topical paper 1: resource-efficiency in the built ...€¦ · topical paper 1: resource-efficiency...

European Commission

Directorate-General Environment

Topical Paper 1: Resource-efficiency in the built environment - a broad-brushed, top-down assessment of priorities

Date February 2013

Author(s) Arjan de Koning (CML), Nina Eisenmenger (AAU-SEC), Ester van der

Voet (CML)

Number of appendices 5

Study name ENV.F.1/ETU/2011/0044 "Assessment of Scenarios and Options towards a Resource Efficient Europe”

Disclaimer: The information contained in this report does not necessarily represent the position

or opinion of the European Commission.

Resource-efficiency in the built environment - a broad-brushed, top-down assessment of priorities

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Contents

1 Introduction ................................................................................................................ 6

2 Methodology and data ................................................................................................. 8 2.1 Input-output analysis .................................................................................................... 8 2.2 Material Flow Accounting ............................................................................................. 9 2.3 Indicators .................................................................................................................... 9 2.4 Investigating driving forces ........................................................................................... 9 2.5 Databases .................................................................................................................. 10

3 Driving forces and trends ........................................................................................... 11 3.1 Population growth...................................................................................................... 11 3.2 Economic growth and capital formation ....................................................................... 12 3.3 Gross fixed capital formation dwellings ........................................................................ 13 3.4 Floor space ................................................................................................................ 15 3.5 Use phase variables .................................................................................................... 17 3.6 Trends in driving forces ............................................................................................... 19

4 Results ...................................................................................................................... 20 4.1 Resource use ............................................................................................................. 20 4.1.1 EIOA .......................................................................................................................... 20 4.1.2 MFA .......................................................................................................................... 22 4.1.3 Conclusions ............................................................................................................... 26 4.2 Emissions ................................................................................................................... 26 4.3 Energy flows .............................................................................................................. 28 4.3.1 Energy consumption in the EU27 ................................................................................. 28 4.3.2 Energy use for space heating and cooling by households ............................................... 29 4.4 Use of other resources: land and water ........................................................................ 31 4.4.1 Land use .................................................................................................................... 31 4.4.2 Water use .................................................................................................................. 32 4.5 Resource efficiency .................................................................................................... 32 4.6 Share of built environment in total resource use and emissions in EU27 ......................... 34 4.7 Contribution analysis .................................................................................................. 36

5 Conclusions ............................................................................................................... 38 5.1 Resource use and emissions ........................................................................................ 38 5.2 Input for scenario modelling ....................................................................................... 38

6 References ................................................................................................................ 39


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Backgrounds of the project: Assessment of Scenarios and Options towards a Resource Efficient Europe The Europe 2020 Strategy, endorsed by the European Council in June 2010, establishes resource

efficiency as one of its fundamental flagship initiatives for ensuring the smart, sustainable and

inclusive growth of Europe. In support of the Flagship, the Commission has placed a contract with

TNO, CML, PE and AAU/SEC for a project with the following aims. It should identify inefficient use of

resources across different sectors and policy area’s at meso- and macro level and then

quantitatively assesses potentials and socio-economic and environmental effects of efficiency

improvements, both from singular as system wide changes, up to 2050. The Built environment is the

focus area. The core methodology is a hybrid modelling approach: identifying improvement options,

their costs and improvement potential at micro/meso level, and to feed them into a macro-model

(EXIOMOD) to assess economy-wide impacts of improvement scenarios. Stakeholder engagement

via workshops is an important part of the study. The study started in January 2012 and will end in

December 2013.

To inform stakeholders, during the project some 8-10 ‘Topical papers’ will be written. The aim is to

get feedback on crucial elements of the scenario modelling with stakeholders. This document is the

first of the topical papers.


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Summary

In this top-down analysis of the environmental emissions and natural resource efficiency in the residential built environment two tools have been used: economy-wide Material Flow Accounting (MFA) and environmentally extended input output analysis (EE-IOA). MFA provides a territorial (per country) and temporal overview of the production, imports, exports of natural resources and energy in a country. EE-IOA gives information on the ‘cradle-to-grave’ use of natural resources and environmental emissions associated with the consumption of construction work in a particular country. In addition, an investigation has been made of driving forces: societal indicators for the size and resource intensity of the construction sector. The residential construction sector is a material intensive sector: it contributes 9% to GDP on average in the EU, but much more to resource use. On average, 50% of bulk construction materials like sand, gravel, clay and stone ends up in residential construction work – the other half largely going into other construction work. About 10 – 20% of metals such as iron, aluminium, copper etc. are incorporated in built residential infrastructure. The bulk construction materials are mainly quarried in the country where they are used. For metals the EU depends almost exclusively on imports from foreign countries except for lead and zinc ores where about 40% is mined within the EU. The construction sector appears to have a substantial contribution to the ‘cradle-to-grave’ emissions at the national level. The emissions are more or less in line with the contribution to GDP (7 - 15% of EU total). The construction sector can thus be characterized as having an average emission intensity, but because it is a large sector it is a relevant one. Important sources of emissions in the cradle-to-gate construction chain are the power plants needed to provide electricity to the construction sector, cement and baked clay products plants, and blast furnace works. The emissions from the construction site itself are important as well, especially for Non-Methane Volatile Organic Chemicals (NMVOC) emissions. Because most of the environmental emissions take place in the supply-chain to the construction work sector, the structure of the supply chain may have a strong influence on the environmental emissions associated with the construction work sector. Including the use phase makes a difference: residential emissions including the use phase are considerably higher (10 – 35% of EU total), mainly due to residential energy use for space heating and cooling. There are significant deviations in the amount of construction minerals used across countries. For example, we see a high wood use in Northern countries, while the slate use in Ireland is particularly high. Patterns like these are interesting to explore further. A decisive influence of climate on emissions of the construction sector cannot be detected. Driving forces for construction activity are population and GDP. More specifically the gross fixed capital formation in dwellings is an important driving force, as it correlates with the number of dwellings completed: on average a quarter of total investment in the European Union was investment in dwellings in 2000. GDP is also an important driving force for the demand. It correlates with average available floor space per capita. Another demand related variable is the life span of buildings, determining the turnover rate. The MFA time series data show that the construction sector is improving its resource and energy efficiency but no absolute decoupling of resource use (neither material nor energy) could be observed. The main driver for the efficiency increase appears to be GDP, not actual changes in the use of materials and energy. Trends in driving forces are relevant for


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modelling and scenario development. Time series information for the EU27 countries is available for population, GDP and investments. For the demand side variables, the database is incomplete.


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1 Introduction

In this paper, a top-down approach is elaborated to assess the relative importance of the built environment for the resource use and emissions of national economies. Two methodologies and databases are used to so this: Environmentally Extended Input Output Analysis (EE-IOA) and economy-wide Material Flow Accounting (MFA). Both approaches cover the EU as a whole as well as all countries within the EU. This enables comparing countries. The most complete and detailed IOA at the EU level is the EXIOPOL database, described below. This database covers the world, including all EU countries separately, for the year 2000. The MFA data from the European Statistical Office contain time series for all EU countries from 2000 to 2009 and for the former EU15 countries also from 1970 onwards. The MFA data therefore allow, besides country comparisons, to spot trends. While the EE-IOA database is based on sectors, the MFA data have their strength in the complete coverage of all materials entering the socio-economic system. Results of the two methodologies should complement each other, but at the same time differences between the methods may lead to relevant insights. Goal of this topical paper The goal of this topical paper is to give an overview of the environmental impacts associated with residential housing in the European Union. The focus of the study is on resource use and emissions as a result of constructing houses, maintaining the housing stock and using these residential houses in the European Union. Of particular interest are trends in the use of resources for residential housing in the European Union as observed in the last decades. The trend analysis might be used as input for base line scenario development to be used to investigate the effects of improvement options in the built environment. In short this paper should answer the questions: 1. What share of resource use and emissions in a country is caused by residential

housing. 2. What is the contribution of the construction phase versus the use/maintenance phase

of residential buildings. 3. How did resource use by residential housing develop in time.

Scope of this topical paper The principal object of this study and the topical paper is all residential housing in the European Union and two of its life cycle stages: the construction phase and the use phase. The use phase comprises of the energy use for space heating and cooling, and construction work and materials necessary for maintenance. The building phase includes everything necessary to construct a new building including ground work, and the whole supply chain towards the construction sector. A detailed description of all activities that belong to the construction sector is given in Appendix D. Demolition of buildings could not be taken into account due to limitations in the data available. Previous studies have shown that the environmental impacts of the demolition of buildings are in the order of 1% of the total environmental impacts associated with residential buildings (Cuéllar-Franca, 2012). Examining the share of resource use and emissions caused by residential housing and the importance of the construction phase versus use/maintenance phase has been done for the year 2000 using Input-Output analysis. Input-Output analysis gives like LCA an cradle-to-grave inventory of all environmental impacts associated with a product or service. The practical difference between IOA and LCA is that IOA examines very broad product categories covering the whole economy and LCAs of focus on single products (or product


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improvements). IOA is sometimes called a top-down analysis and LCA a bottom-up analysis. Examining trends in resource and energy use has been done using material flow analysis and energy statistics. Structure of the report This report starts with a short description of methods, models and data used in Section 2. In Section 3, an overview is given of the main trends that might influence the environmental impacts associated with residential housing: population growth, economic growth and gross fixed capital formation in dwellings, building stock development, energy use in households and water consumption by households. In Section 4 an overview is presented of the resource use associated with new residential construction and use/maintenance of residential buildings. Trends in energy and resource use in the European is discussed in Section 5. In Section 6, some conclusions are drawn with regard to the resource intensity and efficiency of the residential construction sector and built environment.


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2 Methodology and data

In this section, a short description is presented of the main methodologies used, IOA and MFA, and of the most important databases used for this paper. A more detailed description of the IOA tool and MFA tool and the databases behind these tools is given in Appendix A.

2.1 Input-output analysis

For the top-down assessment of the resource-efficiency of the construction of buildings and infrastructure we will use so-called input-output analysis. In this analysis we use input-output tables that describe the production and consumption system in an economy in terms of purchase and sale of product groups, as well as natural resource extractions and emissions. The IO tables describe the relations between different sectors in the economy. They quantify in monetary terms how the output of (goods or services) produced by one sector goes to another sector where it serves as input. An IO model assumes that each sector uses the outputs of the other sectors in fixed proportions in order to produce its own unique and distinct output. Based on this assumption, a matrix is defined such that each column shows in terms of monetary value the inputs from all different sectors required to produce one monetary unit of a sector´s output. For each sector involved, the matrix can be extended environmentally by assuming that the amount of environmental interventions generated by a sector is proportional to the amount of output of the sector, and that the nature of the environmental interventions and the ratios between them are fixed. In the most basic form, an environmental IO analysis can be performed using one vector and two matrices:

the final demand vector that allocates the total demand for products in a country or region to the different products and services. This final demand vector in terms of purchases of goods and services, determines all production activities and their related environmental impacts. The final demand vector can be final consumption expenditure of households and/or government and/or gross fixed capital formation

the 'technology matrix' shows how the production activities of the different sectors interrelate in monetary terms

the 'environment matrix' shows input in terms of direct resource extraction for each sector and output in terms of direct emissions.

When calculating the environmental impacts associated with the final demand of a product group, it is important to realize that the environmental impacts associated with the product group are calculated 'cradle-to-grave'. If for instance the copper ore extraction associated with the construction of buildings & infrastructure is calculated this might have happened because some machinery at a factory somewhere down the production chain needed an electromotor.


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2.2 Material Flow Accounting

Material Flow Accounting and analysis (MFA) is an EU-wide harmonized accounting tool for the material inputs, stocks and outputs of a socioeconomic system From the natural environment, resources extracted from domestic territory (domestic extraction, DE) enter the system as inputs; emissions and waste (domestic processed output, DPO) flow back to nature as outputs. Imports from other economies enter the system, and exports flow from the system into other economies. All solid, gaseous and liquid materials (not including water and air) that cross the above-mentioned system boundaries within one year are counted as material flows in MFA. The unit of measurement is metric tonnes. There is a highly advanced and internationally harmonized methodology which can be used in compiling an MFA (Eurostat 2001, Eurostat 2009).

2.3 Indicators

The focus of this topical paper is on resource use associated with the building phase and use/maintenance of residential buildings but also four of the commonly used life cycle indicators for emissions have been calculated. Resource indicators used in this paper are the domestic extraction of metals and minerals, blue water footprint, green water footprint and land use. Domestic extractions of 8 metals and 6 minerals plus timber are covered. The blue water footprint is the volume of freshwater that evaporated from the global blue water resources (surface water and ground water) to produce the goods and services consumed by the individual or community. The green water footprint is the volume of water evaporated from the global green water resources (rainwater stored in the soil as soil moisture) (Hoekstra et al., 2011). Blue and green water data relate both to agricultural water use. Land use relates to land occupied for agricultural and forestry. Direct land use as occupied by the residential buildings is not accounted for in land use indicator. Both land use and water footprint only refer to biomass production. Therefore these indicators are only indicators for the indirect use of biomass (e.g. timber) by the construction sector and the built environment.

The four emission related life cycle indicators are used for the impact assessment of the

major emissions and cover the following four environmental themes: global warming,

acidification, photochemical oxidant formation and human toxicity. These indicators are

described in detail in the Handbook on Life Cycle Assessment (Guinée et al., 2001).

Indicators for other environmental themes like eutrophication and ecotoxicity could not be

calculated because emissions to surface water which are indispensable to calculate these

indicators are not available in EXIOBASE.

2.4 Investigating driving forces

MFA and EIOA are used to specify and calculate the indicators as described above. In addition, we will investigate some important drivers of resource use and emissions related to the built environment. These drivers, and their specific relation to resource use and emissions, are important as input for the scenario analysis to be performed in the project.


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2.5 Databases

The data to be used for the input-output analysis are extracted from EXIOBASE. The EXIOBASE database contains supply-use tables for 43 countries and 1 Rest of World region for the year 2000 (see Appendix B for the list of countries). In each country/region 129 product groups are distinguished. These 129 product groups can be aggregated to NACE rev 1.1 statistical classification at the 60 sector level. A full description of this classification is given in Appendix C. A more detailed description of EXIOBASE is provided in Appendix A. Material flow data are usually compiled along four main groups: biomass, fossil energy carriers, metals, non-metallic minerals. MFA is predominantly based upon data sets from official statistics and uses estimates for the flows that are absent from or only insufficiently covered in the statistics. Methods for the classification, aggregation and calculation of missing data have undergone significant advancement and harmonization in recent years (Eurostat 2001 and Eurostat 2009). At the European level, data from national material flow accounts are collected and published annually by Eurostat. For the EU15, a time series exists for the years from 1970 onward; for the countries of the EU27, the MFA time series starts in the year 2000. Besides Eurostat data, several MFA dataset exist from detailed national studies (e.g. Austria, Germany, Czech Republic, etc.), to regional comparative studies (e.g. Asia and Pacific), and global datasets (SERI materialflows.net, Krausmann et al. 2009). Auxiliary information on specific aspects of the built environment such as energy use in the households were taken from the Odyssee database (Lapillonne, 2012). Information on the number of houses built and the floor space per house were taken from the housing statistics report series (NBHB, 2005). General economic and population indicators for European Union were taken from Eurostat.


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3 Driving forces and trends

This section treats a number of driving forces for the construction work sector, in as far as

it concerns residential building. These may be relevant as input for the modelling part of

the project. They can be used, to some extent, as explanatory modelling variables for

construction activity – the supply side. In addition, use phase variables are important for

the modelling of future demand. It has not been possible to collect EU-wide data on those,

but some remarks are made on them in section 3.5.

3.1 Population growth

Population growth is one of the important drivers for new built environment both

residential buildings as well as infrastructure. The combined population of Poland, Spain,

Italy, UK, France and Germany represents about 70% of the total population of the

European Union, see Figure 1.

Figure 1: Population in countries of the European Union in 2000, source Eurostat.

Population growth is unevenly distributed over the European Union. Some countries

experienced a decreasing population in the previous decade, notably in some of the east

European countries. Largest population growth is seen in Cyprus, Ireland and Luxembourg.

The average population growth in the European Union from 2000 to 2010 was 3.8 percent

in 10 years.


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Figure 2: Percentage change of population in the European Union from 2000 to 2010,

source Eurostat.

3.2 Economic growth and capital formation

A second important factor influencing the demand for new built environment and energy

use in households is economic growth. GDP per capita in the European countries in 2000 is

show in Figure 3.

Figure 3: GDP per capita in countries of the European Union in 2000, source Eurostat.

The change of GDP per capita from 2000 to 2010 was 20 – 30% in most West European

countries and was in the order of 120 – 200% in some East European countries as shown in

Figure 4. Average increase over 10 years was 29% or 2.5% growth per year.


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Figure 4: GDP change per capita from 2000 to 2010 in the European Union, source

Eurostat.

3.3 Gross fixed capital formation dwellings

The amount of money spent on construction work to provide new dwellings or major

renovation/alteration/additions to existing dwellings is not recorded as a final demand for

construction work but is seen as an investment. The amount of investments in dwellings

are available as the gross fixed capital formation in dwellings. These numbers are available

at Eurostat in the “gross fixed capital formation by 6 asset types - current prices” table

(nama_pi6_c) and shown in Figure 5 for 2000 and all European countries. Only for Belgium

no specific investment in dwellings data were available. These were estimated on the basis

of the average European fraction dwelling investment total investments in a country.

Figure 5: Gross fixed capital formation in dwellings (in mio. Euro) in countries of the

European Union, source Eurostat.

The gross fixed capital formation in dwellings ranged from 124 mio. Euro in Estonia to

139770 mio. Euro in Germany. On average 25.5% of total investment in the European

Union was investment in dwellings in 2000. It should be kept in mind that values for the

gross fixed capital formation in dwellings are probably uncertain due to the difficulties


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assessing property value and differences in definition of what consists an investment and

what not between countries.

The Gross fixed capital formation in dwellings is both newly built residential buildings plus

the renovation/alteration of existing residential buildings. So the GFCF in dwellings

contains information about the construction phase and the maintenance phase of

residential buildings. To be able to make a distinction between the resource use associated

with the construction phase and maintenance phase of residential buildings, the GFCF in

dwellings should be split up into a “new construction part” and “renovation part”.

National statistical agencies do not often report separately GFCF in new dwellings and

GFCF in dwelling renovation. The Canadian statistical office (Statistics Canada, 2008)

reported these values for 2000 and 48.5% of GCFC in dwellings was investment in new

housing construction. In Denmark the fraction GFCF in dwellings used for new housing

construction ranged from 36% to 45% from 1996 to 2000 (Andersson, 2004). In France

improvement-maintenance is estimated to be about 50% of total construction expenditure

(Carassus, 2004). In Germany expenditure on new residential buildings ranged from 54% to

57% in the period from 1996 to 2000 (Andersson & Clobes, 2004). Given these available

numbers we use as working assumption that 50% of the GFCF in dwellings can be

attributed to new housing construction and 50% to the GFCF in dwellings to maintenance

and renovation of the existing housing stock in 2000.

The gross fixed capital formation in dwellings is the investment of private households plus

other actors like housing associations and therefore represents new construction and

maintenance of houses that are owned by private households as well as houses that are

rented and owned by housing associations.

The amount of money invested in new dwellings is not directly a good comparative

indicator for the physical volume of dwellings constructed because the price level of

constructed work may vary a lot between EU countries (Diaz Muriel, 2010). The price level

index of construction work of the cheapest country is Bulgaria which is 26% of the average

European Union price level while the highest price level is found in Sweden at 141%.

Figure 6: Price level index for construction work in the European Union in 2000 (EU = 100),

source Diaz Muriel, 2010.


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Correcting the GFCF in dwellings for price levels and population in the European countries

gives an impression of the intensity of new dwelling construction between the European

countries, see Figure 7.

Figure 7: Gross fixed capital formation per capita for dwellings in 2000 in the European

Union price level corrected, source Eurostat and Diaz Muriel, 2010.

According this monetary metric construction activities were particular intensive in Ireland,

Portugal, Spain and Finland in 2000. In the next section physical indicators of new

construction are investigated.

3.4 Floor space

The series of “housing statistics in the European Union” reports give valuable insight into

the development of the housing stock and new dwelling construction in the European

Union. The total amount of newly build floor space divided by the total number of people

living in the country in the European countries in 2000 was taken from the Housing

statistics report of 2004 (NBHB, 2005) and shown in Figure 8.

Figure 8: Floor space per capita built in 2000 in the European Union, source housing

statistics report.


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According the housing statistics reports building intensity was particularly high in Cyprus,

Ireland, Spain, Greece and Portugal.

The floor space per dwelling of newly built dwellings is generally speaking larger than the

floor space per dwelling of the existing stock in 2000. For several countries the floor space

per dwelling of the existing stock could be compared with the floor space of new dwellings

as shown in figure 9.

Figure 9: Percentage change of the floor space of new dwellings compared to the floor

space of the existing stock of dwellings in 2000, source housing statistics reports.

Another indicator of the amount of new construction is the number of dwellings

completed in a year as shown in Figure 10.

Figure 10: Dwellings completed per 1000 inhabitants in 2000 in the European Union,

source housing statistics reports.

The number of dwellings completed shows quite a good correlation with the GFCF in

dwellings which might be used for the set-up of scenarios, see Figure 11. The relation with

floor space completed in 2000 is less clear. This might be caused by uncertainties in floor

space per dwelling information.


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Figure 11: GFCF dwellings and number of dwellings completed in countries of the European

Union in the year 2000.

3.5 Use phase variables

Use phase variables are important for modelling future demand related to residential

building. For those variables, EU-wide data have not been found. For completeness sake,

some are mentioned in this section.

Important use phase variables are, among others:

GDP/capita seems to be an important explanatory variable for the m2 floor space

per capita available in dwellings. Hu et al. (2010) have shown this to be a quite

tight relationship around the world, based on data from Norway, the Netherlands

and Beijing.

The life span of the buildings is an important variable determining the

requirement for new buildings to maintain the stock. A longer life span generally

means less new construction, but more renovation.

Climate is an important driver for the amount of energy needed for heating. The

heating degree day is a good indicator of the driver for energy use for household

heating. It expresses the number of degrees that a day's average temperature is

below 18o Celsius, the temperature below which buildings need to be heated. In a

similar fashion the number of cooling degree days might be an important driver

for the use of air conditioning systems.

The average heating degree days in the EU27 is shown in Figure 12. On the short time span

no trend can be discerned. 2009 was the latest year for which information was available.


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Figure 12: Average heating degree days in the EU27 from 2000 to 2009, source Eurostat.

The heating degree days in the European Union differs substantially between the different

countries. Clusters analysis on the heating degree days from 2000 to 2009 reveals that

three different groups of countries can be distinguished with respect to HDDs.

1. The Nordic countries: Sweden and Finland

2. West and central Europe: Ranging from Ireland, the Baltic states, Bulgaria,

Romania to France

3. South Europe with Portugal, Spain, Italy, Greece, Malta and Cyprus.

A heat map clearly shows the demarcation between the three groups of countries, see

Figure 13.

Figure 13: Heat map of the number of heating degree days in the European Union from

2000 to 2009, source Eurostat.


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3.6 Trends in driving forces

Figure 14 shows the trend in several of the abovementioned driving forces for the years

2000 - 2010. GDP, dwellings completed, total energy use in households, population and

GFCF dwellings were all indexed to 100 in 2000 as shown in Figure 14. These trends can be

used as input in the scenario development and modelling.

Figure 14: Overview of the main factors influencing the environmental impacts associated with the built environment. All EU average data indexed to 2000 = 100.


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4 Results

4.1 Resource use

4.1.1 EIOA The EXIOPOL database contains a number of raw materials as environmental extensions, representing extractions from the biosphere. Relevant materials for the construction sector are: the metals iron, aluminium, copper, nickel, zinc and lead; the construction materials clay, sand and gravel, limestone, wood, and building stone. For these materials, the amount used by the production sectors included in EXIOPOL can be calculated and compared between countries. Patterns of material use can thus be distinguished. As the basic data of EXIOPOL are monetary, the first thing to conclude is that the “construction work” sector, the sector actually occupied with building and construction, contributes 9% to total GDP. For construction materials such as sand and gravel, the bulk is allocated to the “construction work” sector. Figure 15

1 shows this: almost 50% of sand and gravel is used by

the construction work sector. Since this sector contributes 9% to GDP, it can be characterized as sand-and-gravel intensive. Other sand and gravel using sectors are often related to the built environment as well, such as real estate services, motor vehicles, public administration and tourism. This is as expected, and is a consistent pattern for the other bulk construction materials as well. For these materials, the built environment is the prime user, and in any analysis of the built environment they have to be included. The same is true for wood. With regard to metals, the construction work sector is one of the larger users as well. Below in Figure 16, the demand for iron ore is shown. The construction work sector uses about 15%. This pattern can be detected for the other metals as well: contributions of the construction work sector range from 12% to 16%. These results show that the construction sector is a material intensive one, and an important one, at the EU-level, when it comes to the use of certain materials. Within the EU, there are many countries that each have their own style of building and construction. In the next section, we look into the differences between EU-countries.

1 On the y-axis the resource intensity of each product is plotted in terms of kt/million Euro. On the

x-axis the cumulative final demand for each product is plotted. The order of the product on the x-

axis is from highest resource intensity to lowest resource intensity. The total cumulative demand

for the products approximately equals to GDP of the EU. The area of the bar drawn for each

product is equal to its total ‘cradle-to-grave’ resource use. The sum of all bars is equal to the total

or 100% resource use due to final demand for products in the EU. If the demand for a product has

a 2% or more contribution to the total, its label will be shown in the graph. A label is also shown if

the product is assumed to be a building product. For these products the bar has a dark grey color.

Most of the time it is only the construction work as product that can be seen in the graphs. The

final demand for the other building products is so small that the bar is not more than a very thin

line. Products which have a very high resource intensity which are topped in the graph are

denoted separately in a box.


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4.1.2 MFA

Total material use in the EU27 was 8 billion tonnes in 2009 and only slightly less in 2000. Non-metallic minerals (mostly bulk materials such as sand, gravel, limestone etc., which are used for construction purposes) make up 50% of total material use. The other 50% are composed of 23% biomass, 24% fossil energy carriers, and 3% ores. In per capita terms, the EU27 used 15 tonnes of materials in 2009, compared to 16 t/cap in 2000. The year 2009, however, has to be considered biased due to the global financial crisis that has its effects

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also on material use. Thus, material use in 2008 was 17 tonnes per capita and thus higher as compared to 2009.

Figure 17: material use (DMC in mio. tonnes) in the EU27

The MFA results observed show a more or less stable material use in the past 10 years. The only noteworthy increase took place between 2005 and 2008 in the category “non-metallic minerals”, which then dropped back to levels before 2004. As already mentioned, non-metallic minerals make up half of total material use. In 2000 the EU27 used 8 t/cap, which increased to 9 t/cap in 2008 and dropped down to 7 t/cap in 2009. Next to non-metallic minerals, metal ores are important raw material inputs to construction activities, among those iron and copper ores as the most important materials. However, from an MFA perspective metal ores are used only in minor quantities (3% of total DMC). The material use in the EU builds strongly on domestic raw materials. However, imports and exports increasingly play an important role. Imports make up half of materials domestically extracted. Non-metallic minerals are characterized by a high share of domestic use. Imports and exports of these materials only make up 8% of total material throughput (DMI). The same results are found when looking at the non-metallic resource extraction associated with the final demand for construction work in the EU using the EIO tool, see Appendix G on the contribution analysis which among other things show the location (within EU27 or outside the EU27) where the resource extraction takes place.


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Figure 18: Domestic Extraction (DE), imports and exports of the EU27 (in t/cap)

Figure 19: subcategories of the four material categories

Non-metallic minerals comprise a series of minerals (see Figure 19). In terms of masses, the most important categories are: sand and gravel, limestone (used for cement production), and other stones. Some 94% of non-metallic minerals are materials that are mostly used for construction. Therefore, these materials are often referred to as “construction minerals” in MFA. The sub-category “other non-metallic minerals” on the other hand is dedicated to non-construction uses, often referred to as “industrial minerals” in MFA. For the EU27 this sub-category only makes up 6%. But also significant parts of sand for example are used in industrial processes. For a more detailed analysis see the results of the IO analysis. In the category metals, iron ores and copper make up 80% of total use of metal ores. As specified in the IO section, between 12 and 15% of metals are more or less directly used in the construction sector. In the category biomass, only wood is of relevance for construction purposes.


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On the country level, we see quite some deviation (see figure 20 for the year 2008). Non-metallic minerals mostly make up for 40-55% of total DMC. However, in some countries, the share is much higher reaching shares of 65% or even 75%. These countries with higher use of construction minerals are: Ireland, Cyprus, Spain, Austria, Portugal, Romania, Slovenia, and Finland. Driving factors behind the use of construction materials are phases of accelerated economic growth, colder climate, and lower population density.

Figure 20: DMC for the single European Countries, 2008 in t/cap

Countries with higher use of metal ores are those that are extracting relevant masses of ores in domestic mines. That is the case for Bulgaria (copper, lead), Ireland (zinc, lead), Cyprus (copper), Austria (iron ore, other ores), Poland (copper, lead, zinc, gold/silver/PGM, other ores), Finland (copper, nickel, zinc, gold/silver/PGM, other ores), and Sweden (iron ores, copper, gold/silver/PGM). This reflects the fact that MFA accounts for ores in terms of gross ores, i.e. the metal content plus the waste rock. For iron ore, the ore grade (metal content per ton of gross ore) is around 50%, for copper only 1%. From economy-wide MFA data we can conclude that non-metallic minerals, mostly used for construction activities (94%), make up half of material use. Construction minerals are characterized by being weighty masses of low specific economic value (price). It is therefore not worth to transport non-metallic minerals over longer distances. Instead, most of the construction materials are extracted domestically. For the observed time period (2000-2009), construction minerals remained rather stable, with a slight increase during 2005 and 2008. Metal ores, on the other hand, are point resources not abundantly available. Trade is therefore an important means to globally share unevenly distributed resources. After concentrating the metals, they are used in numerous processes and instruments: communication technology (cables and wires), machines and transportation means, as well as infrastructure and many electrical household appliances. The metal content of the final product can differ widely and ranges from large amounts of iron/steel to tiny traces of so-called ‘spice metals’. A computer, for example, contains 32, a mobile phone even 40 different metals (Meskers and Hagelüken, 2009).


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Materials used for construction purposes are mainly used in two phases: building up new infrastructure and buildings, and renovating existing buildings The energy use of buildings and infrastructure is usually irrelevant in material terms except in countries where timber is used for space heating., see section 4.3.2 on energy use for household heating.

4.1.3 Conclusions On average, 40 – 50% of bulk construction materials and 10 – 20% of metals ends up in residential construction work. The construction sector is a material intensive one: it uses a lot of material but only contributes by 9% to GDP. Energy use during the construction of the buildings is of less interest in contrast to energy use during the use-phase of the building, i.e. residential energy use. Variations per country do appear which require further analysis. An attempt to cluster countries and look for similar patterns is done in Appendix I.

4.2 Emissions

The EXIOPOL database does contain a number of air emissions as environmental extensions which can be aggregated into several impact categories. For each sector, the emissions can therefore be calculated, and the contribution of each sector to the total impact can be assessed. Emissions and impact categories covered are: Greenhouse gas emissions (CO2, CH4 and N2O), Acidifying substances (SO2, NOx and NH3), Toxic substances (human toxicity; a number of emissions to the atmosphere, namely NOx, HCB, Pb, Hg, Ni, Cu, As, Cd, Zn, SOx, NH3, Se, Cr, dioxins, NMVOC, PAH and PM10) and photochemical oxidants (including CO, SOx, CH4 and NMVOC emissions to air). The air emissions in the EXIOPOL database give a quite complete picture of these impact categories. Emissions to surface water, groundwater or soil are not covered by the EXIOPOL database. It is therefore that only the above four categories are taken into account. Impact categories not covered are ecotoxicity, stratospheric ozone depletion and nitrification. For these impact categories emissions to water and soil are important and they are not available in the EXIOPOL database. Among the best monitored emissions are the GHG emissions, especially CO2. At the EU-level, the construction work sector contributes 9% to total GHG emissions. This is quite in line with its contribution to GDP, which is also 9%. Figure 21 shows this. The construction sector therefore, although not particularly GHG-intensive, is an important one because of its size.


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At the EU-level, the contribution of the construction work sector to the other impact categories is 7% to acidification, 11.5% to human toxicity and 15% to POCP. Again, the contribution is relevant, mainly because of the size of the sector. The construction sector appears to have a significant contribution to emissions at the national level. These emissions are more or less in line with the contribution to GDP. The construction sector therefore can be characterized as average, but because it is a large sector it is a relevant one.

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The differences between countries are relatively small, especially for greenhouse gas emissions. For the other types of emissions, the spread is somewhat larger. Some countries consistently have high emissions, while others often can be found at the low end. It would be worthwhile to look for explanations. The MFA database does not offer any information on emissions. However, a study on the Environmentally Weighted Material Consumption (EMC) was conducted with linked Material Flow data with environmental impacts (van der Voet et al., 2005). From this study it was concluded that bulk construction minerals such as sand and gravel contribute little to emissions. The emission rate per kg of these materials is so low that the contribution to total emissions remains well below 1%, even when multiplied with the very large size of the flows. Most of the emissions of the construction phase can be attributed to metals, especially bulk metals such as steel and aluminium. Fossil fuels are important for use phase emissions.

4.3 Energy flows

4.3.1 Energy consumption in the EU27 Figure 22 illustrates final energy consumption in the EU27. We aggregated the detailed information along the categories potentially relevant for discussing the construction sector (including building up stocks as well as renovation). For industry these are the sectors: iron and steel, non-ferrous metals, non-metallic minerals, mining and quarrying, transport equipment, machinery, construction. In the category “other industries” we summarized chemical and petrochemical, food and tobacco, textile and leather, paper/pulp/print, wood and wood products and non-specified industries. Additionally to industrial production, final energy is used in the transport sector, in residential buildings and for other uses

2. These

categories comprise the energy in the “use phase”, which is of high relevance in contrast to material use, as we will see in the following.

Figure 22: final energy consumption in the EU27 [in EJ]

The relevant users in 2009 were industry (24%), transport activities (33%), and residential uses (26%). Among the industry sectors the following sectors are most energy intensive: chemical and petrochemical (19% of industrial use), iron and steel (16%) non-metallic

2 Other final energy use comprises agriculture, forestry, fishing, services, etc. (ref Energy Stats

Manual)


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minerals and paper/pulp/print (both 13%). Mining and quarrying and construction activities only use a minor share, i.e. 1% or 2% respectively. The energy use reported for “residential” is a major use category which includes space and water heating (major share), lighting, air conditioning, refrigeration, electronics, see Section 4.3.2. The overall trend for the EU27 is again rather stable, in particular in the period from 2000 to 2009 (zero growth). The EU15 countries resemble the EU27 growth whereas the EU10 experienced a clear decrease in energy use in the years 1990 to 2000, before the final use returned to the growth pattern. However, the level of final energy use is in 2010 still below the beginning of the observation period, i.e. 1990.

Figure 23: trends in final energy consumption for the EU27, EU15, and EU10 (indexed) Between 2000 and 2009 transport, residential use and other became slightly less energy efficient. All industrial sectors on the other hand became more energy efficient. (see table 1) Table 1: Growth in final energy use between 2000 and 2009

2000-2009 EU27 EU15 EU10

Iron and Steel 0.65 0.66 0.61

Non-Ferrous Metals 0.79 0.78 0.88

Non-Metallic Minerals 0.81 0.80 0.87

Mining and Quarrying 0.74 0.78 0.62

Transport Equipment 0.81 0.78 1.07

Machinery 0.87 0.89 0.88

Construction 0.98 0.96 0.93

Other industry 0.87 0.87 0.87

Transport 1.07 1.03 1.55

Residential 1.01 1.00 1.05

Other final use 1.23 1.26 1.09

Total FEC 0.99 0.98 1.06

4.3.2 Energy use for space heating and cooling by households Energy use data from 2000 to 2010 in households were available from Eurostat (nrg tables) and are shown in Figure 24. Electricity includes all uses (heating, cooling & electrical appliances). About 19% of the electrical energy is used for space heating in the EU (see below). We assume that all other fuels are used for space heating. The indexed energy use


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picture shows (Figure 25) that for most energy sources the consumption decreased in the first half of the decade but picked-up again the second half of the decade again. Electricity use has seen a relentless growth. According the Odyssee data this is the result of increasing number of electrical appliances in households.

Figure 24: Total energy consumption per energy source by households in the European Union from 2000 to 2010.

Figure 25: Indexed total energy consumption per energy source by households in the European Union from 2000 to 2010 (2000 = 100). Electricity use in households is mostly connected to use of household appliances, hot water and cooking. These uses are not considered to be part the built environment. Only space heating and cooling are considered to be part of the built environment. The use of these activities are shown in Figure 26 for the different European Countries in 2009.


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Figure 26: Use of electricity for different purposes in households in countries of the European Union in 2009. Electricity use for space heating is quite important in Sweden, Finland and France. Air conditioning uses quite a lot of electricity in Bulgaria, Croatia and Cyprus. The combined share of electricity for space heating and cooling is shown in Figure 27 which ranges from 42% in Sweden to 1% in Lithuania. On average 19% of the electricity use in households is used for space heating and air conditioning.

Figure 27: Combined share of electricity use for space heating and air conditioning and

cooling in the European Union in 2009.

4.4 Use of other resources: land and water

4.4.1 Land use

Residential and infrastructural land use is not accounted for in EXIOPOL, and neither in MFA accounts. Land use statistics such as the Corine Land Account (EEA ref) use “artificial surfaces” as one category among 5 land use categories

3. Artificial land is further

differentiated along 4 sub-categories: Urban fabric; Industrial, commercial and transport

3 The Corine land use categories are: 1. Artificial surfaces, 2. Agricultural areas, 3. Forest and

semi natural areas, 4. Wetlands, 5. Water bodies. (EEA ref)


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units; Mine, dump and construction sites; Artificial, non-agricultural vegetated areas. Land use data still have to be compiled and analysed. Possible results will be integrated in the next version of the paper. However, it has to be mentioned, that land use data are difficult to prepare. First, data are provided in GIS formats, i.e. spatially explicit. Second, the lowest resolution is 100x100m. In the case of buildings or infrastructure, significant parts of build environment might not be covered. In EXIOBASE, land use data are available for biomass production. This includes wood. It is therefore possible to account for the land required to provide the construction sector with wood.

4.4.2 Water use Domestic water use data in the European Union were taken from Eurostat (env_watq3 table). The availability of domestic water use is limited. Some larger European countries like the UK and France did not report domestic water use. A meaningful total domestic water use per inhabitant for the European Union could therefore not be calculated. The countries that did report domestic water use from 2000 to 2010 show that in some European countries water use increased while in some it decreased. The domestic water use per inhabitant in several European countries is shown in Figure 28. Domestic water use ranges from 16m3 per inhabitant in Lithuania in to 98m3 per inhabitant in Cyprus in 2005.

Figure 28: Development of domestic water use per inhabitant in several European countries. The water footprint data in EXIOBASE are, like land use data, only indirectly related to the built environment. Data on water use in households is not included, but water use for construction materials such as wood are included.

4.5 Resource efficiency

The above presented physical accounting data will now be combined with economic growth data in order to address the question: how did resource efficiency develop in the EU27?


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Material productivity, measured in GDP/DMC4, is growing from 2000 to 2009 by 30%. If we

refer material use to the construction sector, we can define the construction sector rather narrow, i.e. the NACE construction sector, or broader, i.e. all industrial sectors that potentially related to construction activities. The latter comprises the sectors industry (incl. construction) and manufacturing. Material productivity in relation to the narrow construction sector (measured as GDP in the construction sector / DMC construction minerals) grew faster, i.e. by 45%. Both trends show a constant growth, no phases of negative growth can be observed. The broader definition using the GDP in industry and manufacturing leads to a much slower increasing MP. The underlying trend in GDP and DMC show that GDP was growing much faster until 2007 than DMC. In 2007 GDP and DMC dropped significantly and have not yet recovered again.

Figure 28: material and energy productivity in the EU27. MP = GDP/DMC, EP = GDP/FEC GDP in million PPS (Purchasing Power Standard; Eurostat 2012). Energy productivity (measured in economic growth per final energy consumption) is growing comparable to overall material productivity with stagnation in 2002 and 2007. Energy productivity in the construction sector shows a steep and constant increase until 2009. EP in relation to GDP in industry and manufacturing on the other hand grew just as overall energy productivity.

4 DMC in metric tonnes, GDP in PPS (Purchasing Power Standard)


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Figure 29: Material and energy productivity. Apart from trends in resource productivity, the level provides interesting results as well. With regard to material productivity, the construction sector is much less material efficient as compared to industry and manufacturing and the total socio-economic system. Additionally, an increase in material efficiency can only be observed for the total GDP/DMC: For energy productivity measured with GDP in industry and manufacturing, the picture is reversed: the industry sector is more energy efficient as compared to the total economy. However, the energy efficiency of the construction sector is lowest. This resembles the result of material productivity. In terms of gains in energy efficiency, the industry and manufacturing sectors developed positively. Nevertheless, these trends also show that no absolute decoupling of resource use (neither material nor energy) could be observed.

4.6 Share of built environment in total resource use and emissions in EU27

The construction sector includes construction of new houses as well as renovation, but not the use phase of the buildings. An attempt to include use phase emissions and resource use is shown in Figure 29 below. It should be noted that the use phase includes both heating and cooling of the dwellings and construction for renovation. First the larger aggregated footprint and environmental impact categories are shown in Figure 29.


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Figure 29: Contribution of residential buildings to the total resource use and environmental impacts in the European Union. For reference also the final demand associated with residential buildings in the EU compared to the total final demand of the EU is shown. It is important to note once again that the land and water footprints are indicators for indirect impacts only. They include land and water use in the agricultural and forestry sectors for the production of materials, but exclude direct land use by the residential building and domestic water use. The domestic extraction indicator is mass sum of all resources used (energy products, metal ores, mineral ores) connected to the residential buildings. The acidification, photochemical oxidant formation, human toxicity and global warming indicators take into account all air emissions in the supply chain towards the residential buildings plus the direct emissions from households as a result of space heating. If only the construction of new buildings (Build phase) in a single year is looked at in Figure 29 (blue part of the bars) the air emissions associated with new construction follows approximately the same share as final demand for new residential buildings. Something that was also observed in Section 4.2 on emission from the construction sector. Emissions are generally higher, sometimes much higher, when including heating and cooling: up to 35%. The residential built environment therefore appears to be an important sectors to address. The domestic resource use indicator in itself is not so interesting because it is dominated by the use of bulk products like sand and gravel and does not tell you anything about the resource use of metal ores. Therefore a split out was made that gives information about the individual resources in Figure 30.


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Figure 30: Contribution of residential buildings to the specific resource use in the European Union. Resource use shows the same picture as for the construction sector discussed in Section 4.1 , confirming the results, with the exception of wood. This is probably due to the use of wood as a fuel. In the following section we will see that the use of wood is one of the important drives for indirect land use connected to the residential built environment.

4.7 Contribution analysis

With EXIOBASE, it is possible to perform a contribution analysis to detect the contribution of the various underlying processes or sectors to the emissions and resource use. Such a contribution analysis can be used as a check on the results, but more importantly, as an indication of where to look when certain emissions or resource extractions should be reduced. All detailed results of the contribution analysis are given in Appendix G. As an example, two contribution analyses are explained here. The first analysis look at those activities in the supply chain that supports the residential built environment which contribute to global warming impacts. The numerical result is shown in Table 2. The first column shows the activity that is requested to support the residential built environment. Between brackets it can be seen where the activity is located; [EU] means in the EU, [XX] means outside the EU. As an example on the second data row we see that the residential built environment has a direct request for Construction work in the EU. In the second column we see the actual activity where the emission takes place in the supply chain. In the third column we see what kind of emission is responsible. In this case it is either CO2 or an CH4 emission. The second row can now be read as follows: The direct demand for construction work in the EU results in CO2 emissions in the “cement, lime and plaster” sector in the EU that contributes 8% to the total global warming indicator of the residential built environment. Direct means that it is the built residential environment that has direct emissions. It is quite clear that the CO2 emissions for space heating has a large contribution to the global warming indicator. About 55% of the emissions take place in the ‘cradle to gate’ supply chain towards built environment. This is partly demand for energy in the use phase of the built environment (direct demand for electricity & steam and hot water supply) by households. On the other hand demand for construction work leads to emissions at cement plants and in the basic iron manufacturing (blast furnace works). Notice that only contributions >1% are shown.


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Table 2: Contribution of the various activities needed for the residential built environment to the global warming indicator. Commodity(v) Commodity(>) Extension Contrib.

(%)

Direct direct CO2 46

Construction work[EU] Cement, lime and plaster[EU] CO2 8

Electricity by coal[EU] Electricity by coal[EU] CO2 5

Construction work[EU] Basic iron and steel [EU] CO2 5

Steam and hot water supply services[EU] Steam and hot water supply services[EU] CO2 3

Construction work[EU] Electricity by coal[EU] CO2 3

Construction work[EU] Construction work[EU] CO2 3

Coal and lignite; peat[EU] Coal and lignite; peat[EU] CH4 2

Electricity by gas[EU] Electricity by gas[EU] CO2 2

Construction work[EU] Basic iron and steel [XX] CO2 1

Direct direct CH4 1

In Table 3, a similar contribution analysis is shown for nickel ores. This table does not show the column extension because Ni-ore is the only extension involved while for global warming many extensions/emissions can contribute to the indicator. For Nickel the demand for Construction work has the highest contribution to Nickel ore use. The Nickel ore is mined outside the EU by the “Nickel ores and concentrates” activity and as byproduct from the “Precious metal ores and concentrates” This is true for other metals as well. It emphasizes the dependence of the EU on foreign countries for metals. Construction minerals are, as the contribution analysis shows in Appendix G, mainly produced domestically. Some of the Ni ore use takes place in sectors like “Coal and lignite; peat” and “Sand and clay”. This is caused by the Nickel ores and concentrates sector co-producing “sand and gravel”. For example the overburden in an open cast mine is sold too. See Appendix H for more details. Table 3: Contribution of the various activities needed for the residential built environment to the nickel ore use indicator.

Commodity(v) Commodity(>) Contrib. (%)

Construction work[EU] Nickel ores and concentrates[XX] 31

Construction work[EU] Precious metal ores and concentrates[XX] 21

Construction work[EU] Coal and lignite; peat[XX] 18

Construction work[EU] Nickel ores and concentrates[EU] 9

Construction work[EU] Sand and clay[EU] 6

Electricity by coal[EU] Coal and lignite; peat[XX] 3

Construction work[EU] Construction work[EU] 3

Steam and hot water supply services[EU] Coal and lignite; peat[XX] 2


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5 Conclusions

5.1 Resource use and emissions

The top-down approach taken in this paper clearly shows the importance of residential construction as a resource using and emissions generating activity in the EU. It’s contribution to the EU-27 GDP is 9%. The emissions are not particularly high: they follow GDP and contribute roughly around the same percentage to the national total. Nevertheless, being a large sector, the contribution to emissions is still significant. With regard to resources, we can conclude that the construction sector is a very large user: up to 50% for construction minerals, and 15% for metals and wood. Resource intensity, calculated in several ways, is therefore high compared to other sectors. When the use phase of the buildings is included, expanding the analysis to include the (residential) built environment, the contribution to emissions is considerably higher, up to 35% of EU total. The contribution to resource use remains the same, with the exception of wood, which is not only used as a construction material but also as a fuel in the use phase of the building. It seems that the construction sector is quite a steady variable between EU countries. The differences between countries, when looking to emissions, are small. Especially for GHG emissions, the range is quite small. In the use of resources differences appear somewhat larger. On the aggregate level we see significant deviations in the amount of construction minerals used across countries. Reasons for this are unclear – climate does not appear to play an important role, but other local aspects such as availability of certain construction materials do seem to be important. This top-down approach shows a number of gaps that cannot be easily addressed. It is important to keep this in mind, especially with a view on using IOA as a basis for modelling different options for improvement. Most important gaps are:

Emissions and resource use for the use phase of buildings cannot be identified

Information on stocks and stock changes cannot be identified

The level of sectoral detail is insufficient to be able to identify sub-categories of construction

The resources and emissions specified in EXIOPOL, although relatively large, do not cover everything relevant.

Not all of these issues can be addressed in this project. Some of them will have to be. We think it is essential to either further detail the construction sector, or to use a hybrid approach where the IOA model is combined with other models such as dynamic MFA and LCA.

5.2 Input for scenario modelling

In this paper, a number of important driving forces for the construction sector have been identified. Time series of population, GDP and Gross Fixed Capital Formation as a measure of investments in construction can be used as input for scenario modelling. For the demand side, GDP seems to correlate with demand for floor space per capita. The life span of buildings is another important variable. No time series information for these variables has been found.


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