fujioka et al. (1997) estimate these costs to be about0.03 US$ per kWh of fuel (0.08 $ per kWh of electricity if that is what isproduced) for the liquefied pipeline and ocean tanker disposal scheme, and 0.05US$ per kWh of fuel for the dry-ice scheme.

The CO2-rich waters will stimulate biological growth and may seriously altermarine habitats (Takeuchi et al., 1997; Herzog et al., 1996). Stability of thedeposits, and the subsequent fate of any escaped CO2, will have to be estab-lished, e.g. by experiments over periods of many decades.

4.1.2.2 Nuclear Technologies

Nuclear fuel reserves are no larger than those of oil or natural gas if used inonce-through reactor types. Some kind of breeder reactor is required fornuclear technologies to make a credible successor to fossil fuels. Furthermore,if the technologies should qualify for what is termed ‘‘safe nuclear power’’ theymust address the main objections to current nuclear power technologies: pro-liferation issues, large nuclear accidents and long-term storage of waste. Ideasand new technologies for avoiding or reducing these problems have been dis-cussed for some years, but all are still fairly speculative. A few have been testedat laboratory scale, but their implementation will take further technicaldevelopment and would presumably make nuclear power more expensive than

Figure 4.8 Overview of methods for CO2 disposal in oceans (Rubin et al., 2005).

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today. These additional costs have to be justified by including life-cycle costs ofthe problems associated with current nuclear technologies.

Many reactor types to replace the light-water reactors have been studied overthe past 4–5 decades, but none have reached the stage of market introductionon a commercial basis. Among these are high-temperature gas-cooled reactorsand sodium-cooled fast breeders. Current proposals are aware of the issuesraised above, but still far from deal with all of them. The reactor industry hasrecently concluded that a new generation of safer reactors will require sub-stantial breakthroughs (particularly in materials science) that may push com-mercialisation at least 25 years into the future (USDoE, 2002). Severalproposed concepts are summarised in Table 4.1.

The four proposed reactor types operating at temperatures over 1000 K maybe used for direct hydrogen production. All of the concepts operate at tem-peratures higher than theB600 K of existing light-water reactors and thereforewould produce electric power at a higher efficiency. The likely cheapest of thesystems is the extreme pressure water-cooled reactor, but it does not solveproblems of large accidents and large amounts of nuclear waste. The sodium-cooled breeder has already been carried to a large-scale demonstration stage,but has had troubled operational experiences and as a concept does not solvethe problems of safety and cost. Like the three other types in Table 4.1requiring reprocessing of spent fuel, it has severe weapons proliferationdangers. Helium-cooled reactors have also been researched for many years,with the most recent prototype just going critical in Japan. The very high-temperature proposals do pose materials problems expected to require manyyears of research and development efforts. While the Japanese prototype usesfuel pellets in a honeycomb graphite structure, future versions are expected tobe of the pebble-bed type, consisting of millions of 5–10 cm diameter spheres offuel coated with graphite (acting as moderator) and a very hard ceramics layer,to capture and encapsulate fission products. In this way, it is hoped that anaccident will not lead to release of large amounts of radioactivity to theenvironment. However, this depends on temperature control in the event of anaccident, a problem still needing to be resolved. No proposal for safeguardingplutonium created during reprocessing has yet been found credible.

Table 4.1 Various industry proposals for new generations of nuclear reactors(Rubbia et al., 1997; USDoE, 2002; Butler, 2004; Sørensen, 2005).

Technology Coolant PressureTemp.(K) Issues

Conventional breeders sodium low 820 safety, cost, reprocessingSupercritical water water very high 800 safety, materials, corrosionVery high temperature helium high 1300 safety, materials, accidentsGas-cooled breeders helium high 1130 materials, fuels, recyclingLead-cooled breeders lead–bismuth low 800–1100 materials, fuels, recyclingMolten salt fluoride salts low 1000 materials, salts, reprocessingAccelerator breeder lead low 850 Th cycle, 208Tl waste, cost


The energy amplifier proposed by Carlo Rubbia is making significant stepstowards solving the nuclear reactor problems. By using a particle reactor andspallation to create subcritical nuclear material only at the rate in which it isused in a subsequent reactor step, the accident risk is greatly reduced and themilitary connection weakened. Radioactive waste is produced, but most of ithas a half-life of under 100 years, in contrast to the million years for conven-tional plutonium-forming reactors (Rubbia et al., 1997; Sørensen, 2005).Maiorino et al. (2001) proposed the use of multiple spallation points andhelium instead of molten lead as a coolant. Technically, the concept poses manychallenges and an intermediate radioactive isotope, 208Tl, has a very high g-activity that makes reprocessing difficult.

The concept of inherently safe designs largely eliminates the risk of coremeltdown in case the heat from fission processes cannot be led away. Twoexamples of proposed inherently safe reactor designs are either to reduce thesize so much that core melt accidents almost certainly can be contained by thevessel used (this involves maximum unit sizes of 50–100 MW in a traditionaldesign, while the pebble-bed reactor may circumvent this limitation, if theintegrity of the pebbles can be guaranteed), or to use a design in which the coreof a conventional pressurised water reactor (PWR) is enclosed within a vessel ofboronated water that will flood the core if pressure is lost. There is no barrierbetween the core and the pool of water, which in case pressure in the primarysystem is lost will shut the reactor down and continue to remove heat from thecore by natural circulation. It is calculated that in an accident situation,replenishing the cooling fluid can be done at weekly intervals (in contrast tohours or less required for current light-water reactor designs) (Hannerz, 1983;Klueh, 1986).

To avoid proliferation, fissile material such as plutonium should neveraccumulate in large amounts or should be difficult to separate from the streamof spent fuel. This can be addressed by using Rubbia’s energy amplifier.Accelerators are also an option for ‘‘incineration’’ of current nuclear andmilitary waste, in order to reduce waste storage time and again avoid storage ofwaste from which weapons material could be extracted.

There are additional reasons why reviving nuclear power is problematic. Theoriginal developments were done by the brightest scientists and engineers of thetime, wanting to demonstrate that nuclear technologies could be used forpurposes other than weapons for destruction. Similarly, the builders andoperators of nuclear plants felt a particular pride in working with this cutting-edge technology. Today, after 40 years of nearly no new construction activities,the old-timers have gone, nuclear engineering has disappeared from thecurriculum of most universities, and current builders and operators cannotbe expected to see nuclear plants as deserving special care (as evidenced bythe many problems connected with the ongoing construction of a nuclearpower plant given at greatly reduced price to Finland by the starved Frenchmanufacturers). The result of this change in conditions may be an increasedfrequency of Chernobyl-magnitude accidents, should the resurrection ofnuclear power come true.

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4.1.2.3 Renewable Technologies

The main renewable energy sources for energy extraction are direct sun, windand biomass. Other renewable sources are hydro, for which dam constructiondestroying the areas to be flooded and requiring populations to be moved isincreasing seem as unacceptable. Some small-scale and cascading hydroexpansion is still possible. Geothermal steam power plant construction is alsobecoming discouraged, as the pockets of geological steam have proven shorterlived than expected. Low-temperature district heating by use of averageoutflows of heat from the interior of the Earth could still play an important rolein many city and suburban environments. Tidal power plants are suffering fromproblems of siltation and wave energy devices imply a competition betweendevice structural strength at excessively high cost and the disruptive forces ofstorm-situation wave impacts of the energy-collection structures.

The only renewable energy technology that has been consistently viable,technically as well as economically, is wind power. Turbine size has increasedfrom tens of kilowatts to several megawatts, and wind turbine arrays have beensuccessfully built and operated on windy land-sites as well as on off-shore siteswith fairly shallow waters, where the additional cost of foundations at 20–40metres depth is compensated by higher wind speeds over the sea and thushigher power output compared to a similar installation placed inland.

Solar panels producing heat and power have been developed but in manyclimatic regions they are still considered on the expensive side. The problem isthat those regions with the largest space heating demand also have little solarradiation, especially during winter where it is most needed. Solar electricity,e.g. produced by photovoltaic collectors, are still considered expensive even inregions with high levels of radiation, and so is power from solar concentratorsthat work only with direct radiation, not with the scattered radiation that withthe exception of desert areas constitute about half of the total resource.

Biofuels are fuels, usually in the liquid or gaseous phase, made from biogasby biological or thermochemical processes, often with the use of enzymes orcatalysts. They are near economic viability when produced from elementarysugar-containing material and a little more expensive when produced fromcellulosic material. This is an important distinction, because in the first case thebiofuels may compete with food production, while in the second case this is notthe case. Plants assimilate CO2 when growing and release it when, for instance,used in vehicle fuels, so only for short-rotation plant growth can the biomass beclaimed to be carbon neutral. This and the emission of pollutants make life-cycle analysis of biofuels (including of course the solid biomass plainly burnedat present) an important part of assessing whether these energy sources shouldbe allowed in future supply systems. Direct solar and wind energy do not havesuch problems, but on the other hand cannot be stored, so any facilities neededfor handling the intermittency must be included in life-cycle studies.

Details of the renewable energy technologies may be found in Sørensen(2010a) and the same is true for issues of energy transmission and distribution,by ships, pipelines or power lines.


The final step in an energy-conversion chain is the conversion of energydelivered to the end-user into the final product or service demanded. In somecases there would be more than one way to achieve this, with widely differentrequirements of delivered energy. An example is residential houses, whichexcept for the most extreme climates can be built using passive architecturalfeatures making both heating during cold days and cooling during hot dayssuperfluous. Similarly, other types of energy end-use offer solutions with arange of different efficiencies, and often with little cost increase for improvingefficiency. Examples of such end-use technologies may be found in Sørensen(1991) and in volume I of Sørensen (2010b).

4.2 Scenario Techniques

There are many reasons for wanting to make forecasts of the future. Enterprisescould make economic gains from knowing future markets or future resourcerequirements, governments could arrange to promote precisely the right kindsof policies, and environment groups could prove to people just how disastrousan extrapolation of current trends would be. Unfortunately, simple forecastingdoes not work, because there are too many parameters influencing our path,too many possible futures and too many unknowns. Instead, there is the optionto influence the course of events by proposing new paths of development thatappear attractive to our fellow human beings. This is what politics is about andit is where scenarios come in, not as predictions of the future but as tools forinfluencing the direction of present policy. The scientific contribution is to testthe consistency of scenarios for the future and to identify the sequences ofdecisions that must be taken in order to get from the current situation to thesociety envisaged in a certain scenario.

4.2.1 Why Use Scenario Techniques?

In order to assist decision makers in upgrading the existing energy systems andplanning for new, future systems, the LCA method needs a way of describing agiven energy system that is also suitable for systems not yet implemented. Doesthe above critique of simple demand and supply forecasts based on economicmodelling invalidate such attempts? To answer that, one should keep in mindthat most economic theory deals only with the past and occasionally the presentstructure of society. Thus what it can do is possibly to observe relationsbetween different factors, to construct theories describing causal relationships,and to test them on actual data. In order to deal with the future, one may theninvoke the established quantitative relations between components and assumethat they stay valid in the future. This allows for what is called ‘‘business-as-usual’’ forecasts, e.g. using econometric models such as input–output matricesto compute the future situation. Because the measured ‘‘coefficients’’ describingrelations between the ingredients of the economy vary with time, one canimprove the business-as-usual forecast to take into account trends already

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visible in the past development. However, even such trend-forecasts cannot beexpected to retain their validity for very long periods (Makridakis, 1990).Actually, it is not even the period of forecasting time that matters, but changesin the rules governing society. These may change due to abrupt changes intechnology used (in contrast to the predictable, smooth improvements oftechnological capability or average rate of occurrence of novel technologies), tospecial events such as stockmarket collapses, or they may be changed bydeliberate policy choices, assuming, of course, that choice is a feature of humanenterprise, including politics.

Studies such as the ones proposed in connection with system-level life-cycleanalyses that aim at investigating the action room for alternative changes inpolicy (including radical changes that are known to have taken place over timehorizons such as the 50þ year period in some of the cases considered) thereforehave nouse of the conventional forecastingmethod, neither of status quoor lineartrend extrapolation. It is sometimes argued that econometric methods couldinclude non-linear behaviour, e.g. by replacing the input–output coefficients bymore complex functions. However, to predict what these should be cannot bebased on studies of past or existing societies, because the whole point in humanchoice is that options are available that are different from past trends, even non-linear ones. The non-linear, non-predictable relations that may prevail in thefuture, given certain policy interventions at appropriate times, must thus bepostulated on normative grounds. This is precisely what the scenario methoddoes. Or rather, it is one way of describing what goes on in a scenario analysis.The conclusion is therefore that the objective of analysing policy alternativescannot be reached by conventional economic methods, but must invoke ascenario construction and analysis, one way or the other (Sørensen, 1995).

It is important to stress that scenarios are not predictions of the future. Theyshould be presented as policy options that may come true only if a prescribednumber of political actions are indeed carried out. In democratic societies thiscan only happen if preceded by corresponding value changes affecting a suffi-ciently large fraction of the society. Generally, the more radical the scenariodiffers from the present society, the larger must the support of a democraticallyparticipating population be. Of course, not every nation in the world enjoys ademocracy allowing for such participation.

The actual development may comprise a combination of some referencescenarios selected for analysis, each reference scenario being a clear andperhaps extreme example of pursuing a concrete line of political preference. It isimportant that the scenarios selected for political consideration are based onvalues and preferences that are important in the society in question. The valuebasis should be made explicit in the scenario construction.

The scenarios used for illustrating the LCA method in Chapter 8 aremeant to provide a basis upon which an informed discussion of options forgreenhouse emission mitigation can be carried out. The scenarios proposed willbe tested for technical consistency and resilience and a number of environ-mental and social, as well as the basic economic, impacts will be evaluated,based on recent studies in the externality field, but extrapolated to the more


developed and in some cases novel technologies proposed for the mid-21stcentury. The uncertainty of such an appraisal is recognised, but precisely the lackof complete knowledge is a fact that underlies the political decisions that must betaken today, in order to accomplish the development of a better energy system forthe future. The benefit of having a thorough investigation of these impacts, as faras they can be discerned today, available to the political deliberations regardinggreenhouse issues is evident and is why the scenariomethod is here selected as theappropriate tool. It really does not have anymeaningful competition.All analysismade to date of long-term policy alternatives are effectively scenario analyses,although they may differ in the comprehensiveness of the treatment of futuresociety.A simple analysismaymake normative scenario assumptions only for thesector of society of direct interest for the study, assuming the rest to be governedby trend rules similar to those of the past. One of our scenarios is of this kind.A more comprehensive scenario analysis will make a gross scenario for thedevelopment of society as a whole, as a reference framework for a deeperinvestigation of the sectors of particular interest. One may say that the simplescenario is one that uses trend extrapolation for all sectors of the economy exceptthe one focused upon, whereas the more radical scenario will make normative,non-linear assumptions regarding the development of society as a whole. Thefull, normative construction of future societies will come into play for a scenariodescribing an ecologically sustainable global society.

4.2.2 Methodology and Short History of Scenario Construction

The scenario method is a decision support tool used for shaping alternativenational policies. It basically involves selecting a small number of the possiblefutures, selected on the basis of having spurred an interest in the populationand by reflecting different values held in a particular society.

Once identified, these futures have to be modelled, with emphasis on theissues deemed particularly important: better social conditions, less pollutingenergy systems, environmentally sustainable processes, societies offeringhuman relationships within a preferred frame, and so on. During this processone must keep in mind that models are simplified and necessarily inaccuraterenditions of reality and have to be treated accordingly. Models are essentiallyframeworks for discussion.

One would next have to discuss the consistency of the elements in the models,e.g. as regards sustainability, resource availability and consistency betweendifferent aspects of the scenario, and finally discuss possible paths from thepresent situation to the scenario future. This would be done for each scenarioproposed, as part of an assessment involving the full apparatus of politicaldebates and decision-making processes.

Central questions to address are who should propose the scenarios and whoshould stage the debate and decision process. There are clearly many possibi-lities for manipulation and unfair representation of certain views. Whether ademocratic process can be established depends on the level of education andunderstanding of the decision process by the citizens of a given society, as well

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as on the tools used for debate, including questions such as fairness of, andaccess to, media. Many developed countries have a tradition for broad socialdebates, but even in such countries there are also clear efforts by interest groupsor sitting governments to take over the communication media and distort theprocess in favour of their own preferred solutions. These institutional ques-tions, which have to be part of any realistic proposal for a new way ofapproaching development issues, were hinted at in the discussion of Figure 3.3.

The first uses of scenario techniques along lines resembling the onessketched above were inspired by the system dynamics ideas proposed around1970 by Forrester (1971) and H. Odum (1971), building on population modelsused in ecology (E. Odum, 1963). The basis was linear compartment modelsdescribed by coupled sets of first-order differential equations, originally aimedat explaining feed-back loops to students. Application of these methods toresource dynamics, promoted by industrial magnate Peccei and his ‘‘Club ofRome’’, with Meadows as science writer (Meadows et al., 1972), spurred aglobal debate on the finiteness of certain resources, although the actualmodelling was far too oversimplified to be credible.

While the system dynamics people claimed to be able to predict cata-strophes happening if habits were not changed, the scenario models aimprecisely at exploring the alternative policies that would alleviate anyunwanted or unpleasant development. The first ones were primarily aimed atenergy production, a subject very much in the forefront during the early1970s: scenarios for sustainable energy systems were tied to assumptions ofsocially equitable and globally conscious behaviour (Eriksson, 1974; Erikssonet al., 1974; Sørensen, 1975a, 1975b).

These ideas were later taken up, e.g. by Lovins after his visits to Scandinavia,and widely disseminated (Lovins, 1977). However, his reproduction was notentirely faithful, as he postulated that his scenario was already the cheapest in aconventional direct economy evaluation (clearly an incorrect postulate at thetime) and thereby he avoided having to deal with all the more subtle questionsof tackling indirect economy (i.e. precisely the externality and LCA issues).

The use of scenario techniques was again taken up by Johansson and Steen(1978), as well as by a number of other groups all over the world (see overviewin Sørensen, 1981). The attitude towards such modelling efforts have matured,and today, most modellers realise the need to model not only technical systemsbut also the social context into which the technical solutions are imbedded, theenvironmental impacts and the implications for global strategies. In otherwords, the scenarios are seen as more comprehensive visions of future societies,although it is still necessary to restrict the features detailed, in order for themodels to remain manageable (Sørensen, 1995, 2010a).

4.2.3 Sociological and Geopolitical Basis for Scenarios

Energy scenarios often have a fairly long time horizon, such as 50 years. This isnecessary because they aim to investigate options for a future society in which


most current equipment will have been replaced, leaving the possibility ofpolitically influencing the choice of such new equipment. In this sense, scenariosdeal with systemic rather than marginal changes (cf. Figure 1.2). Only in thecase of buildings will there even after 50 years be a fraction left over from thepresent era. Despite the necessity for a long time horizon, the purpose of sce-nario building is to influence policy debates and decisions today, by settingtangible goals and directions for current action. No attempt is made to guessthe most likely development in the absence of such a debate and no prog-nosticating or forecasting of the future is attempted. The aim is to promoteconscious policy-making in contrast to policy by inertia or the common policyby default or least-pressure solutions.

The attitudes characterizing populations of countries, where the level ofeducation and political tradition allows meaningful debates over the selectionof futures to proceed, may in a simplified and highly condensed form bedescribed by just two archetypes (Sørensen, 1989):

� the concerned citizen� the audacious citizen

The concerned citizen is worried over the possible side-effects of humanactivities, whether it is environmental pollution, genetic manipulation or degra-dation of social conditions. If we cannot take in and understand the consequencesof introducing a new technology, then it is better to forego that technology or atleast to issue a moratorium until we better understand the consequences.

Opposed to this attitude, the audacious citizen will say ‘‘Let us take the risk.If something goes wrong, we will deal with it then, and quite likely we shall finda solution’’ (albeit possibly with other unknown consequences). As regardsclimate change caused by greenhouse gas emissions, the audacious person willsay not to worry, as the cost of adapting to any change in climate, should itreally occur, may be smaller that the cost of restraining our activities now, orwe may become better at dealing with the problem, given the progress causedby all the new activities between now and then.

The audacious individuals have produced advances in the past, and they havealso produced quite a number of problems. Likewise, the concerned personshave made contributions, although perhaps less spectacular: they have stimu-lated the development of alternative technologies and have made social changesmore human. In any case, these two groups have existed during the last centuriesin most industrialized countries and they have roughly divided the population intwo equally large fractions, with predominance and political influence movingback and forth between the two groups. Probably the debate created by thesetwo opposing views has been beneficial for overall development.

The environmentally sustainable energy scenario presented in Chapter 8 is areflection of the views of the concerned citizen. The group of authors had moredifficulty in arriving at a precise definition of the other scenario discussed inChapter 8, finally settling for ‘‘the fair market scenario’’. There is no point inmaking a scenario corresponding to the audacious citizen’s views. To satisfy

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this person, there should be as little planning as possible, no restrictions ondevelopment of new technologies and no cost associated with indirect impactsof human activities. Since scenarios should represent realistic futures, thetotally deregulated society caricature of an ultimate liberalism can hardly be ofinterest to societies that, even when they boast of being liberal, still regulate alarge number of areas and have no illusions of realistically doing away with mostof these regulations (buildings safety codes, traffic rules, courts of law, police,etc.). The slogan ‘‘deregulation’’ is an argument in amuchmore restricted debateon whether or not to marginally increase or decrease regulation.

Considering such reflections, one may ask what a scenario contrasting theecological one should then look like? Perhaps the society against which we arecurrently headed, i.e. an extrapolation of the directions of change observedtoday. This direction is itself a compromise between the political groups of thepresent society, and in the above simplified model of social preferences it isthe compromise currently struck between the views of the concerned and theaudacious citizens. Using this choice for a scenario might possibly create apositive one. It might be that the current political balance between the twoviews is already a fair one, and that the society developing as a consequence ofthis balance will indeed be the best in dealing with future challenges, includingthose posed by greenhouse warming. The question being addressed by sub-jecting such a scenario to an LCA is then, if this is really so, whether it can besubstantiated by assessing the impacts, or if a more radical change in politicaloutlook is required, taking into account some of the considerations made bythe concerned citizens.

Even national or regional scenarios have in most cases to be complementedby at least a sketch of the global development. This includes a view on thepopulation development, the type of activities favoured globally and corre-spondingly the demand for resources and the level of international tradeinvolving both resources and products.

In order to make, say, a climate change mitigation scenario for Europecredible, it is fairly evident that global development has to be assumed to followpatterns similar to or consistent with the European ones. It would not besensible, at least in a strict greenhouse mitigation context, to look at aEuropean transition to renewable energy if the rest of the world goes onburning fossil fuels (this does not mean that there could not be reasons, otherthan greenhouse effect mitigation, that could make it attractive to introducerenewable energy). In the European scenarios discussed by Sørensen et al.(1999), it is therefore loosely assumed that a similar policy is pursued all overthe world and further that the disparity between rich and poor countries isdiminished, because otherwise it is difficult to see how the population growthcould be halted (short of nuclear war).

For the environmentally sustainable Danish scenario of Section 8.1.1 (basedon Kuemmel et al., 1997), which is based on low energy consumption as a basisfor introducing a viable renewable energy system, we would thus assume asimilar development of efficient use of energy globally at the same time as thestandard of energy services (as a part of living standards) moves towards a


common, global level of an average rate of energy conversion at around onekilowatt per capita. The fair market scenario of Section 8.1.1 would assume asimilar long-term development globally, but not reaching it so fast and prob-ably not within the planning period.

One very basic fact in energy planning is that the use of primary energy maydecline, while the services delivered to the end-users increase. The differencebetween primary energy and end-use service is not just conversion lossesthrough the steps from primary to final conversion, but also reflects on theactual service derived from the final conversion. The end-use energy is ideallymeant to represent the lowest possible energy required to deliver a given service,using known technology (but not necessarily the technology in current use),including ideas for providing a given service by other means than those usedtoday (e.g. replacing business travel by video conferencing). In practice, thetheoretical minimum end-use efficiency cannot always be realised and it iscustomary instead to use the minimum that may be achieved by any technologycurrently known.

Before going into life-cycle analysis of concrete energy systems, a selection ofgeneric assessment cases are described in Chapter 5. The more detailed studiesof individual components of energy systems are presented in Chapters 6 and 7and then looking at entire systems in Chapter 8, first on a national basis.

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Meadows, D., Randers, J., Behrens, W. (1972). The Limits to Growth. PotomacAssociates, Washington.

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Odum, E. (1963). Ecology. Holt, Rinehardt and Winston, New York.Odum, H. (1971). Environment, Power and Society. Wiley, New York.Rubbia, C., Rubio, J., Buono, S., Carminati, F., Fietier, N., Galvez, J., Geles,

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Part II

APPLICATIONS

APPLICATIONS

The energy applications of life-cycle analysis range from looking at individualdevices to assessing complete systems, either existing ones or those con-templated for the future. This part of the book is organised by first consideringsome generic issues found in many pieces of technology and playing a role forseveral kinds of energy systems. These include greenhouse gas emissions,releases of radioactivity or of toxic substances such as heavy metals and par-ticulate matter, each causing identified health problems. These preliminarieswill be useful, because they enter into most of the systems subsequently studied.The local systems are divided into energy conversion technologies employed inprimary resource extraction and conversion between qualities, such as from themechanical energy of wind to electricity, and then end-use technologies, abroad category comprising all the activities of societies, from providing foodand basic shelter to supporting activities in home and any required trade orindustry. Finally, the look at energy systems will be expanded in scale, fromlocal to national systems, to regional and finally to global systems that mayevolve over the next several decades.Clearly, this is just one way of organising the material. There may be other

ways, just as a cake can be cut in different ways. For product life-cycle analysis,the chain approach has been proven very appropriate, going back to the pro-duction equipment and the resources needed for that, and going forward todiscarding the product and looking at the various fates that may ensue, leavingthe product as waste or establishing some reuse or recycling. The chainapproach has often been proposed also for energy LCA work (cf. Figure 2.1),but in many cases it does not seem the most appropriate. While it may besensible to trace backwards from the electricity produced in a power plant tothe renewable energy harvested or the fuel extracted, it does seem convenient tostop at the electric power and not combine an LCA of the myriads of electricityuses with the LCA going from the primary source to electricity. This impliesthat one can consider partial chains, but of course still with inclusion of ‘‘cradleto grave’’ impacts from the equipment used for the conversions involved.Similarly, ‘‘cradle to grave’’ analysis of the end-use devices and activities inindustry, commerce or residential sectors would be better made by consideringstand-alone components, independent of where input resources such as elec-tricity come from. This allows comparison of different solutions, as long as theelectricity inputs are similar.

CHAPTER 5

Life-Cycle Analysis of ParticularSubstances and Common Issues

In performing life-cycle analysis and assessment there are several emissionsand impacts that appear in many situations. It is therefore useful to makedetailed analyses for these issues and make them available to draw upon inconnection with particular technologies creating such impacts. The particularanalysis will determine the amount of, say, emissions from the technology inquestion, but the impact per unit of emission may be the same independentof the technology causing the emissions. Typically, such common issues arerelated to the impacts of greenhouse gas releases, because they are wellapproximated as becoming thoroughly mixed and distributed in theatmosphere within a few years, so that the long-term impacts becomeindependent of the precise location of the emissions. Other impacts that maybe treated with use of already established dose–effect relationships areradioactivity, heavy metals and toxic trace substances or particulate matterreleased to the atmosphere or to waterways. Most concrete substances wouldbe included in the database inventories available, but it is important forgeneric usage to have included only downstream impacts of the substances.The upstream impacts will depend on the actual source of the releases anddo require a separate investigation for each case.

5.1 LCA of Greenhouse Gases

Climate change has been an integral part of the history of the Earth. However,recently, an increasing fraction of the causes for climate alteration has to beascribed to anthropogenic interventions. Among these, carbon dioxide andparticulate matter emissions stand out, although they are not the only activitiescapable of influencing climate. Also, agricultural practices such as husbandry ofmethane-emitting livestock and land use change causing changes in albedo and


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in moisture balance have made considerable contributions to atmosphericconditions and the associated changes in temperature, precipitation and soilmoisture.

The injection of carbon dioxide and other greenhouse gases such as watervapour, methane, nitrous oxide and chlorofluorocarbons into the atmospherechanges the disposition of incoming solar radiation and outgoing heat radia-tion, leading to an enhancement of the natural greenhouse effect. The modellingof the Earth’s climate system in order to determine the long-term effect ofgreenhouse gas emissions has taken place over the last 50 years with models ofincreasing sophistication and detail. Still, there are many mechanisms that areonly modelled in a crude form and some that are more basically out of reach.The Earth’s atmosphere is a semi-stable system with some measure of chaoticbehaviour. On short timescales the chaotic behaviour is obvious and causesweather forecasts to retain some validity only for periods of under one day to,at most, a week. The period can be estimated by the Lyapunov number, but theclassical equations of motion for the atmosphere contain couplings betweenlarge-scale and small-scale motion that cannot be included in circulationcalculations even with the most powerful computing devices imagined for theforeseeable future. Only on timescales of years is the periodic forcing by the Sunrestoring a quasi-stability with repetitions of gross seasonal behaviour(Sørensen, 1989, 2010). Because the Earth–atmosphere system is not in itslowest-energy state (100% glaciation), anthropogenic interference could atworst induce a transition to a more stable equilibrium, as in the calculationalexperiments first performed by Lorenz (1967).

Details of the calculation of air and water circulation in the Earth–atmosphere system have been and will continue to need to be improved byadding items previously neglected and by improving the resolution inherent inthe selection of the three-dimensional grid used for calculation. For example,the combined effect of sulfur dioxide, which is emitted from fossil fuel burningand in the atmosphere becomes transformed into small particles (aerosols)affecting the radiation balance, has become included only in recent models.Because of the direct health and acid rain impacts of SO2 and because SO2 ismuch easier to remove than CO2, the emissions of SO2 have been or are pre-sently being curbed in many countries. The residence time of SO2 in theatmosphere is about a week, in contrast to the 80–120 years for CO2, so thismeans that the climate models have to be performed dynamically over periodsof at least 100 years. This is in strong contrast to early climate models that wereonly able to calculate an equilibrium situation for a specific selection, e.g. of adoubling of CO2.

Currently used general circulation models for climate change assessmentinclude sea ice formation and melting in a reasonably consistent manner (seethe overview by Bindorff et al., 2007). However, the behaviour of sheet ice inGreenland and the Antarctic is difficult to model, owing to coupling totrajectories of ocean currents and in the long range to land depression andupheaval by the ice masses. Topology changes in high-latitude regions wereimportant 10–20 ky ago for determining ocean currents transporting water of

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different temperatures between the major oceans. Simplified models includingthese effects have been used to trace the topology, coastline contours and sealevel variations during the melting of latest ice-age sheet ice in the NorthernHemisphere (Peltier, 1994; Tarasov and Peltier, 1997; Bintanja et al., 2002), butso far has not been combined with the models used in discussions of greenhousewarming, as surveyed, for example, by the Intergovernmental Panel of ClimateChange (IPCC), an interagency United Nations outfit that has workedindependently from its mother organisations, the World MeteorologicalOrganization (WMO) and the United Nations Environmental Programme(UNEP). Figure 5.1 shows how the recently observed sea level behaviour is atthe upper edge of the uncertainty range spanned by the correspondingpredictions by the different computer models surveyed by the IPCC.

Figure 5.2 shows measured values of CO2 concentrations in the loweratmosphere over the last 300 000 years. During the ice age cycles, systematicvariations between 190 and 280 ppm (parts per million) took place, but theunprecedented increase that has taken place since about 1860 is primarily dueto combustion of fossil fuels, with additional contributions from, for example,changing land use, including felling of tropical forests. If current emissiontrends continue, the atmospheric CO2 concentration will have doubled aroundthe mid-21st century, relative to the pre-industrial value. Reducing emissionshas been politically discussed for the past 50 years, where the danger ofanthropogenic climate interference has been scientifically manifest, but neitherhave the possible energy efficiency improvements been enforced nor the tran-sition from fossil to renewable energy sources. Renewable sources remain atmuch too low a penetration into the energy supply system to seriously reducethe problem, despite some spectacular showcases.

Figure 5.1 Observed sea level change for 1970–2009 and an indication of the intervalspanned by model calculations surveyed in IPCC (2001). Reproduced bypermission from US NRC (2010). Stroeve et al. (2007) found the samebehaviour.

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The excess atmospheric CO2 corresponds to slightly over half the anthro-pogenic emissions, which is in accordance with the models of the overall carboncycle including sinks as well as sources (IPCC, 1996, 2001; Bindorff et al., 2007).The ice core data upon which the historical part of Figure 5.2 is based alsoallow the trends for other greenhouse gases to be established. The behaviour ofmethane is similar to CO2, whereas there is too much complexity for N2O toallow strong conclusions. For the CFC gases, which are being phased out incertain sectors, there is less than 50 years of data available. Both CO2 andmethane concentrations show regular seasonal variations, as well as a distinctasymmetry between the Northern and the Southern hemispheres.

Despite the limitations of climate models (Sørensen, 2010), they are deemedrealistic enough to use for the estimation of impacts due to the climate changespredicted for various scenarios of future greenhouse gas emissions. In fact, theuncertainty of impact estimates is usually dominated by issues appearing

Figure 5.2 History of atmospheric CO2 levels based on ice-core data (Sørensen, 1991;based upon Emiliani, 1978; Berger, 1982; Barnola et al., 1987; Neftel et al.,1985; Friedli et al., 1986; Siegenthaler and Oeschger, 1987; IPCC, 1996).

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further along the impact pathways, rather than by the basic climatologicalknowledge.

Figures 5.3 and 5.4 compare the result of two recent climate developmentcalculations following the changes caused by emissions and altered land usefrom the pre-industrial period to the end of the 21st century. The temperaturesand precipitation amounts being compared are for the climate centred at year2055 relative to that prevailing around 1860. Climate is usually defined as a(running) 30-year average of the variable in question (Sørensen, 2010), but 20years are sometimes used for periods of rapid change.

(a)

Figure 5.3a Difference between January temperatures (1C) around the year 2055 andduring the pre-industrial period around the year 1860, as calculated withtwo climate models: HADGEM1 (Johns et al., 2006) and MIHR(Hasumi and Emori, 2004). The IPCC emission scenario A1B was used inboth calculations. Tabular data for this and the following climate modelillustrations are obtained from IPCC (2010) and are displayed using theMollweide projection of Earth coordinates, thereby ensuring that equalmap areas represent equal actual areas, despite the distortion involved inthe three- to two-dimensional projection.


The emission scenario employed in the model comparison is taken from theinventory of scenarios commissioned by the IPCC for its discussion on climatechange. The scenarios are described in Nakicenovic et al. (2000) and used by theIPCC both in 2001 and 2006. There are four main scenarios, two of which (A1,B1) assume the world population to decline (from a peak of 8.7� 109) after 2050.The third scenario (B2) has a population stabilising at about 10.4� 109 by year2100 and the fourth scenario (A2) has a persistent population growth (year 2100population 15.1� 109), stated to be the result of a world governed by ‘‘familyvalues’’ and ‘‘local traditions’’, thus avoiding globalisation. The A1 scenarioassumes rapid economic growth, globalisation and efficient technology. A1 sub-scenarios have differences in the main energy supply selection, ranging from all-fossil (A1FI) over a broad mixture of fossil, nuclear and renewable (the A1Bscenario considered in Figures 5.3 and 5.4), to A1T, a non-fossil scenario.

(b)

Figure 5.3b Difference between July temperatures (1C) around the year 2055 andduring the pre-industrial period around the year 1860, as calculated withtwo climate models: HADGEM1 (Johns et al., 2006) and MIHR(Hasumi and Emori, 2004). The IPCC emission scenario A1B was used inboth calculations (cf. caption to Figure 5.3a).

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Scenario B1 is similar to A1 but assumes more emphasis on service and infor-mation technologies, and B2 is similar to A2 except for stabilised population andemphasis on decentralisation without fundamentalism. The IPCC scenarioselection was made from a larger collection of scenarios submitted in response toa broad invitation and reflects the most common types among the submittedscenarios. Energy industry players must have been aware of this statistical pro-cedure, as they submitted large numbers of nearly identical scenarios, whileindependent scientists and grass-root organisations mostly seem to have thoughtthat their views were well represented by a single submission.

It is unfortunate that the IPCC based its work on only these very idealisticscenarios. Most sober observers would consider no population growth after2050 as very unlikely and would question the close linkage between populationgrowth and a world without globalisation. The present world is characterised

(a)

Figure 5.4a Difference between January precipitation (10–5 kg m–2 s–1) around theyear 2055 and during the pre-industrial period around the year 1860, ascalculated with two climate models: HADGEM1 (Johns et al., 2006) andMIHR (Hasumi and Emori, 2004). The IPCC emission scenario A1B wasused in both calculations (cf. caption to Figure 5.3a).


by strong globalisation and already few products are not produced at a placedifferent from that of usage. Yet, religious fundamentalism is growing andfamily planning is not considered in large parts of the world (e.g. Africa and theMiddle East) and has de facto failed in India and surrounding countries. Thereshould have been more scenarios without successful global family planning, butthis may have appeared unpalatable to some members of the United Nationssystem.

Equally questionable is the economic optimism underlying all the IPCCscenarios. Even the A2 and B2 scenarios exhibit a 10-fold increase in globaleconomic activities to year 2100, compared with over 20 times assumed increasefor A1 and B1. The scenarios are devoid of financial crises and basically assumea smooth-running liberalistic economy in every corner of the world, where thenecessarily associated increase of disparities between nations and people within

(b)

Figure 5.4b Difference between July precipitation (10–5 kg m–2 s–1) around the year2055 and during the pre-industrial period around the year 1860, as cal-culated with two climate models: HADGEM1 (Johns et al., 2006) andMIHR (Hasumi and Emori, 2004). The IPCC emission scenario A1B wasused in both calculations (cf. caption to Figure 5.3a).

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nations miraculously do not entail any revolts or system breakdowns. Theliberalistic economy that prevails in the current world economy is based ontheoretical work from 18th century England, with little modification. Thesetheories assumed a capitalistic structure characterised by a large number ofsmall enterprises and they assumed ‘‘perfect competition’’, meaning that allplayers had all the information needed for making the right decisions. None ofthese assumptions are valid for the current situation showing a move towardsmaximum globalisation of economic activities. Monopolies are governingproduction and information is unavailable to many actors owing to industrialsecrecy, or is useless due to copyrights, patents and similar absurdities (whichoriginally may have had a role in protecting the concrete individual havingexhibited a stroke of creativity).

The global temperature distributions in January and June are qualitativelysimilar for the two models used. The Japanese model (acronym MIHR) has ahigher resolution than the UK model (acronym HADGEM1), with 160� 320latitude–longitude grid cells as opposed to 145� 192. As expected, the warmingin January is particularly elevated at the high northern latitudes, a featurereproduced by both models. Generally speaking, the warming in the rest of theworld is slightly larger in the HADGEM1 model and it does not exhibit thecooling in equatorial Africa found by the MIHR model. Otherwise the regionalvariations in the two models are very similar, including the Himalayanwarming, for example. Also the July temperature changes (Figure 5.3b) arequalitatively similar in the two calculations. The southern winter does notproduce as much warming (relative to pre-industrial) as found in the northernwinter (Figure 5.3a), and it does not increase all the way to the pole but islargest in the oceans north of Antarctica. On the northern hemisphere,considerable warming is found also in July, but the two models do not alwaysagree on regional patterns (e.g. see North America). As in January, thecalculated warming is generally somewhat larger in the HADGEM1 model.

Figures 5.4a and 5.4b show the corresponding January and July modelcomparison for precipitation. The picture is more complex, owing to rapidlyvarying regional patterns of alternating increase or decrease, but again, thequalitative picture provided by the two models is roughly the same. For Jan-uary, the HADGEM1 model finds an increase in precipitation in many regionsof Europe, where MIHR has a decrease. Also in the equatorial regions there aremany regional differences, with sign differences of the precipitation amountsfrom the two models showing in the northern part of South America, CentralAfrica and the South China Sea region.

In July, similar regional differences are apparent from Figure 5.4b, atroughly the same locations. Particularly, the models disagree in equatorialregions, including that of the Pacific Ocean, where the north–south successionof increase and decrease is reversed. Generally, the HADGEM1 model findslarger precipitation changes than MIHR for the A1B scenario relative to pre-industrial times, as was also the case for temperature changes.

As a further illustration of the regional capabilities of the current generationof climate models, Figures 5.5 and 5.6 show the effect of replacing the A1B


scenario temporal development of emissions by a uniform 1% annual increasein emissions, until a doubling of atmospheric resident CO2 is reached. Thiscalculation is done with the MIHR model (Hasumi and Emori, 2004) andcompared with the scenario A1B results from the same model.

The IPCC emission scenario A1B has emissions rising to the year 2050 andthen declining (as a result of declining population), causing the CO2 con-centration in the atmosphere to grow first exponentially but linearly after 2050.This is the reason for this scenario to produce more early warming than thesteady 1% a year growth, for both seasons.

The same scenario comparison is made in Figures 5.6a and 5.6b for pre-cipitation. As for temperatures, there are discernable regional differences in thenorthern part of South America, equatorial Africa and the South China Sea,

(a)

Figure 5.5a Difference between January temperatures (1C) for IPCC emission sce-nario A1B around the year 2055 relative to the pre-industrial period and(at top) for a 1% annual increase in atmospheric CO2 having persisteduntil a doubling is reached relative to the pre-industrial level. Both cal-culations use the MIHR model (Hasumi and Emori, 2004) (cf. caption toFigure 5.3a).

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particularly in January. In July, differences in populated areas are lessconspicuous.

Generally speaking, the total global precipitation is expected to increase by4–5% by the year 2100, owing to enhancement of the water cycle (evaporation–airborne displacement–precipitation–water motion and runoff) (Meehl et al.,2007).

Sea level change induced by changes in the Earth–atmosphere system iscausing concern in low-lying coastal communities. The comparison of modelcalculations and observations made in Figure 5.1 may be taken as expressingsome doubt as to whether the average sea level rise by the end of the 21st centurycan be kept as low as the 0.2–0.5 m suggested by Bindorff et al. (2007) in theirIPCC review. Recent observation of excess melting of the ice shelf over

(b)

Figure 5.5b Difference between July temperatures (1C) for IPCC emission scenarioA1B around the year 2055 relative to the pre-industrial period and (attop) for a 1% annual increase in atmospheric CO2 having persisted untila doubling is reached relative to the pre-industrial level. Both calcula-tions use the MIHR model (Hasumi and Emori, 2004) (cf. caption toFigure 5.3a).


Antarctica supports this concern (Rignot, 2006). Owing to ocean salinitychanges, currents and tides interacting with land shorelines and altered windpatterns, the regional distribution of sea level rise is uneven, with Canada andNorthern Europe possibly getting an additional 0.1 m rise and the Arctic seaareas by an additional 0.2–0.3 m , whereas the Southern Pacific Ocean gets0.05–0.1 m less sea level rise compared to the global average, and the ocean nearAntarctica 0.1–0.3 m less (Meehl et al., 2007). These predictions are based onaverages of results from several models that find different regional variations,and they have a high level of uncertainty.

Sea level rise is caused by global warming through several distinctmechanisms. The thermal expansion of a warmer ocean would be 0.15–0.3 mby the year 2100 for the A1B emission scenario. Uncertainty derives from

(a)

Figure 5.6a Difference between January precipitation (10–5 kg m–2 s–1) for IPCCemission scenario A1B around the year 2055 relative to the pre-industrialperiod and (at top) for a 1% annual increase in atmospheric CO2 havingpersisted until a doubling is reached relative to the pre-industrial level.Both calculations use the MIHR model (Hasumi and Emori, 2004) (cf.caption to Figure 5.3a).

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different models predicting a different build-up of cold water at certain deep-water locations (Stouffer and Manabe, 2003; Meehl et al., 2007). Continentalice-sheets, ice-caps and glaciers grow by winter precipitation and shrink byevaporation during summer, and near-coast ice shelves shed icebergs into theocean. Also, sea ice undergoes a number of corresponding processes and allcontribute to changing sea levels. Detailed studies have been made for theGreenland and Antarctica ice sheets (Ridley et al., 2005; Hanna et al., 2008;Allison et al., 2009). These effects all contribute to the overall sea level riseestimated for the A1B emission scenario at below 0.5 m by 2100 and below 1.0m by 2300, with considerable uncertainty of the concrete value.

Climate models are basically general circulation models for the atmosphereand oceans, coupled to a number of other models describing processes

(b)

Figure 5.6b Difference between July precipitation (10–5 kg m–2 s–1) for IPCC emissionscenario A1B around the year 2055 relative to the pre-industrial periodand (at top) for a 1% annual increase in atmospheric CO2 having per-sisted until a doubling is reached relative to the pre-industrial level. Bothcalculations use the MIHR model (Hasumi and Emori, 2004) (cf. captionto Figure 5.3a).


interfering with basic quantities such as pressure, temperature and wind speeds.Foremost among these are of course the solar radiation input. Other processesmay be matter cycles such as the water cycle, or they may be complex phe-nomena such as the plant and animal life cycles, and they may be specific eventssuch as volcanic eruptions, earthquakes, activities performed by human society,for instance emissions of greenhouse gases or pollutants, radioactive sub-stances, changes in land use including agriculture and animal husbandry withimplied changes in methane cycles. The complexity of possible components toinclude in climate modelling makes it clear that a never-ending process ofprogram development is required. However, one should not forget that thereare additional sources of incompleteness, which will not go away by increasingthe effort. Grid sizes of climate models have diminished as computers havebecome more potent. Slingo et al. (2009) quote a factor 400 increase in com-puting power achieved over a recent period of about 10 years. Year 2010-vintage state-of-the-art parallel-processing computers can use a grid withhorizontal sides of about 40 km, together with 70 atmospheric height levels inthe atmosphere, and the numbers bring 25 km and 90 levels for the oceanicparts of the models (which in early models had less resolution than the atmo-spheric part). Yet, they also warn that including more phenomena in the modelstructures has a higher priority than further diminishing resolution.

Still, 40 km is not small! A rule of thumb says that the resolution of theoutputs from this type of calculation will typically be five times the grid size,which would be 200 km for the best 2010 model. On a more fundamental level,all computational climate models are based upon a separation of scales intoaverage circulation and chaotic motion, the latter comprising eddy motion andturbulence on scales below some 5 km or time-scales below about 10 minutes(statistical variations in time and place are connected by the ergodic hypothesis;see e.g. Sørensen, 2010).

Only average quantities can be treated in numerical models, because thesmall-scale motion of the atmosphere is chaotic, implying that arbitrarily smallchanges in conditions at one time can lead to macroscopic changes at a latertime. From failures of weather forecasts it is known that such ‘‘later times’’often lie in the range of a few hours to at most a week. In mathematical terms,the Eulerian equations describing air motion cannot be separated into separateequations for large-scale and small-scale motion: there are coupling terms thatcomputational models must neglect because no computer is powerful enough totreat sufficiently small eddies and turbulent motion. Circulation models used inweather forecasting do not work when the coupling terms cannot be neglected,but climate models are saved by the restoring force of the periodic forcing bysolar radiation, implying that reasonably accurate multi-year forecasts can bemade with the same models that are unable to describe the circulation nextweek. These remarks also explain why regional model results are less accuratethan global averages and that some observed year-to-year variations remainunexplained by the computer models.

As an example of the coupling of general circulation to biosphere develop-ment, the model calculation from which Figure 5.7 is derived shows how

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carbon storage is increased due to the combined effects of higher levels ofatmospheric carbon (leading to enhanced plant growth) and the opposite effectsarising from changed vegetation zones as predicted by the climate models(affecting moisture, precipitation and temperature).

Understanding the interplay between the physical climate and the conditionsfor biological processes such as plant growth and agricultural yields, spread ofvector-borne diseases and extinction of animal species is playing an importantrole in the discussions of greenhouse warming impacts. Cereal crop yields havebeen studied by several authors, recently summarised by US NRC (2010). Theydepend on local warming (different from global average, cf. Figures 5.3 or 5.5),on changes in precipitation (Figures 5.4 or 5.6) and on soil carbon (Figure 5.7).Increased yields may arise due to more available CO2 for assimilation and inregions where the length of the growing season is a limiting factor due to thehigher temperatures possibly causing the growing season to become longer. Onthe other hand, the opposite may occur due to many plants growing quickly atelevated temperature but reaching lower grain yields, and due to heat and highevaporation damaging the plants. For global temperature increases of 2 1C(some 3 1C at high latitudes) and for cereals such as rice, the positive andnegative effects on yields may balance, but for corn and wheat, overall yielddecreases of the order of 20% can be expected. For some plants, a negativeyield effect will set in only if the warming exceeds some threshold. For soybeansin the USA, this threshold is around 2.5 1C warming (US NRC, 2010).

Figure 5.7 Simulated changes in equilibrium soil-stored carbon as a function oflatitude (units: 1012 g carbon per half degree latitude), with individualcontributions indicated (based upon Melillo et al., 1996).


The current anthropogenic greenhouse forcing, i.e. the net excess flow ofenergy into the atmosphere, taking into account anthropogenic effects since thelate 18th century, is estimated at 1.4 W m–2 as a balance between a twice aslarge greenhouse gas contribution and a negative contribution from sulfateaerosols (Meehl et al., 2007; see left panel in Figure 5.8). The latter is decreasingin some parts of the world, owing to emission control, notably for powerstations, but probably increasing in developing countries with high economicgrowth. The uncertainty in the total forcing is close to 1 W m–2, of whichnearly all comes from particulate matter emissions because the emission ofgreenhouse gases has been closely monitored during the recent one or twodecades.

The future increase in the concentration of CO2 and other greenhouse gases,together with a less certain stabilisation in emissions leading to the creation ofsulfate aerosols, as well as carbon particulate matter, is shown in Figure 5.8following the IPCC A1B scenario, which again is similar to the business-as-usual scenario (called IS92a) of the second IPCC assessment report (IPCC,1996). The forcing reaches some 4–5 W m–2 by the year 2050 and 6–7 W m–2 bythe year 2100. For the IS92a scenario the doubling of CO2 occurs around theyear 2060 with a forcing estimated at 4.4 W m–2. These estimates are sum-marized in Figure 5.8, together with the non-anthropogenic contributions frompresently observed variations in solar radiation (considered less uncertain in therecent IPCC report than earlier) and from volcanic activity (which exhibits veryirregular variations with time).

Figure 5.8 Components of present and future (geographically averaged) greenhouseforcing, with use of Forster et al. (2007), Meehl et al. (2007) and assuminga development based on the A1B emission scenario, which is similar to theIS92a scenario used earlier (IPCC, 1996; Kuemmel et al., 1997). The lar-gest uncertainty derives from estimating particulate matter emissions.

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It should be noted that it is not strictly allowed to make a summation over allanthropogenic forcing components, because of differences in geographic dis-tribution and in the lifetime of different greenhouse gases in the atmosphere.

Below, a number of important impact areas associated with global warmingare described, attempting to arrive at quantitative estimates of the damage thatwill follow as a consequence of scenarios such as the IPCC A1B emissionscenario. After that, the damage estimates will be presented in a life-cycleframework, allowing a discussion of the alternatives of laissez-faire, adaptationor mitigation approaches.

5.1.1 Food Production and Silviculture

As mentioned above, agriculture is likely to be affected both in a positive and anegative direction by global warming, but the optimism that these might canceleach other has faded away over the recent 5–10 years. The additional CO2 toassimilate will not offset the decreased yields caused by hotter growth seasonsand, additionally, insect attacks on crops will likely increase. There will be morewildfires, which will affect both forests and agricultural crops, and dry spellswill become deeper and more frequent and will put additional stress on watersupplies, both in regions currently producing food by use of natural rain andmoisture (see Ciais et al., 2005) and in areas of artificial irrigation, whichalready in many cases have reached the level where the ground water table islowered, signalling an unsustainable use of the irrigation technology. Warmer,drier climates will enhance this problem. Already, it has become necessary inseveral places to start using desalinated seawater for irrigation; in cases like thedry plains of interior Spain, this is currently done using fossil fuels and thuscreating a negative feed-back loop with more greenhouse gas emission, morewarming and then more demand for desalination.

In addition to global warming, gases such as ozone may have a direct effecton plant growth. Long et al. (2005) estimate that 0.1 ppm of ozone exposure for7 hours a day causes crop yields to decline by 20% for corn and rice, 40% forwheat and 50% for soybeans. Model calculations have identified someunderlying causes for yield changes, such as for example vapour pressurechanges in plant cells (Challinor and Wheeler, 2007). Frost duration alsoinfluences plant growth, as identified for spruce forest growth in Sweden(Rammig et al., 2010) and changes in oxygen content and salinity influenceplant growth in aquatic environments such as the Baltic Sea (Neumann, 2010).Combined effects on food crops or timber production thus require carefulmodelling on a regional scale, and it will be difficult to make globally validstatements. However, looking at the locations where agriculture or forestry iscurrently conducted on a large scale, and extrapolating to any foreseen newareas of activity (such as increased aquaculture), it should be possible to obtainan idea of the possible damage from climate change.

The amounts of reductions in harvest yields for cereal crops, vegetables,residues and forestry-derived biomass will need further scrutiny over the


coming years. Ranges of þ5% to –40% are too large for detailed planning, butthe examples mentioned indicate the beginning of a differentiated assessment,where advice could be given, e.g. to farmers, on the switch between crops thatmay avoid large negative effects.

If the global average yield reduction is say 15%, there will be an increase infood prices and possibly increased hunger problems. An economic assessmentwill put the immediate damage at the monetary value of the 15% lost, but theglobal economy will further suffer if the cost of the remaining 85% of harvestyield goes up. This of course points to the fragility of economic assessment:losing crops will increase prices and make the gross national products ofcountries with agricultural activities go up, a development often interpreted aspositive. However, the reality is still that the world will have greater difficulty infeeding a growing population.

While such damage costs are likely to be large, the cost of adaptation may beconsiderably smaller. If farmers shift to growing the crops with the leastnegative yield response to greenhouse warming, the global harvest reductionmay be kept at a low value. There may be a reduction in gastronomic foodquality, but it is also possible that the shifts in land zones suitable for growingparticular crops may preserve the variety of foods on a global level. Popula-tions preferring rice may have to import it from other regions, and so may thosepreferring rye or wheat. Again more detailed investigations are required. Oneissue is that to adapt to the dynamics of climate change will require a fairly highlevel of education of the farmers. This level is available in most highly devel-oped countries, but is to various degrees absent in countries with poor edu-cation, high percentages of illiterates and possibly with cultural traditionsmaking major shifts in food choices difficult to realise.

Finally, the mitigation option demands that injection of greenhouse gasesinto the atmosphere is stopped and the atmospheric concentration is thus keptbelow a certain level. The speed of replacing fossil fuels by renewable or nuclearenergy sources will determine at what level the concentration will stabilise andthus which fraction of the emission-induced negative effects that will remain.Whether mitigation is less costly than adaptation depends on the technologiesavailable in the two cases and their costs. Mitigation options will be the subjectof Chapter 8 and for the global situation particularly Section 8.2. Figure 5.9gives several examples of mitigation pathways.

Warming may provide more favourable conditions for plant diseases and forinsects damaging crops or trees. In a world where chemical pesticides areincreasingly seen as unacceptable, this problem may be seen as particularlysevere and as limiting the effort to create ecologically acceptable products fromagriculture and silviculture. Exactly how much damage that will ensue dependson human ingenuity in finding and developing new techniques for achievingplant stewardship. Extreme events such as floods or droughts, storms andhurricanes, earthquakes and volcanic eruptions can affect agriculture alongwith other types of damage. They will be discussed below in Section 5.1.2.

For silviculture, fires have always been an important element of naturalmaintenance, but they have in periods become an increasing issue due to man-

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initiated burning. The same holds for agriculture, through habits such asburning straw and stubs on the fields, a procedure that is currently beingreplaced by collection and use for energy generation in most developed coun-tries. As part of the extreme-events discussion in connection with greenhousewarming, the likelihood of more fires and more floods has been predicted andrecently also observed. Insurance companies talk about more than a doublingof such events over the recent 10–20 years, but they may in part be seeing anincreased practice of protecting investments by insuring against natural dis-asters (a possibility excluded in most earlier contracts). Even a 50% increase insuch extreme events over the next decades will have important economicimpacts on both human settlements and agriculture.

5.1.2 Extreme Events

The increasing frequencies of extreme events can have multiple impacts onagriculture, silviculture, settlements and industry, as well as on human lives andwell being. Figures 5.10 and 5.11 give an overview of the human deaths andother impacts on human societies caused by a selection of extreme events.Because of the irregular occurrence and magnitude of extreme events, the datahave been accumulated over a 15-year period, from 1991 to 2005.

It is seen that the current distribution of extreme events is quite unevenamong regions of the world, with poor countries typically affected more thanrich countries, at least for those impacts where technologies exist to reduce theimpact (building dykes against floods, implementing warning systems for

Figure 5.9 Per capita emissions of CO2 which will lead to climate stabilisation atvarious global average temperatures. Each curve corresponds to a miti-gation scenario with a certain strength of measures (Sørensen, 2008a).


Figure 5.10 The present numbers of deaths caused by various extreme events indifferent parts of the world. Data are accumulated from 1991 to 2005 andbased on CRED (2010). Categorisation of countries where the eventstook place is made by the United Nations organisation ISDR (2010).

Figure 5.11 The present numbers of people affected by various extreme events indifferent parts of the world. Data are accumulated from 1991 to 2005 andbased on CRED (2010). Categorisation of countries where the eventstook place is made by the United Nations organisation ISDR (2010).

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tsunamis, etc.). In these cases, diminishing impacts may be foreseen for thefuture, e.g. as a result of the tsunami warning system implemented in the IndianOcean region following the deaths and economic damage caused by the spec-tacular 2004 event. On the other hand, the expected rise in the frequency ofextreme events due to greenhouse warming will work in the opposite direction.

Looking now more closely at some of the extreme event types, Figures 5.12and 5.13 show the current impact of fires on mortality and disability in differentparts of the world, for the year 2002. If the global average incidence were

Figure 5.12 Deaths in 2002 attributed to fires, by country (WHO, 2004b). The globaltotal is 311 400 persons.

Figure 5.13 Disability-adjusted shortening of life (years, abbreviated as DALY) in2002 attributed to fires, by country (WHO, 2004b). The global total is11.5 million years.


augmented by 50% by 2050, the induced damage would be quite substantial:156 000 annual deaths and an additional commitment to nearly 6 million life-years lost, for fire-fighters and victims of smoke, injuries and burns from thefires occurring in a particular year. The WHO (2004b) relation between smokefrom fires and respiratory diseases is supported by time series of ambient smokeand hospital admission in countries with frequent forest fires, such as Australia(Hanigan, et al., 2008).

Floods constitute a substantial cause of death and dislocation, particularly inlow-latitude regions of the world. Figures 5.14 and 5.15 show the number of

Figure 5.14 Distribution of the total number of recorded deaths from January 1985to September 2010 attributed to flooding events (based on data fromDartmouth Flood Observatory, 2010).

Figure 5.15 Distributionof the total number of people displaced from1985 toSeptember2010 due to flooding events (Dartmouth Flood Observatory, 2010).

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deaths and people forced to relocate due to floods, during the period 1985–2010.

Extreme flooding events have increased in magnitude and frequency duringthe period covered in Figures 5.14 and 5.15, as shown in Figure 5.16. There isan increase in both medium and large events during the period that may beassociated with climate change over the past 25 years. Linear extrapolation ofthe roughly fourfold increase in Figure 5.16 to 2050 or 2100 would predict avery large impact both in terms of lives and social disruption (including thehealth problems associated with sudden displacement of people, particularly incountries with limited economic means). In 2010, monsoon rains caused theIndus river to flood large areas in southern Pakistan (Figure 5.17), causingserious damage and massive displacement of people.

The occurrence of droughts can be monitored from satellites throughquantities such as vegetation cover and aerosol optical thickness. Given data onprecipitation and temperature, modelling of the moisture in soil and in variouslevels of the atmosphere can be carried out, as it routinely is in climate models.This also allows prediction of future droughts and wetness anomalies for dif-ferent assumed emission scenarios. There would be, for example, prolongeddroughts where a region is drier than normal for the geographical location andthe time of the year, and there would be shorter excursions perhaps moreworthy of being called extreme events. However, the damage associated withdroughts, including impacts on health, agriculture, animal life and ecology, and

Figure 5.16 Development in the number of flooding events globally from January1985 to September 2010. Threshold sizes are indicated by the logarithmicindex M constructed from the product of flood severity, duration andarea affected (based on data from Dartmouth Flood Observatory, 2010).


on the fire risk, will often become aggravated along with any prolongation ofthe episodes, making it natural to name an unusually long drought an extremeevent.

Figures 5.18 and 5.19 illustrate the current (2005) occurrences of extra dryand extra wet periods by giving the Palmer Drought Severity Index (Palmer,1965). Palmer used a simple moisture model to calculate deviations fromaverage dryness and wetness on the basis of temperature and precipitationrecords. The index is expressed as a number between –15 and þ15, wherepositive values represent excess wetness and negative values excess dryness. Allthe indices express deviations from the average conditions at the particular timeand place considered.

The overview in Figures 5.10 and 5.11 shows that windstorms and tropicalcyclones (comprising tropical storms and hurricanes or typhoons) constitute amajor cause of death as well as physical and economic damage in both the more

(a)

(b)

Figure 5.17 Area north of Hyderabad in Pakistan on 31 July 2009 (a) and sameduring flooding event on 19 August 2010 (b). Landsat-5 satellite imagesfrom NASA Earth Observatory (NASA, 2010; by general permission).

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and the less developed parts of the world. These are also extreme events that aresuspected of becoming more frequent and more violent as greenhouse warmingprogresses.

Figures 5.20 and 5.21 show the number of six-hour periods with wind speedsestimated at a height of 10 m to be over 17 m s–1 (sometimes taken as theminimum for a tropical storm) and over 24.4 m s–1 (the classical meteorologicalthreshold for using the word ‘‘storm’’) during a month of the year 2000 withhighest wind speeds (which is October within and near the North Americancontinent, January within and around the European continent, including theNorth Atlantic Ocean to Greenland). The data employed are ‘‘blended data’’,where the ocean part is derived from satellite scatterometer measurements bythe satellite QuickSCAT that overflows a particular location at twelve-hourintervals (Milliff et al., 1999) and the continental part is derived from land-

Figure 5.18 Palmer’s Drought Severity Index for February 2005. Negative values(drier than normal) are shown in the upper panel, positive values (wetterthan normal) in the lower panel (Dai et al., 2004; NCAR, 2010).


based observations made consistent (to avoid effects of peculiar placement ofcertain meteorological masts) by running a global circulation model with themeasured values as input (Kalnay et al., 1996). The circulation model is alsoused to interpolate between the satellite passage times, so that the entire dataset can be assessed at six-hour intervals and yet retain the higher Fouriercomponents present in the satellite radar data but not in the circulation models.This means that the data depicted are not 6-hour averages but represent short-term values centred at the satellite passage times. The even higher wind speedsin gusts are not captured in these data. The blended data (NCAR, 2006) aretaken as representing winds at a height of 10 m, without the scaling that hasearlier been added in order to use these data for estimating wind turbine output(see the discussion of effective height in Sørensen, 2008c).

Figure 5.19 Palmer’s Drought Severity Index for August 2005. Negative values (drierthan normal) are shown in the upper panel, positive values (wetter thannormal) in the lower panel (Dai et al., 2004; NCAR, 2010).

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It is seen that, as expected, the largest extremes are found over oceans, butthere are a number of instances during the months examined where coastalareas experience over 17 m s–1 winds and more rarely over 24.4 m s–1. Thesesituations are more frequent in Northern Europe than anywhere on the NorthAmerican continent (except for the east coast of Greenland), but in both casesthe frequency drops when moving away from the months of January andOctober, respectively.

Figure 5.20 Extreme winds in North America during October 2000. Based ondata available at 6-h intervals (NCAR, 2006), the number of instancesis shown where the wind speed exceeds 17 m s–1 (left panel) or24.4 m s–1 (right panel). For months other than October the numbers aresmaller.


Following the number of windstorm events over a period of decades,Emanuel (2005) found an increase in severity that may be attributed togreenhouse warming. This has been contested, e.g. by Pielke et al. (2008): theylooked at economic impacts of storms within the USA and found a declineduring the 20th century. However, this type of argument is unlikely to be valid,partly because the impacts on 3–4% of the world’s population can hardly tellmuch about the global trend, and further because the storm events onlymarginally touch continental areas, as seen in Figures 5.20 and 5.21. Thus,although damage is inflicted there because of high population density, the mainindicator of a growth in severity would necessarily have to come from oceaniclocations. On top of these arguments there is reasonable doubt as to whethereconomic valuations for different periods during the 20th century can mean-ingfully be compared, despite attempts to correct for monetary inflation. Theeconomic cost of a stormy event depends on the engineering quality of housesand other structures, which has certainly not stayed constant for such a longtime, and it also depends on settlement patterns, building legislation andinsurance practices, all of which make a cross-century comparison very diffi-cult, even within a single country.

5.1.3 Direct Health Impacts of Climate Change

Extreme temperatures can affect human survival, with special affinity to indi-viduals with particular dispositions, such as coronary trouble. The risk

Figure 5.21 Extreme winds in Europe during January 2000. Based on data availableat 6-h intervals (NCAR, 2006), the number of instances is shown wherethe wind speed exceeds 17 m s–1 (left panel) or 24.4 m s–1 (right panel).For months other than January the numbers are smaller.

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associated with severe frost and its dependence on clothes and shelter is wellknown, and so is the one associated with heat waves, which are supposed tobecome more frequent and/or prolonged in a warmer climate induced bygreenhouse gas emissions.

In the economic evaluation, not only health impacts are important but alsothe impacts on agriculture covered above and the cost of heating and coolingbuildings. A number of studies for the USA conclude that the additional coolingrequired due to greenhouse warming is non-linear but in the range of 9–15% foroffice buildings and 5–20% for residential buildings, for the first degree (K) ofwarming (US NRC, 2010). Clearly, such estimates and the ranges quoteddepend on the standard of the houses in question. In most US locations it ispossible to build energy-efficient houses that require no heating in winter and nocooling in summer (Sørensen, 2007, 2008b). The techniques involved includeinsulation, evaporative cooling ducts, overhangs and careful placement ofwindows. However, many current-stock buildings have a far inferior standardcompared with state-of-the-art architecture. In a similar study, Wang et al.(2010) found excessive energy use in Australia for current best-standard build-ings, as a result of the temperature increases suggested by 2010 for the standardIPCC emission scenarios, amounting to between –26% and þ101%. The lowestis in southern areas with a heating demand, the highest in the central part of thecontinent dominated by cooling demands.

As regards exceptional temperature excursions, the US NRC (2010) presents aUS heat wave duration index defined as the average length increase (in days) ofevents. At 2 1C average warming the length index increases by about 8 days in thesouthern US and by about 4 days in the northern states. The WHO (2004a) havesurveyed the impacts of heat waves and epidemiological studies during recentheat wave incidences have been reviewed by Basu (2009). It is noted that the veryyoung (below 4 years) and the old (a gradual rise is accelerated above age 75) aremost at risk, and that vulnerable groups have dispositions for respiratory, car-diovascular disease and heart failure, myocardial infarction and cerebrovascularconditions. A general relation between maximum daily temperature and mor-tality has been noted both in Europe and the USA, as shown in Figure 5.22. It isinteresting that the two curves are displaced relative to each other, with Madridhaving a higher heat-threshold than the average over several European sites. Onthe other hand, the inhabitants of Madrid also suffer health problems at coldtemperatures above those causing trouble in other parts of Europe. Regionalstudies have found several details of heat-related health impacts. For example,Checkley et al. (2000) found a doubling of diarrhoea cases in Lima (Peru) duringan exceptional heat episode in 1997–98 and Ishigami et al. (2008) find 7–20%elevated mortality per degree warming in a study comprising Budapest, Londonand Milan. Almeida et al. (2010) found about 2% increase in mortality perdegree in Lisbon and Oporto.

As suggested by Figure 5.22, the minimummortality in different locations doesnot occur at the same temperature. This suggests an adaptation of populations toexisting differences in temperature regimes. The additional effect of globalwarming must therefore be evaluated on a regional basis, and the possibility


should be kept in mind that a further adaptation may take place over a period ofmore than 100 years where elevated temperatures due to fossil fuel combustionwill remain. Because of the valley shape of the curves in Figure 5.22, not only theextra mortality at high maximum daily temperatures should be considered, butalso the reducedmortality caused bywarming at the low-temperature end. In fact,the number of people affected in a positive way may be larger than those affectedin a negative way. There could be subtleties in such a conclusion, because thedynamics of heat spells and cold spells may affect people differently. Donaldsen etal. (2003) found that despite an increase in average temperature between 1971 and1997, overall mortality decreased in selected countries over the same period.

In a life-cycle analysis, it would therefore appear best to divide the directheating impacts on health into impacts of an altered mean temperature andhealth impacts deriving from larger and more frequent temperature excursions,‘‘extremes’’. Human populations can adapt to changes in mean temperature,both by technical solutions such as new building construction principles andactive cooling/heating, and to some extent by biological adaptation. It is lesslikely that the latter type of adaptation can be applied to extreme events.

In view of the complex mortality pattern induced by relations such as the oneshown in Figure 5.22, the issue will be explored in more detail, using the geo-graphical modelling methods to pinpoint the distribution of mortality increasedue to more heat waves and the decrease that may be due to less cold spells,

Figure 5.22 Relationship between maximum daily temperature and mortality, basedon European data fromWHO (2004a) that covers the range of –5 to þ301C, and from Diaz and Santiago (2003), who cover the additional tem-perature range of þ30 to þ42 1C, based on data for Madrid .

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both as regards size as well as duration. Figure 5.23 shows the increase inmaximum daily temperature according to the MIHR model used above foraverage temperatures and pressures, for the period 2045–2065 relative to pre-industrial times. These increases are not necessarily representing heat waves.Their magnitude and geographical distribution are very similar to those for theaverage temperatures, as shown in Figures 5.5 and 5.6. Still, the relationbetween daily maximum temperatures and death (of any assigned cause) illu-strated in Figure 5.22 implies that the situation around year 2055 will causeadditional deaths that would not have occurred without global warming, butprobably avoid other ones.

Figure 5.23 Maximum daily temperatures for the years 2045–2065 of the A1Bemission scenario, relative to the pre-industrial ones, averaged overJanuary (upper panel) or over July (lower panel). Data from the MIHRmodel (Hasumi and Emori, 2004) have been used.


To assess this additional mortality, Figure 5.24 shows the geographicaldistribution of annual excess heat-related deaths (described by a factor multi-plying the average death rate) derived from the global climate change from pre-industrial to year 2055 A1B conditions. They are calculated by subtracting pre-industrial heat-related deaths from those for the scenario year 2055, based onthe smoothed version of the mortality factor as a function of the daily max-imum temperature shown in Figure 5.25, constructed with use of the two curvesin Figure 5.22. Figure 5.24 thus shows the increased probability of experiencinga heat-related death as a function of geographical location, but not consideringthe number of people living at that particular location. The quantity shown isthe change in the factor multiplying the death rate that would otherwise bevalid for the geographical place considered. The geographical differences inadaptation to heat in different populations (as indicated by the differencebetween the two curves in Figure 5.22) are not considered, and neither is thepossible additional adaptation taking place as the greenhouse warming pro-gresses. It is thus clear that only a first indication of the geographical change inheat-related deaths can be achieved.

The effect shown in Figure 5.24 is striking, owing to the fact that all thenegative impacts are in areas not too far from the Equator, including Africa,the Middle East, India, South-East Asia, South America and Australia, whilethe positive effects of warming pertains to the rest of the world: North America,Europe, Eastern former Soviet Union, Japan, China, a small western coastal

Figure 5.24 Annually averaged changes in heat-related mortality factor, from pre-industrial times to 2045–2065, based on daily maximum temperatures forthe IPCCA1B run of theMIHRmodel (Hasumi and Emori, 2004) and therelativemortality factors shown inFigure 5.25. If, for example, the averagerelative mortality without greenhouse warming is m (in the interval[�1.5,1.5]), then an indicated factor change of 0.4 to year 2055means thatthe mortality in 2055 will be mþ0.4, while a factor change of –0.4 wouldmake the 2055 mortality m�0.4.

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strip in South America and New Zealand. This warrants a closer look at theseasonal variations, which are presented in Figure 5.26a–l for each month ofthe year. It is seen that significant variations take place over the year, and thatfor some locations (such as middle and southern Europe) the annual averageswill hide cancellations between positive and negative effects.

Now, considering the actual number of people affected, the change in themortality factor describing heat-related death is multiplied by the number ofpeople that would have died at a particular location in the absence of green-house warming. This is done by multiplying the projected year-2050 populationby first the current death rate and then by the mortality factor describing thegreenhouse warming change. The resulting number of excess deaths shown inFigures 5.27a and 5.27b is thus taken as:

Heat-related deaths in a given area¼ (local population density)� (area size)� (current death rate in the area)� (change in relative mortality factor

due to greenhouse warming)

The area entering into the geographical information system (GIS) calcula-tion is a grid area, which for the MIHR model is equal to a latitude increment

Figure 5.25 Relationship between maximum daily temperature and mortality,derived from Figures 5.22 and used in estimating global mortalitychange. The areas below and above ‘‘1’’ are not and should not beidentical. The unity is chosen so that the present average mortality on theSpanish highland plateau equals the observed one. For other locationsthis is assumed to approximately also give the correct impact of low orhigh daily maximum temperatures, neglecting any differences in adap-tation relative to the one prevailing in Spain.


Figure 5.26a–c Changes in heat-related mortality factor, from pre-industrial times to2045–2065, for January (top), February (middle) and March (bottom).

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Figure 5.26d–f Changes in heat-related mortality factor, from pre-industrial times to2045–2065, for April (top), May (middle) and June (bottom).


Figure 5.26g–i Changes in heat-related mortality factor, from pre-industrial times to2045–2065, for July (top), August (middle) and September (bottom).

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Figure 5.26j–l Changes in heat-related mortality factor, from pre-industrial times to2045–2065, for October (top), November (middle) and December(bottom). Remarks and sources mentioned in caption to Figure 5.24.


of 1.1212831 and a longitude increment of 1.1251. This implies that the grid areaat the latitude j is:

area size¼ 15610.6� cos(j) km2

The latitude decrease in unit cell area is important for conveying a realisticdistribution of effects in presentations such as Figure 5.27. The local populationdensity for the mid-21st century is similar to that of a previous model (Sørensenand Meibom, 2000) based on the middle of three UN projections for 2050(CIESIN, 1997; UN, 1997, 2010). The total 2050 population of that model is9.3� 109, which is higher than the 8.7� 109 of the IPCC A1B emission scenario

Figure 5.27 Additional mortality (per grid cell of 1.11� 1.11) caused by greenhousewarming from pre-industrial times to around 2055, constructed fromexcess mortality factors (Figure 5.24) and mid-21st century populationdistributions. Upper panel: mortality reductions (total: 2.2 million peryear). Lower panel: mortality increases (total: 1.6 million per year).

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(but perhaps more realistic, according to the remarks made at the beginning ofthis chapter, at least where there are no major wars or other setbacks). TheIPCC scenario is not made on a geographical area-base and thus cannot beused directly for the type of study undertaken here.

The Sørensen–Meibom model used takes actual population data and projectsthe future development on the basis of demographic and economic development,assuming also a shift in lifestyles halting the previous trend towards larger andlarger population densities in city centres. Instead, city activities are assumedspreading to neighbouring grid cells once the population density exceeds 5000km–2. This spread is in good agreement with average actual developments, butwhether the density concentration associated with prestigious increases in theheight of high-rise buildings will stop remains to be seen.

As the temperatures in city centres can be 1–2 1C higher than that outsidecities, this may have an impact on the mortality estimates. The current deathrates used are national figures given by WRI (2008). Although the mortalitydependence on temperature in Figure 5.25 is used universally, overestimatingthe mortality factor is not very likely because the curve is a lower envelope ofthe measured data in Figure 5.22. The asymmetric rise, with a steep rise attemperatures above 37 1C, is also considered a global phenomenon, because itsignals the difficulty of some individuals to adapt to ambient temperaturesabove normal body temperature. Above this limiting temperature, the humanbody is supposed to maintain its heat balance exclusively through exchange oflatent rather than sensible heat, a functionality that may be reduced in someindividuals. One should also remark that curves such as those shown in Figures5.22 and 5.25 are derived on a purely statistical basis, using the maximumtemperatures prevailing in the period surrounding the time when a personactually dies, rather than on some doctor’s estimated cause of death as foundon death certificates. Avoiding use of concrete death certificates in assigningcause of death is considered an important improvement, and the relationshipfound on the basis of all deaths distributed on daily maximum temperatures islikely to have a much more general validity.

The results displayed in Figures 5.27a and 5.27b show that, around 2055,some 3 million people are affected each year by the climate change broughtabout by the greenhouse gas emissions and changes in area use. Of these,2.2� 106 y–1 in the northern part of the globe (plus New Zealand, the Andesand southern Chile) that would have died without the greenhouse warming dosurvive, and 1.6� 106 y–1 in the equatorial and southern part of the globe thatwould otherwise have survived now die. This is one of several vivid indicationsthat the populations most likely to suffer from greenhouse warming are notthose contributing most to creating the problem.

Bosello et al. (2006) have looked at health impacts of warming based on dataextrapolated from specific investigations and they found for 2050 a decrease ofdeaths from cardiovascular diseases in all regions of the world, totalling1.76� 106, an increase of respiratory diseases causing death in all regions,totalling 0.36� 106, and similarly of deaths from diarrhoea, totalling0.49� 106. The order of magnitude thus agrees with the present study.


However, the details appear quite different. The geographical distributioncannot be compared, because Bosello et al. (2006) use aggregated regions with,for example, India and China lumped together, and they have negative overallimpacts only for the Middle East and the ‘‘rest of the world’’, comprising whatis left after detailing the ‘‘Annex 1’’ countries (UN jargon for countries clas-sified as industrialized or economies in transition). Earlier studies of greenhousewarming impacts by economists concentrated on impacts occurring in the USA(Cline, 1992; Frankhauser, 1995; Nordhaus, 1994; Tol, 1995).

5.1.4 Vector-borne Diseases

A number of diseases caused by viruses or other microbes are transmitted byinsects, called ‘‘vectors’’, with typical ones being mosquitoes. The Plasmodiumfalciparum parasite and anopheline mosquito varieties involved in the malariatransmission cycle are all sensitive to variations in temperature and humidity,and regions with strong seasonality or dryness in periods of the year crucial formosquito breeding may experience considerable diminishment of malariaincidence. Other factors are of course lifestyle and technical means such asmosquito nets over beds or wire netting on windows and doors. Models havebeen constructed for describing the distribution and intensity of malariatransmission under assumptions of various greenhouse warming scenarios.Tanser et al. (2003) found that, for the three IPCC emission scenarios that theystudied, the affected areas in Africa would remain nearly unchanged, but theperson exposure would by the year 2055 have increased by 8–18% due to longerperiods of the year experiencing severe human risk.

A similar global study by van Lieshout et al. (2004), using four IPCCemission scenarios, found that by 2055 the population at risk in the differentscenarios would change from 35 million less to 76 million more than at present(the present population at risk being about 490 million). One might assume(although this could be criticized, see Thomas and Hay, 2005) that the numberof people affected by and dying from malaria will increase by similar numbers,from the present level of about 0.9 million deaths annually out of 173 millionreported cases (WHO, 2004b, 2010). Many things could change that. It is wellknown that malaria was common in most of Europe, Asia and South America(except the southern part), Central America and the east coast of the USA bythe late 19th century, but had disappeared in several of these regions at thesame time as wealth had increased. Several drug treatments bring some relief,but only for a limited period, and use of pesticides to eradicate mosquitoes hasnot been effective either, in addition to the side effects entailed. However, thereis hope that this will change as a better understanding of the genetic make-up ofthe parasite and the vectors is gained. The development in conditions formosquito transmission could be followed by satellite (Rogers et al., 2009). Theeffects of detailed timing of malaria vector development in Madagascar havebeen evoked as suggesting a need for refinement of the models employed in theforecast of incidence under climate change (Bouma, 2003). A recent articlesuggests that even most people normally against loss of genetic diversity would

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be happy to simply see mosquitoes becoming totally extinct (Fang, 2010).Interesting, but hardly realistic!

Current (2002) deaths and disability (taken as DALYs, i.e. life-shortening inyears plus years not allowing a normal, meaningful life) caused by malaria areshown in Figures 5.28 and 5.29 (WHO, 2004b).

There are other parasitic diseases, although with smaller current death tollsthan malaria. Among these, the soil-transmitted helminthiases may showsensitivity to climate change (Weaver et al., 2010). The same is the case fordengue fever, although the number of people affected globally is more modest

Figure 5.28 Malaria deaths in 2002, in thousands, based on countrywide statisticscollected by WHO (2004b).

Figure 5.29 Malaria disability-adjusted shortening of life, in 103 years (DALY) basedon 2002 countrywide statistics collected by WHO (2004b).


(Hales et al., 2002). The current levels of deaths and DALYs for dengue feverare illustrated in Figure 5.30, based on WHO statistics for 2002. One may notethat the ratio of death to disability and life-shortening is smaller in SouthAmerica than in India.

A number of parasitic diseases particular to the tropical regions aresummarized under the name ‘‘tropical-cluster diseases’’. They include schisto-somiasis (bilharziasis), trypanosomiasis and Chagas disease (sleeping sick-nesses), leishmaniasis (black fever), lymphatic filariasis (elephantiasis) andonchocerciasis (river blindness). The current distribution of these diseases overlow-latitude regions is fairly uneven, as shown in Figures 5.31–5.35 for deathtolls. The DALYs generally have a similar distribution and only a summary isgiven (Figure 5.36).

Figure 5.30 Dengue fever deaths in 2002 (upper panel) and disability-adjustedshortening of life (DALY, lower panel) based on WHO (2004b).

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The country distribution of schistosomiasis shows large impacts in Chinaand certain African countries, while India has the largest incidence ofleishmaniasis (Figures 5.31 and 5.32). The sleeping sicknesses are partly inAfrica(trypanosomiasis, Figure 5.33) and partly in South America (Chagas disease,Figure 5.34),with a strong concentration inBrazil. Themapof all tropical-clusterdiseases (Figure 5.35) misses most of these differences. The life-shortening anddisability data (Figure 5.36) for the cluster diseases have a slightly different dis-tribution compared to that of deaths, perhaps due to differences in medicaltreatment.

Figure 5.31 Country distribution of schistosomiasis deaths in 2002, based on WHO(2004b).

Figure 5.32 Country distribution of leishmaniasis deaths in 2002, based on WHO(2004b).


The development of parasitic diseases over time is affected both by climatechange and by social factors such as population increase, life conditions, accessto medical remedies and prevention technologies. WHO has made a cautiousprojection of what they call a ‘‘baseline scenario’’ for the period 2008–2030(Mathers and Loncar, 2006). By ‘‘baseline’’ is meant that special action isconsidered necessary in order to substantially deviate from this projection.Figures 5.37 and 5.38 show the projections of deaths and DALYs for a numberof diseases considered in this section.

Figure 5.33 Country distribution of trypanosomiasis deaths in 2002, based on WHO(2004b).

Figure 5.34 Country distribution of deaths from Chagas disease in 2002, based onWHO (2004b).

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Because of the many factors involved in determining the future impact oftropical diseases on human populations, each with considerable uncertainty, itis very difficult to make statements on the fraction of deaths and disabilitiesattributable to greenhouse warming. The only approach having some merit isthe purely theoretical one of studying the habitat of mosquitoes and parasites,including genetic and epidemic models, along with geographical dispersalmodelling, in order to determine which impacts may be considered climate

Figure 5.35 Country distribution of deaths in 2002 from all tropical-cluster diseases(those of Figures 5.31–5.34 plus lymphatic filariasis and onchocerciasis),based on WHO (2004b).

Figure 5.36 Country distribution of DALYs in 2002 for all tropical-cluster diseases,based on WHO (2004b).


Figure 5.37 UN projection of baseline global deaths from parasitic diseases (based onWHO, 2008).

Figure 5.38 UN projection of baseline global DALYs from parasitic diseases (basedon WHO, 2008). Whereas lymphatic filariasis claims less than 400 annualdeaths, its contribution to DALY is substantial.

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related. As mentioned, such modelling including detailed genetic insights (suchas the recent characterisation of the Plasmodium falciparum metabolic pro-cesses by Olszewski et al., 2010) is forthcoming in the case of the mostimportant parasitic disease, malaria.

Similar progress is hoped for in the medical treatment of humans carryingmalaria infections, where the setback caused by resistance against the medi-cations used earlier (such as quinine, chloroquine and mefloquine) may belifted, e.g. by the development of artemisinin-based drugs beyond their originfrom folk-medicine sweet wormwood plant extracts used in China over 1000years ago (van Noorden, 2010). Naturally, concern over mutations that wouldenable Plasmodium falciparum to develop resistance to these drugs, if they areused more intensely than today, has been expressed.

5.1.5 Ecosystem Impacts

The vegetation zones where specific ranges of plants are favoured and wherespecific species of animals can survive have an evident dependence on climate.Changes in temperature, water and nutrient cycles implied by currently usedclimate models can move vegetation zones by several hundred kilometres. Newkinds of plants may take over natural environments and the survival of theexisting type of fauna will depend on the adaptability of the species involved.Different kinds of animals may find new refuges, if they are capable ofmigrating the distance to the new location of their preferred environment. Themap in Figure 5.39 shows distances to the nearest location that by the year 2100are likely to have a temperature regime similar to the original one in the 1960s.Distances of the order of 1000 km are seen to be involved in many regions.Although natural migration in response to climate variations have certainlytaken place in the past, it is by no means certain that it will be possible in a

Figure 5.39 Distance animals would have had to migrate by the year 2100 in order tofind a cool refuge with the temperatures their species were accustomed toduring the 1960s (US NRC, 2000; based on Wright et al., 2009).


world where human settlements are increasingly present and blocking passagefor many types of animal species.

One current concern is algal growth in near-shore waters. Such growth isinfluenced by temperatures and also by nutrients reaching the oceans fromstreams and rivers receiving surplus nutrients as a result of poor agriculturalpractices. Algae colonies may deprive other species of oxygen and some algalbloom episodes are directly harmful by poisoning edible shellfish and thusinfluencing human health (Kite-Powell et al., 2008). The culprits may in somecases be cyanobacterial toxins causing skin rashes and gastrointestinal,respiratory or allergic reactions (Stewart et al., 2006).

Biota including fauna may also be influenced by physical changes induced byglobal warming and the associated anthropogenic activities, such as changes intropospheric ozone content and increased or reduced particulate emissions ofvarious particle sizes (Doherty et al., 2009; Bell et al., 2008).

The environmental changes that may follow climate impacts further have anumber of more subtle effects, e.g. for hibernating animal species or speciesfor which body size has an influence on survival. The latter could be both apositive and a negative correlation with body mass. Dynamical models cou-pling evolutionary and ecosystem models are coming into use for exploringsuch issues (e.g. Ozgul et al., 2010). This option has already been in use forthe case of insect vectors in tropical regions, as discussed in Section 5.1.4, butit also has applications for insects in other environments (Netherer andSchopf, 2010).

5.1.6 Choice of Impact Valuation Methodology

In Section 3.2.1 a discussion was made of the valuation to use for the occur-rence of an extra death in life-cycle assessments. The value of 2.6 million h usedby a major study under the European Commission Framework Programmes(ETSU/IER, 1995) was accepted as being the correct order of magnitude forsomebody in the developed world killed in connection with impacts from anindustrial activity that the victim had no power to avoid (as opposed to con-scious risk-taking by individuals).

The ExternE project also valued non-fatal impacts such as injuries, diseasesand inconveniences. All the monetary values used in that study are given in Table5.1. For all the energy system assessments actually made by ExternE, themonetary impacts were totally dominated by the fatalities. If one tries to use theExternE assumptions to calculate the cost of one DALY, one obtains values inthe range of h 22 000–800 000, the lower limit based on 365 days of ‘‘activityrestrictions’’, the upper limit on hospitalisation, assuming the average time spentat the hospital for the number quoted by ExternE to be three days. Clearly, thesenumbers are based on average salaries lost plus added costs of hospital beds andpersonnel, without any compensation for suffering and losing meaningful days oryears of life, impacts that the DALYs claim have to be included.

156 Chapter 5

The DALY concept was first introduced by the World Bank (1993) and soonaccepted by United Nations organisations such as the WHO for use in studieslike the ones described above in Section 5.1.4. In their construction of DALYsfrom country data, these organisations employ a 3% discounting factor, sup-posed to reflect that an individual would value a year’s shortening of life lowerif it is likely to be postponed by some years (Mathers et al., 2006). It is ques-tionable whether such factors should in all cases be included into numbers fornational or worldwide assessments of the burden of negative impacts (Arnesonand Nord, 1999; Sørensen, 2010, Chapter 7).

DALYs have been employed in the evaluation of a number of concreteprojects in the developing world, using the expense involved in avoiding oneDALY as a success criterion. In concrete sanitation, pollution reduction andhealth related projects, the cost to the aid organisation of saving a life oravoiding a DALY presently range from one to a few hundred US dollars(Hanrahan et al., 2007). However, this does not say anything relevant for thevaluation of life or DALYs themselves, of course, but may be useful in com-paring different proposed interventions.

The valuation of deaths and DALYs to be used in specific studies describedin the following are given in Table 5.2. For death, the ‘‘European standards’’columns use the same value as the one adopted by the ExternE study, whichinvolved on average a half-life lost at typical European salaries plus an addi-tional amount of slightly lower size reflecting a fairly generous allowance fornon-work types of value (e.g. care and inspiration from grandparents tograndchildren). Dividing the half-life values by 40, an estimate of the value of aDALY is obtained, taking into account the same work and non-work dis-tribution of values accorded to human lives. The value of DALYs given in the‘‘European standards’’ columns of Table 5.2 is within the range derived abovefrom the ExternE assumption, and by adding up one obtains the same totals asone sudden death. The DALY can in this way be claimed to include non-salarytypes of benefits of a life.

It should be stressed that these valuations of life and health do not involveethical judgement but simply try to establish a way for decision makers in

Table 5.1 Valuation assumption used in the ExternE study (ETSU/Metronomica, 1995; European Commission, 1995); cf. Section3.2.1.

Health effect h US $

Mortality (SVL) 2 600 000 3 250 000Respiratory hospital admission 6600 8250Emergency room visits 186 233Bronchitis 138 173One day activity restricted 62 78Asthma attack 31 39One day with symptoms 6 8


society to compare different actions and different solutions on a fairly rationalbasis.

In the less affluent parts of the world, economists advocating inequality as adriver of competition have been happy to reduce the value of life by the averageratio of GNP creation, i.e. according a 100 times lesser value of life to a persononly capable of contributing 1/100 as much to the global economy as hiscounterpart in the most industrious parts of the world. Many observers wouldfind this point of view morally unacceptable, but the proponents would claimthat it reflects current reality. It is included in the rightmost column of Table5.2. The factor of 100 does not reflect the most extreme high or low GNPs percapita (such as 200 000 US $ y–1 cap.–1 in Monaco or 160 US $ y–1 cap.–1 inBurundi), but is rather based on an average of some 50 000 US $ for several EUcountries and 500 $ y–1 cap.–1 for countries such as Tanzania, Uganda, Nepalor Haiti for 2009 (Wikipedia, 2010). The USA GNP value of 46 000 $ y–1 cap.–1

is not used, because it hides an extremely large disparity between members ofthe US society and because the US economy is dominated by internal marketsand therefore the exchange ratio of the US $ towards major currencies isextremely volatile.

In the middle column of Table 5.2, a more modest view is reflected. It saysthat ordinary currency exchange rates do not necessarily reflect the usefulnessof a given sum of money in different parts of the world, e.g. due to powerrelations or the lack of interest in foreign trade by some governments, andthat therefore one should use purchasing power parity (PPP) as a basis forcomparing different countries. In other words, if a certain sum of money in alocal currency enables the bearer to purchase what in the European Unionwould cost three times as much, then a three times lower value (here expressedin h) would buy the same damage compensation. The purchasing power parityfactors translating local currencies into h or US $ presently range from 1.5 to3 (Wikipedia, 2010); a factor of 2.5, typical of many countries in the parts of

Table 5.2 Various valuation assumptions used in several of the LCA studiespresented in the following chapters.

Least developeda

Valuation method European standards PPP adjusted GDP adjusted

Health effect US $ h h hInduced death (SVL) 3 250 000 2 600 000 1 040 000 26 000Disability-adjustedlife-shorteningin years (DALY)

81 250 65 000 26 000 650

aUsing a purchasing power parity (PPP) adjustment by a factor of 2.5 relative to European stan-dards of salaries and market prices for consumer goods. The GDP adjustment is made by scalingthe valuation by an average gross domestic product ratio of 100, the approximate average ratiofound between central African and European Union countries (Wikipedia, 2010). The purpose ofpresenting European and least-developed valuations is to provide practical upper and lowerbounds for LCA calculations, without including the absolute highs or lows for particularindividuals.

158 Chapter 5

the world with an average activity level of around 1000 US $ per capita, hasbeen used in Table 5.2.

5.1.7 Overall Valuation of Greenhouse Warming Impacts

The earlier work of Kuemmel et al. (1997) made a first tentative overallassessment of greenhouse warming impacts, based upon the impact analysis inphysical terms made in the IPCC Second Assessment Report (IPCC, 1996) andusing the IPCC (1992) reference scenario assuming a business-as-usual increasein energy consumption and a doubling of CO2. Because the climate models usedin the Second IPCC Assessment Report did not include cooling by sulfateaerosols, impacts would possibly have been overestimated. In any case,uncertainties in determining the warming impacts on future societies probablyovershadow many details in the basic climate modelling.

The current generation of climate models is substantially improved, but thescenarios for future emissions are still both primitive and likely biased, asdiscussed in the opening pages of Section 5.1, and the impacts evaluations,covered in Sections 5.1.1–5.1.5, cast doubt on many of the estimates madeearlier, while certainly not being without substantial uncertainty themselves. Itis on this foundation that a new valuation of greenhouse warming is herepresented, not pretending to be very accurate, not pretending to be complete,and in any case leaving key parameters such as the economic ones from Section5.1.6 to be discussed by the user. The user would here come from the group ofpolitical decision makers or those trying to influence the direction of policy,from concerned scientists over social justice and environmental protectiongroups to industry lobbyists or just managers wanting to know how thedirection of change will influence their business.

Although neither emission scenarios nor the magnitude of impacts are likelyto produce a smooth development of greenhouse warming costs through the21st century or beyond, the 2045–2065 climate models will be used as a basis forthe assessment; a multiplication by 100 will indicate the rough level of impactsfor the entire next century. Table 5.3 summarises the findings.

The valuation of greenhouse warming impacts made in Table 5.3 providesthree columns of estimates, corresponding to the three evaluation methods ofTable 5.2: ‘‘European standards’’ in line with the EU assessments, ‘‘PPPadjusted’’ correcting for different purchasing power of a given sum of money inother regions of the world, and ‘‘GDP adjusted’’ scaling the impact valuationaccording to the average GDP per capita in different parts of the world (aprocedure perhaps realistic, but certainly immoral).

The first entry in Table 5.3 concerns agricultural production. The 15%decline predicted in Section 5.1.1 before adaptation is assumed, e.g. throughmechanisms of higher food prices, to lead to a change in crop mix marketed andin consequence less that 15% negative impact on nutrition and human survival.There are several challenges facing the future of agricultural practice, includingmore sustainable use of nature, less use of pesticides, better control of fertiliser


Table 5.3 Estimated global warming impacts during the entire 21st century.

Impact descriptiona Valuation (1012 h)

Type of valuation parameters EU standards PPP adjusted GNP adjusted

Decrease in agriculturalproduction (B15% beforeadaptation) - higher foodprices, shifts to other crops -possible starvation. Population atrisk: 0.6 G - 1 G, with B0.1 Gextra deaths over 21st century)

–260 –104 –2.6

Reduced forestry output (as inKuemmel et al., 1997). Impactcurbed by substitution

–4 –1.6 –0.4

Decrease in fishery output(probably more than 15%).Ocean and aquicultureproduction more important infuture, implying maybe 40 Mextra deaths

–104 –42 –1.0

More extreme events: floods(B20% increase, 0.86 - 1.03 Mdeaths, 14 G- 17 G dislocationsat 0.1 DALY)

–20 –9 –4

More extreme events: droughts(B20% increase, 0.07 - 0.08 Mdeaths, 7.0 G - 8.4 G affected at0.01 DALY)

–1 –0.4 –0.01

More extreme events: fires (B20%increase for the 50% of the totalconsidered climate-related, 31 -34 M deaths, 0.57 G - 0.69 GDALYs)

–16 –9 –3.2

More extreme events: storms(B20% increase, 1.57 - 1.89 Mdeaths, 0.5 G - 0.6 G affected at0.01 DALY)

–1 –0.4 –0.01

Unspecific human migration inresponse to environmental &social impacts of warming (0.3 Gaffected)

–4 –1.4 –0.04

Malaria (presently 0.9 M deaths y–1

and 35 M DALY y–1 (with 17 Ginfected). Estimates for 2050 are3–5 times less, clouding –8% to+16% change due to warming)

? ? ?

Dengue fever and tropical-clusterdiseases. Remarks made formalaria apply, but values are 3–6times less

? ? ?

Positive health effects of highertemperatures and fewer coldspells (220 M deaths avoided)

þ572 þ297 +119

160 Chapter 5

usage including higher use of organic fertilisers and less waste to reachwaterways, and more efficient use of water resources. These problems will haveto be addressed both in the currently largest agricultural producers and inupcoming less-developed countries, and the solutions selected will influence theimpacts of greenhouse warming. An average global figure of one millionadditional deaths per year over the 21st century is assumed to arise from somegroups being unable to purchase adequate food at the higher prices, or as aconsequence of the unavailability of necessary imports in poor regions not ableto pay for such imports.

The next entry is for forestry products, where also a reduction is foreseen.However, the impact is difficult to estimate, because wood can be replaced byother materials, and the economic valuation of the earlier assessment is justtaken over.

For fisheries, a growing importance is expected for fish, shellfish and edibleocean plants such as seaweeds. This is because of the increasing populationand the reduction expected for land-based agriculture. However, expansionof ocean fishing and near-shore aquaculture is limited by the problems ofunintelligent over-fishing (such as destroying hatching and nursing areas bytrawl fishing by a fishing industry not even obeying legislation already inplace forbidding activity in these areas) and of oceanic pollution (dumpinglong-lived radioactive and chemical toxic substances into what should havebeen the source of future food production). Upon this background, it isdifficult to assess the additional reduction in ocean harvests caused by climateeffects, but there will be a reduction due to the established higher pro-ductivity in key areas of a colder ocean. The mechanism of price increases forfish products is assumed similar to that of agricultural products, and theglobal warming contribution to inadequate nutrition deaths is taken as 0.4


Impact descriptiona Valuation (1012 h)

Type of valuation parameters EU standards PPP adjusted GNP adjusted

Negative health effects of highertemperatures and more heatwaves (160 M more deaths)

–416 –224 –87

Increase in skin cancer, asthma andallergy cases

–6 –5 –4

Loss of species, ecosystem damage,freshwater problems, insectincrease, etc. (as in Kuemmelet al., 1997)

–50 –20 –0.5

Loss of tourism, socioeconomicadaptation problems

? ? ?

Total of valued impacts (highly

uncertain)

–310 –120 +16

aM=106, G=109.


million per year over the 21st century (40% of the figure for land-basedagriculture).

The following rows of Table 5.3 deal with the effects of extreme events,based on the data given in Section 5.1.2. Most damage is caused by floods(including river overflows and mudslides), according to data from eventstaken place over the recent 14 years. Assuming a 20% increase in such events,there will be an additional death toll of 1700 per year on average for the 21stcentury, but the number of people affected will be as large as 30 million onaverage each year. Injuries and hardship due to dislocation (or permanentmigration away) from flooded areas is taken to imply a 0.1 year shortening oflife (DALY). Flood damage is not restricted to low-income countries such asBangladesh but has had large impacts elsewhere, e.g. in Florida andLouisiana. Also, flooding caused by excess water in rivers, as currentlyexperienced in many European countries, is expected to follow the 20%increase as a result of man-made climate change.

For droughts, a similar 20% increase will demand 120 direct fatalities and 14million people affected on average for each year of the 21st century. Theindirect effects on agriculture is included above and, given little change in theavailability of drinking water, fatalities will be fewer than for flooding and thelife shortening is accordingly being assumed smaller, at 0.01 DALY permember of the affected population.

The statistics on fires shown in Section 5.1.2 include all kinds of fires, and it isassumed that only 50% are climate related. Those caused by climatic drying inconjunction with human carelessness or irresponsibility are included, in addi-tion to self-ignited fires (e.g. by lightning). The greenhouse warming-relatedincrease in deaths is estimated at 30 000 per year and the increase in DALYs as1.2 million per year (e.g. diseases caused by smoke inhalation). Additional costsare associated with the property damage or loss. As shown in Figures 5.12 and5.13, fires are not restricted to low-income countries.

Finally, a wind-storm increase of 20% is predicted, causing 3200 additionaldeaths annually and affecting additionally one million people annually onaverage throughout the 21st century. Injuries (say from falling objects) and life-shortening are taken as 0.01 DALY in the affected population.

In addition to people dislocated in connection with extreme events, there isa substantial wish to migrate away from areas with poor prospects for adecent life into areas of higher prosperity (Latin America to USA andCanada, Africa to Europe, etc.). Causes are wars and criminal gangs, as wellas poor governance and few economic options. Upon this background,additional effects of climate change will be difficult to identify and theassumed value of 3 million affected is basically a residue left over after themigration caused by extreme events is singled out (cf. McMichael et al., 1996;Kuemmel et al., 1997).

For malaria and the other vector-borne diseases considered in Section5.1.4, a highly variable change is projected as caused by climate warming,ranging from some 8% reduction to 16% increase, primarily related to dif-ferences in conditions or at least in the modelling assumptions for different

162 Chapter 5

regions. These effects are likely to be little visible in a development wherevector-borne diseases are projected to rapidly disappear, with a 70%reduction already by 2030, according to the WHO models shown in Figures5.37 and 5.38. The optimism of the UN organisation may turn out to beunwarranted and unexpected developments are common in the field of dis-eases, depending on genetic change, adaptation and development of new‘‘miracle’’ drugs or other treatments, whether the disease is epidemic or, ashere, parasite based. For this reason, no estimate of additional deaths ordisabilities is made here, optimistically consistent with the UN hope that theproblem will go away within the period considered, and that no new insect-related disease will come into play.

The general effects of an average temperature increase considered in Section5.1.3 are reflected in the next two rows of Table 5.3, singling out the positiveand the negative effects, both of which are extremely large and affecting allregions of the world. As discussed in Section 5.1.3, the number of deaths relatedto cold weather avoided (an average of 2.2 million per year through the 21stcentury) exceeds the number of additional deaths due to hot spells and gen-erally warmer weather (1.6 million per year), but preferentially occurs in dif-ferent locations. It would therefore not be reasonable just to quote the netresult of a significant benefit. It is no consolation in warm climates to know thatconditions are becoming better in Siberia, unless there were a programme forresettling populations to higher latitudes.

The final rows in Table 5.3 list increases in skin cancer caused by increasedUV radiation, a temperature-dependent augmentation in cases of asthma andallergies, ecosystem impacts of warming such as loss of species, increasednuisance from insects, freshwater problems and climatic influence on sociallife and tourist incomes. The effect on drinking water supplies due to drynessand lowered groundwater tables in a warmer climate is the one most likely toadmit quantification, and the value used by Kuemmel et al. (1997) is rein-stated here.

Summing up the impacts to a total is hardly permitted, given the missingitems and high uncertainty, but if one still tries to do it, one obtains at least anidea of the magnitude of the problem. If lives are valued at European stan-dards, the negative impact over the 21st century exceeds 300� 109 h, but ifpurchasing parity is used then the amount is 120� 109 h, whereas the valuationis a positive 16� 109 h impact if the value of lives in poorer countries arereduced by the GNP factor. The negative impacts are smaller than the earlierestimate of Kuemmel et al., (1997; their upper and lower estimates were 109 and108 US $), owing to the positive temperature effects and to not valuing malaria.Also Kosugi et al. (2009) found impacts of –500� 109 US $ for the 21st century,with the highest economic impact arising from land use change and the asso-ciated decline in agricultural production. These authors remark that althoughthe damage cost appears high, it is still under 10% of the total GDP createdduring any period of the 21st century.

The information in Table 5.3 is displayed in Figures 5.40–5.42 for the threevaluation cases of all lives and impacts valued in h according to European


Figure 5.40 Valuation of 21st century global warming impacts using EuropeanUnion standards.

Figure 5.41 Valuation of 21st century global warming impacts using purchasingpower parity adjustments for less developed nations.

164 Chapter 5

standards (Figure 5.40), with the impacts in less developed countries valuedsimilar to the standards of the European Union, but in local currencies andtranslated back into h using the purchasing power parity exchange rates (Figure5.41), and finally evaluated with standards scaled down with the ratio of localGDP to the European Union average GDP (Figure 5.42).

5.2 LCA of Combustion Pollutants

Emissions from energy production and conversion plants to the atmosphereinclude particulate matter with an important distribution on particle size (a keypollutant from coal and wood combustion), sulfur and nitrogen oxides fromcombustion of fossil fuels, toxic organic substances and heavy metals, as well asradioactive substances, particularly in the case of nuclear power plants. For thefossil- and biomass-based fuels there is carbon dioxide, discussed in Section 5.1from the point of view of greenhouse warming. Although the relative distributionof these emissions depends on the fuel used as well as on the combustion tech-nology envisaged, there are general impact characteristics that warrant treatingthese emissions at a generic level, aimed at toolbox use in actual LCA studies.

Another important feature characterising the emissions is the type of emission.There may be releases to soil, to waterways or to the atmosphere, and also theparticular release type. For atmospheric releases, this could be through the tail-pipe of a road vehicle or through chimney stacks of various heights. The impactswill depend onwhether the initial emission is in the breathing height of children oradults, from low-altitude stacks of detached home chimneys or through very high

Figure 5.42 Valuation of 21st century global warming impacts using gross domesticproduct downscaling adjustments for less developed nations.


stacks that cause the immediate surroundings to receive only a small fraction ofthe substance emitted. The issue of atmospheric transport of the emitted substancebecomes especially important for releases through high stacks.

In water, dispersal may be by currents, while in the atmosphere it is done bywind, in conjunction with the thermal motion of releases having a temperaturedifferent from that of the surrounding air. If the emission has sufficient mass, itmay be deposited at a distance from the point of release by gravity action, whilelesser particles can stay afloat, suspended in the air for long periods of time.Still, they may eventually become deposited on the ground (or on variousobstacles), in a manner that depends on the roughness of the terrain that thewind moves the polluting substance over. In addition, rain may scavengeparticulate pollution and bring it to the ground. One distinguishes betweenwashout by rain originating above the polluting substance and incorporation ofthe pollutant into raindrops (the pollution particles may serve as a condensa-tion nucleus for water in the atmosphere).

Finally, there are substances which may undergo chemical reactions withother constituents of the atmosphere and thereby change their dispersal char-acteristics (an example being ozone). For many substances there are a knownrelationship between amounts inhaled by humans and the health effects ensu-ing, possibly in a stochastic way that invites use of average dose–effect rela-tionships. These relations would be contained in the inventory database of anLCA toolbox.

For modelling the transport in the atmosphere one may employ circulationmodels, such as the ones used for meteorological forecasts or climate models,just with source and sink equations for the emitted substances added to theEulerian transport equations for wind velocity (Sørensen, 2010). Anotheralternative is to use trajectory models, tracing the motion of a small packet ofpollutant released in a given altitude over a given geographical location andfollowing its journey over the next hours, days or weeks, using data onatmospheric conditions such as wind speeds and directions, precipitation andtemperature. Sometimes this is done backwards, trying to identify where thepollution affecting a particular location may have originated.

The surprise that became a major theme at the 1972 UN Conference on theEnvironment, held in Stockholm, was how far emissions, e.g. from powerplants, would travel and induce measurable effects, such as acidification causedby sulfur dioxide emissions (Rodhe, 1972). Figure 5.43 shows a more recentexample of the fate of the particulate matter emissions from a contemporaryGerman coal-fired power plant at Lauffen. Multiplying the particle content ofeach grid cell, supposed to represent the pollution reaching the ground or thenear-ground breathing air, by the population within this grid cell will yield theexposure distribution, which then will further have to be multiplied by a dose–response factor in order to yield the morbidity, and finally a valuation estimateto reach the monetary impact figure.

The total amount of particulate matter emitted consists of some 90% ofparticles with a diameter above 10 mm and the rest smaller (ETSU/IER, 1995).Current measurements usually are capable of determining both the 10 mm

166 Chapter 5

particles, denoted PM10, and also the PM2.5 particles with diameters down to2.5 mm. Health impacts typically increase with smaller particle size, governed byinitial penetration into bronchial arteries and lung alveoli.

Figure 5.44 gives an example of a close-up of tropospheric ozone emissionsfrom the same German power plant, again using a trajectory model incor-porating changes in wind speeds and direction. The point made in this study,comprising both coal and lignite power plants, is that to include the full extent

Figure 5.43 Increment in annual average TSP (total suspended particulate matter) inmg m–3, caused by the emissions from a 700 MW coal-fired power stationsituated at Lauffen (Baden-Wurttemberg, Germany). Grid cells are100� 100 km2. From chapter 3 in European Commission (1995).


of impacts it is necessary to calculate transport and deposition of the pollutantfor distances of over 1000 km from the source of emission, as illustrated inFigure 5.45 for substances found in the stack emissions of fossil power plants.Figure 5.46 shows an example of even longer transport, here for a pesticide (a-HCH) released over agricultural fields in China. After two years, a con-centration of this pesticide is found over most of the Northern Hemisphere(Leip and Lammel, 2004). The concentrations in the Southern Hemisphere aresmaller, but not zero, owing to the fact that atmospheric transport across theequator is modest (a fact also showing for CO2).

Finally, Figure 5.47 shows the dispersal of nitrogen dioxide from acontemplated natural gas plant in the UK. The radial lines of elevated con-centration seen in this figure as well as in Figure 5.43 are due to the lineartransport assumed within each grid cell, combined with a finite number of winddirections considered.

Because transportation by wind depends on the size of particles or gasaggregates, it will not generally be possible to create a library of dispersionpatterns to use in upcoming LCA cases, but a collection of sets valid fora particular kind of emission and averaged over a year with typical weatherpatterns may be feasible. The folding with population densities could also beincluded in such tools, provided they are unchanging or the changes can beforeseen. Final translation into health impacts may become standardised, if themechanisms are reasonably understood. Chapter 6 will provide some applica-tions of these methods for power plants and other energy conversion systems.Impact pathways such as the ones depicted in Figures 2.1 and 2.8 wouldtypically lead to consideration of the following environmental impacts (cf. thelist in Table 2.3).

Figure 5.44 Increment in ozone concentration in mg m–3 for a specific moment intime, derived from emissions from a 700 MW coal-fired power stationsituated at Lauffen (Baden-Wurttemberg, Germany). From chapter 3 inEuropean Commission (1995).

168 Chapter 5

Human health impacts of the air pollutants such as SO2, NOx, particulates,CH4 and H2O are based on emissions in kg, say per kWh of electricity gener-ated in the case of a power plant. The dispersion model is used to calculateconcentrations (kg m–3 kWh–1), which together with the population density

Figure 5.45 Percentage of damage included by integrating to various distances from thesite of emissions forNO2, SO2 andparticles of different sizes (fromEuropeanCommission, 1995). The smallest particles travel more than 1000 km.

Figure 5.46 Average fallout distribution over soil, vegetation, ocean and atmosphere,two years after the pesticide a-HCH was released in China, according tothe dispersion model of Leip and Lammel (2002). Note the logarithmicscale for deposition (in 10–9 g m–2, with vertical integration, e.g. foratmosphere).


gives the exposure in terms of ingestion or other assimilation (kg cap–1 kWh–1).The pollutants may reach populated areas in hours or days, but they may staysuspended for months or years, giving rise to a time–space profile of exposure.

The next step involves medical expertise, translating exposure into mortalityand morbidity estimates. Because some deaths and most health problems willbe displaced in time, the impact toll at a given point in space–time will consistof parts originating from pollutant ingestion at different times and perhapsdifferent locations, both for an individual victim and for the whole population.The numbers would typically be expressed in terms of number of cases per kWhof power produced.

Several databases exist providing mortality and morbidity as a function ofhuman exposure or one more step back as a function of emission rates. Thebasic measurements behind the databases have considerable uncertainty,because they are based on statistical information for often very inhomogenousgeographical regions or on animal experiments. WHO (2006) gives estimatesfor particular matter (PM) of the order of 0.6% increase in overall mortality foreach 10 mg m–3 increase in concentration of PM. There is, however, anuncertainty interval of 0.4–0.8% and other studies find results lying outsidethese limits. WHO also estimates PM-related mortality with data for particularcauses of death, such as respiratory or cardiovascular diseases, but the uncer-tainty is not diminished. The variability in exposure is illustrated by PM10

Figure 5.47 Average incremental ground-level NO2 distribution in parts per billion(ppb), caused by emissions from a hypothetical combined-cycle naturalgas-fired power plant at West Burton (Nottinghamshire, UK), accordingto the Harwell Trajectory Model (from European Commission, 1995).

170 Chapter 5

measurements in cities of the world, where WHO finds the highest averagevalue (250 mg m–3) in Karachi (Pakistan) and 10–15 times lower values inTokyo (Japan) and Stockholm (Sweden).

For the fossil fuel-derived SO2, WHO (2006) finds a 2.8% (uncertaintyinterval 2.1–4.6) increase in mortality for a 50 mg m–3 increase in SO2, basedon studies in West European cities. For the eastern part of Europe and forcities in the USA, an increase around 1% is found. Again there are hugedifferences between SO2 levels in individual cities, ranging from 100 mg m–3

in Harare (Zimbabwe) to 3 mg m–3 in Calcutta (India). For NO2, Sao Paulo(Brazil) and Mexico City top the list with 83 and 77 mg m–3, while Stock-holm at the other end has 18 mg m–3. Although there is uncertainty in manyof these numbers, governments are mostly aware of the connection betweenair pollution and human health and strive to reduce levels to the WHO(2006) recommended ones.

Several studies have looked at the parts of the pollutant pathway shown inFigure 5.48. Zelm et al. (2008) used a 50� 50 km2 grid for Europe to calculatethe fate of incremental emissions of PM10 (particles with a diameter above 10mm, kg y–1), leading to local grid-cell concentrations (kg m–3) and then toincreased human inhalation (kg y–1, assuming a breath intake of 4745 m3 y–1;US EPA, 2008). The same group also looked at carcinogenic pollutants fromair concentration to disease burden, but in this case only for the Netherlands(Geelen et al., 2009). All quantities are annual averages and for carcinogens thecancer risk is for life-long exposure to a given air concentration (because theseare the data available from WHO, 2006; US EPA, 2008). In contrast, forparticulate matter the risk of death or disease is taken as an incremental

Figure 5.48 The pathway from emission of polluting substances to health damage inthe form of death or morbidity, acute or delayed, which may be com-bined and expressed in disability adjusted life-shortening (DALYsmeasured in years).


increase over some ‘‘normal’’ value assumed for the case of no particulatepollution, because the diseases and causes of death are not reserved for PMpollution but are quite common. Some inputs and results from these studies aresummarised in Table 5.4. The health damage for carcinogens is much smallerthan that found in indicator life-cycle analyses.

If the impact is considered amenable to monetising, the number of cases maysubsequently be translated into a cost in h per kWh produced, or anyequivalent unit (e.g. using Table 5.2).

The same steps would be involved for effluents reaching waterways or con-taminating soils (e.g. by deposition) and the impacts for living species otherthan humans may be calculated along the same lines, by substituting theexposure patterns, the medical damage depending on species genetics, andpossibly a monetary evaluation depending on human evaluation of the value ofthe species in question (say higher for gorillas than for mosquitoes).

This analysis can be repeated for other steps of a fuel cycle or for othercradle-to-grave sequences, such as mining, preparation, energy usage, decom-missioning and residue handling or storage (cf. Figure 2.1).

Impacts are rarely restricted to living creatures. Buildings or other assets ofsociety may become degraded or lost (e.g. due to acid rain originating from SO2

Table 5.4 Risk and damage associated with a selection of particulate andcarcinogenic substance air pollutants (Zelm et al., 2008; Geelenet al. 2009).

Substance consideredand its main effect

Risk increaseper mg m–3

in air

Referenceincidencein risk y–1

DALYsy–1 percase

DALYs perkg emission(Europe)

PM10, long-termmortality

4.3� 10–3 6.76� 10–3 10.0 2.6� 10–4

PM10 from NOx,mortality

6� 10–4 6.76� 10–3 0.25 5.7� 10–5

PM10 from NH4,respiratory

1.14� 10–3 3.08� 10–3 0.025 8.3� 10–5

PM10 from SO2,cardiovascular

5� 10–4 5.28� 10–3 0.027 5.1� 10–5

Substanceconsidered a

Risk per mgm–3 lifetimeexposure

Maineffect

DALYsy–1 percase

DALYs y–1

per cap.(in Holland)b

Tetrachloroethylene 2.27� 10–6 cancer 15.6 3.7� 10–11

Formaldehyde 1.30� 10–5 airway cancer 5.5 1.9� 10–7

Benzo[a]pyrene 8.70� 10–2 lung cancer 14.7 5.8� 10–6

Benzene 6.00� 10–6 leukemia 23.4 9.7� 10–7

Cadmium (&compounds)

1.80� 10–3 lung cancer 14.7 2.7� 10–8

Vinyl chloride 1.00� 10–6 hepatoangiosarcoma 15.6 3.0� 10–10

Ethylene oxide 5.88� 10–6 cancer 15.6 6.7� 10–10

aIARC classification 1 or 2a (WHO, 2006).bConcentrations used are not given in Geelen et al. (2009).

172 Chapter 5

emissions). Soil and water bodies may become polluted and this may havenegative impacts on agriculture and fisheries, and generally, ecosystems invol-ving forests and other plants, fauna and basic geological make-up may becomedisturbed in ways that can bring them into situations of peril, whether related tospecies extinction or to changing conditions for disease-carrying organisms andrelative prevalence and niche occupancy of different groups of species.

Finally, some technological systems may along their life-cycles present othertypes of positive or negative impacts, such as avoidance of heavy work, generallyimproved conditions for people working with the technologies, ambient noiseimpacts, visual impacts and indirect impacts associated with the institutional set-up required for a given technology (as listed in some of the categories mentionedin Table 2.1). Some of these impacts can be quantified and even included inmonetary assessments, while other ones have to be stated in qualitative terms.

5.3 LCA of Radioactive Substances and Accidents

Radioactivity plume models similar to those for chemical pollutants have beenaround for a long time, aimed at studying nuclear accidents (see review inSørensen, 1979) or impacts of nuclear war (Barnaby et al., 1982). Two impactshave to be considered: direct radiation from a passing cloud affecting, forexample, humans exposed, and radiation from radioactive substances depos-ited on the ground, withheld in structures or ingested.

At the 1987 Chernobyl accident in the former Soviet Union, transportmodels were used to bring consistency to measured data suspected to concealattempts by some countries to cover up the high contamination likely to affecttheir produce, including export food articles. The area-based estimates forfallout of the two important radioisotopes 131I and 137Cs, shown in Figures 5.49and 5.50 , revealed that fallout within the Soviet Union had to be substantiallylarger than claimed by the authorities in order to be consistent with the falloutoutside the Soviet territory.

Radioactive pollutants have a half-life that implies diminishing impact withtime (but quite a long time for some isotopes). Non-radioactive pollutants mayexhibit a similar behaviour if chemical reactions or physical degradation changetheir effects with time. In the dispersal calculations the declining magnitude ofradioactivity available for inhalation or other ingestion has to be taken intoaccount. On the other hand, the damage from radioactive substances mayinvolve radiation inside the human body over periods of many years andspecific elements and compounds accumulate in specific organs, often in waysdifferent from that of compounds prevalent in non-radioactive pollutants. Anexample in connection with nuclear accidents is the important, but short-lived,iodide isotopes that tend to accumulate in the thyroid.

Significant nuclear accidents involving military facilities have happenedseveral times in the US and the former Soviet Union (McLaughlin et al., 2000),and the exposure from US (and later Soviet, British, French, Chinese, etc.)military nuclear weapons tests, first on continental land (US, USSR, Australiaand China) and later on unfortunate Pacific islands, have posed quite


important health degradation in the populations around the test sites (accidentlist at Wikipedia, 2009). An accident at the British Windscale Research Reactorin 1957 caused significant fallout all over Europe (UK Atomic Energy Office,1957).

More recently, an accident at the Three Mile Island reactor in the USA(1979) caused some 70% of the nuclear fuel to melt, with severe damage insidethe reactor, but surprisingly hardly any contamination outside the siteboundaries. The explanation seems to be a continued presence of water in thereactor vessel, which prevented a ‘‘China syndrome’’ melt-through (Booth,1987). The fact that the water did not escape though openings that the accidentcould have produced in the vessel structure is described as exceptional beyondstochastic rationality. The reactor did not have the water flooding system thathas been proposed to qualify for an ‘‘inherently safe’’ system (Hannerz, 1983;Sørensen, 2005). Despite the absence of fatalities, the economic damage cost ofthe Three Mile Island accident is already at 2.4� 109 US $ (2006), notably forsecuring the wreck against assembly of critical fissile mass, by robotic dis-assembling of the nuclear fuel compartment (Sovacool, 2008). The workers

Figure 5.49 Summary of measured 131I fallout data for the first few weeks following theChernobyl nuclear accident in 1986, in kBq m–2. Accumulated fallout foreach quadrangle is indicated in italics at the corners, in 1015 Bq, and totalswithin and outside the former Soviet Union are given (Sørensen, 1987).

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operating the robot equipment were allowed a calculated radioactivity expo-sure (maximum 20 hours in 6 weeks; Booth, 1987).

Dealing with the salvaged radioactive debris and actually decommissioningof the entire reactor has not yet started and is estimated to cost several timesmore than the original cost of constructing the plant. For an intact nuclearreactor, the IAEA hopes that the decommissioning cost will be less than theconstruction cost (De, 1990).

The 1986 Chernobyl accident in present Ukraine took place in a reactor of adifferent construction from the ones used in light-water reactors in Westerncountries, which led to the peculiar time succession of radioactivity emissionillustrated in Figure 5.51, where instead of a monotonic decrease one findsmajor releases over a nine-day period, with increasing emission after an initialfall. The reason is that the initial failure and explosive release of reactor corematerial (expelled several km into the air) was followed by a graphite fire thatlasted several days before it rather suddenly came to a halt (USSR StateCommittee on the Utilization of Atomic Energy, 1986). The data are from

Figure 5.50 Summary of measured 137Cs fallout data for the first few weeks followingthe Chernobyl nuclear accident in 1986, in kBq m–2. Accumulated falloutfor each quadrangle is indicated in italics at the corners, in 1015 Bq, andtotals within and outside the former Soviet Union are given (Sørensen,1987).


Berezinsky, a site 600 km away from the accident site, because closer measuringstations were not working or inactive and required manual start (a character-istic state of affairs in the late Soviet Union). The measurements shown inFigure 5.51 are thus time-displaced by an amount depending on prevailingwind speeds; because shifting winds may sometimes have carried debris towardsthe National Park and at other times in other directions, the relative size ofemissions cannot be deduced from Figure 5.51.

Because emissions from Chernobyl took place at different heights and over alonger period of time, they involve fractions experiencing different atmosphericconditions and thus carried in different directions. This is illustrated by thetrajectory calculations shown in Figure 5.52 (selected from a larger set of 6 hcalculations using the then available circulation models) for three levels: groundlevel and elevated levels of 850 mb (ca. 1.5 km) and 700 mb (ca. 3 km). As notedin Sørensen (1987), part of the cloud must have extended above 5 km in orderto produce the fallout pattern observed in Japan and North America. Thetrajectory calculations of Figure 5.52 are in good agreement with similar cal-culations made, for example, in Sweden (WHO, 1986); based on the veryvariable winds (but fairly little precipitation) for the crucial period, an overallpicture of emissions can be constructed, such as the one shown specifically forthe health-impact important radioisotopes 137Cs and 131I in Figure 5.53, taking

Figure 5.51 Time-series of releases of selected isotopes following the Chernobylaccident, as measured at the Berezinsky National Park some 600 kmnorth of the reactor site (part II, annex 5 of USSR State Committee onthe Utilization of Atomic Energy, 1986).

176 Chapter 5

into account the decay of the isotopes until nine days after the first release(IAEA, anonymous staff writer, 1986). The amounts found are in goodagreement with the data consolidation attempt of Figures 5.49 and 5.50 forregions covered by both sources.

The Chernobyl reactor unit suffered a melt-down with release of all inertgases, 10–20% of medium-weight isotopes and about 3% of plutonium and

Figure 5.52 Trajectories of atmospheric transport of releases made 0, 12, 24 and 36 hafter the first radioactivity release by the 1986 accident at the Chernobylnuclear plant (encircled), at three different heights. For each ‘‘puff’’, thetrajectories are marked with positions reached after each subsequent 12 hperiod (Prahm and Rattenborg, 1986). The location of the Berezinskymonitoring facility providing the data shown in Figure 5.51 is indicatedby a cross.


other heavy isotopes, the latter being 10 times more than foreseen in any pre-vious reactor safety studies (Sørensen, 1987).

Accidents are part of the experience with any technology used in humansociety. These range from occupational accidents during all phases of thelife-cycle of an energy plant (Attwood et al., 2006) to catastrophic accidents.For the latter, a list of reported accidents between 1907 and 2007 is surveyed bySovacool (2008), quoting the official information on acute fatalities and actualcosts induced by the accident. Both are lower bounds where a range is quoted,and the deaths exhibit a strong bias, because 171 000 people drowning due to adam collapse are counted, but the people dying from air pollution or radio-active releases are not, because the effects are delayed and spread over a largerpopulation in a stochastic way. For nuclear accidents the number of acutedeaths is 4000 and for fossil power plants 6800 (coal mining accidents, gasexplosions, oil pipeline and tanker accidents), and a fair comparison wouldfurther weigh with the relative share of hydro, nuclear and fossil in the totalenergy sector over the century considered.

Figure 5.54 shows the time distribution of the costs of immediate damage perdecade (costs of property loss, emergency responses and early clean-up, lostenergy production and early legal costs), based on a compilation by Sovacool(2008). The costs of neither early nor delayed fatalities, injuries or diseases areincluded, but the first one could be estimated using the statistical value of lifegiven in Table 5.2 It is possible that not all accidents in the early part of the 20thcentury have been included, as there are no oil-related accidents before 1967,for example, indicating that accidents at the several then existing private US oilwells may not be represented. Despite their modest share in total energy

Figure 5.53 Ground deposition of 137Cs and 131I in Europe, following the 1986Chernobyl nuclear reactor accident, as calculated using the MESOSdispersion model of Imperial College (UK) with radioactive decay up toMay 9th, 1986 (IAEA, anonymous staff writer, 1986).

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production, nuclear and hydropower are seen to cause the largest accidentcosts. Hydro accident toll is dominated by the 1975 Shimantan Dam failure inHenan Province, China, and the total number of hydro accidents reported isjust three, much less than the 50 coal accidents, 68 oil accidents and 63 nuclearaccidents reported over the century. For natural gas, as many as 82 (pipeline-related) accidents are reported plus nine processing plant accidents for liquidnatural gas. The coal accidents are entirely mining accidents, while oil accidentsare spread over tanker, pipeline, storage and off-shore platform accidents.Nuclear accidents are irregular in size and it is too early to say if there has beena decline after the Chernobyl accident. Nearly all remaining nuclear powerplants are based on light-water technology (boiling or pressurised), indicatingthat the frequency distribution may approach one, allowing statistical treat-ment. For oil, the accident toll has increased substantially over the two latestdecades, not only due to the offshore activities. However, the total damage costis still smaller than that of nuclear, despite much larger contributions to energydemands.

Figure 5.55 gives a similar distribution of early fatalities. Coal-mine accidentfatalities were particularly large for the period 1907–1917, declined around1980 when many countries started to phase out coal, but then returned to highvalues in the early 21st century, indicating a new increase in usage but also thatmining technology has not advanced to eliminate the large risks. As mentioned,the large hydro fatalities come from a single event, and a corresponding largenumber induced by delayed effects of fossil fuel-based air pollution and nuclearradioactivity releases are not included. Neither are the accidents that couldhappen in reprocessing plants and waste storage facilities, both of which have

Figure 5.54 Reported cost of immediate damage (property lost, emergency measures)from energy-related accidents for 1907–2007, given per decade and dis-tributed over types of energy (based on data collection in Sovacool, 2008).


hardly started to operate on a full scale. LNG is seen to have a large accidentrate relative to its contribution to the energy supply, and that of oil hasincreased as the industry has moved off-shore or started to explore remotedeposits requiring long-distance pipeline or tanker transport.

Based on the observed number of large nuclear accidents involving core melt-down in commercial reactors (currently Three Mile Island and Chernobyl), animplied ‘‘frequency’’ order-of-magnitude can be illustrated in the way done inTable 5.5. Two accidents over the accumulated power production to mid-2010implies a 3� 10–5 per TWh frequency, and (for one accident) a 1.5� 10–5 per TWhfrequency for an accident with very severe external consequences. At the time ofthe Chernobyl accident the estimate would have been over 10 times higher, owingto the much lower accumulated power production of reactors worldwide by 1986.For comparison, the built-in probability (that is, accepted at the design stage) foran accident with Chernobyl-type consequences for a new, state-of-the-art light-water nuclear reactor is by a fault-tree analysis calculated to be about 1.25� 10–6

per TWh (for a ‘‘ST2-accident’’ according to CEPN, 1995 and Dreicer, 1996). Thefactor 12 difference between the two numbers comes partly from the differencebetween a state-of-the-art reactor and the average stock, and partly from thedifference between the probability of anticipated accidents and the actual fre-quency estimate that includes unanticipated events. The latter used in the past tobe about a factor 10 higher according towhat is called sound engineering practices;however, in recent years, safetymargins of engineered constructions have declined,owing to greater confidence in predictive calculations. The factor 10 would thus beassumed reduced to a factor of two. It is reassuring that the present risk

Figure 5.55 Reported early fatalities from energy-related accidents for 1907–2007,given per decade and distributed for types of energy (based on datacollection in Sovacool, 2008).

180 Chapter 5

assessments based on theoretical and on empirical methods thus have magnitudesthat appear to be basically understood, including the origin of the differencesidentified.

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190 Chapter 5

CHAPTER 6

Life-Cycle Analysis of Primaryand Intermediate EnergyConversion

The life-cycle approach starts with an analysis that defines the flows andprocesses involved during the life cycle of the object studied and collectsnecessary data on quantities of materials, time spent on different tasks andtransfer or transport of parts or work between regions, all focusing on thepathways most important for the object studied, but at least identifying theconnectivity with other potentially contributing pathways for which one maybe so lucky to have independent life-cycle studies to draw from.

In addition to the data relevant for the particular object (product or system)being studied, an inventory may exist or be created of the general relationsbetween causes (emissions, waste streams, labour requirements, stressing work,and so on) and the exposure imposed on human beings, on society or on theenvironment, whether man made or ‘‘natural’’. However, there may be parts ofthe exposure database which do depend on the specific circumstance of theinitiating activity, say in case dispersal (e.g. through waterways or the atmo-sphere) has to be studied for prevailing regional or even local conditions, inorder to arrive at the relevant exposures (such as human intake of toxicsubstances, amounts of acid rain falling onto a particular ecosystem, etc.).Some such generic issues were discussed in Chapter 5.

Databases of a general nature (i.e. not associated just with the particularproduct or system under investigation) may thus be time and location depen-dent and would need to be investigated separately for different situations, inorder to arrive at the required relationships between exposures and impacts (ofpositive or negative kinds), including time sequences of delayed effects.

These prerequisites (the LCA analysis) and the ensuing LCA assessment willbe described in more detail below for some specific energy systems that have


By Bent Sørensen



191

drawn much interest among regulators, decision makers and the concernedcitizens: the systems that convert primary fuels or renewable energy flows intouseful energy of the type demanded by the end users in society.

A central part of this approach is devoted to providing a list of importanteffects to be evaluated as part of a serious life-cycle study, along the linessuggested in Chapter 2. Although such a list is necessarily open ended, it isimportant to point to some obvious areas to which to pay attention, so muchmore because some of them are often forgotten in many current decisionprocesses and even in some of the studies presented as life-cycle assessments.Because life-cycle assessment is used as an instrument for regulation andpolitical framework decisions, there will necessarily be agents trying to pull theteeth out of the method, by restricting its scope and by watering down itscritique of ongoing or contemplated industrial practices. For instance, ifcompanies are allowed to use green LCA certificates in their marketing ofproducts and services, then the political overseers should at least make sure thatthere is a real content behind the green labels.

6.1 Power Production from Fossil Fuels

Common for the fossil combustion energy plants is the need to consideremissions of greenhouse gases and air pollutants of the kinds investigated inChapter 5. The translation of a 3� 1014 h impact from greenhouse emissions(Table 5.3) into externalities for specific energy activities may be done in thefollowing way.

First it should be considered if the emission scenario behind Table 5.3(basically the IPCC A1B scenario) is a representative 21st century average forthe particular society of the LCA investigation to be made. Societies con-tributing less to global emissions should perhaps be attributed less greenhousedamage than those contributing more. However, this could to some extent beseen as a moral approach, since the reality is that greenhouse gases spread overthe entire atmosphere. On the other hand, impacts of global warming do notaffect different parts of the world neither equally nor in proportion to theirshare of the emissions causing the problem. Politically, it is difficult to see anyalternative to dividing the responsibility in proportion to the emission ofgreenhouse gases by each country.

The average CO2 concentration (Figure 5.2) and forcing components shownin Figure 5.8 indicate that CO2 forcing by the year 2060 alone is 4.2 W m–2 orsome 90% of the total anthropogenic forcing. For convenience many investi-gations therefore consider only the CO2 emissions. The non-CO2 emissionsinclude emissions arising from land use changes and industrial pollution, e.g. bysulfate aerosols, and although they may partially cancel some of the warmingtrends caused by CO2, it does not appear reasonable to accord credit for this,considering the health rather than climate negative impacts of aerosol pollu-tion. This discussion is similar to that of the health impacts of warming (Figure5.27), concluding that it is not appropriate to let large positive and negativeimpacts cancel each other when they occur in different parts of the world and

192 Chapter 6

affect different people (Table 5.3). Rather, one should admit that altering therelative life conditions of different regions of the world is in itself a cause forconcern. Although some groups will experience improved conditions, it is at theexpense of other groups.

An issue that has attracted attention is the global equity problem arisingfrom the fact that some regions have used fossil fuels for a longer time and to alarger extent than others, also long before anyone suspected negative impactsfrom this activity (the greenhouse effect was first correctly described scientifi-cally by Arrhenius, 1896). As it is not possible to undo the historical emissionsbut only to regulate future emissions, one could argue that impacts should bedistributed only over future emissions. This is called the grandfathering prin-ciple: instead of ascribing each current emitter of greenhouse gases a fraction ofthe total damage estimate equal to their fraction of the accumulated emissionsfrom the beginning of the industrial period, one should distribute all damageaccording to emissions made after the greenhouse effect was finally acceptedpolitically, say by 1990 or 2000. This reassignment would place a larger burdenon present polluters, which is seen as advantageous by nations with lowemissions. However, the recent rapid economic growth and growth in emissionsfrom fossil energy use in a number of former low-emitting nations has madethis suggestion less attractive, and as a result there is much less talk aboutgrandfathering today than a decade ago. The implications of these two ways ofallocating emissions are illustrated in Table 6.1.

Table 6.1 integrates the CO2 emissions from 1990 to 2060 to obtain a total of814� 1012 kg C; when integrating from 1765 to 2060 the total is 1151� 1012 kgC. The externality costs are then either assigned according the grandfatheringscheme or according to all emissions since 1765, for a doubling of CO2 by themid-21st century (the IS92a scenario of IPCC, 1996). The resulting distributionof the impact burden (taken as the European Standard value in Table 5.3) onunit emissions is 0.18 h per Gt of CO2 emissions in the grandfathering schemeand 0.13 h per Gt of CO2 emissions in the case of no grandfathering.

Table 6.1 Greenhouse warming externalities with and without grandfathering.

Greenhousewarming impacts

Estimate I IPCC(doubling CO2

by 2050),grandfathering

Estimate II IPCC(doubling CO2

by 2050), nograndfathering

Estimate IIISørensen (2008a)DT r 1.5 1Cscenario,grandfathering

Cause (emissionassumptions)

All CO2 emissions1990–2060:814� 1012 kgC¼ 2985 Gt CO2

All CO2 emissions1765–2060:1151� 1012 kgC¼ 4220 Gt CO2

CO2 allowance2000–2100:486� 1012 kgC¼ 1783 Gt CO2

Effect (full 21stcentury cost)

310� 1012 h(Table 5.3)

310� 1012 h(Table 5.3)

187� 1012 h(scaled down)

Specificexternality

0.38 h/kg C=0.10h/kg CO2

0.27 h/kg C=0.07h/kg CO2

0.38 h/kg C=0.10h/kg CO2

193Life-Cycle Analysis of Primary and Intermediate Energy Conversion

To illustrate the political options further, Table 6.1 also gives the greenhousewarming cost in the case of a concerted effort to reduce emissions in such a waythat the global temperature rise may be kept below 1.5 1C. This is the recom-mended policy choice within the range of temperature stabilization levelsconsidered in Sørensen (2008a), as shown in Figure 5.9. The estimatedexternality is lower than for a doubling of CO2 in the atmosphere, but leads tothe same specific cost of 0.10 h per Gt of CO2 emission in the grandfatheringscheme. The fact that emissions to the year 2100 are included in this case makesonly marginal difference, because the total emissions allowed after 2060 aresmall (see Figure 5.9).

In the following life-cycle analyses for specific fossil fuel plants, the EstimateI given in the first column of Table 6.1 will be used as a central estimate, withEstimates II and III indicating an uncertainty range, without claiming thatvalues outside this range could not be defended (considering the probably muchhigher uncertainty involved in the assessment of impacts in Table 5.3, as well asthe monetising issues discussed in Section 5.1.7).

Current coal-fired power stations typically emit 0.27 kg C per kWhelec,gas-fired ones 0.16 kg C per kWhelec and oil-fired plants 0.21 kg C per kWhelec.The relation between values for C and for CO2 is given in Table 6.1 (simply theratio of molecular weights, 12/44). In case heat and electricity are co-generated,one can assign the greenhouse warming externality to the fuel input, or divide itbetween energy outputs in proportion to either energy or exergy, taking intoaccount the higher energy quality of electricity compared to low-temperatureheat. Unfortunately, the higher versatility of electric power is not always fullyreflected in consumer prices, which are often only 50–100% higher than thoseof low-temperature heat deliveries.

In the transportation sector, current use of oil products in gasoline- or diesel-driven automobiles has typical emissions of 660 g C per litre or about 49 g C pervehicle-km, corresponding to an average of 13.5 km per litre of gasoline. Moredetailed LCA investigations of road transport are provided in Chapter 7.

For biofuels such as biogas, bio-diesel, methanol or ethanol from biomass, itis debatable how to count the CO2 emissions. Owing to the short time intervalbetween the carbon assimilation by plants and the subsequent release(assuming that even woody biomass for methanol production comes fromrelatively short-rotation crops), several studies just leave out greenhouseemissions from biofuels. However, the emissions of other greenhouse gases likeN2O or CH4 during combustion should be included, and instead of consideringbiofuels as carbon neutral, it would in some cases be better to account for bothcarbon assimilation and emission, because even relatively small time-lags maybe important during the period of transition away from fossil fuels.

6.1.1 LCA of Coal-fired Power Stations

The chains defining the life cycles of power stations using the combustion offossil fuels start with fuel extraction and go through a number of conversionsteps until the final disposal of residues. Releases of pollutants to the air and

194 Chapter 6

other recipients take place during many of the steps. Purely electricity-producing plants are becoming rare, because optimum efficiency demands thatreject heat be made useful. Coal-fired power stations used to be placed far fromdensely populated areas, owing to the emission of particulates that not onlycaused health damage but also were very visible and caused blackening ofbuilding surfaces. With the current generation of electrostatic filters, particulateemissions are reduced by over 99.9% and SO2 scrubbers and more recentlyNOx removal cycles have further contributed to making it possible to site coal-fired power plants closer to cities, where the waste heat can be made useful indistrict heating lines serving hot water and space heating where required. Adifferent line of improvement has made it possible to transmit heat in fairlyinexpensive insulated pipes over longer and longer distances with tolerablelosses, and piping lines over 50 km are seen in several temperate zone countries.Closer to the equator, heat demand is or should be lower and perhaps too lowto make combined power and heat production economically viable; in practice,however, poor building insulation may negate this observation.

Cleaning of flue gases is one avenue for making continued use of coal-basedpower acceptable, combined cycle operation another, whether it is a question ofco-producing heat and power or sequential energy extraction through morethan one thermodynamic cycle, e.g. a Rankine cycle followed by one or moreBrayton cycles. Advanced coal-burning techniques use pulverised coal withlittle variation in physical or chemical properties, and a coal gasification stepwill allow a number of choices for the subsequent conversion, includingpossibilities for removal of carbon dioxide. These techniques will be employedin several of the examples considered below.

The first three examples illustrated in Tables 6.2–6.4 are from the late 1990s:a proposed British plant with only sulfur and particulate matter removed, aGerman plant with added NOx removal and a Danish combined power andheat plant. The traditional fuel chain for coal-based electricity production wasshown in Figure 2.8.

The methodology used in the three coal studies is based on a bottom-upapproach for a particular installation at a specific place, with the atmosphericmodelling of effluent plume dispersal that has already been described in Section5.2. A dominating influence on total life-cycle externalities comes from globalwarming, the estimate of which will be based on the discussion made in Section5.1 and specifically the ‘‘European Standard’’ evaluation and a possiblestabilisation of greenhouse gas emissions globally that involves at least adoubling to the mid-21st century.

The Table 6.2 entries for emission of pollutants and their valuation are takenfrom ETSU/IER (1995), except for the impacts from the power plant’s con-tributions to greenhouse warming and non-monetised impacts, which are basedon Sørensen (1997) but in the case of climate change updated to the valuationgiven in Table 6.1 (translating other greenhouse gases to CO2 equivalents). Theeconomic impact is the cost of the coal power life-cycle, from fuel extraction tooperation and decommissioning, but with electricity as the delivered productserving a consumer demand. This means that power-line transmission and


Table 6.2 Impacts from a British coal fuel chain, based on ETSU/IER (1995),Table 6.1 and Sørensen (1997), updated to 2010 prices.

Environmental &public impacts

Type ofimpact:emissions(g kWh–1)a Uncertainty

Monetisedvalue(2010 mhkWh–1)a

Uncertainty &rangesb

1. Plant construction anddecommissioning

NA NA

2. Plant operationCO2 880 LSO2 (may form aerosols) 1.1 MNOx (may form aerosols) 2.2 Mparticulates 0.16 MCH4 3 MN2O 0.5 H

Greenhouse warming(cf. Table 6.1)

from CO2,CH4, etc.

117 80–160

Degradation of buildingmaterials

from acidrain

0.7 H, r, n

Reduced crop yields from acidrain

0

Forest and ecosystemimpacts

0

Ozone impacts NQDomestic impacts only Cases

Mortality from primaryparticles (PM10)

0.2 per TWh H 0.4 H, r, n

from secondary aerosols 1.0 per TWh 2.4 H, r, nfrom chronic effects 3 per Twh NQ

Morbidity from dust andaerosols, major acute

4.6 per Twh 0 M, r, n

minor acute(workdays lost)

50 000 perTWh

0.5 M, r, n

chronic cases 200 per TWh 0 M, r, mNoise (from power plant) o0.1 M, l, n

Occupational healthand injury

1. Mining diseases 3 per TWh 0.1 M, l, mMining accidents, death 0.1 per TWh 0.2 L, l, nmajor injury 3.1 per TWh 0.4 L, l, nminor injury 27 per TWh 0.1 H, l, n

2. Transport, death 0.06 per Twh 0.2 L, l, nmajor injury 0.33 per Twh 0 M, l, nminor injury 3.17 per TWh 0 H, l, n

3. Construction anddecommissioning(injury)

1.1 per TWh 0.1 M, l, n

4. Operation (injury) 0.9 per TWh 0 L, l, n

196 Chapter 6

distribution costs should be included. Most studies of power production coststop at the power plant boundary, including costs of upstream life-cycle stepsbut usually not of downstream costs. This used to be defended by setting a highinterest rate (over 5% in real terms, i.e. after correcting for national inflation),which has the effect of making payments that can be postponed a few decadeslook vanishing small.

Current interest rates are lower than the 3% per annum that constitute themean value for the entire 20th century, and inflation has in many countries beeneven lower. This may of course be interpreted as there being too much moneyaround looking for investment opportunities, or as there being too few worthyprojects in which to invest. In any case, it means that downstream life-cyclecosts have to be taken seriously, as they probably would have to anyway in thename of intergenerational equity.

The conventional production price of state-of-the-art conventional pul-verised coal-based power is currently about 4.3 h cents per kWh (van den Broeket al., 2009), in agreement with quotes of 4.0 h cents per kWh a few years ago(Davison, 2007). The cost of power has typically risen four times quicker thanthe consumer price index during the period 2000–2008 (Hamilton et al., 2009).The cost of delivering power to consumers is not included in these estimates.

Privatisation of the electric utility industry in many parts of the world haschanged the behaviour of utility companies. The former state-owned or


Economic impacts

Direct cost (power &delivery)

40–70

Resource use low but finite NQLabour requirements NQImport fraction(into UK)

local coalassumed

NQ

Benefits from power(consumer price)

100–300c

Other impacts

Supply security many importoptions

NQ

Robustness (againsttechnical error,planning errors,assessment changes)

fairly low forlarge plants

NQ

Global issues competition NQDecentralisation andconsumer choice

not possible NQ

Institution building modest NQ

aNA¼ not analysed; NQ¼ not quantified. Values are aggregated and rounded (to zero if below0.0005 h kWh–1).bL, M, H¼ low, medium or high uncertainty; l, r, g¼ local, regional or global impact; n, m,d¼ near, medium or distant time frame.cDanes are willing to pay a price near the upper figure, making this their minimum ‘‘value’’.


Table 6.3 Impacts from a German coal fuel chain, based on ETSU/IER(1995), Table 6.1 and Sørensen (1997), updated to 2010 prices.



Monetisedvalue(2010 mhkWh–1)a

Uncertainty& rangesb


NA NA

2. Plant operationCO2 880 LSO2 (may form aerosols) 0.8 MNOx (may formaerosols)

0.8 M

particulates 0.2 MCH4 3 MN2O 0.5 H


from CO2,CH4, etc.

110 80–150


from acid rain 0.2 H, r, n

Reduced crop yields from acid rain 0Forest and ecosystemimpacts

0

Ozone impacts 0.1 per TWh 0.2Domestic impacts only Cases

Mortality from primaryparticles (PM10)

0.8 per TWh H 1.6 H, r, n

from secondary aerosols 3.0 per TWh 7.2 H, r, nfrom chronic effects 14 per Twh NQ

Morbidity from dust andaerosols, major acute

17.4 per Twh 0 M, r, n

minor acute (workdayslost)

187 000 perTWh

1.7 M, r, n

chronic cases 760 per TWh 0.1 M, r, mNoise (from power plant) o0.1 M, l, n


1. Mining diseases 0.8 per TWh 0 M, l, mMining accidents,death

0.2 per TWh 0.4 L, l, n

major injury 6.8 per TWh 1.2 L, l, nminor injury 70.5 per TWh 0.1 H, l, n

2. Transport, death 0.03 per Twh 0.1 L, l, nmajor injury 0.31 per Twh 0 M, l, nminor injury 9.8 per TWh 0 H, l, n


0 per TWh 0 M, l, n

4. Operation (injury) 0.08 per TWh 0 L, l, n

198 Chapter 6

concessioned utilities taking care of both power production and delivery havebeen divided into privately owned power producers and public net-companiesresponsible for the transmission of power, considering that no meaningfulmarket competition can be established for transmission and that the associatedfacilities (overhead lines, sea cables and buried coaxial cables) should be at thedisposal of any company desiring to sell power on the market. The net-operatoris thus responsible for ensuring access to customers from the location ofproducers and to prioritise network traffic by fair rules in cases where thetransmission capacity is insufficient to cover all requests for usage.

Unfortunately, most countries made the blunder of not keeping distribution inpublic hands. Distribution is the term used for the final connection between themain transmission lines and the buildings of users. Also, for power distribution,meaningful competition is not possible and a reasonable approach would be totreat it in the same way as transmission. Instead, the distributionof power has been privatised and left to either separate distribution companies orto the privatised utilities, who then have two business areas within their portfolio:power production and distribution, but not the intermediate transmission.

In some countries, this has lead utilities to completely change their businessstrategy, offering low prices for the electricity itself because here they are incompetition with other producers, but then moving most of their profits todistribution, where there is no competition. Other producers selling power to a


Economic impacts


40–70

Resource use low but finite NQLabour requirements NQImport fraction local coal

assumedNQ


100–300

Other impacts


NQ

Robustness (against tech-nical error, planningerrors, assessmentchanges)


NQ


not possible NQ


aNA¼ not analysed; NQ¼ not quantified. Values are aggregated and rounded (to zero if below0.0005 h kWh–1).bL, M, H¼ low, medium or high uncertainty; l, r, g¼ local, regional or global impact; n, m,d¼ near, medium or distant time frame.


Table 6.4 Impacts from a Danish coal fuel chain, based on Warming (1996),Table 6.1 and Sørensen (1997), updated to 2010 prices.


Type ofimpact:emissions(g kWh–1),a Uncertainty

Monetisedvalue (2010mh kWh–1)a



NA NA

2. Plant operationCO2 1163 LSO2 (may formaerosols)

1.2 M

NOx (may formaerosols)

1.3 M

particulates 0.3 MCH4 NA MN2O NA H


from CO2 155 100–200


from acid rain 0.2 H, r, n

Reduced crop yields from acid rain 0Forest and ecosystemimpacts

0

Ozone impacts NQDomestic impacts only CasesMortality from primaryparticles (PM10),secondary aerosolsand chronic effects

2.6 per TWh(combined)

H 0.7 H, r, n

Morbidity from dust andaerosols (acute andchronic)

9 per TWh 1.2 M, r, n

Noise (from powerplant)

o0.1 M, r, n


1. Mining diseases,mining accidents, death

all fuelimported

2. Transport, roaddamage

3.1 per Twh 1.6 L, l, n


NA NQ

4. Operation (injury) NA NQ

Economic impacts


40–70

Resource use low but finite NQLabour requirements NQImport fraction local coal

assumedNQ


100–300

200 Chapter 6

given consumer will have to pay the distribution prices demanded to the utilityowning the distribution grid. In Denmark, for example, this has lead dis-tribution charges to change from being small compared to the power produc-tion costs to now being much higher. Although the progress in replacingdistribution from employing overhead lines to the more expensive but lessintruding underground cables may justify a part of the price increase, most of itis clearly motivated by the monopolistic arrangement and absence of priceregulation, as opposed to the increasing competition in power production(municipal combined power and heat producers, wind turbine power having inDenmark captured nearly half the market supplied earlier from large powerplants). Table 6.2 has taken power delivery costs to be 50% of current pro-duction costs at coal-based power stations, but the actual value will changefrom one location to another.

Finally, the item denoted ‘‘Benefits from power’’ in Table 6.2 is the value ofthe power to the consumer. Its upper value is taken to be the price that con-sumers are willing to pay (and in some markets actually pay) for power. Therange given reflects different consumer prices for power in different regions (0.1to 0.3 h per kWh). The price includes taxation and externality payment forenvironmental damage, which in some countries doubles the market price ofelectricity.

The main damage from the coal fuel cycle comes from greenhouse gasemissions, and the uncertainty associated with estimating these is thusinherent in the assessment, with major issues being the allocation of damageoccurring in equatorial countries and benefits occurring in colder regions(Table 5.3). However, there are also differences in the non-warming-relatedpollutants, which show interesting impact variations from case to case. Thesecond case considered here is a German coal-fired power station (Table 6.3;plant located at Lauffen, the same one considered in Section 5.2). It has lowerSO2 and NOx emissions than the British power station, but slightly higheremissions of particulate matter. A second difference is in population


Other impacts


NQ

Robustness (againsttechnical error,planning errors,assessment changes)


NQ


not possible NQ




distribution and weather patterns. Although the basic population density ishigh in both Germany and England, particle trajectories can reach morepeople in central Europe than in the island state, and the atmospheric cir-culation transports pollutants in many directions at lower wind speedscompared with the British islands where stronger, westerly winds prevail andcarry part of the pollutants to continental Europe (which was not included inthe British study). These factors corroborate to make the impact close to thepower plant from heavy particles lower in the German case, but impactsfurther away substantially larger than in the UK.

The third case considered in Table 6.4 is for a Danish coal-based combinedpower and heat plant, but with impacts quoted per unit of electricity produced.Alternatively, about 50% of the damage could be assigned to the heatproduced, or some value in-between, as the quality of the heat produced islower than that of the electricity. The plant has SO2 and NOx removal at levelssimilar to those of the British and German plants, but emits 50% more parti-cles. Circulation model simulation of pollutant transport and dispersal is donethe same way as in the German study, but in the Danish case, wind carriesmuch of the polluting matter over water and to other Nordic countries, all ofwhich except Denmark have low population densities compared to Englandand Germany. The resulting non-warming damage is thus somewhat lowerthan that of Tables 6.2 and 6.3, but far from negligible.

In all three case studies the front end of the damage calculation, associatedwith coal mining and delivery to the location of the power plant, is differentbecause of differences in the sources of the coal. The ETSU/IER (1995) studiesavoid consideration of mining accidents and working conditions in EastEuropean or non-European producer countries by assuming that the coalcomes from British or German coal mines, despite the reality that these arerapidly being decommissioned.

In the Danish case, coal for all power stations is imported from a number ofproviders, including Poland, South Africa and the USA, and may have tra-velled far to get to the power station, with transport externalities involved. Onthe other hand, unloading is easier than for the German site, for example,because nearly all large power plants in Denmark are located by the sea andmany with their own coal unloading port. Because of these complex upstreamcomponents, mining and coal transportation outside the country was notincluded in the Danish study by Warming (1996).

Where it has been considered feasible, Tables 6.2–6.4 give a rough indicationof the level of uncertainties (L, low, within about a factor of two; M, medium,within an order of magnitude; and H, high, more than an order of magnitude)and whether the impacts are local, regional or global (l, r or g), as well aswhether they appear in the near term (n, under one year), medium term (m,1–100 years) or distant term (d, over 100 years into the future). Valuation of theimpacts from non-warming pollutants has in all three studies been using thevalues given in Table 5.1.

Because of the larger reserves of coal compared to other fossil resources, thepossibility of making coal an acceptable fuel by CO2 capture and removal

202 Chapter 6

followed by some acceptable storage has been investigated. Options are CO2

removal after combustion or CO2 removal before combustion, e.g. by trans-forming the fuel into pure hydrogen. LCA studies for the post-combustionpossibility have been performed (e.g. by Rubin et al., 2007; Koornneef et al.,2008; Korre et al., 2010). One problem is that known capture and removalmethods all require large amounts of energy inputs, lowering the overallefficiency of coal use in power plants by some 24–40%. The other majorproblem, shared with pre-combustion capture, is that inexpensive options forstoring the removed CO2 in geological deposits or abandoned wells are notsufficient for large-scale reliance on decarbonised coal. The volumes of CO2 aresimply too large. Figure 6.1 indicates emissions and other flows of interest tolife-cycle analysis, for generic post-combustion capture and removal schemes.

Korre et al. (2010) compare physical impacts from post-combustion capturetechnologies with those of a conventional pulverised coal power station. Figure6.2 shows results for the ‘‘hindered amine absorption’’ technology that theyfind performs best. Each category of impacts is expressed in its own units, takenas some homespun equivalent values relative to a particular substance (aprocedure developed at Leiden University by van Oers et al., 2002, for thehandbook Guinee et al., 2002). Thus resource depletion is measured in terms of‘‘Sb-equivalents’’, which is hardly the most obvious unit for describing oildepletion, for example. It is seen that there is a large potential reduction ingreenhouse warming impacts, but also somewhat increased impacts in other

Figure 6.1 Proposed post-combustion carbon capture system for fossil power plants,with indication of substances to include in the inventory of an LCA (Korreet al., 2010).


categories, owing to the materials used in the capture equipment (aquatictoxicity) and owing to the additional energy required (affecting resourcedepletion). A similar study was made by Koornneef et al. (2008). They warnabout the high uncertainty associated with quoting impacts of a technology notyet developed to an operational stage, and neither study attempts to validatethe impacts identified.

6.1.2 LCA of Power Stations Using Natural Gas or Fuel Oil

Using a methodology similar to that used for Tables 6.2–6.4, Table 6.5estimates life-cycle impacts for a contemporary CCGT natural-gas power cycle,where the gas turbine stage is followed by a steam cycle stage fed by the wasteheat from the first stage (ETSU/IER, 1995). It is first of all noted that thegreenhouse warming impacts are considerably smaller than those of the coalfuel cycle. Conventional air pollution is also less for the advanced gas cycle,partly due to its high efficiency (over 51%).

Macıas and Islas (2010) have used a methodology based on Rabl andSpadaro (1999) and the ETSU/IER (1995) studies behind Tables 6.2–6.5(considering only air pollutants, not greenhouse warming or other impacts) toinvestigate the impacts of selected emissions from seven power stations locatedup to 600 km from Mexico City on the entire metropolitan area. The mainfuel is heavy fuel oil, with contributions from natural gas and in one case coal.Air pollution in Mexico City is, as mentioned earlier, very high, believed tostrengthen the statistical basis for estimating health impacts. The largest part ofthe smaller particles, PM2.5, comes from road vehicles and private buildings.Still, the fraction coming from power plants can be calculated using emission

Figure 6.2 Physical impact changes associated with adding post-combustion carboncapture to a fossil power-producing plant (based on Korre et al., 2010).

204 Chapter 6

Table 6.5 Impacts from a British CCGT natural-gas fuel chain, based onETSU/IER (1995), Table 6.1 and Sørensen (1997), updated to 2010prices.





Fuel extraction &power plantoperation

NA NA

Main emissionsCO2 401 LNOx (may formaerosols)

0.71 M

CH4 0.28 MN2O 0.014 M


from CO2,CH4, etc.

50 40–65

Degradation of steel,painted surfaces

from acid rain M 0.1 H, r, n

Cases

Mortality from acidaerosols

0.16 per TWh M 0.3 M, r, n

Morbidity from acidaerosols

6200 symptomdays, 520serious,per TWh

M o0.1 H, r, n

Noise (from powerplant)

regulatorymaximum

0 M, l, n


Accidents (North Seagas extraction)major offshoreplatform accidents

0.016 per TWh 0.1 H, l, n

other offshoreplatform accidents

0.005 per TWh 0 H, l, n

injury: offshoreplatformconstruction

0.07 per TWh 0 H, l, n

Economic impacts


50–80

Resource use low but finite NQLabour requirements NQImport fraction(into UK)

British gasassumed

NQ


100–300


data and dispersion models, and because the average residence time of PM2.5 inair is about 40 days, atmospheric transport from the power plant locations tothe metropolitan area frequently happens. The result of the investigation is anair pollution damage of 1–2 US cents per kWh, with the lowest value for thepower plant using natural gas.

Uncertainties are estimated as factors between 0.25 and 4.0 multiplying thecentral value. The results only include SO2 and NOx emissions, not the primaryparticulate matter. Primary PM10 is considered in an earlier study aimed at cal-culating the effect of reducing vehicle emissions in Mexico City (McKinley, 2003).This study also analysed the death causes in the metropolitan areas and is thebasis for the valuation underlying these studies. It is shown in Table 6.6 and acomparison with Table 5.1 shows variations in direction both up and down.

6.2 Power from Nuclear Schemes

For nuclear power plants, the assessment in principle proceeds as in the fossilcase, but one expects more important impacts to come from plant construction,


Other impacts

Supply security depends onpipelineintegrity

NQ

Robustness (againsttechnical error, plan-ning errors, assessmentchanges)


NQ


not possible NQ



Table 6.6 Valuation assumptions used in Mexican study (McKinley et al.,2003; Macıas and Islas, 2010).

Health effect 2010 h 2000 US $

Advance of mortality 19 182 21 798Bronchitis 15 691 17 831Respiratory hospital admissions 2580 2932Cardio-cerebrovascular 10 041 11 410Emergency room visits 288 327One-day restricted activity 11 12Asthma attacks 299 340Chronic cough 82 93

206 Chapter 6

fuel treatment, operational risks and final storage of nuclear waste. Because ofthe very long time horizons associated with radiation-induced health problemsand deposition of nuclear waste, the impact assessment period by far exceedsthe plant operation period; thus questions of discounting and of changes intechnological skills over periods of several centuries come to play a decisiverole. Such monetary issues were discussed in Section 3.2. Another issue parti-cularly (but not exclusively) important for nuclear power is the accident-relatedimpacts, the treatment of which may be based on a risk analysis and valuationsuch as the one made in Section 5.3.

The outcome of a simplified LCA chain analysis (excluding side-chains anddifficult issues such as proliferation) of a French nuclear power plant situated atTricastin is shown in Table 6.7 (based on CEPN, 1995, but taking the impactsof major accidents from the estimate of Table 5.5). The emphasis is on impactsfrom the release of radioisotopes and again monetising involves the assump-tions of Tables 5.1–5.3. As expected, the largest non-accident impacts comefrom the reprocessing step. The CEPN (1995) impact estimates are based ondata provided by the operator COGEMA (now AREVA) of the plant at LaHague and are dominated by the release of 14C (half-life, t1

2¼ 5570 y) to the air,

with dose calculation integrated to 100 000 years. Pathways by water are notconsidered but could be substantial, according to actual samples obtained fromthe sea near the plant (Butler, 1997). As regards the deposition of high-levelwaste, the small impact numbers come from assumptions of a surprise-freelong-term storage with no accidental exposure to the material. Nuclear theft,terrorism and proliferation are not considered.

The use of data for nuclear accident analysis, including historical cases suchas the Chernobyl accident, may be criticised for not taking into account tech-nological progress (cf. the discussion above on average fossil power plants andstate-of-the-art technology). However, the reactor industry is currently focus-ing on developing country markets and this may imply that some of theassumptions made in past safety analyses are too optimistic. It would seemprudent not to count on the better standards of operational safety achieved insome industrialized countries as regards early warning plans, information tothe public on the need for staying indoors with controlled closure and openingof windows, and through evacuation, food bans, etc. Preparations for this andthe associated drills have not even been carried out in all present nuclear usercountries, and the preparedness for optimum accident handling cannot becounted on for Third World nuclear installations.

The French reactor used for Table 6.7 uses imported nuclear fuels (pre-sumably from Niger), but with fuel manufacture and reprocessing taking placeat sites in France. The CEPN (1995) study is based on a marginal addition ofone nuclear power station to the system already existing, so energy inputsreflect the overall French energy mix. The neglected impacts from side-chainscontributing inputs to the main fuel-cycle are considered small compared to thelargest impacts included, just as in the fossil case, although this may not hold aswell in the nuclear case, owing to its higher proportion of construction costsand externalities in the total. It is clear that the nuclear fuel chain has a quite


Table 6.7 Impacts of French nuclear fuel cycle, based on CEPN (1995),Tables 5.5 and 6.1, and Sørensen (1997), updated to 2010 prices.

Environmental & publicimpacts




Plant construction anddecommissioning

NA NA

CO2, SO2, NOx particles NA NANoise, smell, visualimpact

NA NA

Radioactivity (accordingto distance)

1.1

1. Fuel extraction andrefinement, local

0.1 L 0.03 M, l, n

regional 0.2 L 0.04 M, rglobal 0 L 0 M, g

2. Normal power plantoperation, local

0.4 M 0.1 M, l, m

regional 0.02 M 0 M, rglobal 1.9 M 0.4 M, d, g

3. Power plant accidents(cf. Table 5.5), local

2 H 1.0 H, l, m

regional 3 H 1.3 H, r, mglobal 4 H 1.5 H, g, d

4. Reprocessing andwaste handling, local

o0.01 H 0 H, l, d

regional 0.2 H 0.04 H, r, dglobal 10.2 H 1.9 H, g, d

Social impacts

Occupational injuries 0 NQOccupationalradioactivity

1. Fuel extraction andrefinement

included above L 0 M

2. Construction anddecommissioning

40.01 M 0 M

3. Transport 0 L 0 L4. Normal power plantoperation

0 M 0 M

5. Power plant accidents 0 M 0 H, l, n6. Reprocessing andwaste handling

0 H 0 H

Accident handling(evacuation, food ban,clean up, backuppower; cf. Table 5.5)

4.5 H, r, m

Indirect accident impacts(expert time, loss ofconfidence, popularconcern; cf. Table 5.5)

1.4 H, g, m

208 Chapter 6

different distribution of impacts on different phases in the supply chain com-pared with fossil plants, even without considering nuclear waste storage(Ramana, 2009).

The relative distribution of radioactivity from accidents on local, regionaland global targets is assumed similar to the Chernobyl pattern described inSection 5.3. Currently, not all reprocessing steps are performed in France, butnuclear waste is shipped to Tomsk-7 in Russian Siberia for new mixed oxide(MOX) nuclear fuel production, which is termed ‘‘recycling’’ despite the factthat nearly 90% of the waste is considered without commercial value and staysin Siberia (so far kept in drums in the open air; Gueret et al., 2009).

The issue of the relation between nuclear power usage and nuclear weaponsproliferation or terrorist use of nuclear material is a complex one. The majorefforts being undertaken to reduce nuclear proliferation would of course be muchsimpler if ‘‘peaceful’’ uses of the atom were not at the same time encouraged.Plutonium may be extracted from spent fuel by reprocessing or weapons-gradeenriched uranium may be produced by the same centrifuge technology as usedfor producing the lightly enriched fuel for nuclear reactors. For example, thismakes distinguishing between Iranian civilian nuclear power and establishmentof a weapon’s capability nearly impossible and leaves the issue as a question oftrusting the Iranian government. The second war against Iraq, waged from 2003


Economic impacts

Direct costs 50–90 LResource use not sustainable

withoutbreeders

NQ

Labour requirements low NQImport fraction (forFrance)

low NQ


100–300 L

Other impacts

Supply security medium NQRobustness (technical,planning, assessment)

important NQ

Global issues (prolifera-tion and weapons)

very important NQ

Decentralisation andchoice

not possible NQ

Institution building(safety and control)

fairly high NQ



to nominally 2010 by the USA and a few supporting countries despite failing toobtain UN endorsement, was based on accusations from US president G. Bush,Jr. (inspired by NIC, 2002) that Iraq had recommenced the path towardsweapons of mass destruction (nuclear or chemical) that was halted by the firstIraq war (conducted with UN support) in 1991.

The bottom line is that Western nations are willing to go very far and spenthuge amounts of lives and money to prevent (correctly identified or falselybelieved) attempts by rogue nations or terrorist gangs to acquire nuclearweapons. In the case of Iraq, centrifuge enrichment was the route selected forthe efforts halted in 1991 and not closely connected with civilian poweraspirations. However, as food for thought, one can think of the sacrifices thatthe US and its allies were willing to put into stopping the even falsely identifiedweapons programme in Iraq: from 2003 to 2010 the USA alone spent morethan 1012 $ (NPP, 2010) and the coalition efforts cost 4568 military persondeaths (to February 2009; Wikipedia, 2010) and more than 100 000 Iraqi lives(to June 2006; Alkhuzai et al., 2008), possibly six times more if definite killingsare augmented by death caused by side effects of the war (Burnham et al.,2006). The numbers give an idea of the magnitude of impacts that may beattributed to the mixing of civilian and military nuclear power even if, in thedefinite cases mentioned, other causes would also have played a role (forexample, access to Iraqi oil has been mentioned, e.g. by Delucchi and Morphy,2008, but not admitted by the coalition).

Few complete life-cycle assessment studies have been performed for nuclearreactor cycles. Many just focus on energy payback and greenhouse gas emis-sions (several such studies for light-water reactors are reviewed by Lenzen,2008; the greenhouse gas emission studies have been criticized by Sovacool,2008b). Reduction of the safe storage time for radioactive waste can be sig-nificantly reduced by employing accelerator-based thorium cycles (Sørensen,2005; Yasin and Shahzad, 2010). Accident frequency and severity will also bereduced due to the use of sub-critical assemblies of fissile material. The alter-native to the accelerator approach to nuclear safety is to make reactor sizes sosmall that accidents can always be contained behind the structural containmentused (Sørensen, 2005; Ingersoll, 2009).

Fast breeder reactors were researched some decades ago, but abandoned dueto poor safety and reliability performance. However, according to resourcedepletion considerations, breeding is required if nuclear energy should becomea major contributor to energy supply. Penner et al. (2008) argue for a revivalbased, for example, on the helium-cooled pebble-bed design, claimed to reducethe proliferation risk. A more general reduction in negative impacts wouldrequire use of the accelerator-based concepts mentioned above. A Frenchsurvey postpones the revival of breeder technologies towards the end of the 21stcentury (Dautray and Friedel, 2007).

Studies of life-cycle impacts from fusion power plants have also been pub-lished. While it is generally a good idea to perform LCA studies before intro-ducing a new technology and choosing its design, the fusion studies are difficult,because fusion is not only far from viability but hardly even a proven

210 Chapter 6

technology. Should it become so, it would likely be by invention of newschemes or modifications not considered today. In the study by Hamacher et al.(2001), normal operation causes little externality, accidents are assumed at afrequency below 10–7 y–1 and the only significant impacts are from 3H and 14Cfrom long-term waste storage.

6.3 Renewable Energy Chains

LCA chain calculations for renewable energy systems are often characterisedby a concentration of impacts on the construction phase. Operation mostly hasfew impacts when no fuels are combusted, and decommissioning in most casesconsists in removing the equipment and returning the site to its original state.There is mining only for materials used in construction, few pollutants spreadin the environment and no long-term waste problems. This is true for wind andsolar energy but less so for hydropower, which often causes irreversibleenvironmental changes, and biofuels, which are combusted and hence cause allthe types of negative impacts associated with fossil fuels (these being of coursealso biofuels, by origin). The following sections present, for each category,examples of life-cycle assessments relevant for the applications that have comeon-line during recent decades.

6.3.1 LCA of Wind Power Plants

Several life-cycle analyses and assessments have been made for the windturbines currently in use. Typical units feature three-bladed glass fibre rotorsmounted on steel-tube or concrete towers, transmitting a.c. (alternatingcurrent) power via a gearbox to an induction generator, which again is attachedto the standard utility grid-lines via an electronic control box. Some conceptsuse gearless technology with a synchronous generator, feeding direct currentinto an inverter connected to the power grid. Several of the impacts to beassessed exhibit a dependence on the natural, social and human settings. Thisshould be kept in mind when transferring data from one setting to another.

The highest penetration of wind power presently occurs in the Danishelectricity system, where it is about 20%, but the total number of installations islarger in Germany, Spain, the USA or India. As penetrations get higher, thequestion of energy storage or other handling of intermittency has to beaddressed and the corresponding impacts included in the LCA. For grid sys-tems characterised by strong international power transmission links, thesecould help dealing with the variability of wind energy production at a very lowcost (Sørensen, 1981a; Meibom et al., 1999; Sørensen, 2011).The direct cost ofproducing wind energy at the best land-based locations is currently 3.0–3.5 h

cents per kWh (Bolinger and Wiser, 2009; Sørensen, 2010a), with operation andmaintenance (O&M) constituting under 1 h cent per kWh out of this, averagedover an assumed 20-year lifetime. The cost for off-shore wind generators issimilar, because higher capital costs are offset by higher energy production.Because the capital cost dominates, there is little uncertainty in cost after the


turbine is installed, as opposed to a fossil fuel-based system. For a Danish-produced wind turbine placed in Denmark, the import fraction of the capitalcost has been estimated as 28%, that of the running cost 15% and there is anemployment factor of about 16 (full-time equivalent jobs per million 2010-hsspent; adjusted from Sørensen, 1986). Whether labour is considered a positiveor negative impact within an economy depends on whether there is unem-ployment or not, while for the individual it depends on how tightly social assetsare bound to work in a given society, and on that individual’s attitude to work(work as a satisfying activity versus work activities as just the means to fundinglife activities). In any case, creating jobs within a society is often viewed aspreferable compared with creating jobs abroad.

The land use associated with wind turbines may be assessed as follows. Windturbines may be placed in park configurations or individually. In order not toexperience reduced wind access, wind turbines in a wind park have to be placedseveral rotor diameters apart. The land between them and right up to thetowers may be used for agriculture, so that the largest cost in terms of land useis often the access roads needed for service purposes. Typical values are 10 m2

per kW rated power (Sørensen, 1986). Land resources are returned intact afterdecommissioning.

The visual impact of wind turbines would also depend on whether individualturbines or arrays of turbines occupy a given location. Aesthetically, slendertowers and light-coloured blades have been found to produce the most positivereception. A factor in the assessment is also the long history of wind power incountries such as Holland or Denmark, which causes wind turbines to be moreeasily accepted as parts of the visual landscape, along with farm houses andchurches often having towers as conspicuous as those of wind turbines. Forwind parks, architects are usually employed to ensure a visually acceptableintegration into the particular traits of a given landscape (Sørensen, 1981b).When a wind turbine density somewhere around the swept area over the landsurface equal to 0.2% is reached, further expansion of wind power will likelyrather use off-shore locations, if such are available (cf. Sørensen, 2008b).

The mechanical noise from Danish wind turbines erected during the 1990s was97 dB(A) at the point of emission and that of newer turbines has been continuallyreduced. The noise originating from the nacelle and gearbox (if any) can begreatly reduced by sound insulation. On the other hand, the aerodynamic noisefrom the blades depends on wind speed and is similar to that of other structuresor vegetation. It can therefore not be arbitrarily reduced (Sørensen, 1981b). Thenoise from a single wind turbine becomes inaudible some 5–10 rotor diametersfrom the site, and even for wind farms the increment over background noise isless than 2 dB(A) at a distance of 1.5 km (Eyre, 1995). Average background noiseis typically 35–37 dB(A) in quiet rural locations, and legislation, e.g. in Denmark,requires that this level is not noticeably increased by human activities.

Telecommunication interference has been studied and found similar to thatof static structures (e.g. buildings), with the exception of frequency modula-tions propagating in particularly shaped mountain locations (Sørensen, 1986).

212 Chapter 6

The extraction of power from the wind has a slight influence on the micro-climate below and behind the turbines (Sørensen, 1996), but otherwise there isno pollution associated with the operation of wind turbines, assuming lubri-cants to be contained. The chief potential source of pollution is the manu-facture and maintenance operations, which in Table 6.8 have been assumed toemploy the current Danish mix of energy sources as energy inputs (to bothmanufacture and transportation). The impacts will decrease in proportion tothe possible future transition to larger penetration of renewable energy sources.Available accident statistics show an exceedingly small risk to members of thegeneral public being hit by expelled rotor blades in cases of rotor failure(Sørensen, 1981b).

The work environment at manufacturers of windmill components is similarto that of other equipment manufacturers, while the work environment fortower building, assembly and maintenance resembles that of work in thebuilding industry, with open-air activities and scaffold work at a height. Withproper safety precautions, such work generally offers a varied and challengingenvironment. The accident rates assumed in Table 6.8 are taken from industrialstatistical data for the relevant sectors. One significant component has his-torically been electrocution accidents during improper maintenance attempts,often by a local owner rather than by professional teams. The current moveaway from privately to utility owned wind turbines should reduce this risk.

Health problems are primarily associated with the industrial part of manu-facture, including in particular the use of epoxy resins in blade manufacture.Modern production technology should confine this step of production to closedspaces with fully automated facilities, implying that employees only do control-room work, so that the risk of exposure to harmful chemicals would basicallybe accidents. Numerical estimates of health and accident risks are uncertain,because of the aggregate nature of available statistical data and because of thedifferent production techniques used by different wind turbine manufacturers.

The social benefit of wind turbines is based on the electric power produced(and as before taken as the price consumers are willing to pay). This benefitmight decrease at higher penetration of wind energy in the power supply sys-tem, if the variations of wind-produced power would occasionally requiredumping of excess power. The analysis therefore assumes that the intermittencyproblem has been solved, either by trade arrangements with neighbouringregions or by establishment of or access to storage facilities. The consequencesof increased length of transmission or of energy storage will have to be sub-jected to independent life-cycle investigations, implying a need for system-wideLCA, the subject of Chapter 8.

Wind energy can have an impact on details of the infrastructure of anelectricity supply system. If wind turbines are sited in a very dispersed fashion,the stresses on the power transmission network might be reduced owing toshorter average distances to consumers; if, on the other hand, large wind farmsare placed off-shore at windy locations far from consumers, transmission dis-tances may instead increase.


Table 6.8 Impacts from wind power, derived from Danish data (Kuemmel etal., 1997; Table 6.1; Sørensen, 2010a) and updated to 2010 prices.

Environmentalimpacts

Type ofimpact:emissions(g kWh–1) Uncertainty



Releases from fossilenergy currently used1. Turbine manufacture(6.6 GJ kW–1 rated)CO2 (leading togreenhouse effect)

12.1 L 1.6 1.1–2.5

SO2 (leading to acidrain and aerosols)

0.05 L o0.01 H, r, n

NOx (possibly aerosolsand health impacts)

0.04 L B0 H, r, n

particulates (lungdiseases)

0.002 L o0.01 H, r, n

2. Operation (2.2 GJkW–1 over 20-yearlifetime)CO2 (leading togreenhouse effect)

3.8 L 0.9 0.6–1.2

SO2 (leading to acidrain and aerosols)

0.01 L 0

NOx (possibly aerosolsand health impacts)

0.02 L 0

particulates 0 L 0Other

Gearbox noise increaseat about 1 km distance

o1 dB(A) H, l, n

Noise from wind–bladeinteraction

o3 dB(A) o0.1 total

Land use 10 m2 kW–1 NQVisual intrusion � like church

towers, etc.NQ

Social impacts

Occupational injuries(manufacture andmaterials)

1. Turbine manufacture,death

0.03 per TWh L 0 L, l, n

major injury 0.9 per TWh L 0.1 L, l, nminor injury 5.0 per TWh M 0 M, l, n

2. Operation (samecategories combined)

0 M, l, n

214 Chapter 6

Security of supply is generally high owing to the many independent gen-erators, but with the qualifications related to the variability of wind conditions.Failures may occur in all parts of the system, but not the common-mode fail-ures characterising large centralised power stations and particularly nuclearreactors. Up to 10% of Danish wind turbines experience a component failure inany given month. About 4% of the failures result in replacement of a com-ponent (e.g. a blade, the generator, the control unit), according to the variousissues of the newsletterWindpower Monthly/Windstats Quarterly. These failuresare represented in the overall O&M costs, which also include an insurancepremium. A wind power system thus has little sensitivity to individual turbinefailures, owing to the modular nature of the system. Because of the short timelag between deciding to build a turbine and its becoming operational, windtechnology is much less sensitive to planning errors (e.g. wrong forecast offuture loads) and changes in criteria used for selecting technology than systemswith several years lag between decision and operation.

The impacts of wind power generation (for one turbine or a cluster of turbines)is summarised in Table 6.8, together with their valuation in 2010-h per kWh.


Economic impacts


40–70

Resource use (energypayback time given)

1.0 y L NQ

Labour requirements(manufacture)

9 person-yMW–1

L NQ

Import fraction (in thecase of Denmark)

0.28 L NQ

Benefits from power sold(without influence fromintermittency)

100–300

Other impacts

Supply security (varia-bility if wind is high,entry based on plantavailability)

high NQ

Robustness (up-frontinvestment, entry basedon technical reliability)

high NQ

Global issues (non-exploiting policy)

compatible NQ

Decentralisation andchoice (less with largesize)

good NQ

Institution building (gridrequired)

modest NQ

aNQ¼ not quantified. Values are aggregated and rounded (to zero if below 0.0005 h kWh–1).bL, M, H¼ low, medium or high uncertainty; l, r, g¼ local, regional or global impact; n, m,d¼ near, medium or distant time frame.


Wind power is consistent with keeping options open for the future. It might beabandoned without repercussions (in contrast to e.g. nuclear installations andwaste repositories, which have to be looked after long after decommissioning),and wind power is consistent with goals of creating an energy system with as littleenvironmental impact as possible. It constitutes a national solution and it thusavoids global issues such as the over-use of resources by the traditionally richcountries, while at the same time it ensures national independence of energysupply, in proportion to its penetration.

Wind power started with broad participation in the decision-makingprocesses as one of several possible decentralised solutions permitting localcommunities to choose their own solutions. This initial advantage of dispersedownership is currently largely lost, as wind power has become a target forexisting large utility companies, owing to its competitive price compared toboth conventional and other renewable solutions. A key issue in at leastmaintaining the option of local ownership is the fixation of prices for buyingfrom and selling power to the national grid (questions of feed-in tariffs and netmetering). Some of the associated social and systemic impacts would be difficultto quantify, but they are important to place on the table in a democratic debateon the preferred energy supply for a given country, and an attempt is made to atleast flag them in Table 6.8.

Life-cycle analysis for large wind turbines placed in Spain and France hasrecently been made. The Spanish study gives the results in units of ‘‘ecopoints’’taken directly from commercial software (Martinez et al., 2009). The impactscoring highest is from the foundation of the turbine and is called ‘‘inorganicrespiration’’, presumably referring to human inhalation of pollutants such asparticulate matter from manufacture of the concrete (called ‘‘cement’’ in thearticle, although the binder cement is only part of what constitutes the concreteused in foundations and towers for wind turbines). Since the source of the highscore is not disclosed, one can only guess what may have induced it. A likelypossibility is that the inventory data of the commercial software describes thefact that making concrete in principle may cause emission of large amounts ofparticulate matter. However, if proper precautions are taken, both in themanufacture and in workers’ handling during construction (wearing protectivemasks), substantial reductions of impacts can be achieved. The conclusionmade by the authors, that steel appears to be much better to use instead ofconcrete, thus seems to be an example of the artefacts produced by the‘‘automated’’ commercial LCA software, and particularly of the process usedto construct ‘‘ecopoints’’ for inventory substances without detailed modellingof the pathways to (in this case) human ingestion that may exist in the concreteapplication at a specific location.

The French study by Tremeac and Meunier (2009) compares a 4.5 MW windturbine placed in S. France with a miniature 250 W turbine. Transportation ofthe large turbine (900 km) and tower (1200 km) from the sites of manufacture isfound to contribute nearly half of the life-cycle health impacts (Table 6.9). Thestudy again uses commercial LCA software (from Pre Consultants), focusingon environmental emissions. Occupational impacts do not seem to be included.

216 Chapter 6

Table 6.9 Impacts from a 4.5 MW wind turbine in France (Tremeac andMeunier, 2009; Tables 5.3 and 6.1).

Environmentalimpacts




Releases from fossilenergy currently used

NA

1. Turbine manufacture(11.7 GJ kW–1 rated)greenhouse gases(CO2 equivalent)

13.4 (g kWh–1) L 1.3 1.2–2.0

SO2, NOx, particles(causing healthimpacts)

1.2� 10–8

(DALYkWh–1)

M 0.8 M, r, n

2. Transportation(Finland to France,truck)

Depends onmode oftransport

greenhouse gases(CO2 equivalent)

5.0� 2.5(g kWh–1)

H 0.5� 0.2 0.3–0.7


9� 10–9

(DALYkWh–1)

H 0.6� 0.3 0.3–0.9

3. Operation (1.2 GJkW–1 over 20-yearlifetime)greenhouse gases(CO2 equivalent)

0.9 (g kWh–1) L 0.1 � 0.05


7� 10–10

(DALYkWh–1)

M 0.05 M, r, n

Decommissioning(transport and energy)

0.9 (g kWh–1) M 0.1 M, r, n

Materials recycling afterdecommissioning

–3.0 (g kWh–1) M –0.3 M, r, n

Ecosystem impacts(mainly frommanufacture)

10–5 m–2 y–1

speciespotentiallylost

B0 H, l, n

Noise NQLand use NQVisual intrusion NQ

Social impacts

Occupational injuries(manufacturing andmaterials)

1. Turbine manufacture NA L NQ L, l, n2. Operation NA L NQ L, l, n


Greenhouse gas emissions from fossil fuels used in manufacture are seen to bein good agreement with the earlier study behind Table 6.8. The manufacturerappears less efficient in energy use per kW rated, which is strange in light of thefact that the quoted data source is the Vestas (2006a) study discussed below.The negative contribution to human health from emissions of SO2, NOx andparticles is also surprisingly high, not just for the trucks used for transportationbut also for manufacturing the wind turbine. Non-environmental impacts arenot included in the French study.

The turbine manufacturer Vestas has produced LCA reports on its windturbines placed onshore or offshore (Vestas, 2006a, 2006b). Emission of par-ticulate matter is included in the second study of an onshore turbine but not inthe first one, considering both on- and offshore siting (Table 6.10). A detailedaccounting of input materials and their impact rating in the commercial soft-ware used (from GaBi) is given, but without valuation. The smaller impactfrom greenhouse gases, compared with the turbine of Table 6.8, is primarily dueto Vestas assuming that the energy it uses in production to a large extent comesfrom either hydro (70%, from Norway) or wind (5%) and to a smaller degreedue to the larger energy production relative to manufacturing effort, comparedwith the smaller turbine used for the data in Table 6.8. Vestas in this way takesadvantage of the electricity market liberalisation that allows them to purchasemost of their power from Norway. However, although there are no greenhousegases from hydropower, there are environmental costs associated with dambuilding and reservoir establishment, which are probably far larger then theecosystem impacts from identified emission sources. The remaining 30% ofenergy inputs follows the Denmark power mix, with 20% wind.

The energy payback time is smaller than for the smaller turbine considered inTable 6.8, but there is a much smaller energy input to manufacture and


Economic impacts

Direct costs (power &delivery)

NA (40–70)


0.6 y L


NA L NQ

Import fraction (in thecase of Denmark)

NA L NQ


NA (100–300)

Other impacts

NA NQ


218 Chapter 6

Table 6.10 Impacts from Vestas VX-82 1.65 MW wind turbine (Vestas,2006b; Table 6.1; Sørensen, 2010a)

Environmental impacts




Releases assume energy mixcurrently used. Totallifetime energy use¼ 2.06GJ kW–1 rated

NA NA

Selected emissions to airand waterwaysCO2 equiv. (greenhouseeffect)

7 L 0.7 0.5–1.0

SO2 equiv. (acidification) 0.04 L o0.1 H, r, nNOx equiv. (ecology,health)

0.04 L B0 H, r, n

particulates (health) 0.006 L o0.1 H, r, nvolatile organics (health) 0.005 L –inorganic salts (waterecology)

0.1 L –

organic compounds(water ecology)

0.001 L –

Hazardous waste 0.05 L –Approximatedistribution (%)

1. Turbine manufacture 922. Transportation tosite of use

8

3. Operation (20 y) 04. Decommissioning –c

Noise, land use, visualimpact

NA NQ

Social impacts

Occupational impacts NA L NQ L, l, n

Economic impacts

Direct costs (power &delivery)

40–70


0.6 y L –

Labour requirements,import fraction

NA L NQ


100–300

Other impacts

NA NQ

aNA¼ not analysed; NQ¼ not quantified. Values are aggregated and rounded (to zero if below0.0005 h kWh–1).bL, M, H¼ low, medium or high uncertainty; l, r, g¼ local, regional or global impact; n, m,d¼ near, medium or distant time frame.cPositive impacts around 30% of the negative found in terms of avoided new production forrecycled materials.


operation (2.0 GJ kW–1 a compared to 8.8 GJ kW–1), so the energy paybacktime should have been even smaller. In any case, as Vestas correctly recognises,once the concrete impacts of energy use are accounted for, adding energypayback to the impact list would be double counting. The software used byVestas avoids the overestimation of transportation impacts found in the Frenchstudy of Table 6.7.

The bottom line of the three wind-energy studies shown in Tables 6.8–6.10 isin any case that the overall life-cycle impacts of wind power are very smallcompared to most other energy systems in use today.

6.3.2 LCA of Photovoltaic and other Solar Energy Systems

Even more than for wind power, the LCA impacts of a photovoltaic (PV)power system are dominated by the manufacturing process. The manufactureof crystalline silicon panels involves the main steps depicted in Figure 6.3, with

Figure 6.3 Main steps involved in the LCA chain for monocrystalline siliconphotovoltaic cells.

220 Chapter 6

elaborate growth of crystals on seeds before slicing wafers; for amorphoussilicon panels, wafer formation, cutting and surface doping steps are replacedby direct vapour deposition of doped gases onto a substrate. Multi-crystallinecells are produced by direct casting ingots of, say, the silicon material and thenslicing it into wafers. The newest ribbon technology produces the wafers in onestep by a continuous thin-film process.

Different types of solar modules forming the panels mounted on buildings orstand-alone ground-based arrays differ with respect to use of substrates, covermaterial, anti-reflection films and support structure. The cells may have surfacetextures and elaborate grooving patterns for conductors and modules mayincorporate reflectors to concentrate the light modestly; in some cases, bypassdiodes and built-in inverters (which otherwise would be separate system com-ponents) are also used. Finally, the mounting of panels in arrays may involvededicated support structures, if not integrated into building facades or roofs.

On the system side, further transformer equipment may appear, as well asbattery storage or backup devices in the case of stand-alone systems. Decom-missioning and dismantling of the solar equipment is expected to follow therecycling and reuse patterns emerging for the building industry in general,probably as a front-runner industry.

Assessing impacts has traditionally used data from the microelectronicsindustry. The basic raw material for silicon cells is silicon dioxide (sand,quartzite). It is reduced to metallurgical grade silicon in arc furnaces. Bothmining and reduction may produce dust (and hence risk of silicosis). The fur-naces additionally produce carbon monoxide and a range of silicon-containingcompounds that appear as dust and might be inhaled, e.g. during cleaningoperations (Boeniger and Briggs, 1980). In the past the photovoltaic industryhas used scrap material obtained inexpensively from the microelectronicsindustry, but now nearly all modules are produced from solar grade material, amuch less expensive product compared to microelectronics grade silicon,because solar cells are macroscopic devices not requiring the extreme minia-turisation of microelectronics.

The next step is production of silane (SiH4) in the case of amorphous cells ortrichlorosilane for crystalline cells, usually produced in a fluidised bed andsubsequently purified to multi-crystalline silicon, for subsequent doping andgrowth of mono-crystalline ingots. These are ground to a cylindrical shape andsliced into wafers, which are then cleaned. Multi-crystalline cells may beobtained by slicing the ingots made of cast multi-crystalline silicon in a processsimilar to that used for crystalline cells, or they may be formed by vapourdeposition similar to the process for amorphous cells, but at considerablyhigher deposition temperatures. The material used for mono-crystalline cells iscurrently thicker and more expensive, also in input energy, than the thin-filmmaterials that already are beginning to dominate the market.

The chlorosilane production involves hydrochloric acid and the chlor-osilanes themselves are corrosive, skin and lung irritating as well as toxic.Workers are required to use protective clothing and facemasks with filters.Further risks are posed by hydrogen/air mixtures that are present, which could


ignite and explode. One such case has been reported (Moskowitz et al., 1994).For amorphous silicon, special precautions are needed for handling silane gas,as it ignites spontaneously. One solution is never to store larger quantities ofsilane gas and to use special containers designed to avoid leakage even in casesof strong pressure increases. Fabrication sites are typically equipped withautomatic fire-extinguishing devices and unfastened roofs that may help reducedamage in case of explosions.

Vacuum growth of crystalline material may involve dispersal of oily aerosolsthat have to be controlled by wet scrubbers and electrostatic filters (CECS-MUD, 1982). Doping of p-type material can involve boron trichloride, whichreacts with water vapour to form acids easily absorbed through the skin, ordiborane, which is a strong irritant and flammable as well. The n-type doping atthe top layer of a crystalline cell uses phosphorus diffusion of POCl3 or P2O5 insealed environments, whereas the n-type doping of amorphous cells mayinvolve phosphine (PH3), a highly toxic substance widely used in the semi-conductor industry (Watt, 1993).

Grinding and cleaning of wafers produce a silicon-containing slurry withremains of the detergents used. An alternative is ribbon growth, which avoidsthese problems (CECSMUD, 1982). Amorphous cell manufacture also involvesa number of cleaning agents. Etching of surface textures may employ a varietyof techniques, selected on the basis of concern for recycling of chemicals andreduction of the use of toxic substances (Watt, 1993). Workers have to wearprotective clothing and high levels of ventilation are required. Drying usesliquid nitrogen and may be fairly energy intensive.

Screen printing of electric circuits involves possible work environmentproblems familiar to themicroelectronics industry (caused bymetal particles andorganic solvents). Laser grooving involves the laser safety precautions forradiation and fires, and the application of coatings such as titanium oxide orsilicon dioxide is considered relatively harmless. Cell testing and light soaking ofamorphous cells (in order to avoid restructuring degradation) should be done inspecial rooms owing to the risk of exposure to ultraviolet radiation. Personnelreplacing bulbs should wear safety masks and gloves, if pressurized kryptonlamps are used. Polymer coatings such as ethylene–vinyl acetate (EVA) orpoly(vinyl fluoride) (Tedlar) may have some health impacts during their manu-facture. If soldering is used in module assembly, fumes have to be controlled.

The tendency is for increasing use of robots in the manufacturing processlines, leading normally to reductions in health impacts for remaining workers.Cells based on cadmium telluride and gallium arsenide involve different typesof potential impacts (Moskowitz et al., 1995), which could lead to potentiallyhigh life-cycle impacts (Alsema and van Engelenburg, 1992). Furthermore,these cells are based on expensive materials, the natural abundance of which ismuch smaller than that of silicon and therefore total recycling is required. Alarge fraction of the calculated impacts is related to releases of toxic materials infires involving solar panels. The photovoltaic industry is aware of these pro-blems and aims at controlling or replacing chemicals identified as troublesome(Patterson, 1997).

222 Chapter 6

There are few impacts during the operation of photovoltaic installations.Land use may be an issue for central plants, but not for building integratedpanels. Albedo changes caused by the presence of the panels are not significantlydifferent from those of alternative roof surfaces in the case of roof-integratedcells, but could have climatic impacts in cases of large, centralized solar plants,e.g. when located in desert areas. Reflections from panels located in cities couldbe annoying and considerations of visual impacts will generally require carefularchitectural integration of panels. In some areas, cleaning of solar panel sur-faces for dust may be required and electronic control equipment such asinverters may cause radiofrequency disturbances, if not properly shielded.

As mentioned for non-silicon cells, the behaviour of panels during fires is animportant consideration. The necessity for recycling of solar cell materials andequipment has also been advocated (Sørensen, 1993) and today put into effectby most manufacturers.

For a silicon-based photovoltaic system integrated into a building, the LCAimpact evaluation is presented in Table 6.11. The modest negative impactsmostly occur during the manufacturing phase, and substantial positive impactsin the area of impacts on the local and global society. The impacts duringmanufacture to a large degree result from the use of fossil fuels for mining,manufacture and transport, according to the marginal approach taken in thereferences used. However, also the handling of chemical substances such as H2,HF, HCl, H2S, SiH4 and SiHCl3 contribute to accident and injury rates abovethe industrial average. Increasing use of robot handling in manufacture iscounted on to reduce negative impacts as the photovoltaic industry grows.

The source used for energy payback times and carbon dioxide emissions isYamada et al. (1995). Other estimates are similar, with current energy paybacktimes for a-Si and c-Si systems in the range of 2–3 years and future ones below1 year (Alsema, 1997; Frankl et al., 1997). Other studies of greenhouse gasemissions estimated current emissions at 100–200 g CO2-equivalent per kWh ofpower produced, declining to some 40 g CO2-equiv per kWh after 2010 (Donesand Frischknecht, 1997).

The photovoltaic case is special in that the direct cost at present is furtherfrom being competitive than that of most other renewable energy solutions. Ifthe cost continues to decrease in the future, many of the impacts will alsodecrease, because they are associated with material use or processes that willhave to be eliminated or optimised in order to reach the cost goals.

The cost per kWh produced obviously also depends on the location of theinstallation. The average solar radiation in, say, Denmark is about half that inArizona or the Sahara, and the cost per kWh produced is therefore twice ashigh (in addition to problems associated with the poor correlation betweenseasonal solar production and electricity load, found at locations without highrequirements for space cooling).

For variable resources such as solar energy, there will be additional costs incase the penetration becomes significant compared with the overall systemservices by a common grid network, because in that case additional equipment(for energy storage or transmission between regions) must be introduced to deal


Table 6.11 Estimated impacts from present and future rooftop photovoltaicenergy systems based onmulti-crystalline (m-Si) or amorphous (a-Si)silicon cells, placed at average European locations (Sørensen andWatt, 1993; Yamada et al. 1995; Sørensen, 1994a, 2010a; Table 5.3).


Type ofimpact:emissions(g kWh–1)a,b Uncertainty

Monetisedvalue (2010mh kWh–1)b

Uncertainty& rangesc

Releases from fossil energyin all steps of cycleCO2 (m-Si now andfuture; could become 0)

75 (10) L H, g, m

CO2 (a-Si now andfuture; could become 0)

44 (10) L H, r, n

SO2 and NOx (m-Si nowand future)

0.3 (0.04) L H, r, n

SO2 and NOx (am-Si nowand future)

0.2 (0.04) L H, r, n

Greenhouse effect fromfossil emissionsm-Si (now and future) 7.5 (1.0) 0.7–3.5a-Si (now and future) 4.4 (1.0) 0.3–2.1

(large reduction to followwhen non-fossil energy isno longer used inproduction)

(or 0) 0

Mortality and morbidityfrom fossil air pollution

m-Si (now and future) 0.4 (0) H, r, na-Si (now and future) 0.3 (0) H, r, nLand use (zero if buildingintegrated)

0 0 L, l, n

Visual intrusion NA NQ

Social impacts

Occupational injuries1. Silicon provision and cell

manufactureB10–12 0.1 M, l, n

2. Panel assembling,mounting and installing

o10–12 o0.1 L, l, n

3. Operation B0 0 L, l, n4. Decommissioning o10–12 o0.1 L, l, n

Economic impacts

Direct costs (at present) 250–500 MEnergy payback time(now and future)

3 (0.5) y

Labour requirements(now and future)

40 (4)person-yMW–1

NQ

Benefits from power sold(ignoring intermittency)

100–300c

224 Chapter 6

with the fluctuating power production. This intermittency problem, which canbe specified by power duration curves (Sørensen, 1976, 2010a), may add sub-stantially to the cost of direct use of solar energy.

Table 6.12 summarises the results of a recent LCA study for different photo-voltaic technologies (Fthenakis and Kim, 2010). The environmental emissions arefound largest for mono-crystalline cells, smaller for multi-crystalline cells, stillsmaller for ribbon-type cells and smallest for cadmium–tellurium cells. Lookingat the mounted modules, the smaller efficiency of CdTe cells shows up as slightlylarger impacts from greenhouse gases, but in all cases the negative impactsassociated with the use of fossil fuels will of course gradually disappear as theenergy system (hopefully) changes away from fuels emitting greenhouse gases.Compared to Table 6.11, it is seen that a gradual diminishing of energy input tothe manufacturing process has materialised over the recent decade. A furtherpositive turn as regards damage size comes from the fact that the current volumeof PV manufacture is large enough to support its own solar-grade siliconindustry, refining the base material to the required quality for large-area appli-cation but no longer to the higher quality norms of the microelectronics industry.

The study assumes annual average solar irradiation of 205 W m–2 in some ofits LCA work and 194 W m–2 in the rest, both of which are in the high end asfar as global solar resources are concerned. Based on a ground-mountedinstallation in Arizona, a fairly detailed LCA inventory for the balance ofsystem (BOS), i.e. what is needed beyond the modules, has also been made.BOS includes support structure, land (in this case), inverters and moduleinterconnections ensuring low sensitivity to part-shadowing or part-failure.Social impacts are estimated as far as the manufacturing phase is concerned,considering the particular substances entering into solar cell processing: tri-chlorosilane for manufacture, hydrogen fluoride for etching the power channelsfrom the cell surface to contacts and hydrochloric acid for cleaning, all used inm-Si cell production. A decade of industrial experience indicates injury rateshigher than for the average production industry, but possibly declining with


Other impacts

Supply security (plantavailability)

high NQ

Robustness (technicalreliability)

high NQ

Global issues(non-exploiting)

compatible NQ

Decentralisation and choice good NQInstitution building(grid required)

modest NQ

aThe alternatives in parentheses are estimated to be the most likely technologies for the future.bNA¼ not analysed; NQ¼ not quantified. Values are aggregated and rounded (to zero if below0.0005 h/kWh).cL, M, H¼ low, medium or high uncertainty; l, r, g¼ local, regional or global impact; n, m,d¼ near, medium or distant time frame.


Table 6.12 Estimated impacts from ground-mounted PV energy systemsbased on crystalline (c-Si), multi-crystalline (m-Si) or ribbon (r-Si)silicon cells and CdTe cells, exposed to an average of 194 or 205W solar radiation (S. Europe, Arizona) (Fthenakis and Alsema,2006; Fthenakis and Kim, 2010; Tables 5.3 and 6.1).


Type of impact:emissions(g kWh–1)a Uncertainty



From fossil energy incell and modulemanufacture

1.2–3.7 H, g, m

CO2 equiv. (c-Si, m-Si,r-Si, CdTe technology)

37, 29, 22,12–18

L H, r, n

SO2 (c-Si, m-Sitechnology)

0.142, 0.138 L H, r, n

SO2 (r-Si, CdTetechnology)

0.105, 0.060 L H, r, n

NOx (c-Si, m-Sitechnology)

0.079, 0.078 L H, r, n

NOx (r-Si, CdTetechnology)

0.059, 0.032 L H, r, n

Cd, Hg, As, Cr, Pb, Niemissions (ordered)

3� 10–7 to3� 10–5

From frame and balanceof system

0.6–0.9 H, g, m

CO2 equiv. (c-Si, m-Si,r-Si, CdTe technology)

8, 8, 8, 9 to 6 L H, r, n

SO2 (c-Si, m-Sitechnology)

0.023, 0.023 L H, r, n

SO2 (r-Si, CdTetechnology)

0.027, 0.020 L H, r, n

NOx (c-Si, m-Sitechnology)

0.013, 0.014 L H, r, n

NOx (r-Si, CdTetechnology)

0.016, 0.010 L H, r, n

Health impacts from theemissions listed

o0.3

Land use NA NQVisual intrusion NA NQ

Social impacts

Occupational injuries Cases1. Manufacture (toxic andflammable substances)

4� 10–12

(10–10–10–13)o0.4 M, l, n

2. Plant construction (falls,physical injuries)

NA NQ L, l, n

3. Operation anddecommissioning

NA NQ

226 Chapter 6

time (Fthenakis and Kim, 2010). Because the annual data exhibit variationsexceeding three orders of magnitude, the valuation attempted in Table 6.12 is tobe considered very preliminary.

The direct cost is more favourable than that of Table 6.11, owing to thehigher solar radiation regime assumed, but the general conclusions regardingenergy payback and pollution reduction are very similar.

6.3.3 LCA of Hydropower and Geothermal Energy

Large hydropower installations may have severe impacts, e.g. if areas areflooded to establish reservoirs, if people living there are displaced, if the floodedareas possess natural or archaeological/historical artefacts (examples are AbuSimbel on the Nile and the Ilisu Dam in Turkey) and of course as a result oflarge dam failures, which according to the survey of Sovacool (2008a)(illustrated in Figures 5.54 and 5.55) make hydropower exceed all other energysources in causing accidental death.

Table 6.13 gives a summary of results from an LCA study of a largehydropower plant in Brazil (Ribeiro and Silva, 2010). The artificial lake createdbehind the dam is 1350 km2 and the installation is estimated to produce 8.88PWh over a 100-year period. The turbine rating is 14 GW, so the averagecapacity factor is 0.73. The main construction of the dam and power stationtook place between 1975 and 1986, but further work and the addition of moreturbines continued to 2004.

The impacts evaluated are seen to be small and mainly derive from themodest fraction of Brazilian energy coming from sources other than hydro-electricity. However, some of the major concerns listed in the start of thissection have not been assessed.

In order to avoid the problems of reservoir creation and dam safety, muchhydropower activity is currently directed at much smaller-scale schemes withseveral modest expansion of river flows rather than single, large reservoirs, in


Economic impacts

Direct costs (at present;S. Europe, S. USA)

efficiency 14%to 9%

175–350

Energy payback time 2.5 y to 1 yLabour requirements NA NQBenefits (power sold,ignoring intermittency)

100–300

Other impacts

NA NQ



Table 6.13 Life-cycle inventory and estimated impacts from the 14 GWhydropower plant Itaipu on the Parana River at the Brazil/Paraguay border (Ribeiro and Silva, 2010; Table 6.1; Sørensen,2010a).


Impact type:emissions(g kWh–1)a Uncertaintyb



Construction (Brazilianenergy mix 1975–1986)

0.04

CO2 0.445 L H, g, mSO2 0.002 L H, r, nNOx 0.003 L H, r, nparticulates 0.020 L H, r, nCH4 B0 L H, r, nCO 0.071 L H, r, n

100-year operation(current Brazilianenergy mix)

0.11

CO2 1.120 L H, g, mSO2 0.002 L H, r, nNOx B0 L H, r, nparticulates 0.005 L H, r, nCH4 0.132 L H, r, nCO 0.141 L H, r, n

Health impacts fromemissions listed

o0.5 H, r, n

Land use 153 m2 GWh–1 L NQVisual intrusion NA NQEcology damage NA NQ

Social impacts

Occupational injuries NA NQPeople displaced NA NQAccidents NA NQ

Economic impacts

Direct costs (cost ofpower)

20–50

Energy payback time 0.25 yLabour requirements NA NQBenefits (power sold,ignoring intermittency)

100–300

Other impacts

NA NQ


228 Chapter 6

what is called a cascading system (Catalao et al., 2010). Such schemes wouldavoid several of the key negative impacts of large hydro projects.

Traditional geothermal power production is limited to sites with suitablegeological activity. CO2 emissions are usually modest, 9 g kWh–1 during con-struction and 2 g kWh–1 during operation in a Japanese case (Hondo, 2005).Other impacts are more difficult to assess. In some cases the pressure of theunderground steam diminishes after some decades of operation, signalling thatthis type of installation is not based on the average heat flow from the interiorof the Earth, but on some particular gas pockets of limited life. Geothermalsites usually emit unhealthy odours connected notably with the sulfur contentof the underground water cells (0.1–1.5 g H2S per kg of steam reaching thesurface; Barbier, 2002), and sometimes power generation at the sites is inconflict with deriving tourist incomes from the geyser activity because it maylower groundwater levels and reduce jet heights (Bromley, 2009).

A different line of geothermal usage attempts to draw energy from theaverage flows rather than from particular concentrated flows. This means waterof temperature below 200 1C, which can be used for low-efficiency power-and-heat production (Frick et al., 2010) or for plain district heating (Ungemach,2001), eventually with help from a heat pump (Saner et al., 2010). Constructingand operating the plants for utilisation of specific 100–200 1C geothermal for-mations at some 1.5 km depth uses more energy than traditional geothermalpower plants and emits some five times more greenhouse gases (50 g CO2

equiv., 0.4 g SO2 equiv. and around 0.06 g PO43– per kWh, according to Frick

et al., 2010).The even lower 50–100 1C geothermal heating (10 kW) and cooling (6 kW)

systems for single-family homes, combined with a 10 kW heat pump, that areconsidered by Saner et al. (2010) for three locations in Europe (S. Germany,Spain and Sweden), are found to have the impacts summarised in Table 6.14,based on an early (2008) version of the ReCiPe (2010) LCA methodology.

The study finds that impacts overwhelmingly occur in the operational phaseand over 87% comes from the use of electricity for the heat pump, for theaverage continental European energy mix. This implies that these impacts varyfrom about zero to twice the values indicated in Table 6.14 when going from arenewable energy-based power system (Norway) to a coal-based system(Poland). Similarly, the impacts from ozone-depleting gases and resourcedepletion pertain to the current average European situation. The energy inputto the system for the base case is 2 kW annual average and of this 0.5 kW iselectric power input to the heat pump; the rest is geothermal heat extracted.In most of Europe the cooling requirements are small, so provision of low-temperature heat is the main output from the system.

6.3.4 LCA of Hydrogen Production and Large-scale

Fuel Cell Plants

Fuel cell technologies hold promise for increased efficiency of vehicle tractionsystems as well as central power or combined power-and-heat (CPH) plants,


Table 6.14 Life-cycle inventory and estimated impacts from 10 kW/6 kWgeothermal heat pump system for low-temperature heating andcooling (Saner et al., 2010; Table 6.1; Sørensen, 2010a).





Construction and transport(European energy mix)

NA

CO2 equiv. 6 L H, g, mSO2 equiv. 0.04 L H, r, nN equiv. 0.007 L H, r, nP equiv. 0.0002 L H, r, nparticulates (PM10 equiv.) 0.02 L H, r, nCFC-11 equiv. 8� 10–7 L H, r, nvolatile organics 0.07 L H, r, ndichlorobenzene equiv. 0.25 L H, r, n

Operation (20 y, Europeanenergy mix)CO2 equiv. 171 L H, g, mSO2 equiv. 0.65 L H, r, nN equiv. 0.04 L H, r, nP equiv. 0.003 L H, r, nparticulates (PM10 equiv.) 0.21 L H, r, nCFC-11 equiv. 0.0002 L H, r, nvolatile organics 0.33 L H, r, ndichlorobenzene equiv. 13.5 L H, r, n

Impacts from greenhousegases

18 H

Health impacts fromparticulates, etc.

5–10 H

Ozone depletion (otherrefrigerant could be used)

small M

Ecosystem damage (land,fresh/ocean water)

some H

Land use 150 m2

GWh–1significant

Visual intrusion NA NQResource depletion(metals could berecycled)

fossil fuels,metals

variable

Social impacts

NA NQ

Economic impacts

Direct costs (cost ofheating/cooling)

NA NQ

Labour requirements NA NQBenefits (depends onheat/cool relativedemand)

80–150

230 Chapter 6

particularly in connection with the future use of hydrogen as an energycarrier. However, none of the fuel cell types under development has as yetreached the economy, the reliability or the lifetime needed for viability. Small,vehicle-suited fuel cells will be discussed in Chapter 7. Here, traditionalhydrogen production from natural gas will be analysed, followed by the use ofhigh-temperature fuel cell types suited for large-scale stationary powerproduction (surveyed more comprehensively in Sørensen, 2005).

Hydrogen production conventionally uses steam reforming of natural gas. Itgives rise to a number of impacts caused by emissions to the atmosphere (Table6.15), as well as impacts from the equipment production and disposal streamand from materials used, such as Ni catalysts, if they escape to the environmentdespite efforts towards complete recycling. The impacts caused by the emissionsinclude global warming (from emission of CO2, CH4, N2O, etc.), waterwayacidification (from SOx) and eutrophication (from N and P) and humanrespiratory diseases (from SOx, NOx, benzene and particles, as well as fromsoot and winter smog involving C formed by various side reactions; seeSørensen, 2005; Koroneos et al., 2004).

Table 6.15 shows that the externality cost of hydrogen produced on the basisof natural gas is high, owing to global warming caused by the emission ofgreenhouse gases. The cost of removing CO2 from the steam reforming plantwould, for the higher valuations of global warming impacts, appear to be lowerthan the global warming externality associated with not handling the CO2 issue.

Hydrogen production could alternatively be based on biomass resources,including cyanobacteria or algae. Some of these pathways will be discussedbelow. For renewable resources such as solar, wind or hydro, the naturalpathway to hydrogen production is through electricity and (presently alkaline)electrolysis. This pathway is suited for high-purity hydrogen (as required byproton exchange membrane fuel cells) and is in regular use today, but on a 5%level. The impacts are dramatically reduced by using electrolysis instead ofsteam reformation. Only the occupational impacts are presently larger, owingto their approximate scaling with the cost of the conversion equipment,whether conventional electrolysers or other fuel cells operated in reverse(Sørensen, 2005).

Centralised fuel cell plants are primarily expected to be solid-oxide fuel cells(SOFC), as past focus on molten carbonate and sulfuric acid cells does notseem to have led to commercially viable products (although these fuel cell typesstill have their proponents).


Other impacts

NA NQ



A life-cycle study of SOFC with comparison to competing technologieshas been performed by Pehnt (2003). A summary of results for the SOFC isshown in Table 6.16. Because of the high operating temperature, SOFCsauto-reform fossil fuels like natural gas or methanol and therefore avoid theneed to first produce purified hydrogen, a clear advantage as long as theenergy inputs considered are from non-renewable sources. For renewablesources, there is little advantage in first producing other fuels than hydro-gen. The Pehnt study only looks at fossil fuel input to the SOFC and finds

Table 6.15 Life-cycle impacts from natural gas conversion into hydrogen bysteam reformation (based on Spath and Mann, 2001; Tables 5.2and 6.1).

Impact category

Physicalamount (gkWh–1 of H2)

Monetisedvalue (2010mh kWh–1

of H2)Uncertainty(or range)

Environment EmissionsPlant operationCO2 320 32 (20–50)SOx 0.29 0.17a highNOx 0.38 0.23a highCH4 4.4 52 (20–100)benzene 0.042 NQCO 0.18 NQN2O 0.0012non-benzene hydrocarbons 0.79 NQparticulates 0.06 0.04a highNi catalyst material NA

Plant construction/decommissioning NA

Occupational Number

Industrial disease and accident 0.5 majorinjuryTWh–1

0.0004 low

Economic

Direct economy (production costs) 10–40b

Resource usage serious inlong run

NQ

Labour needs for manufacture 5 person-yMW–1

NQ

Import fraction NABenefits (value of product) 60–200

Other

Supply security low to fair NQRobustness medium NQGeopolitical competition NQ

aThe study assumes a mortality valuation of 2.4� 10–8 mh g–1 in 2001 and a morbidity valuation of1.1� 10–2 mh g–1 in 2001, inflated to 2010 by a factor of 1.2.bUpdated from Sørensen (2005).

232 Chapter 6

modest improvements in life-cycle impacts compared to those of combinedcycle natural gas power plants: 8% lower greenhouse gas emission, a similarreduction in summer smog, 35% reduction in acidification and 58%reduction in eutrophication.

The impact contribution coming from fuel cell manufacture can be expectedto diminish if the cost does, but the impact from efficiency improvement willremain low because, for example, a gas turbine already has an efficiency near

Table 6.16 Life-cycle impacts from a 20 MW SOFC power plant using non-renewable energy input (Pehnt, 2003; Table 6.1). Pehnt uses theamounts of emission divided by the daily German per capitaimpact for each category as an indicator of damage.

Environmental Impact



Uncertaintyand rangesb

Emissions from manu-facture and operation(fossil fuel used: 7.37MJ kWh–1)CO2 equiv. 415 L H, g, mSO2 equiv. 0.29 L H, r, nPO4

3– equiv. 0.023 L H, r, nvolatile organics 0.16 L H, r, nImpacts from greenhousegases

42

Health impacts frompollution

some H, r, n

Ecosystem damage (land,fresh/ocean water)

some H

Land use NA smallVisual intrusion NA smallResource depletion(metals, etc.)

fossil fuels,metals

NQ H

Social impacts

NA NQ

Economic impacts

Direct costs (cost of power) NA NQLabour requirements NA NQBenefits (depends on heat/cool relative demand)

100–300

Other impacts

NA NQ

aNA¼ not analysed; NQ¼ not quantified. Values are aggregated and rounded (to zero if below0.0005 h kWh�1).bL, M, H¼ low, medium and high uncertainty; l, r, g¼ local, regional and global impact; n, m,d¼ near, medium and distant time frame.


50% for pure power production and higher for CPH applications, while that ofthe SOFC is unlikely to surpass 70%.

A few other studies are available for molten carbonate fuel cells used in ships(Lunghi and Bove, 2003; further discussed in Sørensen, 2005), for alkaline cellsin building CPH applications (Staffell and Ingram, 2010) and for SOFCs asreplacements for diesel engines for producing power on ships (Strazza et al.,2010), concluding that a SOFC using, for example, natural gas as fuel has verymuch smaller impacts than a diesel engine. A table puts the global warmingcommitment of the SOFC as 0.48 and that of the diesel engine as 747 kg CO2

equiv. kWh–1, the latter likely a factor of 1000 too high. Proton exchangemembrane (PEM) fuel cells aimed at operation in decentralised installations (inbuildings and vehicles) will be discussed in Chapter 7.

6.3.5 LCA of Food Provision

Food is more than energy but food energy is part of the energy system, a factthat is more obvious when turning to renewable energy sources, as thesecomprise biomass, which can have uses both as food, biofuels and raw material(in the chemical industry, timber industry, etc.), sometimes in harmony witheach other and other times in competition.

Early studies of environmental impacts from agriculture often did notinclude the full life-cycle chain comprising such activities as shipment ofhigh-protein side-crops from South America to Europe, with the associatedimpacts from both production and transport. The first efforts to account forenergy flows in agriculture were made by Odum (1963) and in more detail byAnsbæk et al. (1973) and Sørensen (1994b, 1994c). Life-cycle studies of foodproduction chains have subsequently appeared, both for primary agriculture,for raising livestock and for fish and aquaculture activities. In addition, LCA ofhuman diets has been performed (e.g. Davis et al., 2009). Table 6.17 looks atthe impacts of a particular crop (wheat) in the UK, cultivated (99.3%) byconventional chemical farming in an agricultural system based on commercialfertilisers and pesticides (Williams et al., 2006). Some other studies are Nielsenet al. (2003) and Brentrup et al. (2004) (the latter seems to understate emissionsby a factor of 10).

Table 6.17 includes (fossil) energy used for production and delivery of fer-tilizers and pesticides in the non-ecological cases, and for farm vehicles andmachinery, with associated impacts. Nitrogen fertilizer use contributes 47 outof the 169 g CO2-equiv. kWh–1 in the UK study. The impact reduction found inthe Danish study for ecological (also called ‘‘organic’’) farming is partly due tousing only recycled fertilisers from manure and residues. The UK study alsolooks at ecological farming (only 0.7% in the UK), but finds land use perunit of harvest yield an unlikely three times higher in ecological than inchemistry-based farms, while in Denmark it is 1.5 times higher. Some generalreflections on the sustainability of land use have been made by Walter andStutzel (2009).

234 Chapter 6

For wheat grain, an energy content of 4.19 kWh kg–1 has been used, foredible beef meat 3.33 kWh kg–1 (a fraction of 0.43 times the live weight taken asedible, according to de Vries and de Boer, 2010), for milk 0.76 kWh kg–1 andfor edible chicken meat 1.34 kWh kg–1 (edible fraction 0.56).

Table 6.17 Life-cycle impacts from conventional wheat grain production inthe UK (Williams et al., 2006) or Denmark (Nielsen et al., 2003)and from ecological wheat farming in the Danish study (values inparentheses). Average annual grain yield 2.9 kWh m–2 y–1;assumed N-fertilizer application in UK case of 20 g m–2 y–1.

Environmental impact

Impact type:emissions(g kWh–1),relative toenergy in graina Uncertaintyb



Emissions from agri-cultural productioncycle (fossil energy used:0.6 MJkWh–1; rest is solar)CO2 equiv. 169–191 (67) M H, g, mSO2 equiv. 0.76–1.26 (1.07) M H, r, nPO4

3– equiv. 0.74 M H, r, nNO3 equiv. 15.5 (4.5) M H, r, nparticulates 0.17 M H, r, nvolatile organics,cadmium

small M H, r, n

Impacts from greenhousegases

17–19 H

Health impacts;ecosystem damage

some

Land use 0.35 (0.53) m2 ykWh–1

L large

Visual intrusion NA largeResource depletion fossil fuels, N, P modest

Social impacts

NA NQ

Economic impacts

Direct costs (cost ofwheat production)

NA 50–100

Labour requirements NA NQBenefits (consumer priceof wheat products)

NA 400–1000

Other impacts

NA NQ



The growth of crops directly for use in the energy sector has been suggested,both on marginal land and on prime food crop soils, disregarding the criticismof contributing to starvation by making food more expensive (e.g. the pro-duction of alcohol fuels in Brazil and the USA). These biofuels will be furtherdiscussed in Section 6.3.6. An LCA study of the cultivation of ‘‘energy crops’’aimed at such uses has been made by Hanegraaf et al., (1998).

Table 6.18 confirms the expected extremely high levels of impacts fromanimal food products compared with vegetable products. Beef (ox meat) causesthe highest damage, both in terms of global warming and for ecosystem impactsthrough acid rain, eutrophication and land use. It is seen that the price paid forthe meat products by consumers does not always cover the impact values. Theimpacts of dairy products appear to be lower, although still high, but there is achoice of allocation between meat and milk, which causes a factor two differ-ence in milk impacts relative to those given in Table 6.18 (see discussion inFAO, 2010). However, there is no disagreement that the majority of impactsshould be assigned to the meat, no matter if considering calves bred for meatalone or dairy cows primarily used for milk production but eventuallyslaughtered (Cederberg and Stadig, 2003). For pork (pig meat), the impacts arelower than for beef, but not as low as for chicken meat.

The chicken meat LCA impacts shown in Table 6.18 are still very significantin all categories, but the difference is smaller when considering edible meatrather than whole-carcass weight. Table 6.18 uses the conversion factors givenabove to express the impacts per unit of energy in the edible part of the animalproduct. One interesting observation is that the value of animal products asapproximated by the price that consumers are willing to pay for them is closerto, although still higher than, those of vegetable products than the sizes of theimpacts would suggest (compare Tables 6.17 and 6.18). The well-known pro-blem that meat constitutes a higher proportion of the human diet in many partsof the world than what is considered most healthy may well be related to thefact that meat is too inexpensive, not only as viewed from consideration of adiet balanced in relation to human health, but also as viewed in a life-cycleassessment focusing on damage from greenhouse gases, air pollution andeco-toxic substances.

Table 6.18 also list the amounts of water required for the growth of wheatcrops and raising of animals for meat and milk, based on Chapagain andHoekstra (2004). The valuation is put at near zero, because the LCA studies arenorth European and pertain to areas where natural water usage by agricultureis not threatening water supplies. The situation may be quite different in aridregions both near the equator and also in subtropical zones in southern Europeor the USA.

Tables 6.17 and 6.18 still leave a number of impact categories unaccountedfor, pointing to the need to discuss future food supply in a broader context,towards which the studies made so far are only a beginning. There are a numberof issues in all such studies, related to both uncertainty and to a general dis-cussion of mankind’s future as regards population size and food provision.

236 Chapter 6

Table 6.18 Life-cycle impacts of selected animal food products (Williamset al., 2006; de Vries and de Boer, 2010; Chapagain and Hoekstra,2004; Table 6.1). Translated into impacts per kWh of edibleproduct energy content.

Environmental impact




Life-cycle impacts: beef(ox meat)fossil energy use (5.6times meat content)

20 MJ kWh–1 M

CO2 equiv. (globalwarming)

11 174 M 1117 H, g, m

SO2 equiv. (acid rain) 328 M large H, r, nPO4

3– equiv.(eutrophication)

107–180 M large H, r, n

land use (range andfield, during life of ox)

16 m2 kWh–1 M very large M, r, n

water use 4.6 m3 kWh–1 M near zero M, r, nLife-cycle impacts: milkproductsfossil energy use 33 MJ kWh–1 MCO2 equiv. (globalwarming)

1387 M 139 H, g, m

SO2 equiv. (acid rain) 21 LM modest H, r, nPO4


8.4 M modest H, r, n

land use 1.4 m2 kWh–1 M significant M, r, nwater use 1.3 m3 kWh–1 M near zero M, r, n

Life-cycle impacts: chickenmeatfossil energy use 16 MJ kWh–1 MCO2 equiv. (globalwarming)

6130 M 613 H, g, m

SO2 equiv. (acid rain) 231 M considerable H, r, nPO4


65 M considerable H, r, n

land use 8.5 m2 kWh–1 M large M, r, nwater use 2.9 m3 kWh–1 M near zero M, r, n

Visual intrusion NA large

Social impacts

NA NQ

Economic impacts

Direct costs (cost of meat/dairy production)

100–700

Labour requirements NA NQBenefits (consumer priceof meat/dairy products)

500–1500


Also, one should not forget that the primary biomass growth delivers morematerial and energy than that reaching the dinner table. Some of these mate-rials (straw and husk and refuse) can be used as fibres or for energy purposes,e.g. in furnaces or in biofuel production (see next subsection), and thus therewill be a question of distributing the damage between food and the other end-products. This allocation issue continues for animal husbandry, where theimpacts should be distributed over dairy products, edible meat products andother useful parts of the slaughtered animals.

Furthermore, there are significant variations in agriculture among regions ofthe world. For example, a Swedish dairy cow produces some 7000 kg milk peryear (plus 500 kg for one calf per year) and some 200 kg bone-free meat whenslaughtered (typical life 2.5 y, about twice as long for beef cows) (Cederbergand Stadig, 2003). The world average milk production per cow is 3.5 timeslower (FAO, 2010) and, consequently, life-cycle impacts from milk products indifferent parts of the world can be very different. The reasons include differ-ences in pasture humidity and temperature, with the highest global warmingimpacts in warm, arid regions (such as sub-Sahara, India, Australia). Moretechnical reasons for differences between studies may include varying com-pleteness in treating imports and exports, inclusion of farm vehicle andmachinery energy use, and differences in the manufacture of fertilizers, whichvary considerable according to the method of manufacture.

Ecological (‘‘organic’’) agriculture avoids many of the negative impacts byusing considerably less fossil energy inputs and no industrial fertilizers orpesticides. In consequence, the LCA impacts are smaller, despite decreases innet output amounting to 10–50% per unit of land area used for growth.

An important part of the food supply industry is fish and shellfishproducts. In particular, the importance of aquaculture in estuaries and oceanfarms is expected to grow in the future as world population grows. This calls forlife-cycle analysis, not only of the farming procedure used, but also of thehealth impacts that derive from previous abuse of the rivers, lakes and oceans,by dumping toxic and radioactive waste in large quantities. Partial LCA studieshave been made for tuna fishing (Hospido and Tyedmers, 2005), for ocean fish-farms (Aubin et al., 2009) and for mussel aquaculture (Iribarren et al., 2010).

6.3.6 LCA of Gaseous and Liquid Biofuels

Biofuels comprise conventional biomass for combustion and gaseous or liquidfuels obtained by industrial processing and conversion of biomass material of


Other impacts

NA NQ


238 Chapter 6

plant or animal origin. In principle, energy uses of biomass are in competitionwith the traditional uses of biomass for food and for structural materials, fibresfor fabric or paper, or other feedstock for industrial uses. It is common todenote biofuel technologies using plant grains in direct competition with foodusage as ‘‘first-generation biofuels’’ and those using only residues or waste fromthe food chain as ‘‘second-generation biofuels’’.

The examples given in this section deal with large-scale combustion, e.g. incombined power and heat (CPH) plants, with biogas and a range of liquidbiofuels aimed at application in the transportation sector as a replacement forgasoline and diesel fuels. The transportation biofuels will be further discussedin Chapter 7, in connection with the LCA of person and goods transportationtechnologies, as will decentralized uses of fuelwood and other biofuels aimed atthe end-user markets.

Both small and large power plants and CPH plants using wood waste, straw,paper and cardboard waste have been used for some decades, e.g. in a com-bined setup where the power plant will accept both such biofuels and alsopulverized coal and natural gas (Nielsen, 1998). Reducing emissions from strawcombustion down to the neighbourhood of those for coal has been achieved byDanish utilities in a concerted learning process.

The main results of a life-cycle study for an Austrian CPH plant burningwood chips, scrap wood and sawdust with glue remains are presented in Table6.19 (Jungmeier et al., 1998). Because the installation produces six times moreheat than electric power, the impacts are given per kWh of thermal output. Thebiofuels energy efficiency (conversion into electricity plus heat) is assumed to be85%. The study ignores CO2 emissions from the biomass combusted, assumingbiofuels to be greenhouse gas neutral. This is true for short-rotation crops,where the time displacement between CO2 assimilation and emission is short ina global warming context. However, it is not necessarily true if the time intervalfrom assimilation to combustion and emission is long. For wood, this may bethe case, depending on the source of wood. Forestry operation may haverotation periods of around 40 years, but for felling mature forests the periodmay be larger. Even 40 years is not unimportant in a global warming contextsuch as the present one, where the greenhouse gas content of the atmosphere isincreasing and compensating assimilation that may happen 40 years into thefuture is not removing the negative impacts during the period of interest tohuman societies. Such reflections should be made for any use of biomass in theenergy sector, where ‘‘safe’’ biofuels must be made from residues of short-rotation crops. A further step is of course to capture and store the emissions ofCO2 from the power plant, which can be done if the biomass is gasified in acombined cycle concept (Carpentieri et al., 2005).

The combined use of forest and agricultural waste and residues together withfossil fuels, mentioned above for Danish CPH plants, is used in several parts ofEurope, with impacts that have been assessed, e.g. by Bauer (2008). His life-cycleemissions (again under the assumption of carbon neutrality of the wood resi-dues) are only slightly higher than those in Table 6.19 when the biomass residuesare transported less than 25 km (by lorry), but 4–6 times higher if long-distance


(over 1000 km) transport by train or barge is required, as it sometimes is forutilities purchasing (‘‘cheaper’’) bio-residues from distant suppliers.

Biogas can be produced on the basis of several biomass resources, e.g.manure, plant residues or household waste (Table 6.20 shows a typical com-position). An example of current technology is the plant at Ribe in Denmark,which annually converts about 110 million kg of manure and 30 million kg ofother organic waste into 100 TJ of biogas. This is at the lower end of conversion

Table 6.19 Life-cycle impacts from an Austrian CPH plant burning woodresidues (max. 10 MW fuel input, annual average production 0.54MW electricity and 3.3 MW heat; Jungmeier et al., 1998). Impactsare given as a function of heat production kWhth.

Environmental Impact


Monetisedvalue (2010mh kWhth

–1)aUncertaintyand rangesb

Emissions from entire lifecycle (from operationalphase in parentheses)CO2 (compensatingassimilation assumed)

17 (0.07) M H, g, m

SO2 0.07 (0.05) L H, r, nNOx 0.60 (0.05) L H, r, nhydrocarbons 0.13 (0.06) L H, r, nparticulates 0.06 (0.03) L H, r, nvolatile organics 0.07 (0.05) L H, r, n

Solid and liquid waste 47 (22) L H, r, nImpacts from greenhousegases

1.7 H

Health impacts; ecosystemdamage

o1 H

Noise 65 dB L o0.1 HRoad transport of fuel B0.0003

km/kWhth

M NQ

Social impacts

Fires considered NQAccidents considered NQ

Economic impacts

Direct costs NA 50–100Labour requirements 3� 10–4 h

kWhth–1

Benefits (consumerprice of heat)

50–150

Other impacts

NA NQ


240 Chapter 6

efficiencies for the 10 large biogas plants operated in Denmark, ranging inenergy terms from 30% to 60%, depending on feedstock (Danish EnergyAgency, 1996; Nielsen and Holm-Nielsen, 1996; Sørensen, 2010a). An averageconversion efficiency of 50% may be assumed for new plants.

Biogas consists of methane (CH4) plus varying amounts of carbon dioxide(CO2). Methane especially has a high greenhouse warming potential (GWP), sothat leakages during production and transport, e.g. via pipelines or in con-tainers, have to be avoided or kept at a low value. Feedstock for the Ribebiogas plants is mainly slurry from farms transported by road to the plant, butthere is a small solid component.

Table 6.21 gives some technical data for the Ribe biogas plant, relevant forthe LCA. One issue of concern is the presence of modest amounts of hydrogensulfide (H2S), which could contribute to acid rain formation. For anotherDanish biogas plant, located at Fangel, a cleaning process aimed at reducingthe H2S content to between 700 and 1500 ppm has been tested (Danish EnergyAgency, 1995). This corresponds to a weight percentage of 0.09–0.2, the uppervalue being equal to the one assumed in Table 6.21. More stringent sulfuremission limits should be considered in case biogas production reaches animportant penetration in future energy systems.

Important emissions are those of methane liberated from the slurry tanksbefore or during slurry collection and while being transported to the biogasplant. However, it is estimated that collecting the slurry and using it in a biogasplant will reduce methane emissions compared to emissions from standardpractice, where the manure is stored for several months before being spreadonto fields. This process can be described via the methane conversion factor(MCF), defined to mean the conversion of the carbon in the slurry to methane.The MCF varies with the seasons of the year, being higher in summer than inwinter. Nielsen and Holm-Nielsen (1996) assume an average MCF of 10% forDanish storage tanks. They calculate the reduction for the Ribe biogas plant tobe 160 t CH4 per year, minus 40 t due to leakage from storage at the biogasplant. The greenhouse warming potential of these amounts of methane should

Table 6.20 Elementary analysis and energy content of Danish waste (KrugerEngineers, 1989).

Substance Weight percent Range

Carbon 25 15–35Oxygen 18 12–24Hydrogen 3 2–5Nitrogen 0.6 0.2–1.0Sulfur 0.003 0.002–0.6Chlorine 0.7 0.5–1.0Water 20 15–35Ash 25 15–40Lower heating value, municipal solid waste 8.8 GJ t–1 8.4–9.2 GJ t–1

Lower heating value, industrial waste 13.7 GJ t–1 8.7–19.0 GJ t–1


be credited to the biogas energy system, if the agricultural sector life-cycleimpacts are not part of the investigation. It is not generally recommended toomit connected sectors in a life-cycle analysis, but if it appears necessary, therewill be positive and negative contributions treated as indirect costs or benefits.One should be aware of the difference between ‘‘avoided negative impact’’ and‘‘positive impact’’. The use of ‘‘reference systems’’ is also problematic becausesuch systems tend to change with time.

Table 6.21 Technical data for the Ribe biogas plant, with auxiliary estimates(Danish Energy Agency, 1995; Nielsen and Holm-Nielsen, 1996;ETSU/IER, 1995; Oko Institute, 1993).

Parameter Value Remarks

Technical dataSpecific investment 2750 US$ kW–1

(in 1995)45.3 million DKr total(1995)

O&M 9.6% p.a. 4.6 million DKr annually(1995)

Net capacity 2.7 MW 10 000 m3 per dayAnnual load 8700 hLifetime 20 yLifetime generation 469.8 GWhOverall net efficiency B35% 30–60%, depending on

feedstockInput and compositionBiomass 410 t d–1 60% cow manure, 20%

pig slurryBiomass transportAverage total 32 kmAverage animal slurry 22 kmBiogas compositionCH4 64.8%CO2 35%Rest (H2, N2, H2S) taken as H2S 0.2% using GEMIS generic

databaseCombustion value (MJ m–3) 23.4Material demand Energy used for

manufactureSteel 5 t 22.2 GJ t–1

Concrete 10 t 4.6 GJ t–1

Transport of materialsSteel by truck 150 km for constructionSteel by railway 50 km for constructionConcrete by truck 50 km for constructionProcess demands per MJ biogasProcess heat 0.12Electricity 0.01Emissions per MJ biogasCH4 from storage at plant 0.4 gCH4 avoided at farm tanks 1.6 g impacts to be subtractedMiscellaneousArea demand 1 ha estimated

242 Chapter 6

The methane emissions from Danish livestock in 1990 were about 160 millionkg (from 11.7 million animals, mainly cattle and pigs). This amount is thecontribution from enteric fermentation. A similar amount, 125 million kg, isemitted from manure (Fenhann and Kilde, 1994). These emissions have forsome time been considered in the greenhouse balance of the agricultural sector.They may also be divided between the agricultural and the energy sectors, e.g. inproportion to the revenues from the two types of operation. However, theyshould of course not appear twice. This illustrates the remark made above aboutLCA impacts occurring in more than one economic sector.

Emissions are summarised in Table 6.22. The emissions from manure spreadon the soil is low and for the biogas plant residues returned to the fields is nearlyzero. The biogas chain impacts shown are estimated on the basis of emissionsand energy production given in Table 6.21. Methane emissions from cattlemetabolism are not included, as it is considered that they would be the same aswithout the diversion of manure to the biogas plants. The avoided methaneemissions from farm storage of manure are seen to constitute the dominatingcontribution to the LCA costs. It varies from installation to installation and hasto be assessed for the actual conditions.

Some Danish biogas plants accept household refuse and waste from foodindustries, but the experience is mixed. General use of industrial biomasswaste is permitted only if there are no significant residues of heavy metals inthe slurry. Household sorted refuse may also contain undesirable elementsand in one case (the Elsinore biogas plant) it was impossible to maintain astable biogas production with household waste alone. The bacterial culturesformed in a biogas reactor often take several weeks to reach suitable popu-lation ratios, making it important that the input composition does not varysubstantially with time (Sørensen, 2010a). This condition was not fulfilled inthe plant that failed. Another plant (at Vegger) has solved this problem bymixing a certain amount of animal manure into the feedstock, along with thesource-separated household waste (based on one bin for organic waste,another for the rest, except items like paper and computer parts recycled inother ways).

LCA studies have been made not just for large biogas plants but also for thesmaller, farm-scale installations installed in Europe (Borjesson and Berglund,2006), inspired by the long-term available installations in China and India(Sørensen, 2010a). Impacts for the smaller biogas plants are typically smallerthan for the large ones, because of shorter transport of the raw material. InSweden and a few other countries, biogas in used as fuel for vehicles. In mostother countries it is used for electricity generation or for heating. If hydrogenbecomes viable as an energy carrier, transformation of biomass into hydrogenwill be an interesting option. It can be done by gasification (e.g. using woodscrap as input) followed by traditional reformation, in the same way ashydrogen is currently made from natural gas, or it can be done by electrolysis,e.g. based on electric power generated from biogas. The life-cycle impacts ofthese two routes have been analysed by Koroneos et al. (2008). They find thatalthough the electrolysis route is likely to remain more expensive, its


Table 6.22 Impacts from large biogas plant at Ribe, Denmark (per kWh ofbiogas produced) (Nielsen and Holm-Nielsen, 1996; Kuemmeland Sørensen, 1997).





From fossil energy used inplant construction andoperation (not infeedstock or biogas use)

CO2 equiv. (leading togreenhouse effect)plant construction,truck manufacture

23 L 4 0.5–1.1

transportation offeedstock and residues

90 L 2 1–3

methane leaks (incurredminus avoided)

–285c M –6 –4 to –8

SO2 (leading to acid rainand aerosols)

0.25 L 0.4 H, r, n

NOx (possibly aerosols/health impacts)

0.36 L 1 H, r, n

Particulates (lungdiseases)

0.03 L 0.1 H, r, n

Land use NA NQ

Social impacts

Occupational healthdamage (manufactureand operation)

Cases perTWh

death 1.7 L 4 L, l, nmajor injury 2.2 L 0.2 L, l, nminor injury 0.7 M 0.1 M, l, nreduced span of life 6.0 M 13 M, l, n

Economic impacts

Direct costs 60–120Resource use (energypayback time given)

2.1 y L NQ


17 person-yMW–1

L NQ

Import fraction (forDenmark)

0.1 L NQ

Benefits from energysold

60–200

Other impacts

Supply security (basedon plant availability;feedstock supplymay vary)

fairly high NQ

244 Chapter 6

environmental impacts are smaller than those of the reformation route by morethan a factor two, using an indicator-based life-cycle assessment.

Waste treatment is a basic problem for contemporary societies and, in anumber of cases, energy extraction from the waste is not possible or practical.For agricultural residues, energy extraction is feasible and may in the future notbe in the form of biogas but of liquid biofuels (LCA investigation made byCherubini and Ulgiati, 2010); for city solid waste the often currently usedincineration or landfill disposal may be replaced by other processes, such ascomposting (LCA preference suggested by Banar et al., 2009). Waste that canbe recycled, such as paper and cardboard waste, should be so, as LCA impactsare much lower than for other disposal methods (Schmidt et al., 2007).

While traditional bio-ethanol (used extensively in vehicles in Brazil andblended with gasoline in the USA) has acquired a bad reputation for its use offood-quality sugarcane or grain as biomass source, current interest is in‘‘second-generation’’ bio-ethanol, based on agricultural residues such as strawand other lignocellulosic materials. Prospects for achieving low emissions andlow LCA impacts have been signalled, e.g. in a survey by Spatari et al. (2010).

Production of bio-diesel (fatty acid methyl ester) fuel from a variety ofbiomass residues has attracted considerable attention, not least due to thehigher efficiency attainable with common-rail diesel engines, relative to Ottoengine gasoline vehicles (Sørensen, 2010b). However, as with ethanol,production at first used oil from plant seeds such as rapeseed (triacylglycerol)or the related canola as the basis for bio-diesel production. In Table 6.23,bio-diesel could be assumed to be made from waste products such as usedcooking oil, which would avoid the competition with food but demand adifficult (and possibly costly in life-cycle impacts) waste collection scheme (cf.Figure 6.4).

Impacts from plant construction are not included and process impacts aredivided between bio-diesel and glycerine according to weight. In the vehicle


Robustness (up-frontinvestment binds, entrybased on technicalreliability)

fairly high NQ

Global issues(non-exploiting)

compatible NQ

Decentralisation(less as size increases)

fairlycompatible

NQ

Institution building(collection management)

modest NQ

aNA¼ not analysed; NQ¼ not quantified. Values are aggregated and rounded (to zero if below0.0005 h kWh–1).bL, M, H¼ low, medium or high uncertainty; l, r, g¼ local, regional or global impact; n, m,d¼ near, medium or distant time frame.cThe negative impact is due to a reduction of impacts outside the energy sector that would nototherwise be counted (see text).


application phase (not included in Table 6.23), the impacts from particularmatter and SO2 are substantially reduced compared to mineral diesel oil, whilethose from NOx and hydrocarbons are increased (California EPA, 2008).Carbon neutrality has not been assumed in the Table 6.23 emissions, but thereare good reasons to omit greenhouse warming when bio-diesel is producedfrom agricultural rapeseed (an annual crop) or by extraction from foodindustry or household waste. Several other diesel-like fuels may be producedfrom biomass resources, including dimethyl ether (DME) and synthetic dieselsobtained by gasification and Fischer–Tropsch synthesis. Green diesel isproduced from biomass resources by fractional distillation rather than bytransesterification, and oils may also be extracted from microalgae grown inponds or in ocean aqua-farms to produce biofuels with low emissions and high

Table 6.23 Life-cycle impacts from bio-diesel production from cooking-oilwaste, using an alkaline catalyst (Harding et al., 2007).



Monetisedvalue (2010mh kWhth

–1)aUncertaintyand rangesb

Selected emissions to airand waterwaysCO2 equiv. (compensatedby assimilation)

SO2 equiv. (acidification) 551 LPO4


4 L small H, r, n

C2H2 (photochemicaloxidation)

5 L considerable H, r, n

Largest impacts fromfarming and fertilisers

0.2 L considerable H, r, n

Noise, land use, visualimpact

NA L some

Social impacts

Occupational impacts NA L NQ L, l, n

Economic impacts

Direct costs (power anddelivery)

NQ


NA L NQ

Labour requirements,import fraction

NA L NQ

Benefits from power sold 100–200

Other impacts

NA NQ


246 Chapter 6

biodegradability (Jorquera et al., 2009; Campbell et al., 2011). Investigations ofthe use of algae for biofuels are still in an early stage, with problems pertainingto stability of growth and difficulties in extracting a high fraction of the oilspresent in the algae.

The essential process step is a transesterification, requiring large amounts ofalcohol (typically six times the amount of oil) that have to be recycled nearly100%. The reaction needs a catalyst, which may be sodium hydroxide (NaOH)or a suitable enzyme (Harding et al., 2007); in addition to bio-diesel, it deliversglycerol that has a market value, at least if the quantities are limited. The energycontent of the bio-diesel oil is very close to that of the original rapeseed oil, about7.53 kWh kg–1 (density 1.23 kg L–1). The main process steps are shown in Figure6.4. Animal fat may be used as an alternative to plant-based oils and grease.Table 6.23 shows impacts for the methanol/alkali catalyst case.

The present discussion of biofuels has not included the end use, except for aremark on larger NOx pollution. These issues will be taken up in the followingChapter 7 in connection with vehicle LCA studies.

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Walter, C., Stutzel, H. (2009). A new method for assessing the sustainability ofland-use systems (I &II). Ecol. Econ. 68, 1275–1287; 1288–1300.

Warming, S. (1996). Valuation of environmental impacts from coal-basedpower production. ELSAM Power Utility (unpublished note in Danish).

Watt, M. (1993). Environmental &Health Considerations in the Production ofCells and Modules. Centre for Photovoltaic Devices &Systems Report#1993/02, University of New South Wales, Sydney.

Wikipedia (2010). Casualties of the Iraq War. http://en.wikipedia.org.Williams, A., Audsley, E., Sandars, D. (2006). Determining the environmental

burdens and resource use in the production of agricultural and horticulturalcommodities. Defra project report IS 0205. Cranfield University, Bedford.Results for milk updated on http : //www.cranfield.ac.uk/sas/naturalresources/research/ projects/is0205.html (accessed October 2010).

Yamada, K., Komiyama, H., Kato, K., Inaba, A. (1995). Evaluation ofphotovoltaic energy systems in terms of economic, energy and CO2

emissions. University of Tokyo, Internal Report.Yasin, Z., Shahzad, M. (2010). From conventional nuclear power reactors to

accelerator-driven systems. Ann. Nucl. Energy 37, 87–92.

254 Chapter 6

CHAPTER 7

Life-Cycle Analysis of End-UseEnergy Conversion

A large number of energy conversion processes take place at the end user,including use of appliances and electronic devices, space conditioning, work-place tools and transport of persons and goods. The activities involved canbe subjected to life-cycle analyses, which can be summed up in categories forthe purpose of policy intervention (building codes, appliance and vehicleenergy consumption standards, etc.). Individual LCA studies are relevant formanufacturers of the equipment involved and they would naturally resembleproduct life-cycle analyses. The examples below deal with groups of activitiesthat involve several types of impacts, from equipment and its operation tohuman habits and preferences, for example in selecting the means of trans-portation (personal, family based or collective) or the desirable kind of shel-ter (apartment, detached house, with different choices of architecture, floorspace per inhabitant, and selection of an energy supply system).

7.1 LCA of Road Traffic

7.1.1 Conventional Gasoline Otto-engine Passenger Car

The transportation sector is characterised not only by a number of fuel-relatedimpacts but also a variety of other externalities, related to the infrastructureneeded for road transportation systems. Table 7.1 is based on a review ofseveral LCA studies, aimed to embrace or at least flag all identified impacts ofowning and using a motor vehicle. As a reference case, a conventional pas-senger vehicle is selected, with the following assumptions on technology andusage: the evaluation uses a year-2000 vintage, average-sized car, assumed todrive 200 000 km over 10 years with an average efficiency of 13.5 km per litre ofgasoline (corresponding to mixed urban and highway driving and equivalent to7.4 litres per 100 km).


By Bent Sørensen



255

Table 7.1 Impacts from an average Danish passenger car (13.5 km per litre ofgasoline). Updated from earlier study by Kuemmel et al. (1997).


Type of impact:emissions(g per kWhof fuel)a

Monetisedvalue (2010mh pervehicle-km)

Monetisedvalue (2010mh per kWhof fuel)a


Environmental emissionsCar manufacture anddecommissioning

industryaverage

2 3 H

Car maintenance NQRoad construction andmaintenance

NQ

OperationCO2 277 LNOx (may formaerosols)

2.9 M

CO 17 Mhydrocarbons 3.0 4 6 Mparticles 0.06 18 28 M

Health impacts frompollutants

3 5 H, l, n

Greenhouse warming H, g, mNoise (large variations) increase: 1.5

dB(A)12 17 H, l, n

Environmental andvisual degradation(from roads, signs,filling stations, etc.)

H, l, m

Health and injury Cases

Occupational (car/roadconstruction andmaintenance)

NQ

Traffic accidents (incl.material damage,hospital and rescuecosts)

10 16 M, l, n

deaths 2.4� 10–8

per kWh-fuelheavy injury 24� 10–8 per

kWh-fuellight injury (whenreported)

16� 10–8 perkWh-fuel

Stress and inconvenience(e.g. to pedestrianpassage)

3 5 H, l, n

Economic impacts

Direct economy(cars, roads, gasoline,service andmaintenance)

taxes excluded 30 46 L, l, n

256 Chapter 7

The greenhouse warming externality is based on the European standardcolumn in Table 6.1. The health effect caused by air pollution from car exhaustsis taken as 0.035 h per km driven for 2010, an inflation-corrected numberarrived at in early Danish studies (Danish Transport Council, 1993; DanishTechnology Council, 1993). More recently derived values will be used in asecond road vehicle example in Section 7.1.2. Accident statistics give a firmbasis for estimating deaths and injuries connected with road traffic, but rates ofaccidents vary considerably between regions as well as with time. The actualvaluation to be attributed to police and rescue team efforts, hospital treatment,lost workdays and lives all have to be estimated. For deaths, Table 7.1 uses thevalue given in Table 5.3, and for time loss a figure of 9 h h–1 is used (inflationcorrected to 2010 from a value based on an interview study on perceived valuesof waiting time; Danish Technology Council, 1993). This is a ‘‘recreational’’value in the sense that it rather corresponds to unemployment compensationthan to average salaries in Denmark. The ‘‘stress and inconvenience’’ entrytakes into account the barrier effect of roads with traffic, e.g. causing pedes-trians to have to wait (at red lights) or to walk a larger distance to circumventthe road barrier. This may again be valued as time lost.

Danish road traffic is characterised by a low rate of deaths by road accidents,compared with most other European countries. This implies that road accidentswill be themost important externality inmany other countries, while inDenmarkthey turn out not to dominate the total. The noise impact damage estimate at 3 hkm–1 in 2010 is based on hedonic pricing, i.e. the reduction in the value ofproperty exposed to noise (e.g. houses along major highways compared to thosein secluded suburban locations; Danish Transport Council, 1993). A similarapproach is taken to estimate the visual degradation of the environment due toroads, signs, filling stations, parking lots and so on. Property values were col-lected in 1996 (from newspaper advertisements) for detached houses of similarstandard, located at the same distances from the Copenhagen city centre (but


Resource use significant NQLabour requirementsand import fraction(Denmark)

B50% of directcosts are local

NQ

Benefits (valuedat cost of publictransportation)

70–120 110–180 M, l, n

Time use (contingencyvaluation)

15 23 H, l, n

Other impacts

NA


257Life-Cycle Analysis of End-Use Energy Conversion

outside the high-rise area, at distances of 10–25 km from the centre) and exposedto different levels of visual and noise impact from traffic. The externality is thentaken as the number of people exposed times the sum of property losses. Theproperty loss found is 25–45% and the total damage for 0.5 million people with0.2 million houses and cars is 1.9� 1010 h or 0.50 h km–1, of which about half isassumed to derive from visual impacts. A further reduction by a factor of two isintroduced by going from a suburban environment near Copenhagen to acountry average. The value arrived at is thus 0.12 h km–1.

The direct economic impact includes capital expenses and operation for carsand roads, as well as the property value of parking space in garages, carports oropen parking spaces, but omits any taxes and duties as they may be representa-tions of the damage being valued. The benefits from driving are taken at the valueof public transportation (considering that differences in convenience and incon-veniences even out, e.g. being able to read when driving versus schedule waitingtimes). Time use is, as mentioned above, derived from a contingency valuation(i.e. interviews). The cost of driving a passenger car, i.e. all direct costs and indirectLCA impact items except benefits and time use (the most uncertain impacts), isthen 0.80 h km–1, of which some 10% is related to owning the car (purchase pricewithout taxes plus environmental impacts of car manufacture) and the remainingLCA costs relate to driving the car. A fair taxation level, reflecting external costs,would then be to divide taxes into a vehicle tax of no more than 4000 h and akilometres-driven component that levied onto the fuel would amount to nearly 5 hper litre. The actual taxation within the current Danish legislative regime is muchhigher for car ownership (nearly three times import price) and much lower forgasoline purchase (taxes well under 1 h per litre). One may explain this differenceas a desire to discourage customers from buying the most inefficient cars (to theextent that they are also the more expensive ones).

In summary, including both passenger transportation and car ownership inthe LCA, the following types of impacts have been included in the analysis:

� health effects from pollutants� traffic accidents� contributions to enhancing the greenhouse effect� noise� visual aspects� barrier effects and inconvenience from road installations� road construction� car manufacture and decommissioning

The cost of road construction and maintenance is taken as an externalityowing to the borders selected for this study, which focuses on all aspects ofpersonal road transport rather than only the vehicle or its propulsion system.One may argue that roads are used by vehicles other than those associated withpersonal transport. Transportation of goods has a considerable role to play inroad planning and contributes significantly to maintenance requirements,accidents, visual impacts, etc. For pavement degradation, large lorries are

258 Chapter 7

responsible for a higher fraction than their share in the use of the roads wouldsuggest. An LCA of pavement construction and repair costs with associatedimpacts has recently been made, finding quite substantial damage from the useof asphalt (Huang et al., 2009).

7.1.2 Fuel Cell Passenger Car Compared with Conventional Car

This section compares a hydrogen-fuelled proton exchange membrane (PEM)fuel cell car with a very efficient diesel oil-fuelled common rail diesel engine carand with an average conventional gasoline-fuelled Otto engine car.

The passenger cars selected for this LCA are characterised by the featureslisted in Table 7.2. The Daimler-Chrysler (DC) f-cell was the first fuel-cellpassenger car to be produced in a limited series (rather than a few concept cars)

Table 7.2 Basic vehicle data used for comparison (from Sørensen, 2004).

Passenger car (1–5 persons plus luggage)

Description

Average USA(2000), Ottoengine, ToyotaCamry

Best Europe(2000), common-rail diesel, VWLupo 3L

PEM fuel cell,35 MPa H2,DC f-cell

Bare mass (body, chassis) (kg) 930 570 800Propulsion system mass (kg) 340 220 600Battery mass (kg) 12 10 40Fuel and container/handlingmass (kg)

o40 o35 3þ 100

Proper mass (unloaded) (kg) 1300 825 1589Mass of steel (kg) 410Mass of plastics, rubber (kg) 130Mass of light metals (kg) 130Load mass (kg) o350 o340 o340Total mass (occupancy: 2;0.67 full tank) (kg)

1440 980 1725

Coefficient of rollingresistance

0.009 0.0068 0.0068

Drag coefficient 0.33 0.25 0.25Auxiliary power (kW) 0.7 0.6 1Engine/fuel cell rating (kW) 109 45 69Electric motor rating (kW) 65Battery rating (kW Wh–1) 4/732 20/1400Engine/fuel cell efficiencya 0.38 0.52 0.68Gear and transmissionefficiencya

0.75 0.87 0.93

Electric motor efficiency 0.8Fuel usea (MJ km–1) 2.73 1.08 0.8–1.44Fuel usea (km L–1) 12 33Fuel to wheel efficiencya 0.15 0.27 0.36

aFor standard European mixed driving cycle. Fuel-to-wheel efficiency is the work performed by thecar to overcome air and road friction, plus work performed against gravity and for acceleration/deceleration, divided by fuel input. Sources: Weiss et al. (2000,2003); Schweimer and Levin (2001);VW (2002, 2003); Tokyo Gas Co. (2003).


for demonstration purposes; the estimated quantity was some 60–80 units,denoted a ‘‘zero-series’’ and not claiming mass production but exploring someof the issues arising in series production. The f-cell car is based on a slightlylonger version of the commercial A2 series of Mercedes-Benz gasoline anddiesel fuel cars; Table 7.2 reflects the limited data available at the time of cal-culation. The two non-fuel-cell cars studied for comparison are a ToyotaCamry gasoline/Otto engine car, representing a typical year-2000 US vehicle ina previous life-cycle study (Weiss et al., 2000, 2003), and the Lupo 3L TDIdiesel car that for a number of years topped the European ranking list fordriving efficiency, but is no longer in production (VW, 2002, 2003). Table 7.2gives a gross survey of materials used, as well as basic weight and fuel con-sumption details that will be used in the life-cycle analysis. The fuel con-sumption was 1.44 MJ km–1 for the first f-cell cars manufactured, but isexpected to become lower on future versions (DC, 2004). Some of the prop-erties given in Table 7.2 are also summarised in Figures 7.1 and 7.2.

Figure 7.1 shows that while the Lupo has diminished weight compared to anaverage car through use of lightweight materials where possible (but still being inthe top safety category according to crash tests), the f-cell car, although small ofappearance, has a higher mass than even the conventional car, owing to theheavy equipment associated with hydrogen management and conversion. Figure7.2 compares the efficiencies of the three cars studied. In terms of energy content,the fuel use of the f-cell car is slightly below that of the Lupo, both being con-siderably below the current average car. The fuel-to-wheel efficiency improvesconsiderably for the fuel cell vehicle, both over the efficient diesel car and of

Figure 7.1 Mass distribution for the passenger cars included in the comparative LCAanalysis (Sørensen, 2004).

260 Chapter 7

course over the conventional gasoline car. Fuel use has been estimated bysimulation, employing the new European driving cycle used for official rating ofcars in Europe. The shape of this driving profile is shown in Figure 7.3.

7.1.2.1 Environmental Impact Analysis

Table 7.3 gives the environmental LCA estimates available for the three cars, interms of energy used and emissions occurring during the phases of the vehiclelife-cycle. The data are based on the studies mentioned, supplemented with owncalculations and estimates. For the fuel cell car, two versions are considered,depending on whether the hydrogen comes from natural gas or from renewable

Figure 7.3 Driving cycle used for emission certification of passenger cars in Europe,with an urban stop–go section and at the end a continuous sequence atspeeds up to 120 km h–1 (European Commission, 2001).

Figure 7.2 Total efficiency breakdown for the three cars compared in the LCA study(Sørensen, 2004).


Table 7.3 Vehicle environmental life-cycle impacts (Sørensen, 2004).

Passenger car (1–5 persons & luggage)

Life-cycle emissions


Best Europe(2000),common-raildiesel, VWLupo 3L

H2 fromnatural gas,PEMFC/elec. motor,DC f-cell

H2 fromwind surplus,PEMFC/elec.motor, DCf-cell

Car manufacture Productionandmaterials

Total/FCstack

Total/FCstack

Energy use (GJ) 87 37þ 51 93/?, 178/80a

93/?, 178/80

Greenhouse gasemissions (tCeq)

1.7 0.5þ 0.5 1.7/?, 2.8/1.4a

1.7/?, 2.8/1.4a

SO2 emissions (kg) 1.6þ 10.0 36/14.5a 36/14.5a

CO emissions (kg) ?/1.7 ?/1.7NOx emissions (kg) 1.8þ 4.6 ?/14.5 ?/14.5Non-CH4 volatileorganic compounds(kg)

2.0þ 1.3 ?/1.7 ?/1.7

Particulate matteremissions (kg)

0.3þ 4.0 ?/2.6 ?/2.6

Benzene (g) ?/2.3 ?/2.3Benzo[a]pyrene (g) ?/0.034 ?/0.034Fuel production (for300 000 km)

Energy use (GJ) 156 67 185 185Greenhouse gasemissions (tCeq)

3.6 0.4 8.6 0

SO2 (kg) 9 0NOx (kg) 40 0Non-CH4 volatileorganic compounds(kg)

60 0

Particulate matter (kg) 1 0Lifetime operation(15 y, 300 000 km)b

Decommissioning Impactestimationincluded

Energy use (GJ) 819 324 240 240Greenhouse gasemissions (tCeq)

16.1 6.5 0 0

SO2 (kg) 1.6 0 0CO (kg) 30 0 0NOx (kg) 75 0 0Non-methane volatileorganic compounds(kg)

2.7 0 0

Particulate matter (kg) 6 0 0PAH (kg) 1.5 0 0N2O: effect onstratosphericozone (kg)

13 1 B0 0

262 Chapter 7

(wind-produced) electricity. The impacts are given in physical units, as requiredfor an LCA inventory and will subsequently be valued as in previous examples,rendering them into externality costs to human health and the environment,including global warming effects. Of particular interest are the impacts from themanufacture and use of the fuel cell component in the f-cell car, further dis-cussed in Sørensen (2005).

The fuel cell vehicle considered in this study uses hydrogen directly. Ifreformation of methanol or gasoline were used, as automakers tried during the1990s, then additional impacts would be derived from the reformer, includingoften quite large impacts from a catalyst such as palladium, which again shouldbe recycled as fully as possible.

No separate data have been found for decommissioning impacts, althoughVW (2002) claims to have included them under ‘‘lifetime operation’’. In Den-mark, cars delivered to a recycling station pay a fee of about 500 h, supposed tocover the decommissioning costs minus income from selling extracted parts forreuse. European regulation is discussed where decommissioning would be partof the initial purchase price and the manufacturer would be obliged to optimiseassembly structures and numbers of parts for decommissioning, and to take thevehicle back at the end of service for maximum recycling.

The Volkswagen report (Schweimer and Levin, 2001) is a detailed and site-specific LCA for the car manufacturing plant at Wolfsburg, including materials


Life-cycle emissions


Best Europe(2000),common-raildiesel, VWLupo 3L

H2 fromnatural gas,PEMFC/elec. motor,DC f-cell

H2 fromwind surplus,PEMFC/elec.motor, DCf-cell

Decommissioning included above includedabove

includedabove

includedabove

TotalsEnergy use (GJ) 1062 479 603 603Greenhouse gasemissions (tCeq)

21.4 7.9 11.4 2.8

SO2 (kg) 61 22.2 36 36CO (kg) 30NOx (kg) 70 121Non-methane volatileorganic compounds(kg)

66

Particulate matter (kg) 12 11.3

aPt manufacturing (assumed in South Africa) accounts for 30% of energy, 40% of greenhouse gasesand 67% of acidification, with no recycling assumed (Pehnt, 2001). The two sets of comma-separated numbers refer to the Weiss et al. and Pehnt studies.bMaintenance impacts not estimated.Sources: Weiss et al. (2000, 2003); VW (2002, 2003); Pehnt (2001, 2003) and own estimates.



and water delivered to or coming out of the plant. It is centred on VW Golfcars, but the scaling made here for application to Lupo has in gross termsalready been made previously in the VW environmental report (2002). Theenvironmental impacts of Table 7.3 are summarised in Figure 7.4 (note100� scale for greenhouse gases).

7.1.2.2 Social and Economic Impact Analysis

Table 7.4 gives occupational risks during the life cycles of the vehicles, based onstandard industrial data (i.e. the impacts are proportional to cost). The jobcontent is based on statistics from the energy sector in Denmark (Kuemmelet al., 1997). The frequency of accidents on the road is taken from severalDanish studies and is fairly low compared to some parts of the world.Evaluation of the health and injury impacts are again based on several Danishstudies (some of which mentioned above; see also Kuemmel et al., 1997), as arethe less tangible visual and noise impacts (estimated by hedonic pricing) and theinconveniences such as children having to be supervised when near public roadsor pedestrians in general having to use detours to get to street crossings withtraffic lights, where also the waiting time is valued.

Cars need roads for driving and the road infrastructure is thus an ‘‘extern-ality’’ to vehicle LCA, which has to be evaluated along with the car operationinfrastructure. This is done in monetary terms based on Kuemmel et al. (1997)and is included in Tables 7.5 and 7.6. Table 7.5 gives the direct costs involved(and for comparison the cost of public transportation), without including anyof the substantial taxes and/or subsidies characterising the actual consumer

Figure 7.4 Comparison of environmental impacts from the three passenger vehiclesconsidered in the life-cycle analysis, with hydrogen for the fuel cell car beingderived from either natural gas or excess wind power (Sørensen, 2004).

264 Chapter 7

costs in many countries. The cost of vehicles such as the f-cell car is notavailable at the present time, but has been taken as that of the correspondingMercedes-Benz (smallest car) plus the cost of a fuel cell stack taken as 100 h

kW–1; the associated hydrogen handling and storage costs are assumed to besimilar to that of the stack. Finally, a factor of two is applied owing to the smallseries of production. It will go away when mass production is in place andmarket conditions could lead to further price reductions. This way ofdistributing costs is similar to the one estimated for the Citaro F fuel cell bus(according to brochures on the Evobus EC project).

Maintenance costs are taken as a fixed fraction of capital cost and thus arelarge for the f-cell car (hardly unrealistic for a new construction). The hydrogen

Table 7.4 Vehicle social life-cycle impacts (Sørensen, 2004).

Passenger car (1–5 persons & luggage)a

LCA social andadditionalenvironmental impacts(Unit: Number or cases)

Average USA(2000), Ottoengine,ToyotaCamry

Best Europe,(2000),common-railDiesel, VWLupo 3L

H2 bynatural gas,PEM fuelcell,DC f-cell

H2 by windsurplus,PEM fuelcell, DCf-cell

Car manufacture anddecommissioning

Job creation(person-years)

0.3 0.3 1.8 1.8

Occupational risk:death

0.0001 0.0001 0.0005 0.0005

Occupational risk:severe injury

0.003 0.002 0.015 0.015

Occupational risk:minor injury

0.015 0.013 0.08 0.08

MaintenanceJob creation 0.3 0.3Occupational risks(death/major/minor injury)

0.0001/0.003/0.015

0.0001/0.002/0.013

DrivingAccidents (death/severe injury)b

0.005/0.050 0.005/0.050 0.005/0.050 0.005/0.050

Stress/inconvenience some some some someMobility advanced advanced advanced advancedTime use as social factor(individual perception)

varies varies varies varies

Noise (economicquantification inTable 7.6)

some some less less

Visual impacts (of cars in environment; different perception by individuals)Impacts from road infrastructure (road construction, maintenance, visual impacts:estimated in monetary terms in Table 7.6)

Impacts from car infrastructure (service, repair, traffic police & courts, insurance:mostly included in cost given in Table 7.5)

aAll figures for service life of 15 years, 300 000 km.bDanish statistical information used. Sources: Kuemmel et al. (1997); European Commission (1995).


cost is that of production from natural gas, ramped down as a function of time.It does not include the initial high cost of establishing hydrogen filling stations,which could be done as part of an extended station renewal or replacementprogramme running over several years. No separate estimate is made forthe cost of producing hydrogen from wind, discussed in Sørensen et al. (2004).The fuel price for gasoline and diesel fuel has been taken at the current level,disregarding possible increases during the period of operating the vehicles. Thesocial life-cycle impacts are summarised in Figure 7.5.

7.1.2.3 Overall Assessment of Vehicles Selected for Comparison

The total externality costs (i.e. those not reflected in direct consumer costs) aresummarised in Table 7.6. This involves translating the impacts from physicalunits into common monetary units, with the problems inherent in such anapproach, notably valuing the loss of a human life to society. The caveats are

Table 7.5 Vehicle economic life-cycle impacts in h (Sørensen, 2004).


LCA economic impacts(life expectancy of car:15 years, 300 000 km)

Average USA(2000), Ottoengine,Toyota Camry

Best Europe(2000),common-rail Diesel,VW Lupo 3L

H2 fromnatural gas,PEM fuelcell, DCf-cell

H2 from windsurplus, PEMfuel cell, DCf-cell

Direct economyCar (estimated costwithout taxes/subsidies)

15 000 13 000 80 000b 80 000b

Roads (monetaryevaluation in Table 7.6)

Fuel cost (at fillingstation, no tax)a

15 000 5455 15 600 15 600

Service and maintenance 15 000 13 000 80 000 80 000Decommissioning(see text)

Time use (individualappraisal)

Reference cost ofsatisfying mobilityneedsc

35 000 35 000 35 000 35 000

Resource useSee materials in Table 7.2 (recycling will modify these)Balance of labourand trade

Job intensity (near 50% local, even if no local car or fuel production)Import and export fractions (varies)

aOil price staying at current level, hydrogen price dropping linearly from 100 to 30 hGJ–1 (projectedfor 50 000 vehicle penetration; Jeong and Oh, 2002) during 15-year period, initial cost of hydrogenfilling stations not included.bSmall-series cost is reflected; the current 85-kW PEMFC stack cost is about 10 000 h (withB2500 hprojected for 2025) (Sørensen, 1998; Tsuchiya and Kobayashi, 2004).cPublic transportation estimated cost (roughly in centre of interval given in Table 7.1).

266 Chapter 7

Table 7.6 Vehicle externality assessment in h (Sørensen, 2004).

Passenger car (1–5 persons plus luggage)

Life-cycle assessment;externality monetisingexercise

Average USA(2000), Ottoengine,ToyotaCamry

Best Europe(2000),common-railDiesel, VWLupo 3L

H2 fromnatural gas,PEM fuelcell, DCf-cell

H2 fromwind surplus,PEM fuelcell, DCf-cell

Vehicle-related environmentalemissions (based onTable 7.3)

Human health impacts 33 000 12 100–34 700a

19 500b 19 500b

Global climate impacts(Table 6.1)

8132 3002 4332 1064

Quantified social impacts(based on Tables 7.4 and 7.5)

Occupational health risks 562 548 2809 2809Traffic accidents,including rescueand hospital costsc

26 000 26 000 26 000 26 000

Traffic noise 9000 9000 5000 5000Road infrastructure (environ-mental and visual impacts)

28 000 28 000 28 000 28 000

Inconvenience (to children,pedestrians, etc.)

30 000 30 000 30 000 30 000

aThe upper estimate is due to possible increased impacts associated with NOx compared to earliervaluations (may be reduced by vehicle NOx exhaust cleaning).bCould be reduced by recycling of Pt (Pehnt, 2001).cAbout half of this is from the Table 5.3 valuation of accidental death.

Figure 7.5 Comparison of social impacts from the three passenger vehicles consideredin the life-cycle analysis (Sørensen, 2004).


associated with the fact that impacts such as accidental deaths do not alwaysoccur in the same society that harvests the benefits of car driving. These issuesare part of the general discussion introduced in Section 2.1.2.

All monetised impacts are summarised in Figure 7.6 for the threevehicles considered. A very large, but also very uncertain, fraction of theimpacts is derived from road infrastructure, traffic accidents and annoyance;perhaps surprisingly, global warming is far from dominant. The significantchanges in our everyday environment caused by roads and the vehicles popu-lating them have perhaps become part of life in such a way that we arenot sensitive to their negative value, with exceptions being polluted city airand our joy when occasionally being exposed to nature without cars. Sincemany of the social impacts are identical for all vehicles, no reduction can beachieved by just changing the propulsion system of the vehicle. An exception isnoise, which is definitely smaller for hydrogen vehicles. The other large con-tribution is from emissions of pollutants to the air. They are in part frommanufacture and maintenance and, in the case of the gasoline and diesel cars,from emissions in human breathing height and children’s playing height,despite attempts at exhaust cleaning (which is much less efficient than forcentral power plants). This component is much larger for the average car thanfor the Lupo 3L, as is the fuel cost. Regarding greenhouse gas emissions, thef-cell car using hydrogen from natural gas is no better than the Lupo car, andonly when using hydrogen from renewable energy sources can a substantialadvantage be claimed.

Concern over particulate air emissions involving small-diameter particles hasin the past made many countries prefer gasoline cars over diesel cars, except for

Figure 7.6 Summary of monetised vehicle life-cycle impacts.

268 Chapter 7

trucks and buses where the higher efficiency has been the overriding factor. TheUSA still maintains this attitude, despite some changes in the scene broughtabout by the invention of the common-rail diesel engine in the 1990s, and dueto the increasingly efficient particle filters becoming compulsory in all kinds ofdiesel-driven vehicles. The mechanisms involved in the dispersion of smallparticles have been the subject of intense study (e.g. see Kryukov et al., 2004).The Lupo diesel car considered above has reduced the particulate emissions(Table 7.3) to levels comparable with those of gasoline cars, but newerEuropean diesel cars, including both efficient passenger cars, buses and trucks,all have electrostatic filters reducing the particle emissions by over 90%, whichis better than the SO2 removal by the small catalyst devices used in gasoline cars(but in both cases not as good as the exhaust cleaning at large, stationary powerplants). Particle removal is becoming a requirement in European Unionregulation after 2010, for all diesel cars.

For fuel cell cars carrying methanol and using an on-board reformer, there isdirect emission of greenhouse gases, as well as additional impacts from themanufacture of fuel and reformer, leading to an overall CO2 equivalentcontribution at least 10% higher than for a corresponding car with a purehydrogen fuel stream (Patyk and Hopfner, 1999; Pehnt, 2002; MacLean andLave, 2003; Ogden et al., 2004).

The present goal lifetime of a PEM fuel cell for automotive application is fiveyears. This is the same as the goal recently achieved for advanced batteries;considering the similarity between the two technologies (electrodes, electrolyte,membrane transfers), it seems reasonable to assume that this goal can beachieved, but that longer lifetimes are unlikely to materialize soon. This mustbe held together with the recent increases in the lifetime of cars themselves, with15–20 years already reached by the best manufacturers. This long life is war-ranted because the technology is mature and because it will reduce the overalllife-cycle damage to society and to the environment. However, it means that afuture fuel cell car will need to replace the fuel cell 2–3 times during the life ofthe vehicle. Because the fuel cell is a very large fraction of the total cost of sucha vehicle, and because replacement costs will be even higher for manualreplacement at a garage, then the reduction in fuel cell price that will make thistechnology viable will be much larger than appears possible. The conclusiondrawn from this line of argument is that pure fuel cell cars are unlikely to everdominate the automotive market, but that hybrid cars combining fuel celltechnology with biofuels or with advanced batteries may make it. The reason isthat an optimised combination of battery and fuel cell will be both cheaper andmore efficient than either a pure fuel cell or a pure electric vehicle, and at thesame time will overcome the range problem of pure battery-driven vehicles(Sørensen, 2010b).

If the fuel cell share of a hybrid is below a certain amount (fuel cell rating), itwill not be able to fully recharge batteries during sessions of driving at less thanfull power, and stationary recharging is necessary. Such a hybrid vehicle iscalled a plug-in hybrid. The development of relative battery and fuel cell priceswill determine if plug-in vehicles are preferable to stand-alone hybrid vehicles,


and at present it seems that the optimum may be just in the transition areabetween plug-in and stand-alone hybrids (Sørensen, 2010b). Economic andenvironmental impacts of plug-in hybrid vehicles have been investigated bySilva et al. (2009). Complete chains from hydrogen production (by steamreforming or electrolysis, based on fossil fuels or wind) to use in pure fuel cellvehicles have been investigated under Korean conditions by Lee et al. (2009).For the wind energy electrolysis pathway, a more complete LCA study has beenperformed (Lee et al., 2010). The study assumes a price development that willmake the fuel cell systems viable and concludes that establishing a combinedwind power and hydrogen production facility will make it easier to sell surpluswind power to electric utilities. Economically this means being able to sell windat higher average prices in case the wind is used both for the electricity and thetransport sector. The technical problems and advantages of hybrid vehicleshave been addressed by driving cycle simulations (e.g. the one depicted inFigure 7.3; Liaw and Dubarry, 2007; Sørensen, 2006, 2010b). Matheys et al.(2007) discuss different ways of assessing the life-cycle impacts of tractionbatteries. The conclusion across the different methods is that lithium-ion andsodium/nickel chloride batteries have lower LCA impacts than conventionallead/iron and the other advanced battery types investigated.

7.1.3 Other Transport Modes

LCA studies have also been made for lorries, ships, trains and airplanes.Arteconi et al. (2010) found that using liquefied natural gas rather than dieseloil in lorries does not reduce LCA damage. Strazza et al. (2010) found thatSOFC fuels cells are attractive for maritime applications, provided that thehydrogen is produced with low LCA impacts, suggested to be the case for bio-methanol. The authors consider this biofuel as CO2 neutral, not going into thedisplaced timing of assimilation and emission discussed in Section 6.3.6. Che-ster and Horvath (2009) looked at a range of transportation technologies, fromgasoline-fuelled passenger cars and special utility vehicles over urban buses andvarious rail systems (metro-commuter and light rail) to aircraft of differentsizes. For most of the transport systems the main impacts are from theoperational phase, owing to the fossil fuels being used. Gasoline and dieselvehicles in the US are found to have large CO emissions, US diesel buses verylarge NOx emissions and light rail systems (in particular the one in Boston) verylarge SO2 emissions. As regards energy use and CO2 emissions, public trans-portation scores better than individual transport and particularly metro trainsystems (San Francisco Bay Area Rapid Transit) do very well. However, alsoairline transportation is found to be low in these respects, compared to auto-mobiles, which was not the case a decade ago (Sørensen, 2006). However, asthis is a US study not including the energy efficient cars (particularly the 24–33km per litre common-rail diesel vehicles) that have dominated the Europeanmarket during the recent decade, it may be too kind to the air-transportationalternative. As underlined by Chester and Horvath (2009), the occupancy ofvehicles used in public transportation is a crucial parameter and Figure 7.7

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Figure 7.7 Sensitivity (expressed as ‘‘error bars’’) to typical variations in vehicleoccupation, for energy, greenhouse gases and air pollutants of the trans-port modes considered by Chester and Horvath (2009). Reproduced bypermission from the Institute of Physics.


shows the impact on the different LCA categories of varying this. Generalaspects of transport air emissions have been surveyed by Uherek et al. (2010).

7.2 LCA of Buildings and Space Conditioning

7.2.1 Heat Transfer through the Building Shell

Buildings used for living, for work and for production may in an LCA contextbe viewed as aggregate systems comprising a variety of individual devices opento energy analysis and study of life-cycle impacts. Here the devices associatedwith the functioning of the building itself are focused upon: sheltering byinsulated walls, lighting by windows of varying sophistication, active heating,cooling or ventilation systems based on fuels, electricity or renewable energysystems such as solar heat or electricity panels and energy stores. In addition tothe devices considered part of the building, there will be the devices serving thehuman activities in the building, to be discussed in Section 7.3.

It is tempting to analyse the impacts from the entire building system, possiblygoing into less detail for the components than what would be required in a‘‘product LCA’’ specifically aimed at one component. Inventories suitable forsuch system-level LCA have been established (e.g. see Verbeeck and Hens,2010). A feature of buildings essential for energy evaluation is the amount ofinsulation used in the facades and in the roof plus earth-facing surfaces.Insulation reduces the need for active heating, often to near zero. An exampleof this feature is the heating requirement as a function of insulation thicknessfor Denmark (at 561N latitude), depicted in Figure 7.8. In a global context, the

Figure 7.8 Energy used for manufacture of mineral wool and the declining heat lossresulting from using it as insulation in building walls (based on informa-tion from Rockwool International, 1996).

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space heating and cooling demands can be derived from seasonal temperatures,such as the ones shown in Figure 7.9. The source of data is a reanalysis of 40years of temperature measurements near the ground (Uppala et al., 2006). Thereanalysis consists in making the data consistent (using global circulationmodelling) and uniform in coverage of the entire globe at 6-h intervals. Figure7.9 presents the data in such a way that temperatures between 16 and 24 1C arenot shown, because they are not considered to require any heating or cooling ofa building. If the building has closures such as walls (to prevent winds), thenactivities of humans in the building (body heat and heat of devices such aslights, appliances or microelectronics for computers and audio-visual enter-tainment or information rendering) will increase the indoor temperature to the20 1C suitable for the human body; if the temperature is below 24 1C, it is withinthe range regulated by body heat exchange with the surroundings (sweating,convention). Heat generation is less if the building is unoccupied, but then thetemperature requirements are also more relaxed, serving only to preventdamage to furniture, sensitive equipment or art in the building. Only outsidethe 16–24 1C range will active heating or cooling be needed, and only if asufficient temperature gradient cannot be established by insulation.

Figure 7.10 shows the need for space heating or cooling for a personoccupying 60 m2 at a given location (to be multiplied by population density toobtain the actual energy demand). This is a reasonable value for upper middleclass people in affluent countries, having access to some 40 m2 cap.–1 eachwithin their home (the home being typically shared with other people such asspouse and children/parents), plus some 20 m2 cap.–1 at work (office space, salesroom, liberal profession quarters or factory floor). These values have beentaken as representing future (mid-21st century) floor space access in variousenergy scenarios (Sørensen and Meibom, 2000; Sørensen, 2008a, 2008b). Thefinal amount of energy required for space heating and cooling can then beexpressed in terms of the population density and a parameter describing theenergy efficiency of the buildings occupied, in the following way:

Pheating ¼ c� d � ð16�� C� TÞ for T below 16� C

Pcooling ¼ c� d � ðT � 24�CÞ forT above 24� C

where d is the population density (cap. m–2) and the insulation standardparameter c is 24 W cap.–1 1C for the best current quality of buildings inNorthern Europe. The value c¼ 18 W cap.–1 1C was used in a recent scenariofor Northern Europe around 2060 (Sørensen, 2008a).

LCA investigations of insulation materials that may be used to achieve thesestandards have been performed by Kuemmel et al. (1997), from which Table 7.7has been compiled, comprising the impacts of production, installation, use anddecommissioning of building insulation materials. Other insulation materialsare produced for use in high-temperature processes in industry or powerstations, and in connection with district heating transmission lines.


Figure 7.9 Average temperatures (1C) for January, April, July and October, indi-cating needs for space cooling or heating (based on ECMWC, 2006).

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Several insulation materials are in use or contemplated. The most commoninsulation material in Denmark is mineral wool, which according to themanufacturer involves an energy use for manufacture of 11.6 kWh m–2 for each10 cm thickness (Rockwool International, 1996). As illustrated in Figure 7.8,the optimum insulation thickness under Danish conditions from an energypoint of view is then 60–80 cm. However, increased thickness reduces the insidearea of the building relative to its outside measures, a reduction that influencesthe overall building cost per m2 of floor area. For this reason, builders considerthe economic optimum today as being in the interval 20–30 cm mineral wool-equivalent thickness, and only a few ‘‘zero-energy’’ houses have been builtworldwide with more insulation (an example is found in Leckner andZmeureanu, 2011, for a location in Canada).

In climates where space cooling is required, insulation may work to keep theindoor temperature below the one outside the building. A similar effect isachieved by the very heavy stone and rock materials used in traditional

Figure 7.10 Space heating (top) and cooling (bottom) requirements.


Table 7.7 Energy and environmental impacts of insulation materials used in Denmark (BAT, 1996; Cemsystem, 1996; RockwoolInternational, 1996).

Paperwool Perlite Polystyrene Glasswool Rockwool Cemskum

PropertiesDensity (kg m–3) 28 80 20 18 30 230Thermal conductivity (W m–1 K–1) 0.04 0.04 0.05 0.055 0.039 0.074Primary material (g m–3 paperwooleq)

a newspaper (32.8) Perlite (84.7) polystyrene (41.2) glass refuse (35.0) diabase (35.2) cement (708)Secondary materials(g m–3 paperwooleq)

a9% Al(OH)3, 3%borex, 3%H3BO3 (0.05)

silicon resin(0.19)

(0.6) 4–12% Bakeliteresin, 1% oil(0.44)

1.5–5% Bakeliteresin, 1% oil(0.31)

additives(1.5)

MaterialsEnergy content (MJ m–3) 32 800Transportation (MJ m–3) 13 85Distance (km)primary materials 6 6300 B1400 B1400 50secondary materials 1400 200

ManufactureEnergy use (MJ m–3) 17 240 180 500 400 2125Emissions from transport andmanufacture (g m–3 paperwooleq)

a,b

SO2 2.3 143.2 57.0 7.0 4.6 97NOx 22.3 189.1 27.8 19.2 13.9 1089Particles 4.1 85.1 1.6 30.4 32.6 533HCl 0.002 0.004 0.012 0.007 0.005 0.029HF 0.000 0.000 0.001 0.001 0.001 0.003CO2 equiv. 3300 12 686 14 352 5032 4960 283 700Installation dust dust fibres fibresOperationFire hazard during use high resistant ignitable inflammable resistantEmissions during use andmanufacture (confinable)

C5H12, styrene,solids

fibres, NH3,HCHO, phenol

NH3, HCHO,phenol,hydrocarbons

Industrial risk H2 explosionsDisposition recyclable recyclable?

aVolumes are paperwool-equivalents, i.e. the volume giving the same insulation as one m3 of paperwool.bIncludes emissions from an assumed 200 km transport of the product to user (50 km for Cemskum) (European Commission, 1995). The fair market scenario (seeChapter 8) energy mix is used for calculating the emissions.

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buildings in warm climates, although they do not help to keep winter indoortemperatures up, as required in, say, Southern Europe or the southern part ofthe United States. Unfortunately, architect fashions have moved away fromsustainability in building energy use towards structures with large glass facadescapturing sunlight during summer (creating an artificial need for space cooling)and insulating poorly during winter (creating a similarly artificial need forspace heating). In most parts of the world, building the house right will alleviatethe need for energy expenditure, totally or almost totally.

The insulation materials for which Table 7.7 summarises LCA inventory andimpacts data comprise six types of insulation materials, including both con-ventional and new products (BAT, 1996).

1. Paperwool is the trade name of a material produced from discardednewspapers, using an aluminium hydroxide and borax salt impregnationto reduce flammability. The borax is mined in Hungary and transportedto the factory in Denmark by truck. Substitute plant-based impregnationis under study. Problems include dust emission during installation andfire hazards. An advantage is that the material can be fully recycled.

2. Perlite is the trade name of a material made in Denmark from volcanicstone imported from Greece or Turkey by ship. Recycling may be pos-sible if the material is not mixed with other building materials.

3. Expanded polystyrene is based on oil or gas, with the basic styrenemanufactured at refineries (at the moment outside Denmark). The styr-ene is expanded into balls or blocks that are highly flammable and emitblack smoke and 800 MJ m–3 of heat, plus pentane, under fire.

4. Glasswool is the trade name of a material made from glass fibres boundby Bakelite and impregnated with oil emulsions to prevent water uptakeand dust emissions. Phenol, formaldehyde, ammonia and volatile organiccompounds are released during hardening and recycling is difficult. Itmelts during fires.

5. Rockwool is the trade name of a material made from diabase rockimported from Sweden. This mineral wool uses the same kinds of bindersas glasswool and cannot currently be recycled. It can be madeinflammable.

6. Cemskum is the trade name of a material based on water and concrete.Hydrogen is released during manufacture (explosion risk). The materialhas high structural strength and is used in power stations where hightemperatures make it impossible to use other insulation materials. Thenature of the foam-creating additives is not disclosed (Cemsystem, 1996);in the LCA calculation, an oil-based substance is assumed.

Window areas are the other important source of heat loss from buildings.Currently, ‘‘energy-glazed’’ windows consisting of two layers of glass with airevacuated from the space between them and filled with a low heat-conductancegas is the most commonly used construction, replacing earlier 2–4 layeredwindows with air between the panes. Dry air is also of low conductivity, but


moisture intrusion made these windows perform poorly after some period ofuse. Also, the weight of 3–4 layers of glass often makes the windows too heavyfor one person to handle, which limits the ease of installation.

Syrrakou et al. (2006) have looked at greenhouse gas emissions, energy pay-back and cost of ‘‘smart windows’’, i.e. electrochromic multi-layered panes withmicroprocessor-controlled transmission of light and heat losses similar to thoseof good ‘‘energy-panes’’ (heat-loss U-value under 1 W m–2 K–1). They find thatalthough the complex technology introduces impacts not present with tradi-tional windows, the net energy balance is very favourable and the emission ofgreenhouse gases avoided is in excess of expenditures. Problems are the costand lifetime of the panes.

7.2.2 Building Heating and Hybrid Energy Systems

Many individual heating systems are in use for buildings, in addition to the optionof district heating from a central plant. These include boilers for coal (dis-appearing but still in use, e.g. in China), fuel oil, wood or woody residues, naturalgas and more advanced types with recovery of condensation heat, or combina-tions with heat pumps, working on warm used water, on air or on heat from soilor aquifers beneath the building or its surroundings. Heat pumps typically useelectricity and are seen as replacements for the resistance heaters characterised bya large loss of exergy, when degrading high-quality electric energy into low-temperature heat. Alternative heating systems and concepts under developmentare micro-CPH plants converting, for example, natural gas into both power andheat, solar panels and reversible fuel cells capable of converting stored hydrogeninto power and heat, or electricity (such as surplus wind power) into hydrogen tostore or use in the vehicles used by the household (Sørensen, 2005).

LCA calculations have been performed for several of these systems. Blomet al. (2010) made a detailed study of impacts from natural gas boilers in theNetherlands, including condensing ones and heat pumps and considering thelife cycle from manufacture and construction, through operation, maintenanceand necessary replacements but omitting decommissioning. They concludedthat the use of heat pumps does not reduce environmental impacts. Alanneet al. (2007) compared conventional heating systems with solid-oxide fuel cellmicro-CPH installations in residential buildings and found a possibility oflower impacts from the SOFC system, although the data are uncertain and onlyheat seems to be considered in the cogeneration alternative. Verduzco et al.(2007) performed LCA calculations for various proton exchange membranefuel cell systems for individual homes or groups of buildings, comparinghydrogen produced by steam reforming of natural gas with hydrogen fromelectrolysers, and aiming to cover all heat and power needs of the buildingsserved. Compared to conventional systems, both single-dwelling and districtfuel cell systems are found to have lower impacts of both greenhouse gases andall air pollutants considered.

Ortiz et al. (2009) compared residential LCA impacts for both spaceconditioning and activities in the building such as cooking, for systems based

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on electric energy (no heat pumps) or a combination with natural gas, and fortwo different settings, Spain and Columbia. Of these, the natural gas systemshave the lowest amounts of impacts.

Solar thermal and photovoltaic installations have impacts in addition tothose of the systems themselves (e.g. see Section 6.3.2) when they are integratedinto buildings. For solar heating systems this could be the result of the energystorage system required in most applications (hot water, phase change or otherchemical energy type of store; see Sørensen, 2010a). Masruroh et al. (2006)found lower LCA impacts for a thermochemical store than for a hot-waterstore, largely due to higher efficiency making larger lifetime energy provisionoutweigh the initial impacts of manufacturing the system. LCA of building-integrated photovoltaic systems have been investigated under different geo-graphical conditions, such as Australia (Crawford et al., 2006) or India (Chelet al., 2009). In both cases, despite being installed in areas of high solar radiationinput, the advantage of avoided greenhouse gas emissions during operation isweakened by the currently very long pay-back times for energy embodied in theproduction and installation of modules. However, as remarked in Chapter 6,the mechanisms that may bring the price of PV systems down will also bring thenegative impacts down. Crawford et al. (2006) included credit for the use of heatco-produced by the cells. The modest efficiency of the solar cells makes thecombined photovoltaic thermal (PVT) design a natural choice (Sørensen, 2002).

Special attention has to be paid to wood-burning stoves and furnaces,extensively used for ‘‘creating ambience’’ and for obtaining the lowest priceheating in regions such as Scandinavia, Canada and New England. Emissionsfrom residential wood burning are disproportionally high compared to theenergy they provide. A Danish study concludes that primary particulate matterpollution of air at breathing height caused by residential wood-burners in 2010amounts to 61% of the total (up from 47% in 2005), while the energycontribution of wood-burners is just a few percent (Danish National Envir-onmental Research Institute, 2010b; Danish Energy Agency, 2006). In Norway,residential wood-burning contributed 61% of respirable dust, with local winterpeaks above 90% (SSB Norway, 2001). Clearly, the health impacts depend onwhether the emitting devices are cooking stoves as in poor countries, openfireplaces or closed wood-burners. The first two cases lead to indoor pollution,while the third distributes emissions over the neighbourhood following releasethrough a chimney. Typically, chimneys for wood-burning devices are low,implying that the pollution has its strongest effect locally. Chimney-installeddevices that remove particulate matter, hydrocarbons such as PAH and volatileorganics have been proposed and claimed to be cheaper than the health coststhey help to avoid (Haaland, 2005), but such technologies are more practical atcentral wood-burning plants and for the residential uses one would think thatother alternatives would be less expensive, or that the benefits of the fireplacesare so small that the combustion activities are better abandoned.

Figure 7.11 shows a typical distribution of numbers of particles and theirmasses on particle size, for a typical residential woodstove used in Norway. Thenumber distributions are dN/d log D, where N is the number of particles and


D their diameter. It is seen that pollution is far greater during start-up of theburner and that particle sizes extend down into the nanometer range. EuropeanUnion regulation has recently changed suggested limits from specifying PM10

to specifying PM2.5; Figure 7.11 shows that sizes below 2.5 mg play animportant role. The EU suggestions are 10–20 mg m–3 for long-term exposureand 35 mg m–3 for short-term exposure to PM2.5. Generally, the health impactsare larger the smaller the particles. Traditional impact assessment efforts arebased on PM10, such as the values shown in Table 7.8, taken from a Norwegiansummary of international data.

Based on Table 7.8 and measured particle pollution in Norway, Rosendahl(2000) calculated the total impacts and valued them according to the mon-etising assumptions given in Table 7.9, with an SVL some 40% lower than theExternE value shown in Tables 5.1 and 5.2, but with other entries similar.Singling out the contribution from residential wood-burning, Haaland arrivesat a damage figure for the city of Oslo alone of 100 million h per year, or 1250 hper wood-burning fireplace, or 240 h per mg of PM10 in the city and suburbanair (Haaland, 2005).

The study of health effects from particulate pollution is an active researchfield, with increasing evidence for the ultrafine particles being even moreharmful than the larger ones, both in the already identified area of lung diseases(Asgharian and Price, 2007) and in new areas such as DNA damage (Brauneret al., 2007).

Figure 7.11 Small particle emission from residential wood burners during differentphases of combustion. The distributions are on logarithmic intervals of theparticle diameter (mm), measured close to the point of release. The massdistributions (right-hand scale) are in arbitrary units, but total emissions atstart-up and stable burning are 126 and 36mg m–3 (Haaland, 2005).

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Pollution by fine particles has been mapped in Denmark (National Envir-onmental Research Institute, 2010a, 2010b) and in Finland (Karvosenoja,2008; Karvosenoja et al., 2009), where wood plays a large role in residentialenergy supply. Emissions identified by the Finnish study are shown in Table7.10. There are large variations, depending on the type of wood-burning device

Table 7.8 Increased annual risk of death or disability for a (Norwegian)person exposed to 1mg m–3 of PM10 particles (based on Rosen-dahl, 2000).

Impacts from 1mg m–3 exposure to PM10 particles

Risk per year Uncertaintya

Short-term exposurePremature death 0.000 747 4 LRespiratory hospitalisation 0.0076 MUpper respiratory tract, children 0.000 528 HLower respiratory tract, children 0.000 097 2 HDisability day 0.000 158 904 MLong-term exposurePremature cardiovascular death 0.007 04 MPremature cancer death 0.000 55 HBronchitis in children 0.145 HChronic pulmonary disease 0.055 M

aL¼ low, M¼medium, H¼high.

Table 7.9 Valuation assumption used in Norwegian studies (Rosendahl,2000), updated from 1997 to 2005 using inflation and exchangerate.

Impact Valuation (h)

Induced death (SVL) 1 500 000One year-of-life lost 69 000Chronic lung disease 240 000Bronchitis in child 240 000Hospital day (institutional costþwelfare loss) 504þ 613Day with symptom in upper respiratory tract (child) 27Day with symptom in lower respiratory tract (child) 67One salaried hour lost 22

Table 7.10 Small particle emissions from Finnish residential wood burning(based on Karvosenoja et al., 2009).

Type of residential usePM2.5 emission in Finland,year 2000 (t y–1)

Emission per unit of heatprovided (mg kWhth

–1)

Primary space heating 4040 720Occasional supplement 2230 573Vacation cottages 1310 943


used, but the largest emissions from basic residential heat provision comes frommanual-feed boilers and in all categories from iron stoves and open fireplaces,which are more common in Finland than in Denmark. In line with the Danishfindings of Figure 7.11, the large emissions from occasional wood uses andoccupation of vacation cottages (e.g. used in winter as a base for skiing) signalthe poor performance of wood burners during start-up. The particle emissionsfrom residential wood burning is 2–3 times higher than for burning coal in apower plant (per unit of final energy provided; for combustion heat the factor isanother 2–3 times higher, cf. Table 6.3).

Use of wood for residential heating is also common in China, along with coaland charcoal briquettes causing heating season pollution with both particlesand soot similar to those of London a century ago. Figures 7.12–7.14 show the1990–2005 emissions of small-size particles, black carbon (soot) and organiccompounds in China, distributed on sources. It is seen that the residentialsector is a major source of such emissions, but with the increasing personaltransportation sector augmenting its share. In 2005, the fine particles (PM2.5)contributed 39% of the particle emissions, 2.5–10 mm particles 15%, and par-ticles above 10 mm (PM10) 47% (Wu, 2009). Modernisation of the cementindustry has made its contribution decline, but the contributions from mostother industries and particularly from road traffic are increasing.

Black carbon emissions (Figure 7.13) overwhelmingly come from the resi-dential sector; while the contributions from burning coal products is aboutconstant, that of wood-burning is increasing. The emissions of organic com-pounds shown in Figure 7.14 are dominated by contributions from residentialwood burning, which thus impacts on human health in at least three important

Figure 7.12 Distribution of fine particle emissions in China on sources, for the period1990–2005. In 2005, 100% corresponded to 12.5 million tons PM2.5 (Wu,2009).

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ways. Studies in various parts of the world have also looked at the detailedtime-of-day dependence of the emissions from fuel-wood combustion, and anexample is shown in Figure 7.15 for Bamako (Mali), which is one of the mostpolluted cities of the world (cf. the discussion in Chapter 5.2). The highestvalues are in the evenings, when people are at home and use firewood.

In affluent countries, deliberate air pollution not for heating or otherdemand-related purposes is made on special days. An example is the bonfires

Figure 7.13 Distribution of black carbon emissions in China on sources, for theperiod 1990–2005 (Wu, 2009).

Figure 7.14 Distribution of organic compounds emissions in China on sources, forthe period 1990–2005 (Wu, 2009).


accompanying midsummer celebrations, consisting of open-air fires of woodand straw scrap. The burning of agricultural residues on the fields has beenabandoned in most countries today, but on this particular day the emissionsexceeding normal values by one to two orders of magnitude are accepted.Another celebration is New Year’s Eve, where pyrotechnic fireworks have aglobal impact, not only from smoke and particles but also seriously from heavymetals such as barium, strontium, potassium and iron. Steinhauser et al. (2008)measured concentrations of barium in Saalback (Austria), with snow samplesup to 500 times normal, and saw enrichment factors of 1–10 for the othermetals. In Denmark (population 5.4 M), it is estimated that 2500 tons offireworks (purchase price 50 Mh) are discharged every New Year’s night(Danish Association of the Hard of Hearing, 2008).

7.3 LCA of Home and Work Activities

Having looked at the building shell in Section 7.2, the next step will be toconsider the equipment use and activities taking place inside particular build-ings, such as private homes and various kinds of work places for industry,commerce and service. The variety of tools and devices in use is large, andalthough LCA studies of particular industries or activities may comprise a fullinventory of hardware and processes, there are many studies that choose toaggregate the data. In this respect, contemporary homes and work places arenot always so different as they may have used to be: microelectronic equipmentof various kinds dominate the cursory glance over activities, and only in spe-cialised industries such as raw materials extraction or basic manufacture will

Figure 7.15 Measured black carbon in city air over a 10-day period in Bamako, Mali(mg C m–3). Levels in other cities are indicated (Liousse et al., 2009).

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other concrete processes dominate the picture, as far as energy use and life-cycleimpacts are concerned.

As one example of an aggregate investigation, the life-cycle assessment ofcomplete life activities for a family may be considered. Such a study wascommissioned by the Danish Environmental Agency (Dall and Toft, 1996) andthe Danish Consumer Agency (1996). The approach is to use global materialsusage and global emissions to air, waterways and soils as a reference anddetermine if the Danish families are below or above the global averages. Incases where the resource or emission is not global, mean local values are used.This implies that the purpose of the study is to point to possible improvementsin the behaviour of Danish families, eventually helped by legislative initiatives,rather than to assess absolute values of the impacts.

The average global resource amounts consumed are interesting in themselvesand reproduced in Table 7.11. The emissions that are more representative forDenmark than for the world are shown in Table 7.12. With these referencevalues at hand, the resource usage and emissions from particular activities canbe assessed. This is done for a typical Danish family of two adults and twochildren, age 2 and 10, giving the distribution of resource and effluent impacts

Table 7.11 Average world citizen use of selectedresources (Dall and Toft, 1996).

Resource Value (kg cap–1 y–1)

Nickel 0.18Zinc 1.38Copper 1.67Manganese 1.79Chromium 2.33Aluminium 3.38Iron 103Natural gas 309Crude oil 592Brown coal 254Hard coal 574Wood 323Ground water 106 383Surface water 611 995

Table 7.12 Average world citizen discharge of selectedsubstances (kg y–1) (Dall and Toft, 1996).

Discharge Value (kg cap–1 y–1)

Toxic waste 21Radioactive waste 0.04Cinders, slag, char and ash 350Refuse 1350Emissions causing acidification 139Photochemical oxidants 19Greenhouse gases 9009


shown in Table 7.13, in units of the average world-citizen value. This is not afull life-cycle analysis, as for instance the resources and effluents used intreatment of the waste produced by the family are not assessed, but only theprimary amount discarded (1619 kg y–1 for the reference family).

One may be surprised that the resources and discharges of a four-memberDanish family are similar to those of an average world citizen, but the reason isof course that only the residential section impacts are included in the values forthe Danish family, while the figures for the world citizen comprise all activities,i.e. the remaining sectors of industry and commerce, of offices, administrationand public institutions (e.g. sewage treatment) and of non-private transporta-tion, as well as of primary raw materials extraction and conversion, e.g. inpower plants.

The figures in Table 7.13, which sum up to 147% and 99% of the averageglobal citizen values, are said by the authors to be uncertain by about a factor

Table 7.13 Resource use and environmental discharges of a Danish family(percent of world-citizen average per year) (Danish ConsumerAgency, 1996).

Activity Resource Discharge

FoodFood production 30.5 20.4Preparation and cooking 15.4 5.5Serving, dishwashing 4.9 2.8Food storage, refrigeration 3.0 3.8Food shopping 2.2 2.9ClothesWashing, drying 6.7 6.1Manufacture and purchase 3.2 2.1Maintenance and repair 0.2 0.1HygieneBath, etc. 11.0 3.6Toilet use 4.3 0.1Cosmetics, drugs (not included) 0.1 0.1RecreationComputer, audio-visual 8.6 4.0Sport, vacations, etc. 6.6 2.6Furniture, lighting 6.8 5.3CleaningWet cleaning, floors, etc. 2.1 0.5Vacuum cleaning, dust removal 0.6 0.4Other maintenance 0.1 0.0Space conditioningHeating 19.3 11.7Watering (garden, etc.) 1.1 0.0Maintenance work 0.2 0.1Personal transportBy car 20.1 26.4Bicycling 0.2 0.2

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of two. Although primitive, this kind of work may inspire to further studies,using other criteria than the moving target of some fictive 1996 world citizen. Itsuggests that even in affluent countries, food provision has very large impacts(in agreement with the LCA data for agriculture discussed in Section 6.3.5),followed by transportation and water usage. If the material welfare productsare sufficiently represented is more doubtful.

There have been detailed LCA studies of selected family activities. Forinstance, Greene (1992) in a study for the Australian Consumer’s Associationlooked at domestic and imported washing machines. The finding was that thelargest impacts were associated with use of hot water, both as regards energyuse, greenhouse gas emissions and emissions to air, soil and waterways. Thenext largest impact was from detergent manufacture, packaging and disposal,and in third place came the manufacture of the washing machine itself. Life-cycle greenhouse gas emissions for one washing machine were 10–18 t CO2

equivalent for use of hot-water washing cycles, less if cold-water washing wasselected, but possibly with higher impacts from detergents. Human andenvironmental toxicity of these detergents would be expected to be higher thanfor hot-water detergents, but these issues were not analysed in the study.

The question of recycling discarded home appliances has been dealt with byseveral authors. The Danish family study described above gave credit in theresource usage estimates for recycling of metals, without calculating the costof recycling; a more recent study by Nakamura and Kondo (2006) looks at therecycling of parts of electronic household appliances such as television sets orrefrigerators, also with the purpose of possibly giving an LCA credit. They findthat by taking into account the full cost and effort of disassembling and sortingthe end-of-life products, it is not certain that the externality of cheap disposalmethods (such as landfill dumping) will pay for the recycling. However, theyalso note that if the appliance in the first place is prepared for easy disassemblyand recycling by design, then the recycling can become economically preferablein an LCA perspective.

Many of the appliances and equipment types used in private households arealso used in offices and other workplaces. This is true of computers andassociated peripheral equipment such as printers, external storage media, flatscreens, copiers and scanners, and it is also true for mobile phones, road orboat navigation GPS units and smart phones. As an example, Zhou andSchoenung (2007) have looked at the transition from cathode-ray displays toliquid crystal and similar flat-screen technologies in an LCA perspective. Theypoint out that LCA studies may be useful both in the early design stage ofelectronic devices and also as a tool in consumer influence through evaluationof products and exposition of environmental factors in determining marketpreferences.

Batteries are increasingly used both in small-scale appliances and increas-ingly in larger size ones for garden equipment and for craftsman’s tools. Thenext step will be for traction of hybrid vehicles, as discussed in Section 7.1.2.Batteries are important in both household, transport and work appliances inindustry and offices. One particular case is batteries used for increasing the


availability of power in connection with intermittent energy production, e.g.from photovoltaic panels. Such storage batteries are discussed by Rydh andSanden (2005) in terms of energy payback rather than a full LCA. They findthat precisely the batteries preferred for their technical performance (energyand power densities) also have the best energy payback times. For NaS and Li-ion batteries, energy payback times of 3.5–4 years are found in a reference casewhere the batteries have a lifetime of 15 years and are operated in an optimisedPV battery configuration.

In analogy to the family LCA study mentioned above, an innovative LCAstudy has been made for ‘‘a week at the office’’ (Lehmann and Hietanen, 2009).A key subject for exploration is the distance-working possibilities offered bycomputer and telecommunication technologies. Employees may communicatewith company databases and colleagues from anywhere in the world (planes,cars, trains, homes or mountain resorts) and they may establish fully-featuredhome working bases. Compared to traditional office work, these options avoidcommuting travel and possibly reduce the need for company office space, bothof which have substantial energy costs and environmental impacts. Meetingsand conferences that do not require personal nearness may be conducted overvideophone channels, but with giving up many habits connected with rituals ofhandshaking and commonly enjoyed drinks.

Lehmann and Hietanen (2009) consider six alternatives to the conventionaloffice worker. The main features of the profiles may be summarised as follows:

� Profile A: Traditional office worker. Does all work in downtown officewithin normal working hours. Lives in same town and commutes by bus.

� Profile B: One-in-five day tele-worker. Works at home one day a week.Lives in suburbs and commutes by train.

� Profile C: Mobile worker. Does distance work four days a week, usingprivate car for meetings and frequent airplane trips abroad. Works anyplace, including hotel rooms; overtime with no fixed hours.

� Profile D: International elite. International travel three days a week, ofwhich two intercontinental. Rest of time in office; long hours. Commutesby train (the authors are from Switzerland and Finland!).

� Profile E: Home worker. All work in home office. Occasional nationaltravel to meetings, e.g. with employer. Uses private car or train.

� Profile F: Super-mobile worker. Always travelling worldwide, works onplanes or anywhere. Uses (hired) cars, taxis away from airports.

� Profile G: Virtual nerd. Works in cyberspace, using brain–computerinterfacing. Stays mostly at home.

The LCA impacts following from these modes of work are summarized inFigure 7.16, using one of the Pre Consultant’s indicator sets (EIP-99; see Pre,2006) to weigh impacts. Air travel dominates this assessment to an extent thatsuggests that the data used are not the most recent ones, and the use of publictransportation rather than private cars for commuting is not reflected in thechoice made by commuters (and particularly executives) in most countries. Yet

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the study gives an interesting new look on the environmental impacts of modesof work, with the possible changes to unfold in an increasingly more globalisedwork situation. The lowest impact is found for working from a home office, butas only environmental impacts are considered, one would have to add anassessment of other factors, such as work environment, the value of personalcontacts and impacts on family life.

Precursors to studies like that of Lehmann and Hietanen (2009) stretch backto the early realisation that computers could alter the work conditions in manytypes of businesses as well as private life, for the good or the bad, depending onwhether computers were used to provide more single-track unification, sur-veillance and control or to expand freedom and opportunities through uncen-sored and uncommercial communication across borders and political systems(Valaskakis and Fitzpatrick-Martin, 1980; Sørensen, 1985, 2001, 2008a).

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CHAPTER 8

Life-Cycle Analysis on aSystem-Wide Level

Individual life-cycle studies may be collected to allow assessment of entiresystems. Examples would be the electric utility sector of a country, a largecity (e.g. see Kennedy et al., 2010) or the complete energy provision and usesystem on a national, regional or global level. The aggregation is not alwaystrivial, because new types of impacts appear at the higher levels of perspec-tive, while others may appear less important. Furthermore, aggregate studiesare necessary ingredients in well-informed political debates on policy choicefor future development of the (energy) system, and the planning perspectivediscussed in Section 4.2 will place new requirements on the system-wideapplication of life-cycle methodologies. The following sections deal with thecharacterization of impact profiles to investigate on a national and on a glo-bal level, followed by a concluding section summing up where the LCA fieldstands today, and where it might be or should be going.

8.1 LCA in National Energy-System Planning

The consideration of impacts of an energy system on a national level would addsome concerns to the economic, environmental and social impacts consideredin most of the examples given in previous chapters. These include stability ofthe system against both technical breakdown and insufficient supply–demandmatching, but also against changes in external conditions, such as the prices ofimported fuels. To this come preferences in the society in question, regardingfactors such as decentralisation, democratic influence on the institutions in theenergy sector and questions of being able to rely on indigenous naturalresources and human skills. This makes issues of local employment and balanceof foreign payments important in the overall assessment, issues covered in theitems (d) and (e) in Table 2.1. Also, social factors associated with satisfactionof needs will enter into the political choice among different energy options.


By Bent Sørensen



295

As a result, the preparation of life-cycle assessment for assisting the decision-making process will need to place more emphasis on precisely the issues thatare difficult to present in monetary terms.

National life-cycle assessments of energy systems would usually compare arange of possible future supply structures and use the analysis of the systemcurrently in place as reference. Selecting future systems to contemplate may bedone by the scenario method described in Chapter 4, selecting (out of infinitelymany possibilities) a small number of scenarios that have been identified asinteresting in public or professional debates. Because an exceptionally largenumber of such scenarios have been proposed and discussed for Denmark,starting some 35 years ago, some of these will be chosen as examples below.

8.1.1 LCA of Selected Scenarios for Future Danish

Energy Systems

Energy scenarios have served as a tool for discussion between concerned citi-zens, acting individually or together in ‘‘grass-root groups’’, and governmentsand established energy departments or agencies since the appearance of theearliest scenario work going beyond business-as-usual forecasting (Sørensen,1975a, 1975b). In Denmark, some of the authors of these early scenariosbecame planners in the newly formed Department of Energy (1979) and soonthe official government reports contained not just one path but a fan ofalternatives offered for public discussion (fossil, nuclear and renewable sce-narios; Danish Department of Energy, 1981). The renewable solution foundpublic support and soon Denmark was a lead country in wind power and largebiogas plants. This lasted until the early 1990s, when the coal lobby succeededin obtaining permission to build a large overcapacity of coal-fired power plants.Combined with the following privatisation of the utility industry, this lead tofavouring coal as the ‘‘cheapest solution’’, omitting externality or indirect LCAcosts and levying the same carbon tax on all sources of energy, claiming that itwas fair to treat all in the same manner, whether or not they actually emittedgreenhouse gases. Despite the political success of the coal lobby, the debatecontinued and the positions in favour of renewable energy won acceptance farbeyond the ‘‘grass-root’’ movements, e.g. as evidenced by scenarios proposedby the Association of Engineers in Denmark (2006).

Generally, the scenarios proposed became more detailed with time and thefirst sketches were replaced by scenarios with careful checking of internalconsistency and existence of suitable implementation routes. During the late1990s, scenarios were worked out (Sørensen et al., 1994; Sørensen andMeibom,2000), based 100% on renewable energy and suggesting measures that wouldincrease efficiency by a factor of 3–5 over a 30-year period, in line with severalinternational studies (von Weiszacker et al., 1998). At the same time, moremodest scenarios were worked out in European Union projects (LTI ResearchGroup, 1998) that would lead to some 67% renewable energy in Europe (the 15EU countries at the time) as a whole.

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In the beginning of the 21st century, even more detailed scenarios wereconstructed, similar to the early 100% renewable ones, except that now thepossibility was explored that using Scandinavian hydro as backup forintermittent renewable energy production might no longer be possible(prompted by a Norwegian quest for exceedingly high economic compensationfor lending their reservoir assets to this purpose), but that instead Denmarkcould use the hydrogen technologies then appearing to be in rapid development(Sørensen et al., 2004; Sørensen, 2005). After the mentioned plan by theAssociation of Engineers in Denmark (2006), a new line of Danish energyscenarios explored the possibility that both Denmark and the other Nordiccountries could produce much more renewable energy that their domesticdemand and sell the surplus to Germany (likely not having enough renewableresources for its own energy demand), either as wind-produced electricitythrough existing (but reinforced) transmission lines or as liquid biofuels derivedfrom wood residues from the large forest areas particularly in Sweden andFinland (Sørensen et al., 2008; Sørensen, 2008).

Unfortunately, life-cycle assessments based on the more recent of thesescenarios have not (yet) been performed, so the earlier projects will be used forillustration, as there are also no recent national energy life-cycle analyses foundfor other countries.

Tables 8.1–8.3 gives summaries of life-cycle impacts and their valuation fortwo scenarios for future systems, compared with the life-cycle assessment of theexisting 1992 Danish energy system. The two scenarios are the 1994 100%renewable scenario for year 2030 (Sørensen et al., 1994) and the two-thirdsrenewable Danish part (Nielsen and Sørensen, 1998) of the scenario presentedby the LTI Research Group (1998) for 2050.

In 1992, the Danish energy system was still largely fossil, with smallcontributions from biomass and wind. The fossil energy products were also stillpredominately imported, as the Danish North Sea oil and gas explorationswere still at fairly low volumes. The inventory data used in Tables 8.1–8.3 aregiven in Kuemmel et al. (1997) and Figures 8.1 and 8.2 give an overview of theenergy flows in the overall Danish system in 1992, and in the agricultural sectorspecifically.

For the fair market scenario in Table 8.2 it has been assumed that Denmarkand the other members of the European Union will use specific energylegislation sparingly to achieve the necessary changes in future energy systems,and instead will introduce general legislation aimed at making the marketfunction in a better way than currently, taking into account the externality costswhenever energy decisions are made by consumers or by enterprises andinvestors. Exactly how to achieve this is a question still discussed by scholarsand largely ignored by those elected to political power, seemingly preferring toact on a day-to-day basis in response to newspaper or television headlines. Inany case, the fair market scenario of the European study (LTI Research Group,1998) assumes that it has somehow been achieved. In that work, a discussion ofthe fair market scenario for all the European countries is undertaken. Here theDanish part shown in Figure. 8.3 is used, based on the primary energy supply

297Life-Cycle Analysis on a System-Wide Level

Table 8.1 LCA impacts from the Danish energy system in 1992. The first entryin each column includes impacts globally; the second, separated bya ‘‘/’’, only impacts within Denmark (Kuemmel et al., 1997).

Environmental impactsand public health

Emissions(106 kg y–1)

Monetised value(Mh y–1)a

Range ofuncertainty(Mh y–1)b

Emission impacts from allsectors except trafficSO2 107/90 246/206 uncertainty of

air pollutionimpactsalmostentirely frommonetising

NOx (air pollution impactsin this row)

303/285 635/577

particulates 12.6/8.8 48/34HCl 3.8/3.6HF 0.2/0.2CO2 55 095/48 695CH4 84/25other volatile organiccompounds

142/130

N2O 2/2CO 849/813above greenhouse gasesas CO2 equivalents

73 676/65 098 7368/6510 H, g, m

Emission impacts fromtransportation sectorair pollution from carmanufacture

875/0 H, r, n-m

air pollution fromdomestic traffic

1752/1752 H, r, n-m

greenhouse gas emissionsas CO2 equivalents

15 485/8105 1549/11 H, g, m

Other impacts from sectorsapart from trafficvisual impacts 0.1/0.1 H, l, nnoise impacts 0.5/0.5 M, l, n

Other impacts fromtransportation sectorvisual impacts 6497/6497 H, l, nnoise impacts 1531/1531 H, l, ntraffic accidents 5029/5029 L, l, nstress and inconvenience 1562/1562 H, l, n

Occupational health and injury

All sectors excepttransportation

cases (per year)

death 11/2 29/5 M, l, nmajor injury 298/177 24/14 factor of 3

up/downminor injury 1728/380 2.1/0.5 factor of 3

up/down

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development shown in Figure. 8.4 and the end-use demand shown in Figure.8.5. These are the demands expected to materialize by rational behaviour of theplayers in the energy market. Details are given in Nielsen and Sørensen (1998).

The study behind the ecologically sustainable scenario of Table 8.3 alsoconsidered an intermediate scenario with both fossil and renewable energy,similar to the fair market scenario. The ecologically sustainable scenario isbased on normative assumptions of accepting a move towards an energy systemwhere energy efficiency investments that have costs lower than that of theenergy saved are indeed made, before energy supply is determined. The Danishintermediate conversion system is already fairly efficient, so the implication isthat the end user makes the necessary efficiency investments. Figures 8.6 and8.7 show the ecologically sustainable 2030 scenario layout and details of theagricultural sector; Figures 8.8 and 8.9 show the development in primary andend-use energy, in analogy to 8.1,8.2,8.4 and 8.5.

One impact not listed in Tables 8.1–8.3 is that of direct economy. The cost offuture systems depends on fuel price changes and development in the costsassociated with renewable energy equipment. These are in the ecologicallysustainable scenario assumed to reach values that will make it possible to realisethe scenario, while in the fair market scenario it is assumed that the marketimperfections are corrected so that the lower environmental costs of renewableenergy, together with technology improvement and economy of mass produc-tion, will make them enter into market conditions.

The environmental advantage of avoiding greenhouse gas emissions and airpollutants by use of renewable energy sources is clear, as the summary ofTables 8.1–8.3 in Figure 8.10 clearly shows. Details of the life-cycle analysesperformed have several uncertainties and the original calculation of Kuemmelet al. (1997) used a higher monetised value for global warming, making the 1992impacts considerably higher than those of the fair market scenario. Here, thefair market scenario has the same level of monetised impacts as the originalfossil system. This is because the annoyance of people having to look at windturbines or solar collectors is taken as very high; the same is the case for noiseimpacts (based on ExternE, European Commission, 1995). Probably the noiselevels from wind turbines that were estimated when this study was made were


Other impacts

Road construction andmaintenance

1291/1291 L, r, n

Other infrastructure NQLabour requirements lowImport fraction highResilience lowSocial benefits highResource depletion high

aNQ=not quantified. Values are aggregated and rounded (to zero if below 0.1 mh kWh–1).bL, M, H=low, medium or high uncertainty; l, r, g=local, regional or global impact; n, m, d=near,medium or distant time frame.


Table 8.2 LCA impacts from the 2050 energy scenario for Denmark as part ofa fair market European scenario (Kuemmel et al., 1997; Nielsen andSørensen, 1998). Global and Danish impacts; see caption and notesfor Table 8.1.

Environmental impactsand public health


Monetisedvalue(Mh y–1)a


Emission impacts from allsectors except trafficSO2 8.1/4.6 19/11 uncertainty of

air pollutionimpacts almostentirely frommonetising

NOx 7.3/9.2 23/29particulates 0.5/0.2 2/1HCl 0.002/0HF 0/0CO2 (from importedequipment/materials only)

893/0

CH4 –623/–635other volatile organiccompounds

18/30

N2O 1.5/4.7CO 11/4above greenhouse gasesas CO2 equivalents

1228/1438 123/144 H, g, m


1427/0 H, r, n-m

air pollution fromdomestic traffic

204/204 H, r, n-m

CH4 from biogas –4.4/–4.4 H, g, mNOx from methane engines 4.8/4.8CO from methane engines 1.3/1.3oil product combustion CO2 4749/427total net greenhouse gasemissions as CO2

equivalents

4854/532 485/53 H, g, m

Other impacts fromsectors apart from trafficvisual impacts 4/14 H, l, nnoise impacts 27/85 M, l, n

Other domestic impactsfrom transportationvisual impacts 10 593/10 593 H, l, nnoise impacts 2496/2496 H, l, ntraffic accidents 8200/8200 L, l, nstress and inconvenience 2547/2547 H, l, n



cases (per year)

death 3/9 8/23 M, l, nmajor injury 159/512 13/40 5–35/14–113minor injury 412/1205 0.5/1.4 0.2–1.4/0.5–4

300 Chapter 8

higher than it would be for present turbines, and the visual impacts wereevaluated on the basis of attitudes in European countries with no experiencewith wind energy. Interview studies in Holland and Denmark, where windturbines have been used for centuries, showed much less offence taken. Tomake the comparison fair, the same valuations of noise and visual impacts havebeen used in valuating the ecologically sustainable scenario, and it is seen thatdespite the possible overestimation of these impacts the total of monetisedimpacts have been reduced to less than half, relative to the fair market scenarioor the original fossil system.

The issue for the policy debate is thus centred on the economic dimension,but of course including the externality costs identified by the LCA studies. Ifthe fossil resources nearing depletion have rising prices, as economic expecta-tion of market behaviour in a situation of shortage would predict, then sub-stitution will take place and the market is supposed to select the lowest-pricealternative. If this happens to be wind power, this supply option will beexpanded, but because renewable energy supply is limited by fundamentalresource flow properties, a ceiling will eventually be hit, above which wind is nolonger the most attractive choice, or will simply not be available. Then theinvestors will move to the next item on the list, which may be biomass, andwhen the natural limitations of this source has been reached, move further onto photovoltaic power, or whatever comes next in price priority. This process ofsubstitution is unlikely to be smooth and basic uncertainties have been pointedout, as discussed in Section 4.1.2.

8.2 Assessing Future Directions in a Global Context

The investigation of global energy choices by the use of LCA methods againshifts the emphasis onto issues of geopolitical significance, such as resilience,stability and avoiding causes for conflict or unequal treatment of differentgroups of countries. Clearly, the consultant-based LCA studies comprisingonly environmental impacts will not suffice to provide the necessary signals tointernational decision makers or discussion participants.


Other impacts


2106/2106 L, r, n

Other infrastructure NQLabour requirements mediumImport fraction mediumResilience fairly highSocial benefits highResource depletion fairly low

aNQ¼ not quantified. Values are aggregated and rounded (to zero if below 0.1 mh kWh–1).bL, M, H=low, medium or high uncertainty; l, r, g=local, regional or global impact; n, m, d=near,medium or distant time frame.


Table 8.3 LCA impacts from an efficient, 100% renewable Danish energysystem in 2030, called the ecologically sustainable scenario(Kuemmel et al., 1997; Sørensen et al., 1994). Global and Danishimpacts, cf. Table 8.1.

Environmental impacts andpublic health


Monetisedvalue (Mh y–1)a


Emission impacts from allsectors except trafficSO2 10.7/8.6 25/20 uncertainty of

air pollutionimpacts almostentirely frommonetising

NOx (air pollution impactsin this row)

9.8/4.7 31/15

particulates 0.8/0.5 3/2HCl 0.004/0HF 0.005/0CO2 455/0CH4 –52/–54other volatile organiccompounds

14/13

N2O 2.3/1.9CO 58/48above greenhouse gases asCO2 equivalents

2472/1614 247/161 H, g, m


662/0 H, r, n-m

air pollution from domestictraffic

192/192 H, r, n-m

NOx from biofuel engines 4.8/3.2CO from biofuel engines 1.3/0.9above two greenhouse gasesas CO2 equivalents

196/131 20/13 24–74

Other impacts from sectorsother than trafficvisual impacts 2/2 H, l, nnoise impacts 15/15 M, l, n

Other domestic impactsfrom transportationvisual impacts 4920/4920 H, l, nnoise impacts 1159/1159 H, l, ntraffic accidents 3808/3808 L, l, nstress and inconvenience 1183/1183 H, l, n



cases (per year)

death 4/4 10/10 M, l, nmajor injury 160/156 13/12 factor of 3 up/

downminor injury 424/420 0.5/0.5 factor of 3 up/

down

302 Chapter 8

Resilience comprises the requirement that energy prices do not jump up anddown in ways that may negatively influence the global economy, e.g. by makinginvestors hesitate to put their money in the energy sector. Price behaviour suchas the one exhibited in Figure 4.6 is an example. Geopolitical implications ofuncertain fossil energy prices and threats of withdrawing delivery can lead toconflicts, including wars, and the same appears to be the case for nuclearproliferation, a problem entrenched in the combined pursuance of civil andmilitary nuclear technologies (see the discussion in Section 6.2).


Other impacts


978/978 L, r, n

Other infrastructure NQLabour requirements B10 person-y

MWinst–1

Import fraction lowResilience highSocial benefits highResource depletion low

aNQ=not quantified. Values are aggregated and rounded (to zero if below 0.1 mh kWh–1).bL, M, H=low, medium or high uncertainty; l, r, g=local, regional or global impact; n, m, d=near,medium or distant time frame.

Figure 8.1 Danish energy system 1992 (units: PJ y–1; Sørensen et al., 1994).


Figure 8.3 The 2050 Danish energy system envisaged by the fair market scenario(units: TWh y–1). The total primary input of 235 TWh y–1 is equivalent to775 PJ y–1. The transport demand listed as ‘‘biogas’’ may include hydro-gen (Nielsen and Sørensen, 1998).

Figure 8.2 Danish biomass sector 1992 (units: PJ y–1; Sørensen et al., 1994).

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Figure 8.4 Primary energy endpoints in the Danish fair market scenario (Kuemmelet al., 1997).

Figure 8.5 End-use energy demand development in the Danish fair market scenario(Kuemmel et al., 1997).


Figure 8.6 Danish ecologically sustainable energy scenario for 2030 (PJ y–1; Sørensenet al., 1994).

Figure 8.7 Biomass sector of 2030 scenario (PJ y–1; Sørensen et al., 1994).

306 Chapter 8

There may also be drawbacks of trying to present too aggregated life-cycleassessments. Presenting overall positive average impact amounts may hide thatparticular parts of the energy system are leading to unacceptably high damage,e.g. for a limited group of people.

Delayed impacts are often associated with the assessment of energy systems,from the greenhouse effect depending on emissions accumulated over decades,or radioactive and toxic waste believed disposed but reappearing into thebiosphere after 50 or 500 years (like the war gases dumped in the Baltic Seaafter World War II and now showing up in fish catches from the region).Different populations enjoy the benefits of energy use and the adverse effects oftime-displaced impacts, both different populations in space (exemplified bygreenhouse warming having negative impacts in parts of the world notcontributing significantly to the problem, cf. Section 5.1.3) and differentpopulations in time. The latter issue is studied under the name ‘‘intergenera-tional equity’’ (e.g. see Diesendorf, 1997) and it is important to keep it on thelist of impacts, which often leads to abandoning the conventional use of

Figure 8.8 Primary energy endpoints in the Danish ecologically sustainable scenario(Kuemmel et al., 1997).


discounting and instead apply an intergenerational interest rate near zero(Sørensen, 2010).

Another impact area of particular importance for global assessment is thequestion of poverty and of equity. This touches the areas of health as well asthat of development (cf. Table 2.1). Different energy solutions will affectdifferent groups in developing societies differently: some will allow electricity tobe used in remote regions, by use of decentralized power production rather thanhaving to extend grids from centralized power plants, some will use biomassresidues in a way that leaves improved fertiliser as a byproduct, to the benefit oflocal agriculture, and so on. These impacts should be flagged or evaluated andthe importance of development issues should be truly reflected in the valuation,even if it may not be quantitative (e.g. see WRI, 2008). Damage cost wouldinclude those arising from a development where a more equitable distributionof wealth is not accomplished, but this again involves difficult-to-valuate issuessuch as social unrest, conflict and war.

Figure 8.9 End-use energy demand development in the Danish ecologically sustain-able scenario (Kuemmel et al., 1997).

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Again, very few of the many global scenarios created over the past decadeshave been subjected to LCA to an extent comparable with the LCA studies ofsingle installations or even national systems. A meaningful assessment mustinclude the difficult issues and this would be an obvious invitation for scholarsto address over the coming years.

8.3 Wrapping Up

From its origin, the life-cycle assessment technique was aimed at providing thedecision maker with a tool for allowing a comprehensive comparison of tech-nological solutions with very different profiles of positive and negative impacts.It was essential to include all impacts, upstream and downstream, and from sidechains delivering input or handling output from the main chain from manu-facture over operation to final disposal.

Many of the required methods were already available 50 years ago: resourcedepletion studies, risk analysis, environmental impact assessment, direct costand occupational health as well as public health studies, but they had to becombined and presented in a way suited for non-technical decision makers.This was the start of the discipline that was first called total assessment orcradle-to-grave assessment and ended up as life-cycle analysis and assessment.The intention was to include all impacts and it was recognized that one had to

Figure 8.10 Comparison of all monetised impacts in the fair market and the ecolo-gically sustainable scenarios for future energy supply in Denmark,together with, as reference, the system already in place (based on Tables8.1–8.3 and Table 6.1 for global warming impacts).


be open to new types of impact being identified and the need to add these in thefuture. So far so good!

However, when around 1990 the LCA came to be seen as a business areafor consultants, a disagreement arose between the LCA service-providingcompanies and the scientific community. The former wanted to restrict thescope of LCA to environmental pollutants and impacts on ecology andhuman health (probably because this was an established area of engineeringconsultancy, conducted under names such as ‘‘environmental impact assess-ment’’ or just EIA) and omit other impacts such as social and geopolitical ones.They wanted to standardize the procedure so that different consultants wouldnot provide wildly different results (that had happened in California where thefirst legislative demand for LCA had been introduced) and for this reasonindustry prescriptions were formulated and soon transformed into an ISOstandard.

This should have caused the alarm bells to ring. No other area of science isrestricted by ISO norms and the practical application of technology assessmentmethods should be open ended because both the technologies and the publicperception of what is important will necessarily change with time. The ISOpeople have had a certain amount of understanding for this as they state thatno single methodology will be recommended, but in practice only theenvironmental dimension is seriously covered by the descriptions in the ISOdocuments; it is only recently that ‘‘dissidents’’ have raised the possibility ofadding some social impact categories (UNEP, 2009).

It is therefore high time to remind ourselves that the whole purpose of LCAis to include all impacts as comprehensively as possible, and that posingrestrictions on what should be included amounts to a return to the situationbefore LCA was first discussed (without using the name), a situation whereproponents of one technology or another produced analyses proving that theirtechnology was superior to others on the basis of a select subset of criteria (suchas nuclear power studies including impacts on global warming but not impactson nuclear proliferation).

Likewise, it can be a problem that the LCA software includes thousands ofsubstances and invites a long list of associated impacts, sometimes based onstudies in Romania that may be totally irrelevant for the actual location andtechnology, but which crop up as ‘‘default’’ if the user of the software does notpay attention. The scientific analysis should identify which are the importantimpacts in the concrete case at hand and should quantify and communicate theimpacts derived for these in a way that is clear to the decision maker. Theoutput from most ISO-conforming software is far from achieving this clarity orit attempts to achieve clarity by inventing some indicators that do not havegeneral acceptance and are often not transparent to the decision maker (andsometimes not even to the consultant, as evidenced by examples where apotentially dangerous substance is highlighted as giving unacceptably highimpacts in the indicator display, but where in reality the pathways leading toproducing such high impacts can be controlled by suitable engineeringmeasures).

310 Chapter 8

It is important to present the findings of impact studies in a way that reachesthe target group of decision makers and politically active citizens. However,this does not mean simplifying the format arbitrarily. Very few comprehensivestudies allow results to be expressed in a single number, not in dollars or euros,and equally not in eco-points or other indicators. Not only may the scientificcontent be blurred by weighting quantities not easily lending themselves tocommon units, but impacts may escape attention because they can only beexpressed in ways fundamentally different from the one involving monetising(whether into currency or into indicators). This strongly emphasises the need tokeep results in a multivariate form and to devote work to presenting these inways that will not scare off the members of the target groups (cf. Ulgiati et al.,2006). To put things on the edge, one could say that if the impact fromsolutions to choose from could each be characterised by a single number,one would not need politicians to tell which is the smallest and make theobvious choice.

In conclusion, there is a need to get back to the basic view of LCA as a wayto provide the decision makers, as well as the general population wantingto exercise their democratic influence, with a comprehensive and easilyunderstandable overview of impacts in different categories, allowing theweighting to emerge as the outcome of a political debate rather than beingimposed by bureaucrats. One may see it as a kind of consolation that noimportant political decisions in history have been taken on the basis ofeconomics alone, implying perhaps that political decision makers are aware ofthe risk associated with relying on too narrow a field of expertise.

References

Association of Engineers in Denmark (2006). Ingeniørforeningens Energiplan2030. Ingeniørforeningen i Danmark, Copenhagen.

Danish Department of Energy (1981). Energiplan-81. Copenhagen (in Danish).Diesendorf, M. (1997). Principles of ecological sustainability. Chap. 3 in

Human Ecology, Human Economy (Diesendorf, M., Hamilton, C., eds.),pp. 64–97. Allen & Unwin, Sydney.


Kennedy, C., et al. (2010). Methodology for inventorying greenhouse gasemissions from global cities. Energy Policy, doi: 10/1016/j.enpol.2009.08.050.


LTI Research Group (1998). Long-Term Integration of Renewable EnergySources into the European Energy System. Physica-Verlag, Heidelberg.

Nielsen, S., Sørensen, B. (1998). A fair-market scenario for the Europeanenergy system. In LTI Research Group (1998), Chap. 3, pp. 127–191.

Sørensen, B. (1975a). Energy and resources. Science 189, 255–260.


Sørensen, B. (1975b). An alternative development. In Alternative EnergySources and Policies (U. Geertsen, ed.; in Danish), pp. 12–37. EnergyInformation Board, Danish Ministry of Trade, Copenhagen.


Sørensen, B. (2008). A renewable energy and hydrogen scenario for NorthernEurope. Int. J. Energy Res. 32, 471–500.

Sørensen, B. (2010). Renewable Energy, 4th edn. Academic/Elsevier, BurlingtonMA (previous edns. 1979, 2000 and 2004).

Sørensen, B., Nielsen, L., Pedersen, S., Illum, K., Morthorst, P. (1994).Renewable energy system of the future (in Danish). Danish TechnologyCouncil, Report 1994/3, Copenhagen.


Sørensen, B., Petersen, A., Juhl, C., Ravn, H., Søndergren, C., Simonsen,P., Jørgensen, K., Nielsen, L., Larsen, H., Morthorst, P., Schleisner,L., Sørensen, F., Petersen, T. (2004). Hydrogen as an energy carrier:scenarios for future use of hydrogen in the Danish energy system. Int. J.Hydrogen Energy 29, 23–32. First issued in Danish as Text 390 fromIMFUFA, Roskilde University. Available at http://rudar.ruc.dk/handle/1800/3500, file IMFUFA_390.pdf.

Sørensen, B., Meibom, P., Nielsen, L., Karlsson, K., Petersen, A., Lindboe,H., Bregnebæk, L. (2008). Comparative assessment of hydrogen storage andinternational electricity trade for a Danish energy system with wind powerand hydrogen/fuel cell technologies. Final Report to Danish Energy Agency.Roskilde University. Part available as EECG Research Paper 1/08 fromhttp://rudar.ruc.dk/handle/1800/2431.

Ulgiati, S., Raugei, M., Bargigli, S. (2006). Overcoming the inadequacyof single-criterion approaches to life cycle assessment. Ecol. Model. 190,432–442.

UNEP (2009). Guidelines for social life cycle assessment of products. UNEP/SETAC Life Cycle Initiative, UNEP Paris, www.unep.org/pdf/DTIE_PDFS/DTI�1164�PA-guidelines_sLCA.pdf.

von Weiszacher, E., Lovins, A., Lovins, H. (1998). Factor four: Doublingwealth, halving resource use – the new report to the Club of Rome.Earthscan, London.

WRI (2008). World Resources 2008 (P. Angell, ed.). In collaboration withUnited Nations Development Programme and the World Bank. WorldResources Institute, Washington, DC; available online at http : //www.wri.org.

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Glossary of Words and Concepts

Avoidance cost: Rather than calculating the cost of damage from a certainactivity, one may calculate the cost of avoiding the damage by estab-lishing some other way of achieving the same end. Ideally, both costsshould be calculated and compared as avoiding impacts is a goal ofLCA, but there are many ways of avoiding an impact and one cannotbe sure that all have been identified. However, if one identifiedavoidance cost is lower than the cost of the damage of the ongoingactivity, it provides a backstop solution. Sometimes the avoidance costis just used as a template for a damage cost that cannot be evaluated.

Carbon dioxide (CO2): The most important greenhouse gas emitted by com-bustion of fossil fuels.

CCGT power plant: Combined cycle gas turbine, allowing power to be drawnalso from primary step exhaust gas.

CFC gases: Chlorofluorocarbons used, for example, as working fluids inrefrigerators; may, if released, travel to the upper atmosphere andcause ozone depletion. They are also greenhouse gases altering theradiation balance.

Contingency valuation: Establishing the monetary value of some impact byinterview studies in the relevant population.

Damage cost: The monetised value of a calculated impact from the activityunder study.

Dengue: A tropical disease.Dose–response relationship: The number or magnitude of impacts (e.g. on

health) as a function of the dose of the offending substance (e.g. airconcentration of a pollutant).

ECU: Currency unit used during an initial period by the European Union (notto be confused with a historical French currency denomination of thesame name), subsequently replaced by the euro. The ECU was aweighted average of the currencies of European Union member statesand not, as the euro, an independently valued currency.


By Bent Sørensen



313

End-use energy: The energy actually made useful by the final user, i.e. theperson converting energy into a service or a product. This is differentfrom the energy delivered to the end user, by the conversion losses ofthe final conversion.

Euro (h):A common European currency supposed to be used only by countriesthat fulfil certain economic stability conditions.

Externality: A cost being inflicted upon specific actors in a market (the costmay eventually be picked up by entire societies through governmentsor other public agents), but not included in the market prices.Examples are certain environmental clean-up costs or restrictions inthe choices remaining for future generations.

Fair market: A market where transaction costs reflect all costs, whether director indirect, but where no other disturbance enters into prices (such asgeneral taxation). It is a market not distorted by monopolies or actorsof widely different levels of power.

GNP: Gross national product; a monetary measure of all activities in a society,whether or not they are necessary or desirable.

Hedonic pricing: Estimating externality costs by comparing property pricesfor similar locations, but with and without the offending impactconsidered.

Impact profile: A presentation of impacts as a range of values expressed indifferent units. See also Multivariate analysis.

Impacts: The effects on health, environment and social structure studied in alife-cycle analysis.

Implementation: The process of realising (here) a given energy scenario over aperiod of time, taking the necessary political decisions along the way.

Information society: A society where most activities are knowledge based asopposed to material based. Sometimes the term is understood to includematerial activities related to information handling and transfer.

Input–output matrix: The input–output method furnishes a consistent picture ofa given economy, by keeping track of how outputs from one sector areused as inputs to other sectors. Each transfer is represented by acoefficient in an input–output matrix. The coefficients have to bedetermined by actual measurement (or available statistical data) andwill in general vary with time.

Inventory: A collection of data required for performing a life-cycle analysis,usually comprising at least a list of materials used in the product orsystem under study.

Life-cycle analysis (LCA): Identifying direct and indirect impacts from aproduct or a system through all the phases of procurement,manufacture, use and disposal.

Life-cycle assessment: Evaluating the impacts found by life-cycle analysis, usingmonetisation or indicators with politically determined weights ofdifferent impact types, or multivariate analysis.

Load management: Achieving a desired load profile by deferring certainnon-time-urgent energy activities (e.g. shifting clothes washing

314 Glossary of Words and Concepts

off-peak by signals from a timer either in the washing machine or sentfrom the generating utility over the electricity grid or the telephonenetwork).

Malaria: Important tropical disease transmitted by mosquitoes. It has becomeresistant to several drugs traditionally used to treat and preventspreading of the disease.

Market: The outlet for trading transactions between different actors, oftenassumed to comprise a large number of independent agents of similar(small) size. The latter requirement reflects the view that a marketsituation cannot be established with the presence of monopolisticagents on the selling or buying side.

Multivariate analysis: Stating impacts in a range of separate units for thedecision makers to weigh against each other in a multicriteriaassessment.

Onchocerciasis: A tropical disease.Primary energy: Energy supplied for further conversion or use. Primary energy

usually denotes the energy left after losses in extraction and initialtreatment.

Purchase parity: Using equal purchasing power instead of currency exchangerates.

Renewable energy: Energy sources that are replenished in practical terms,despite human utilisation. This includes energy sources derived fromthe disposition of solar radiation in the Earth–atmosphere system(direct solar energy, wind energy, wave energy, biomass), disregardingthe ultimate depletion of nuclear fuels within the Sun. The solarradiation received is returned as heat re-radiation to space, whether ornot there has been human intervention in the chain of conversionprocesses. Also, tidal energy from solar system gravitational energyand geothermal energy from absorbed solar radiation are consideredrenewable, in contrast to geothermal energy derived from radioactivityin the Earth’s crust. For each renewable energy flow there is a max-imum rate of sustainable use, beyond which the used energy may notbe fully replaced.

Scenario: A more or less detailed snapshot picture of society or of some sectorof society, usually describing one of several options for the future.

Schistosomiasis: A tropical disease.Standard price: The market price that will ensure a prescribed penetration of a

given product or service. This may be highly dependent on other partsof the system, or on economic decisions in other areas, and thus is oflimited use.

Statistical value of life: The average monetary damage to society of losing anarbitrary member of society by an accident, a health impact or otherinflicted impact. No ethical valuation of human life is involved.Some studies (such as European Commission, 1995) use the sameconcept to represent the average value attributed to a life by individualcitizens.

315Glossary of Words and Concepts

Stochastic processes: Processes subject to the laws of a statistical distribution.The risk of failure for a large number of identical components may fallinto this category.

Sustainable system or practice: One that can be maintained indefinitely, withoutincreasing impacts on the remaining system or society.

Transport work: For person transportation, equal to the product of thenumbers of passengers and the kilometres driven; for freighttransportation, equal to the product of the tonnes carried and thekilometres driven.

US $: The common currency unit of the United States of America. This unit isoften used for international comparison of costs, although it is fairlyunsuited due to the rather small importance of international trade inthe US economy, and hence a political lack of interest in keeping stableexchange rates between the US $ and other important currencies.

Willingness to pay: An indirect way of valuing damage, based on interviewstudies or indirect disclosure. Caveats relate to the different affluence ofpeople influencing their expression of willingness.

316 Glossary of Words and Concepts

Units and Conversion Factors

Powers of 10

Prefix Symbol Value Prefix Symbol Value

atto a 10–18 kilo k 103

femto f 10–15 mega M 106

pico p 10–12 giga G 109

nano n 10–9 tera T 1012

micro m 10–6 peta P 1015

milli m 10–3 exa E 1018

SI Units

Basic unit Name Symbol

electric current ampere Alength metre mluminousintensity

candela cd

mass kilogram kgplane angle radian radsolid angle steradian srtemperature degree Kelvin Ktime second s

Derived unit Name Symbol Definition

electric capacitance farad F A s V�1

electric charge coulomb C A s


By Bent Sørensen



317

Derived unit Name Symbol Definition

electric resistance ohm O V A�1

energy joule J kg m2 s�2

force newton N J m�1

frequency hertz Hz cycle s�1

illumination lux lx cd sr m�2

inductance henry H V s A�1

luminous flux lumen lm cd srmagnetic flux weber Wb V smagnetic flux density tesla T V s m�2

potential difference volt V J A�1 s�1

power watt W J s�1

Conversion FactorsType Name Symbol Approximate value

energy electon volt eV 1.6021� 10�19 Jenergy erg erg 10�7 J (exact)energy calorie (thermochemical) cal 4.184 Jenergy British thermal unit Btu 1055.06 Jenergy Q Q 1018 Btu (exact)energy quad q 1015 Btu (exact)energy tons oil equivalent toe 4.19� 1010 Jenergy barrels oil equivalent bbl 5.74� 109 Jenergy tons coal equivalent tce 2.93� 1010 Jenergy m3 of natural gas 3.4� 107 Jenergy kg of methane 6.13� 107 Jenergy m3 of biogas 2.3� 107 Jenergy litre of gasoline 3.29� 107 Jenergy kg of gasoline 4.38� 107 Jenergy litre of diesel oil 3.59� 107 Jenergy kg of diesel oil/gasoil 4.27� 107 Jenergy m3 of hydrogen at 1 atm 1.0� 107 Jenergy kg of hydrogen 1.2� 108 Jenergy kilowatthour kWh 3.6� 106 Jlength angstrom A 10�10 mlength inch in 0.0254 mlength foot ft 0.3048 mlength mile (statute) mi 1609 mmass tonne (metric) t 103 kgmass pound lb 0.4536 kgmass ounce oz 0.02835 kgpower horsepower hp 745.7 Wpower kWh per year kWh y�1 0.114 W

318 Units and Conversion Factors

Type Name Symbol Approximate value

pressure atmosphere atm 1.013� 105 Papressure bar bar 105 Papressure pounds inch�2 psi 6890 Paradioactivity curie Ci 3.7� 108 s�1

radioactivity becqerel Bq 1 s�1

radiation dose rad rad 10�2 J kg�1

radiation dose gray Gy J kg�1

dose equivalent rem rem 10�2 J kg�1

dose equivalent sievert Sv J kg�1

temperature degree Celsius 1C K – 273.15temperature degree Fahrenheit 1F 9/5 Cþ 32time minute min 60 s (exact)time hour h 3600 s (exact)time year y 8760 hvolume litre l 10�3 m3

volume gallon (US) 3.785� 10�3 m3

319Units and Conversion Factors

Subject Index

A1 IPCC climate modelscenario 114–16

A1B IPCC climate model scenario114–21, 124–5, 139–40, 146–7

accidents/injurysee also deaths/mortality; healthimpacts; risk

BritainCCGT natural-gas fuel chainexample 205

coal fuel example 196definition of accidents 40–1Denmark

1992 energy system 298passenger cars 256, 264–5, 268

France, nuclear fuel cycleexample 208

Germany, coal fuel example 198hydropower 227mining accidents 179, 202monetising accidental deaths 70,71–3

nuclear reactors 44–5, 94, 95, 96,173–81, 207

photovoltaic cell manufacture 222,223

wind turbine manufacture 214activities, human 87, 88–90, 284–9actor triangle 77–8adaptation to temperaturechange 137–8, 147

advertising ethics 39aggregation dimensions 15, 44–7

fuel sources 46sites 44, 45, 46

social settings 44–5technologies 44, 45, 46time 44

agriculturebiofuels extraction 97, 245energy supply/demand 88food provision 234–8greenhouse warming 125–7, 159,160, 161

plant diseases 126air pollution see emissionsairplane industry safety 41algae

hydrogen production 231microalgae 246, 247near-shore waters 156

allocating methods, emissions 192,193

amorphous silicon panels 221,224–5

animal food products 236, 237,238, 243

anopheline mosquito 148–9applications of life-cycleanalysis 109–311

artificial points systems 6, 14–16,69

assessment see life-cycle assessmentatmospheric transport see emissionsaudacious citizen archetype 102–3audio equipment 87Austrian biofuel combined power andheat plant 239–40

average world citizen 285, 286avoidance cost 313

B1 IPCC climate model scenario 114,115, 116

background inventories 8, 54–63Bamako (Mali) 283, 284basic energy demands 82–90basics of life-cycle analysis 26–34batteries, home appliances 287–8beef meat production 236, 237Berezinsky National Park, USSR176

bilharziasis 150, 151, 153bio-diesel 245–7bio-ethanol 245biofuels

Austrian biofuel combined powerand heat plant 239–40

carbon dioxide emissions 194first/second-generation 239gaseous/liquid 238–47overview 97

biogas 241, 242, 243, 244biologically-acceptablesurroundings 83, 84–5

biomass 239, 240, 304, 306black carbon emissions 282, 283bottom-up approach 19, 44, 82,195

Brazil, hydropower plant 227, 228Britain

CCGT natural gas fuel chain205–6

coal fuel chain example 196–7buildings 85, 137, 272–84bureaucracy 15business-as-usual forecasts 98

cadmium–tellurium cells 225–7caesium-137 175, 178California 5carbon capture 92–4, 203–4carbon dioxide

allocation 192, 193biofuels 194disposal 92–4fuel cell plants 231grandfathering principle 193, 194

last 300,000 years 111, 112ocean disposal 93–4per capita emissions 127photovoltaic cells 223post-combustion capturetechnologies 92–4, 203–4

Slovenian steam plantemissions 60, 62–3

storage 123US road vehicle traffic 270–2

carcinogenic substances 172Carson, Rachel 2catalytic processes 93, 247cause of death, assignation 147CCGT natural-gas power cycle 204,205–6

celebratory fires 283–4cellulosic material 97Cemskums insulation 276, 277centralised photovoltaicinstallations 81, 82

Chagas disease 150, 152, 153chains of energy conversion 27, 28,29, 47–51

chaotic Earth–atmospheresystem 110

checklists of concerns 3–4chemical reactions 166

carbon dioxide conversion tomethanol 93

transesterification 247Chernobyl 1987 nuclear accident 44,173–80

chicken meat 236, 237China, residential heating 282–3China syndrome melt-through174

chlorosilane 221circulation models

Earth–atmosphere system 29–31,110–25

particulate matter dispersal166

weather forecasting 122clean conversion technologies 80clean fossil technologies 90–4

322 Subject Index

climate changedirect health impacts 136–48ecosystem impacts 155–6modelling 110–25

grid size 122coal-fired power plants

Britain, coal fuel chainexample 196–7

carbon dioxide emissions 194chain calculations 48–50Denmark

coal fuel chain example 200–1,202

energy scenario 296ExternE coal externality study 5,34, 156–7

Germanycoal fuel chain example 198–9Lauffen German plant 166–8

impact profile approach 76life cycle analysis 194–204mining

accidents 179, 202ExternE externality study 34

combined cycle gas turbines(CCGT) 204, 205–6

combined power and heat (CPH)plants 239–47

combustion emissions 165–73, 192–206commercial software 6–7, 9–16communication with decisionmakers 67–8

compliance 58computer models 110–25

softwarecommercial 6–7, 9–16generic databases 6, 7ISO-conforming 310ReCiPe approach 9, 10

concerned citizen archetype 102–3concerns checklists 3–4concrete 216construction industry 88

Denmark, roads 258–9, 264–8consumer product life-cycleanalysis 35

context choice 41–4contingency evaluations 70, 313conventional fuel-based energysystems see fossil fuels

conversion factors 318–19cooking, energy supply/demand 86cooking oil waste 246–7cooling

buildings 85, 272–84nuclear reactors 95, 96

costs see damage costscost–benefit analysis 2–3country-based import/exportlimits 32–4, 36

CPH (combined power and heat)plants 239–47

cradle-to-grave analysis 4, 14, 56crystal silicon growth 222cyanobacteria 231

Daimler-Chrysler (DC) fuel cellpassenger car 259–60, 261,262–7

DALY (disability-adjusted shorteningof life years) 129–30, 149, 153–4,156–8

dam failures 227damage costs

see also economic impacts;monetised values

coal-based power, interestrates 197

definition 313Denmark

energy system scenarios 299passenger cars 266, 267

interest rates 7, 197nuclear accidents 178–9photovoltaic cells 223, 227

data collection/selection 25, 32–4,43

databasesEC/JRC, 2010b 9–16generic 6, 7inventory building 54–63obscure filenames 12, 14

323Subject Index

databases (continued)particulate matter healthimpacts 170–1

ReCiPe approach 9, 10time/location-dependent 191

deaths/mortalitysee also accidents/injury; healthimpacts

cause of death assignation 147combustion pollutants 170–1Denmark, passenger cars 256, 257,265

extreme events 127, 128, 129,130–1

heat-related 139–48hydropower accidents 227impact assesment methodchoice 156–7

Iraq War (2003–10) 210monetising 70, 71–3nuclear power 44, 95, 96, 173–80,207

occupational, types of energysystems 178–80

parasitic diseases 149, 150–4particulate matter, residentialwood burners 281

vector-borne parasiticdiseases 149–52

decision-makingaggregation issues 47basics 26–7communicating with decision-makers 67–8

democratic planning process 77–8,99

incomplete information 40definitions

energy demand and supply 82–98energy production/conversion/end use 90–8

energy system types 79–104IPCC emission scenarios 114–15resource base 91scenario techniques 98–104words/concepts 313–16

delayed impacts 2, 73–4, 307–8demand, definitions 82–98democratic planning process 77–8, 99dengue fever 149, 150, 153, 160Denmark

1992 energy system 297, 298–9,309

biofuel combined power and heatplant 239, 241–3

coal fuel chain example 200–1, 202energy system scenarios 296–309environmentally-sustainablescenario 103–4

family life activitiesassessment 285, 286, 287

insulation materials impacts 275,276

passenger car impacts 256–7, 263residential wood burners 280, 281,282

wind turbines 212, 214–15depreciation, monetising issue 73–4derived energy demands 82–90detergents 287development discontinuities 16–17development impacts definition35, 39

diesel cars 245–7, 260, 261, 262–7disability-adjusted shortening of lifeyears (DALY) 129–30, 149, 153–4,156–8

disasters see extreme eventsdischarge of substances 285–7

see also waste materialsdiscounting 2, 73–4, 307–8diseases

human 147–55, 160, 162–3, 315plant 126

dispersalchain calculations 50nitrogen dioxide 168, 170particles 166–70patterns 166–70RAINS model 53

distribution/transmission 199, 201,213

324 Subject Index

domestic impacts 196, 198dose-response relationship 14, 313double counting problem 31–2, 52, 53drinking water supplies 163droughts

greenhouse warming effectsvaluation 160, 162

occurrence 131–3Palmer Drought SeverityIndex 132, 133, 134

Earth–atmosphere system 29–31,110–25

eco-points 6, 14–16, 69ecologically sustainable Danish 2030energy system scenario 299,302–3, 306, 307, 308, 309

economic impactsanimal food products 237bio-diesel production fromcooking oil 246

Brazilian hydropowerexample 228

BritainCCGT natural gas fuel chainexample 205

coal fuel chain example 197climate modellingscenarios 116–17

definition 35–6Denmark

coal fuel chain example 200passenger cars 256–7, 258,264–6

Ribe biogas plant 244France

nuclear fuel cycle example 209wind turbine example 218

geothermal heat pump system230

Germany, coal fuel chainexample 199

natural gas steam reformation intohydrogen 232

photovoltaic cell types 227plant growth, global warming 126

silicon-based photovoltaiccells 224, 227

solid-oxide fuel cell powerplant 233

UK, wheat grain production 235Vestas VX-82 1.65 MW windturbine 219

wind power example 215ecosystem impacts 155–6

see also environmental impactseducation of farmers 126efficiency 260–1

end-use 29–31, 104electronic household devices 287electrostatic particle filters 269emissions

see also carbon dioxide;greenhouse gases; particulatematter

allocating methods 192chain calculations 48–50China, residential heating 282–3combustion pollutants 165–73Denmark

1992 energy system 2982030 ecologically sustainableenergy system scenario 302

fair market 2050 energy systemscenario 300

insulation materials 276passenger cars 256, 262–3,268–9

greenhouse gases 109–65IPCC scenarios 114–25

inventory database building 55,57–63

Mexico City 204, 206Slovenia, steam plant 57–61, 62types, chain calculations 50US, road vehicle traffic 270–2USSR, Chernobyl releases 174–8wind turbine manufacture 214

employmentcomplex effects 26quality of life 38salary lost by accidental death 72

325Subject Index

employment (continued)work activities 284–9work environments 38, 213work modes 288, 289working from home/travel 89

end-use energybuildings/spaceconditioning 272–84

conversion 255–89definition 314demand 305, 308efficiency 29–31, 104home/work activities 284–9road traffic 255–72technologies 98

energy payback timesbatteries 288environmental impacts 37photovoltaic cells 223wind turbines 218, 220

energy system definitions 79–104demand and supply 82–98energy production/conversion/end use 90–8, 104

scenario techniques 98–104Environmental Impact Assessmentmethodology (US EPA) 4

environmental impactsanimal food products 237bio-diesel production fromcooking oil 246

Brazil, hydropower example 228Britain

CCGT natural gas fuel chainexample 205

coal fuel chain example 196wheat grain production 235

definition 35, 36–7Denmark

1992 energy system 298–92030 ecologically sustainableenergy system scenario 302

coal fuel chain example 200–1fair market 2050 energy systemscenario 300

insulation materials 273, 276

passenger cars 256, 261–4, 265,267

Ribe biogas plant 244France

nuclear fuel cycle example 208wind turbine example 217

geothermal heat pump system 230Germany, coal fuel chainexample 198

natural gas steam reformation intohydrogen 232

The Netherlands, ReCiPedatabase 9, 10

photovoltaic cell types 226silicon-based photovoltaiccells 224

solid-oxide fuel cell powerplant 233

Vestas VX-82 1.65 MW windturbine 219

wind power example 214work modes 289

environmentally-sustainable Danishscenarios 103–4, 299, 302–3, 306–9

equatorial regions 140equipment lifetimes 17, 269equity 193, 307–8ETSU/IER pollutants emissionvaluation 195, 196–7, 204–6

Eulerian equations 122European Commission (EC/JRC,2010b) database 9–16

European Standardscoal-fired power stations 195impacts valuation 160–2ISO-based assessmentprocess 10–16

life value 163, 164, 165European windstorms (Jan 2000) 136event tree analysis 41expanded polystyrene 276, 277exportation 18, 32–4, 36externalities

concept/types 26definition 314ExternE project 5, 34, 156–7

326 Subject Index

history in economic analyses 1–2passenger cars, Denmark 266–7

ExternE coal externality study(EU) 5, 34, 156–7

extreme events 126–36see also accidents/injurydroughts 131–3, 160, 162flooding 130–2, 160, 162forest fires 126–7, 129–30temperature change 136–48, 160,162

windstorms 132–6

fair marketdefinition 314Denmark, energy systemscenario 300–1, 304, 305, 309

family life activities 285, 286, 287farmer education 126fatty acid methyl ester 245–7fault tree analysis 41feedback mechanisms 43, 44fertilisers 234, 238, 308filenames, obscure 12, 14filters 195, 269fine particles 280–1, 282–3

see also particulate matterFinland 281, 282fires

deaths/DALYs by 129–30fireworks 284forests 126–7, 129–30phovoltaic panels 222, 223

fisheries 160, 161, 238flooding events 130–1, 160, 162flue gases, cleaning 195food production 85–6, 125–7,234–8agriculture 125–7, 159, 160, 161

energy supply/demand 88farmer education 126

global warming effects 125–7life cycle analysis 234–8meat products 236, 237, 243

forest fires 126–7, 129–30forestry products 160, 161

fossil fuelssee also coal-fired power plantscarbon dioxide disposal 92–4clean technologies 90–4future energy system example 80oil resource depletion 91–2power production 192–206transformation to hydrogen 93types 91

France 207, 208–9, 216–18fresh water bodies 59, 62fuel cell passenger cars 259–70fuel cell plants 229, 231–4fuel oil power stations 204–6fuel price resilience 301, 303fuel source aggregation issue 46fuel supply security 38, 40

GaBi software company 6gas-fired steam production 55–62gaseous biofuels 238–47gasoline engine passengercars 255–70

GDP-adjusted evaluation 159, 163, 165generic databases 6, 7generic energy chains 27, 28, 29, 47geopolitical aspects 101–4geothermal energy 229, 230–1Germany 166–8, 198–9Glasswools insulation 276, 277global aspects

energy system input/outputstreams 29–31

equity problem 193future directions 301–9greenhouse gases 109–311

extreme events 127–36food production/silviculture 125–7

renewable energy scenarios 81, 82temperature change 273, 274, 275

GNP (Gross National Product) 158,160–2, 163, 314

goal satisfaction, supply/demand 82–90

grandfathering principle 193, 194

327Subject Index

green LCA certificates 192greenhouse effect mechanism 110greenhouse forcing 124–5greenhouse gases

biogas 224–5, 241, 243fossil fuel powerproduction 192–206

fuel cell plants 231life cycle analysis 109–65US road vehicle traffic 270–2

grid size of climate models 122

HADGEM1 UK climatemodel 113–16, 117

half-life, radioactive 173health impacts

see also accidents/injury; deaths/mortality; occupational health/injury

air pollutants 169–71, 280, 281assessment method choice 156–9Britain

CCGT natural gas fuel chainexample 205

coal fuel chain example 196climate change 136–48coal-fired power 48–50Denmark

coal fuel chain example 200passenger cars 256, 264–5, 267

dose–effect relations 14France, nuclear fuel cycleexample 208

Germany, coal fuel chainexample 198

matrix calculations 53Mexico, fuel oil power stationexample 204, 206

nuclear energy 44–5, 94, 95, 96,173–80, 207

pathway method 48–51residential wood burners 280,281

vector-borne diseases 148–55, 160,162–3

wind turbine manufacturing 213

health needs 86–7heat transfer, building shells 272–8heat transmission, insulatedpipes 195

heat waves, risk groups 137heat-related mortality 139–48heating

buildings 272–84energy demand 85system types 278

hedonic pricing 314helium-cooled pebble-bedreactors 210

hidden criteria, artificial points 69hindered amine absorptiontechnology 203, 204

historyatmospheric carbon dioxide, last300,000 years 111, 112

current LCA approach 16–19Denmark, energy systemscenarios 296–309

life-cycle analysis/assessment 1–9national energy systems 79scenario techniques 101world temperatures/precipitationmodelling, 1860 113–21

homes/housessee also buildingsactivities 284–9appliances 287–8heating/cooling 85, 279–84waste, biogas production 240, 243working, impacts 289

human aspectssee also health impacts; politicalaspects; social setting

adaptation to temperaturechange 137–8, 147

aggregation over human setting 47definition 43goals for energy supply/demand 82–90

SVL (statistical value of life) 70,71–3, 315

hurricanes 132–6

328 Subject Index

hybrid energy systems 278–84hybrid vehicles, plug-in 269–70hydrogen

energy carrier 80fossil fuels transformation to 93fuel cell passenger vehicles 262–7post-combustion capturetechnologies 203

productionfuel cell plants 231–2life cycle analysis 229–34transformation of biomassinto 243

proton exchange membrane fuelcar 259–70

hydrogen sulfide 241, 242hydropower 97, 227–9

IAEA (International Atomic EnergyAgency) 4

ice core data 111, 112ice formation/melting 110–11, 119–21impact profile approach 74–6, 314impacts

see also individual impact typesassessment, choice ofmethod 156–7

definition 26–7, 314identification of origins in singlelife-cycle step 29

inclusion/exclusion for import/export data 32–4

positive/negative, checklist 3–4types for inclusion inanalysis 34–41

importationcoal 202nuclear fuels 207, 209scenarios appraisal 18treatment in analysis 32–4, 36

incomplete information 40indicators

concerns checklists 3–4impact assessment 68midpoint indicators 9, 10software inventions 310, 311

indirect economics (1970s) 3indirect impacts 26–7industrialisation 113–21industries see activities; employment;manufacturing

information society 314inherently safe nuclear reactordesigns 96, 174

injury see accidents/injuryinput–output matrices 314input–output streams 29insulated pipes 195insulation materials

building shells 272, 273, 275–7production impacts 273, 275,276

types 276, 277interest rates 2, 7, 73, 197intergenerational equity 2, 73–4,307–8

intermittency, photovoltaic cells225

International Atomic Energy Agency(IAEA) 4

interview studies 70, 71inventory database building 54–63,314

iodine-131 174, 178IPCC (Intergovernmental Panel ofClimate Change)A1 scenario 114–16A1B scenario 114–21, 124–5,139–40, 146–7

climate change modelling 111,112, 113–16

Iraq War (2003–10) 209–10irrigation technology 125ISO (International Organization forStandardization) standards 614040 standard 814044 norms 8implementation 9–16restriction by 310

Itaipu, Brazil 227, 228

Japan 95, 113–16, 117–21

329Subject Index

land use 113–16, 212large-scale fuel cell plants 229–34Lauffen, Germany 166–8, 198–9leak rates, natural gas 61–2leishmaniasis 150, 151, 153leisure-related appliances 87life value

European standards 163, 164,165

GNP (Gross National Product)-adjusted 158

purchasing power parity 163,164

SVL (Statistical Value of Life) 70,71–3, 315

life-cycle assessment 67–78European ISO-based assessmentprocess 10–16

monetising issues 69–74multivariate presentation 74–8

life-cycle single steps 29lifetimes, equipment 17, 269lighting 87liquid biofuels 238–47livestock methane emissions 243

see also animal food productsload management 314–15location-dependent databases 191,192, 193

Lupo 3L TDI VW diesel car 260, 261,262–7

Lyapunov number 110lymphatic filariasis 150, 153, 154

malaria 148–9, 155, 160, 162–3, 315Mali, Bamako 283, 284manufacturing

energy supply/demand 89insulation materials 273, 275,276

silicon photovoltaic cells 220–2transportation 7wind turbines 213, 214, 216, 218

manure 240, 242, 243marginal appraisal 8marginal change 53–4

market interest rates 73matrix calculations 31, 51–4, 79, 80MCF (methane conversionfactor) 241

meat products 236, 237, 243media coverage 43, 44medical treatments, malaria 155methane

biofuel combined power and heatplant emissions 241, 242

conversion factor (MCF) 241Denmark, livestock emissions243

ice core data 112Slovenian steam plantemissions 60, 62–3

methanol 93, 269methodology

energy system definition 79–104life-cycle analysis 25–63life-cycle assessment 67–78scenario techniques 100–1

Mexico City, air pollution 204, 206microalgae 246, 247microclimate interference 213microelectronics industry 221–2midpoint indicators 9, 10migration distances 155, 160, 162MIHR Japanese climatemodel 113–16, 117–21, 139, 140,141

milk products 236, 237, 238mineral wool insulation 272, 275mining accidents 179, 202mitigation options 126modelling climate change 110–25monetised values

see also damage costs; economicimpacts

communicating with decisionmakers 67–8

Denmarkenergy system scenarios 299,309

passenger car impacts 256–7,267–8

330 Subject Index

depreciation 73–4impact on human society 50–1issues in assessment 69–74Norway, particulate matterpollution 280, 281

statistical value of life 70, 71–3,315

mono-crystalline silicon photovoltaiccells 220–2, 225–7

monsoons, Pakistan 131, 132monthly figures

precipitation, 1860/2055global 115, 116, 117, 119,120, 121

temperatures1860/2055 global 113–14, 117,118–19

heat-related mortalityprediction 2045–2065 142–5

mortality see deaths/mortalitymotor vehicles 255–70multi-crystalline photovoltaiccells 221, 224, 225–7

multivariate analysis 51, 70, 74–8, 315

national energy systemplanning 295–301

national independence, windpower 216

natural gasboilers, heating buildings 278leak rates 61–2power stations 204–6Slovenian steam plant 55–62steam reforming, fuel cellplants 231–2

natural setting 42–3, 46near-shore waters 156needs, basic 82–90negative feedback loops 125negative impacts checklist 3–4

see also impactsThe Netherlands, ReCiPeapproach 9, 10

nitrogen dioxide dispersal 168, 169,170

nitrogen fertiliser 234, 238, 308noise

passenger cars, Denmark 265,267, 268

software inclusion 18wind turbines 212, 299, 301

Norway, residential woodburners 279–81

nuclear energyaccidents 44–5, 94, 95, 96, 173–81,207

global scenario 82IAEA (International AtomicEnergy Agency) 4

life cycle analysis 206–11reactor types 94–6safety data shortcomings 207skills lack 96societal effects on response to44–5

system definitions 80, 81, 82Tricastin, France, nuclearplant 207, 208–9

waste, intergenerational interestrate 74

weapons proliferation 209, 210

objectivity, impact assessment 68occupational health/injury

Britain 196, 205deaths, energy systems178–80

Denmark 200, 298, 300, 302Germany 198natural gas steam reformation intohydrogen 232

oceanscarbon dioxide disposal 93–4ice formation/melting 110–11near-shore waters, algalgrowth 156

sea level change1970–2009 111observations 119–21

Slovenian steam plantemissions 60

331Subject Index

OECD (Organisation for EconomicCo-operation and Development)/IEA (International Energy Agency)2004 energy statistics series 58

oil resources 91–2onchocerciasis 150, 151, 153organic compound emissions 282, 283Otto-engine passenger cars 255–70ox meat 236, 237ozone emissions 167, 168

Pakistan, flooding 131, 132Palmer Drought Severity Index 132,133, 134

Paperwools insulation 276, 277parasitic diseases 148–55particulate matter (PM) 165–73

see also emissionscarbon 124concrete production 216distribution, weather patterns 202filters, coal-based power 195fine 280–1, 282–3passenger cars 268–9residential wood burners 279–84wind turbine manufacture 216,218

passenger cars 255–70pathway method 48–51pay-back times 4PEM (proton exchange membrane)fuel cell 259–70, 278

Perlites insulation 276, 277personal assessment 26personal environment 83, 84–5photovoltaic energy systems 220–7

centralised 81, 82components 220–1heating buildings 279overview 97production process 221–2technologies comparison 226–7

planning horizons, 30–50 year 16–17plant growth

biofuels 97diseases 126

food provision 234–8greenhouse warming effects 123–7,159, 160, 161

Plasmodium falciparum 148–9, 155plug-in hybrid vehicles 269–70plutonium 95, 96, 209, 210points systems 6, 14–16, 69political aspects

see also decision-makingdemocratic planning process 77–8,99

fuel supply dependency on foreigncountries 40

green LCA certificates 192impact assessment 68impact definition 35, 39–40scope restriction of data 26social setting 42–4

polystyrene, expanded 276, 277population density 273population growth 115–16positive/negative impactschecklist 3–4

post-combustion carbon dioxidecapture technologies 203–4

poverty, energy system solutions 308powers of ten 317PPP (purchasing power parity) 158,160–2, 163, 164, 315

Pre (Dutch consulting company)6, 15

precipitationclimate change modelling 1860/2055 115–17, 120–1

extreme eventsdroughts 131–3, 134, 160, 162floods 130–2, 160, 162greenhouse warming effectsvaluation 160, 162

global seasonal variation 115, 116,117, 119, 120, 121

price regulation 201, 314price resilience 35, 38–9, 301, 303primary energy conversion

definition 315fossil fuels 80, 90–4, 192–206

332 Subject Index

nuclear 80, 81, 82, 94–6, 206–11renewables 80, 81, 89–90, 211–47

privatisation 199, 201probability, limitations of use 41proton exchange membrane (PEM)fuel cell 259–70, 278

public assessment, definition 26public health impacts

Britain 196, 205Denmark 200, 298France 208Germany 198photovoltaic cells 226

purchasing power parity (PPP) 158,160–2, 163, 164, 315

purpose definition 27–32

qualitative estimatesimpact assessments 40impact statements 68values/attitudes of a society 43

quality of life, employment 38quantitative estimates

see also monetised valuesimpact assessments 40impact statements 68LCA software 14–16points systems 6, 14–16, 69

radioactive substances fallout 173–81radioactive waste reprocessing 207,209, 210

RAINS model 53rapeseed oil 246, 247ReCiPe approach 9, 10recycling 263, 287renewable energy

see also photovoltaic energysystems; wind power

chains analysis 211–47conversion equipment 89–90definition 315Denmark 299, 302–3, 307, 308extraction, environmentalimpacts 36–7

system definitions 80, 81

reprocessing, nuclear 207, 209reserves, fossil fuel types 91residential heating 279–84resilience of prices 35, 38–9, 301,303

resource extraction 36mining accidents 179, 202

resource use 285, 286ribbon-type photovoltaic cells 221,225–7

Ribe, Denmark 240–1, 242risk

analysis, externalities inclusion 2resilience definition 35, 38–9risk groups, heat waves 137risk-related impacts 40–1safety factors 1–2

road construction 258–9, 264, 265,266, 267, 268

road traffic 255–72robots 222, 223Rockwools insulation 276, 277Rubbia’s energy amplifier 96Russia 44, 173–80

safety factors 1–2, 40–1see also accidents/injury; deaths/mortality; health impacts;occupational health/injury; risk

salary, lost by accidental death 72satellite scatterometers 133–5scenario method 98–104

appraisal 8, 17–18definition 315Denmark, energy systems 296–309history 101impact assessment 47methodology 100–1

schistosomiasis 150, 151, 153scope 27–32screen printing 222sea level change 111, 119–21

see also oceansseasonal variation

precipitation, global 115, 116, 117,119, 120, 121

333Subject Index

seasonal variation (continued)temperatures

global 113, 114, 117, 118, 119,273, 274

heat-related mortality 141–5Second IPCC Assessment Report(1992) 159

security impacts 35, 38, 40security of supply 35, 38, 40, 215security-related institutions 86SETAC (Society of EnvironmentalToxicology and Chemistry) 5, 6

shelter 84–5see also homes/houses

shift reaction 93Shimantan Dam failure (1975) 179SI units 317–18Siberia, nuclear reprocessing 209side chains/sideline processes 28silane 221, 222Silent Spring (Rachel Carson) 2silicon dioxide 221silicon photovoltaic cells 220–7silviculture

forest fires 126–7forestry products 160, 161global warming effects 125–7greenhouse warming effectsvaluation 160, 161

site-specific data 7, 41–2skin cancer 161, 163Slovenia 55–62small particles 280–1, 282–3social context 43, 44–6social impacts

Brazil, hydropower example 228categories 310definition 35, 37–8Denmark

passenger cars 264–6, 267, 268Ribe biogas plant 244

Francenuclear fuel cycle example 208wind turbine example 217

human needs 87–8photovoltaic cell types 226

silicon-based photovoltaiccells 224

wind turbines 213, 214, 217social setting 43, 44–6societal goals 39Society of Environmental Toxicologyand Chemistry (SETAC) 5, 6

sociological basis of scenarioconstruction 99, 101–4

SOFC (solid-oxide fuel cells) 231,233, 234, 278

softwarecommercial 6–7, 9–16generic databases 6, 7ISO-conforming 310ReCiPe approach 9, 10

soil, non-agricultural 58soil-stored carbon 123solar panels see photovoltaic energysystems

solar radiation modelling input 122,124

solid-oxide fuel cells (SOFC) 231,233, 234, 278

Sørensen–Meibom model 146, 147space conditioning 84–5, 272–84Spain, wind turbines 216spin doctors 68standard price definition 315standards

establishment 5ISO standards 6, 8, 9–16, 310

Starr, Chauncey 2–3statistical value of life (SVL) 70,71–3, 315

steam production emissions 55–62steam reforming of natural gas 231–2stochastic processes 316storage

energy, photovoltaic cells 279food storage, energy supply/demand 86

radioactive waste 210storms, wind 132–6sugar-containing materials 97sulfate aerosols 124

334 Subject Index

sulfur dioxide 110, 169, 171supply security 35, 38, 40supply/demand 82–98surroundings, biologicallyacceptable 83, 84–5

sustainable systems 316Denmark 103–4, 299, 302–3, 306–9

SVL (statistical value of life) 70,71–3, 315

Sweden 5system-level analysis 295–311

double counting problem 31–2dynamics, scenarioconstruction 101

global context futuredirections 301–9

national energy systemplanning 295–301

overview/conclusions 309–11scope definition 27, 31

systemic change, versus marginalchange 53–4

taxation, passenger cars,Denmark 258

telecommunications interference 212temperatures

geothermal power 229global

heating/coolingrequirements 273, 274, 275

seasonal variation 113, 114,117, 118, 119, 273, 274

heat-related mortality 139–48heating/cooling demand 85human adaptation tochange 137–8, 147

pre-industrial/future globalmodelling 113–14, 117, 118–19

terrorism, security of supply 35, 38,40, 215

Third World, pollution imports 34Three Mile Island reactor 174time

aggregation over 44grandfathering principle 193, 194

horizons, nuclear energy 207time-dependent databases 191time-displaced impacts 307–8time-displaced irresponsibility 2treatment in commercial LCAsoftware 7

top-down approach 19total energy analysis 4Toyota Camry gasoline/Otto enginecar 260, 261, 262–7

traffic 255–72trans-border issues 32–4, 36transesterification 247transportation

biomass residues 239, 240Denmark, 1992 energy system298

efficiency 31energy supply/demand 87–9inventory database building 56manufacture 7pollutants across borders 34road traffic 255–72sector carbon dioxideemissions 194

transport work 316trees see silvicultureTricastin, France, nuclear plant 207,208–9

tropical cyclones 132–6tropical-cluster diseases 150–3, 160trypanosomiasis 150, 152, 153types of energy system 79–104typhoons 132–6

UKCCGT natural gas fuelchain 205–6

coal fuel chain example 196–7UN (United Nations)

Environment Conference(Stockholm) 5

UNEP (United NationsEnvironment Programme) 4, 5,6, 111

unanticipated event chains 41

335Subject Index

unitsconversion factors 318–19point systems 6, 14–16, 69powers of 10 317quantitative impact assessment68, 69

SI units 317–18usefulness 311

USdollars, definition 316Environmental Impact Assessmentmethodology 4

EPA (Environmental ProtectionAgency) 4, 5

North America, windstorms 135Three Mile Island reactor 174

USSR 44, 173–80

valuationsee also damage costs; economicimpacts; monetised values

greenhouse warmingimpacts 159–65

human life 70, 71–3, 158, 315points systems 14–16, 69social context-related 43vector-borne disease impacts 160,162–3

vector-borne diseases 148–55, 160,162–3

vegetable products, impacts 236vehicles, road traffic 255–72Vestas VX-82 1.65 MW windturbine 218, 219, 220

video equipment 87visual impact/intrusion 18, 212, 223VW Lupo 3L TDI diesel car 260, 261,262–7

wafers, crystalline silicon 221, 222washing machines 287waste materials

biofuel combined heat and powerplants 239–47

Denmark, elementary analysis241

discharge, average world citizen285–7

household 240, 243radioactive 207, 209, 210treatment/energy extraction 245

waterdrinking water supplies 163human needs 85–6hydropower 97, 227–9oceans

carbon dioxide disposal 93–4ice formation/melting 110–11near-shore waters 156sea level change 111, 119–21Slovenian steam plantemissions 60

particulate matter dispersal in 166wheat crops/animal raising 236, 237

wealth distribution 308weather 122, 202

see also precipitation;temperatures; wind

wheat grain production 234–5willingness to pay (WTP) 70, 71, 316wind

European ISO-based assessmentprocess criticisms 12–13

extreme events 132–6, 160, 162impact profile approach 76life cycle analysis 211–20power

Denmark 212, 214–15overview 97

turbines 299, 301window areas, heat loss 277–8WMO (World MeteorologicalOrganization) 111

woodsee also silvicultureresidential wood burners 279–84residues 239–40

work see employmentworld citizen concept 285–7World Meteorological Organization(WMO) 111

WTP (willingness to pay) 70, 71

336 Subject Index

1849731454 lifecycle

Documents

energy eld

renewable energy physics

renewable energy conversion

fundamentals of energy

authora history of energy

eld of science

broader eld of systems

royal society of chemistry