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"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
RDC-Environment & Pira International, May 2001
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Table of content
EXECUTIVE SUMMARY............................................................................................................................7
1 CONSTRAINTS ...................................................................................................................................8
2 INTRODUCTION AND OBJECTIVES ..........................................................................................12
2.1 OBJECTIVES AND SCOPE OF THE STUDY ............................................................................................12
2.2 CONTRACTOR'S TASKS......................................................................................................................13
2.3 GENERAL METHODOLOGICAL APPROACH – LIFE CYCLE COST BENEFIT ANALYSIS ...........................16
3 DETAILED METHODOLOGY .......................................................................................................22
3.1 REVIEW OF THE CURRENT SITUATION (STEP 1) .................................................................................22
3.2 SELECTING AND DEFINING THE CASE STUDIES (STEP 2) ....................................................................24
3.3 FULL COST BENEFIT ANALYSIS OF CASE STUDIES (STEP 3)................................................................29
3.4 APPLICATION OF THE CBA RESULTS TO DETERMINE OPTIMAL RECYCLING TARGETS (STEP 4).........46
3.5 RECOMMENDATIONS AND CONCLUSIONS (STEP 5) ...........................................................................55
4 RESULTS............................................................................................................................................56
4.1 EVALUATION OF THE CURRENT SITUATION.......................................................................................56
4.2 RESULTS OF CASE STUDY CBAS ......................................................................................................60
4.3 SUGGESTED RECYCLING TARGETS ....................................................................................................90
4.4 REUSE...............................................................................................................................................99
5 CONCLUSIONS AND RECOMMENDATIONS .........................................................................112
6 GLOSSARY ......................................................................................................................................118
7 BIBLIOGRAPHY.............................................................................................................................119
ANNEXES...................................................................................................................................................123
ANNEX 1: PROCESS TREES AND SYSTEM DESCRIPTIONS...........................................................................123
ANNEX 2: INCINERATION AND LANDFILL MODELS ...................................................................................123
ANNEX 3: INTERNAL COST DATA .............................................................................................................123
ANNEX 4: ECONOMIC VALUATIONS APPLIED – SOURCES AND DERIVATION.............................................123
ANNEX 5: EMPLOYMENT DATA –JOBS FOR WASTE MANAGEMENT ACTIVITIES ........................................123
ANNEX 6: PACKAGING MIX BY MEMBER STATE ......................................................................................123
ANNEX 7: ENVIRONMENTAL DATA SOURCES ...........................................................................................123
ANNEX 8: CURRENT PERFORMANCE OF MEMBER STATES .......................................................................123
ANNEX 9: CRITICAL FACTORS LIMITING RECYCLING AND REUSE.............................................................123
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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ANNEX 10 : PRESENTATION OF CBA RESULTS FOR RECYCLING CASE STUDIES .......................................123
ANNEX 11 : CALCULATION OF RECYCLING RATES PER MEMBER STATES ................................................123
ANNEX 12 : PRESENTATION OF CBA RESULTS FOR REUSE CASE STUDIES ...............................................123
Table of figuresFigure 1 : Stepwise approach of the methodology............................................................ 22
Figure 2 : generic process tree for the recycling case study (household packaging) ........ 27
Figure 3 : Generic process tree for the recycling case study (industrial packaging) ........ 28
Figure 4 : Full CBA of case studies – sub-steps ............................................................... 31
Figure 5 : Impact assessment in LCA ............................................................................... 41
Figure 6 : Application of CBA results to determine possible recycling targets................ 48
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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Table of tablesTable 1 : Recycling case studies selected for full CBA .................................................... 25
Table 2 : Reuse case studies selected for full CBA........................................................... 25
Table 3 : Scenarios relating to household packaging waste.............................................. 32
Table 4 : scenarios relating to industrial & commercial packaging waste........................ 32
Table 5 : Achievable recycling rates for household packaging waste (%) ....................... 34
Table 6 : Determination of the potential recycling rate according to the application....... 36
Table 7 : achievable recycling rates for industrial packaging waste................................. 37
Table 8 : economic valuations........................................................................................... 42
Table 9 :Population density distribution by Member State (estimation for 2000)........... 51
Table 10 :Percentage split of municipal solid waste management (estimation for 2000). 52
Table 11 : Population mix as a function of density and national MSW treatment
(estimation for 2000)................................................................................................. 53
Table 12 : Performance of the Member States in 1997..................................................... 57
Table 13 : Summary of the recycling difficulties.............................................................. 58
Table 14 : Scenarios considered for PET beverage bottles............................................... 60
Table 15 : Calculation of GWP externality for 1 tonne PET bottles to landfill, low
population density ..................................................................................................... 63
Table 16 : Total externalities for PET bottles, Scenario 3 ................................................ 64
Table 17 : Internal costs, external costs and total social costs (low pop. density)............ 66
Table 18 : Internal costs, external costs and total social costs (high pop. density)........... 67
Table 19 : Transport distances .......................................................................................... 76
Table 20 : Optimum systems for steel packaging ............................................................. 84
Table 21 : Optimum systems for aluminium cans............................................................. 85
Table 22 : Optimum systems for other rigid and semi-rigid aluminium packaging ......... 86
Table 23 : Optimum systems for paper & board packaging ............................................. 86
Table 24 : Optimum systems for LBC packaging............................................................. 87
Table 25 : Optimum systems for mix plastic packaging................................................... 88
Table 26 : Optimum collection systems per case study, based on CBA........................... 90
Table 27 : Optimal collection systems for metal packaging ............................................ 91
Table 28 : Optimal recycling ranges per case study.......................................................... 91
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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Table 29 : Calculation of minimum and maximum recycling rate for the EU.................. 93
Table 30 : Summary of the ranges of optimal recycling rates per Member States ........... 95
Table 31 : Recycling rate per material .............................................................................. 96
Table 32 : Recycling targets per Member State in 2006 ................................................... 97
Table 33 : Sensitivity of the material recycling rates to the packaging mix ..................... 98
Table 34 : Internal, external and total cost of beverage packaging systems ................... 107
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Table of GraphsGraph 1 : Total social costs (low population density)....................................................... 66
Graph 2 : Total social costs (high population density)...................................................... 67
Graph 3 : Sensitivity of the results to the external economic valuations applied - Low
population density ..................................................................................................... 69
Graph 4 : Sensitivity of the results to the external economic valuations applied - High
population density ..................................................................................................... 70
Graph 5 : Sensitivity of the results to the internal economic costs considered - Low
population density ..................................................................................................... 71
Graph 6 : Sensitivity of the results to the internal economic costs considered - High
population density ..................................................................................................... 71
Graph 7 : Addition of employment as an impact category - low pop. density.................. 72
Graph 8 : Addition of employment as an impact category - high pop. density ................ 72
Graph 9 : Sensitivity of the results to energy recovery assumptions ................................ 73
Graph 10 : Sensitivity of the results to energy recovery assumptions .............................. 74
Graph 11 : Sensitivity of results to offset electricity assumption - Low pop. density ...... 75
Graph 12 : Sensitivity of results to offset electricity assumption - High pop. density...... 75
Graph 13 : Sensitivity of results to transport distances - Low population density............ 77
Graph 14 : Sensitivity of results to transport distances - High population density........... 77
Graph 15 : Sensitivity of results to consumer transport step - High pop. density............. 78
Graph 16 : Sensitivity of results to consumer transport step - High pop. density............. 78
Graph 17 : Sensitivity of results to overseas transport step - Low population density ..... 80
Graph 18 : Sensitivity of results to overseas transport step - High population density .... 81
Graph 19 : Sensitivity of results to virgin production credit - Low pop. density.............. 81
Graph 20 : Sensitivity of results to virgin production credit - High pop. density............. 82
Graph 21 : Internal costs for glass................................................................................... 100
Graph 22 : External costs for glass.................................................................................. 101
Graph 23 : Total social costs for glass ........................................................................... 102
Graph 24 : Internal costs for PET.................................................................................... 104
Graph 25 : External costs for PET .................................................................................. 105
Graph 26 : Total social costs for PET ............................................................................ 106
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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Graph 27 : Internal costs for refillable and non refillable glass (33cl) and PET (1.5l)
beverage packaging ................................................................................................. 108
Graph 28 : External costs for refillable and non refillable glass (33cl) and PET (1.5l)
beverage packaging ................................................................................................. 109
Graph 29 : Total social costs for refillable and non refillable glass (33cl) and PET
(1.5l) beverage packaging ....................................................................................... 110
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EXECUTIVE SUMMARY
Will be written when the main report is definitive.
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1 CONSTRAINTS
This study aims to evaluate the costs and benefits of increased recycling targets for
packaging waste in the frame of the Packaging and Packaging Waste Directive
(94/62/EC). It also investigates the costs and benefits of reusable primary packaging.
In order to achieve this, the study applies the technique of life cycle cost benefit
analysis (CBA). This is a combined life cycle assessment and economic valuation
analysis.
To perform a full cost benefit analysis for all packaging recovery and recycling
options in all EU Member States would be an immense task, and its added value
might be limited. Due to budget and time restrictions, the consultants have therefore
limited the extent of the study so as to produce a representative but accessible
analysis. Choices have had to be made which lead to simplifications that do not
always represent the full details of real conditions.
It is recognised that there need to be reservations with regards to the validity of the
details of the study results. However, it is believed that the study gives a good overall
picture of the costs and benefits linked to the investigated targets and that the main
driving forces for the results have been covered.
Nonetheless, in order to prevent misunderstandings in the interpretation and
application of the study results, it is important to consider a number of constraints
imposed by the methodology, the extent of the analysis and the data applied. These
are discussed below.
1) Life cycle cost benefit analysis
Life cycle cost benefit analysis (CBA) is a new and developing technique. There is
no standardised methodology. This study aims to apply the best available knowledge
in the field, but debate continues amongst practitioners on key aspects of the
approach, including:
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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♦ The economic valuations applied to environmental impacts
♦ The limitations of life cycle assessment methodologies on which CBA is
based
The limitations of CBA are discussed in detail in Section 2.3 of this report.
2) Scope of the study
As required by the terms of reference, this study considers the costs and benefits of
various treatment options once packaging has become waste. The system boundaries
have been drafted to reflect this.
For the investigation of recycling of packaging waste, the system boundaries begin at
the point at which packaging is discarded by the final user. For the investigation of
reusable packaging, the system boundaries include the entire life cycle of the
packaging (including extraction, conversion, filling, and distribution).
The study does not consider upstream issues of material selection. It is recognised
that higher recycling targets (and therefore end of life management costs) for one
material compared to another may induce a switch from one material to another. This
could lead to changes in the competitivity of different materials and changes in the
overall environmental performance of packaging systems. This is not addressed in
the study.
3) Limitations of data collection
Data collection and the development and testing of hypotheses was limited due to
time and budget constraints:
♦ Data have been collected from a limited number of sources (often only one
or two sources)
♦ Assumptions and hypothesis have been necessary
♦ Data from literature has not always been cross-checked with other sources
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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4) Differences between Member States
The analysis considers the following differences between Member States
♦ The packaging mix available for recycling
♦ The fraction of a Member State’s population living in densely populated
areas
♦ The residual MSW treatment system applied to packaging waste that is not
recycled (i.e. landfill or incineration with energy recovery).
The internal costs of operating processes vary across EU. This will influence the costs
and benefits of recycling in different Member States. This is addressed where
possible by considering data ranges for internal costs.
The case studies do not explicitly take into account the following differences between
MS :
• Motivation of the population to participate in recycling schemes
This significantly influences the range of recycling rates that can be achieved
in Member States. The range of recycling rates modeled in the analysis
considers the collection and recycling rates that could be achieved if a scheme
is implemented where a motivated population exists. This implies an
appropriate level of communication of the scheme. However, communication
does not guarantee motivation of the population. In some Member States the
achievable collection and recycling rates may be lower than the range
modeled, in other Member States it may be higher. Cultural differences may
play an important role. This is not considered in the analysis.
• Existence of recycling infrastructures
The capital costs of infrastructure are allocated per ton of material handle, but
the analysis does not consider the existence or absence of an existing recycling
infrastructure in each MS. A “steady state” analysis is considered. The results
do not take into account the difficulty of establishing additional infrastructure.
It is assumed that there is available capacity throughout the EU or such
capacity may be established if there is enough supply of material and
sufficient demand for recyclate.
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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• Typical family structure
Although the packaging mix in each Member State has been considered, the
typical family structure has not been considered. This may influence the
composition of packaging waste in the household MSW stream, which will
ultimately influence collection and sorting of packaging waste arising from
households.
• Specific geographical problems
The study does not consider specific geographical problems imposed by
adverse weather conditions or isolated communities such as island or
mountain based communities.
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2 INTRODUCTION AND OBJECTIVES
The Directive on packaging and packaging waste (94/62/EC) established the
following targets1 for the recovery and recycling of packaging waste for the period
1996 – 2001:
• A recovery target of between 50% and 65% by weight of packaging waste andwithin this,
• A recycling target of between 25% and 45% by weight of packaging waste with aminimum of 15% by weight for each packaging material.
The Directive requires the EC to review these targets before the end of the first five-
year period. As part of this review, the European Commission has commissioned a
number of studies, including this study.
The main purpose of this study is to perform an evaluation of the costs and benefits of
higher recycling targets and reuse targets. This section describes the study’s
objectives, scope and the concept of cost benefit analysis.
2.1 Objectives and scope of the study
As stated in the call for tender, “The objective of the study is to perform a
cost/benefit analysis of packaging recycling and reuse systems, including:
1. an evaluation of the situation concerning the fulfillment of specific targets as
required by the packaging and packaging waste Directive 94/62/EC by the end of
the first five-year phase (30/06/2001), i.e. 15% for each packaging material
(glass, plastic, paper/board, metals, composites, wood, others),
2. a prospective study concerning the fulfillment of higher recycling targets for
packaging materials by the end of the second five-year phase (30/06/2006) taking
into account limiting factors such as technical feasibility, economic implications
and environmental benefits,
3. an investigation concerning the possible establishment of reuse targets for the
relevant packaging materials by the end of the second five-year phase
1 Member States are permitted to implement higher targets where it can bedemonstrated that these can be achieved without disrupting the functioning of theinternal market.
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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(30/06/2006) taking into account technical feasibility, costs and environmental
benefits, and the development of a methodology for the calculation and
monitoring of these targets.”
A possible approach was to start from different recycling rates, to determine the way
to achieve them and to determine their costs and benefits. The approach used in this
study is different: we first considered the different possible systems, we determined
their optimum organization, calculated their costs and benefits and then considered
the recycling rates achievable by the “cheapest” system.
The study aims to cover:
♦ All fifteen Member States
♦ Each individual packaging material (glass, plastic, paper/board, metals,
composites, wood, others)
♦ All packaging applications (primary, secondary, tertiary)
♦ Alternative packaging collection and reprocessing options
However, in order to achieve the analysis within the budget and time constraints, it
has been necessary to make assumptions and hypotheses which limit the scope of the
analysis (see chapter 1 of this report).
2.2 Contractor's tasks
As stated in the call for tender, the contractor's tasks are the following ones :
"Task 1: Data compilation
The contractor shall perform a review of the relevant studies in the field of packaging
waste management systems including cost-benefit analyses.
The contractor shall also use the data provided by Member States according to the
provisions of the packaging and packaging waste Directive 94/62/EC and the
Commission Decision 97/138/EC establishing the database formats. This data covers
the calendar year 1997 and includes figures on the quantity of packaging material
placed on the market, re-used, recycled, recovered and disposed of.
The study shall consider both packaging waste treated within the territories of the
Member States as well as exported quantities. Information shall be given on the
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
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countries of destination of exports, the used treatment methods and the monitoring
systems applied in these countries.
Data concerning the different packaging materials shall take into account their
source (municipal, industrial,...) and their utilisation nature (primary, secondary and
tertiary packaging).
Task 2: Analysis of collection, recycling and reuse systems
The different existing collection and sorting systems shall be described in terms of
costs and effectiveness (collection of packaging with the general municipal waste and
further sorting; selective collection through kerbside or drop-off systems; other
options).
The different existing treatment routes for recycling shall be described in as much
detail as possible in terms of capacities, costs and environmental impacts.
Special emphasis shall be put on the description of the different recycling processes
for plastics2, which shall be defined as clearly as possible. In that context, the
analysis will consider as far as possible the different plastics packaging materials
split up as relevant in PE (polyethylene), LDPE (low density polyethylene), HDPE
(high density polyethylene), LLDPE (linear low density polyethylene), PET
(polyethylene terephtalate), PP (polypropylene), PS (polystyrene), PVC
(polyvinylchloride),...
Existing deposit systems for returnable and reuse packaging materials shall be
investigated.
2 "mechanical recycling" where plastics are reprocessed with unchanged chemicalstructure;•"chemical recycling" (also known as feedstock recycling) where the polymericchemical structure is broken down to monomer or to a more basic chemical structure,including inter alia de-polymerisation processes such as methanolysis, glycolysis.aminolysis and acidolysis, thermal cracking processes (as Veba, BASF and BPprocesses), pyrolysis, gasification (Texaco process) and blast furnace process (use ofplastics as reductor agent);"pseudo recycling processes" consisting in an energy recovery from plasticspackaging, waste after "mechanical recycling" and/or "chemical recycling"
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Task 3: Costs and benefits of packaging waste management according to current
and possible future targets
The contractor shall establish an appropriate general method of calculating costs
and benefits of packaging waste management. This method shall then be applied to
the situation in the fifteen Member States according to the scenarios described in
tasks 3.1, 3.2 and 3.3. Particular emphasis shall be put on plastics and composites
packaging.
§ The financial balance shall identify all relevant costs related to the collection and
treatment of packaging waste according to the various options, identify possible
revenues from the sale of secondary materials and calculate the reduced costs of
municipal waste management as a result of the separate collection.
§ The environmental evaluation shall identify the amounts of the primary raw
materials that can be saved through the re-use and recycling of packaging
according to the various possible targets. The associated change of environmental
impacts (in particular: climate change, acidification, tropospheric ozone,
eutrophication, toxic substances dispersion and disposal of final solid waste) shall
be quantified as far as possible in monetary terms of avoided externalities. In the
absence of monetary figures, quantitative values of avoided pollution shall be
given.
§ Employment and social effects shall be described and quantified as far as
possible.
The contractor shall also perform a sensitivity analysis on factors that might
substantially influence the results of the cost-benefit analysis.
Task 3.1: fulfillment of specific recycling targets as required by the Packaging
Directive by June 2001, i.e. 15% for each packaging material,
The contractor shall make an evaluation of the situation in the different Member
States:
• confirming that the targets foreseen will be met
• and describing possible positive or negative variations.
Task 3.2: fulfillment of higher recycling targets by June 2096.
The contractor shall, in agreement with the Commission, identify a set of meaningful
targets to be achieved by June 2006 for the various materials with a view to
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maximising environmental benefits. A minimum of eight relevant case studies shall
describe possible combinations of these targets and investigate different optional
routes to achieve these targets. Again, particular emphasis should be put on the
recycling of plastics and composite packaging.
The contractor shall determine limiting factors for the achievement of these higher
targets, such as technical, ecological, economic and practical ones in terms of
collection. The contractor shall discuss possible solutions to be applied to these
limiting factors. Possible Community and national measures that are likely to
improve the efficiency of the systems shall be identified. Measures might include in
particular legislative and voluntary initiatives, financial assistance, innovation
incentives, etc.
Task 3.3: establishment of reuse targets
The report shall include information on existing deposit systems on packaging. It
shall describe and evaluate these systems according to the following factors:
materials covered, return rates/number of observed rotations, reuse/recycling levels
achieved, costs, system management and other issues that are of interest with respect
to the current situation and future development of these systems.The contractor shall make an evaluation of the technical feasibility, the costs and the
environmental benefits in order to set reuse targets by June 2006 for the relevant
packaging materials. A methodology for the calculation and monitoring of these
targets shall be proposed."
2.3 General methodological approach – Life cycle cost benefitanalysis
The general approach applied is based on the principle of life cycle cost benefit
analysis (CBA). This section of the report briefly describes the concept of CBA. A
detailed description of the methodology applied in this study is provided in Section 3
of this report.
What is CBA?
CBA is an economic evaluation tool used to compare the costs against the benefits of
different activities. Within the context of policy development, CBA attempts to
quantify the total costs and total benefits of a given policy option in order to
determine whether the policy is worth pursuing.
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The policy is considered from the social welfare perspective. An action is considered
worthwhile if the total benefits to society outweigh the total costs to society.
These costs and benefits must be considered across the whole life cycle of the system
affected by the policy decision. Therefore, life cycle cost benefit analysis combines
aspects of financial cost benefit analysis with the economic valuation of the
environmental impacts which are determined by life cycle assessment techniques.
Why use CBA?
Environmental policies are pursued in order to provide environmental protection and
environmental improvement. These are the benefits of environmental policies. Such
benefits may be measured in terms of environmental protection provided or
environmental improvements made. For example, policies to reduce the effects of
global warming may be quantified in terms of avoided greenhouse gas (measured in
kilograms of CO2 equivalents). These benefits are known as externalities, as they are
external to the traditional economic model.
However, in addition to these environmental benefits, an environmental policy
decision will also incur implementation costs. Different policy options will incur
different cost implications. The internal costs of implementation are known as
internalities, as they are internal to the traditional economic model.
Politicians and decision-makers seek to pursue policies that provide good value for
money by achieving environmental objectives / benefits without incurring
disproportionate internal costs. A quantitative comparison of the costs and benefits of
environmental policies can only be achieved if the internalities and externalities are
measured in a common unit. CBA seeks to do this by valuing in monetary terms the
externalities, and comparing these against the internal costs of implementation. In
this way, we gain insight into the trade-offs (within and between economic costs and
environmental benefits) that are inevitably made when selecting and implementing
policies.
Limitations to CBA
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CBA is a new and developing technique. As with all tools and techniques, there are
limitations to the methodology. The limitations of CBA should be recognised before
the methodology is applied:
• Ethical issues
Many critics of CBA question the underlying ethics of monetary valuation of
environmental impacts. They believe that the environment is something sacred upon
which it is not acceptable to place a monetary value. It needs to be underlined,
though, that every political decision on environmental measures implicitly gives a
value to the environment. The question is whether this is done on the basis of
transparent information or not.
• Methodological limitations of LCA
The environmental analysis that is performed prior to the economic valuation of the
environmental impacts is based on life cycle assessment (LCA) methodologies. LCA
has been subject to international standardisation efforts, but some methodological
limitations persist:
Ø The nature of choices and assumptions made in LCA (e.g. system boundary
setting, selection of data sources and impact categories) may be subjective
Ø Models used for inventory analysis or to assess environmental impacts are
limited by their assumptions , and may not be available for all potential
impacts
Ø Results for LCA studies focusing on global or regional issues may not be
appropriate for specific local applications
Ø The accuracy of LCA studies may be limited by accessibility or availability of
relevant data, or by data quality and data gaps
Ø A lack of spatial and temporal considerations in inventory data that are
subsequently used for impact assessment may introduce uncertainty to the
results
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• Achieving economic valuation of environmental impacts
Not every externality can be valued in monetary terms at present:
Ø Several external effects are difficult to measure
Ø Some environmental impacts are too site specific to be reliably transferred
from specific studies to a general CBA methodology
Ø Studies to determine economic valuations have only been conducted in a
limited number of areas. Willingness-to-pay for prevention of damages to the
environment may vary between geographical populations, but it is necessary
to rely on the concept of benefit transfer in order to develop a general CBA
methodology.
• Methodological difficulties arising from attempts to perform monetisation
Where monetisation can be performed, the reliability of the values derived may be
questioned. A variety of techniques can be applied to derive economic valuations. In
many cases, application of different techniques results in conflicting valuations being
achieved, suggesting inherent bias in valuation methodologies. The alternative
techniques that can be applied are described in detail in Annex 4: Economic
valuations applied – sources and derivation.
§ Increasing difficulties of isolating external costs
Increasingly, national environmental policies have attempted to internalise some
aspects of external costs. For example, emission permits and landfill taxes effectively
internalise some elements of pollution. The charges for these permits and taxes have
rarely been based on a detailed evaluation of the external costs of the avoided
environmental impact. These charges should not be included when performing CBA,
but it is not easy to accurately determine the level of internalisation. This may lead to
some double counting in the methodology.
• Quantifying indirect and secondary effects
The difficulties of quantifying indirect costs and secondary effects means that many
studies focus only on the direct costs. This limited approach could have a significant
influence on the true “social cost”. In some cases, wider effects can only be taken
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into account by inclusion of broad assumptions, which may be limiting. Indirect and
secondary effects have not been considered in this study.
How to use CBA
This type of approach enables decision-makers and stakeholders to better understand
the trade-offs within and between economic costs and environmental benefits that are
inevitably made when selecting policies. Thus, CBA makes decision-making more
transparent. It is an aid to the decision-making process, not a substitute for it.
The decision-maker must still judge how to weigh up environmental effects,
economic costs and the distributional impacts of the different policy options in order
to select the preferred option
It is important to recognize CBA as a useful tool rather than a decision rule. By
asking the right questions it opens up the discussion and identifies key issues.
Relationship of CBA to other economic evaluation tools
CBA considers the micro-economic effects of the policy in detail. This is known as a
“bottom-up” approach. However, in considering these micro-economic effects,
broader consequences of the policy decision should not be overlooked. In some
cases, it may be appropriate to support CBA with some form of “top-down” macro-
economic analyses.
Such macro-economic analysis techniques may consider the impacts of policy on
economic indicators such as GDP, inflation rate, and the trade balance. This type of
analysis is most appropriate for policy instruments with potentially significant macro-
economic effects.
Examples of macro-economic tools include:
§ General and partial equilibrium models
§ Input-Output models
§ Application of multipliers.
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However, macro-economic analyses in isolation may not be appropriate for assessing
the potential benefits of specific environmental policy measures. Statistics such as
GDP are measures of the volume and structure of market transactions rather than
measures of welfare or the efficiency of resource use. Macro-economic analyses
sacrifice technical detail for greater spatial scope
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3 DETAILED METHODOLOGY
This section describes the methodological approach applied in order to fulfil the study
objectives. The approach has been broken down into a series of steps, as described in
Figure 1. Where appropriate, the application of the methodology has been
demonstrated through reference to the calculations performed for a specific case study
(PET bottles).
Figure 1 : Stepwise approach of the methodology
Each of the Steps is described in greater detail in the following sections.
3.1 Review of the current situation (step 1)
In this step, the current packaging waste recovery and recycling situation in Europe is
reviewed. The aim is:
• To determine the performance of Member States against the current targets for
packaging waste recovery and recycling
STEP 1:Review ofcurrentsituation
STEP 2:Selecting andDefining CaseStudies
STEP 3:Full CBA ofSelectedCase Studies
STEP 4:Application ofresults to determinepossible recyclingtargets
STEP 5:Recommendationsand Conclusions
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• To determine the critical factors that limit the levels of recycling or reuse that
can be achieved
3.1.1 Current performance of Member States
Data and forecasts have been collected for the years 1997, 1998 and 1999.
The collected data is classified by the following parameters:
♦ Classification of the data per year
♦ Classification according to waste production (packaging brought on the
market), and recycled amount, for individual Member States
♦ Data were collected for the material classes as detailed as possible
(as much sub-divisions according to material applications as
possible)
♦ glass,
♦ plastics,
♦ paper & cardboard,
♦ metals,
♦ composites,
♦ wood,
♦ other packaging materials
3.1.2 Critical factors limiting recycling and reuse
The critical factors limiting the levels of recycling or reuse that can be achieved for a
material and/or by packaging application are classified according to their specific
nature:
♦ Technical
♦ Economic
♦ Marketing
The critical factors for each material have been identified through a combination of
literature search and discussion with stakeholders.
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3.2 Selecting and defining the case studies (step 2)
Due to the constraints of time and budget, the full cost benefit analysis can only be
applied to a limited number of case studies. The aim of Step 2 of the methodology is
to select appropriate case studies for full cost benefit analysis and to define the
specific process tree for each case study.
3.2.1 Select packaging applications for full cost benefit analysis
The selection of packaging applications for full CBA is ultimately subjective, but in
determining the case studies the following criteria have been considered:
♦ Packaging applications are not considered for full CBA where there is a
general consensus that the recycling rate should be high
♦ Packaging applications which contribute to the production of the highest
quantity (by weight) of packaging waste in the EU are favoured
♦ Special attention is given to plastics and composites3
♦ Some reuse systems must be included
♦ Efforts are made to ensure that a sufficient diversity of packaging materials
and applications are considered
♦ Efforts are made to ensure that there is a sufficient quality of data to complete
each CBA
Based on the consideration of these criteria, the following case studies have been
selected.
3 As required by the EC in the call for tender
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Table 1 : Recycling case studies selected for full CBA
N° Material Case study Industrial/household
1 Plastics LDPE films Industrial
2 Paper/cardboard Corrugated board Industrial
3 Plastics PET bottles Household
4 Plastics Mixed plastics Household
5 Steel All applications Household
6 Aluminium All rigid and semi-rigid applications Household
7 Aluminium All flexible applications Household
8 Paper/cardboard All applications Household
9 Composites Liquid beverage cartons (LBC) Household
10 Glass Beverage bottles Household
Note: the two aluminium systems can be done as a single scenario for total aluminium
Table 2 : Reuse case studies selected for full CBA
N° Material Case study Industrial/household
1 Glass Single trip beverage bottles and
reusable beverage bottles
Household
2 PET Single trip beverage bottles and
reusable beverage bottles
Household
The recycling case studies selected represent a significant fraction of the total
packaging waste stream. The following important packaging waste flows have been
excluded from the full CBA case studies, as there is a general consensus that high
reuse and recycling rates should be achieved for these applications:
♦ Industrial steel applications, such as drums and pails (due to the high
economic value of the material high rates of reuse, reconditioning and
recycling are already achieved for these applications)
♦ Wood packaging applications, such as pallets - high levels of reuse,
reconditioning and recycling of wood pallets and other wood packaging
applications are already achieved
♦ Rigid industrial packaging applications, such as crates, drums and pails
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3.2.2 For each packaging material / application selected for full CBA, define the
process tree
The process tree defines the individual unit processes and the system boundaries
considered in the analysis. A unit process is the smallest portion of a system for
which data are collected when performing an LCA study. The system boundary is the
interface between a system and the environment or other systems. Data is only
collected for those unit processes inside the system boundary.
The full process trees for each case study are presented and described in Annex 1:
Process trees and system descriptions of this report. The incineration and landfill
models considered are described in Annex 2: Incineration and landfill models.
3.2.2.1 Recycling case studies
Figure 2 and Figure 3 show the generic process trees for the recycling case studies.
The system boundaries begin at the point at which the packaging material is discarded
by the final holder. The system boundaries end at the point of final disposal (i.e.
landfill or incineration) or at the point at which the material directly replaces a virgin
product/material. The point at which the material directly replaces a virgin
product/material may be immediately after sorting or may be after some reprocessing
of the sorted packaging waste. Credit for offset virgin production is included in the
system boundaries.
Within the system boundaries, the operation of each unit process is considered. This
includes all waste management, reprocessing, transport, and energy production unit
process. The system boundaries include the capital necessary to provide these unit
processes.
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Figure 2 : generic process tree for the recycling case study (household packaging)
PACKAGING
WASTE ARISING
LANDFILL
MSW INCINERATION
ENERGY
CREDIT
RECYCLING
COLLECTION FOR
INCINERATION
COLLECTION FOR
LANDFILL
TRANSPORT TO
RECYCLERSSORTING +
BALING
SEPARATE
KERBSIDE
COLLECTION
ROUND
COLLECTION
FROM BRING
BANK
TRANSPORT TO
BRING BANK
MATERIAL
CREDIT
ENERGY
CREDIT
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Figure 3 : Generic process tree for the recycling case study (industrial packaging)
PACKAGING
WASTE ARISINGMSW
INCINERATION
COLLECTION
FOR
INCINERATION
ENERGY
CREDIT
LANDFILLENERGY
CREDIT
COLLECTION
FOR
LANDFILL
RECYCLINGSORTING
COLLECTION
FOR
RECYCLING
MATERIAL
CREDIT
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3.2.2.2 Reuse case studies
The system boundaries begin at the extraction of raw materials for the production of
packaging. The system boundaries end at the point of final disposal (i.e. landfill or
incineration) or at the point at which the material directly replaces a virgin
product/material. Within the system boundaries, the operation of each unit process is
considered. This includes all production, waste management, reprocessing, transport,
and energy production unit process, including those associated with the collection,
sorting, and washing of packaging for reuse. The system boundaries include the
capital necessary to provide these unit processes.
3.3 Full cost benefit analysis of case studies (step 3)
This section of the methodology describes how CBA techniques are applied to the
selected case studies. Life cycle cost benefit analysis (CBA) is an economic
evaluation tool used to compare the costs against the benefits of different activities.
CBA attempts to quantify the total social costs and total social benefits of an activity.
The total social costs of an activity are the sum of the internal costs and external costs.
Internal costs are those costs internalised to the economy. External costs are the costs
that arise when the social or economic activities of one group of people have an
impact on another, and when the first group fails to fully account for their impact.
For example, external costs arise if an economic activity causes environmental
damage and the polluter does not pay for clean up or fails to compensate those who
suffer from this damage.
The classic example of an external effect is that of an upstream factory polluting a
river in a way that has a negative impact on catches in a downstream fishery. In
deciding upon how much it will produce and consequently how much it will emit to
the river, the upstream factory will not take this effect into account.
To determine the internal and external costs and benefits, CBA combines aspects of
financial cost benefit analysis with the economic valuation of environmental impacts
as determined by life cycle assessment techniques.
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Life cycle assessment is a technique for assessing the potential environmental impacts
of a product or process by compiling an inventory of relevant inputs and outputs of
the system and subsequently evaluating the potential environment impacts associated
with those inputs and outputs.
Economic valuation is a technique for determining the monetary value of a specific
environmental impact. This facilitates the direct summation of different
environmental impacts for comparison against the internal costs and benefits. It also
allows to take into account some types of local environmental impacts that are usually
not considered in LCA due to the lack of valuation methodology, in particular for
transport (traffic congestion, traffic accidents, traffic noise) and disaminity (odours,
vibrations, harmful animals, fear, dust…).
The full CBA of the case studies is completed in a series of sub-steps as illustrated in
Figure 4.
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Figure 4 : Full CBA of case studies – sub-steps
DETERMINE SCENARIOS
MODELINTERNAL
COSTS
MODELEXTERNAL
COSTS
MODEL + VALUEGROSS
EMPLOYMENT
COMPILETOTALSOCIALCOSTS
UNCERTAINTY/SENSITIVITY ANALYSIS
INTERPRETATION
Each sub-step is described in detail below.
3.3.1 Determine scenarios
The specific scenarios to be considered in each case study must be determined. This
sub-step describes how the scenarios are derived.
3.3.1.1 Recycling case studies
For each household packaging waste case study, scenarios are determined according
to three key parameters:
♦ Population density (i.e. high or low population density)
♦ National municipal solid waste (MSW) management option available as an
alternative to recycling (i.e. landfill or incineration)
♦ Where recycling is considered, the type of selective collection scheme (i.e. bring
scheme or separate collection)
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Thus, for the household packaging waste case studies the following combinations of
scenarios are possible:
Table 3 : Scenarios relating to household packaging waste
Population density Waste management of MSW Collection scheme Recycling rate
High Landfill None 0%
High Landfill Bring W to X%
High Landfill Separate kerbside collection Y to Z%
High Incineration None 0%
High Incineration Bring W to X%
High Incineration Separate kerbside collection Y to Z%
Low Landfill None 0%
Low Landfill Bring A to B%
Low Landfill Separate kerbside collection C to D%
Low Incineration None 0%
Low Incineration Bring A to B%
Low Incineration Separate kerbside collection C to D%
For each case study, the specific recycling rates considered are those that are
achievable in a steady state situation applying the selective collection system with an
efficient management, i.e. considering:
♦ efficient organization of the scheme, e.g. :
§ frequency (e.g. once every 2 weeks for kerbside collection of light packaging)
or
§ density (e.g. one glass bottle bank for 1000 or less inhabitants)
♦ efficient communication of the scheme to potential participants
♦ a scheme in existence for at least 3 years (steady state achieved).
For each commercial & industrial packaging waste case study, the scenarios are
determined only according to the solid waste management option available as an
alternative to recycling (i.e. landfill or incineration). Thus, for industrial &
commercial packaging waste case studies the following combinations of scenarios are
possible:
Table 4 : scenarios relating to industrial & commercial packaging waste
Waste management of MSW Collection scheme Recycling rate
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Landfill None 0%
Landfill Source separated selective collection U to V%
Incineration None 0%
Incineration Source separated selective collection U to V%
Again, for each case study, the specific recycling rates considered are those that are
achievable applying the selective collection system with an efficient management, i.e.
considering:
♦ efficient collection frequency (no full containers)
♦ efficient communication of the scheme to workers.
The recycling rates considered for the household packaging case studies are
summarised in Table 5.
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Table 5 : Achievable recycling rates for household packaging waste (%)
High density Low density
% Kerb. Bring Kerb. Bring
Plastics PET bottles 59-69 22-32 70-80 35-45
LPDE films 20-25 20-25 20-25 20-25
HDPE bottles 48-58 17-27 57-67 28-38
Mixed plastics - mech. recycling 5-10 5-10
Mixed plastics – blast furnace 60-80 60-80
Steel* 40-60 15-21 40-60 15-21
Aluminium* Cans 45-55 31-41 45-55 31-41
Other rigid and semi-rigidpackaging
6-16 3-8 7-17 3-10
Flexible packaging 0 0 0 0
Wood 0 0 0 0
Cardboard 55-65 19-29 61-71 25-35
composites LBC 55-65 24-34 55-65 24-34
Mainly based on plastic 20-25 20-25 20-25 20-25
Mainly based on cardboard 20-25 20-25 20-25 20-25
Mainly based on Al 20-25 20-25 20-25 20-25
Glass 42-91 73-83
Other 0 0 0 0
* A possible reason for the relatively low values of the achievable rates for the metals
(specially beverage cans) is the fact that a large part is consumed in the industry and
may not enter the selective collection schemes for household packaging waste.
Collections schemes of household packaging in industry have not been investigated.
The sources of those achievable recycling rates are given below. Only the sources
that refer to efficient selective collection systems (see above) were considered.
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Data Sources Comments
Plastics Interview of Eco-Emballages
Extrapolation of data publishedin the Annual Report of theCompliance Schemes
Potential for post-user plasticwaste recycling, Sofres-TNO,commissioned by APME, March1998
Range of ± 5% was applied inorder to take into account thedifferences between MS.
Steel Interview of APEAL
Extrapolation of data publishedin the Annual Report of theCompliance Schemes
Range was discussed withAPEAL.
Aluminium Interview of EAA
Extrapolation of data publishedin the Annual Report of theCompliance Schemes
Interview of Eco-Emballages
Range of ± 5% was applied inorder to take into account thedifferences between MS
Cardboard Interview of Eco-Emballagesand CEPI
Extrapolation of data publishedin the Annual Report of theCompliance Schemes
Range of ± 5% was applied inorder to take into account thedifferences between MS
LBC Interview of ACE
Extrapolation of data publishedin the Annual Report of theCompliance Schemes
"What happens to used beveragecartons ?", brochure made byTetra Pak, January 2000
Range of ± 5% was applied inorder to take into account thedifferences between MS
Glass Glass recycling in EuropeanCountries – 1999, data providedby FEVE, November 2000
Eco-Emballages, interview ofstakeholders
In case of low pop. density a rangeof ± 5% was applied in order totake into account the differencesbetween MS.
Compositesother than LBC
Assumption
Wood and othermaterials
Assumption Insufficient amount to be collectedselectively
Example: Scenarios determined for the PET bottles case study
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See Table 14, p. 60
Industrial packaging waste is subdivided into 3 categories (Table 6):
- waste that can’t be recycled for technical reasons (contamination, has contained
hazardous waste ,…)
- waste that can’t be recycled for economical reasons, i.e. when the industry does
not produce a sufficient amount packaging waste (assumption : 5% of the non
contaminated amount)
- waste that should be recycled
Table 6 illustrates the analysis of industrial plastic packaging, which was performed
in collaboration with EuPC.
Table 6 : Determination of the potential recycling rate according to theapplication
% % % achievablerecyclingrate
weightedtarget
20% hazardous 0% 0%
15% notrecyclable
0% 0%
30% small (<60l)
80% nonhazardous
85% recyclable 95% 19,4%
70% large (>60l) 100% reuse 10% 7%
Drums
(100%HDPE)
Total 26,4%
30% hazardous 0% 0%
50% not recyclable 0% 0%70% nonhazardous 50% food recyclable 95% 33,3%
Jerricans+/-100%HDPE
Total 33,3%
IBC 100% reuse 95% 95%
44% shrink 85% 37.4%
56% stretch 50% 28%
Films *
Total 65.4%
EPS notrecyclable
0%
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Sacks 30% 30%
HDPE,LDPE, PP
Pallets pallets 96% reuse 40% 40%
Crates crates 90-95% reuse 25% 25%
* Stretch and shrink films can not be recycled together. They can be easily
identified and separated by hand by professionals.
The achievable recycling rates considered for the industrial & commercial packaging
waste case studies, taking into account the recycling limits, are summarised in Table
7:
Table 7 : achievable recycling rates for industrial packaging waste
Best estimate Range
Plastics LDPE films 65.4% 55-75%
Others 31.3% 21-41%
Total 46.3% 36-56%
Wood 60% 50-70%
Steel 85% 80-90%
Corrugated board 72% 64-80%
Glass 66% 50-83%
Others 0% 0%
The sources for those data are the following ones.
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Data Source Comments
Plastics Interview of EuPC
Potential for post-user plasticwaste recycling, Sofres-TNO,commissioned by APME,March 1998
The recycling rates determined incollaboration with EuPC wereapplied to the available amount inWestern Europe.
Wood 40% are assumed to be used byhousehold – 60% recycling forrepair of pallets and making ofparticle board
Steel Interview of APEAL
Corrugated board Interview of CEPI
Glass Interview of FEVE In case of high amount, assumedto be mainly household packaging
Others Assumption Insufficient amount to be collectedselectively
3.3.1.2 Reuse case study
For the reuse case study, the following systems are considered:
♦ Single-trip packaging system for glass and PET
♦ Reusable packaging system for glass and PET
For the reusable system, a baseline scenario is modelled as a function of 2 main
influencing factors:
♦ Reuse rate of reusable primary pack = x times
♦ Distance travelled for the collection of reusable packaging = y km
The influence of reuse rate and distance are then investigated. Results are presented
as a function of those factors. But no optimum target can be derived from the
calculations because no market data was sought on the actual:
♦ transport distances
♦ number of uses of the refillable packaging
3.3.2 Model the internal costs
The internal costs considered in this study are defined as “the operational costs
incurred by industry”.
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3.3.2.1 Recycling case studies
A “steady state” model is assumed (i.e. the costs of operating an existing successful
system are considered). The analysis includes the capital costs required to develop
the infrastructure necessary to achieve the defined recycling rate. These capital costs
are considered only as a function of throughput of waste (i.e. they are allocated per
tonne of waste managed). No consideration of the time at which these capital costs
would be incurred by each Member State has been made. E.g. for an incineration
plant, the cost per ton includes :
• the investment cost per ton : investment value / tons handled over the
lifetime
• the financing cost per ton : present value of the interests paid in the future
to finance the investment / tons handled over the lifetime
The total internal cost of each scenario is the sum of all costs minus the sum of all
revenues. This is similar to the concept of “financing need” as considered in the TN
Sofres report “Cost efficiency of Packaging Recovery Systems – The case of France,
Germany, The Netherlands and the UK”. Where the financing need is positive,
recycling is not a self-supporting activity – intervention in the market is required to
stimulate recycling. Where the financing need is negative, recycling is a potentially
profitable activity, and under the right circumstances may occur without intervention
in the market.
Internal costs have been determined for each specific detailed system. However, even
where equivalent waste management practices are compared, internal costs can vary
considerably between Member States, depending on a range of factors such as cost of
living and geographical considerations (mountainous regions, islands, etc). Therefore
the sensitivity analysis considers the influence of a variation of +/- 20% of the total
internal costs on the determination of the optimum system. The size of the range is
based on interviews with compliance schemes and industrials.
The internal costs applied in this study are summarised in Annex 3: Internal cost
data.
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Example: Internal cost calculation for PET Bottles scenarios
See chapter 4.2.1.2
3.3.2.2 Reuse case studies
For the reuse case studies, the internal costs of reuse systems include the costs of raw
material production and conversion, filling, distribution, collection, washing, and
waste management of non-returned bottles (or single-trip bottles). The influence of
reuse rate and distance on internal costs is investigated. The internal costs applied in
this study are summarised in Annex 3: Internal cost data.
3.3.3 Model the external costs
In this study, the environmental impacts of each scenario are modelled using an LCA
approach.
First, the environmental inputs and outputs are modelled in line with the requirements
of ISO 140404 and ISO140415, using the Pira International LCA model PEMS 4.7
(inventory analysis).
Each environmental input or output is then classified according to the environmental
impacts to which it may contribute, and characterised according to its potential to
contribute to that impact. (For the LCA part the ISO methodology is applied, i.e. no
weighting. In a consecutive stage, the CBA methodology is applied, including
monetisation6 of environmental problems. This process is demonstrated in Figure 5.
4 ISO14040 Environmental management - Life cycle assessment - Principles andframework5 ISO14041 Environmental management - Life cycle assessment - Goal and scopedefinition and inventory analysis6 also called "economic valuation"
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Figure 5 : Impact assessment in LCA
CO2 Global warming (in Kg of CO2equivalent)
CFC's
HCFC's
Ozone layer depletion (in Kg ofCFC11 equivalent)
"Environmental score"CH4 Photochemical oxidant formation
(in Kg of C2H4 equivalent)
HC
NOxAcidification (in Kg of SO2equivalent)
SO2
EconomicValuation
Inventory Classification/Characterisation
LCA part CBA part
Finally, an economic valuation is applied to each environmental impact category.
This allows the environmental impacts to be converted into a common monetary unit,
which can then be summed to provide an estimate of the total external costs of the
scenario. The sources of environmental data applied in this study are listed in Annex
7: Environmental data sources.
The methodology applied in this study considers the following impact categories (as
listed in Table 8).
The following environmental impact categories and economic valuations are applied:
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Table 8 : economic valuations
Unit Valuation
GWP (kg CO2 eq.) /kg CO2 0,01344
Ozone depletion (kg CFC 11 eq.) /kg CFC11 0,68
Acidification /kg H+ 8,70
Toxicity Carcinogens (Cd equiv.) /kg Cadmium (carcinogenic effects only) 22
Toxicity Gaseous non carcinogens(SO2 equiv.)
/kg SO2 from electricity production 1
Toxicity Metals non carcinogens(Pb equiv.)
/kg Pb 62
Toxicity Particulates & aerosols(PM10 equiv.)
/kg PM10 from electricity production 24
Smog (ethylene equiv.) /kg VOC 0,73
Black smoke (kg dust eq.) /kg smoke 0,66
Fertilisation /kg expressed as NO2 mass equivalents -0,7
Traffic accidents (risk equiv.) /1000 km travelled on an average road 17
Traffic Congestion (car km equiv.) per 1000 car km equivalents 86
Traffic Noise (car km equiv.) per 1000 car km equivalents 3
Water Quality Eutrophication (Pequiv.)
/kg P 4,7
Disaminity (kg LF waste equiv.) /kg waste in landfill 0,037
The economic valuations applied in this study are principally based on damage cost
estimates, derived from hedonic pricing methods or willingness-to-pay studies. A
detailed summary of the sources and derivation of these economic valuations is
provided in Annex 4: Economic valuations applied – sources and derivation.
3.3.3.1 Recycling case studies
Example: Calculation of externalities for PET bottles scenarios
See chapter 4.2.1.3
3.3.3.2 Reuse case studies
The externalities are determined for the base case, and investigated as a function of
the reuse rate and collection distance.
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3.3.4 Model gross employment created by each system
The EU has a special obligation to consider employment aspects in the development
of policies under the Treaty of Amsterdam.
However, in neo-classical economics, no social cost is associated with
unemployment. It is assumed that the economy is effectively fully employed. The
labour market is fully flexible and unemployed labour will find employment
elsewhere in the economy. Any unemployment is the result of transitional periods.
The terms of labour employment contracts and the terms of unemployment benefits
will reflect the presence of such periods. There will be no cost to society from the
existence of a pool of transitionally unemployed workers. Therefore, CBA of
environmental policies often deliberately excludes the direct and indirect employment
effects.
However, market conditions are not perfect. Some Member States experience
unemployment that is not due to a short-term transition in supply and demand of
labour and skills, but due to a medium or long-term lack of employment
opportunities. This unemployment has costs that should be considered. These costs
include the economic burden of unemployment benefit, and the social welfare (health
and well being) of the unemployed individuals and their family. Therefore a
consideration of the costs and benefits of employment generated by some policies
may be important.
However, quantifying the net employment created by recycling is not an easy task.
Recycling will undoubtedly generate new employment in collection, sorting and
reprocessing activities. Other jobs may be lost (in virgin material extraction and
processing and MSW management) although obviously less due to the scale of the
activities and the high automation value of the virgin material production systems. It
needs to be underlined that a full evaluation of the employment effect of a policy
measure can only be made after consideration of macroeconomic effects (e.g.
crowding out effects). This is beyond the scope of this study. Even where this
information could be derived, difficulties exist in determining an acceptable economic
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valuation for each job created, especially considering the variable quality of
employment in this sector7.
In this study, an attempt has been made to determine the employment created. Only
the gross jobs of each scenario are quantified. The gross jobs are those involved in
the collection and subsequent waste management processes (i.e. landfill & incinerator
operation, sorting and reprocessing). The base data used to determine the gross jobs
per scenario is presented in Annex 5: Employment data –jobs for waste
management activities. This data has been sourced from Beture, interviews of
compliance schemes and visits of recycling plants.
No economic valuation has been applied to the gross jobs in the base case. But the
effect of economic valuation of net job creation on the cost-benefit balances has been
tested in the sensitivity analysis. The information is considered cautiously in the
interpretation of the results.
3.3.4.1 Recycling case studies
Example: Calculation of gross employment for PET bottles scenarios
See chapter 4.2.1.4
7 for more detailed information see: “Employment effects of waste managementpolicies”, RPA for the European Commission, forthcoming in 2001
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3.3.4.2 Reuse case studies
Only the gross jobs created by collection are considered.
3.3.5 Compile total social costs of each scenario
3.3.5.1 Recycling case studies
For each scenario, the total social cost is determined. The total social cost considered
is the sum of the internal costs to industry and the total externality.
Example: Total social costs by scenario for PET bottles
See chapter 4.2.1.5
3.3.5.2 Reuse case studies
The total social cost is determined as a function of reuse rate and distance for
collection.
3.3.6 Uncertainty / Sensitivity analysis of the CBA results
For each of the scenarios modelled, the main parameters that may affect the results
are investigated. Two types of parameters are considered:
♦ Uncertainties arising from methodological choices, including but not limited to:
♦ Energy model assumed
♦ Offset energy production from incineration (average or marginal)
♦ Valuations applied to externalities (a list of alternative economic valuations
that may be applied is given in Annex 4: Economic valuations applied –
sources and derivation)
♦ Uncertainties arising from scenario choices, including but not limited to:
♦ Distances for kerbside collection rounds and bring schemes
♦ Transport distances for delivery of sorted material to reprocessors
♦ Offset virgin production and save ratio
♦ Type of energy recovery from incineration and landfill (CH&P instead of
power)
♦ Alternative recovery options
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♦ Data used and data gaps
Example: Uncertainty and sensitivity analysis for PET bottle case study
See chapters 4.2.1.7 and 4.2.1.8
3.3.7 Interpretation
3.3.7.1 Recycling case studies
For each case study, the results are presented as ranges for the following:
♦ total external costs
♦ total internal costs
♦ total social costs (sum of external and internal costs)
The key parameters influencing the results are presented, and the limitations this may
place on conclusions that can be drawn are discussed.
Example: Interpretation of results for PET bottles case study
See chapter 4.2.1.6 and 4.2.1.9
3.3.7.2 Reuse case studies
For the reuse case studies, the results are considered in light of the influence of reuse
rate and distance for collection.
3.4 Application of the CBA results to determine optimal recycling targets(step 4)
The aim of this step is to show how the results of the CBA case studies may be
applied to determine possible recycling targets.
A combination of factors will determine the ability of a Member State to meet a
specific recycling target. The following factors are considered in this analysis to
determine recycling targets:
♦ the packaging mix of the Member State
♦ the proportion of population living in high and low population density areas in
the Member State
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♦ the proportion of landfill and incineration with energy recovery available in
the Member State
♦ the proportion of companies producing small and large quantities of packaging
waste (for commercial and industrial packaging applications only)
These factors are quantified for each Member State, so as to allow targets to be
determined at a number of levels:
♦ aggregated global targets
♦ Member State specific targets
♦ material specific targets
The process of applying the CBA results to determine the recycling targets is
illustrated by the sub-steps shown in Figure 6:
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Figure 6 : Application of CBA results to determine possible recycling targets
3.4.1 Determine optimal recycling rate by application
For each household packaging application, the optimal recycling rate is determined
for each of the following combinations of parameters:
2.4.3: Determine optimal recycling rateby application for:• high population density, landfill
MSW• high population density, incineration
MSW
low population density, landfill
2.4.5: Determine optimalrecycling target perapplication for each MS
2.4.4: DetermineMS characteristics
2.4.7: Determine optimalrecycling target per MS
2.4.6: Determine totalpackaging mix byapplication for each MS
2.4.8: Determine globaloptimum recycling rate forthe European Union
2.4.9: Sensitivity Analysis
2.4.1: Determine collection system withthe lowest social cost by application for:• high population density, landfill
MSW• high population density, incineration
MSW
low population density, landfill
2.4.2: Determineachievable recycling ratewith the collection systemhaving the lowest socialcost
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♦ High population density, with landfill as the alternative waste management
option
♦ High population density, with incineration as the alternative waste
management option
♦ Low population density, with landfill as the alternative waste management
option
♦ Low population density, with incineration as the alternative waste
management option
For each combination of parameters, the “optimal” recycling rate is considered to be
the recycling rate achievable by the scenario modelled with the lowest total social
cost.
Example: Determination of optimal recycling rate for PET bottles in function of the
MS characteristics
See chapters 4.2.1.5 & 4.2.1.6
For each (group of) industrial packaging application(s), the industrial companies are
classified according to the amount of packaging waste they produce. The internal and
external costs and benefits are calculated for 3 systems :
• selective collection and recycling
• no selective collection and incineration
• no selective collection and landfill
The internal costs of the selective collection are considered as a function of the
amount of packaging waste of the concerned material (cost of selective collection
decreases when the amount of waste increases). The amount of packaging waste for
which the total social cost of the selective collection system is equal to the total social
cost of the (cheapest among the 2) non-selective collection system(s) is the break-
even amount.
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• Selective collection within companies which produce a “small” (i.e. smaller than
the break-even) amount of packaging waste is considered not beneficial8 and
therefore the optimum recycling rate is 0%.
• Selective collection within companies which produce a “high” (i.e. more than the
break-even) amount of packaging waste is considered beneficial and therefore
should be applied. The optimum recycling rate is considered to be the recycling
rate achievable with the selective collection.
The “optimum” recycling rate for the industrial packaging application is then equal to
:
Percentage of the packaging waste arising in companies which produce a “high”
amount of packaging waste multiplied by the recycling rate achievable in companies
who do make selective collection.
The 3 key stages of the work are :
• the determination of the break-even amount of packaging waste
• the determination of the fraction of the industrial packaging waste arising from
the companies producing larger amount than the break-even amount and
• the determination of the recycling rate achieved when there is a selective
collection
The optimum recycling rate is calculated according to 2 approaches :
Ø cost-benefit analysis : the break-even amount is the one for which the additional
cost due to the selective collection equals the (environmental and job creation)
benefits. An assumption needs further to be made on the fraction of the packaging
waste arising from large packaging waste production sites
Ø market approach : for Member States where the incineration/landfill tax is about
the same level as the (external) benefits of the selective collection, the external
benefits are considered as fully internalised. Therefore, assuming the market is
8 i.e. the total social cost of selective collection + recycling is higher than the total
social cost of non selective waste collection + incineration or landfill. ie theadditional internal cost for selective collection exceeds the additional externalbenefits from recycling
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efficient, the current recycling rate is the optimum one. This second approach is
used to check and calibrate the first model.
3.4.2 Determine Member State Characteristics
For each Member State the following characteristics are determined:
♦ Population mix by density and alternative waste management option
This data is applied in the calculation of the optimal recycling target for household
packaging applications.
The population of each Member State is classified into 4 categories:
♦ High population density (> 200 inhabitants/km2) served by landfill
♦ High population density (> 200 inhabitants/km2) served by incineration
♦ Low population density (< 200 inhabitants/km2) served by landfill
♦ Low population density (< 200 inhabitants/km2) served by incineration
To achieve this, the % of the population living in high and low population density
areas is determined for each Member State, based on data available at I-Mage
(Belgian consulting company working for the EC) and checked by local consulting
companies9. The proportion of the population living in high and low population
density areas is shown in Table 9.
Table 9 :Population density distribution by Member State (estimation for 2000)
Population density AUT B DK FIN F D GK IRL I L NL P SP SE UK
Low density % pop 47% 14% 66% 58% 34% 26% 41% 50% 28% 34% 13% 40% 55% 73% 16%
High density % pop 53% 86% 34% 42% 66% 74% 59% 50% 72% 66% 87% 60% 45% 27% 84%
The percentage of municipal solid waste sent to landfill or incineration with energy
recovery in each Member State was determined by local consulting companies. The
distribution is determined based on data and forecasts for 2000. Otherwise data
9 A network of consulting company specialised in environmental matters support thedata search and checked the local data
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related to previous years (1998-1999) are used. The proportion of landfill to
incineration is summarized in Table 10.
Table 10 :Percentage split of municipal solid waste management (estimation for2000)
Member State Waste fraction incinerated Waste fraction landfilled
Austria 30% 70%
Belgium 50% 50%
Denmark 100% 0%
Finland 5% 95%
France 47% 53%
Germany 40% 60%
Greece 0% 100%
Ireland 3% 97%
Italy 8% 92%
Luxembourg 70% 30%
The Netherlands 50% 50%
Portugal 9% 91%
Spain 7% 93%
Sweden 65% 35%
United Kingdom 7% 93%
Sources :
• Eco-Emballages 1999• Interviews of stakeholders 2000• Network of consultants.
Subsequently, the population is classified according to both the population mix and
the national MSW treat option. The results of this are presented in Table 11.
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Table 11 : Population mix as a function of density and national MSWtreatment (estimation for 2000)
PopDensity
MSWsystem
AUT B DK FIN F D GR IRL I L NL P SP SE UK
Landfill 47% 7% 0% 58% 22% 16% 41% 49% 26% 10% 6% 36% 51% 26% 15%Low
Incin. 0% 7% 66% 0% 8% 10% 0% 2% 2% 24% 6% 4% 4% 47% 1%
Landfill 37% 43% 0% 40% 32% 44% 59% 48% 66% 20% 44% 55% 42% 9% 78%High
Incin. 16% 43% 34% 2% 39% 30% 0% 1% 6% 46% 44% 5% 3% 18% 6%
It should be noted that this allocation assumes that the proportion of landfill to
incineration is the same in high and low population density areas. In reality, there
may be localised variations that have been addressed in this study as far as data were
available (e.g. for Austria, France, Finland).
The situation in 2006 is considered in the sensitivity analysis.
3.4.3 Determine total packaging mix by application for each Member State
It is assumed that the optimal recycling rate in a Member State is a function of the
packaging mix in that Member State, as some packaging materials/applications will
be easier to recycle than others. Therefore the packaging mix in each Member State
must be determined in order to calculate the Member State’s optimal recycling target.
In this analysis, the packaging mix for 2000 is considered as the baseline. No forecast
for the year 2005 is considered, though the effect of changes in the packaging mix on
the optimal recycling rates are investigated in the sensitivity analysis.
In this analysis, data on the Member State packaging mix has been derived from a
number of sources:
♦ Data provided by the national compliance schemes
♦ Member State’s official declarations
♦ Additional input from local consultants where possible
The detailed packaging mix of each Member State as determined for this analysis is
given in Annex 6: Packaging mix by Member State.
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3.4.4 Determine optimal recycling target per application for each Member State
The optimal recycling rate per application for each Member State is calculated by
combining the optimum recycling rate per application with the Member State
characteristics.
Example: PET bottles optimal recycling rate
EU PET packaging amount 1 501 kt
landfill Inc. landfill Inc.27% 12% 41% 20%
70% 35% 59% 59% 887 59%80% 80% 69% 69% 1 101 73%
amount to berecycled
Target range
Min targets
Max target
Achievable recycling rates
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
In the above table the minimum target (i.e. minimum achievable recycling rate when
the collection systems with the lowest total social cost are applied) is 59%, i.e. 887
kt/1501 kt or 59% = (27%*70%) + (12%*35%) + (41%*59%) + (20%*59%).
3.4.5 Determine the optimal recycling rate for each Member State
By combining the optimal recycling rate for each packaging material/application by
Member State with the packaging mix by Member State, the overall recycling target
for that Member State is determined. The overall recycling targeted is a weighted
average of the individual packaging material/application targets.
3.4.6 Determine global packaging recycling for the whole EU
The optimal recycling rate of all packaging waste for the whole EU is the weighted
average of the optimal recycling rates of the individual Member States. The
weighting factor is the annual amount of packaging waste.
3.4.7 Sensitivity analysis
The sensitivity of the recycling targets to changes in the packaging mix is
investigated. Forecast for packaging mix in 2006 was investigated. Optimum
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recycling ranges per application were applied to this new packaging mix, in order to
determine the influence of the packaging mix on the global results.
3.5 Recommendations and Conclusions (step 5)
Based on the results of the analysis, the consultants make conclusions and
recommendations on:
♦ The existing recycling and recovery rates achieved by the Member States
♦ The possible options for implementing higher recycling targets
♦ The possible range of the recycling targets
♦ The key factors that influence the costs and benefits of reuse
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4 RESULTS
4.1 Evaluation of the current situation
4.1.1 Current performance of Member States
As explained in the description of the methodology (see chapter 3.1.1) the current
performances of the Member States were investigated.
The methodology and the problems encountered are described in Annex 8: Current
performance of Member States.
Data of 1999 are presented in Table 12. Data for 1997 and 1998 are presented in
annex 8 bis.
The main conclusions are:
v Most data were found for 1997 and 1998
v Exact data on the amount of waste, packaging waste and recycling are hard to get;
v Data on the amount of waste, packaging waste and recycling are not comparable;
v More reliable data are/will be available for 1998 and especially 1999 thanks to the
larger experience and the improvement of the calculation methods.
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Table 12 : Performance of the Member States in 1997
Total HH + industrialMaterial Glass Plastic Paper and
boardMetals Al Steel composite
sWood Other Total
Application
1997Waste
AUT 260 180 666 85 28 50 1269BE 310 208 530 121 17 142 29 1356DK 202 183 463 58 61 4 971FI 52 90 244 31 417FR 3296 1571 3611 622 290 1679 11069DE 3750 1502 5448 1121 87 1034 1892 17 13731GK 1456IE 452IT 2248 1777 3246 487 1802 9560LU 17 7 11 3 1 1 80NL 469 611 1449 216 0 2745PO 1050SP 1398 1215 2255 340 671 5879SE 177 150 527 70 924UK 1787 1356 3035 809 112 697 749 18 7755EURecycled
AUT 199 36 500 29 8 7 779BE 217 53 411 85 5 75 846DK 124 11 219 2 357FI 24 9 136 2 171FR 1388 102 2276 331 300 4397DE 2797 675 3193 915 1040 8621GK 180
IE 80IT 750 164 1170 25 700 2809LU
NL 354 76 941 145 1516PO 32SP 522 65 1242 76 60 1966SE 134 21 348 32 535UK 441 100 1609 211 27 184 2361EULegend:
data EC -MS reports 1997data report PWC review data MS 1997data valorlux : chiffres cléfs only HHdata PWC The facts a European cost/benefit analysis 1998
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4.1.2 Critical factors limiting recycling and reuse
The critical factors identified in this section are taken into account in the calculations
and the hypothesis taken for packaging applications when no CBA is performed.
Recycling difficulties can be classified according to technical, economic and
marketing constraints. Marketing constraints can be avoided by specific marketing
actions: they mainly depend on the willingness of the industries.
On the other hand technical and economical constraints are more difficult – or
impossible up to now - to overcome. Technical constraints require R&D investments
or increase of collecting, sorting and/or treatment capacities. Economic constraints are
very difficult to control: e.g.: market prices, internal market barriers.
In Annex 9: Critical factors limiting recycling and reuse, the different material are
investigated.
Table 13 shows the identified recycling constraints per material. They are classified in
factors which are reasonable reasons to limit recycling and factors which may be valid
points but are not really a reason to limit recycling.
Table 13 : Summary of the recycling difficulties
Recycling difficulties Glass Plastics Paper/board Metals CompositesCapacity X (X)Output market / market price X Xcontamination X X X (X)imbalance supply-demand X XInsufficient amount of waste X (X) XRecycling lifetime XNature of waste (too thin,…) X X XRecycling costs X
Factors which are not really a reason to limit recycling Noise XHuman wound XInsufficient maintenance XDisposers participation X X X X XColour, odour XResistance to the use of recyclate X
The critical factors identified in this section are taken into account in the calculations
and the hypothesis taken for packaging applications when no CBA is performed.
For reuse processes, as for recycling, it is possible to distinguish between technical
and economical constraints. The third kind of constraints concern consumer
convenience.
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These constraints are discussed in Annex 9: Critical factors limiting recycling and
reuse.
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4.2 Results of Case study CBAs
In this section, the full set of calculations and results for PET beverage bottles are
explained, including a detailed presentation of the sensitivity analysis. For other
cases studies, only the main results and conclusions and the implications of the
sensitivity analysis are presented.
4.2.1 PET bottles from household sources
4.2.1.1 Scenarios considered
Table 14 summarises the parameters considered for the baseline scenarios modelled.
Table 14 : Scenarios considered for PET beverage bottles
Population density
Selective collection scheme
Recycling rate achieved
MSW Waste management option
Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low Separate kerbside collection 70-80% LandfillScenario 4 Low Separate kerbside collection 70-80% IncinerationScenario 5 Low Bring scheme 35-45% LandfillScenario 6 Low Bring scheme 35-45% IncinerationScenario 7 High None 0% LandfillScenario 8 High None 0% IncinerationScenario 9 High Separate kerbside collection 59-69% LandfillScenario 10 High Separate kerbside collection 59-69% IncinerationScenario 11 High Bring scheme 22-32% LandfillScenario 12 High Bring scheme 22-32% Incineration
4.2.1.2 Calculation of internal costs
The internal costs of each possible waste management option are calculated. To
achieve this, a number of allocations are applied:
♦ Allocation of MSW collection costs proportionally to the compressed density in
the collection truck
♦ Allocation of sorting costs proportionally to the density
♦ Allocation of fixed incineration costs proportionally to calorific value, necessary
combustion air (mainly), ash content, steel content, Al content, depending on the
part of the facilities
Allocation of variable incineration costs proportionally to variable parameters
(a.o. necessary combustion air, ash content, steel content, Al content)
For further details about incineration costs, see Annex 2: Incineration and
landfill models.
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♦ Allocation of landfill costs proportionally to the crushed waste density in landfill
Costs for Landfilling 1 tonne PET bottles
Collection costs (Euro pertonne of PET bottles)
Landfill costs (Euro pertonne of PET bottles)
Total internal costsper tonne PET bottles
High populationdensity
294 140 434
Low populationdensity
228 140 368
Costs for Incineration of 1 tonne PET bottles
Collection costs(Euro per tonneof PET bottles)
Incineration –fixed costs (Europer tonne of PETbottles)
Incineration –variable costs(Euro per tonneof PET bottles)
Total internalcosts per tonnePET bottles
High populationdensity
294 161 -63 392
Low populationdensity
228 161 -63 326
Costs for Recycling 1 tonne of PET bottles via separate kerbside collection
Collection
costs (Euro
per tonne of
PET bottles
recycled)
Sorting costs
(Euro per
tonne of
PET bottles
recycled)
Transport from
sorting plant to
reprocessor
(Euro per tonne
of PET bottles
recycled)
Reprocessing
cost (Euro per
tonne of
output)
Revenue
received for
reprocessed
material
Total internal
cost per tonne
PET bottles
recycled
High
population
density
255 474 46 332 -540 566
Low
population
density
306 474 46 332 -540 618
Costs for Recycling 1 tonne PET bottles via bring bank collection
Transport costs
from bring
bank to sorting
plant (Euro per
tonne of PET
bottles
recycled)
Sorting costs
(Euro per
tonne of
PET bottles
recycled)
Transport from
sorting plant to
reprocessor
(Euro per tonne
of PET bottles
recycled)
Reprocessing
cost (Euro per
tonne of
output)
Revenue
received for
reprocessed
material
Total internal
cost per tonne
PET bottles
recycled
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High
population
density
196 474 46 332 -540 508
Low
population
density
242 474 46 332 -540 553
The costs per tonne for each waste treatment option are combined to give the cost per
tonne for each scenario modelled. For example, Scenario 3 considers low population
density, in which 70-80% of the PET bottles are recycled via separate kerbside
collection, with the remaining 20-30% going to landfill. Thus, the cost per tonne for
Scenario 3 can be calculated:
Scenario 3 cost per tonne = (0.7 * 618) + (0.3 * 368) to (0.8 * 618) + (0.2 * 368)
= 542 – 567 Euro per tonne
4.2.1.3 Calculation of externalities
The environmental models for each option were constructed using Pira International’s
LCI/LCIA software PEMS. The life cycle inventory is then compiled.
The environmental impacts associated with the inventory data set are then calculated.
To achieve this, the inventory data are characterised according to the potential impact
categories that they contribute to, and then multiplied by classification values.
Finally, the impact assessment data is multiplied by the economic valuations (as listed
in Annex 4: Economic valuations applied – sources and derivation) to achieve the
external cost of each impact category.
For example, if we consider only the global warming impact category, the following
results are achieved for PET bottles scenario 3:
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Table 15 : Calculation of GWP externality for 1 tonne PET bottles to landfill,low population density
Classification factor
Economic valuation (Euro per kg CO2 Equiv)
carbon tetrachloride 0,0 to 0,0 -225 0,0 to 0,0CFC (unspecified) 0,0 to 0,0 1320 0,0 to 0,0CFC-11 0,0 to 0,0 1320 0,0 to 0,0CO2 (non renewable) -1479,4 to -1693,9 1 -1479,4 to -1693,9CO2 (renewable) 0,0 to 0,0 1 0,0 to 0,0CO2 (unspecified) 34,5 to 38,5 1 34,5 to 38,5dichloromethane 0,0 to 0,0 9 0,0 to 0,0haloginated HC (unspecified) 0,0 to 0,0 4 0,0 to 0,0halon -1301 0,0 to 0,0 -49750 -0,5 to -0,5halons (unspecified) 0,0 to 0,0 -49750 0,0 to 0,0HCFC (unspecified) 0,0 to 0,0 1350 0,0 to 0,0HCFC-22 0,0 to 0,0 1350 0,0 to 0,0hexafluoroethane 0,0 to 0,0 9200 0,0 to 0,0HFC (unspecified) 0,0 to 0,0 1000 0,0 to 0,0methane 0,2 to 0,2 21 4,5 to 5,0N2O 0,0 to 0,0 310 4,0 to 4,5tetrafluoromethane 0,0 to 0,0 6500 0,0 to 0,1tetrafluroethylene 0,0 to 0,0 1300 0,0 to 0,0trichloroethane 0,0 to 0,0 -1525 0,0 to 0,0trichloromethane 0,0 to 0,0 4 0,0 to 0,0
-1436,8 -1646,4 0,01344 -19,3112 to -22,127
Results of characterisation (CO2 Equiv.) Externality (Euros)
Emissions (kg of emission per tonne PET
landfilled)Inventory data
For each scenario, the external cost of all impact categories is summed to determine
the total external cost. The total external cost for PET bottles scenario 3 are presented
in Table 16
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Table 16 : Total externalities for PET bottles, Scenario 3
ExternalitiesGWP (kg CO2 eq.) -19,3 to -22,1
Ozone depletion (kg CFC 11 eq.) 0,0 to 0,0Acidification (Acid equiv.) -6,9 to -7,9
Toxicity Carcinogens (Cd equiv) 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) -24,8 to -28,4
Toxicity Metals non carcinogens (Pb equiv.) -5,4 to -6,2Toxicity Particulates & aerosols (PM10 equiv) -164,9 to -189,8
Toxicity Smog (ethylene equiv.) -35,7 to -40,9Black smoke (kg dust eq.) -16,5 to -18,9
Fertilisation 9,2 to 10,5Traffic accidents (risk equiv.) 0,9 to 1,0
Traffic Congestion (car km equiv.) 5,0 to 5,7Traffic Noise (car km equiv.) 2,8 to 3,1
Water Quality Eutrophication (P equiv.) -0,8 to -0,9Disaminity (kg LF waste equiv.) 11,1 to 7,4
TOTAL EXTERNALITIES -245,5 to -287,4
Euro per tonne
4.2.1.4 Calculation of Employment
The gross employment is determined for each waste management option. This is
presented in the tables below.
Gross Employment, landfilling of PET bottles (jobs per 1000 tonne per annum)
Collection Landfill management / operation TotalHigh population density 1.2 0.1 1.3Low population density 1.15 0.1 1.25
Gross Employment , incineration of PET bottles (jobs per 1000 tonne per annum)
Collection Incinerator management / operation TotalHigh population density 1.2 0.27 1.47Low population density 1.15 0.27 1.42
Gross Employment , kerbside collection and sorting of PET bottles
Jobs per 1000 tonne perannum
Collection Sorting Transport from sorting toreprocessing
Total
High population density 14.7 0.71 0.19 15.6Low population density 17.7 0.71 0.19 18.6
Gross Employment , bring scheme collection and sorting of PET bottles
Jobs per 1000 tonneper annum
Transport, bring bankto sorting
Sorting Transport fromsorting to
reprocessing
Total
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High populationdensity
3.2 0.71 0.19 4.1
Low populationdensity
3.8 0.71 0.19 4.7
The total gross jobs for each scenario modelled can then be calculated. For example,
Scenario 3 considers low population density, in which 70-80% of the PET bottles are
recycled via separate kerbside collection, with the remaining 20-30% going to
landfill. Thus, the gross employment per tonne for Scenario 3 can be calculated :
Scenario 3 jobs per 1000 tonne = (0.7 * 18.6) + (0.3 * 1.25) to (0.8 * 18.6) + (0.2 *
1.25)
= 13.4 – 15.13 jobs per 1000 tonne per annum (or 14.27
jobs per 1000 tonne per annum if the median is
considered).
The external economic value for these jobs is then calculated by applying the
economic valuation for employment (2945 Euro per job per annum, as described in
Annex 4: Economic valuations applied – sources and derivation). Thus, for
Scenario 3 the external economic value is 14.27/1000*2495 = 42.01 Euro per tonne of
waste PET bottles.
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4.2.1.5 Compile total social costs - Results of the cost benefit analysis
Table 17 : Internal costs, external costs and total social costs (low pop. density)
Graph 1 : Total social costs (low population density)
PET bottles - Low Population DensityTotal Social Cost
0
50
100
150
200
250
300
350
400
450
Landfill Separatekerbside
collection / landfill
Bring scheme /landfill
Incineration Separatekerbside
collection /incineration
Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
/ Eu
ro p
er t
on
ne
Collection method N/A N/ARecycling rate 0,0 0,0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 0,4 19,2 -19,3 to -22,1 -13,7 to -18,4 -9,5 to -12,3 2,8 toOzone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to
Acidification (Acid equiv.) 0,0 -1,2 -6,9 to -7,9 -7,3 to -8,1 -3,4 to -4,4 -4,2 toToxicity Carcinogens (Cd equiv) 0,0 -0,1 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 toToxicity Gaseous (SO2 equiv.) 0,1 -4,1 -24,8 to -28,4 -26,1 to -29,3 -12,0 to -15,4 -14,7 to -1
Toxicity Metals non carcinogens (Pb equiv.) 0,1 -0,5 -5,4 to -6,2 -5,6 to -6,3 -2,6 to -3,4 -3,0 toToxicity Particulates & aerosols (PM10 equiv) 9,6 -44,6 -164,9 to -189,8 -181,2 to -200,7 -83,4 to -110,0 -118,6 to -13
Toxicity Smog (ethylene equiv.) 0,3 -0,8 -35,7 to -40,9 -36,1 to -41,1 -17,7 to -22,9 -18,4 to -2Black smoke (kg dust eq.) 0,2 -3,9 -16,5 to -18,9 -17,8 to -19,7 -8,1 to -10,5 -10,8 to -1
Fertilisation -0,1 0,4 9,2 to 10,5 9,4 to 10,6 4,5 to 5,9 4,9 toTraffic accidents (risk equiv.) 0,1 0,1 0,9 to 1,0 0,9 to 1,0 2,4 to 3,0 2,4 to
Traffic Congestion (car km equiv.) 0,1 0,1 5,0 to 5,7 5,0 to 5,7 2,6 to 3,3 2,6 toTraffic Noise (car km equiv.) 0,4 0,4 2,8 to 3,1 2,8 to 3,1 1,3 to 1,5 1,3 to
Water Quality Eutrophication (P equiv.) 0,0 -0,1 -0,8 to -0,9 -0,8 to -0,9 -0,4 to -0,5 -0,4 toDisaminity (kg LF waste equiv.) 37,0 12,0 11,1 to 7,4 3,6 to 2,4 24,1 to 20,4 7,8 to
TOTAL EXTERNALITIES 48,2 -22,9 -245,5 to -287,4 -266,8 to -301,6 -102,3 to -145,3 -148,5 to -18INTERNAL COSTS 368,0 326,0 542,3 to 567,2 529,7 to 558,8 432,8 to 451,3 405,5 to 42TOTAL SOCIAL COSTS 416,2 303,1 296,8 to 279,8 262,9 to 257,2 330,5 to 306,0 256,9 to 24
Bring scheme35-45%Landfill
Separate kerbside
collection70-80%
Incineration
Bring scheme35-45%
Incineration
Separate Kerbside collection
70-80%Landfill
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Table 18 : Internal costs, external costs and total social costs (high pop. density)
Collection method N/A N/ARecycling rate 0,0 0,0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 0,3 19,1 -15,9 to -18,7 -8,2 to -12,8 -6,2 to -9,1 8,5 to 3,7Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0
Acidification (Acid equiv.) 0,0 -1,2 -5,5 to -6,4 -6,0 to -6,8 -2,2 to -3,1 -3,1 to -4,0Toxicity Carcinogens (Cd equiv) 0,0 -0,1 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) 0,1 -4,1 -19,8 to -23,2 -21,5 to -24,5 -7,7 to -11,2 -11,0 to -14,1
Toxicity Metals non carcinogens (Pb equiv.) 0,1 -0,5 -4,3 to -5,1 -4,5 to -5,2 -1,6 to -2,4 -2,1 to -2,8Toxicity Particulates & aerosols (PM10 equiv) 8,3 -45,9 -136,3 to -160,8 -158,5 to -177,6 -52,6 to -80,2 -94,8 to -117,1
Toxicity Smog (ethylene equiv.) 0,2 -0,9 -28,7 to -33,6 -29,1 to -33,9 -11,2 to -16,4 -12,1 to -17,2Black smoke (kg dust eq.) 0,2 -3,9 -13,2 to -15,5 -14,9 to -16,8 -5,1 to -7,5 -8,3 to -10,3
Fertilisation -0,1 0,5 7,4 to 8,7 7,7 to 8,9 2,9 to 4,3 3,3 to 4,6Traffic accidents (risk equiv.) 0,2 0,2 1,0 to 1,1 1,0 to 1,1 0,8 to 1,1 0,8 to 1,1
Traffic Congestion (car km equiv.) 8,2 8,2 44,4 to 50,5 44,4 to 50,5 25,4 to 33,3 25,5 to 33,3Traffic Noise (car km equiv.) 0,2 0,2 1,1 to 1,3 1,1 to 1,3 0,4 to 0,6 0,4 to 0,6
Water Quality Eutrophication (P equiv.) 0,0 -0,1 -0,6 to -0,7 -0,7 to -0,7 -0,2 to -0,4 -0,3 to -0,4Disaminity (kg LF waste equiv.) 37,0 12,0 15,2 to 11,5 4,9 to 3,7 28,9 to 25,2 9,4 to 8,2
TOTAL EXTERNALITIES 54,6 -16,5 -155,3 to -190,9 -184,4 to -212,9 -28,4 to -66,1 -83,8 to -114,4INTERNAL COSTS 434,0 392,0 511,9 to 525,1 494,7 to 512,1 450,3 to 457,7 417,5 to 429,1TOTAL SOCIAL COSTS 488,6 375,5 356,6 to 334,2 310,2 to 299,2 421,9 to 391,6 333,7 to 314,7
Separate Kerbside collection
Separate kerbside collection Bring scheme Bring scheme
59-69% 59-69% 22-32% 22-32%Landfill Incineration Landfill Incineration
Graph 2 : Total social costs (high population density)
PET bottles - High Population DensityTotal Social Cost
0
100
200
300
400
500
600
Landfill Separate kerbsidecollection / landfill
Bring scheme /landfill
Incineration Separate kerbsidecollection /incineration
Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
/ E
uro
pet
to
nn
e
4.2.1.6 Initial conclusions
For low population density, where landfill is the MSW treatment option the main
conclusions are:
♦ Landfilling is the preferred option from an internal cost perspective
♦ When total social costs are considered separate kerbside collection achieving a
recycling rate of 70-80% is the optimal solution of the options considered. This is
due to the environmental credit achieved by avoided production of virgin bottle
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grade PET. The main benefit is associated with avoided emissions of particulates
and aerosols.
For low population density, where incineration is the MSW treatment option the main
conclusions are:
♦ Incineration is the preferred option from an internal cost perspective
♦ When total social costs are considered a bring scheme achieving a recycling rate
of 35-45% is the optimal solution of the options considered. This is due to the
environmental credit achieved by avoided production of virgin bottle grade PET.
The main benefit is associated with avoided emissions of particulates and
aerosols.
For high population density, where landfill is the MSW treatment option the main
conclusions are:
♦ Landfilling is the preferred option from an internal cost perspective
♦ When total social costs are considered separate kerbside collection achieving a
recycling rate of 59-69% is the optimal solution of the options considered. This is
due to the environmental credit achieved by avoided production of virgin bottle
grade PET. The main benefit is associated with avoided emissions of particulates
and aerosols.
For high population density, where incineration is the MSW treatment option the
main conclusions are:
♦ Incineration is the preferred option from an internal cost perspective
♦ When total social costs are considered a separate kerbside collection achieving a
recycling rate of 59-69% is the optimal solution of the options considered. This is
due to the environmental credit achieved by avoided production of virgin bottle
grade PET. The main benefit is associated with avoided emissions of particulates
and aerosols.
4.2.1.7 Sensitivity analysis: Methodological choices
Choice of external valuation values
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Graph 3 and Graph 4 show the sensitivity of the analysis to the economic valuations
applied to the defined environmental impacts. The graph has been produced by
considering the same environmental impact results, but applying different impact
assessment valuations (see Annex 4: Economic valuations applied – sources and
derivation for a list of maximum and minimum valuations applied). The results of
the analysis and conclusions that can be drawn are extremely dependent on the
economic valuations applied. Applying the full range of available economic
valuations makes it impossible to make a clear and reliable distinction between any of
the waste management scenarios investigated.
Graph 3 : Sensitivity of the results to the external economic valuations applied -Low population density
PET bottles - Low Population DensitySensitivity analysis on variations in economic valuations
applied
-3500.0-3000.0-2500.0-2000.0-1500.0-1000.0
-500.0
0.0500.0
1000.0
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
/ E
uro
per
to
nn
e
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Graph 4 : Sensitivity of the results to the external economic valuations applied- High population density
PET bottles - High Population DensitySensitivity analysis on variations in economic valuations
applied
-3000.0
-2500.0
-2000.0
-1500.0
-1000.0
-500.0
0.0
500.0
1000.0
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
/ E
uro
per
to
nn
e
Internal costs
The internal costs applied in this study have been sourced mostly from the UK,
France and Belgium. Even where equivalent waste management practices are
compared internal costs can vary considerably between Member States, depending on
a range of factors such as cost of living and geographical considerations (mountainous
regions, islands, etc). In this part of the sensitivity analysis, the effect on the results
of considering a +/-20% variation in internal costs is investigated. The results are
presented in Graph 5 and Graph 6.
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Graph 5 : Sensitivity of the results to the internal economic costs considered -Low population density
PET bottles - Low Population DensitySensitivity analysis on variations in Internal Costs
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separatekerbside
collection / landfill
Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
To
tal s
oci
al c
ost
s / E
uro
per
to
nn
e
Graph 6 : Sensitivity of the results to the internal economic costs considered -High population density
PET bottles - High Population DensitySensitivity analysis on variations in Internal Costs
0.0
100.0
200.0
300.0
400.0
500.0
600.0
700.0
Landfill Incineration Separatekerbside
collection / landfill
Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
To
tal s
oci
al c
ost
/ E
uro
per
to
nn
e
The graphs show that the conclusions that can be drawn from the analysis are highly
dependent upon the internal cost assumptions made.
Inclusion of employment as an impact category
In Graph 7 and Graph 8, employment has been added as an external impact category.
The graphs show that for low population density where incineration is the alternative
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MSW option the scenario incorporating separate kerbside collection now becomes the
optimal system for the scenario considered.
Graph 7 : Addition of employment as an impact category - low pop. density
PET bottles - Low Population DensityTotal Social Cost
0,0
50,0
100,0
150,0
200,0
250,0
300,0
350,0
400,0
450,0
Landfill Incineration Separate kerbsidecollection / landfill
Separate kerbsidecollection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
Graph 8 : Addition of employment as an impact category - high pop. density
PET bottles - High Population DensityTotal Social Cost
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separate kerbsidecollection / landfill
Separate kerbsidecollection / incineration
Bring scheme / landfill Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
4.2.1.8 Sensitivity analysis: scenario and modelling choices
Incineration model
The baseline analysis for scenarios where incineration is the MSW option considers
that a proportion of the energy is recovered and converted to electricity. In this part
of the sensitivity analysis, the effect of considering combined heat and power is
investigated. The effect on the results for high and low population density is
presented in Graph 9 and Graph 10.
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Graph 9 : Sensitivity of the results to energy recovery assumptions
low population density
P E T b o t t l e s - L o w P o p u l a t i o n D e n s i t yS e n s i t i v i t y a n a l y s i s o n i n c i n e r a t i o n w i t h C H P
0,0
50,0
100,0
150,0
200,0
250,0
300,0
350,0
Incinerat ion Sepa ra te ke rbs i decollection / incineration
B r i n g s c h e m e /incineration
S c e n a r i o
To
tal S
oci
al C
ost
/ E
uro
per
to
nn
e
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Graph 10 : Sensitivity of the results to energy recovery assumptions
high population density
PET bottles - High Population DensitySensitivity analysis on incineration with CHP
0,0
50,0
100,0
150,0
200,0
250,0
300,0
350,0
400,0
Incineration Separate kerbside collection /incineration
Bring scheme / incineration
Scenario
To
tal S
oci
al C
ost
/ E
uro
per
to
nn
e
Although considering an efficient CHP scenario reduces the Total Social Cost of
incineration, the relative standing of the options is not affected. The results are not
sensitive to this assumption.
The baseline incineration model considers that the offset electricity from the
incineration process is undelivered average European electricity. Graph 11 and Graph
12 investigate the effect of considering a specific offset electricity production method
: coal.
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Graph 11 : Sensitivity of results to offset electricity assumption - Low pop.density
PET bottles - Low Population Density
Sensitivity analysis on offset electricity production
180.0
190.0
200.0
210.0
220.0
230.0
240.0
250.0
Incineration Separate kerbside collection /incineration
Bring scheme / incineration
Scenario
Tota
l Soc
ial C
ost /
Eur
o pe
r ton
ne
Graph 12 : Sensitivity of results to offset electricity assumption - High pop.density
PET bottles - High Population DensitySensitivity analysis on incineration with CHP
240.0
250.0
260.0
270.0
280.0
290.0
300.0
310.0
Incineration Separate kerbside collection /incineration
Bring scheme / incineration
Scenario
Tota
l Soc
ial C
ost /
Eur
o pe
r to
nne
The analysis shows that the total social cost for incineration options is significantly
reduced. For low population density, the 100% incineration scenario is now
preferable to the scenario incorporating kerbside collection, but the overall conclusion
that the bring scheme achieving a recycling rate of 35-45% is the optimal scenario
remains valid. For high population density, the bring scheme achieving a recycling
rate of 35-45% is now slightly preferable than the kerbside collection. However 100%
incineration scenario remains the worst solution.
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Transport distances
For the baseline models, the median distance was selected from a range for each
transport step. In the baseline analysis, transportation steps are relatively
uninfluential in determining the relative standing of the systems. However, in this
part of the sensitivity analysis the influence of the assumed transport distances is
investigated by compiling best case transport scenarios for landfilling and
incineration, and worst cast transport scenarios for kerbside collection and bring
schemes. The data applied are summarised in Table 19:
Table 19 : Transport distances
Transportation journey Baseline distance (kmper tonne)
Sensitivity (km pertonne)
Landfill and incineration
MSW collection, low population density 22.1 12
MSW collection, high population density 9.7 4
Separate kerbside collection
Kerbside collection round, low pop density 151.1 228
Kerbside collection round, high pop density 64.4 108
Transport from sorting plant to reprocessor 23.05 27
Bring scheme
Collection from bring bank, low pop density 83.05 124
Collection from bring bank, high pop density 27.6 37
Transport from sorting plant to reprocessor 23.05 27
The reason we made this type of analysis is that the objective is to try to find out if the
conclusions are robust. The results suggest that the scenarios incorporating recycling
are preferable. But what happens if the MSW options are better and the recycling
options worse? To find out, we reduce MSW collection round and increase separate
kerbside round, etc. This gives us best case MSW and worst case recycling for the
sensitivity analysis. If we considered the other end of the scale, (i.e. increase MSW
round, reduce recycling transport) all we would do is increase the difference between
the options.
The results are presented in Graph 13 and Graph 14.
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Graph 13 : Sensitivity of results to transport distances - Low population density
PET bottles - Low Population DensityTotal Social Cost
0.0
50.0
100.0
150.0
200.0
250.0
300.0
350.0
400.0
450.0
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
Graph 14 : Sensitivity of results to transport distances - High populationdensity
PET bottles - High Population Density
Total Social Cost
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
These graphs demonstrate that the results and conclusions drawn are not sensitive to
the transport assumptions made for MSW collection, kerbside collection round,
collection from bring banks and transport from sorting to reprocessing. It is sensitive
for high population density in case of incineration considered as MSW alternative
treatment. Bring scheme is then “better” than kerbside collection system, from a total
social cost point of view. However, this does not provide any indication of the
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sensitivity of the results to assumptions made for transport by the public to deliver
bottles to the bring bank. This is not easily tested, as no range of data for this
transport step was available, just a single value. In order to gauge whether this may
be an important parameter the assumed transport distance has been doubled – the
results of this sensitivity analysis are presented below.
Graph 15 : Sensitivity of results to consumer transport step - High pop. density
PET bottles - Low Population DensityTotal Social Cost
0.0
50.0
100.0
150.0
200.0
250.0
300.0
350.0
400.0
450.0
Landfill Incineration Separatekerbside
collection /
landfill
Separatekerbside
collection /
incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
Tota
l Soc
ial C
ost
Graph 16 : Sensitivity of results to consumer transport step - High pop. density
PET bottles - High Population DensityTotal Social Cost
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
Tota
l Soc
ial C
ost
From these graphs it can be seen that doubling distance reduces the favourability of
the bring scheme scenario in comparison with the separate kerbside system. The
relative standing of the bring scheme scenarios is not altered in comparison to 100%
landfill or 100% incineration.
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Reprocessing overseas
The baseline scenario assumes that recycling will occur within the EU (within the
country of origin of the packaging waste, or in a neighbouring Member State).
However, it is common for secondary materials to be reprocessed overseas. The
influence of this assumption is investigated in Graph 17 and Graph 18, which add an
additional ship transport step to the journey from the sorting plant to reprocessing.
Although the total social cost of scenarios incorporating recycling is increased, the
relative standing of the scenarios is unaffected.
Graph 17 : Sensitivity of results to overseas transport step - Low populationdensity
PET bottles - Low Population DensityTotal Social Cost
0.0
50.0
100.0
150.0
200.0
250.0
300.0
350.0
400.0
450.0
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
Scenario
To
tal S
oci
al C
ost
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Graph 18 : Sensitivity of results to overseas transport step - High populationdensity
PET bottles - High Population DensityTotal Social Cost
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separate
kerbsidecollection /
landfill
Separate
kerbsidecollection /
incineration
Bring scheme /
landfill
Bring scheme /
incineration
Scenario
To
tal S
oci
al C
ost
Offset virgin production
The baseline scenarios for PET recycling assume that the recyclate offsets virgin
bottle grade PET production, with a save ratio of 1:1. The offset virgin production
accounts for the credit which dominates the externalities for the recycling systems.
The effect of this assumption on the validity of the results and conclusions is
investigated in Graph 19 and Graph 20, where it is assumed that the save ratio is
reduced to 0.8:1, and a lower grade of virgin PET is offset.
Graph 19 : Sensitivity of results to virgin production credit - Low pop. density
PET bottles - Low Population DensityTotal Social Cost
0,0
50,0
100,0
150,0
200,0
250,0
300,0
350,0
400,0
450,0
Landfill Incineration Separate
kerbsidecollection / landfill
Separate
kerbsidecollection /incineration
Bring scheme /
landfill
Bring scheme /
incineration
Scenario
To
tal S
oci
al C
ost
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Graph 20 : Sensitivity of results to virgin production credit - High pop. density
PET bottles - High Population DensityTotal Social Cost
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separate
kerbside
collection /landfill
Separate
kerbside
collection /incineration
Bring scheme /
landfill
Bring scheme /
incineration
Scenario
To
tal S
oci
al C
ost
Where landfill is the alternative MSW option, there is no change in the relative
standing of the scenarios. However, where incineration is the alternative MSW
option, changing the assumptions for the offset virgin production credit could
influence the results and conclusions – in this analysis (high population density) it
becomes very difficult to distinguish between 100% incineration and the scenarios
that incorporate recycling.
Alternative reprocessing options
The baseline scenarios consider that the PET bottle waste is reprocessed into PET
granulate for use in further PET bottle manufacture. Other options are available for
reprocessing of PET. In order to investigate the sensitivity of the results to this
parameter, Eco-Emballages provided life cycle data for the three layers and
Supercycle reprocessing processes.
In order to protect the confidentiality of the data, specific results are not presented in
this report, but the analysis revealed that the environmental externalities for the
alternative reprocessing options are of a similar scale due to the similar energy
requirements of the processes. In some specific cases where incineration is the MSW
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option the choice of reprocessing option could make it difficult to distinguish between
a 100% incineration scenario and a scenario incorporating recycling.
Using data provided by Eco-Emballages, a sensitivity analysis using LCI data for the
TBI process was also applied. Due to time and resource constraints, the sensitivity
analysis considered only the implications of the alternative reprocessing route for
Global warming potential and for internal costs. The analysis suggested that although
TBI reprocessing may have higher internal costs the process could potentially
compete with material recycling from a total social cost perspective.
4.2.1.9 Summary of sensitivity analysis
Parameter investigated Influence on CBA results Influence on conclusionsdrawn
Methodological issues
Economic values applied Significant Critical – applying a maximum andminimum range of economic valuationsmakes it impossible to distinguishbetween scenarios
Internal costs Significant Critical – applying a +/-20% range ofinternal costs makes it impossible todistinguish between scenarios
Inclusion of employment as anexternality
Significant for kerbside collectionscenarios
Critical – valuing employment as anexternal impact category would changethe relative position of some scenarios.Where incineration with energyrecovery is the alternative MSW option,the scenarios incorporating separatekerbside collection would now beconsidered the optimal system, therebyincreasing optimal recycling rates forthis situation.
Scenario choices
Incineration model - CHP Total social cost of incinerationscenarios reduced
No effect on relative standing of thescenarios
Incineration model – offset electricity Total social cost of incinerationscenarios reduced.
For low population density, 100%incineration is now more favourablethan a system incorporating kerbsidecollection, but a system incorporating abring scheme remains the optimal of thescenarios considered
Significant for high population density,where incineration is the alternativeMSW option, the bring scheme systemwould now be considered the optimalsystem, thereby decreasing optimalrecycling rates for this situation.
Transport distances – MSW collectionround distance, separate kerbside round,
collection from bring banks, transportfrom bring bank to reprocessor
Effect on the relative standing ofscenarios
No effect on the choice of optimumscenarios
Significant for high population density,where incineration is the alternativeMSW option, the bring scheme systemwould now be considered the optimal
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system, thereby decreasing optimalrecycling rates for this situation.
Transport distances – consumertransport to bring bank
Increases total social cost of bringschemes
Where incineration is the alternativeMSW option, choice of optimumscenario could change from systemincorporating bring scheme to systemincorporating separate kerbsidecollection. This would increase theoptimum recycling rate
Overseas reprocessing Total social cost of scenariosincorporating recycling is increased, butno change in relative standing of thescenarios
No effect on the choice of optimumscenarios
Offset virgin production Total social costs of scenariosincorporating recycling is increased.
Where landfill is the MSW option, thereis no change in the relative standing ofthe scenarios.
In high population density, whereincineration is the MSW option, itbecomes impossible to choose betweenthe scenarios
Where landfill is MSW option, no effecton choice of optimum scenario
Where incineration is MSW option, noobvious optimum scenario and thereforeno obvious optimum recycling rate, incase of high population density.
Alternative reprocessing options General scale of externalities remainsthe same.
Could affect the choice of optimumscenario under certain circumstances
4.2.2 Steel packaging from household sources
18 scenarios were modelled taking into account the following parameters :
- low and high population density
- landfill, incineration with energy recovery but without slags recovery and
incineration with energy and slags recovery as alternative MSW treatment
options
- no selective collection, kerbside collection and bring scheme as potential
collection systems.
Results are compared from total social cost perspective, and the optimum system for
the scenarios considered is determined according to the methodology described in
chapter 3.4.1. (see Table 20)
Table 20 : Optimum systems for steel packaging
Low population density High population density
Landfill Bring scheme (Although thedifference between allscenarios is very small)
No selective collection andbring scheme (because thedifference between thesystems is negligible)
Incineration without slags Bring scheme No selective collection and
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recovery bring scheme (because thedifference between thesystems is negligible)
Incineration with slagsrecovery
No selective collection No selective collection
Detailed results of the CBA and the sensitivity analysis are presented in Annex 10 :
Presentation of CBA results for recycling case studies.
4.2.3 Aluminium packaging from household sources
4.2.3.1 Cans
18 scenarios were modelled taking into account the following parameters :
- low and high population density
- landfill, incineration with energy recovery but without slags recovery and
incineration with energy and slags recovery as alternative MSW treatment
options
- no selective collection, kerbside collection and bring scheme as potential
collection systems.
Results are compared from total social cost perspective, and the optimum system for
the scenarios considered is determined. Results are given in Table 21.
Table 21 : Optimum systems for aluminium cans
Low population density High population density
Landfill Separate kerbside collectionscheme
Separate kerbside collectionscheme
Incineration without slagsrecovery
Separate kerbside collectionscheme
Separate kerbside collectionscheme
Incineration with slagsrecovery
No selective collection Bring scheme
Detailed results of the CBA and the sensitivity analysis are given in Annex 10 :
Presentation of CBA results for recycling case studies.
4.2.3.2 Other rigid and semi-rigid application
18 scenarios were modelled taking into account the following parameters :
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- low and high population density
- landfill, incineration with energy recovery but without slags recovery and
incineration with energy and slags recovery as alternative MSW treatment
options
- no selective collection, kerbside collection and bring scheme as potential
collection systems.
Results are compared from total social cost perspective, and the optimum system for
the scenarios considered is determined. Results are given in Table 22.
Table 22 : Optimum systems for other rigid and semi-rigid aluminiumpackaging
Low population density High population density
Landfill separate kerbside collection separate kerbside collectionand bring scheme
Incineration without slagsrecovery
separate kerbside collectionand bring scheme
Incineration with slagsrecovery
separate kerbside collectionand bring scheme
Detailed results of the CBA and the sensitivity analysis are given in Annex 10 :
Presentation of CBA results for recycling case studies.
4.2.4 Paper and board packaging from household sources
12 scenarios were modelled taking into account the following parameters :
- low and high population density
- landfill and incineration with energy recovery as alternative MSW treatment
options
- no selective collection, kerbside collection and bring scheme as potential
collection systems.
Results are compared from total social cost perspective, and the optimum system for
the scenarios considered is determined. Results are given in Table 23.
Table 23 : Optimum systems for paper & board packaging
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Low population density High population density
Landfill kerbside collection scheme kerbside collection scheme
Incineration with slagsrecovery
kerbside collection scheme kerbside collection scheme
Detailed results of the CBA and the sensitivity analysis are given in Annex 10 :
Presentation of CBA results for recycling case studies.
4.2.5 LBC from household sources
16 scenarios were modelled taking into account the following parameters :
- low and high population density
- landfill and incineration with energy recovery as alternative MSW treatment
options
- landfill and incineration with energy recovery as recycling rejects treatment
options
- no selective collection, kerbside collection and bring scheme as potential
collection systems.
Results are compared from total social cost perspective, and the optimum system for
the scenarios considered is determined. Results are given in Table 24.
Table 24 : Optimum systems for LBC packaging
MSW treatment Rejects treatment Low pop. density High pop. density
Landfill Landfill No selective collection No selective collection
Landfill Incineration No selective collection No selective collection
Incineration withslags recovery
Incineration No selective collection No selective collection
Detailed results of the CBA and the sensitivity analysis are given in Annex 10 :
Presentation of CBA results for recycling case studies.
4.2.6 Mix plastic packaging from household sources
12 scenarios were modelled taking into account the following parameters :
- low and high population density
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- landfill and incineration with energy recovery as alternative MSW treatment
options
- no selective collection, kerbside collection with mechanical recycling or with
treatment in blast furnace as potential collection & recycling options.
Results are compared from total social cost perspective, and the optimum system for
the scenarios considered is determined. Results are given in Table 25.
Table 25 : Optimum systems for mix plastic packaging
MSW treatment Low pop. density High pop. density
Landfill No selective collection No selective collection
Incineration with slags recovery No selective collection No selective collection
Detailed results of the CBA and the sensitivity analysis are given in Annex 10 :
Presentation of CBA results for recycling case studies.
4.2.7 Industrial case studies
For the 2 industrial case studies, i.e. LDPE plastic films and cardboard, we calculated
the minimum packaging waste production under which the selective collection is not
beneficial.
The external benefits (EB) of collecting and recycling industrial packaging waste has
been calculated as 11.7 EURO/t (corrugated board) and 208 EURO/t (PE film).
Collecting and transporting corrugated board and PE films as mixed waste is often
cheaper than collecting and transporting source sorted packaging. There is thus an
additional collection cost (ACC) to collect selectively.
The annual production of industrial packaging waste for which the ACC = EB is
Ø 5.5 t/year for cardboard
Ø 0.01 t/year for LDPE plastic films
Above this waste production the environmental benefits outweigh the additional
internal cost for the selective collection.
This means that, from a cost-benefit viewpoint, the companies who produce more
waste than 0.01 t of plastic film or 5.5 t of corrugated board per year should have a
selective collection scheme to recycle it. As the "break-even" amount is very low for
PE films, it can be concluded that selective collection of industrial packaging should
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be systematic throughout the EU. As there are limits to the modelling, it has been
assumed for this study that 95% of the industrial sites (percentage in packaging
weight) should make the selective collection of packaging.
This means that the recycling rates that should achieved for the industrial packaging is
equal to "95% of the collection rate achievable when a selective collection scheme is
set up" multiplied by the fraction of the waste that may be recycled for safety (in
contact with hazardous products) or technical reasons (too high material degradation).
In other words, the recycling rates that minimise (read "optimise") the social cost of
the industrial packaging waste management are the ones given in Table 7 on page 37
multiplied by 95%.
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4.3 Suggested recycling targets
4.3.1 Determination of optimum systems and recycling ranges
For each combination of parameters (i.e. population density, alternative MSW
treatment options), the “optimal” collection system is considered to be the collection
system corresponding to the scenario modelled with the lowest total social cost. The
scenarios and their results are discussed in chapter 4.2 and summarised in Table 26
Table 26 : Optimum collection systems per case study, based on CBA
Low population density High population density
Landfill Incineration Landfill Incineration
PET bottles Kerbside Bring Kerbside Kerbside
Steel packaging Bring No SC No or bring No SC
Al cans Kerbside No SC Kerbside Bring
Rigid & semi-rigid Alpackaging excluding cans
Kerbside Kerbside orbring
Kerbside orbring
Kerbside orbring
Paper and board packaging Kerbside Kerbside Kerbside Kerbside
LBC No SC No SC No SC No SC
Mix plastic packaging No SC No SC No SC No SC
However the choice of optimum collection system has also to consider
communication aspects. It mainly means to take into account the understanding and
behaviour of the consumer. E.g. the consumer will not be able to make the difference
between aluminium and steel cans. Therefore it assumed that both packaging material
should be collected with the same collection systems.
Insofar as the optimal collection systems, based on CBA calculation, are not the same
for all metals packaging, weighted Total Social Costs are compared in order to
determine the common optimal system. The weighting parameters are the amount of
packaging put on the market. The common optimal collection systems are given in
Table 27.
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Table 27 : Optimal collection systems for metal packaging
Low population density High population density
Landfill Incineration Landfill Incineration
Steel packaging Bring and kerbside No SC Kerbside No SC
Al cans Bring and kerbside No SC Kerbside No SC
Rigid & semi-rigid Alpackaging excluding cans
Bring and kerbside No SC Kerbside No SC
On the other hand the models do not consider scale effects. Therefore PET bottles,
LBC and metals packaging could be collected with different collection systems
provided that the collected amount is sufficient to justify a frequency of at least once a
month.
The “optimal” recycling rate is considered to be the recycling rate achievable by the
“optimal” collection system. Therefore Table 28 gives the range of “optimal”
recycling rates for each case study.
Table 28 : Optimal recycling ranges per case study
Low population density High populationdensity
Landfill Incineration Landfill Incineration
PET bottles 70-80% 35-45% 59-69% 59-69%
Steel packaging 15-60% 80% 40-60% 80%
Al cans 31-55% 76% 45-55% 76%
Rigid & semi-rigid Al packagingexcluding cans
3-17% 50% 3-8% 50%
Paper and board packaging 61-71% 61-71% 55-65% 55-65%
LBC 0% 0% 0% 0%
Mix plastic packaging 0% 0% 0% 0%
4.3.2 Determination of optimal recycling rate for each Member State
This chapter concerns the determination of ranges of global optimal recycling rate for
each Member States. The global recycling rate takes into account all the packaging
whatever their origin (i.e. household and industrial sources).
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For each application, optimal recycling rates were determined for each of the 4
categories (population density / MSW treatment) (see Table 28). The optimum target
for an application in a specific Member State is the weighted average of the 4 targets
related to the 4 categories. The weighting factors are the ones given in Table 11.
In order to obtain ranges of recycling targets, the minimum and maximum optimal
recycling rates are successively applied to the packaging mix of each Member State.
Table 29 illustrates the calculation of the range of global optimal recycling rate for the
European Union. The packaging mix considered is the sum of the packaging amount
arising in all the Member States.
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Table 29 : Calculation of minimum and maximum recycling rate for the EU
Minimum recycling ratesEU 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 4.018 1.348LDPE films 1.651 869Other 2.367 479
Wood 7.812 3.711Steel 1.818 1.382Cardboard 18.823 11.444glass 1.789 850Other 289 0
Total 34.549 18.735
Global Target Industrial waste 54%
landfill Inc. landfill Inc.Household waste 27% 12% 41% 20%
Plastics 5.871 1.374PET bottles 1.502 70% 35% 59% 59% 887LPDE films 1.205 0% 0% 0% 0% 0HDPE bottles 1.015 57% 28% 48% 48% 487other 2.150 0% 0% 0% 0% 0
Steel 2.214 15% 80% 40% 80% 1.022aluminium total 391,6 96Wood 128 0% 0% 0% 0% 0Cardboard total 5.947 61% 61% 55% 55% 3.411composites liquid beverage c a 710 0% 0% 0% 0% 0
mainly based on p 109 0% 0% 0% 0% 0mainly based on c 165 0% 0% 0% 0% 0mainly based on A 86 0% 0% 0% 0% 0
Glass 13.445 73% 73% 42% 42% 7.288Other 65 0% 0% 0% 0% 0
Total 29.132 13.191
Global Target Household waste 45%
Total 63.681 31.926
Global target (Industrial + Household waste) 50%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
0% 50%0% 0%
0% 80%0% 64%
0% 21%0% 50%
0% 55%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
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Maximum recycling ratesEU 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 4.018 2.111LDPE films 1.651 1.182Other 2.367 929
Wood 7.812 5.195Steel 1.818 1.555Cardboard 18.823 14.306glass 1.789 1.411Other 289 0
Total 34.549 24.577
Global Target Industrial waste 71%
landfill Inc. landfill Inc.Household waste 27% 12% 41% 20%
Plastics 5.871 1.626PET bottles 1.502 80% 45% 69% 69% 1.037LPDE films 1.205 0% 0% 0% 0% 0HDPE bottles 1.015 67% 38% 58% 58% 589other 2.150 0% 0% 0% 0% 0
Steel 2.214 60% 80% 60% 80% 1.472aluminium total 391,6 122Wood 128 0% 0% 0% 0% 0Cardboard total 5.947 71% 71% 65% 65% 4.006composites liquid beverage c 710 0% 0% 0% 0% 0
mainly based o n 109 0% 0% 0% 0% 0mainly based o n 165 0% 0% 0% 0% 0mainly based o n 86 0% 0% 0% 0% 0
Glass 13.445 83% 83% 91% 91% 11.811Other 65 0% 0% 0% 0% 0
Total 29.132 19.036
Global Target Household waste 65%
Total 63.681 43.613
Global target (Industrial + Household waste) 68%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 75%0% 41%0% 70%0% 90%0% 80%0% 83%0% 0%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Detailed tables per Member State are given in Annex 11 : Calculation of recycling
rates per Member States.
The minimum and maximum recycling targets are summarised per Member States in
Table 30. They are detailed per industrial and household packaging sources.
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Table 30 : Summary of the ranges of optimal recycling rates per MemberStates
Global Target Industrialwaste
Global Target Householdwaste
Global target (Industrial +Household waste)
Min Max Min Max Min Max
Austria 56% 74% 42% 60% 49% 67%
Belgium 54% 70% 42% 65% 48% 67%
Denmark 54% 70% 53% 66% 53% 68%
Finland 57% 73% 35% 48% 48% 63%
France 53% 72% 45% 68% 50% 70%
Germany 56% 72% 45% 71% 51% 72%
Greece 53% 70% 39% 52% 46% 61%
Ireland 50% 67% 27% 38% 40% 54%
Italy 54% 71% 44% 65% 49% 68%
Luxembourg 54% 70% 46% 66% 50% 68%
The Netherlands 55% 71% 44% 64% 51% 68%
Portugal 57% 75% 46% 64% 47% 65%
Spain 50% 66% 47% 65% 49% 65%
Sweden 59% 76% 44% 54% 52% 66%
United Kingdom 56% 72% 39% 64% 49% 69%
EU 54% 71% 45% 65% 50% 68%
Depending on MS and assumptions, the optimum recycling rate varies from 40% to
72%.
There is no uniform optimum recycling rate valid throughout EU. The optimum can
vary from MS to MS by as much as 31% (in absolute terms, i.e. from the minimum of
the minimum targets to the maximum of the maximum targets).
4.3.3 Determination of optimal recycling rate for each packaging material (at the
EU level)
The optimum recycling target for a material (e.g. plastics) in a specific Member State
is the weighted average of the optimum targets of the different applications (e.g. for
plastics: PET bottles, HDPE containers, LDPE industrial films, LDPE household
films and others) in this Member State.
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In order to complete the previous data Table 31 summarised the range of recycling
rate per material for the European Union.
Table 31 : Recycling rate per material
Minimum recycling rate Maximum recycling rate
Plastic 28% 38%
Steel 60% 75%
Aluminium 25% 31%
Wood 47% 65%
Paper & board 60% 74%
Glass 53% 87%
Composites 0% 0%
4.3.4 Sensitivity analysis
Global recycling targets were calculated with the packaging mix forecast for 2000.
Insofar new targets will be applied in 2006, the influence of the packaging mix and
the evolution of the population density and the alternative MSW treatment on the
results are analysed.
The main constraint is the data availability. Forecasts for 2006 are not always
available and have to be used with caution.
The packaging mix modelled for 2006 is given in Annex 6: Packaging mix by
Member State.
Table 32 gives the global recycling rates that should be achieved considering the
packaging mix modelled for 2006.
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Table 32 : Recycling targets per Member State in 2006
Min Max
Industrial Household Total Industrial Household Total
Austria 56% 41% 49% 74% 59% 66%
Belgium 54% 41% 47% 70% 62% 66%
Denmark 54% 49% 52% 70% 62% 67%
Finland 54% 39% 47% 72% 50% 62%
France 53% 46% 50% 72% 69% 70%
Germany 55% 42% 50% 72% 64% 68%
Greece 52% 38% 45% 70% 51% 60%
Ireland 49% 43% 47% 66% 60% 64%
Italy 54% 45% 50% 71% 66% 68%
Luxembourg 54% 47% 51% 70% 67% 68%
Netherlands 54% 42% 49% 71% 60% 66%
Portugal 52% 48% 49% 70% 67% 67%
Spain 51% 48% 49% 66% 66% 66%
Sweden 57% 42% 50% 74% 53% 65%
United Kingdom 55% 38% 48% 72% 61% 67%
EU10 54% 45% 50% 71% 64% 68%
Depending on MS and assumptions, the optimum recycling rate varies from 45 to
70%.
There is no uniform optimum recycling rate valid throughout EU. The optimum can
vary from MS to MS by as much as 25% (in absolute terms, i.e. from the minimum of
the minimum targets to the maximum of the maximum targets).
In general, the evolution of the packaging mix between 2001 and 2006 has only little
influence on the global recycling targets (mainly because the relative evolution is
rather limited).
10 Packaging mix modelled for the EU is the sum of packaging mix of all the Memberstates
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However the influence of the packaging mix evolution on the "optimum" recycling
rates for household packaging is larger for Austria, Finland, Germany, Ireland and
The Netherlands.
Regarding the specific targets for Portugal, the influence of the packaging mix
evolution is also substantial but it is counterbalanced by the evolution of the
population density and alternative MSW treatment options so that the "optimum"
recycling rates show only a slight evolution.
The sensitivity of the material targets to the packaging mix was also examined (Table
33).
Table 33 : Sensitivity of the material recycling rates to the packaging mix
2000 2006
Min Max Min Max
Plastic 28% 38% 26% 36%
Steel 60% 75% 63% 76%
Aluminium 25% 31% 26% 31%
Wood 47% 65% 47% 66%
Paper & board 60% 74% 60% 74%
Glass 53% 87% 53% 87%
Composites 0% 0% 0% 0%
Considering the uncertainty on the assumptions, the evolution of the packaging mix
does not strongly influences the material recycling rates.
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4.4 Reuse
The complete results concerning reuse are presented in Annex 12 : Presentation of
CBA results for reuse case studies.
4.4.1 Glass
The results concerning the internal, external and total social costs for glass are
summarised in Graph 21, Graph 22 and Graph 23 (next pages).
From an internal cost perspective, the glass returnable system is cheaper than the one-
way system as long as the distance from filler to distribution centre is smaller than :
• 125 km in the case 20 uses - 91% recycling rate
• 150 km in the case 20 uses - 42% recycling rate
• 100 km in the case 5 uses - 91% recycling rate
• 120 km in the case 5 uses - 42% recycling rate
From an external cost perspective, the glass returnable system is better for the
environment than the one-way system as long as the distance from filler to
distribution centre is smaller than :
• 3500 km in the case 20 uses - 91% recycling rate
• 4200 km in the case 20 uses - 42% recycling rate
• 2300 km in the case 5 uses - 91% recycling rate
• 3000 km in the case 5 uses - 42% recycling rate
The total social cost for the glass returnable system is a better option than the one-way
system as long as the distance from filler to distribution centre is smaller than :
• 230 km in the case 20 uses - 91% recycling rate
• 280 km in the case 20 uses - 42% recycling rate
• 175 km in the case 5 uses - 91% recycling rate
• 220 km in the case 5 uses - 42% recycling rate
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Graph 21 : Internal costs for glass
Internal costs - returnables versus single trip
0
100
200
300
400
500
600
700
800
50 100 150 200Distance to market (km)
Inte
rnal
co
st (
Eu
ro p
er 1
000l
pro
du
ct
pu
rch
ased
by
con
sum
er)
returnables (5 reuses)
returnables (20 reuses
single trip (42%recycling)
"single trip (91%recycling)
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Graph 22 : External costs for glass
External costs - returnables versus single trip (assuming 100% return rate)
0
100
200
300
400
500
600
700
0 1000 2000 3000 4000 5000 6000
Distance to market (km)
Ext
ern
al c
ost
(E
uro
per
100
0l p
rod
uct
p
urc
has
ed b
y co
nsu
mer
) returnables (5 reuses)
returnables (20 reuses
single trip (42%recycling)
single trip (91%recycling)
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Graph 23 : Total social costs for glass
Total social costs - returnables versus single trip (assuming 100% return rate)
700
800
900
1000
1100
1200
1300
1400
1500
150 200 250 300 350
Distance to market (km)
To
tal s
oci
al c
ost
(E
uro
per
100
0l
pro
du
ct p
urc
hse
d b
y co
nsu
mer
)
returnables (5 reuses)
returnables (20 reuses
single trip (42%recycling)
"single trip (91%recycling)
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From these results it can be drawn that :
♦ The reuse system is cheaper for relatively short transportation distances11 (under
100 to 150 km)
♦ The reuse system is always better from an environmental point of view
♦ From an total social cost perspective, the reuse system is preferable for short and
medium transportation distances12 (under 175 to 280 km).
4.4.2 PET
The results concerning the internal, external and total social costs for PET are
summarised in Graph 24, Graph 25 and Graph 26 (next pages).
From an internal cost perspective, the PET returnable system is always more
expensive than the single trip system. The difference is significant in the in the case
of 5 uses and less substantial for 20 uses.
From an external cost perspective, the PET returnable system is better for the
environment than the one-way system as long as the distance from filler to
distribution centre is smaller than :
• 50-130 km in the case 80% recycling rate
• 220-300 km in the case 20% recycling rate
From an total social cost perspective, the internal costs outweigh the external costs so
that logically, the conclusions are the same as for the internal costs : the PET single
trip system is always a better option than the returnable system. The difference is
significant in the in the case of 5 uses and less substantial for 20 uses.
11 from filler to distribution centre12 from filler to distribution centre
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Graph 24 : Internal costs for PET
Internal costs - returnables versus single trip (assuming 100% return rate)
0
100
200
300
0 50 100 150 200
Distance to market (km)
Inte
rnal
cos
t (Eu
ro p
er 1
000l
pro
duct
pu
rcha
sed
by c
onsu
mer
) returnables (5reuses)
returnables (20reuses
single trip (42%recycling)
"single trip (91%recycling)
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Graph 25 : External costs for PET
External costs - returnables versus single trip (assuming 100% return rate)
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Distance to market (km)
Ext
ern
al c
ost
(E
uro
per
100
0l p
rod
uct
p
urc
has
ed b
y co
nsu
mer
) returnables (5 reuses)
returnables (20 reuses
single trip (42%recycling)
single trip (91%recycling)
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Graph 26 : Total social costs for PET
Total social costs - returnables versus single trip (assuming 100% return rate)
0
100
200
300
400
0 50 100 150 200
Distance to market (km)
To
tal s
oci
al c
ost
(E
uro
per
100
0l p
rod
uct
p
urc
hse
d b
y co
nsu
mer
) returnables (5 reuses)
returnables (20 reuses
single trip (42%recycling)
"single trip (91%recycling)
c
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4.4.3 Glass and PET
The results concerning the internal, external and total social costs for both glass and
PET are summarised in Table 34and in Graph 27, Graph 28 and Graph 29 (next
pages). It is very important to note that as small content were considered for glass
packaging (330 ml) and large content (1.5 litre) for PET bottles, the comparison
between materials is biased.
Table 34 : Internal, external and total cost of beverage packaging systems
Distance from filler to
distribution centre
System
type
System Internal
Cost
External
Cost
Total Social
Cost
Glass 5U 249.15 90.30 339.45
PET 5U 234.80 9.95 244.76
Glass 20U 204.84 30.46 235.30refillable
PET 20U 106.05 7.42 113.47
Glass 42% 448.83 265.19 714.02
Glass 91% 410.81 224.71 635.52
PET 20% 79.63 15.72 95.35
0 km
single trip
PET 80% 88.46 10.90 99.36
Glass 5U 6225.15 269.68 6494.83
PET 5U 1175.34 109.38 1284.72
Glass 20U 6180.84 209.85 6390.69refillable
PET 20U 1046.58 106.84 1153.43
Glass 42% 3436.83 345.11 3781.94
Glass 91% 3398.81 304.64 3703.45
PET 20% 598.31 68.15 666.46
1800 km
single trip
PET 80% 607.14 63.32 670.46
A first conclusion from those results is that the internal costs outweigh the
environmental costs (external costs represent 10% or less of the total cost with the
exception of glass single trip – 60%).
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Graph 27 : Internal costs for refillable and non refillable glass (33cl) and PET(1.5l) beverage packaging
Internal cost of beverage packaging systems
0
1 000
2 000
3 000
4 000
5 000
6 000
7 000
0 km 1800 km
Distance from fi l ler to distribution centre
cost
(E
UR
O/1
000
litre
s
Glass 5 uses
Glass 20 uses
PET 5 uses
PET 20 uses
Glass 42%
Glass 91%
PET 20%
PET 80%
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Graph 28 : External costs for refillable and non refillable glass (33cl) and PET(1.5l) beverage packaging
External cost of beverage packaging systems
0
50
100
150
200
250
300
350
400
0 km 1800 km
Distance from filler to distribution centre
cost
(E
UR
O/1
000
litre
s
Glass 5 uses
Glass 20 uses
PET 5 uses
PET 20 uses
Glass 42%
Glass 91%
PET 20%
PET 80%
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Graph 29 : Total social costs for refillable and non refillable glass (33cl) andPET (1.5l) beverage packaging
Total Social cost of beverage packaging systems
0
1 000
2 000
3 000
4 000
5 000
6 000
7 000
0 km 1800 km
Distance from fi l ler to distribution centre
cost
(E
UR
O/1
000
litre
s
Glass 5 uses
Glass 20 uses
PET 5 uses
PET 20 uses
Glass 42%
Glass 91%
PET 20%
PET 80%
From an internal cost perspective, the PET single trip system is clearly the cheapest
system. For short distances, the PET refillable system is also +/- competitive if the
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number of uses is sufficient (20% more expensive for 20 uses, i.e. 0.02 EURO/litre)
but the difference is much more significant for the other refillable systems :
• glass 20 uses : 0.12 EURO/litre
• PET-5 uses : 0.15 EURO/litre;
• glass 5 uses : 0.16 EURO/litre;
For long distances, no system can compete with the PET single trip system
(difference of minimum 0.5 EURO/ litre for 1800 km13).
From an external cost perspective (environment) :
• for short distances, the PET returnable system is the best system, although the
PET single trip system’s score is quite similar. The glass returnable system
creates impacts that are 3 to 4 times higher (20 uses) or about 10 times higher
(5 uses). The impacts of the single trip glass are tremendous, even for high
recycling rates (about 25 times the impacts of PET systems).
• for long distances, the PET single trip system becomes the best system,
although the PET returnable system’s score remains quite similar. The glass
returnable and single trip systems create much more impacts.
The total social cost figures are similar to the internal cost figures.
• for short distances, the PET single trip and returnable 20 uses are the best
options. The returnable systems PET-5 uses and glass-20 uses are about 2 to
2.5 times higher and the glass-5 uses about 3 to 3.5 times. The single trip
glass is 6 to 7 times higher.
• For long distances, no system can compete with the PET single trip system
(difference of minimum 0.5 EURO/ litre for 1800 km14).
13 reminder : distance are given for the one-way trip14 reminder : distance are given for the one-way trip
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5 CONCLUSIONS AND RECOMMENDATIONS
Reservations using those results
When using the results to inform the revision of the recycling targets in the context of
the Directive, the EC should take into account that :
ü CBA is not yet a mature instrument, specially concerning the economic valuation
of the environmental impacts which must therefore be considered carefully.
ü Materials that, according to this study, should attain a high recycling rate could be
financially penalised compared to other materials. Changes to packaging material
market shares that may be induced unintentionally by material specific targets
could have an adverse environmental impact if the entire packaging production
chain is considered. Material specific targets, if any, should thus take into account
the full production chain of the packaging, in order to avoid the risk to favour less
environmentally friendly materials.
ü Some results achieved and conclusions drawn (PET, paper&board15) are based
upon recent and current market prices for the recycled materials. These materials
can be subject to significant price fluctuations, which would change the results of
the cost benefit analysis.
ü The results achieved should not be interpreted and applied too simplistically.
Whilst every effort has been made to take into account variable factors that affect
the costs and benefits of recycling, it should be recognised that other local factors
not considered may also affect the results (e.g. availability of local output market
for the recycled materials). Nationally or locally, higher or lower recycling rates
than the ones suggested by the results may be acceptable.
For other reservations about the results please refer to chapter 1 Constraints on page 8
and chapter 2.3 General methodological approach – Life cycle cost benefit
analysis"Limitations to CBA".
Conclusion 1 Achieved recycling rates are satisfactory
Most Member States already achieved the recycling rates set in the Packaging
Directive in 1998. It seems that all member States will reach and often significantly
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exceed the 25-45% overall recycling target by 2001, with the authorised exception of
the 3 Member States that had to fulfill less stringent requirements (i.e. Greece, Ireland
and Portugal). The 15% minimum target for each material will be reached in all
concerned Member States, with the exception of plastics for which the target will not
be reached in several Member States.
Conclusion 2 Generally speaking selective collection is better for the society
Generally speaking the selective collection of both household and industrial
packaging is better for the society than its treatment together with unsorted waste.
But there are some remarkable exceptions (see further conclusions).
Conclusion 3 Household packaging: separate kerbside collection is often
preferable
For household packaging very often the separate kerbside collection is preferable (and
might thus be considered as the "optimum system" among the modelled systems) due
to the higher collection rate. Notable exceptions are :
• Glass should be collected from bottle banks (minimum density : 1 bottle bank
per 1000 inhabitants)
• The metals
Ø should not be collected selectively in areas where the MSW is incinerated
with metals recovery and
Ø may also be collected selectively by a bring system in areas with a low
population density
• There is no evidence to support a mandatory target for the selective collection
of LBC, composites and mixed plastics
• Plastic bottles should be collected selectively by a bring system in areas where
both conditions are fulfilled at the same time :
Ø a low population density and
Ø the MSW is incinerated with efficient energy recovery
15 The other ones are based on average value over the last 3 years and are thus morestable
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This is summarised in the following table (Table 26 on page 90 and Table 27 on page
91)
Low population density High population density
Landfill Incineration Landfill Incineration
PET bottles Kerbside Bring Kerbside Kerbside
Steel packaging Bring +kerbside
No SC Kerbside No SC
Al cans Bring +kerbside
No SC Kerbside No SC
Rigid & semi-rigid Alpackaging excludingcans
Bring +kerbside
No SC Kerbside No SC
Paper and boardpackaging
Kerbside Kerbside Kerbside Kerbside
LBC No SC No SC No SC No SC
Mix plastic packaging No SC No SC No SC No SCNo SC = no selective collection
The following recycling rates are the ones achievable with the those systems (Table
28 on page 91).
Low population density High populationdensity
Landfill Incineration Landfill Incineration
PET bottles 70-80% 35-45% 59-69% 59-69%
Steel packaging 15-60% 80% 40-60% 80%
Al cans 31-55% 76% 45-55% 76%
Rigid & semi-rigid Al packagingexcluding cans
3-17% 50% 3-8% 50%
Paper and board packaging 61-71% 61-71% 55-65% 55-65%
LBC 0% 0% 0% 0%
Mix plastic packaging 0% 0% 0% 0%
The results were calculated for mechanical recycling. Based on the sensitivity
analysis, there are some indications that some alternative routes could be considered
as about equivalent to the mechanical recycling : Supercycle, TBI. However these
routes have not been investigated deeply so that these conclusions have to be
considered very cautiously.
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Conclusion 4 Industrial packaging : separate collection is preferable
For industrial packaging the separate collection for recycling is preferable. Notable
exceptions are :
• packaging that contained hazardous waste should be collected separately
because hazardous waste but should not be recycled
• Companies which produce a very small amount of cardboard waste (< 5.5 t
per year) may put the cardboard waste together with the unsorted waste due to
the relatively high additional internal cost.
Conclusion 5 Revised recycling targets
The recycling rates achievable with the "optimum systems" are summarised in the
following tables. They are given :
• per Member State and for the EU as a whole
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Global Target Industrialwaste
Global Target Householdwaste
Global target (Industrial +Household waste)
Min Max Min Max Min Max
Austria 56% 74% 42% 60% 49% 67%
Belgium 54% 70% 42% 65% 48% 67%
Denmark 54% 70% 53% 66% 53% 68%
Finland 57% 73% 35% 48% 48% 63%
France 53% 72% 45% 68% 50% 70%
Germany 56% 72% 45% 71% 51% 72%
Greece 53% 70% 39% 52% 46% 61%
Ireland 50% 67% 27% 38% 40% 54%
Italy 54% 71% 44% 65% 49% 68%
Luxembourg 54% 70% 46% 66% 50% 68%
The Netherlands 55% 71% 44% 64% 51% 68%
Portugal 57% 75% 46% 64% 47% 65%
Spain 50% 66% 47% 65% 49% 65%
Sweden 59% 76% 44% 54% 52% 66%
United Kingdom 56% 72% 39% 64% 49% 69%
EU 54% 71% 45% 65% 50% 68%
Depending on MS and assumptions, the optimum recycling rate varies from 40% to
72%.
There is no uniform optimum recycling rate valid throughout EU. The optimum can
vary from MS to MS by as much as 31% (in absolute terms, i.e. from the minimum of
the minimum targets to the maximum of the maximum targets).
• per packaging material and for all materials together
Minimum recycling rate Maximum recycling rate
Plastic 28% 38%
Steel 60% 75%
Aluminium 25% 31%
Wood 47% 65%
Paper & board 60% 74%
Glass 53% 87%
Composites 0% 0%
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Conclusion 6 Reuse should not be encouraged for beverage packaging
The PET single trip and PET returnable-20 uses are the best options for the beverage
packaging (only glass and PET systems were considered). The glass systems have
each a serious inconvenience :
• the impacts of the glass production (even at high recycling rates) for single trip
glass;
• the impacts of the additional transport for returnable glass.
However, as a small content were considered for glass packaging (330 ml) and a large
content (1.5 litre) for PET bottles, the comparison between materials is biased.
Thus, based on the results and with the reservations already expressed :
• non refillable glass is clearly the less favourable option for beverage
packaging 16;
• refillable systems for beverage packaging are not preferable to the PET single
trip system.
Those conclusions do not take into account some possible technical constraints. In
some cases those technical constraints could make it undesirable to favour the
systems that appear as the preferable ones considering only the environmental and
economic aspects. Exemples : single trip glass may be acceptable for whiskey for
conservation quality and it might be difficult to use PET bottles up to 20 times.
16 the relative difference is so huge for both the internal and external costs that theconclusion remains valid even if the content of the glass and PET bottles are different
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6 GLOSSARY
CBA : Cost – Benefit Analysis
EBS :
EC : European Commission
ER : Energy Recovery
Grey bag Municipal solid waste
LBC : Liquid beverage cartons
MPM : Multiple Pathway Method
MS : Member State
MSW : Municipal Solid Waste
PMC : Plastic bottles, Metals and LBC ("Cartons")
WF : Weight Factor
PWP : packaging waste producers
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7 BIBLIOGRAPHY
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[32] Ecoembes (SP), Ecovidrio (SP), Plastval (PO), Sociedade Ponto Verde (PO),
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Ireland
[36] Increasing recovery and recycling of packaging waste in the UK - The
Challenge Ahead: A forward Look for Planning Purposes, DETR, UK
[37] Secondo rapporto sui rifiuti urbani e sugli imballagi e rifiuti di imballagio,
Agenzia Nazonale per la protezione dell'ambiante, February 1999
[38] Italy - Summary of management and prevention plan of Conai, European
packaging and waste law, N° 79, July 2000, pp. 32-34
[39] Municipal Solid Waste Incineration in Europe, Juniper, 1995
[40] Gestion des déchets d’emballages en Europe, Eco-emballages, 1999
[41] Interviews of stakeholders in 2000
[42] Network of consultants
[43] Valuation of waste-related externalities, Pieter van Beukering, April 2000
[44] Glass Gazette N° 25, FEVE, October 1999
[45] Glass recycling in European Countries – 1999, data provided by FEVE,
November 2000
[46] Determination and characterisation of optimised collection systems, Beture
Environnement, 2000
[47] Meeting with FOST Plus, November 10 & 13, 2000
[48] Meeting with Eco-Emballages (00-06-09) and e-mail from Ms Noguer (00-10-
17)
[49] Corinair, Inventaire des émissions de SO2, Nox, et COV dans la Communauté
Européenne, 1995
[50] Interview Mr Meneguzzi, ANDRIN, November 2000
[51] Interview Mr Dhaene, Valomac, November 2000
[52] Ökobilanzdaten für Weissblech und ECCS, Informationszentrum Weissblech,
Oktober 1995
[53] Visit and interview of several sorting plants, RDC-Environment, 2000
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,
RDC-Environment & Pira International, May 2001
122
[54] Environmental Profile Report for the European Aluminium Industry EAA
April 2000
[55] Recycling and recovery of plastics from packagings in household waste –
LCA-type Analysis of different strategies, Fraunhofer-Institut, Freising,
December 1997
[56] Interview of Ace and Tetra Pak, 2000
[57] Interview of Dr. Ing. Janz, Stahlwerke Bremen, November 2000
[58] Recycling & Recovery (1) A1 2.2.2.3 (citation from Pira)
[59] Life cycle inventories for packagings, vol. 1 & 2, Buwal, 1998
[60] Reference Document on Best Available Techniques in the Glass
Manufacturing Industry, July 2000
[61] Interview of Colruyt
[62] Richtlijn Verpakking – Glas, HigH5, 2000
[63] DSD technical information
[64] Interview of Mr. Servol, TBI, November 2000
[65] Analyse de cycle de vie du recyclage chimique du PET en polyolspolyesters
selon le procédé TBI, BIO-Intellingence Service, December 1999
(Confidential)
[66] Interview of Pro-Europe Members, October 2000 – January 2001
[67] Interview of CEPI, 26/04/2000
[68] Interviews of ACE, August – December 2000
[69] Specific processing costs of waste materials in a municipal solid waste
combustion facility, TNO, TNO-MEP-R 96/248, 07/11/1996
[70] Interview consultant of constructors of incineration plant
[71] Tenders for incineration plants in Belgium
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ANNEXES
Annex 1: Process trees and system descriptions
Annex 2: Incineration and landfill models
Annex 3: Internal cost data
Annex 4: Economic valuations applied – sources and derivation
Annex 5: Employment data –jobs for waste management activities
Annex 6: Packaging mix by Member State
Annex 7: Environmental data sources
Annex 8: Current performance of Member States
Annex 9: Critical factors limiting recycling and reuse
Annex 10 : Presentation of CBA results for recycling case studies
Annex 11 : Calculation of recycling rates per Member States
Annex 12 : Presentation of CBA results for reuse case studies
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Annex 1: Process trees and system descriptions
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May 01
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1 GENERAL SYSTEM PARAMETERS
1.1 Optimised recycling chains
In this paragraph, optimised recycling chains are described for the different scenarios for which a
CBA is performed. Final system flow diagrams are given in chapter 2 of this annex.
1.2 Industrial packaging approach
For the 2 industrial case studies, i.e. LDPE plastic films and cardboard, we calculated the minimum
packaging waste production under which the selective collection is not beneficial.
The external benefits (EB) of collecting and recycling industrial packaging waste has been
calculated as 11.7 EURO/t (corrugated board) and 208 EURO/t (PE film).
Collecting and transporting corrugated board and PE films as mixed waste is often cheaper than
collecting and transporting source sorted packaging. There is thus an additional collection cost
(ACC) to collect selectively.
The annual production of industrial packaging waste for which the ACC = EB is
Ø 5.5 t/year for cardboard
Ø 0.01 t/year for LDPE plastic films.
Above this waste production the environmental benefits outweigh the additional internal cost for the
selective collection.
This means that, from a cost-benefit viewpoint, the companies who produce more waste than
0.01 t of plastic film or 5.5 t of corrugated board per year should have a selective collection
scheme to recycle it. As the "break-even" amount is very low for PE films, it can be concluded that
selective collection of industrial packaging should be systematic throughout the EU. As there are
limits to the modelling, it has been assumed for this study that 95% of the industrial sites
(percentage in packaging weight) should make the selective collection of packaging.
1.3 Kerbside collection
For PMC, it is assumed that the material is placed by the householder in a PMC selective collection
bag.
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May 01
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The selective collection bag may contain "light packaging" : plastic bottles, metals and LBC. It is
collected twice a month in high and low population density areas.
Collection vehicle is a truck with a volume of 16m_. The collected material is transported directly
to the sorting facility. Distance to sorting plant is about :
Truck Vehicle type High population density Low population density
Paper & board 17-25t truck 8 – 71,1 km/t 86,1 – 176,1 km/t
light packaging 17-25t truck 21,1 – 107,7 km/t 74,4 – 227,8 km/t
Employment and internal costs were determined based on Beture Environnement and FOST Plus
data. Air emissions from trucks are based on Corinair. Transport distances were provided by Eco-
emballages.
The paper and board selective collection happens once a month in high and low population density
areas. Packaging and magazines are collected together without any condition on the conditioning
(packaging).
Collection vehicle is a truck with a volume of 16m_.
Sources:[46], [48], [49], [66]
Note : The cost for selective collection is assumed to be independent from the amount of material to
be collected separately because the collection frequency is adapted to the amount of waste.
However, this is not true anymore for very low amounts (and frequencies) because there is a
minimum frequency under which the system is not efficient anymore.
1.4 Bring scheme
Consumers bring their sorted1 packaging waste and other waste to the bring scheme. Assumptions
on the distance which has to be attributed to “packaging collection” has be given by Eco-
Emballages..
In the bring scheme, packaging are collected in container of about 30m_. These containers are
transported to the sorting plant or the recycling facility about once a week for light packaging and
for paper & board packaging in high and low population density areas. The collected material is
taken directly to the sorting facility. Distance to sorting plant is about :
1 packaging waste are sorted in 2 fractions: light packaging on the first hand and paper & board +magazines on the other hand.
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frameof the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International
May 01
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Truck High population density Low population density
Paper & board 3,8 – 10,5 km/t 11,1 – 20,2 km/t
Light packaging 18 – 37,2 km/t 42,2 – 123,9 km/t
Sources:[46], [48], [66]
1.5 Sorting
Only limited data for the environmental impacts at a sorting plant was sourced. Data for energy
consumption at the sorting plant (electricity to power conveyors and space heating) has been
collected. For residual material arising at the sorting plant, the following assumption has been
made:
• Waste arising at sorting plant from materials collected by separate kerbside collection – 20%
• Waste arising at sorting plant from materials collected by bring bank – 10%
The sorted material is baled. Energy consumption for baling has been included in the model.
Bag opening
The selective collection bags are torn open by a mechanical ripping unit. The contents are then
transported by conveyor belt to a drum sieve which separates out large-volume items and foils and
films.
Foil and film and bags residues separation (not systematically)
The foils, films and bags pieces are then passed on to a so-called air separator, which automatically
separates them from any impurities (items wrongly disposed of in the selective collection bag),
before being pressed into bales.
Tinplate extraction
The recyclable materials, now minus the impurities, foils and films (if any), are then transported by
conveyor belt to the magnet separator. A magnet extracts iron-containing metal packaging such as
tinplate cans, crown caps and jar lids from the recycling stream.
Aluminium separation
Downstream of the magnet, an eddy current separator separates out the aluminium and composites
containing aluminium.
Separation of beverage cartons (not taken into account in this study)
More and more sorting plants are using machines for the automatic identification and segregation of
beverage cartons. These are passed in front of a near-infrared light, recognised by a computer and
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frameof the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International
May 01
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blown aside with compressed air. If this type of unit is positioned upstream of the eddy current
separator, it can also separate out composites containing aluminium at the same time.
Plastics sorting
To sort the materials completely, plastic bottles have to be sorted by hand according to their
characteristics:
- clear PET bottles,
- light blue PET bottles
- coloured PET bottles,
- HDPE bottles.
Note : There also exist different physical and opto-electronic based sorting machine for plastics
such as the sink-float process or hydrocyclone process.
Sources :[47], [53], [63], [66]
Sorted / baled materials are transported to the reprocessor for recycling. The specific transport
distances considered are summarised in the table below.
Transport from sorting plant to recycling facility
Stream Average loadmin max t
PET bottles 19,2 26,9 13HDPE bottles 17,7 52,0 13Glass bottles 2,0 9,6 20Al 15,0 91,7 6Steel 0,4 24,0 14-22Paper and cardboard 2,0 6,3 24Liquid beverage cartons 14,6 60,0 24
Transport distance (range in km/t)
Sources :[47], [48], [66]
1.6 Case study : Commercial and Industrial LDPE palletisation film
In case of non selective collection, packaging waste are landfilled or incinerated. Both options are
investigated.
This analysis is concerned with post-use commercial and industrial film, defined as “films for
palletisation”. This source of materials is fairly clean, at approximately 95-98% plastic. The results
of this case study only apply where there is a high degree of source separation (homogeneity of
material) and the material is clean. For example, where the source is clean shrink and stretch wrap
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used to transport bottles from production to filling – this film is homogenous, and has come from a
food environment and should therefore be clean. Backdoor waste from supermarkets is also a major
source of film for recycling, though cross-contamination of materials / plastics may occur at
supermarkets due to the diversity of packs being handled.
Other materials that may be collected will be less clean, for example agricultural films which may
be only 60% plastic, the remainder being contamination (stones, soil, etc). This contamination must
be removed by washing otherwise damage to the blades during recycling can occur. The results of
this case study do not apply to such materials.
For material recycling, it is assumed that the source separated material is collected and transported
directly to the reprocessor.
Material losses through washing and sorting at the reprocessing are 27%. During reprocessing, the
recyclate must be mixed with a degree of virgin material. In this analysis, it is assumed that the
film produced is made up of 86% recycled LDPE and 14% virgin LLDPE material.
The recycled film is assumed to offset production of virgin LDPE film for white and other light
coloured sacks, with a save ratio of 80%.
1.7 Case study : Commercial and industrial corrugated board
In case of non selective collection, packaging waste are landfilled or incinerated. Both options are
investigated.
For material recycling, it is assumed that the collected corrugated board will be recycled into new
corrugated board materials. In order to credit the system for increased recycling, the burdens for the
production of testliner (a component of corrugated board which has a 100% recycled content) have
been compared to the burdens for the production of kraftliner (a component of corrugated board
with a recycled content of less than 20%). The difference between the high recycled content
testliner and low recycled content kraftliner is the assumed environmental credit.
The displacement ratio is assumed to be 80%. The actual displacement ratio could be within the
range 60 and 100% depending on the end use application and the quality of waste input (this is
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frameof the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International
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investigated in the sensitivity analysis). The quality of the collected material and its usability in the
selected application is likely to reduce as the overall recycling rate increases.
It is important to note that the recycling loop for paper and board is extremely complex. Fibres
degrade, and cannot be used for the same application indefinitely. Each application requires
specific properties, and therefore specific mixes of fibres from different sources. Increasing the
recycled content of corrugated board may reduce the properties of the board.
Therefore, the situation modelled in this analysis is a theoretical situation, which illustrates the
range of costs and benefits that may be incurred where corrugated cases are recycled.
1.8 Case study : PET bottles
PET bottles can be
- collected with MSW and then landfilled or incinerated with energy recovery, according to
the scenario
- selectively collected with aluminium, steel and LBC by kerbside collection
- selectively collected with aluminium, steel and LBC within a bring scheme
In case of selective collection, plastic bottles are transported to the sorting plant where they are
manually sorted according to their characteristics (colour and polymer), crushed and baled.
Bales are transported to the recycling facility.
In the mechanical recycling facility, PET bottles are unbaled and PVC is separated. Then PET is
ground, washed and dried. Mechanical recycling into granulate for use in bottle production has been
considered in this study. The recycled material produced has been credited against the production
of virgin PET. The displacement save ratio assumed is 100%. For PET bottles, other reprocessing
routes are also available (for example fibre production or TBI process). These routes have not been
considered in detail in this analysis.
Interpretation and application of the results should take into account the following limitations:
§ The sorted/baled material sent to the reprocessor must meet required bale specifications in order
to be recycled by this technology. Therefore, results only apply to clear PET bottles and baled
materials that meet the required specifications.
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§ Internal and external costs for other reprocessing routes will be different from those considered
in the analysis
The sensitivity analysis considers feedstock process as recycling alternative.
Sources :[55], [57], [63], [64], [65]
1.9 Case study : Mixed plastics from household sources
Four waste management options are considered for mixed plastics from household sources:
• Landfill
• Incineration with energy recovery
• Mechanical recycling (press forming) via separate kerbside collection
• Recovery in a blast furnace via separate kerbside collection.
In case of selective collection, mix plastic packaging waste are transported to the sorting plant
where they are sorted, crushed and baled.
Bales are transported to the mechanical recycling facility or to the agglomeration plant (in case of
use in cement kilns or in blast furnace), according to the scenario.
In the mechanical recycling facility, mix plastic packaging are unbaled. After a dry process, plastic
is extruded in order to be used as palisade. The recovered material from mechanical recycling is
used for plastic palisade, and is assumed to offset production of wood. A displacement save ratio of
100% is assumed, although in reality this is highly variable (it is therefore investigated in the
sensitivity analysis). The recycling consists of a number of steps. Firstly, there is a dry treatment
stage. The output of this process is ground plastics. Losses at this stage are 20%. The ground
plastics are then press extruded into a product (in this case, palisade).
In the agglomeration plant the plastics mixture is processed in order to meet defined quality
criteria as regards bulk density, grain size, chlorine and dust content and residual moisture.
In technical terms, agglomeration consists of a sequence of shredding and separating processes,
followed by compacting of the plastic material. During the pelletisation process the shredded waste
plastic is compacted by means of pressure. The material is forced through the drilled holes of a
pelletiser and cut off with cutters : the process delivers agglomerate.
The so-called agglomerate is then transported or not to blast furnace or cement kiln where it is used
as a partial substitute for heavy oil (reduction process in blast furnace) or as secondary fuel (cement
kiln).
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For recovery via the blast furnace, the system is credited against fuel oil (low sulphur). It is
assumed that 1 tonne of agglomerate entering the blast furnace offset 964kg of fuel oil. The blast
furnace recovery route consists of a number of steps. Firstly, agglomerate is produced. Losses at
this stage are 24%. The agglomerate is then injected into the blast furnace, where it is assumed to
offset fuel oil.
Interpretation of the results of the cost benefit analysis should consider the following:
§ Other recovery routes are also available (for example, recovery in a cement kiln). These options
have not been considered in this analysis. The internal and external costs for these options will
be different.
Sources :[55], [57], [63]
Note : the bring system has not been analysed because there is no data available for such a system.
1.10 Case study : household steel applications
Five waste management options are considered for steel packaging arising from households
• Landfill
• Incineration with energy recovery
• Incineration with energy recovery and extraction of steel from slags
• Material recycling via separate kerbside collection, selectively collected with aluminium,
plastic bottles and LBC
• Material recycling via bring scheme, selectively collected with aluminium, plastic bottles and
LBC.
In case of selective collection, steel packaging are transported to the sorting plant where they are
automatically sorted with magnetic separator and baled.
Bales are transported to the recycling facilities (blast furnace) where they are melt (after shredding
or not).
Two production routes are assumed for production of packing steel. These are the oxygen furnace
using principally iron ore as the raw material and the electric arc furnace using scrap steel.
Increased recycling increases electric arc steel production whilst reducing blast furnace production,
thereby yielding an environmental credit.
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frameof the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International
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For incineration with extraction of slags it is assumed that 80% of the steel entering the incinerator
is recovered and sent for recycling.
A save ratio of 100% is considered for the recycled steel.
1.11 Case study : Aluminium beverage packaging
Household aluminium packaging waste can be
- collected with MSW and then landfilled or incinerated with aluminium recovery, according
to the scenario
- selectively collected with steel, plastic bottles and LBC by kerbside collection
- selectively collected with steel, plastic bottles and LBC within a bring scheme
Five waste management options are considered for aluminium beverage packaging arising from
households
• Landfill
• Incineration with energy recovery
• Incineration with energy recovery and extraction of aluminium from slags
• Material recycling via separate kerbside collection, selectively collected with steel, plastic
bottles and LBC
• Material recycling via bring scheme, selectively collected with steel, plastic bottles and LBC.
For incineration with extraction of aluminium from slags, it is assumed that 76% of the
aluminium beverage packaging entering the incinerator is recovered and sent for recycling.
In case of selective collection, aluminium packaging are transported to the sorting plant where they
are automatically sorted with Eddy current separator and baled.
Baled aluminium beverage cans from the sorting plant go through a scrap preparation stage. Losses
at the scrap preparation stage are 19%. The material is then melted and alloyed. The recycled
aluminium ingots are assumed to offset production of virgin aluminium ingots. A save ratio of
100% is assumed.
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1.12 Case study : Other rigid and semi-rigid aluminium packaging
Five waste management options are considered for other rigid and semi-rigid aluminium packaging
arising from households:
• Landfill
• Incineration with energy recovery
• Incineration with energy recovery and extraction of aluminium from slags
• Material recycling via separate kerbside collection, selectively collected with steel, plastic
bottles and LBC
• Material recycling via bring scheme, selectively collected with steel, plastic bottles and LBC.
For incineration with extraction of aluminium from slags, it is assumed that 50% of the rigid and
semi-rigid aluminium packaging except beverage cans entering the incinerator is recovered and sent
for recycling.
Baled aluminium from the sorting plant go through a scrap preparation stage. Losses at the scrap
preparation stage are 19%. The material is then melted and alloyed. The recycled aluminium
ingots are assumed to offset production of virgin aluminium ingots. A save ratio of 100% is
assumed.
1.13 Case study : household paper & board
Household Paper & Board packaging waste can be
- collected with MSW and then landfilled or incinerated with energy recovery, according to
the scenario
- selectively collected with magazines by kerbside collection
- selectively collected with magazines within a bring scheme
Paper & board selectively collected are first purified and manually sorted into various qualities.
They are then baled and transported to the pulp and paper plant.
At the pulp & paper plant, paper and board waste are pulped (after shredding or not). After
screening or centrifugal cleaning the pulp is purified and is ridded of all undesirable elements.
Fibbers are dried on a conveyer belt (Filtration - water is extracted and fibres remain).
Fibres are recovered and the rejects are incinerated or landfilled.
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For material recycling, limited life cycle inventory data or internal cost data for recycling processes
specific to household paper and cardboard packaging was available to the consultants.
Therefore the following limitations to the model should be recognised:
• It is assumed that the recovered fibre is reprocessed into testliner, and that the testliner
offsets the production of kraftliner (a save ratio of 80% has been assumed). This is a considerable
limitation of the model. The assumption has been made to facilitate a comparison of the burdens
associated with the production of a high recycled content substrate with the production of a low
recycled content substrate. In reality, recovered fibre from household paper and board packaging
will be mixed with virgin fibre and recovered fibre from other sources. The final application of the
substrate determines the properties required and therefore dictates the necessary pulp furnish. This
therefore also dictates the achievable recycling rate in the paper and board sector as a whole.
Increasing the recycling rate of paper and board packaging from household sources may not
increase the recycling rate of fibre overall. Increased recycling of paper and board packaging from
household sources may reduce recycling from other sectors such as newsprint. This has not been
addressed in this study, and should be recognised as a further limitation of the model.
Therefore, the situation modelled in this analysis is a theoretical situation, which illustrates the
range of costs and benefits that may be incurred where paper and cardboard packaging from
household sources are recycled.
Sources:[66], [67]
1.14 Case study : liquid beverage cartons
Six waste management options are considered for liquid beverage cartons:
• Landfill
• Incineration with energy recovery
• Material recycling of the fibre via separate kerbside collection (rejected aluminium and PE to
landfill)
• Material recycling of the fibre via separate kerbside collection (rejected aluminium and PE to
incineration)
• Material recycling of fibre via bring scheme (rejected aluminium and PE to landfill)
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• Material recycling of fibre via bring scheme (rejected aluminium and PE to incineration)
It is assumed that LBC is selectively collected with aluminium, plastic bottles and steel packaging.
In case of selective collection, LBC are transported to the sorting plant where they are automatically
sorted with Eddy current separator, crushed and baled. Other sorting techniques are described in
paragraph “Sorting ”, but are not included in the CBA.
Bales are transported to the recycling facilities (pulp & paper plant) where they are pulped (after
shredding or not). After screening or centrifugal cleaning pulp is purified and is ridded of all
undesirable elements. Fibbers are dried on a conveyer belt (Filtration - water is extracted and fibres
remain).
As with the household paper and cardboard packaging model, it is assumed that the recovered fibre
is reprocessed into testliner, and that the testliner offsets the production of kraftliner (with a save
ratio of 80% assumed). The same limitations therefore apply as in the household paper and card
model.
The Al/PE fraction can be energetically valorised in cement kilns/incinerators or used in pyrolysis.
Both landfill and incineration routes are analysed in this study.
Source :[66], [68]
1.15 Case study Glass bottles
Three waste management options are considered for household glass beverage packaging:
• Landfill
• Incineration with energy recovery
• Material recycling via a bring scheme
The LCI data available to the consultants is lacking in transparency. The data aggregates the
reprocessing steps and environmental credit, but no description of the assumptions made and
conditions under which the data is applicable are provided. No indication of the type of cullet being
recycled is given.
Therefore, the results of this case study should be considered only as indicative to the possible costs
and benefits that may be incurred when glass bottles from household sources are recycled.
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in theframe of the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International
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2 CASE STUDY PROCESS TREES
See annex 1 bis
MIXEDPLASTICS
SYSTEM BOUNDARY
COLLECTIONFOR
LANDFILL LANDFILL
MIXED PLASTICS FROM HOUSEHOLD
AGGLOMERATEPRODUCTION
BLASTFURNACE
Creditagainstfuel oil
COLLECTIONFOR
INCINERATION
MSW INCINERATION
ElectricityProduction
(av Europeanundelivered)
TRANSPORT TOREPROCESSOR
PRESSMOULDING
KERBSIDECOLLECTION
FOR RECOVERY
PLASTICPALISADE(CREDITAGAINSTWOOD)
SORTING +BALING
SORTING +BALING
MIXED PAPERPACKAGING
LANDFILL
SYSTEM BOUNDARY
MSW INCINERATION
ElectricityProduction
(av Europeanundelivered)
PAPER AND BOARD ARISINGFROM HOUSEHOLDS
TRANSPORT TOBRING BANK
TESTLINERPRODUCTION
(Screening,Pulping,
Papermaking)
SORTINGTRANSPORT
TORECYCLERS
COLLECTIONFOR
LANDFILL
COLLECTIONFOR
INCINERATION
KERBSIDECOLLECTION
FORIRECYCLING
COLLECTIONFROM BRING
BANK
EnergyElectricity
(av Europeanundelivered from
landfill gas collection)
TESTLINER(CREDITAGAINST
KRAFTLINER)
STEELPACKAGING
SYSTEM BOUNDARY
LANDFILL
MSW INCINERATION
STEEL PRODUCTION(ELECTRIC ARC OROXYGEN FURNACE
CREDITAGAINST VIRGIN
PRODUCTION
STEEL PACKAGING FROM HOUSEHOLD
METALS RECOVERYFROM INCINERATION
TRANSPORT TOREPROCESSOR
COLLECTIONFOR
INCINERATION
COLLECTIONFOR
LANDFILL
TRANSPORT TOREPROCESSOR
(STEEL MILL)
SORTING +BALING
KERBSIDECOLLECTION
FORRECYCLING
COLLECTIONFROM BRING
BANK
TRANSPORTTO BRING
BANK
WASTEBEVERAGE
CARTONS
SYSTEM BOUNDARY
COLLECTIONFOR
INCINERATIONMSW
INCINERATION
ElectricityProduction
(av Europeanundelivered)
COMPOSITE BEVERAGE CARTONSFROM HOUSEHOLD
CONSUMERTRANSPORT
TO BRINGBANK
KERBSIDECOLLECTION
FORRECYCLING
COLLECTIONFROM BRING
BANK
REPULPINGPROCESS
REJECTS (PE +AL) TO MSW
INCINERATION
COLLECTIONFOR
LANDFILLLANDFILL
EnergyElectricity
(av Europeanundelivered from landfill
gas collection)
SORTING +BALING
REJECTS (PE +AL) TO
LANDFILL
TESTLINERPRODUCTION
TESTLINER(CREDITAGAINSTKRAFTLINER)
RIGID + SEMI-RIGID
ALUMINIUMPACKAGING
SYSTEM BOUNDARY
COLLECTIONFOR
LANDFILL
COLLECTIONFOR
INCINERATION
KERBSIDECOLLECTION
FORRECYCLING
TRANSPORT TOREPROCESSOR
SORTING +BALING
RECYCLING +PRODUCTION
(SCRAPPREPARATIONSMELTING AND
ALLOYING)
TRANSPORTTO BRING
BANK
COLLECTIONFROM BRING
BANK
RIGID AND SEMI-RIGID ALUMINIUMPACKAGING FROM HOUSEHOLD
LANDFILL
MSW INCINERATION
MATERIALSRECOVERY FROM
INCINERATION
CREDITAGAINSTVIRGIN
PRODUCTION
LDPE FILMS
SYSTEM BOUNDARY
COLLECTIONFOR
LANDFILL LANDFILL
COLLECTIONFOR
INCINERATION
MSW INCINERATION
ElectricityProduction
(av Europeanundelivered)
COLLECTIONAND BALING
FORRECYCLING
TRANSPORT TOREPROCESSOR
FILMRECYCLING
Credit to LDPEFILM
LDPE FILMS ARISING FROMINDUSTRIAL SOURCES
CORRUGATEDBOARD
COLLECTIONFOR
LANDFILL LANDFILL
SYSTEM BOUNDARY
COLLECTIONFOR
INCINERATIONMSW
INCINERATION
COLLECTIONFOR
RECYCLING
TESTLINERPRODUCTION
(Screening,Pulping,
Papermaking)
TESTLINER (CREDITAGAINST KRAFTLINER)
CORRUGATED BOARD ARISINGFROM INDUSTRIAL SOURCES
ElectricityProduction
(av Europeanundelivered)
EnergyElectricity
(av European undeliveredfrom landfill gas collection)
SYSTEM BOUNDARY
PET BOTTLES FROM HOUSEHOLD
WASTE PETBOTTLES
COLLECTIONFOR
INCINERATION
COLLECTIONFOR
LANDFILL LANDFILL
MSW INCINERATION
ElectricityProduction
(av Europeanundelivered)
KERBSIDECOLLECTION
FORRECYCLING
TRANSPORT TOREPROCESSORSORTING +
BALING
PETRECYCLING
PETGRANULATE
TRANSPORT TOBRING BANK
COLLECTIONFROM BRING
BANK
GLASS
SYSTEM BOUNDARY
COLLECTIONFOR
LANDFILL LANDFILL
COLLECTIONFOR
INCINERATION
MSW INCINERATION
CREDITAGAINST
LOW
TRANSPORT TOREPROCESSOR
GLASSRECYCLING
TRANSPORTTO BRING
BANK
COLLECTIONFROM BRING
BANK
GLASS BOTTLES FROM HOUSEHOLD
SORTING
GLASS
BOTTLE
PRODUCTION
TRANSPORT
TO FILLERFILLING
TRANSPORT/
DISTRIBUTIONUSE
TRANSPORT
TO BRING
BANK
COLLECTION
FOR LANDFILL
COLLECTION
FROM
INCINERATION
COLLECTION
FROM BRING
BANK
SORTING
TRANSPORT
TO
RECYCLERS
RECYCLINGMATERIAL
CREDIT
LANDFILL
MSW
INCINERATION
WASHING
TRANSPORT
TO WASHING SORTINGTRANSPORT
TO SORTING
PROCESS TREE: GLASS BOTTLES RETURNABLE
REUSABLE
PLASTIC
CRATE
REUSE OF
PLASTIC
CRATES
RECYCLING
OF PLASTIC
CRATES
RETURN +
DEPOSIT
GLASS
BOTTLE
PRODUCTION
TRANSPORT
TO FILLERFILLING
TRANSPORT/
DISTRIBUTIONUSE
TRANSPORT
TO BRING
BANK
COLLECTION
FOR LANDFILL
COLLECTION
FROM
INCINERATION
COLLECTION
FROM BRING
BANK
SORTING
TRANSPORT
TO
RECYCLERS
RECYCLINGMATERIAL
CREDIT
LANDFILL
MSW
INCINERATION
PROCESS TREE: GLASS BOTTLES SINGLE TRIP
RECYCLING
OF
SECONDARY
PACKAGING
SECONDARY
PACKAGING –
CORRUGATED
BOARD
MATERIAL
CREDITS
PET BOTTLE
PRODUCTIONTRANSPORT
TO FILLERFILLING
TRANSPORT/
DISTRIBUTIONUSE
COLLECTION
FOR LANDFILL
COLLECTION
FROM
INCINERATION
SEPARATE
KERSIDE
COLLECTION
SORTING
TRANSPORT
TO
RECYCLERS
RECYCLINGMATERIAL
CREDIT
LANDFILL
MSW
INCINERATION
PROCESS TREE: PET BOTTLES SINGLE TRIP
RECYCLING
OF
SECONDARY
PACKAGING
SECONDARY
PACKAGING –
CARTONBOARD,
FILM
MATERIAL
CREDITS
PET BOTTLE
PRODUCTIONTRANSPORT
TO FILLERFILLING
TRANSPORT/
DISTRIBUTIONUSE
COLLECTION
FOR LANDFILL
COLLECTION
FROM
INCINERATION
SORTING
TRANSPORT
TO
RECYCLERS
RECYCLINGMATERIAL
CREDIT
LANDFILL
MSW
INCINERATION
WASHING
TRANSPORT
TO WASHING SORTINGTRANSPORT
TO SORTING
PROCESS TREE: PET BOTTLES RETURNABLE
PLASTIC
CRATES
REUSE OF
PLASTIC
CRATES
RECYCLING
OF PLASTIC
CRATES
SEPARATE
KERBSIDE
COLLECTION
RETURN +
DEPOSIT
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in theframe of the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International
May 01
Annex 2: Incineration and landfill models
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in theframe of the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International
May 01
1 NON SELECTIVELY COLLECTED MSW2 COLLECTION SYSTEM
The grey bag is collected
• twice a week in high population density areas and
• once a week in low population density areas.
Collection vehicle is a truck with a volume of 16m_.
Employment and internal costs were determined by Beture Environnement [46].
2 INCINERATION MODEL
Pira Int. developed the incineration model shown in Figure 1.
Figure 1 : Incineration model
Activated carbonOn Site
vehical
Waste to Incineration
hydrogen chloride as HCl
HCl Acid
Sodium Hydroxide
electricity to grid
fly ash
ammonia
bottom ash
Sludge/cake
Incineration (Paper &
Board)General
Waste water treatment
Energy Conversion
Use of Heat
HEAT, natural
gas
HEAT, Heating oil
Gas, natural, delivered,
Europe
Oil, heating,
low sulphur, Europe
Incinerator Capital
"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in theframe of the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International
May 01
2.1 Internal costs data
Allocation rules for the incineration cost
The allocation principle is to find a causal link between the waste composition and the incineration
cost.
The possible bases for the allocation are :
* The waste volume (or mass when only mass data are available and it is difficult to determine
the density) : to be used for the processes concerned when the waste is transported and stored
* The stoechiometric oxygen demand for full combustion (or fume volume or waste calorific
value) : to be used for the processes concerned when the waste produces heat and flue gas
* The waste inert content : to be used for the processes concerning the waste combustion
residues
* The pollutant concentration : to be used for the flue gas cleaning
Next tables give the allocation rules and the data and assumptions.
Annexes 1-2-3.doc
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Allocation baseA. Fixed cost
Construction
Reception, offices, waste pit mass
Furnace
grid mass
chamber stoichiometric oxygen demand for full combustion
Boiler, gas cleaning, chimney stoichiometric oxygen demand for full combustion
energy recovery (turbine, alternator) caloric value
Bottom ash extractor and treatment inert content
Magnetic separation Ferrous metal content
Eddy current separation Non ferrous metal content
Maintenance and replacement of pieces proportional to construction cost
Personnel proportional to construction cost
B. Variable costElectricity consumption stoichiometric oxygen demand for full combustion
Disposal of
Fly ash ash content
Boiler ash ash content
Bottom ash inert content
Gas cleaning residues
for acidic stage chlorine content
for basic stage sulphur content
activated carbon stoichiometric oxygen demand for full combustion
Consumption of additives
Activated carbon stoichiometric oxygen demand for full combustion
CaO for acidic stage chlorine content
CaO for basic stage sulphur content
Ammonia De-Nox stoichiometric oxygen demand for full combustion
C. Variable revenuesElectricity production calorific valueFerrous metals Ferrous metal contentNon Ferrous metals (Al) Non ferrous metal content
Cost Item
should be volume but very complicated to apply
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Incineration model - main data and assumptions
capacity 200.000 t/y Eurostaff 65 pers * 1.650.000 F 107.250.000 FB/y 2.658.658
Depreciation period 20 yearsinterest rate 6,0%
Fixed costReception, offices, waste pit 360.000.000 FB 8.924.167Furnace - grid 240.000.000 FB 5.949.445Furnace - chamber 360.000.000 FB 8.924.167Boiler, gas cleaning, chimney 1.480.000.000 FB 36.688.242energy recovery (turbine, alternator) 1.360.000.000 FB 33.713.519Bottom ash extractor and treatment 120.000.000 FB 2.974.722Magnetic separation 3.000.000 FB 74.368Eddy current separation 6.000.000 FB 148.736
Total 3.929.000.000 FB 97.397.366Variable cost
cost of treatment of dangerous waste (fly ash, gas cleaning residues) + landfilling class 1 6.000 FB/t 149amount of CaCl2.H2O + Ca(OH)2 generated 2,49 t residue / t Cl (CaCl2 + Ca(OH)2))stoechiometric coefficient (dictated by HCl) 1,65amount of CaSO4.1/2H2O generated for stoechiometry = 1 4,53 t CaSO4 / t Samount of Ca(OH)2 residue generated 1,50 t CaSO4 / t Samount of CaSO4 + Ca(OH)2 in landfill 6,03 t CaSO4 / t Ssale value of Fe recovered from bottom ash -587 FB/t Fe -15sale value of Al recovered from bottom ash -18.825 FB/t Al -467Ca(OH)2 cost 4.500 FB/t Ca(OH)2 112Ca(OH)2 use for acidic stage 1,72 t Ca(OH)2 / t ClCa(OH)2 use for basic stage 3,82 t Ca(OH)2 / t Scost of activated carbon 45.000 FB/ t act. carbon 1.116use of activated carbon 113 t act. Carbon /ycost of landfilling class 2 2.000 FB/t 50ammonia cost 3.654 FB/t 91ammonia use 114 t/yfly ash and boiler ash production 2,5% t/t MSWefficiency of electricity production (overall) 24,0%Internal electricity consumption -2,5% of low calorific valueefficiency of electricity production (net) 21,5%waste - low caloric value (positive) 10,2 GJ/tconversion factor 3,6 GJ/MWhelectricity sale price -1.500 FB/MWh -37production total 136.588 MWh/yInternal electricity consumption -14.228 MWh/ynet production 122.360 MWh/y
Specific flue gas volume (11% O2 dry) 6.000 Nm3/t (11% O2 dry)Inert content in MSW (including Fe and Al) 21% t inert/t MSW
bottom ash humidity 20% t water / t dry bottom ashFerrous metal content in MSW 2% t Fe / t MSWAl content in MSW 0,5% t Al / t MSWchlorine content 0,48% t Cl / t MSWsulphur content 0,075% t S / t MSWFe extraction rate from bottom ash 80% t Fe extracted / t Fe in MSW
Al extraction rate from bottom ash (only cans) 76%Electricity consumption for Fe extraction 0,007 MWh/t Fe extractedElectricity consumption for Al extraction 0,114 MWh/t Al extracted
t Al extracted / t Al in MSW(only cans)
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Therefore the costs are apportioned as follows :
Fixed cost Variablecost
Total cost Fixed cost Variablecost
Total cost
FB / t FB / t FB / t EURO / t EURO / t EURO / t
PVC 4.709 10.608 15.317 117 263 380
water 589 229 818 15 6 20
paper & board 4.230 718 4.948 105 18 123
glass 963 2.000 2.963 24 50 73
composites(LBC)
5.651 -31 5.619 140 -1 139
flexible Al 4.634 3.863 8.497 115 96 211
PE 10.918 -3.029 7.889 271 -75 196
PET 6.495 -2.532 3.963 161 -63 98
Fe 1.087 -69 1.017 27 -2 25
Rigid Al 1.950 -13.698 -11.747 48 -340 -291
PP 10.918 -3.449 7.469 271 -86 185
MSW 3.231 -138 3.094 80 -3 77
Sources :[69], [70], [71]
2.2 Environmental data
The incinerator modelled in this study assumes full compliance with current European
requirements for MSW incineration. In its original form the data assumed a set MSW mix.
The information summarised below has been use to allocate emissions between different
components of the waste stream:
• The allocation of CO2 emissions have been made on the basis of the carbon content of
the waste component
• The allocation of energy credits on the basis of the net energy yield of the waste
component
• The allocation of the bottom ash on the basis of the ash content of the waste component
• The allocation of the process related burdens, (e.g. NOx, SO2 & particulates) on the
basis of exhaust gas quantity
Annexes 1-2-3.doc
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• The allocation of waste independent burdens here assumed to include pre-treatment, on
site transport and burdens associated with the capital are allocated on a weight basis.
Main Assumptions
% Water2 %
Carbon1&2
% ash
Content3
Energy dry
weight)2
Exhaust Gas
(dry weight)4
Energy used
by water1
% % % MJ/kg kg/kg MJ/kg
Paper & board 24% 44% 8% 11 8 -480
Mixed Film 28% 85% 12% 22 24 -560
PE/PP Film 28% 86% 12% 31 24 -560
Rigid Plastic Mixed 10.50% 80% 7% 22 24 -210
PET 10.50% 58% 7% 22 14 -210
PE/PP 10.50% 86% 7% 31 24 -210
Ferrous metals 4.50% 0% 100% 0 -90
Aluminum (rigid) 12% 0% 100% -1 -240
Aluminum (foil) 12% 0% 189% 25 6 -240
Glass 2.50% 0% 100% -1 -50
Composite
beverage
24% 49% 17% 15 11 -482
1 Calculated2 sourced from Life Cycle Inventory Development for Waste Management Operations: Incineration, R&D Project Record P1/392/6,for the UK Environment Agency3 sourced from Integrated Waste Management, A Life Cycle Inventory, PR White, M Franke and P Hindle, 19954 from information supplied by RDC
3 LANDFILL MODEL
3.1 Internal costs
The landfill is operated in line with the landfill directive of April 26, 1999 (EC/1999/31).
The main environmental impact is the disamenity. The disamenity caused by waste is
assumed to be proportional to the waste volume.
The landfill costs (50 EURO/t of MSW) are also allocated proportionally to the waste
volume. The waste density is assumed to be the same as the bales density after sorting as
both are crushed.
Annexes 1-2-3.doc
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The costs are :
Density Cost Costkg/m3 EURO/t EURO/m3
MSW 700 50 35steel 800 43.75 35aluminium 200 175 35PET bottles 250 140 35LBC 500 70 35paper & board 500 70 35
3.2 Environmental data
The data used in this study is based on data generated in a study for the UK environment
agency. The landfill considered is fully lined with active gas management, energy
generation and an on site biological effluent treatment plant.
The model assumes that roughly one third of the landfill gas generated over the life time of
the site is flared, with one third being burnt for energy generation and one third lost to
atmosphere. The losses to atmosphere mainly occur during loading and after the active gas
management of the site has ceased. Leachate in this study has been assumed to be related to
moisture content, Alternative allocations have not been considered due to the low
significance of the leachate emissions for packaging related systems.
Dry quantity % Water Land Fill Gas Leachate Residual waste
% kg Kg kg
Paper & Board 1000 24% 913 316 87
Plastic Film 1000 28% 0 389 1000
Rigid Plastic 1000 10.50% 0 117 1000
Ferrous metals 1000 4.50% 0 47 1000
Non Ferrous Metals 1000 12% 0 136 1000
Glass 1000 2.50% 0 26 1000
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Annex 3: Internal cost data
Annexes 1-2-3.doc
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Costs for Landfilling 1 tonne PET bottles
Euro per tonne of packaging Collection costs Landfill costs Total internal costs
High population density 294 140 434
Low population density 234 140 374
Costs for Landfilling 1 tonne steel packaging
Euro per tonne of packaging Collection costs Landfill costs Total internal costs
High population density 88.2 43.8 132
Low population density 68.4 43.8 112.2
Costs for Landfilling 1 tonne rigid and semi - rigid aluminium packaging
Euro per tonne of packaging Collection costs Landfill costs Total internal costs
High population density 490 175 665
Low population density 380 175 555
Costs for Landfilling 1 tonne paper & board packaging
Euro per tonne of packaging Collection costs Landfill costs Total internal costs
High population density 78.8 70 148.8
Low population density 61.1 70 131.1
Costs for Landfilling 1 tonne Liquid Beverage Cartons
Euro per tonne of packaging Collection costs Landfill costs Total internal costs
High population density 126 70 196
Low population density 98 70 168
Costs for Landfilling 1 tonne mix plastics packaging
Euro per tonne of packaging Collection costs Landfill costs Total internal costs
High population density 294 140 434
Low population density 228 140 368
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Costs for Incineration of 1 tonne PET bottles
Euro per tonne ofpackaging
Collection costs Incineration –fixed costs
Incineration –variable costs
Total internalcosts
High pop. density 294 161 -63 392
Low pop. density 228 161 -63 326
Costs for Incineration of 1 tonne steel packaging
Euro per tonne ofpackaging
Collection costs Incineration –fixed costs
Incineration –variable costs
Total internalcosts
High pop. density- no slag recovery
88.2 73* 161.2
High pop. density- slag recovery
88.2 27 -2 113.2
Low pop. density- slag recovery
68.4 73* 141.4
Low pop. density- slag recovery
68.4 27 -2 93.4
Costs for Incineration of 1 tonne rigid and semi-rigid aluminium packaging
Euro per tonne ofpackaging
Collection costs Incineration –fixed costs
Incineration –variable costs
Total internalcosts
High pop. densitywith no slagrecovery
490 73* 563
High pop. densitywith slagrecovery (cans)
490 48 -340 198
High pop. densitywith slagrecovery(rigid/semi rigid)
490 48 -206 332
Low pop. densitywith no slagrecovery
380 73* 453
Low pop. densitywith slagrecovery (cans)
380 48 -340 88
Low pop. densitywith slagrecovery(rigid/semi rigid)
380 48 -206 222
Annexes 1-2-3.doc
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Costs for Incineration of 1 tonne Paper & Board packaging
Euro per tonne ofpackaging
Collection costs Incineration –fixed costs
Incineration –variable costs
Total internalcosts
High pop. density 78.8 105 18 201.8
Low pop. density 61.1 105 18 184.1
Costs for Incineration of 1 tonne Liquid Beverage Cartons
Euro per tonne ofpackaging
Collection costs Incineration –fixed costs
Incineration –variable costs
Total internalcosts
High pop. density 126 140 -1 265
Low pop. density 98 140 -1 237
Costs for Incineration of 1 tonne mix plastics packaging
Euro per tonne ofpackaging
Collection costs Incineration –fixed costs
Incineration –variable costs
Total internalcosts
High pop. density 294 271 -75 490
Low pop. density 228 271 -75 424
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Costs for Recycling 1 tonne of PET bottles via separate kerbside collection
Collection costs (Europer tonne of PET bottlesrecycled)
Sorting costs (Europer tonne of PETbottles recycled)
Transport from sorting plantto reprocessor (Euro pertonne of PET bottlesrecycled)
Reprocessing cost (Europer tonne of output)
Revenue received forreprocessed material
Total internal cost per tonnePET bottles recycled
High pop. density 255 474 46 332 -540* 566Low pop. density 306 474 46 332 -540 618*corresponding to a 540-332-46 = 162 EURO/t at the outlet of the sorting plant. This value is representative for the 2001 market situation. It issupposed to be more representative of the situation in 2006 than the average value over the last years (1998-2000) because the market has not beenstable and prices did not reflect the real cost in an efficient market.
Costs for Recycling 1 tonne PET bottles via bring bank collection
Transport costs from bringbank to sorting plant (Europer tonne of PET bottlesrecycled)
Sorting costs (Europer tonne of PETbottles recycled)
Transport from sortingplant to reprocessor (Europer tonne of PET bottlesrecycled)
Reprocessing cost (Europer tonne of output)
Revenue received forreprocessed material
Total internal cost per tonnePET bottles recycled
High pop. density 196 474 46 332 -540 508Low pop. density 242 474 46 332 -540 553
Costs for Recycling 1 tonne of steel packaging via separate kerbside collection
Euro per tonne of steel recycled Collection costs Sorting costs Transport from sorting plant to reprocessor Revenue received for material ready for use in steelproduction
Total internalcost
High population density 83.5 75.4 22.9 -34 147.8Low population density 100.5 75.4 22.9 -34 164.8
Costs for Recycling 1 tonne steel packaging via bring bank collection
Euro per tonne of steel recycled Transport costs from bringbank to sorting plant
Sorting costs Transport from sorting plant toreprocessor
Revenue received for material ready for use in steelproduction
Total internalcost
High population density 64.4 75.4 22.9 -34 128.7Low population density 79.2 75.4 22.9 -34 143.5
Annexes 1-2-3.doc
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Costs for Recycling 1 tonne of rigid and semi-rigid aluminium packaging via separate kerbside collection
Euro per tonne of aluminium sorted Collection costs Sorting costs Transport from sorting plant to reprocessor Revenue received for material ready for use inAl production
Total internal cost
High population density 178.3 571.9 53.4 -316 487.6Low population density 214.6 571.9 53.4 -316 523.9
Costs for Recycling 1 tonne rigid and semi-rigid aluminium packaging via bring bank collection
Euro per tonne ofaluminium sorted
Transport costs from bringbank to sorting plant
Sorting costs Transport from sorting plant to reprocessor Revenue received for material ready for use inAl production
Total internal cost
High population density 137.4 571.9 53.4 -316 446.7
Low population density 169.1 571.9 53.4 -316 478.4
Costs for Recycling 1 tonne of Paper & Board packaging via separate kerbside collection
Euro per tonne of paper & board Collection costs Sorting costs Transport from sorting plant to reprocessor Revenue received for baled paper Total internal cost
High population density 41.2 35 22.9 -21.6 77.5Low population density 49.6 35 22.9 -21.6 85.9
Costs for Recycling 1 tonne Paper & Board packaging via bring bank collection
Euro per tonne of paper &board
Transport costs from bring bank tosorting plant
Sorting costs Transport from sorting plant toreprocessor
Revenue received for baled paper Total internal cost
High population density 34 35 22.9 -21.6 70.3Low population density 41 35 22.9 -21.6 77.3
Annexes 1-2-3.doc
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Costs for Recycling 1 tonne of Liquid Beverage Cartons via separate kerbside collection (incineration of rejects)
Euro per tonne ofLBC sorted
Collection costs Sorting costs Transport fromsorting plant toreprocessor
Revenues frombales
Reprocessingcosts
Revenues frompaper product
Costs - revenues ofincineration of rejects (euro/trejects)
Total internal cost
High pop. density 146.2 302.3 22.9 -20 433 -455 57 486.4Low populationdensity
175.9 302.3 22.9 -20 433 -455 57 516.1
Costs for Recycling 1 tonne Liquid Beverage Cartons via bring bank collection (incineration of rejects)
Euro per tonne ofLBC sorted
Transport costs frombring bank to sortingplant
Sortingcosts
Transport from sortingplant to reprocessor
Revenues frombales
Reprocessingcosts
Revenues frompaper product
Costs - revenues ofincineration of rejects(euro/t rejects)
Total internalcost
High pop. density 112.6 302.3 22.9 -20 433 -455 57 452.8Low pop. density 138.6 302.3 22.9 -20 433 -455 57 478.8
Costs for Recycling 1 tonne of Liquid Beverage Cartons via separate kerbside collection (landfilling of rejects)
Euro per tonne ofLBC sorted
Collectioncosts
Sortingcosts
Transport from sortingplant to reprocessor
Revenues fromrecycling
Reprocessingcosts
Revenues from paperproduct
Costs - revenues oflandfilling of rejects(euro/t rejects)
Total internalcost
High populationdensity
146.2 302.3 22.9 -20 433 -455 38.2 467.6
Low populationdensity
175.9 302.3 22.9 -20 433 -455 38.2 497.3
Costs for Recycling 1 tonne Liquid Beverage Cartons via bring bank collection (landfilling of rejects)
Euro per tonne ofLBC sorted
Transport costs frombring bank to sortingplant
Sortingcosts
Transport from sortingplant to reprocessor
Revenues fromrecycling
Reprocessingcosts
Revenues from paperproduct
Costs - revenues oflandfilling of rejects(euro/t rejects)
Total internalcost
High pop. density 112.6 302.3 22.9 -20 433 -455 38.2 434Low pop. density 138.6 302.3 22.9 -20 433 -455 38.2 460
Annexes 1-2-3.doc
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Costs for Recycling 1 tonne of mix plastics packaging via separate kerbside collection (mechanical recycling)
Euro per tonne of mix plastics sorted Collection, sorting, transport 1 Processing & transport 2 Overhead Revenue Total internal cost
High population density 1227 354 73 0 1654
Low population density 1227 354 73 0 1654
Costs for Recycling 1 tonne mix plastics packaging via separate kerbside collection (feedstock recycling)
Euro per tonne of mix plastics sorted Collection, sorting, transport 1 Processing & transport 2 Overhead Revenue Total internal cost
High population density 1227 354 73 0 1654
Low population density 1227 354 73 0 1654
Annexes 4-5-6.doc
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Annex 4: Economic valuations applied – sources
and derivation
Annexes 4-5-6.doc
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1 INTRODUCTION
The cost benefit analysis methodology used in the study is based on a life cycle assessment
to determine the environmental impacts of the selected systems, and economic valuation to
convert these environmental impacts into monetary values. The underlying characterisation
tables used are included in Table 1 (annex 4bis). Table 2 (annex 4bis) contains data on a
range of valuation and moneterisation methods, including the values applied in this study.
The environmental costs and benefits are summed to determine the total externality.
In parallel to this, the internal costs of the system are determined. The internal costs of the
system are the total costs minus the total revenues.
The externalities and internal costs of the system are summed to determine the total social
cost of the system.
The detail of determining environmental costs is discussed in the sections below.
The economic valuations applied in this study have been sourced by Pieter van Beukering
of IVM (Institute for Environmental Studies, University of Amsterdam) unless otherwise
indicated. The economic valuations have been sourced from a variety of reports and
documents. As far as possible, damage cost values are applied. However, where necessary
prevention costs have been used.
2 ENVIRONMENTAL IMPACTS
LCA is used to determine the environmental impacts of the system. The quantitative life
cycle inventory is generated. Characterisation and classification is then applied to the
inventory data. Characterisation assigns each environmental input and output (the
inventory data) to the environmental impacts to which it may potentially contribute.
Classification then applies a weighting factor according to the potential level of impact
relative to a specific reference emission. For example, the reference emission for global
warming is CO2. The weighting applied to CO2 is therefore 1. All other emissions which
Annexes 4-5-6.doc
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contribute to CO2 are weighted relative to their CO2 equivalence. For example, the effect
of global warming caused by a 1kg emission of methane is 21 times greater than the effect
caused by 1kg of CO2. Therefore methane is given a classification of 21.
The impact assessment data is then converted to monetary values through the application of
economic valuations to each individual impact category. The impact categories considered
and the impact assessment methodology applied have been developed with a consideration
of the needs of the economic valuations then applied. In some cases, this influences the
type of inventory data that is required in order to make a complete external economic
analysis.
The sections below and accompanying tables detail the classification values and economic
valuations applied.
2.1 Global warming
Global warming is characterised in CO2 equivalents. The classification values applied -
Time Horizon 100 years - are taken from figures given in Climate Change 1995
(Contribution of WG1 to IPPC second assessment report). The two principal contributors to
this category are carbon dioxide and methane with a GWP of 1 and 21 respectively.
The valuation stage is based on the most recent estimates from the FUND II model (Tol
and Downing 2000, FUND2 model, forthcoming).
Tol and Downing report the following marginal damages expressed per tonne of carbon (tC
not tCO2):
Pure time preference rate = 0% $75
Pure time preference rate = 1% $46
Pure time preference rate = 3% $16
Applying a 5% pure time preference rate, a value for GWP of US$46 tC, or US$12.5tCO2
(converted to 13.44 Euro per tonne CO2) is considered for this study.
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As global warming is not site specific, the emissions from different processes can be
directly summed. Overlap with other environmental effects can be ignored. One issue of
potential importance is that of the time horizon over which the emissions occur (i.e. in
incineration immediately and in landfill over many years). This issue has not been
addressed directly in the method applied, however previous studies suggest that application
of a time dependant analysis is of low significance. Where global warming is critical in the
results and time issues might be significant then the issue will be addressed in sensitivity
analysis.
New classification figures are due to be released shortly from the IPPC’s Third assessment
report but these were not available in time to be included in this study.
2.2 Ozone depletion
This category is typically unimportant for packaging waste systems, it is quantified in CFC
11 equivalents : The classification values applied are based on those in Climate Change
1995 and are listed in Annex 4 bis. The economic valuation applied to the impact
assessment data is 680 Euro per tonne of CFC 11 equivalents. This is based on an estimated
cost, associated with increased radiation, of 177 billion dollars and cumulative emissions of
an estimated 200 billion kg and should be considered as very approximate. This value has
been derived by Pira International specifically for inclusion in this study.
2.3 Human toxicity (Carcinogens)
Toxicity (carcinogens) refers to carcinogenic airborne emissions. Toxicity (carcinogens) is
quantified in Cd equivalents. The classification values applied to carcinogenic emissions
are listed in Annex 4 bis. The economic valuation applied to the impact assessment data is
22 140 Euro per tonne of Cd equivalents. This value is the average of the range of damage
costs reported by Dorland et al, 2000. The range reported is 5774 – 38498 Euro per tonne.
The range applies to damages to human health by emissions of cadmium arising from
production processes and electricity production.
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2.4 Human toxicity (Smog)
Toxicity (smog) relates to the production of ozone in the troposphere and is characterised in
Ethylene equivalents based on the values developed by Harwell Laboratories (Derwent &
Jenkin, 1990). NOx which also contributes to the formation of low level ozone is given a
value equivalent to 1.19kg ethylene/kg. The classification values applied to emissions that
contribute to Toxicity (smog) are listed in Annex 4 bis.
The economic valuation applied to the impact assessment data is 734 Euro per tonne of
Ethylene equivalents. The valuation is for VOC indirect impacts through ozone formation,
as reported in Dorland et al, (2000). The value refers to damages to human health by
emissions of production processes and electricity generation.
2.5 Human Toxicity (particulates)
Toxicity (particulates) refers to airborne emissions typically generated and measured
directly, such as PM10 or indirectly through the production of aerosols (Sulphate &
Nitrate). Toxicity (particulates) is measured in PM10 equivalents. The classification values
applied to emissions that contribute to Toxicity (particulates) are listed in Annex 4 bis. The
economic valuation applied to the impact assessment data is 23686 Euro per tonne of PM10
equivalents, as reported in Dorland et al, (2000). This value is for emissions of PM10
(directly emitted). The value refers to damages to human health by emissions arising from
production processes and electricity generation.
2.6 Human toxicity (Other air)
Toxicity (Other air) refers to airborne emissions which have toxic effects, other than
carcinogenic effects or effects caused by smog or particulates. Toxicity (other air) is
quantified in SO2 equivalents. The classification values applied to emissions that
contribute to this category are based on their relative human toxicity value and are listed in
Annex 4 bis.
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The economic valuation applied to the impact assessment data is 1002 Euro per tonne of
SO2 equivalents. This value is non-specific and based on general non-transport related
emissions. Should this category prove important then a sensitivity analysis will be
conducted to consider the significantly higher burden associated with SO2 emitted from
vehicles (over 2000 Euro/tonne).
2.7 Acidification
Acidification is quantified in Acid equivalents (H+). The classification values applied to
emissions that contribute to acidification are listed in Annex 4 bis. The economic valuation
applied to the impact assessment data is 8.7 Euro per kg of Acid equivalents equivalent to
0.27 Euro/kg of SO2. This value excludes the costs due to damage to buildings but includes
damage to crops, forestry and lakes (see Table 1).
Table 1
Crop Damage
Dorland et al. (2000)
Forests
(EC 1995)
Lakes
(EC 1995)
Total
0.215 0.036 0.015 0.27/kg SO2
= 8.7/kg H+ equiv.
2.8 Damage to structures
Damage to structures refers to soiling of buildings caused by black smoke. The definition
of black smoke is based on chemical properties of particles rather than on particle size, so
the size composition of black smoke can vary considerably. However, roughly speaking
black smoke consists of particles with a diameter of less than 15µm.
Damage to structures is measured in dust equivalents: The classification values applied to
emissions that contribute to Damage to structures are listed in Annex 4 bis. The economic
valuation applied to the impact assessment data is 662 Euro per tonne of dust equivalents.
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This value is sourced from Dorland et al 2000 who determine a damage cost of 662 Euro
per tonne of particulate emitted in the form of black smoke. This value is calculated by
Pieter van Beukering, estimated based on the total UK emissions of black smoke and an
assessment of the size of the UK market for cleaning buildings that is completely
attributable to soiling from particle pollution (as reported in Newby et al 1991).
In the methodology applied in this analysis, no distinction is made between emissions
arising from processes and emissions arising from transport.
2.9 Fertilisation
Deposited nitrogen has a beneficial effect on crop yields because it acts as a fertiliser. The
level of this externality is determined by the value of the yield increase due to the deposited
nitrogen. Pieter van Beukering provides a value of –697 Euro per tonne of NOx (expressed
as NO2 mass equivalents). It is uncertain whether these fertilisation effects are sustainable
in the long term.
The classification values applied to emissions that contribute to Fertilisation are listed in
Annex 4 bis.
2.10 Traffic accidents
The economic valuation applied to traffic accidents in this study has been calculated by
Pira International specifically for this project.
Traffic accidents is quantified in Car km equivalents. The classification values applied to
different road types are listed in Annex 4 bis and based on UK transport statistics. Little
evidence was found in these statistics of a difference between HGV/Commercial vehicles
and passenger cars in terms of the accidents or deaths/km driven (see Table 2).
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Table 2
Rate of Serious & Fatal Accidents/ 100 million vehicle km
Car 12
Light Van 10
Goods Vehicle 12
Road type however is significant - motorways being considerably safer. The higher value
for rural roads seems counter intuitive - however Rural roads are defined here as roads with
a speed restriction above 40 mph (~64 km/h). The overall accident rate goes counter to this
with urban roads having a rate more than twice as high. (See Table 3)
Table 3
Fatalities1999
SeriousAccidents
Total roadtraffic billionvehicle km
Deaths/billionvehicle km
SeriousAccidents /billionvehicle km
Characterisation(fatalityequivalent)
Characterisation- Seriousaccidentequivalent.
Motorway 176 1218 83.6 2.1 14.6 0.31 0.19
Urban 1338 23011 200.2 6.7 114.9 1.00 1.47
Rural 1621 12176 183.3 8.8 66.4 1.32 0.85
All 3135 36405 467.1 6.7 77.9 1.00 1.00
The methodology assumes that the average European situation follows the UK situation
and uses the characterisation values above to combine the different road types.
The serious accident figures are being excluded; firstly because the low valuation of injury
versus fatality means that it becomes insignificant and secondly because there is a risk of
double counting as the statistics for serious accidents include accidents, which led to
fatalities.
The economic valuation applied to the impact assessment data is 16.9 Euro per 1000 km
travelled on an average road.
2.11 Traffic congestion
The external costs of congestion result from various effects. The most important costs are
the time costs of delay. Indirect effects include increased emissions levels and danger in
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traffic. Traffic congestion is quantified in Car km equivalents with a HGV or van
equivalent to 2 cars. The differentiation between road types is based on UK data. The
classification values applied are listed in Annex 4 bis. The economic valuation applied to
the impact assessment data is 85.5 Euro per 1000 car km equivalents.
Brossier (1996) estimates the marginal congestion costs of trucks averaged over a year on
“National roads” at 17.1 Euro per 100 HGV km. No description of the term “national
roads” is provided, but assuming that this refers to a typical UK A road (rather than an
urban road) this gives an economic value of 8.55 Euro per 100 car km equivalents.
2.12 Traffic Noise
Noise is any unwanted sound. The main source of noise in recycling systems is transport
and disposal sites. The noise externality of landfill sites is included in the disamenity value
of landfilling (Section 2.14), so the focus of this impact category is transport related noise.
In many EU countries, transport is the most pervasive source of noise in the environment
(Houghton 1994).
It is difficult to relate noise or noise nuisance to a parameter that is quantifiable in a life
cycle study. The impact pathway is complex with many influencing factors. However, as
waste disposal and recycling activities involve a considerable amount of transport. The
disamenity of noise from transport cannot be neglected. Therefore, an attempt to quantify
this important impact has been made for the purposes of this study.
Two types of noise exist:
♦ Acute noise – arising from the operation of heavy machinery, and therefore mainly
related to occupational health
♦ Nuisance noise – less sudden noise, such as that experienced by people living near a
main road or rail track. The effects can include impairment of communication, loss of
concentration and loss of sleep.
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The actual damage of noise has three forms:
♦ Property value reductions
♦ Productivity loss resulting due to medical complaints of workers
♦ Damage to ecosystems (frightened wildlife)
An overview of available hedonic and contingent valuations is presented in Table 4.
Table 4 : Summary of studies on the WTP to halve the noise exposure level
Study Hedonic valuation (in Euro) Contingent valuation (in Euro)
Pommerehne (1988) 51 46
Iten and Maggi (1988) 43 -
Willeke et al (1990) - 81
Soguel (1994) 37 35-42Source: Soguel 1994
Even though two different techniques are applied, the estimates are within the same range.
Assuming a linear relationship between WTP and noise exposure, the average WTP for a
reduction of noise exposure is 3.8 Euro per dB(A).
Kageson (1993) determines the noise costs for road transport at 2-3 Euro per 1000 km and
passenger km, and rail transport at 0.5 – 0.7 Euro per 1000 km.
For this study, “Traffic noise” is quantified in Car km equivalents, using the economic
value of 3 Euro per 1000 car km equivalents. The classification values applied to different
transportation modes are listed in Annex 4 bis.
2.13 Water Quality – Eutrophication
Several difficulties exist in transferring the external effects of surface water pollution for
externalities occurring in recycling processes. Firstly, most values are presented in an
aggregated manner, whereas waste related and recycling processes are valued on a marginal
basis. Secondly, transferability is hampered by demographic differences. Most water
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pollution studies have been conducted in Scandinavian countries. Thirdly, the type of
water pollution may differ from the type of water contamination. Forth, there remains a
lack of reliable dose-response function information.
In this study, Water Quality – Eutrophication is quantified in P equivalents. The
classification values applied to water borne emissions that contribute to Eutrophication are
listed in Annex 4 bis. The economic valuation applied to the impact assessment data is
4700 Euro per tonne P equivalents. This is derived from Gren et al (1996), and is based on
the costs of increased abatement capacity at sewage or industrial plants necessary to reduce
these emissions.
2.14 Disamenity
Disamenity effects of waste management processes are likely to make up a significant share
of the externalities caused. In particular, landfill sites and incineration facilities generate
substantial social costs to their neighbouring population. The disamenity may take a
number of forms:
♦ Increased traffic noise (see Section 2.12 for details of valuation applied)
♦ Increased traffic congestion (see Section 2.11 for details of valuation applied)
♦ Odour and visual pollution
♦ (Perceived) increased health risk
A common approach to determine disamenity effects is to use variations in house prices
(hedonic price method). In this study, the externality of increased traffic noise and
congestion are valued separately. Changes in house price are assumed to relate to odour
and visual disamenity only, as these aspects are not valued elsewhere in the methodology.
It should be highlighted that this approach may lead to potential double counting of some of
the externalities.
Several hedonic price method studies on the value of disamenity effects of landfill have
been performed. Landfilling and incineration produce different effects, and therefore
should be assigned different externalities. Households are reluctant to live near an
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incinerator due to the perceived health effects of emissions. Disamenity of landfill is
caused by the perception of groundwater pollution, and the visual pollution and odour
nuisance. However, as no valuation data have been found to distinguish between their
waste management practices the overall disamenity value for landfilling and incineration
has been assumed to be equal.
All studies identify a significant house price reduction due to the existence of waste sites
nearby. House prices increase approximately 3-4% per kilometre distance from a landfill
site, within a radius of approximately 5.5 km.
Similarly, Contingent valuation studies demonstrate that WTP1 declines with distance to
the facility. An important determinant of WTP is income and perception of the risk of
leachate pollution of water supplies. Households with a high income whose water supplies
were at risk are willing to pay substantially more than low-income households dependent
on piped city-water. However, the CVM2 findings are generally consistent with the
findings of the HPM3.
Based on the literature, the following linear regression equation is determined (Brisson and
Pearce 1995): ∆ HP = 12.8 – 2.34 * D
(∆ HP = the percentage change in house price, D = distance in km from facility)
This suggests a maximum house price depreciation of 12.8% at the site of the facility, with
no price differential beyond 5.5 km.
Based on the disamenity function, the annual value of reduction in the real estate prices can
be calculated. Graph 1 shows how this varies substantially considering five categories of
household density and five levels of average house price. The overall values are converted
to annual values by taking 8% of the total reduction.
1 Willingness To Pay2 Contingent Valuation Method
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Graph 1
To link variations in the life cycle and economic valuation, external costs are then
calculated on a per unit basis. This step in the analysis is uncommon – in reality the
disamenity is not determined by the quantity of waste processed by the facility, but by the
simple existence of the facility. However, to facilitate a link disamenity value is assumed
to be proportional to the total amount of waste processed. Values reported in the literature
vary from 1.2 Euro per tonne for a study relating to landfilling in Minnesota (IIED 1996) to
10.6 Euro per tonne for a study in Milan, Italy (Ascari and Cernischi 1996). These
differences may arise due to the processing capacities of the facilities.
Table 5 determines the annual disamenity value of 1 tonne of landfilled and incinerated
solid waste. However, due to the potential influence of the simplifying assumptions, such
as the uniform disamentiy value for landfill and incinerator, and the neglect of income
elasticity, these values should be treated with caution. Ideally, the values should be
determined on a marginal basis and considering local circumstances such as average house
price, population density and processing capacity.
3 Hedonic Price Method
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Table 5 : Calculation of disamenity valuation per tonne of solid waste
Annual processingcapacity (ton / annum)
Total disamenity(million Euro)***
Disamenity per unit ofwaste (Euro per tonne)
Landfill* 200000 7.4 37
Incinerator** 730000 7.4 10* Total capacity estimated at 4 million tonnes over 20 year life time** Total capacity estimated at 10 million tonnes over a 14 year life time*** Based on an average house price of Euro 100000 and a density of 250 houses per km2
2.15 Heavy metals (airborne)
An accurate valuation is not available for this category. However a crude approximation
has been generated by Pira International specifically for this study, by dividing the
estimated total damage cost by the total emissions. Dubourg (1996) estimates that airborne
Pb was responsible for 62 deaths in England & Wales in 1987. Taking this figure and
multiplying by 3.1 million Euro (the value for a statistical life assumed for this calculation)
gives us a total cost of 192.2 million Euro. Another publication (The Environment in
Europe and North America, Annotated Statistics 1992, Economic Commission for Europe,
United Nations Publication) gives the total emissions of lead in the UK as 3100 tonnes in
1988. This gives us an economic value of 62 Euro/kg of Pb emitted.
2.16 Employment
Standard economic theory says that it is not possible to create a job without displacing
other employment. The argument is that for every job that is created, some other job is lost
– the reason being that economics assumes full employment in the economy. Any one not
in employment is in a transitional stage between one job and another, rather than being
“involuntarily unemployed”, and has therefore internalised the costs of unemployment in
their decision-making. If you now create a job for this person in recycling, it means that
this person is now not available for the job he/she would have taken if this job hadn’t been
created. There is therefore no social value in creating employment.
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However, the fact is that a proportion of the unemployed in Europe are not unemployed
voluntarily (i.e. they are not in a transitional stage, and have not internalised the costs of
unemployment in a decision). In such a case, the unemployment represents a social cost. If
such involuntary unemployment represents a significant and long-term proportion of the
total unemployment, then it may be argued that employment creation policies will have a
positive social impact and employment should have an economic valuation.
Table 6 presents unemployment rates in the EU for May 2000. For some Member States
high unemployment rates are experienced. This may include long-term involuntary
unemployment, and therefore an economic valuation of employment could be appropriate.
Thus, for this study, an economic valuation for employment is included in the sensitivity
analysis. The economic valuation applied is 2945 Euro per job per annum. This value
has been derived by RDC-Environment specifically for this study, and is based on the
economic support to job creation in Belgium. It is the value of the reduction of social
security taxes for newly employed workers in Belgium (law of 1999-03-26).
Table 6 :Unemployment rates in Europe (as at May 2000)
Country %
Austria 3.2
Belgium 8.4
Denmark 4.7
Finland 9.5
France 9.8
Germany 8.4
Greece No data
Ireland 4.7
Italy 10.7*
Luxembourg 2.2
Netherlands 3.0*
Portugal 4.5
Spain 14.3
Sweden 6.1
UK 5.7*** as at April 2000
** as at March 2000
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3 ALTERNATIVE ECONOMIC VALUATIONS
Economic valuation and cost benefit analysis are developing disciplines. Different
practitioners apply different economic valuations. Some alternative economic valuations
are list in annex 4 bis.
4 REFERENCES
Ascari, S and S Cernischi (1996) Integration of pollutant dispersion modelling and hedonoc
pricing techniques for the evaluation of external costs of waste disposal sites. In: A
Baranzini and F Carlevaro (eds) Econometrics of Environment and Transdisciplinarity
(Volume I). Preceeding of the LIst International Conference of the Applied Econometrics
Association (AEA), Lisbon, April 1-12 1996, 156-173
Brisson IE and D Pearce (1995) Benefits transfer for Disamenity from Waste Disposal. .
CSERGE Working Paper WM95-06. London, Centre for Social and Economic Research of
the Global Environment (CSERGE), University College London
Brossier, C (1996) Mise a jour de l’etude de l’implication des couts d’infrastrucre de
transports, Report for the Ministry of Transport, Paris
Derwent & Jenkin, 1990
Dorland C, AQA Omtzight and AA Olsthoorn (2000), Marginal Costs – The Netherlands,
In: R Friedrich and P Bickel (eds), External Environmental Costs of Transport, University
of Stuttgart
Gren, I-M, T Soderqvist, F Wulff, S Langrass and C Folke (1996) Reduced nutrient loads
to the Baltic Sea: Ecological consequences, costs and benefits. Beijer Discussion Paper
Annexes 4-5-6.doc
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Series No 83, Beijer International Institute of Ecological Ecomonics, The Royal Swedish
Academy of Science, Stockholm
Houghton, Sir John (1994) Eighteenth Report Transport and the Environment, Royal
Commission on Environmental Pollution. HMSO, London
IIED (1996), Towards a Sustainable Paper Cycle, International Institute for Environment
and Development / World Business Council for Sustainable Development, London
Intergovernmental Panel on Climate Change (1995) Climate Change 1995 The science of
Climate Change, Contribution of Woking Group 1 to the Second Assessment Report of the
Intergovernmental Panel on Climate Change, Cambridge University Press
Kageson (1993) Getting the Prices Right: a European Scheme for Making Transport Pay
its True Costs. European Federation of Transport and the Environment, T&E 93/6,
Stockholm
Newby P T, T A Mandfield and RS Hamilton (1991) Sources and economic implications of
building soiling in urban areas, The Science of the Total Environment, 100, 347
Newbery, DM (1995) Royal Commission Report on Transport and the Environment:
Economic Effects of Recommendations, The Economic Journal. Sept, Oxford, UK
Soguel N, (1994) Measuring benefits from traffic noise reduction using a contingent
market. CSERGE Working Paper WM94-03. London, Centre for Social and Economic
Research of the Global Environment (CSERGE), University College London
R Tol and T Downing, (2000) The Marginal Cost of Climate Changing Gases, Paper 00-08,
Institute for Environmental Studies, Free University of Amsterdam.
Annex 4 bis Appendix 1 - Characterisation Tables
Burden Name: Multiplier: Notes:
GWP (kg CO2 eq.)carbon tetrachloride -225CFC (unspecified) 1320 assumed as CFC-11CFC-11 1320CO2 (non renewable) 1CO2 (renewable) 1CO2 (unspecified) 1dichloromethane 9haloginated HC (unspecified) 4halon -1301 -49750halons (unspecified) -49750 assumed as halon-1301HCFC (unspecified) 1350 assumed as HFC-22HCFC-22 1350hexafluoroethane 9200HFC (unspecified) 1000methane 21N2O 310tetrafluoromethane 6500tetrafluroethylene 1300trichloroethane -1525trichloromethane 4
Ozone depletion (kg CFC 11 eq.)carbon tetrachloride 1.08CFC (unspecified) 1 assumed as for CFC 11CFC-11 1halon -1301 16halons (unspecified) 0.14 assumed as for Halon-2311HCFC (unspecified) 0.055 assumed as for HCFC 22HCFC-22 0.055trichloroethane 0.12
Acidification (Acid equiv.)acid as H+ (waterborne) 1HCl 0.02743484HF 0.050005NH3 0.02941176NOx 0.01086957SO2 0.03125
Toxicity Carcinogens (Cd equiv)acetaldehyde 0.0000016 acetaldehyde aromatics (unspecified) 0.000019 assumed as benzeneAs 0.18 Arsenic As (soil) 0.098 Arsenic (ind.) As (waterborne) 0.49 Arsenic benzene 0.000019 benzene benzene (waterborne) 0.000031 benzene benzo(a)pyrene 0.029 benzo(a)pyrene benzo(a)pyrene (waterborne) 22butadiene 0.00012 1,3-butadiene carbon tetrachloride 0.0062 carbontetrachloride Cd 1 Cadmium Cd (soil) 0.029 Cadmium (ind.) Cd (waterborne) 0.53 Cadmium Cr (IV) 13 assumed as Cr (6+)Cr (unspecified) 13Cr (unspecified) (soil) 2 Chromium (ind.) Cr (unspecified) (waterborne) 2.5 as Cr IVCr-VI (waterborne) 0.029 Chromium (VI) dichloroethane 0.00022 1-2 dichloroethanedichloromethane 0.0000032 dichloromethane dioxins and furanes (unspecified) 1300 assumed as 2,3,7,8-TCDD Dioxinethylene oxide 0.0014 ethylene oxide formaldehyde 0.0000073 formaldehyde formaldehyde (waterborne) 0.000037 formaldehyde haloginated HC (unspecified) 0.0000032 assumed as dichloromethaneheavy metals (air) 0.039 assumed as metalsinsecticide (unspecified) 0.0026 as lindanelindane 0.0026 gamma-HCH (Lindane) metals (unspecified) 0.039 metals Ni 0.17 Nickel Ni (soil) 0.029 Nickel (ind.) Ni (waterborne) 0.23 Nickel PAH (unspecified) 0.43 as Benzo(a) anthracenePAH (waterborne) 4.9 as Benzo(a) anthraceneparticulate (diesel) 0.000072 particles diesel soot pesticides (unspecified) (waterborne) 0.031 gamma-HCH (Lindane) styrene 0.00000018 styrene tetrachloride-dibenzo-dioxin 1300 2,3,7,8-TCDD Dioxin tetrachloroethene 0.0000036 perchloroethylenetrichloromethane 0.00019 chloroform vinyl chloride 0.0000015 vinyl chloride
Toxicity Metals non carcinogens (Pb equiv.) Relative toxicities taken from Ecoindicator 95
Page 1 of 4
Annex 4 bis Appendix 1 - Characterisation Tables
Burden Name: Multiplier: Notes:B (waterborne) 0.03Ba (waterborne) 0.14Cu (waterborne) 0.005heavy metals (air) 1heavy metals (waterborne) 1 assumed as PbHg 1Hg (waterborne) 10metals (unspecified) 1 assumed as Pbmetals (unspecified) (waterborne) 1 assumed as PbMn 1Mn (waterborne) 0.02Mo (waterborne) 0.14Pb 1Pb (waterborne) 1
Toxicity Gaseous non carcinogens (SO2 equiv.)CO 0.67 Value based on EI99 (Respirotary effects - Egalitarian)H2S 43.59NH3 1.12SO2 1.00
Toxicity Particulates & aerosols (PM10 equiv)NOx 0.2particulate (diesel) 15.7PM10 1SO2 0.24TSP 0.7 Assumed as PM10 *.7
Toxicity Smog (ethylene equiv.)acetaldehyde 1.4acetic acid 1.1 assumed as for Non Methane hydrocarbons (average)acetone 0.47acrolein 1.1 assumed as for Non Methane hydrocarbons (average)alcohols (unspecified) 0.52aldehydes (unspecified) 1.2alkanes (unspecified) 1.1alkenes (unspecified) 2.4aromatics (unspecified) 2benzene 0.5benzo(a)pyrene 1.1 assumed as for Non Methane hydrocarbons (average)butadiene 1.1 assumed as for Non Methane hydrocarbons (average)butane (i) 0.84butane (n) 1.1butane (unspecified) 0.84 assumed as for i-butanebutene 2.6carbon tetrachloride 0.056 assumed as for halogenated hydrocarbons (average)CFC (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)CFC-11 0.056 assumed as for halogenated hydrocarbons (average)cyclic alkanes (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)dichloromethane 0.027dioxins and furanes (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)esters (unspecified) 0.59ethane 0.22ethanol 0.71ethene 2.7ethers (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)ethylbenzene 1.6ethylene dichloride 1.1 assumed as for Non Methane hydrocarbons (average)ethylene oxide 1.1 assumed as for Non Methane hydrocarbons (average)ethyne 0.45formaldehyde 1.1haloginated HC (unspecified) 0.056halon -1301 0.056 assumed as for halogenated hydrocarbons (average)halons (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)HC (unspecified) 1HC excl CH4 (unspecified) 1.1HCFC (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)HCFC-22 0.056 assumed as for halogenated hydrocarbons (average)heptane 1.4hexafluoroethane 0.056 assumed as for halogenated hydrocarbons (average)hexane 1.1 assumed as for n-hexaneHFC (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)ketone 0.86mercaptans/smell gas (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)methane 0.019methanol 0.33methyl tert-butyl ether 1.1 assumed as for Non Methane hydrocarbons (average)naphthalene 1.1 assumed as for Non Methane hydrocarbons (average)non methane VOC (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)NOx 1.2organic acids (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)PAH (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)pentane 0.93phenol 1.1 assumed as for Non Methane hydrocarbons (average)phenols (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)phthalates (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)
Page 2 of 4
Annex 4 bis Appendix 1 - Characterisation Tables
Burden Name: Multiplier: Notes:propane 1.1propene 2.7propionaldehyde 1.6propionic acid 1.1 assumed as for Non Methane hydrocarbons (average)styrene 1.1 assumed as for Non Methane hydrocarbons (average)tetrachloride-dibenzo-dioxin 0.056 assumed as for halogenated hydrocarbons (average)tetrafluoromethane 0.056 assumed as for halogenated hydrocarbons (average)tetrafluroethylene 0.056 assumed as for halogenated hydrocarbons (average)toluene 1.5trichloroethane 0.056 assumed as for halogenated hydrocarbons (average)trichloromethane 0.056 assumed as for halogenated hydrocarbons (average)VOC 1xylene (unspecified) 2.3 assumed as average xylenexylene(m-) 2.6xylene(o-) 1.8xylene(p-) 2.4
Damage to Structures (kg dust eq.)NOx 0.37particulate (diesel) 1PM10 1SO2 1.06 702 ecu/662 ecuTSP 1 assumed as particulates
FertilisationNOx 1
Traffic accidentsCar (motorway) 0.31Car (rural) 1.32Car (unspecified) 1Car (urban) 1HGV (motorway) 0.31HGV (rural) 1.32HGV (unspecified) 1HGV (urban) 1Road transport (rural) 0.31Road transport (unspecified) 1Road transport (urban) 1
Traffic Congestion (car km equiv.)Car (motorway) 0.08Car (rural) 0.03Car (unspecified) 1Car (urban) 4.9HGV (motorway) 0.15HGV (rural) 0.06HGV (unspecified) 2HGV (urban) 9.8Road transport (rural) 0.06 Car km congestion equiv.Road transport (unspecified) 2 Car km congestion equiv.Road transport (urban) 9.8 Car km congestion equiv.
Traffic Noise (car km equiv.)Car (motorway) 1Car (rural) 1Car (unspecified) 1Car (urban) 1HGV (motorway) 6HGV (rural) 6HGV (unspecified) 6HGV (urban) 6Road transport (rural) 6 Car km noise equiv.Road transport (unspecified) 6 Car km noise equiv.Road transport (urban) 6 Car km noise equiv.
Water Quality Eutrophication (P equiv.)COD 0.0072N (waterborne) 0.14NH3 0.029 Assuming 25% ends up in surface waternitrates (waterborne) 0.033 Average value for NO3- to waternitrites (waterborne) 0.033 Average value for NO3- to waternitrogenous compounds (unspecified) (waterborne)0.033 Average value for NO3- to waterNOx 0.011 Assuming 25% ends up in surface waterP (waterborne) 1phosphates (waterborne) 0.33
Disaminity (kg LF waste equiv.)Waste into Incinerator 0.274 200000/730000 ton/yearWaste into Landfill 1
Ecotoxicity (cu equiv.)As 0.41 Arsenic As (soil) 0.42 Arsenic (ind.) As (waterborne) 0.0078 Arsenic benzene 0.0000019 benzene benzene (waterborne) 0.000033 benzene
Page 3 of 4
Annex 4 bis Appendix 1 - Characterisation Tables
Burden Name: Multiplier: Notes:Cd 6.6 Cadmium Cd (soil) 6.8 Cadmium (ind.) Cd (waterborne) 0.33 Cadmium Cr (IV) 2.8 as CrCr (unspecified) 2.8 Chromium Cr (unspecified) (soil) 2.9 Chromium (ind.) Cr (unspecified) (waterborne) 0.047 Chromium Cu 1 Copper Cu (soil) 1 Copper (ind.) Cu (waterborne) 0.1 Copper Hg 0.57 Mercury Hg (soil) 1.2 Mercury (ind.) Hg (waterborne) 0.13 Mercury insecticide (unspecified) 0.08 Malathion lindane 0.0015 gamma-HCH (Lindane) metals (unspecified) 0.18 metals Ni 4.9 Nickel Ni (soil) 5 Nickel (ind.) Ni (waterborne) 0.098 Nickel PAH (unspecified) 0.00000053 PAH's PAH (waterborne) 0.0000014 PAH's Pb 1.7 Lead Pb (soil) 0.0088 Lead (ind.) Pb (waterborne) 0.0051 Lead pesticides (unspecified) (waterborne) 0.0071 gamma-HCH (Lindane) tetrachloride-dibenzo-dioxin 90 2,3,7,8-TCDD Dioxin toluene 0.00000016 toluene toluene (waterborne) 0.00012 toluene Zn 2 Zinc Zn (soil) 2 Zinc (ind.) Zn (waterborne) 0.011 Zinc
Page 4 of 4
Annex 4 bis Appendix 2 - Moneterisation/Valuation
Prevention cost from Delft university
(Vogtlander et al 1999)
Prevention cost from Delft university
(Vogtlander et al 1999)
Ec--Indicator 95
marginal cost (1) average cost (1)
Global Warming Potential /kg CO2 equ. 0.114 0.08 0.01344
CO2 0.0632 0.0014 0.0018 0.01375 0.003 0.193
CH4 1.548
Acidification 204.8 22.857 1.86 3.27 8.73
SOx 6.4 2.5435 1.03 1.4 0.47 0.06 0.10
NOx 2.0348 0.911 1.16 2.3 16
Photochemical pollution due to VOCs 50 3.5 2.0348 3.55 0.734
O3 0.44 0.58 2.5 2.5
Ozone depletion (CFC11) 4.459 0.68
Toxicity : other emissions to air (SO2 equ.) 1.002
CO NA NA 0.0763 NA NA 0.01002
Eutrophication kg Phosphate equi. 3.05 0.0009 NA 2.357 NA 1.5369
COD in water 0.7122 NA NA
Eutrophication kg P equi. 9.327217125 0.002752294 NA NA 4.7
Winter Smog
Particulates (<10 µm) 12.3 5 0.5087 0.39 0.51 1.43 17 29 23.686
SO2
TSP
NOx
Heavy metals (Pb) NA 1571 62
Zn 680 0.3
Toxicity : carcinogenic substances NA NA
PAH 12.3 3837 6022.08
Dioxines NA 2000000 19720319
Arsenic 33 1571.4 44 6.642
Cadnium 9100 12000 78571 81 22.14
Chromium 330 440 314.2 820 128
Nickel 330 1688 17 7.08
Damages to structures (S02) 0.662
Disamenity Landfill 0.037
Disamenity Incinerator 0.01
Traffic accident /1000 km 16.9
Traffic congestion/1000km 86
Traffic noise/1000km 3
Fertilisation (N02 equ.) 0 -0.697
Ecotoxicity
Resource depletion (MJ) 0
Resources - fossil (MJ) 0
Land Use (m2.a) 0
Environmental damage cost (Krewitt et al. 1997 and Eyres
et al 1997) (max)
Eco-INDICATOR 95 (max)Impact / Flux damage cost GUA méthodology (CBA) (1)
Eco-INDICATOR 95 (min) Environmental damage cost (Krewitt et al. 1997 and Eyres
et al 1997) (min)
Pira International economic valuation
Page 1 of 2
Annex 4 bis Appendix 2 - Moneterisation/Valuation
Global Warming Potential /kg CO2 equ.
CO2
CH4
Acidification
SOx
NOx
Photochemical pollution due to VOCs
O3
Ozone depletion (CFC11)
Toxicity : other emissions to air (SO2 equ.)
CO
Eutrophication kg Phosphate equi.
COD in water
Eutrophication kg P equi.
Winter Smog
Particulates (<10 µm)
SO2
TSP
NOx
Heavy metals (Pb)
Zn
Toxicity : carcinogenic substances
PAH
Dioxines
Arsenic
Cadnium
Chromium
Nickel
Damages to structures (S02)
Disamenity Landfill
Disamenity Incinerator
Traffic accident /1000 km
Traffic congestion/1000km
Traffic noise/1000km
Fertilisation (N02 equ.)
Ecotoxicity
Resource depletion (MJ)
Resources - fossil (MJ)
Land Use (m2.a)
Impact / Flux
0.0014 0.193
0.0041 0.0133
0.0852 0.2933
0.06 0.10 1.860 205
0.01 0.04 0.734 50
20.32 56.67 1 4.459
1.002 1.002
0.010 0.0763
0.0009 3.05
0.712 0.7122
0.00275 9.327217125
7.26 18.27 0.390 29
1.06 2.60
2.13 5.35
0.08 2.31
2.18 247.65 62.00 1571
46.48 281.78 0.3 680
0.00 4.42 12.3 6022
0.00 4654000.00 2000000 19720319
66.67 639.60 6.64 1571
686.67 3510.00 22.14 78571
11933.39 45500.00 128 820
452.67 611.00 7.08 1688
0 0.662
0 0.037
0 0.01
0 16.9
0 86
0 3
-0.697 0
2.18 247.65 0.00 0
0.87 48.92 0 0
0.00 0.14 0 0.000
0.06 0.11 0 0.000
Eco-INDICATOR 99 (min) Not moneterisation!
Eco-INDICATOR 99 (max) Not
moneterisation!
MAX excluding EI 99MIN excluding EI 99
Page 2 of 2
Annex 4 bis Valuation table
Unit Valuation Min MaxGWP (kg CO2 eq.) /kg CO2 0.01344 0.0014 0.19Ozone depletion (kg CFC 11 eq.) /kg CFC11 0.68 0.68 0.68Acidification /kg H+ 8.70 1.9 200Toxicity Carcinogens (Cd equiv) /kg Cadmium (carcinogenic effects only) from electricity production22 22 12000Toxicity Gaseous non carcinogens (SO2 equiv.) /kg SO2 from electricity production 1 0 1Toxicity Metals non carcinogens (Pb equiv.) /kg Pb 62 0 62Toxicity Particulates & aerosols (PM10 equiv) /kg PM10 from electricity production 24 0.39 29Smog (ethylene equiv.) /kg VOC indirect impacts through ozone formation from electricity production0.73 0.73 50Black smoke (kg dust eq.) [damage to structure] /kg smoke 0.66 0 0.66Fertilisation /kg expressed as NO2 mass equivalents -0.7 -0.7 0Traffic accidents (risk equiv.) euro/1000 km travelled on an average road 17 0 17Traffic Congestion (car km equiv.) Euro per 1000 car km equivalents 86 0 86Traffic Noise (car km equiv.) Euro per 1000 car km equivalents 3 0 3Water Quality Eutrophication (P equiv.) /kg P 4.7 0.0028 9.3Disaminity (kg LF waste equiv.) /kg landfill 0.037 0 0.037
Annexes 4-5-6.doc
Page 18 of 18
Annex 5: Employment data –jobs for waste
management activities
Annexes 4-5-6.doc
Page 19 of 19
1 PACKAGING FROM HOUSEHOLD SOURCES
Gross Employment, Landfilling 1 tonne PET bottles
Jobs per 1000 tonne per annum Collection Landfill management / operation Total
High population density 1.2 0.1 1.3
Low population density 1.15 0.1 1.25
Gross Employment for Landfilling 1 tonne steel packaging
Jobs per 1000 tonne per annum Collection Landfill management / operation Total
High population density 1.2 0.1 1.3
Low population density 1.15 0.1 1.25
Gross Employment for Landfilling 1 tonne rigid and semi - rigid aluminium packaging
Jobs per 1000 tonne per annum Collection Landfill management / operation Total
High population density 1.2 0.1 1.3
Low population density 1.15 0.1 1.25
Gross Employment for Landfilling 1 tonne paper & board packaging
Jobs per 1000 tonne per annum Collection Landfill management / operation Total
High population density 1.2 0.1 1.3
Low population density 1.15 0.1 1.25
Gross Employment for Landfilling 1 tonne Liquid Beverage Cartons
Jobs per 1000 tonne per annum Collection Landfill management / operation Total
High population density 1.2 0.1 1.3
Low population density 1.15 0.1 1.25
Gross Employment for Landfilling 1 tonne mix plastics packaging
Jobs per 1000 tonne per annum Collection Landfill management / operation Total
High population density 1.2 0.1 1.3
Low population density 1.15 0.1 1.25
Gross Employment for Landfilling 1 tonne glass
Jobs per 1000 tonne per annum Collection Landfill management / operation Total
High population density 1.2 0.1 1.3
Low population density 1.15 0.1 1.25
Annexes 4-5-6.doc
Page 20 of 20
Gross Employment for Incineration of 1 tonne PET bottles
Jobs per 1000 tonne per annum Collection Incinerator management / operation Total
High pop. density 1.2 0.27 1.47
Low pop. density 1.15 0.27 1.42
Gross Employment for Incineration of 1 tonne steel packaging
Jobs per 1000 tonne per annum Collection Incinerator management / operation Total
High pop. density 1.2 0.27 1.47
Low pop. density 1.15 0.27 1.42
Gross Employment for Incineration of 1 tonne rigid and semi-rigid aluminium packaging
Jobs per 1000 tonne per annum Collection Incinerator management / operation Total
High pop. density 1.2 0.27 1.47
Low pop. density 1.15 0.27 1.42
Gross Employment for Incineration of 1 tonne Paper & Board packaging
Jobs per 1000 tonne per annum Collection Incinerator management / operation Total
High pop. density 1.2 0.27 1.47
Low pop. density 1.15 0.27 1.42
Gross Employment for Incineration of 1 tonne Liquid Beverage Cartons
Jobs per 1000 tonne per annum Collection Incinerator management / operation Total
High pop. density 1.2 0.27 1.47
Low pop. density 1.15 0.27 1.42
Gross Employment for Incineration of 1 tonne mix plastics packaging
Jobs per 1000 tonne per annum Collection Incinerator management / operation Total
High pop. density 1.2 0.27 1.47
Low pop. density 1.15 0.27 1.42
Gross Employment for Incineration of 1 tonne glass
Jobs per 1000 tonne per annum Collection Incinerator management / operation Total
High pop. density 1.2 0.27 1.47
Low pop. density 1.15 0.27 1.42
Annexes 4-5-6.doc
Gross Employment , kerbside collection and sorting of PET bottles
Jobs per 1000 tonne per annum Collection Sorting Transport from sorting to reprocessing Total
High pop. density 14.7 0.71 0.19 15.6Low pop. density 17.7 0.71 0.19 18.6
Gross Employment , bring scheme collection and sorting of PET bottles
Jobs per 1000 tonne per annum Transport, bring bank to sorting Sorting Transport from sorting to reprocessing Total
High pop. density 3.2 0.71 0.19 4.1
Low pop. density 3.8 0.71 0.19 4.7
Gross Employment , kerbside collection and sorting of steel packaging
Jobs per 1000 tonne per annum Collection Sorting Transport from sorting plant to reprocessor Total
High population density 4.8 0.53 0.1 5.43
Low population density 5.8 0.53 0.1 6.43
Gross Employment , bring scheme collection and sorting of steel packaging
Jobs per 1000 tonne perannum
Transport from bring bank to sortingplant
Sorting Transport from sorting plant toreprocessor
Total
High population density 1 0.53 0.1 1.63
Low population density 1.2 0.53 0.1 1.83
Gross Employment , kerbside collection and sorting of rigid and semi-rigid aluminium packaging
Jobs per 1000 tonne per annum Collection Sorting Transport from sorting plant to reprocessor Total
High population density 10.3 0.03 0.68 11.01
Low population density 12.4 0.03 0.68 13.11
Gross Employment , bring scheme collection and sorting of rigid and semi-rigid aluminium
packaging
Jobs per 1000 tonne perannum
Transport from bring bank to sortingplant
Sorting Transport from sorting plant toreprocessor
Total
High population density 2.1 0.03 0.68 2.81
Low population density 2.6 0.03 0.68 3.31
Gross Employment , kerbside collection and sorting of Paper & Board packaging
Jobs per 1000 tonne per annum Collection Sorting Transport from sorting plant to reprocessor Total
High population density 2.6 n.a. 0.03 2.63
Low population density 3.1 n.a. 0.03 3.13
Annexes 4-5-6.doc
Gross Employment , bring scheme collection and sorting of Paper & Board packaging
Jobs per 1000 tonne perannum
Transport from bring bank to sortingplant
Sorting Transport from sorting plant toreprocessor
Total
High population density 0.3 n.a. 0.03 0.33
Low population density 0.4 n.a. 0.03 0.43
Gross Employment , kerbside collection and sorting of Liquid Beverage Cartons (incineration of
rejects)
Jobs per 1000 tonne perannum
Collection
Sorting
Transport from sorting plant toreprocessor
incineration of rejects (jobs/1000trejects per annum)
Total
High populationdensity
8.4 0.7 0.14 0.07 9.31
Low population density 10.1 0.7 0.14 0.07 11.01
Gross Employment , bring scheme collection and sorting of Liquid Beverage Cartons (incineration
of rejects)
Jobs per 1000 tonneper annum
Transport from bring bank tosorting plant
Sorting
Transport from sorting plant toreprocessor
incineration of rejects(jobs/1000t rejectsper annum)
Total
High pop. density 1.8 0.7 0.14 0.07 2.71
Low pop. density 2.2 0.7 0.14 0.07 3.11
Gross Employment , kerbside collection and sorting of Liquid Beverage Cartons (landfilling of
rejects)
Jobs per 1000 tonne of LBCper annum
Collection
Sorting
Transport from sorting plant toreprocessor
landfilling of rejects (jobs/1000trejects per annum)
Total
High population density 8.4 0.7 0.14 0.03 9.27
Low population density 10.1 0.7 0.14 0.03 10.97
Gross Employment , bring scheme collection and sorting of Liquid Beverage Cartons (landfilling of
rejects)
Jobs per 1000 tonne ofLBC per annum
Transport from bring bank tosorting plant
Sorting
Transport from sorting plant toreprocessor
landfilling of rejects(jobs/1000t rejectsper annum)
Total
High pop. density 1.8 0.7 0.14 0.03 2.67
Low pop. density 2.2 0.7 0.14 0.03 3.07
Gross Employment , bring scheme collection and sorting of Glass (landfilling of rejects)
Jobs per 1000 tonne per annum Transport from bring bank to sorting plant Transport from sorting plant to reprocessor Total
High pop. density 0.3 0.061 0.036
Low pop. density 0.3 0.061 0.036
Annexes 4-5-6.doc
2 COMMERCIAL AND INDUSTRIAL CASE STUDIES
Gross Employment, Landfilling 1 tonne C&I films
Collection Landfill management / operation Total
Jobs per 1000 tonne per annum 1.2 0.1 1.3
Gross Employment for Incineration of 1 tonne C&I films
Collection Incinerator management / operation Total
Jobs per 1000 tonne per annum 1.2 0.27 1.47
Gross Employment for Recycling of 1 tonne C&I films
Collection Total
Jobs per 1000 tonne per annum 1.2 1.2
Gross Employment, Landfilling 1 tonne C&I corrugated board
Collection Landfill management / operation Total
Jobs per 1000 tonne per annum 1.2 0.1 1.3
Gross Employment for Incineration of 1 tonne C&I corrugated board
Collection Incinerator management / operation Total
Jobs per 1000 tonne per annum 1.2 0.27 1.47
Gross Employment for Recycling of 1 tonne C&I corrugated board
Collection Total
Jobs per 1000 tonne per annum 1.2 1.2
Annexes 4-5-6.doc
Annex 6: Packaging mix by Member State
Annexes 4-5-6.doc
1 INTRODUCTION
It is assumed that the optimal recycling rate in a Member State is a function of the packaging mix in
that Member State, as some packaging materials/applications will be easier to recycle than others.
Therefore the packaging mix in each Member State must be determined in order to calculate the
Member State’s optimal recycling target.
2 DATA SOURCES AND EXTRAPOLATION RULES
The main data sources are:
§ Member State’s official declarations for 1997 and 1998
§ Data provided by the national compliance schemes (1998-1999-2000)
§ Reports and interview from/of European Material Federations (APME, FEVE)
§ Additional input from local consultants where possible
Where data are missing, extrapolation rules are derived from the report “The Facts: A European
cost/benefit perspective” commissioned by ERRA in 1998, e.g. for the split between industrial &
commercial packaging and household packaging. The following assumptions are made
§ the ratios between industrial and household packaging applications remain unchanged up to
2000
§ the ratios between material applications are the best forecast where no other data is available
§ for industrial packaging, distribution between packaging material applications is assumed to be
the same in the south countries (Italy, Greece, Portugal and Spain)
§ data for 1998 or 1999 provide a reasonable forecast for 2000
Annexes 4-5-6.doc
Member State Source Comment
Austria "Bundesabfallwirtschaftsplan" 1998
Member State declaration, 1998
Data reviewed by the ComplianceScheme
Belgium Fost Plus, 2000
Val-I-Pac, 1999
Data provided and reviewed byCompliance Scheme
Extrapolation from Annual report andinterview
Denmark DEPA = Miljostyrelsen, 1998 Data provided by COWI
Finland PYR, 2000 Data reviewed by the ComplianceScheme
Shops packaging waste are consideredas industrial packaging waste
Extrapolation based on ERRA andAPME reports when no data available.
France Eco-Emballages, 1998 Data reviewed by Eco-emballages
Germany GVM Gesallschaft fürVerpackungsmarktforschung mbH,1998
Data reviewed by the ComplianceScheme
Greece Forecast for 2000 Data provided by Ecopolis
Ireland National Waste database report 1998,Environmental Protection Agency
Data reviewed by the ComplianceScheme
Italy CONAI, 2000 Data reviewed by the ComplianceScheme
Luxembourg Valorlux Data reviewed by the ComplianceScheme
The Netherlands Data reviewed by the ComplianceScheme
Portugal Sociedade Ponto Verde, 1999
PLASTVAL, 1999
Data collected by IDOM
Spain ECOEMBALAJES ESPAÑA, S.A
ECOVIDRIO
Data reviewed by the ComplianceScheme
Data collected by IDOM andinterview of Ecoembes.
Sweden Member State declaration, 1998
Interview of RVF SvenskaRenhållningsverksföreningen, TheSwedish Association of WasteManagement
UK Increasing recovery and recycling ofpackaging waste in the UK TheChallenge Ahead: A forward Look forPlanning Purposes, DETR (versionunder production)
Plastic packaging amount are splitbetween application according toAPME ratios
Data reviewed by the Compliance
Annexes 4-5-6.doc
Annex 6 bis
Year 2000 unit: kt
Material Application
AUT BE DK FI FR DE GK IE IT LU NL PO SP SE UKLDPE films 55 42 51 22 260 384 28 13 261 2 92 24 125 19 273Other 20 49 58 26 470 486 102 39 330 3 163 0 286 21 314total 75 91 109 48 730 870 129 52 591 5 256 24 411 40 587
Wood all appl. 60 168 84 0 1,690 1,969 38 0 2,295 9 379 7 443 0 670Steel all appl. 4 56 11 18 280 654 108 10 223 3 118 20 43 53 217Cardboard all appl. 384 371 314 192 3,100 4,350 403 242 2,875 19 1,128 75 1,627 370 3,373glass all appl. 47 4 0 6 960 88 118 52 60 0 23 22 0 60 350Other all appl. 0 14 0 0 0 0 22 31 0 1 0 4 177 0 40
570 704 518 264 6,760 7,930 818 387 6,043 36 1,905 152 2,702 523 5,237PET bottles 20 44 5 6 250 100 34 11 426 2 67 106 159 19 252LPDE films 24 43 20 17 140 175 25 11 248 2 59 98 130 25 190HDPE bottles 24 18 17 15 100 152 21 9 215 1 51 75 112 22 183other 44 57 21 0 412 201 152 86 420 2 58 10 200 27 459Total 112 162 63 37 902 628 232 117 1,309 7 235 289 601 94 1,084
Steel all appl. 69 80 37 12 350 358 87 21 247 2 92 81 235 9 533Aluminium all appl. 9 14 7 2 36 62 14 8 57 1 10 15 41 8 108Metals Al + steel 81 93.5 44 14 386 421 101 29 304 3 109 96 276 17 641Wood all appl. 9 10 109 0Cardboard all appl. 98 153 121 18 872 978 302 50 1,300 11 447 198 828 150 420
liquid beverage cartons 23 20 0 29 120 209 25 8 10 1 47 12 117 40 51mainly based on plastic 4 3 1 4 18 32 4 1 2 0 7 2 18 6 7mainly based on cardboard 5 5 1 6 28 48 6 2 2 0 11 3 27 9 11mainly based on Al. 3 2 1 0 15 26 3 1 1 1 6 2 15 5 6Total 35 30 3 40 181 315 38 12 15 2 70 18 176 61 75
Glass all appl. 183 330 176 50 2,550 3,512 145 59 2,189 17 436 314 1,523 111 1,848Other all appl. 14 32 19
506 768 416 160 4,901 5,867 818 300 5,227 40 1,291 915 3,423 433 4,068
Material AUT BE DK FI FR DE GK IE IT LU NL PO SP SE UKGlass 230 334 176 56 3,510 3,600 263 111 2,249 17 459 336 1,523 171 2,198Plastic 191 256 173 89 1,650 1,530 365 170 1,902 12 498 315 1,029 140 1,678Paper and board 510 548 436 246 4,120 5,585 735 302 4,187 32 1,633 287 2,598 570 3,855Metals 85 152 56 32 681 1,100 212 40 528 7 226 118 334 75 864Wood 60 168 93 0 1,700 1,969 38 0 2,404 9 379 7 443 0 670Other 0 14 0 0 0 14 22 63 0 1 0 4 196 0 40Total 1,076 1,472 934 423 11,661 13,798 1,635 686 11,270 77 3,195 1,067 6,125 956 9,305
Total Household
composites
Plastics
PlasticsTotal Industrial
Annex 7: Environmental data sources
Environmental data for background systemsLCI data for the environmental analysis has been derived from the following sources:
Data Source CommentsTransportstepsVehicleemissions
“Life Cycle InventoryDevelopment for WasteManagement Operations: WasteTransport and Other VehicleUse”, UK Environment Agency2000
Data collected and reported byLatham S & Mudge G (TransportResearch Laboratory), 1997 asresearch contractors to the UKEnvironment Agency
Electricity andother energies
Calculated from “Life cycleinventories of energy systems”,ETH, Zurich, 1994
Raw materials Various sources including:“Life cycle inventories of energysystems”, ETH, Zurich, 1994
Environmental data related to PET bottles from household sourcesLCI data for the environmental analysis has been derived from the following sources:
Original Data Source CommentsWastemanagementLandfilling ofrigid plastics
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Rigid plasticsincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995"Specific processing costs of wastematerials in a MSWcombustionfacility", ir. L.P.M Rijpkema andDr.ir.J.A. Zeevalkink,TNO 1996
MaterialrecyclingSorting Derived from “Life Cycle
Inventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000
Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment Agency
Baling Derived from “Life CycleAssessment of PackagingSystems for Beer and SoftDrinks, Disposable PETBottles”, Danish EnvironmentalProtection Agency, 1998
Recycling –Regranulation
“Life Cycle Assessment ofPackaging Systems for Beer andSoft Drinks, Disposable PETBottles”, Danish EnvironmentalProtection Agency, 1998
PET (bottlegrade andamorphous)
"Ecoprofiles of the Europeanplastics industry Report 8:Polyethylene terephthalate",APME, 1995
Environmental data related to Paper & board packaging from householdsources
LCI data for the environmental analysis has been derived from the following sources:Data Source Comments
WastemanagementLandfilling ofpaper
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Paperincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingSorting Derived from “Life Cycle
Inventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000
Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to theEnvironment Agency
Testlinerproduction
Derived from “EuropeanDatabase for Corrugated BoardLife Cycle Studies”, FEFCO,Groupemont Ondule and KraftInstitute, 1997
Kraftlinerproduction
Derived from “EuropeanDatabase for Corrugated BoardLife Cycle Studies”, FEFCO,Groupemont Ondule and KraftInstitute, 1997
Environmental data related to corrugated board packaging from industrialsources
LCI data for the environmental analysis has been derived from the following sources:Data Source Comments
WastemanagementLandfilling ofpaper
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Paperincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingTestlinerproduction
Derived from “EuropeanDatabase for Corrugated BoardLife Cycle Studies”, FEFCO,Groupemont Ondule and KraftInstitute, 1997
Kraftlinerproduction
Derived from “EuropeanDatabase for Corrugated BoardLife Cycle Studies”, FEFCO,Groupemont Ondule and KraftInstitute, 1997
Environmental data related LDPE films from Commercial and IndustrialSources
LCI data for the environmental analysis has been derived from the following sources:Original Data Source Comments
WastemanagementLandfilling offlexible plastics
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
LDPE films toincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingRecyclingprocesses
Derived from: "Recycling andRecovery of Plastics fromPackagings in Domestic Waste",Michael Heyde and MarkusKremer, LCA Documents, Vol 5,1999
Study carried out between 1994and 1995
LLDPE "Ecoprofiles of the Europeanplastics industry Report 8:Polyethylene terephthalate",APME, 1995
LDPE "Ecoprofiles of the Europeanplastics industry Report 8:Polyethylene terephthalate",APME, 1995
Environmental data related Mixed plastics from household sourcesLCI data for the environmental analysis has been derived from the following sources:
Original Data Source CommentsWastemanagementLandfilling ofmixed plastics
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Mixed plasticsto incineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingSorting andrecyclingprocesses
Derived from: "Recycling andRecovery of Plastics fromPackagings in Domestic Waste",Michael Heyde and MarkusKremer, LCA Documents, Vol 5,1999
Study carried out between 1994and 1995
Pallisade(assumed to bewoodconstructionmaterial)
“Life cycle inventories of energysystems”, ETH, Zurich, 1994
OtherreprocessingAgglomerationand Blastfurnace
Derived from: "Recycling andRecovery of Plastics fromPackagings in Domestic Waste",Michael Heyde and MarkusKremer, LCA Documents, Vol 5,1999
Study carried out between 1994and 1995
Heating oil “Life cycle inventories of energysystems”, ETH, Zurich, 1994
Environmental data related to Glass beverage bottles from household sourcesLCI data for the environmental analysis has been derived from the following sources:
Original Data Source CommentsWastemanagementLandfilling ofglass
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Glass toincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingRecyclingprocesses andcredit
Derived from “Life CycleInventory Development forWaste Management Operations:Recycling”, UK EnvironmentAgency 2000
Sorting Derived from “Life CycleInventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000
Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment AgencyDatacollected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to theEnvironment Agency
Environmental data related to aluminium beverage, rigid and semi-rigid fromhousehold sources
LCI data for the environmental analysis has been derived from the following sources:Original Data Source Comments
WastemanagementLandfilling ofaluminium
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Aluminium toincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingRecyclingprocesses andvirginproduction
Derived from “EnvironmentalProfile Report for the EuropeanAluminium Industry”, EuropeanAluminium Association, April2000
Sorting andbaling
Derived from “Life CycleInventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000
Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment Agency
Environmental data related to steel from household sourcesLCI data for the environmental analysis has been derived from the following sources:
Original Data Source CommentsWastemanagementLandfilling ofsteel
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Steel toincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingRecyclingprocesses andvirginproduction
Derived from «Ökobilanzdatenfür Weissblech und ECCS » ;InformationszentrumWeissblech ; October 1995
Sorting andbaling
Derived from “Life CycleInventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000
Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment Agency
Environmental data related to LBC from household sourcesLCI data for the environmental analysis has been derived from the following sources:
Original Data Source CommentsWastemanagementLandfilling ofLBC
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment AgencyThe data for paper, aluminium andplastic film has been combined torepresent LBC
LBC toincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995The data for paper, aluminium foiland plastic film has beencombined to represent LBC
MaterialrecyclingFibre recyclingprocesses andcredit
Derived from “EuropeanDatabase for Corrugated BoardLife Cycle Studies”, FEFCO,Groupemont Ondule and KraftInstitute, 1997
Based on comparison of kraftlinerproduction and testliner production
Incineration ofrejects
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995The data for aluminium foil and
plastic film has been combined torepresent LBC
Landfilling ofrejects
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
The data for aluminium and plasticfilm has been combined torepresent LBC
Sorting andbaling
Derived from “Life CycleInventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000
Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment Agency
Environmental Data for Refillable and single tripPET bottles
Environmental data related to PET bottles from household sourcesLCI data for the environmental analysis has been derived from the following sources:
Original Data Source CommentsMaterialproductionPET Bottlegrade
"Ecoprofiles of the Europeanplastics industry Report 8:Polyethylene terephthalate",APME, 1995
HDPE "Ecoprofiles of the Europeanplastics industry Report 3:Polyethylene andpolypropolene" , APME, 1993
BottleproductionPreform andbottleproduction
Derived from "Life cycleassessment of PackagingSystems for Beer and SoftDrinks, Refillable PET Bottles",Environment Project No404,Danish EnvironmentalProtection Agency, 1998
CrateproductionCrateproduction andgrinding
"Life cycle assessment ofPackaging Systems for Beer andSoft Drinks, Refillable PETBottles", Environment ProjectNo404, Danish EnvironmentalProtection Agency, 1998
ReuseWashing &filling
"Life cycle assessment ofPackaging Systems for Beer andSoft Drinks, Refillable PETBottles", Environment ProjectNo404, Danish EnvironmentalProtection Agency, 1998
WastemanagementLandfilling ofrigid plastics
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Rigid plastics RDC and Pira International 2000 Data reworked by P Dobson, Pira
Caevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingSorting Derived from “Life Cycle
Inventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000
Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment Agency
Baling Derived from “Life CycleAssessment of PackagingSystems for Beer and SoftDrinks, Disposable PETBottles”, Danish EnvironmentalProtection Agency, 1998
Recycling –Regranulation
“Life Cycle Assessment ofPackaging Systems for Beer andSoft Drinks, Disposable PETBottles”, Danish EnvironmentalProtection Agency, 1998
PET (bottlegrade andamorphous)
"Ecoprofiles of the Europeanplastics industry Report 8:Polyethylene terephthalate",APME, 1995
Environmental Data for Refillable and single tripGlass bottles
Environmental data related to PET bottles from household sourcesLCI data for the environmental analysis has been derived from the following sources:
Original Data Source CommentsMaterialproductionHDPE "Ecoprofiles of the European
plastics industry Report 3:Polyethylene andpolypropolene" , APME, 1993
BottleproductionGlass bottleproduction
Derived from "Vergleichendeokologische bewertung vonanstrichstoffen im baubereich",BUWAL, 1999
Data for 1993-1995
CrateproductionCrateproduction andgrinding
"Life cycle assessment ofPackaging Systems for Beer andSoft Drinks, Refillable GlassBottles", Environment ProjectNo400, Danish EnvironmentalProtection Agency, 1998
ReuseWashing &filling
"Life cycle assessment ofPackaging Systems for Beer andSoft Drinks, Refillable GlassBottles", Environment ProjectNo400, Danish EnvironmentalProtection Agency, 1998
WastemanagementLandfilling ofglass
Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000
Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency
Glass toincineration
RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK Environment
“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995
MaterialrecyclingRecyclingprocesses andcredit
Derived from “Life CycleInventory Development forWaste Management Operations:Recycling”, UK EnvironmentAgency 2000
Sorting Derived from “Life CycleInventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000
Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment Agency
Annexes 8 - 9.doc
Annex 8 : Current performance of Member States
Annexes 8 - 9.doc
1 METHODOLOGY FOR THE DATA COLLECTION:
♦ Classification of the data per year
♦ Classification of the data (total (MSW + non-MSW)) into production (packaging brought on the
market) and recycling summary tables for individual Member States and for the whole of
Europe
♦ Data were collected for the material classes as detailed as possible (as much sub-divisions
according to material applications as possible)
♦ glass,
♦ plastics,
♦ paper & cardboard,
♦ metals,
♦ composites1 ,
♦ wood,
♦ other packaging materials
This gives the tables shown in Annex 8 bis (for 1997, 1998 and 1999).
1.1 Data of 1997
1.1.1 Introduction
For 1997 a lot of data has been published (by Compliance Scheme) besides the official reporting
from the Member States to the European Commission.
The data reported to the European Commission concern total data per material (quantities brought
on the market, reuse, recycling and recovery data), but not detailed data per material application and
no distinction between household and industrial packaging.
However, Member States are asked to report their data in the official data format, established by the
European Commission. This data format encourages the Member States to fill in data within
divisions of the main material groups (i.e. for PET, PP, PVC,... within the plastics group),
nevertheless on a voluntary basis. The total amounts per material group are obligatory to report.
1 composite means packaging made of different materials and which can not be separated by hand. [Commission
Annexes 8 - 9.doc
This means generally that Member States have only reported the obligatory data, meaning data for
glass, plastics, paper & cardboard and metals. Also obligatory is to report total data for quantities
on the market, total recycling and total recovery (the division in organic recycling, incineration, etc.
is voluntary and thus generally not reported).
Member States are asked to report within 18 months of the end of the relevant year (this means July
1999 was the end date for reporting the data of 1997, and the results of 1998 can be expected in July
2000).
1.1.2 Results
11 countries officially reported to the European Commission (Austria, Belgium, Denmark, Finland,
France, Germany, Italy, Spain, Sweden, the Netherlands and the United Kingdom).
No global data were reported from Luxembourg, Portugal, Greece, Ireland.
Comparable data for these countries were found in other sources, especially in references [2]and
[3]. Those two reports already analysed the 1997 data on packaging and packaging waste and
provided ERRA with summary tables with specific data of household, industrial and total data for
the Member States.
The conclusions of these studies [2], [3] by Price Waterhouse Coopers were:
v Exact data on the amount of waste, packaging waste and recycling is hard to get and
ambitious;
v Data on the amount of waste, packaging waste and recycling is not comparable; due to the
fact that :
v the definitions of packaging and other terms used are interpreted differently and the methods
of data collection and analysis differ
v e.g. for some countries the only information available concerns packaging processed by the
packaging organisations, those amounts have not been corrected to a national level, because of
insufficient information, so it is clear that total amounts of packaging for these countries are
higher (the same is true for recycling amounts)
v e.g. MSW sometimes includes packaging from small businesses, sometimes not
v a potential cause of inaccuracy of data is the inclusion of quantities exported for recycling in
the final recycling results (some countries reported these quantities separately, other not)
v methodologies for recycling and recovery assessment are not reported
Annexes 8 - 9.doc
v it is plausible that national factors influence the amount of packaging placed on the market
and the extent to which it is recycled (factors like Gross Domestic Product, geographical
position, reuse promotion, type of valorisation scheme have to be analysed in more detail to be
able to draw some conclusions)
Other specific data (for 1997) were found in various reports of packaging recovery organisations
and available study reports (see Bibliography).
1.2 Data of 1998 and following years
For some countries global data can be found in (annual) reports from packaging recovery
organisations (Duales System Deutschland for Germany, Altstoff Recycling Austria for Austria,
Sociedade Ponto Verde for Portugal, Valorlux for Luxembourg, …). Also material recycling
organisations publish data on collected and recycled amounts (e.g. Svensk Glasåtervinning for
Sweden, PYR for Finland,…).
Important to notice is that the results reported by the packaging recovery organisations do not
include full country coverage and are sometimes specific for MSW.
Generally, more specific information and data were found through the national (and European)
material federations.
The official data (of 1998) from the Member States available at the European Commission are also
included.
1.3 Summary of the results of the data compilation
v Most data were found for 1997 and 1998
v Exact data on the amount of waste, packaging waste and recycling are hard to get;
v Data on the amount of waste, packaging waste and recycling are not comparable;
v More reliable data are/will be available for 1998 and especially 1999 thanks to the
experiment and the improvement of the calculation methods.
1.4 Sources :
[1], [2], [3], [4], [5], [6], [7], [8], [9], [10]
Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frame of the packaging and packaging waste directive 94/62/EC
Total HH + industrial
Material Glass Plastic Paper and board Metals Al Steel composites Wood Other TotalApplication
1997WasteAUT 260 180 666 85 28 50 1269BE 310 208 529.6 120.5 17.2 142 28.8 1356.1DK 202.306 183.43 463.021 58.035 60.782 3.639 971.213FI 52 90 243.5 31 416.5FR 3296 1571 3611 622 290 1679 11069DE 3750.3 1502.1 5447.8 1121.4 87.2 1034.2 1892.2 16.9 13730.7GK 1456IE 452IT 2248 1777 3246 487 1802 9560LU 17.3 7 11.3 2.8 0.68 0.92 80NL 469 611 1449 216 0 2745PO 1050SP 1398.1 1215 2255 340 670.7 5878.8SE 177.4 150 526.5 70 923.9UK 1787.265 1356.019 3034.893 809.093 112.258 696.835 749.476 17.769 7754.515EURecycledAUT 199 36 500 29 8 7 779BE 217.3 52.7 410.6 84.7 5.2 75 845.5DK 124.122 11.249 219 2.17 356.541FI 24.4 9.2 135.6 1.5 170.7FR 1388 102 2276 331 300 4397DE 2797.3 675.3 3193.1 914.9 1040 8620.6GK 180IE 80IT 750 164 1170 25 700 2809LUNL 354 76 941 145 1516PO 32SP 521.5 64.95 1242.4 76.4 60.4 1965.6SE 134.2 21 348 31.8 535UK 441 100 1609 211 27 184 2361EULegend:data EC -MS reports 1997data report PWC review data MS 1997data valorlux : chiffres cléfs only HHdata PWC The facts a European cost/benefit analysis 1998
RDC-Environment and Pira Int.Page 1 of 1 (1997)
Draft report
Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frame of the packaging and packaging waste directive 94/62/EC
Total HH + industrial
Material Glass Plastic Paper and board Metals Al Steel composites Wood Other TotalApplication
1998WasteAUT 230 190 510 85 40 60 1115BEDK 176 172 435 55 838FI 55 90 246 33 424FR 3513 1628 4123 681 1696 11641DE 6215.416GKIEIT 2200 1800 4023 511 57 454 2050 10584LU 21 9 28 5 12 77NL 459 491 1633 227 379 3189POSPSE 171 140 570 75 955UK 1889 1316 3015 808 123 7169EURecycledAUT 193.944 40.898 286.55 28.246 7.794 723BEDK 268FI 34.6 9.2 140.4 5 189FR 1576 131 2515 308 305 4835DE 2704.859 600.015 1415.502 418.216 43.343 374.873 344.962 5483.554GKIEIT 810 192 1489 34 7 27 400 2925LU 32NL 385 49 775 176 86 1471POSPSE 143.1 583UK 434.306 115.169 1894.086 161.738 14.517 147.221 170 2775.299EULegend:data EC -MS reports 1998data DSD : annual report 1998, only HH?data ARA: annual report 1998data DSD: press information mass flow verification 1999, only HH?data Swedish Glass recycling Facts 1998data PYR: Finnisch statistics for 1998data Ministery VROM: jaarverslag 1998data Conai: source : European Packaging and waste Law, N°79, July 2000, p.33, 34
RDC-Environment and Pira Int.Page 1 of 1 (1998)
Draft report
Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frame of the packaging and packaging waste directive 94/62/EC
Total HH + industrial
Material Glass Plastic Paper and board Metals Al Steel composites Wood Other TotalApplication
1999WasteAUTBEDKFIFRDE 6382
GKIEIT 2249 1850 4105 526 59 467 2404 11134
LUNLPO 261.027 108.9 207.776 44.204 5.574 38.63 2.677 3.536
SPSEUKEURecycledAUT 48.597BEDKFIFRDE 2710 610 1480 359 37 322 391 5909GKIEIT 890 243 1600 57 13 44 910 3700LUNLPOSPSEUKEULegend:data ÖKK Austria: verwertung kunststoff verpackungen 1999data DSD: press information mass flow verification 1999, only HH?data Sociedade Ponto verde : resultados Globais 1999data Conai: source : European Packaging and waste Law, N°79, July 2000, p.33, 34
RDC-Environment and Pira Int.
Page 1 of 1 (1999)
Draft report
Annexes 8 - 9.doc
Annex 9 : Critical factors limiting recycling and reuse
Annexes 8 - 9.doc
1 RECYCLING DIFFICULTIES
The critical factors identified in this section are taken into account in the calculations and the
hypothesis taken for packaging applications when no CBA is performed.
Recycling difficulties can be classified according to technical, economic and marketing constraints.
Marketing constraints can be avoided by specific marketing actions: they mainly depend on the
willingness of the industries.
On the other hand technical and economical constraints are more difficult – or impossible up to now
- to overcome. Technical constraints require R&D investments or increase of collecting, sorting
and/or treatment capacities. Economic constraints are very difficult to control: e.g.: market prices,
internal market barriers.
This paragraph provides a brief description of recycling difficulties and a summary of them. Reuse
recycling difficulties are also described.
1.1 Glass[11], [12], [13]
Especially for glass packaging the consultant identifies factors which are reasonable reasons to limit
recycling from factors which may be valid points but are not really a reason to limit recycling.
“Reasonable” factors are mainly technical and economic limits:
(1) Contamination : the stream quality must be free of contamination (e. g. no china cups),
otherwise the whole load may be rejected by the glass recycler.
(2) Imbalance in colour: the national glass production has to be in agreement with the national
glass consumption. This constraint could be avoided through the development of alternative
end-uses for recycled green glass.
(3) Market price: the low price value of glass hampers international trading and long transport
distance.
Factors which may be valid points recycling limitations but are not really a reason to limit recycling
mainly concern:
• Noise when disposal : it can lead to problems with the disturbance of neighbouring
residential areas
• Human wound : glass is dangerous once broken
Annexes 8 - 9.doc
• Consumers participation : put green glass in clear glass reduces the value of the load or may
cause it to be rejected. In countries where households are charged and recyclables taken away
free of charge, less care is taken to include only recyclable material in recycling collection
containers. Therefore automated processing of waste glass to remove colour and foreign objects
contamination has been more rapidly developed. On the other hand permitted contaminant
levels are set lower than in countries without direct waste disposal charges. This represent one
possibility to avoid this recycling limit.
The consultant concludes that recycling limits exists but could be avoided thanks to communication,
improved maintenance and custom changes.
1.2 Plastics[14], [15], [16]
Plastic applications constitute a very important issue as stakeholders point of view on their
recyclability diverge. The following critical factors were identified:
Technical limits
(a) Contamination
According to the nature of the impurities (surface or embedded contamination, e.g.) washing
can be considered to avoid this difficulty.
Bags containing raw materials may present sufficiently low contamination to be recycled
without difficulties. Contamination of pallet covers (plastic films) depends on the content and
the stock conditions. Recycling is therefore possible according to the contamination level.
(b) Insufficient amount (profitability aspect): throughput of recycling plants must be sufficient
in order to be profitable. The throughout will be dependent on a number of factors, including
available supply and market demand.
(c) Too thin plastic films : the thicker the film, the easier to recycle. This difficulty is linked to
contamination. It is only feasible to remove contamination if the thickness is sufficient.
(d) Nature of the plastics : due to the different molecular construction, practical recycling
depends on the ability to separate them from each other. Moreover, the output market is
different for each plastic type. Generally recycling is only possible if packaging is previously
sorted by material.
(e) (Main) Technical performance and processing difficulties : specific comments on these
subjects, if any, where integrated in the CBA.
Market acceptance
Annexes 8 - 9.doc
(f) Image : Can also be positive. Can be reversed if there are investments to convince the
consumers. Investments can only start if there are enough.
(g) Risk : failures in material performance are more frequent. A severe quality control could
partly overcome this problem, but would increase the cost of recycling.
(h) Minor characteristics (odour, touch and look) : current treatment techniques do not
overcome these problems. If guarantees are offered to consumers concerning the main technical
performance and if the image is improved, this might be overcome. This kind of difficulty could
also be reduced by marketing actions if marketers are convinced they have to help the market to
accept different colours.
(i) Legislative barriers : [[14], p.31]
EU food contact legislation (Pira to provide full reference) prevent the use of recycled plastics
for applications in direct contact with food. This limits the market potential of plastics recyclate
to non-food grade applications However there exist recycling techniques which allow PET
recycling into PET food grade.
(j) Polymer prices – polymer prices are very volatile and it is important it is recognised that the
virgin price can – and does - fall below the total costs associated with the recovery and
recycling of used plastic materials. The demise of many recycling companies is evidence of
this.
The cause of polymer price volatility is:
♦ Inequality in capacity and demand, which is difficult to rectify due to the fact that each new
production unit must be so large
♦ Stock building during a low price situation and stock use during high price situations
exacerbates the situation
♦ Price of virgin is also linked to oil price
However, the cost of collecting and recycling used film remains constant.
Economical reasons
(k) Recycling costs: high collection costs in Europe hinder general introduction of plastics
recycling. Development of sorting machines should reduce collecting and sorting costs and
increase the plastic streams quality.
1.3 Paper and board[17], [18]
Paper and board are widely recycled and not only as packaging waste. The critical factors are the
same for packaging and non packaging applications. They are described hereafter.
Annexes 8 - 9.doc
(1) Recycling close loop lifetime: paper cannot be continuously recycled (max ~4 times)
because the fibres will gradually degrade during the repeated pulping process
(2) Technical properties of the fibre – fibres from different sources (both virgin and recycled)
provide different technical properties. The demands of the end use product and the properties of
the fibres must be compatible. In effect, the end-use application determines the recycled content
that can be incorporated.
(3) Waste packaging composition (intrinsic contamination): paper to be recycled must be
pulpable ⇒ not laminated with plastics, no synthetic glues (⇒ sticky residues), no ink
(formulated to resist dispersion in water) ⇒ design new product for easier recycling
(4) Food contact legislation – food contact laws limit the use of recycled fibre for applications
in direct contact with food.
(5) Contamination : contamination such as fat or organic coming from the packaged product
should be avoided.
(6) Price volatilty and the balance of supply and demand :
Fibre is a global commodity, and the economic feasibility of particular paper and board
recycling activities may be dependent on the price of virgin fibre. Fibre prices are volatile:
♦ Inequality in capacity and demand, which is difficult to rectify due to the fact that each new
production unit is expensive and introduces significant new capacity
♦ Stock building during a low price situation and stock use during high price situations
exacerbates the situation
When the price of virgin fibre is low, then it can be cheaper than the cost of producing
recycled fibre.
1.4 Metals (steel and aluminium)
Identified limits to recycling are technical limits :
(1) Insufficient amount : there is very little aluminium in household waste stream (less than 1%).
Selective collection have to be adapted to local conditions
(2) Contamination : aluminium foils can be contaminated with food.
For both aluminium and steel recycling there is no output markets limits : fluctuating end-use
markets do not limit recycling as for paper. Whatever the price variation, it remains higher than for
other materials.
Annexes 8 - 9.doc
The consultant concludes that there is no technical, economical or marketing limits to recycling for
steel and aluminium packaging which can’t be avoided, except for contaminated aluminium foils.
1.5 Composites2
Packaging made of different material can be found at three different levels:
- compound packaging, where materials are put together with or without mechanical connections
or glue
- complex packaging, where materials are put together with glue or in a more durable manner
- composite packaging, where materials merge together in order to constitute a new material
Compound packaging are favourable to material recycling, while material recycling of complex
packaging can depend on technical and economic constraints. Energy recovery could be encouraged
due to the high calorific value of this latest packaging. [19]
Composite packaging contributes to a small extent to the packaging consumption (and waste).
For composite packaging waste other than liquid beverage cartons, the main difficulty is therefore
the low amount of waste. There are two main recycling route :
- they could be recycled with the main material stream, taking into account the same recycling
difficulties as for the main material recycling scheme
- Energy recovery or chemical recycling are recommended by the author (Sarens).[19].
Different publications [20] of the Alliance for Beverage Cartons and the Environment (ACE)
mentioned the composition of composites and suggest waste management options. No recycling
difficulties such as material separation are mentioned.
The composite beverage carton is made out of 89% paper and 11% PE or can consist of 70% paper,
25% PE and 5% Al.. Composite beverage carton is potentially suitable for different waste
management options:
- recycling: repulping enables the high quality fibre to be recycled, plastic and aluminium are
recovered separately
- energy recovery: high calorific value due to the content of paperboard and PE
- composting/biomethanisation: due to the high organic content of the paper
The consultant concludes that there is no technical constraints to recycle liquid beverage cartons.
Other recycling limits are the same as for the paper and board packaging waste recycling.
2 “Composite” means packaging made of different materials, and which cannot be separated by hand, none exceeding agiven percent by weight, which shall be established in accordance with the procedure laid down in Article 21 of
Annexes 8 - 9.doc
2 SUMMARY OF RECYCLING DIFFICULTIES
The above mentioned critical factors are considered in the definition of the range of recycling rates
considered in the cost benefit analysis. Table 1 shows the identified recycling constraints per
material. They are classified in factors which are reasonable reasons to limit recycling and factors
which may be valid points but are not really a reason to limit recycling.
Table 1 : Summary of the recycling difficulties
Recycling difficulties Glass Plastics Paper/board Metals CompositesCapacity X (X)Output market / market price X Xcontamination X X X (X)imbalance supply-demand X XInsufficient amount of waste X (X) XRecycling lifetime XNature of waste (too thin,…) X X XRecycling costs X
Factors which are not really a reason to limit recycling Noise XHuman wound XInsufficient maintenance XDisposers participation X X X X XColour, odour XResistance to the use of recyclate X
The critical factors identified in this section are taken into account in the calculations and the
hypothesis taken for packaging applications when no CBA is performed.
3 REUSE DIFFICULTIES[21], [22]
Reuse was one of the issue of this study. It is not a priority of the revision but it has to be taken into
account. Therefore a good understanding of its critical factors is essential to tackle the question. As
for recycling it is possible to distinguish between technical and economical constraints. The third
kind of constraints concern consumer convenience.
Economical constraints mainly concern the initial capital investment of re-usable packaging much
higher than for the disposable packaging3 and the on-cost burden of reverse logistics (e.g. transport
3 this is exacerbated if the reusable packaging line replaces a single trip line which has not yet reached the end of its
Annexes 8 - 9.doc
costs) of returning the empty packaging to its point of origin. The latest constraint can be reduced
by the development of European standard such as Europallets. Reuse can in this case happen in the
same geographical area as the use.
Maintenance (washing,…) and repairs can also can be costly and time consuming.
Consumer convenience can influence the reuse rate :
- by the choice between 1-way and reuse and
- by the level of return (the end-user may not return the packaging after use)
While the second point does not seem to be a limit to reuse rate, the first one has to be managed by
the way of communication and design.
Finally, technical limits mainly relate to the quality of reuse packaging and the necessity of an
effective control.
4 SECONDARY EFFECTS OF HIGHER RECYCLING TARGETS
Industry globally accepts efforts as long as they are the same for all competitors in all countries.
But they are opposed to :
ü very expensive systems (control becomes difficult and free riders get a sensible economic
advantage above honest competitors)
ü market decrease for packed products and/or for packaging materials
So the Industry's basic arguments/reasons are :
Reuse targets
ü "Reusable packaging is often less convenient for the consumer : heavier, no volume
reduction for storage at home (it may not be crushed), immobilised assets (deposit)… è the
market (of packed products) decreases.
ü Reuse system might be more expensive (mainly due to management cost of deposit and
returned packaging) è the market (of packed products) decreases."
Recycling targets
ü "Recycled materials compete with virgin materials è market prices and volume of virgin
materials decrease.
ü High cost encourages fraud infringers get a competitive advantage market share
decreases for honest industry"
So, the only basic concern of the industry is, by definition in an open market economy, to
maintain/increase the sales and benefits. So Industry's basic arguments/reasons to resist high targets
Annexes 8 - 9.doc
As industry seeks to reduce their waste management cost, they are inclined to favour energy
recovery (whose cost is supported by the public authorities). This means industry won't try to do
better than the mandatory targets. If industry had to finance all waste management operations (i.e.
also incineration and landfilling), recycling would appear relatively more attractive at their eyes.
This would motivate industry to do more than mandatory, give more confidence in the recycling
chain and so favour investments.
Annex 10: Presentation of the CBA results
1 Steel from household sources
1.1 Scenarios considered
Table 1 summarises the parameters considered for the baseline scenarios modelled.
Table 1 : Scenarios considered for steelPopulationdensity
Selective collection scheme Recyclingrate achieved
MSW waste managementoption
Scenario 1 Low None 0% Landfill
Scenario 2 Low None 0% IncinerationScenario 3 Low None 80% Incineration with slag
recoveryScenario 4 Low Separate kerbside collection 40-60% LandfillScenario 5 Low Separate kerbside collection 40-60% IncinerationScenario 6 Low Separate kerbside collection 88-92% Incineration with slag
recoveryScenario 7 Low Bring scheme 15-21% LandfillScenario 8 Low Bring scheme 15-21% IncinerationScenario 9 Low Bring scheme 83-84% Incineration with slag
recoveryScenario 10 High None 0% LandfillScenario 11 High None 0% IncinerationScenario 12 High None 80% Incineration with slag
recoveryScenario 13 High Separate kerbside collection 40-60% LandfillScenario 14 High Separate kerbside collection 40-60% IncinerationScenario 15 High Separate kerbside collection 88-92% Incineration with slag
recoveryScenario 16 High Bring scheme 15-21% LandfillScenario 17 High Bring scheme 15-21% IncinerationScenario 18 High Bring scheme 83-84% Incineration with slag
recovery
1.2 Results of the cost benefit analysis of steel
Table 2 :Steel – low population density: Internal costs, external costs and total social costs
Collection method N/A N/A N/ARecycling rate 0% 0% 80%
Residual waste management option Landfill Incineration
Incineration with recovery of steel from
slagsExternalities
GWP (kg CO2 eq.) 0,4 0,6 -14,0 -5,3 to -7,0 -5,1 to -6,8 -14,9 to -15,2 -0,8 to -2,5 -0,6 to -2,3 -14,2 to -14,5Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0
Acidification (Acid equiv.) 0,0 0,1 -0,2 0,0 to -0,1 0,0 to 0,0 -0,2 to -0,2 0,0 to 0,0 0,1 to 0,0 -0,2 to -0,2Toxicity Carcinogens (Cd equiv) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) 0,1 0,2 -6,5 -2,6 to -3,4 -2,5 to -3,3 -7,0 to -7,1 -0,4 to -1,1 -0,3 to -1,0 -6,5 to -6,6
Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,0 0,5 0,2 to 0,3 0,2 to 0,3 0,5 to 0,5 0,1 to 0,2 0,1 to 0,2 0,5 to 0,5Toxicity Particulates & aerosols (PM10 equiv) 9,2 8,8 13,0 14,8 to 16,4 14,5 to 16,2 17,2 to 18,5 9,3 to 9,3 8,9 to 8,9 12,7 to 12,4
Toxicity Smog (ethylene equiv.) 0,3 0,2 -0,4 0,2 to 0,1 0,2 to 0,1 -0,2 to -0,2 0,2 to 0,2 0,2 to 0,2 -0,3 to -0,3Black smoke (kg dust eq.) 0,2 0,3 -0,7 -0,1 to -0,3 -0,1 to -0,2 -0,8 to -0,8 0,1 to 0,0 0,2 to 0,1 -0,7 to -0,7
Fertilisation -0,1 -0,1 0,5 0,1 to 0,1 0,1 to 0,1 0,5 to 0,5 -0,1 to 0,0 -0,1 to 0,0 0,5 to 0,5Traffic accidents (risk equiv.) 0,1 0,1 0,6 0,4 to 0,5 0,4 to 0,5 0,8 to 0,8 0,6 to 1,2 0,6 to 1,2 1,0 to 1,6
Traffic Congestion (car km equiv.) 0,1 0,1 11,1 1,3 to 1,7 1,4 to 1,7 8,7 to 8,0 0,4 to 0,8 0,4 to 0,8 10,6 to 9,9Traffic Noise (car km equiv.) 0,4 0,4 1,1 1,5 to 1,8 1,5 to 1,8 2,0 to 2,2 0,6 to 0,8 0,6 to 0,8 1,3 to 1,4
Water Quality Eutrophication (P equiv.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 24,8 to 21,1 6,8 to 5,8 6,8 to 5,8 34,4 to 30,7 9,4 to 8,4 9,4 to 8,4
TOTAL EXTERNALITIES 47,8 21,0 15,1 35,3 to 31,5 17,3 to 16,2 13,4 to 12,9 44,4 to 39,6 19,4 to 17,3 14,0 to 12,5INTERNAL COSTS 112,2 141,4 93,4 133,2 to 143,8 150,8 to 155,4 122,0 to 136,2 116,9 to 118,8 141,7 to 141,8 100,9 to 103,9TOTAL SOCIAL COSTS 160,0 162,4 108,5 168,5 to 175,2 168,0 to 171,6 135,3 to 149,1 161,3 to 158,4 161,2 to 159,1 114,9 to 116,4
Bring scheme15-21%
Landfill
Separate kerbside
collection40-60
Incineration
Separate kerbside
collection88-92%
Incineration with recovery of steel from
slags
Bring scheme15-21
Incineration
Separate Kerbside collection
40-60%
Landfill
Bring scheme83-84%
Incineration with recovery of steel from
slags
Table 3 : Steel – high population density: Internal costs, external costs and total social costs
Collection method N/A N/A N/ARecycling rate 0% 0% 80%
Residual waste management option Landfill Incineration
Incineration with recovery of steel from
slagsExeternalities
GWP (kg CO2 eq.) 0,3 0,5 -14,8 -3,4 to -4,8 -3,2 to -4,7 -14,6 to -14,6 -0,7 to -1,6 -0,4 to -1,3 -14,9 to -15,1Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0
Acidification (Acid equiv.) 0,0 0,1 -0,2 0,0 to -0,1 0,0 to 0,0 -0,2 to -0,2 0,0 to 0,0 0,0 to 0,0 -0,2 to -0,2Toxicity Carcinogens (Cd equiv) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) 0,1 0,2 -6,7 -1,6 to -2,2 -1,5 to -2,2 -6,6 to -6,6 -0,3 to -0,7 -0,2 to -0,6 -6,7 to -6,8
Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,0 0,5 0,2 to 0,2 0,1 to 0,2 0,5 to 0,5 0,1 to 0,1 0,1 to 0,1 0,5 to 0,5Toxicity Particulates & aerosols (PM10 equiv) 8,0 7,5 -7,3 8,8 to 9,1 8,5 to 8,8 -2,6 to -0,8 7,4 to 6,9 7,0 to 6,5 -7,0 to -6,8
Toxicity Smog (ethylene equiv.) 0,2 0,2 -0,7 0,0 to 0,0 0,0 to -0,1 -0,7 to -0,6 0,1 to 0,1 0,1 to 0,1 -0,7 to -0,7Black smoke (kg dust eq.) 0,2 0,2 -0,9 -0,1 to -0,2 0,0 to -0,1 -0,9 to -0,9 0,1 to 0,0 0,2 to 0,1 -0,9 to -0,9
Fertilisation -0,1 -0,1 0,7 0,1 to 0,1 0,1 to 0,1 0,7 to 0,6 0,0 to 0,0 0,0 to 0,0 0,7 to 0,7Traffic accidents (risk equiv.) 0,2 0,2 0,3 0,4 to 0,5 0,4 to 0,5 0,5 to 0,6 0,3 to 0,4 0,3 to 0,4 0,4 to 0,5
Traffic Congestion (car km equiv.) 8,2 8,2 10,6 20,3 to 25,1 20,3 to 25,1 22,1 to 26,7 11,9 to 15,7 11,9 to 15,7 14,2 to 17,8Traffic Noise (car km equiv.) 0,2 0,2 0,3 0,5 to 0,6 0,5 to 0,6 0,6 to 0,7 0,2 to 0,3 0,2 to 0,3 0,4 to 0,4
Water Quality Eutrophication (P equiv.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 27,8 to 24,1 7,6 to 6,6 7,6 to 6,6 35,2 to 33,3 9,6 to 9,1 9,6 to 9,1
TOTAL EXTERNALITIES 54,2 27,3 -8,1 52,9 to 52,4 32,7 to 34,9 6,2 to 11,9 54,4 to 54,7 28,9 to 30,5 -4,7 to -1,4INTERNAL COSTS 132,0 161,2 113,2 138,3 to 141,5 155,8 to 153,2 127,0 to 134,0 131,5 to 131,3 156,3 to 154,4 115,5 to 116,5TOTAL SOCIAL COSTS 186,2 188,5 105,1 191,2 to 193,9 188,6 to 188,1 133,2 to 145,9 185,9 to 186,0 185,2 to 184,8 110,8 to 115,1
Bring scheme83-84%
Incineration with recovery of steel from
slags
Bring scheme15-21%
Incineration
Separate Kerbside collection
40-60%
Landfill
Bring scheme15-21%
Landfill
Separate kerbside
collection40-60%
Incineration
Separate kerbside
collection88-92%
Incineration with recovery of steel from
slags
Graph 1 : Steel – low population density: Total social costs
Steel - Low PopulationTotal Social Cost
020406080
100120140160180200
L a n d f i l l Incineration Incineration
w i th s tee l
r e c o v e r y
Separate
kerbs ide
collection /
L a n d f i l l
Separate
kerbs ide
collection /
Incineration
Separate
kerbs ide
collection /
Incineration
w i th s tee l
r e c o v e r y
Br ing scheme
/ Landfill
Br ing scheme
/ Incineration
Br ing scheme
/ Incineration
w i th s tee l
r e c o v e r y
Scenario
To
tal S
oci
al C
ost
Graph 2 : Steel – high population density: Total social costs
Steel - High Population DensityTotal Social Cost
0
50
100
150
200
250
Landfill Separatekerbside
collection /Landfill
Bringscheme /Landfill
Incineration Separatekerbside
collection /Incineration
Bringscheme /
Incineration
Incinerationwith steelrecovery
Separatekerbside
collection /Incinerationwith steelrecovery
Bringscheme /
Incinerationwith steelrecovery
Scenario
To
tal S
oci
al C
ost
(E
uro
per
to
nn
e)
1.3 Main findings:
For low population density:♦ From total social cost perspective, where landfilling is the MSW option, a bring scheme achieving a
recycling rate of 7-17% is the optimum system from the scenarios considered. (Although the differencebetween all scenarios is very small).
♦ From total social cost perspective, where incineration with energy recovery but no slag recovery is theMSW option, a bring scheme achieving a recycling rate of 7-17% is the optimum system from thescenarios considered.
♦ From total social cost perspective, where incineration with energy recovery and slag recovery is the MSWoption, 100% incineration with recycling of steel recovered from slags is the optimum system for thescenarios considered.
For high population density:♦ From total social cost perspective, where landfilling is the MSW option, 100% landfilling is the optimum
system (although the difference between the systems is very small)♦ From total social cost perspective, where incineration with energy recovery but no slag recovery is the
MSW option, there is no distinction between 100% incineration and a bring scheme achieving a recyclingrate of 5-10% as the optimum system from the scenarios considered.
♦ From total social cost perspective, where incineration with energy recovery and slag recovery is the MSWoption, 100% incineration with recycling of steel recovered from slags is the optimum system for thescenarios considered.
1.4 Sensitivity analysis
1.4.1 Methodological choices1.4.1.1 Choice of external valuationsGraph 3 & Graph 4 show the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impact results,but applying different impact assessment valuations (see Annex 4 for a list of maximum and minimumvaluations applied).
Graph 3 & Graph 4 show that the results achieved and conclusions drawn are highly dependent upon theeconomic valuations applied to the environmental impacts. Applying the full range of available economicvaluations makes it impossible to distinguish an optimum system from the scenarios studied.
Graph 3 : Steel – low population density: Sensitivity of the results to the external economic valuations applied
Steel - Low PopulationSensitivity analysis on variations in economic valuations applied
-150.0-100.0-50.0
0.050.0
100.0
150.0200.0250.0
Landfill Incineration Incinerationwith steelrecovery
Separatekerbside
collection /Landfill
Separatekerbside
collection /Incineration
Separatekerbside
collection /Incinerationwith steelrecovery
Bringscheme /Landfill
Bringscheme /
Incineration
Bringscheme /
Incinerationwith steelrecovery
Scenario
To
tal S
oci
al C
ost
(E
uro
per
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e)
Graph 4 : Steel – high population density: Sensitivity of the results to the external economic valuationsapplied
Steel - High Population DensitySensitivity analysis on variations in economic valuations applied
-150
-100
-50
0
50
100
150
200
250
Landfill Separatekerbside
collection /Landfill
Bring scheme /Landfill
Incineration Separatekerbside
collection /Incineration
Bring scheme /Incineration
Incinerationwith steelrecovery
Separatekerbside
collection /Incinerationwith steelrecovery
Bring scheme /Incinerationwith steelrecovery
Scenario
To
tal S
oci
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ost
(E
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e)
1.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium. Evenwhere equivalent waste management practices are compared internal costs can vary considerably betweenMember States, depending on a range of factors such as cost of living and geographical considerations(mountainous regions, island populations, etc.). In this part of the sensitivity analysis, the effect on the resultsof considering a +/-20% variation in internal costs is investigated. The results are presented in Graph 5 &Graph 6.
The graphs show that the results achieved and conclusions drawn are highly dependent upon the internal costsapplied. Applying a range of +/-20% to the internal costs makes it impossible to distinguish an optimumsystem from the scenarios studied.
Graph 5 : Steel – low population density: Sensitivity of the results to the internal economic costs considered
Steel - Low PopulationSensitivity analysis on variations in Internal Costs
0
50
100
150
200
250
Landfill Separatekerbside
collection /Landfill
Bring scheme/ Landfill
Incineration Separatekerbside
collection /Incineration
Bring scheme/ Incineration
Incinerationwith steelrecovery
Separatekerbside
collection /Incinerationwith steelrecovery
Bring scheme/ Incineration
with steelrecovery
Scenario
To
tal S
oci
al C
ost
(E
uro
per
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e)
Graph 6 : Steel – high population density: Sensitivity of the results to the internal economic costs considered
Steel - High Population DensitySensitivity analysis on variations in Internal Costs
0
50
100
150
200
250
Landfill Separatekerbside
collection /Landfill
Bring scheme /Landfill
Incineration Separatekerbside
collection /Incineration
Bring scheme /Incineration
Incinerationwith steelrecovery
Separatekerbside
collection /Incinerationwith steelrecovery
Bring scheme /Incinerationwith steelrecovery
Scenario
To
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oci
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(E
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e)
1.4.1.3 Inclusion of employment as an impact category
Graph 7 & Graph 8 show the sensitivity of the analysis to the inclusion of employment as an impact category.The graphs have been produced by including employment along with the other environmental impacts used inthe baseline analysis.
Graph 7 : Steel – low pop. density: Sensitivity of the results to the addition of employment as an impactcategory
Steel - Low PopulationTotal Social Cost
0.020.040.060.080.0
100.0120.0140.0160.0180.0
Landfill Incineration Incinerationwith steelrecovery
Separatekerbside
collection /Landfill
Separatekerbside
collection /Incineration
Separatekerbside
collection /Incinerationwith steelrecovery
Bringscheme /Landfill
Bringscheme /
Incineration
Bringscheme /
Incinerationwith steelrecovery
Scenario
To
tal S
oci
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ost
(E
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e)
Graph 8 : Steel – high pop. density: Sensitivity of the results to the addition of employment as an impactcategory
Steel - High Population DensityTotal Social Cost
020406080
100120140160180200
Landfill Separatekerbside
collection /Landfill
Bringscheme /Landfill
Incineration Separatekerbside
collection /Incineration
Bringscheme /
Incineration
Incinerationwith steelrecovery
Separatekerbside
collection /Incinerationwith steelrecovery
Bringscheme /
Incinerationwith steelrecovery
Scenario
To
tal S
oci
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ost
(E
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e)
The following implications of including employment should be considered:For low population density:♦ From total social cost perspective, where landfill is the MSW option it is no longer possible to distinguish
between the scenarios♦ From total social cost perspective, where incineration with energy recovery but no slag recovery is the
MSW option it is no longer possible to distinguish between the scenarios♦ From total social cost perspective, where incineration with energy recovery and slag recovery is the MSW
option, it is not possible to distinguish between 100% incineration with recycling of steel recovered fromslags or a bring scheme achieving 7-17% recycling as the optimum system for the scenarios considered.
For high population density:♦ From total social cost perspective, where landfilling is the MSW option, it is no longer possible to
distinguish between the scenarios♦ From total social cost perspective, where incineration with energy recovery but no slag recovery is the
MSW option it is no longer possible to distinguish between the scenarios♦ From total social cost perspective, where incineration with energy recovery and slag recovery is the MSW
option, it is not possible to distinguish between 100% incineration with recycling of steel recovered fromslags or a bring scheme achieving 5-10% recycling as the optimum system for the scenarios considered.
1.4.2 Scenario and modelling choices
Findings from the sensitivity analysis of scenario and modelling choices are summarised in Table 4.
Table 4 : Summary of sensitivity analysis of scenario and modelling choices for steelParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model
Combined heat and powerNo significant effect on scale ofCBA results
No effect on choice of optimumscenario
Incineration modelOffset electricity
No significant effect on scale ofCBA results
No effect on choice of optimumscenario
Transport distancesMSW collection round
Kerbside collection roundCollection from bring bank
Transport from sorting plant toreprocessor
Transport assumptions made canhave significant influence on therelative standing of results.
Considering best and worst casesfor each scenario makes itimpossible to determine anoptimum system for each set ofconditions
Transport distanceConsumer transport to bring
bank
Consumer transport assumptionscritical to relative standing of thebring scheme scenario
Alternative assumptions wouldaffect the choice of optimumscenario
2 Aluminium cans
2.1 Scenarios considered
The table below summarises the parameters considered for the baseline scenarios modelled.
Table 5 : Scenarios considered for aluminium cansPopulationdensity
Selective collection scheme Recycling rateachieved
MSW waste management option
Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low None 76% Incineration with slag recoveryScenario 4 Low Separate kerbside collection 45-55% LandfillScenario 5 Low Separate kerbside collection 45-55% IncinerationScenario 6 Low Separate kerbside collection 87-89% Incineration with slag recoveryScenario 7 Low Bring scheme 31-41% LandfillScenario 8 Low Bring scheme 31-41% IncinerationScenario 9 Low Bring scheme 83-86% Incineration with slag recoveryScenario 10 High None 0% LandfillScenario 11 High None 0% IncinerationScenario 12 High None 76% Incineration with slag recoveryScenario 13 High Separate kerbside collection 45-55% LandfillScenario 14 High Separate kerbside collection 45-55% IncinerationScenario 15 High Separate kerbside collection 87-89% Incineration with slag recoveryScenario 16 High Bring scheme 31-41% LandfillScenario 17 High Bring scheme 31-41% IncinerationScenario 18 High Bring scheme 83-86% Incineration with slag recovery
2.2 Results of the cost benefit analysis for aluminium cans
This section presents and discusses the results of the cost benefit analysis for aluminium cans.
Table 6 : Aluminium cans - low population density: Internal costs, external costs and total social costs
Collection method N/A N/A N/A Separate Kerbsidecollection
Separate kerbsidecollection
Separate kerbsidecollection
Bring scheme Bring scheme Bring scheme
Recycling rate 0,0 0,0 80% 45-55% 45-55% 87-89% 31-41% 31-41% 83-86%Residual waste management option Landfill Inciner
ationIncinerati
on withnodule
recovery
Landfill Incineration Incineration withnodule recovery
Landfill Incineration Incineration withnodule recovery
ExeternalitiesGWP (kg CO2 eq.) 0,4 1,0 -95,5 -55,9 to -68,4 -55,5 to -68,1 -108,6 to -111,5 -38,4 to -50,9 -37,9 to -50,5 -104,5 to -107,5
Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Acidification (Acid equiv.) 0,0 0,1 -13,1 -7,7 to -9,4 -7,7 to -9,4 -14,9 to -15,4 -5,3 to -7,0 -5,2 to -7,0 -14,3 to -14,8
Toxicity Carcinogens (Cd equiv) 0,0 0,0 -19,3 -11,4 to -13,9 -11,4 to -13,9 -22,0 to -22,6 -7,9 to -10,4 -7,9 to -10,4 -21,2 to -21,8
Toxicity Gaseous (SO2 equiv.) 0,1 0,3 -79,6 -47,0 to -57,5 -46,9 to -57,4 -90,8 to -93,3 -32,0 to -42,3 -31,9 to -42,2 -87,0 to -89,4Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,1 -337,7 -199.9 to -244,4 -199,9 to -244,4 -385,7 to -396,4 -137,6 to -182,1 -137,7 to -182,1 -370,7 to -381,4
Toxicity Particulates & aerosols (PM10 equiv) 9,7 10,5 -550,4 -306.7 to -377,0 -306,2 to -376,6 -614,7 to -629,0 -213,4 to -285,3 -212,8 to -284,8 -599,8 to -615,8Toxicity Smog (ethylene equiv.) 0,3 0,3 -18,0 -10,2 to -12,5 -10,2 to -12,5 -20,2 to -20,7 -6,9 to -9,2 -6,9 to -9,2 -19,5 to -20,0
Black smoke (kg dust eq.) 0,2 0,4 -43,0 -25,3 to -31,0 -25,2 to -30,9 -49,1 to -50,5 -17,3 to -23,0 -17,2 to -22,9 -47,2 to -48,5
Fertilisation -0,1 -0,2 10,6 6,1 to 7,4 6,0 to 7,4 11,9 to 12,2 4,1 to 5,5 4,1 to 5,5 11,5 to 11,8Traffic accidents (risk equiv.) 0,1 0,1 0,6 0,8 to 0,9 0,8 to 0,9 1,0 to 1,1 2,2 to 2,9 2,2 to 2,9 2,5 to 3,2
Traffic Congestion (car km equiv.) 0,1 0,1 10,8 6,8 to 8,3 6,8 to 8,3 12,7 to 13,1 4,8 to 6,3 4,8 to 6,3 12,1 to 12,6Traffic Noise (car km equiv.) 0,4 0,4 1,1 2,2 to 2,6 2,2 to 2,6 2,6 to 2,9 1,3 to 1,6 1,3 to 1,6 1,8 to 2,1
Water Quality Eutrophication (P equiv.) 0,0 0,0 -1,0 -0,6 to -0,7 -0,6 to -0,7 -1,1 to -1,1 -0,4 to -0,5 -0,4 to -0,5 -1,1 to -1,1
Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 20,4 to 16,7 5,6 to 4,6 5,6 to 4,6 25,5 to 21,8 7,0 to 6,0 7,0 to 6,0TOTAL EXTERNALITIES 48,3 23,4 -1124,4 -628,5 to -778,9 -642,3 to -790,2 -1273,5 to -1306,6 -421,2 to -572,7 -438,4 to -587,4 -1230,3 to -1264,5INTERNAL COSTS 555,0 453,0 88,0 541,0 to 537,9 484,9 to 492,0 336,5 to 327,7 531,3 to 523,6 460,9 to 463,4 209,0 to 248,1TOTAL SOCIAL COSTS 603,3 476,4 -1036,4 -87,5 to -241,0 -157,3 to -298,2 -937,0 to -978,9 110,1 to -49,1 22,5 to -124,0 -1021,3 to -1016,5
Table 7 : Aluminium cans – high population density: Internal costs, external costs and total social costs
Collection method N/A N/A N/A Separate Kerbsidecollection
Separate kerbsidecollection
Separate kerbsidecollection
Bring scheme Bring scheme Bring scheme
Recycling rate 0,0 0,0 80% 45-55% 45-55% 87-89% 31-41% 31-41% 83-86%Residual waste management option Landfill Inciner
ationIncinerati
on withnodule
recovery
Landfill Incineration Incineration withnodule recovery
Landfill Incineration Incineration withnodule recovery
Externalities
GWP (kg CO2 eq.) 0,3 0,9 -95,9 -56,4 to -69,0 -56,1 to -68,8 -109,3 to -112,3 -38,8 to -51,4 -38,4 to -51,1 -105,2 to -108,2
Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Acidification (Acid equiv.) 0,0 0,1 -13,1 -7,8 to -9,5 -7,7 to -9,5 -15,0 to -15,4 -5,3 to -7,1 -5,3 to -7,0 -14,4 to -14,8
Toxicity Carcinogens (Cd equiv) 0,0 0,0 -19,3 -11,4 to -14,0 -11,4 to -13,9 -22,0 to -22,6 -7,9 to -10,4 -7,9 to -10,4 -21,2 to -21,8Toxicity Gaseous (SO2 equiv.) 0,1 0,3 -79,7 -47,1 to -57,6 -47,0 to -57,5 -91,0 to -93,5 -32,3 to -42,7 -32,1 to -42,6 -87,3 to -89,8
Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,1 -337,7 -199,9 to -244,4 -199,9 to -244,4 -385,7 to -396,4 -137,7 to -182,1 -137,7 to -182,1 -370,8 to -381,4
Toxicity Particulates & aerosols (PM10 equiv) 8,4 9,2 -563,9 -312,8 to -384,2 -312,3 to -383,8 -627,5 to -641,7 -218,1 to -291,1 -217,5 to -290,6 -612,9 to -628,7Toxicity Smog (ethylene equiv.) 0,2 0,2 -18,2 -10,5 to -12,9 -10,5 to -12,9 -20,6 to -21,1 -7,2 to -9,5 -7,2 to -9,5 -19,9 to -20,4
Black smoke (kg dust eq.) 0,2 0,4 -43,1 -25,5 to -31,2 -25,4 to -31,1 -49,3 to -50,7 -17,5 to -23,2 -17,3 to -23,1 -47,4 to -48,7Fertilisation -0,1 -0,1 10,7 6,2 to 7,6 6,2 to 7,6 12,1 to 12,4 4,2 to 5,6 4,2 to 5,6 11,7 to 12,0
Traffic accidents (risk equiv.) 0,2 0,2 0,6 1,0 to 1,2 1,0 to 1,2 1,2 to 1,4 1,1 to 1,5 1,1 to 1,5 1,5 to 1,7
Traffic Congestion (car km equiv.) 8,2 8,2 18,8 41,3 to 48,7 41,3 to 48,7 47,2 to 53,5 35,0 to 43,6 35,0 to 43,6 42,3 to 49,9Traffic Noise (car km equiv.) 0,2 0,2 0,9 1,2 to 1,4 1,2 to 1,4 1,6 to 1,7 0,7 to 0,9 0,7 to 0,9 1,2 to 1,3
Water Quality Eutrophication (P equiv.) 0,0 0,0 -1,0 -0,6 to -0,7 -0,6 to -0,7 -1,1 to -1,1 -0,4 to -0,5 -0,4 to -0,5 -1,1 to -1,1Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 20,4 to 16,7 5,6 to 4,6 5,6 to 4,6 25,5 to 21,8 7,0 to 6,0 7,0 to 6,0
TOTAL EXTERNALITIES 54,7 29,7 -1130,7 -601,9 to -747,8 -615,6 to -759,0 -1253,9 to -1281,2 -398,4 to -544,6 -415,6 to -559,3 -1216,3 to -1244,0INTERNAL COSTS 665,0 563,0 198,0 585,2 to 567,4 529,1 to 521,5 377,1 to 357,3 597,3 to 575,5 526,9 to 515,3 275,1 to 300,0TOTAL SOCIAL COSTS 719,7 592,7 -932,7 -16,7 to -180,4 -86,6 to -237,5 -876,8 to -923,9 198,9 to 30,9 111,3 to -44,0 -941,2 to -944,0
Graph 9 : Aluminium cans – low population density: Total social cost
Aluminium cans - Low Population DensityTotal Social Cost
-1200-1000
-800-600-400-200
0200400600800
Landfill Separatekerbside
collection /landfill
Bring scheme /landfill
Incineration Separatekerbside
collection /incineration
Bring scheme /incineration
Incinerationwith recovery
Separatekerbside
collection /incineration
with recovery
Bring scheme /incineration
with recovery
Scenario
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Graph 10 : Aluminium cans – high population density: Total social cost
Aluminium cans - High Population DensityTotal Social Cost
-1200-1000-800-600-400-200
0200400600800
1000
Landfill Separatekerbside
collection /landfill
Bring scheme /landfill
Incineration Separatekerbside
collection /incineration
Bring scheme /incineration
Incinerationwith recovery
Separatekerbside
collection /incineration
with recovery
Bring scheme /incineration
with recovery
Scenario
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2.3 Main findings:
For low population density:♦ From total social cost perspective, where landfilling is the MSW option, a separate kerbside
collection scheme achieving a recycling rate of 45-55% is the optimum system from the scenariosconsidered.
♦ From total social cost perspective, where incineration with energy recovery but no slag recovery isthe MSW option a separate kerbside collection scheme achieving a recycling rate of 45-55% is theoptimum system from the scenarios considered.
♦ From total social cost perspective, where incineration with energy recovery and slag recovery isthe MSW option, 100% incineration with recycling of aluminium recovered from slags is theoptimum system for the scenarios considered.
For high population density:♦ From total social cost perspective, where landfilling is the MSW option, a separate kerbside
collection scheme achieving a recycling rate of 45-55% is the optimum system from the scenariosconsidered.
♦ From total social cost perspective, where incineration with energy recovery but no slag recovery isthe MSW option a separate kerbside collection scheme achieving a recycling rate of 45-55% is theoptimum system from the scenarios considered.
♦ From total social cost perspective, where incineration with energy recovery and slag recovery isthe MSW option, a bring scheme achieving a recycling rate of 31-41% is the optimum system forthe scenarios considered.
2.4 Sensitivity analysis
2.4.1 Methodological choices2.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impactresults, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied).
For low population density, the graphs show when the full range of economic valuations is appliedwhere landfill is the MSW option it is no longer possible to distinguish between separate kerbsidecollection achieving 45-55% recycling and a bring scheme achieving 31-41% as the optimal systemfrom those considered.
Where incineration with energy recovery but no recovery of slags is the MSW option it is no longerpossible to distinguish between separate kerbside collection achieving 45-55% recycling and a bringscheme achieving 31-41% as the optimal system from those considered. that for low populationdensity.
Where incineration with slag recovery is the MSW option, it is not possible to distinguish between theoptions considered.
For high population density, when the full range of economic valuations is applied where landfill isthe MSW option it is no longer possible to distinguish between separate kerbside collection achieving45-55% recycling and a bring scheme achieving 31-41% as the optimal system from those considered.
Where incineration with energy recovery but no recovery of slags is the MSW option it is no longerpossible to distinguish between separate kerbside collection achieving 45-55% recycling and a bringscheme achieving 31-41% as the optimal system from those considered.
Where incineration with slag recovery is the MSW option, it is not possible to distinguish between theoptions considered.
Graph 11 : Aluminium cans – low population density: Sensitivity of results to the external economicvaluations applied
Aluminium cans - Low Population DensitySensitivity analysis on variations in economic valuations applied
-18000
-16000
-14000
-12000
-10000
-8000
-6000
-4000
-2000
0
2000
Landfill Separatekerbside
collection /landfill
Bringscheme /
landfill
Incineration Separatekerbside
collection /incineration
Bringscheme /
incineration
Incinerationwith
recovery
Separatekerbside
collection /incineration
withrecovery
Bringscheme /
incinerationwith
recovery
Scenario
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Graph 12 : Aluminium cans – high population density: Sensitivity of results to the external economicvaluations applied
Aluminium cans - High Population DensitySensitivity analysis on variations in economic valuations applied
-18000
-16000
-14000
-12000
-10000
-8000
-6000
-4000
-2000
0
2000
Landfill Separatekerbside
collection /landfill
Bringscheme /
landfill
Incineration Separatekerbside
collection /incineration
Bringscheme /
incineration
Incinerationwith
recovery
Separatekerbside
collection /incineration
withrecovery
Bringscheme /
incinerationwith
recovery
Scenario
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2.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium.Even where equivalent waste management practices are compared internal costs can vary considerablybetween Member States, depending on a range of factors such as cost of living and geographicalconsiderations (mountainous regions, island populations, etc.). In this part of the sensitivity analysis,the effect on the results of considering a +/-20% variation in internal costs is investigated. The resultsare presented in the graph below.
For low population density where landfill is the MSW option, it is no longer possible to distinguishbetween separate kerbside collection achieving 45-55% recycling and a bring scheme achieving 31-41% as the optimal system from those considered.
Where incineration with energy recovery but no slag recovery is the MSW option, the results are notsensitive to variations in the internal costs.
Where incineration with energy recovery and slag recovery is the MSW option it is not possible todistinguish between the options considered when variations in internal costs are taken into account.
For high population density, where landfill is the MSW option, it is no longer possible to distinguishbetween separate kerbside collection achieving 45-55% recycling and a bring scheme achieving 31-41% as the optimal system from those considered.
Where incineration with energy recovery but no slag recovery is the MSW option, the results are notsensitive to variations in the internal costs.
Where incineration with energy recovery and slag recovery is the MSW option it is not possible todistinguish between the options considered when variations in internal costs are taken into account.
Graph 13 : Aluminium cans – low population density: Sensitivity of the results to the internaleconomic costs considered
Aluminium cans - Low Population DensitySensitivity analysis on variations in Internal Costs
-1200.0-1000.0-800.0-600.0-400.0-200.0
0.0200.0400.0600.0800.0
1000.0
Landfill Incineration Incinerationwith
recovery
Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Separatekerbside
collection /incineration
withrecovery
Bringscheme /
landfill
Bringscheme /
incineration
Bringscheme /
incinerationwith
recoveryScenario
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Graph 14 : Aluminium cans – high population density: Sensitivity of the results to the internaleconomic costs considered
Aluminium cans - High Population DensitySensitivity analysis on variations in Internal Costs
-1500.0
-1000.0
-500.0
0.0
500.0
1000.0
Landfill Incineration Incinerationwith
recovery
Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Separatekerbside
collection /incineration
withrecovery
Bringscheme /
landfill
Bringscheme /
incineration
Bringscheme /
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Scenario
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2.4.1.3 Inclusion of employment as an impact category
The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis.
The graphs show that the results achieved and conclusions drawn are not sensitive to the inclusion ofthis parameter as an external impact category.
Graph 15 : Aluminium cans – low population density: Sensitivity of the results to the addition ofemployment as an impact category
Aluminium cans - low population densityTotal Social Cost when including employment as an impact category
-1200
-1000
-800
-600
-400
-200
0
200
400
600
800
Landfill Incineration Incinerationwith
recovery
Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Separatekerbside
collection /incineration
withrecovery
Bringscheme /
landfill
Bringscheme /
incineration
Bringscheme /
incinerationwith
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Graph 16 : Aluminium cans – high population density: Sensitivity of the results to the addition ofemployment as an impact category
Aluminium cans - high population densityTotal Social Cost when including employment as an impact category
-1200-1000-800-600-400-200
0200400600800
Landfill Incineration Incinerationwith
recovery
Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Separatekerbside
collection /incineration
withrecovery
Bringscheme /
landfill
Bringscheme /
incineration
Bringscheme /
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Scenario
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2.4.2 Scenario and modelling choices
Findings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.
Table 8 : Summary of sensitivity analysis of scenario and modelling choices for aluminium cansParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model
Combined heat and powerNo significant effect on scale ofCBA results
No influence on choice ofoptimal scenario
Incineration modelOffset electricity
No significant effect on scale ofCBA results
No influence on choice ofoptimal scenario
Transport distancesMSW collection round
Kerbside collection roundCollection from bring bank
Transport from sorting plant toreprocessor
No influence on the relativestanding of options
No influence on choice ofoptimal scenario
Transport distanceConsumer transport to bring
bankNo influence on the relativestanding of options
No influence on choice ofoptimal scenario
3 Aluminium (other rigid and semi-rigid aluminium packaging,excluding beverage cans)
3.1 Scenarios considered
The table below summarises the parameters considered for the baseline scenarios modelled.
Table 9 : Scenarios considered for aluminium (other rigid than beverage cans)Populationdensity
Selective collection scheme Recyclingrate achieved
MSW waste managementoption
Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low None 0% Incineration with slag
recoveryScenario 4 Low Separate kerbside collection 7-17% LandfillScenario 5 Low Separate kerbside collection 7-17% IncinerationScenario 6 Low Separate kerbside collection 7-17% Incineration with slag
recoveryScenario 7 Low Bring scheme 3-10% LandfillScenario 8 Low Bring scheme 3-10% IncinerationScenario 9 Low Bring scheme 3-10% Incineration with slag
recoveryScenario 10 High None 0% LandfillScenario 11 High None 0% IncinerationScenario 12 High None 0% Incineration with slag
recoveryScenario 13 High Separate kerbside collection 6-16% LandfillScenario 14 High Separate kerbside collection 6-16% IncinerationScenario 15 High Separate kerbside collection 6-16% Incineration with slag
recoveryScenario 16 High Bring scheme 3-8% LandfillScenario 17 High Bring scheme 3-8% IncinerationScenario 18 High Bring scheme 3-8% Incineration with slag
recovery
3.2 Results of the cost benefit analysis for aluminium
Table 10 : Aluminium – low population density: Internal costs, external costs and total social costs
Collection method N/A N/A N/ARecycling rate 0,0 0,0 0,0
Residual waste management option Landfill Incineration
Incineration with slag recovery
ExeternalitiesGWP (kg CO2 eq.) 0,4 1,0 -79,0 -8,3 to -20,8 -7,8 to -20,4 -82,2 to -86,8 -3,3 to -12,1 -2,8 to -11,6 -80,4 to -83,6
Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Acidification (Acid equiv.) 0,0 0,1 -10,8 -1,2 to -2,9 -1,1 to -2,8 -11,3 to -11,9 -0,5 to -1,7 -0,4 to -1,6 -11,0 to -11,5
Toxicity Carcinogens (Cd equiv) 0,0 0,0 -16,0 -1,8 to -4,3 -1,8 to -4,3 -16,6 to -17,6 -0,8 to -2,5 -0,8 to -2,5 -16,3 to -16,9Toxicity Gaseous (SO2 equiv.) 0,1 0,3 -65,9 -7,2 to -17,7 -7,0 to -17,5 -68,6 to -72,5 -3,0 to -10,2 -2,8 to -10,0 -67,0 to -69,7
Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,1 -279,9 -31,0 to -75,5 -31,0 to -75,5 -291,4 to -307,9 -13,2 to -44,3 -13,3 to -44,4 -284,8 to -296,3Toxicity Particulates & aerosols (PM10 equiv) 9,7 10,5 -454,4 -39,6 to -109,9 -38,7 to -109,1 -471,2 to -495,1 -11,9 to -62,3 -11,1 to -61,5 -462,1 to -480,0
Toxicity Smog (ethylene equiv.) 0,3 0,3 -14,9 -1,4 to -3,7 -1,3 to -3,7 -15,4 to -16,3 -0,4 to -2,1 -0,4 to -2,0 -15,1 to -15,7Black smoke (kg dust eq.) 0,2 0,4 -35,6 -3,8 to -9,4 -3,6 to -9,3 -37,1 to -39,2 -1,5 to -5,5 -1,3 to -5,3 -36,2 to -37,7
Fertilisation -0,1 -0,2 8,7 0,8 to 2,2 0,8 to 2,2 9,1 to 9,6 0,3 to 1,2 0,3 to 1,2 8,9 to 9,2Traffic accidents (risk equiv.) 0,1 0,1 0,5 0,2 to 0,4 0,2 to 0,4 0,6 to 0,7 0,3 to 0,8 0,3 to 0,8 0,7 to 1,1
Traffic Congestion (car km equiv.) 0,1 0,1 9,0 1,2 to 2,6 1,2 to 2,7 9,4 to 10,0 0,6 to 1,6 0,6 to 1,6 9,1 to 9,6Traffic Noise (car km equiv.) 0,4 0,4 1,0 0,7 to 1,1 0,7 to 1,1 1,2 to 1,6 0,5 to 0,7 0,5 to 0,7 1,1 to 1,2
Water Quality Eutrophication (P equiv.) 0,0 0,0 -0,8 -0,1 to -0,2 -0,1 to -0,2 -0,8 to -0,9 0,0 to -0,1 0,0 to -0,1 -0,8 to -0,8Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 34,4 to 30,7 9,4 to 8,4 9,4 to 8,4 35,9 to 33,3 9,8 to 9,1 9,8 to 9,1
TOTAL EXTERNALITIES 48,3 23,4 -928,0 -57,0 to -207,4 -80,2 to -228,1 -965,0 to -1017,8 2,9 to -103,1 -21,3 to -125,6 -944,2 to -981,9INTERNAL COSTS 555,0 453,0 222,0 552,8 to 549,7 458,0 to 465,1 243,1 to 273,3 552,7 to 547,3 453,8 to 455,5 229,7 to 247,6TOTAL SOCIAL COSTS 603,3 476,4 -706,0 495,9 to 342,3 377,8 to 237,0 -721,8 to -744,4 555,6 to 444,2 432,4 to 329,9 -714,5 to -734,2
Separate Kerbside
7-17%
Landfill
Bring scheme3-10%
Landfill
Separate kerbside
7-17%
Separate kerbside
7-17%Incineration with nodule
recovery
Bring scheme3-10%
Incineration
Incineration with nodule
recovery
Bring scheme3-10%
Incineration
Table 11 : Aluminium – high population density: Internal costs, external costs and total social costs
Collection method N/A N/A N/ARecycling rate 0,0 0,0 0,0
Residual waste management option Landfill Incineration
Incineration with slag recovery
ExeternalitiesGWP (kg CO2 eq.) 0,3 0,9 -79,4 -7,3 to -19,9 -6,7 to -19,4 -82,1 to -86,8 -3,5 to -9,8 -2,9 to -9,3 -80,8 to -83,1
Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Acidification (Acid equiv.) 0,0 0,1 -10,8 -1,0 to -2,7 -0,9 to -2,7 -11,2 to -11,9 -0,5 to -1,3 -0,4 to -1,3 -11,0 to -11,4
Toxicity Carcinogens (Cd equiv) 0,0 0,0 -16,0 -1,5 to -4,1 -1,5 to -4,1 -16,5 to -17,5 -0,8 to -2,0 -0,8 to -2,0 -16,3 to -16,7Toxicity Gaseous (SO2 equiv.) 0,1 0,3 -66,0 -6,2 to -16,7 -6,0 to -16,5 -68,3 to -72,2 -3,0 to -8,2 -2,8 to -8,1 -67,1 to -69,1
Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,1 -279,9 -26,6 to -71,0 -26,6 to -71,1 -289,8 to -306,2 -13,3 to -35,5 -13,3 to -35,5 -284,9 to -293,1Toxicity Particulates & aerosols (PM10 equiv) 8,4 9,2 -465,8 -34,4 to -105,8 -33,6 to -105,1 -480,2 to -504,2 -13,5 to -50,1 -12,7 to -49,3 -473,5 to -486,3
Toxicity Smog (ethylene equiv.) 0,2 0,2 -15,1 -1,2 to -3,6 -1,2 to -3,6 -15,6 to -16,4 -0,5 to -1,7 -0,5 to -1,7 -15,3 to -15,7Black smoke (kg dust eq.) 0,2 0,4 -35,7 -3,2 to -8,9 -3,1 to -8,8 -36,9 to -39,1 -1,5 to -4,4 -1,3 to -4,2 -36,3 to -37,4
Fertilisation -0,1 -0,1 8,8 0,7 to 2,1 0,7 to 2,1 9,1 to 9,6 0,3 to 1,0 0,3 to 1,0 9,0 to 9,2Traffic accidents (risk equiv.) 0,2 0,2 0,5 0,3 to 0,5 0,3 to 0,5 0,6 to 0,8 0,3 to 0,4 0,3 to 0,4 0,6 to 0,8
Traffic Congestion (car km equiv.) 8,2 8,2 17,0 12,6 to 20,0 12,6 to 20,0 20,9 to 27,4 10,8 to 15,1 10,8 to 15,1 19,4 to 23,2Traffic Noise (car km equiv.) 0,2 0,2 0,8 0,3 to 0,5 0,3 to 0,5 0,9 to 1,0 0,2 to 0,3 0,2 to 0,3 0,8 to 0,9
Water Quality Eutrophication (P equiv.) 0,0 0,0 -0,8 -0,1 to -0,2 -0,1 to -0,2 -0,8 to -0,9 0,0 to -0,1 0,0 to -0,1 -0,8 to -0,8Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 34,8 to 31,1 9,5 to 8,5 9,5 to 8,5 35,9 to 34,0 9,8 to 9,3 9,8 to 9,3
TOTAL EXTERNALITIES 54,7 29,7 -932,2 -32,8 to -178,7 -56,3 to -199,7 -960,5 to -1007,7 10,9 to -62,2 -13,4 to -85,2 -946,4 to -970,2INTERNAL COSTS 665,0 563,0 332,0 654,4 to 636,6 558,5 to 550,9 341,3 to 356,9 658,5 to 647,5 559,5 to 553,7 335,4 to 341,2TOTAL SOCIAL COSTS 719,7 592,7 -600,2 621,5 to 457,9 502,2 to 351,2 -619,2 to -650,8 669,3 to 585,3 546,1 to 468,5 -611,0 to -629,0
Incineration with slag recovery
Bring scheme3-8%
Incineration
Incineration with slag recovery
Bring scheme3-8%
Incineration
Separate Kerbside collection
6-16%
Landfill
Bring scheme3-8%
Landfill
Separate kerbside
collection6-16%
Separate kerbside
collection6-16%
Graph 17 : Aluminium – low population density: Total social costs
Aluminium (rigid) - Low Population DensityTotal Social Cost
-1000.0
-800.0
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0.0
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Landfill Incineration Incinerationwith
recovery
Separatekerbside
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Separatekerbside
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Separatekerbside
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withrecovery
Bringscheme /
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Bringscheme /
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Graph 18 : Aluminium – high population density: Total social costs
Aluminium (rigid) - High Population DensityTotal Social Cost
-800.0
-600.0
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-200.0
0.0
200.0
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Landfill Incineration Incinerationwith
recovery
Separatekerbside
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Separatekerbside
collection /incineration
Separatekerbside
collection /incineration
withrecovery
Bringscheme /
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Bringscheme /
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Bringscheme /
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3.3 Main findings:
For low population density:Where landfill is the MSW option, for a total social cost perspective it is not possible to distinguishbetween separate kerbside collection achieving a recycling rate of 7-17% and a bring scheme achieving3-10% as the optimum system from the scenarios modelled.
Where incineration with energy recovery but no slag recovery is the MSW option, for a total social costperspective it is not possible to distinguish between separate kerbside collection achieving a recyclingrate of 7-17% and a bring scheme achieving 3-10% as the optimum system from the scenariosmodelled.
Where incineration with energy recovery and slag recovery is the MSW option, for a total social costperspective it is not possible to distinguish between separate kerbside collection achieving a recyclingrate of 7-17% and a bring scheme achieving 3-10% as the optimum system from the scenariosmodelled.
For high population density
Where landfill is the MSW option, for a total social cost perspective it is not possible to distinguishbetween separate kerbside collection achieving a recycling rate of 6-16% and a bring scheme achieving3-8% as the optimum system from the scenarios modelled.
Where incineration with energy recovery but no slag recovery is the MSW option, for a total social costperspective it is not possible to distinguish between separate kerbside collection achieving a recyclingrate of 6-16% and a bring scheme achieving 3-8% as the optimum system from the scenarios modelled.
Where incineration with energy recovery and slag recovery is the MSW option, for a total social costperspective it is not possible to distinguish between separate kerbside collection achieving a recyclingrate of 6-16% and a bring scheme achieving 3-8% as the optimum system from the scenarios modelled.
3.4 Sensitivity analysis
3.4.1 Methodological choices3.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impactresults, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied).
Graph 19 : Aluminium – low population density: Sensitivity of the results to the external economicvaluations applied
Aluminium (rigid) - Low Population DensitySensitivity analysis on variations in economic valuations applied
-14000.0
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Landfill Incineration Incinerationwith
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Separatekerbside
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Separatekerbside
collection /incineration
Separatekerbside
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withrecovery
Bringscheme /
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Bringscheme /
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Graph 20 : Aluminium – high population density: Sensitivity of the results to the external economicvaluations applied
Aluminium (rigid) - High Population DensitySensitivity analysis on variations in economic valuations applied
-14000.0
-12000.0
-10000.0
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Landfill Incineration Incinerationwith
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Separatekerbside
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Separatekerbside
collection /incineration
Separatekerbside
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Bringscheme /
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Bringscheme /
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For low population densityWhere landfill is the MSW option, there is no influence on the results achieved or conclusions drawn.Where incineration with energy recovery but no slag recovery or incineration with energy and slagrecovery is the MSW option, it is no longer possible to distinguish between the systems modelled.
For high population density:Where landfill or incineration with energy recovery and no slag recovery is the MSW option, there isno influence on the results achieved or conclusions drawn.Where incineration with energy and slag recovery is the MSW option, it is no longer possible todistinguish between the systems modelled.
3.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium.Even where equivalent waste management practices are compared internal costs can vary considerablybetween Member States, depending on a range of factors such as cost of living and geographicalconsiderations (mountainous regions, island populations, etc.). In this part of the sensitivity analysis,the effect on the results of considering a +/-20% variation in internal costs is investigated. The resultsare presented in the graph below.
When potential variations in internal costs are taken into account it is no longer possible to distinguishbetween the alternative systems modelled.
Graph 21 : Aluminium – low population density: Sensitivity of the results to the internal economiccosts considered
Aluminium (rigid) - Low Population DensitySensitivity analysis on variations in Internal Costs
-1000.0-800.0-600.0-400.0-200.0
0.0200.0400.0600.0800.0
Landfill Incineration Incinerationwith
recovery
Separatekerbside
collection /landfill
Separatekerbside
collection /incineration
Separatekerbside
collection /incineration
withrecovery
Bringscheme /
landfill
Bringscheme /
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Bringscheme /
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Graph 22 : Aluminium – high population density: Sensitivity of the results to the internal economiccosts considered
Aluminium (rigid) - High Population DensitySensitivity analysis on variations in Internal Costs
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-600.0
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Landfill Incineration Incinerationwith
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Separatekerbside
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Separatekerbside
collection /incineration
Separatekerbside
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withrecovery
Bringscheme /
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Bringscheme /
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3.4.1.3 Inclusion of employment as an impact category
The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis.
The results show that the results achieved and conclusions drawn are not sensitive to the inclusion ofthis parameter as an external impact.
Graph 23 : Aluminium – low population density: Sensitivity of the results to the addition of employmentas an impact category
Aluminium (rigid) - low population densityTotal Social Cost when including employment as an impact category
-1000.0-800.0-600.0-400.0-200.0
0.0200.0400.0600.0800.0
Landfill Incineration Incinerationwith
recovery
Separatekerbside
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Separatekerbside
collection /incineration
Separatekerbside
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withrecovery
Bringscheme /
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Bringscheme /
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Bringscheme /
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Scenario
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Graph 24 : Aluminium – high population density: Sensitivity of the results to the addition ofemployment as an impact category
Aluminium (other rigid than aluminium cans)Total Social Cost when including employment as an impact category
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0
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Landfill Incineration Incinerationwith recovery
Separatekerbside
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Separatekerbside
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with recovery
Bring scheme/ landfill
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3.4.2 Scenario and modelling choices
Findings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.
Table 12 : Summary of sensitivity analysis of scenario and modelling choices for aluminiumParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model
Combined heat and power No influence on the relativestanding of options
No influence on choice ofoptimal scenario
Incineration modelOffset electricity No influence on the relative
standing of optionsNo influence on choice ofoptimal scenario
Transport distancesMSW collection round
Kerbside collection roundCollection from bring bank
Transport from sorting plant toreprocessor
No influence on the relativestanding of options
No influence on choice ofoptimal scenario
Transport distanceConsumer transport to bring
bankNo influence on the relativestanding of options
No influence on choice ofoptimal scenario
4 Paper from household sources
4.1 Scenarios considered
The table below summarises the parameters considered for the baseline scenarios modelled.
Table 13 : Scenarios considered for paperPopulationdensity
Selective collection scheme Recyclingrate achieved
MSW wastemanagement option
Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low Separate kerbside collection 61-71% LandfillScenario 4 Low Separate kerbside collection 61-71% IncinerationScenario 5 Low Bring scheme 25-35% LandfillScenario 6 Low Bring scheme 25-35% IncinerationScenario 7 High None 0% LandfillScenario 8 High None 0% IncinerationScenario 9 High Separate kerbside collection 55-65% LandfillScenario 10 High Separate kerbside collection 55-65% IncinerationScenario 11 High Bring scheme 19-29% LandfillScenario 12 High Bring scheme 19-29% Incineration
4.2 Results of the cost benefit analysis for paper
Table 14 : Paper – low population density: Internal costs, external costs and total social costs
Collection method N/A N/ARecycling rate 0,0 0,0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 32,5 17,0 26,5 to 25,5 20,5 to 21,0 29,9 to 28,9 18,3 to 18,8Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0
Acidification (Acid equiv.) -0,1 -0,4 -0,3 to -0,4 -0,4 to -0,4 -0,2 to -0,2 -0,4 to -0,4Toxicity Carcinogens (Cd equiv) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) -0,6 -1,5 -0,9 to -1,0 -1,3 to -1,3 -0,5 to -0,5 -1,2 to -1,0
Toxicity Metals non carcinogens (Pb equiv.) 0,0 -0,2 -0,1 to -0,1 -0,2 to -0,2 0,0 to 0,0 -0,1 to -0,1Toxicity Particulates & aerosols (PM10 equiv) 6,3 -11,9 2,4 to 1,8 -4,7 to -3,5 -2,3 to -5,7 -15,9 to -17,5
Toxicity Smog (ethylene equiv.) 1,8 0,0 0,6 to 0,4 -0,1 to -0,1 1,3 to 1,1 -0,1 to -0,1Black smoke (kg dust eq.) -0,3 -1,4 -1,4 to -1,6 -1,8 to -1,9 -0,7 to -0,9 -1,6 to -1,6
Fertilisation -0,2 -0,1 0,0 to 0,0 0,1 to 0,1 -0,1 to 0,0 0,0 to 0,1Traffic accidents (risk equiv.) 0,1 0,1 0,7 to 0,8 0,7 to 0,8 1,6 to 2,2 1,6 to 2,2
Traffic Congestion (car km equiv.) 0,1 0,1 7,2 to 8,4 7,2 to 8,4 3,0 to 4,2 3,0 to 4,2Traffic Noise (car km equiv.) 0,4 0,4 2,0 to 2,2 2,0 to 2,2 0,6 to 0,7 0,6 to 0,7
Water Quality Eutrophication (P equiv.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Disaminity (kg LF waste equiv.) 37,0 11,2 14,6 to 11,0 4,6 to 3,5 27,8 to 24,2 8,5 to 7,4
TOTAL EXTERNALITIES 77,1 13,5 51,3 to 47,1 26,5 to 28,7 60,4 to 53,8 12,7 to 12,4INTERNAL COSTS 131,1 184,1 103,5 to 99,0 124,2 to 114,4 117,7 to 112,3 157,4 to 146,7TOTAL SOCIAL COSTS 208,2 197,6 154,9 to 146,1 150,7 to 143,0 178,1 to 166,0 170,1 to 159,1
Bring scheme25-35%Landfill
Separate kerbside
collection61-71%
Incineration
Bring scheme25-35%
Incineration
Separate Kerbside collection
61-71%Landfill
Table 15 : Paper – high population density: Internal costs, external costs and total social costs
Collection method N/A N/ARecycling rate 0,0 0,0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 32,4 16,9 26,4 to 25,3 19,4 to 19,9 30,8 to 30,0 18,3 to 19,0Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0
Acidification (Acid equiv.) -0,1 -0,4 -0,4 to -0,4 -0,5 to -0,5 -0,2 to -0,3 -0,5 to -0,5Toxicity Carcinogens (Cd equiv) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) -0,6 -1,5 -1,1 to -1,1 -1,5 to -1,4 -0,7 to -0,7 -1,4 to -1,4
Toxicity Metals non carcinogens (Pb equiv.) 0,0 -0,2 -0,1 to -0,2 -0,2 to -0,2 -0,1 to -0,1 -0,2 to -0,2Toxicity Particulates & aerosols (PM10 equiv) 5,0 -13,2 -7,8 to -10,2 -16,0 to -16,5 -2,7 to -6,8 -17,5 to -19,7
Toxicity Smog (ethylene equiv.) 1,8 0,0 0,4 to 0,1 -0,4 to -0,5 1,3 to 1,0 -0,2 to -0,3Black smoke (kg dust eq.) -0,3 -1,4 -1,4 to -1,6 -1,9 to -2,0 -0,7 to -1,0 -1,6 to -1,8
Fertilisation -0,2 0,0 0,1 to 0,2 0,2 to 0,3 -0,1 to 0,0 0,1 to 0,1Traffic accidents (risk equiv.) 0,2 0,2 0,6 to 0,7 0,6 to 0,7 0,7 to 0,9 0,7 to 0,9
Traffic Congestion (car km equiv.) 8,2 8,2 32,6 to 37,1 32,6 to 37,1 22,1 to 29,4 22,1 to 29,4Traffic Noise (car km equiv.) 0,2 0,2 0,6 to 0,7 0,6 to 0,7 0,3 to 0,3 0,3 to 0,3
Water Quality Eutrophication (P equiv.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Disaminity (kg LF waste equiv.) 37,0 11,2 16,8 to 13,2 5,2 to 4,1 30,0 to 26,4 9,2 to 8,1
TOTAL EXTERNALITIES 83,5 19,8 66,8 to 63,7 38,1 to 41,5 80,7 to 79,3 29,2 to 34,1INTERNAL COSTS 148,8 201,8 109,6 to 102,5 133,4 to 121,0 133,9 to 126,0 176,8 to 163,7TOTAL SOCIAL COSTS 232,3 221,6 176,4 to 166,2 171,6 to 162,5 214,6 to 205,3 206,0 to 197,8
Bring scheme19-29%Landfill
Separate kerbside
collection55-65%
Incineration
Bring scheme19-29%
Incineration
Separate Kerbside collection
55-65%Landfill
Graph 25 : Paper – low population density: Total social cost
Paper - Low Population DensityTotal Social Cost
0.0
50.0
100.0
150.0
200.0
250.0
Landfill Incineration Separatekerbside
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Separatekerbside
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Bring scheme /landfill
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Graph 26 : Paper – high population density: Total social costs
Paper - High Population DensityTotal Social Cost
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250.0
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
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Bring scheme /Landfill
Bring scheme /Incineration
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4.3 Main findings:
For low population density, a kerbside collection scheme achieving a recycling rate of 61-71% is theoptimum system for the scenarios considered. This is not dependent on the available alternative wastemanagement option.
For high population density, a kerbside collection scheme achieving a recycling rate of 55-65% is theoptimum system for the scenarios considered. This is not dependent on the available alternative wastemanagement option.
4.4 Sensitivity analysis
4.4.1 Methodological choices4.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impact
results, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied).
The graphs show that results are extremely sensitive to the external economic valuations applied. If thefull range of available external economic valuations is applied then it is not possible to make a cleardistinction as to which is the optimal waste management system for the scenarios considered.
Graph 27 : Paper – low population density: Sensitivity of the results to the external economicvaluations applied
Paper - Low Population DensitySensitivity analysis on variations in economic valuations applied
0.0
100.0
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500.0
600.0
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Landfill Incineration Separatekerbside
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Separatekerbside
collection /incineration
Bring scheme /landfill
Bring scheme /incineration
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Graph 28 : Paper – high population density: Sensitivity of the results to the external valuationsapplied
Paper - High Population DensitySensitivity analysis on variations in economic valuations applied
0.0100.0200.0300.0400.0500.0600.0700.0800.0900.0
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
collection /Incineration
Bring scheme /Landfill
Bring scheme /Incineration
Scenario
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4.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium.Even where equivalent waste management practices are compared internal costs can vary considerablybetween Member States, depending on a range of factors such as cost of living and geographicalconsiderations (mountainous regions, island populations, etc.). In this part of the sensitivity analysis,the effect on the results of considering a +/-20% variation in internal costs is investigated. The resultsare presented in the graph below.
The following points should be noted:♦ For low population density where landfill is the MSW option, it is no longer possible to distinguish
between separate kerbside collection achieving a recycling rate of 61-71% and a bring schemeachieving a recycling rate of 25-35%.
♦ For low population density where incineration is the MSW option it is no longer possible todistinguish between 100% incineration, separate kerbside collection achieving a recycling rate of61-71% and a bring scheme achieving a recycling rate of 25-35%.
♦ For high population density where landfill is the MSW option, it is no longer possible todistinguish between separate kerbside collection achieving a recycling rate of 61-71% and a bringscheme achieving a recycling rate of 25-35%.
♦ For high population density where incineration is the MSW option it is no longer possible todistinguish between 100% incineration, separate kerbside collection achieving a recycling rate of61-71% and a bring scheme achieving a recycling rate of 25-35%.
Graph 29 : Paper – low population density: Sensitivity of the results to the internal economic costsconsidered
Paper - Low Population DensitySensitivity analysis on variations in Internal Costs
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Bring scheme /landfill
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Graph 30 : Paper – high population density: Sensitivity of results to the internal economic costsconsidered
Paper - High Population DensitySensitivity analysis on variations in Internal Costs
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Bring scheme /Landfill
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Scenario
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4.4.1.3 Inclusion of employment as an impact category
The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis. The main conclusions drawn are not sensitive to the inclusion ofthis additional parameter.
Graph 31 : Paper – low population density: Sensitivity of the results to the addition of employment asan impact category
Paper from household sourcesTotal Social Cost when including employment as an impact category
0
50
100
150
200
250
Landfill Incineration Separatekerbside
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Separatekerbside
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Bring scheme /landfill
Bring scheme /incineration
Scenario
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Graph 32 : Paper – high population density: Sensitivity of the results to the addition of employment asan impact category
Paper from household sourcesTotal Social Cost when including employment as an impact category
0
50
100
150
200
250
Landfill Incineration Separatekerbside
collection /landfill
Separatekerbside
collection /Incineration
Bring scheme /Landfill
Bring scheme /Incineration
Scenario
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4.4.2 Scenario and modelling choices
Findings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.
Table 16 : Summary of sensitivity analysis of scenario and modelling choices for paperParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model
Combined heat and powerTotal social cost of incinerationoptions is reducedNo influence on the relativestanding of alternative systems
No influence on the choice ofoptimum system
Incineration modelOffset electricity
Total social cost of incinerationoptions is reducedNo influence on the relativestanding of alternative systems
No influence on the choice ofoptimum system
Transport distancesMSW collection round
Kerbside collection roundCollection from bring bank
Transport from sorting plant toreprocessor
Similar total social costsobserved for separate kerbsidecollection and bring schemescenarios.No distinction between kerbsidecollection and bring schemescenarios is possible
Could influence choice ofoptimum scenario – broaderoptimum recycling range wouldbe achieved
Transport distanceConsumer transport to bring
bank
Total social costs of recyclingoptions increased, but noinfluence on the relativestanding of alternative systems
No influence on the choice ofoptimum system
5 Liquid beverage cartons from household sources
5.1 Scenarios considered
The table below summarises the parameters considered for the baseline scenarios modelled.
Table 17 : Scenarios considered for aseptic composite beverage cartonsPopulationdensity
Selective collection scheme Recyclingrate achieved
MSW wastemanagementoption
Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low Separate kerbside collection (fibres
recycled, foil/plastic residual to landfill)55-65% Landfill
Scenario 4 Low Separate kerbside collection (fibresrecycled, foil/plastic residual toincineration)
55-65% Landfill
Scenario 5 Low Separate kerbside collection (fibresrecycled, foil/plastic residual toincineration)
55-65% Incineration
Scenario 6 Low Bring scheme (fibre recycled, foil/plasticresidual to landfill)
24-34% Landfill
Scenario 7 Low Bring scheme (fibre recycled, foil/plasticresidual to incineration)
24-34% Landfill
Scenario 8 Low Bring scheme (fibre recycled, foil/plasticresidual to incineration)
24-34% Incineration
Scenario 9 High None 0% LandfillScenario 10 High None 0% IncinerationScenario 11 High Separate kerbside collection (fibres
recycled, foil/plastic residual to landfill)55-65% Landfill
Scenario 12 High Separate kerbside collection (fibresrecycled, foil/plastic residual toincineration)
55-65% Landfill
Scenario 13 High Separate kerbside collection (fibresrecycled, foil/plastic residual toincineration)
55-65% Incineration
Scenario 14 High Bring scheme (fibre recycled, foil/plasticresidual to landfill)
24-34% Landfill
Scenario 15 High Bring scheme (fibre recycled, foil/plasticresidual to incineration)
24-34% Landfill
Scenario 16 High Bring scheme (fibre recycled, foil/plasticresidual to incineration)
24-34% Incineration
5.2 Results of the cost benefit analysis for liquid beverage cartons
Table 18 : LBC – low population density: Internal costs, external costs and total social costs
Collection method N/A N/ARecycling rate 0.0 0.0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 24.2 21.0 21.0 to 20.4 25.5 to 25.8 24.1 to 24.7 22.8 to 22.2 24.8 to 25.0 22.4 to 22.9Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0
Acidification (Acid equiv.) -0.1 -0.6 -0.2 to -0.2 -0.3 to -0.3 -0.5 to -0.5 -0.1 to -0.1 -0.2 to -0.2 -0.5 to -0.5Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0Toxicity Gaseous (SO2 equiv.) -0.4 -2.0 -0.4 to -0.5 -0.9 to -1.0 -1.6 to -1.6 -0.2 to -0.1 -0.4 to -0.4 -1.6 to -1.4
Toxicity Metals non carcinogens (Pb equiv.) 0.0 -0.2 0.0 to -0.1 -0.1 to -0.1 -0.2 to -0.2 0.0 to 0.0 0.0 to 0.0 -0.2 to -0.2Toxicity Particulates & aerosols (PM10 equiv) 7.1 -17.1 23.6 to 26.6 17.5 to 19.4 6.6 to 10.9 10.3 to 11.7 7.7 to 7.9 -10.7 to -8.0
Toxicity Smog (ethylene equiv.) 1.4 0.0 1.0 to 0.9 1.0 to 0.9 0.3 to 0.4 1.3 to 1.2 1.2 to 1.2 0.2 to 0.2Black smoke (kg dust eq.) -0.1 -1.8 -0.7 to -0.8 -1.2 to -1.4 -1.9 to -1.9 -0.4 to -0.4 -0.6 to -0.7 -1.8 to -1.8
Fertilisation -0.2 -0.1 -0.2 to -0.2 -0.2 to -0.2 -0.2 to -0.2 -0.2 to -0.2 -0.2 to -0.2 -0.1 to -0.1Traffic accidents (risk equiv.) 0.1 0.1 0.9 to 1.0 0.9 to 1.0 0.9 to 1.0 1.7 to 2.4 1.7 to 2.4 1.7 to 2.4
Traffic Congestion (car km equiv.) 0.1 0.1 10.0 to 11.8 10.0 to 11.8 10.0 to 11.8 4.5 to 6.3 4.5 to 6.3 4.5 to 6.3Traffic Noise (car km equiv.) 0.4 0.4 2.4 to 2.8 2.4 to 2.8 2.4 to 2.8 1.0 to 1.3 1.0 to 1.3 1.0 to 1.3
Water Quality Eutrophication (P equiv.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0Disaminity (kg LF waste equiv.) 37.0 11.7 22.0 to 19.3 18.6 to 15.3 7.2 to 6.4 30.5 to 27.8 29.0 to 25.6 9.7 to 8.9
Employment -3.7 -4.0 -19.4 -22.2 -19.4 -22.2 -19.5 -22.3 -4.9 -5.5 -4.9 -5.5 -5.2 -5.7TOTALEXTERNALITIES
69.6 11.6 79.3 to 81.1 73.2 to 73.8 47.1 to 53.5 71.3 to 72.0 68.6 to 68.2 24.6 to 30.0INTERNAL COSTS 168.0 237.0 349.1 to 382.0 359.5 to 394.3 390.5 to 418.4 238.1 to 267.3 242.6 to 273.7 295.0 to 319.2TOTAL SOCIALCOSTS
237.6 248.6 428.4 to 463.1 432.6 to 468.1 437.6 to 472.0 309.4 to 339.3 311.2 to 341.9 319.6 to 349.2
Separatekerbside
collection(fibres recycled,
foil/plasticresidual to
incineration)55-65%Landfill
Bring scheme(fibre recycled,
foil/plasticresidual to
incineration)24-34%Landfill
Bring scheme(fibre recycled,
foil/plasticresidual to
landfill)24-34%Landfill
Separatekerbside
collection(fibres
recycled,foil/plasticresidual to
incineration)
SeparateKerbsidecollection
(fibresrecycled,
foil/plasticresidual to
landfill)55-65%Landfill
55-65%Incineration
Bring scheme(fibre recycled,
foil/plasticresidual to
incineration)24-34%
Incineration
Graph 33 : LBC – low population density: Total social cost
Liquid Beverage Cartons - Low Population DensityTotal Social Cost
0.050.0
100.0150.0
200.0250.0300.0350.0400.0450.0500.0
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Bringscheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ incineration
Scenario
To
tal S
oci
al C
ost
(E
uro
per
to
nn
e)
Liquid Beverage Cartons - Low Population DensityTotal Social Cost
0.050.0
100.0150.0200.0250.0300.0350.0400.0450.0500.0
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Bringscheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ incineration
Scenario
To
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(E
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nn
e)
Table 19 : LBC – high population density: Internal costs, external costs and total social costs
Collection method N/A N/ARecycling rate 0.0 0.0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 24.1 20.9 20.3 to 19.6 24.9 to 25.0 23.4 to 23.9 22.4 to 21.7 24.4 to 24.5 22.0 to 22.4Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0
Acidification (Acid equiv.) -0.1 -0.6 -0.2 to -0.2 -0.3 to -0.4 -0.6 to -0.6 -0.1 to -0.2 -0.2 to -0.2 -0.6 to -0.5Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0
Toxicity Gaseous (SO2 equiv.) -0.4 -2.0 -0.6 to -0.6 -1.1 to -1.2 -1.8 to -1.7 -0.4 to -0.3 -0.6 to -0.7 -1.8 to -1.7Toxicity Metals non carcinogens (Pb equiv.) 0.0 -0.2 -0.1 to -0.1 -0.1 to -0.2 -0.2 to -0.2 0.0 to 0.0 0.0 to -0.1 -0.2 to -0.2
Toxicity Particulates & aerosols (PM10 equiv) 5.8 -18.7 16.4 to 18.4 10.4 to 11.2 -0.6 to 2.7 6.4 to 6.7 3.8 to 2.9 -14.8 to -13.2Toxicity Smog (ethylene equiv.) 1.4 0.0 0.7 to 0.5 0.6 to 0.5 0.0 to 0.0 1.1 to 0.9 1.0 to 0.9 0.0 to 0.0
Black smoke (kg dust eq.) -0.2 -1.8 -0.9 to -1.0 -1.3 to -1.5 -2.1 to -2.1 -0.5 to -0.6 -0.7 to -0.9 -1.9 to -2.0Fertilisation -0.2 -0.1 -0.1 to 0.0 -0.1 to 0.0 0.0 to 0.0 -0.1 to -0.1 -0.1 to -0.1 0.0 to 0.0
Traffic accidents (risk equiv.) 0.2 0.2 1.1 to 1.3 1.1 to 1.3 1.1 to 1.3 0.9 to 1.2 0.9 to 1.2 0.9 to 1.2Traffic Congestion (car km equiv.) 8.2 7.6 50.4 to 58.1 50.4 to 58.1 50.1 to 57.9 29.7 to 38.6 29.7 to 38.6 29.2 to 38.2
Traffic Noise (car km equiv.) 0.2 0.2 1.2 to 1.4 1.2 to 1.4 1.2 to 1.4 0.5 to 0.7 0.5 to 0.7 0.5 to 0.6Water Quality Eutrophication (P equiv.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0
Disaminity (kg LF waste equiv.) 37.0 11.7 22.0 to 19.3 18.6 to 15.3 7.2 to 6.4 30.5 to 27.8 29.0 to 25.6 9.7 to 8.9TOTAL EXTERNALITIES 75.9 17.1 110.5 to 116.7 104.3 to 109.5 77.8 to 88.9 90.4 to 96.4 87.7 to 92.6 43.0 to 53.7INTERNAL COSTS 196.0 265.0 345.4 to 372.5 355.7 to 384.8 386.8 to 408.9 253.1 to 276.9 257.6 to 283.3 310.1 to 337.9TOTAL SOCIAL COSTS 271.9 282.1 455.8 to 489.3 460.0 to 494.2 464.6 to 497.8 343.5 to 373.3 345.3 to 375.9 353.0 to 391.6
Separate kerbside
collection (fibres recycled,
foil/plastic residual to
incineration)55-65%Landfill
Bring scheme (fibre recycled,
foil/plastic residual to
incineration)24-34%Landfill
Bring scheme (fibre recycled,
foil/plastic residual to
landfill)24-34%Landfill
Separate kerbside
collection (fibres recycled,
foil/plastic residual to
incineration)
Separate Kerbside
collection (fibres recycled,
foil/plastic residual to
landfill)55-65%Landfill
55-65%Incineration
Bring scheme (fibre recycled,
foil/plastic residual to
incineration)24-34%
Incineration
Graph 34 : LBC – high population density: Total social cost
Liquid Beverage Cartons - High Population DensityTotal Social Cost
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration) /incineration
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration) /incineration
Bring scheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bring scheme(fibres
recycled,foil/plasticresidual to
incineration) /landfill
Bring scheme(fibres
recycled,foil/plasticresidual to
incineration) /incineration
Scenario
To
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oci
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ost
(E
uro
per
to
nn
e)
Liquid Beverage Cartons - High Population DensityTotal Social Cost
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration) /incineration
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration) /incineration
Bring scheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bring scheme(fibres
recycled,foil/plasticresidual to
incineration) /landfill
Bring scheme(fibres
recycled,foil/plasticresidual to
incineration) /incineration
Scenario
To
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ost
(E
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nn
e)
5.3 Main findings:
From an internal cost perspective, where landfill is the MSW option 100% landfilling is the preferredwaste management system from the scenarios considered for both high and low population density.Where incineration is the MSW option, 100% incineration is the preferred waste management systemfrom the scenarios considered for both high and low population density.
5.4 Sensitivity analysis
5.4.1 Methodological choices
5.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impactresults, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied).
The graphs show that the results achieved and conclusions drawn are sensitive to the economic valuesapplied to environmental impact categories. Applying the full range of available economic valuationsmakes it impossible to distinguish an optimal system from the scenarios considered.
Graph 35 : LBC – low population density: Sensitivity of the results to the external economicvaluations applied
Liquid Beverage Cartons - Low Population DensitySensitivity analysis on variations in economic valuations applied
0.0
100.0
200.0
300.0
400.0
500.0
600.0
700.0
800.0
900.0
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Bringscheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ incineration
Scenario
To
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oci
al C
ost
(E
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per
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nn
e)
Graph 36 : LBC – high population density: Sensitivity of the results to the external economicvaluations applied
Liquid Beverage Cartons - High Population DensitySensitivity analysis on variations in economic valuations applied
0.0100.0200.0300.0400.0500.0600.0700.0800.0900.0
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Bringscheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ incineration
Scenario
To
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ost
(E
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nn
e)
5.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium.Even where equivalent waste management practices are compared internal costs can vary considerablybetween Member States, depending on a range of factors such as cost of living and geographicalconsiderations (mountainous regions, island populations, etc.). In this part of the sensitivity analysis,the effect on the results of considering a +/-20% variation in internal costs is investigated. The resultsare presented in the graph below.
The graphs show that the results achieved and conclusions drawn are sensitive to potential variations ininternal costs. If a +/-20% variation in internal costs is considered, where landfill is the MSW option itis no longer possible to distinguish between 100% landfill and a bring scheme achieving a recyclingrate of 24-34% for either high or low population density. Where incineration is the MSW option it isno longer possible to distinguish between 100% incineration and a bring scheme achieving a recyclingrate of 24-34% for either high or low population density.
This sensitivity would affect the choice of optimum system from the scenarios considered, andtherefore affect the choice of optimum recycling rate selected from the cost benefit analysis.
Graph 37 : LBC – low population density: Sensitivity of the results to the internal economic costsconsidered
Liquid Beverage Cartons - Low Population DensitySensitivity analysis on variations in Internal Costs
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Bringscheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ incineration
Scenario
To
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oci
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ost
(E
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per
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nn
e)
Graph 38 : LBC – high population density: Sensitivity of the results to the internal economic costsconsidered
Liquid Beverage Cartons - High Population DensitySensitivity analysis on variations in Internal Costs
0.0
100.0
200.0
300.0
400.0
500.0
600.0
700.0
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Bringscheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ incineration
Scenario
To
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(E
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per
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e)
5.4.1.3 Inclusion of employment as an impact categoryThe graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis.
The graphs show that the results achieved and conclusions drawn are not sensitive to inclusion of thisimpact category.
Graph 39 : LBC – low population density: Sensitivity of the results to the addition of employment as animpact category
Liquid beverage cartons - low population densityTotal Social Cost when including employment as an impact category
050
100150200250300350400450500
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Bringscheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ incineration
Scenario
To
tal S
oci
al C
ost
(E
uro
per
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nn
e)
Graph 40 : LBC – low population density: Sensitivity of the results to the addition of employment as animpact category
Liquid beverage cartons - high population densityTotal Social Cost when including employment as an impact category
0
100
200
300
400
500
600
Landfill Incineration Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual tolandfill) /landfill
Separatekerbside
collection(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Separatekerbsidecollection
(fibresrecycled,foil/plasticresidual to
incineration)/ incineration
Bringscheme(fibres
recycled,foil/plasticresidual tolandfill) /landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ landfill
Bringscheme(fibres
recycled,foil/plasticresidual to
incineration)/ incineration
Scenario
To
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(E
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e)
5.4.2 Scenario and modelling choicesFindings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.
Table 20 : Summary of sensitivity analysis of scenario and modelling choices for liquid beveragecartonsParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model
Combined heat and powerNo influence on the relativestanding of scenarios modelled
No influence on choice ofoptimum waste managementsystem from the scenariosconsideredNo influence on choice ofoptimum recycling rate
Incineration modelOffset electricity
No influence on the relativestanding of scenarios modelled
No influence on choice ofoptimum waste managementsystem from the scenariosconsideredNo influence on choice ofoptimum recycling rate
Transport distancesMSW collection round
Kerbside collection roundCollection from bring bank
Transport from sorting plant toreprocessor
No influence on the relativestanding of scenarios modelled
No influence on choice ofoptimum waste managementsystem from the scenariosconsideredNo influence on choice ofoptimum recycling rate
Transport distanceConsumer transport to bring
bank
No influence on the relativestanding of scenarios modelled
No influence on choice ofoptimum waste managementsystem from the scenariosconsideredNo influence on choice ofoptimum recycling rate
6 Glass from household sources
6.1 Scenarios considered
The table below summarises the parameters considered for the baseline scenarios modelled.
Table 21 : Scenarios considered for glassPopulationdensity
Selective collection scheme Recycling rateachieved
MSW wastemanagement option
Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low Bring scheme 73-83% LandfillScenario 4 Low Bring scheme 73-83% IncinerationScenario 5 High None 0% LandfillScenario 6 High None 0% IncinerationScenario 7 High Bring scheme 42-91% LandfillScenario 8 High Bring scheme 42-91% Incineration
6.2 Results of the cost benefit analysis for glass
Table 22 : Glass – low population density: Internal costs, external costs and total social costs
Collection method N/A N/ARecycling rate 0.0 0.0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 0.4 0.9 -19.5 to -22.2 -19.3 to -22.1Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0
Acidification (Acid equiv.) 0.0 0.1 -2.9 to -3.3 -2.9 to -3.3Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0
Toxicity Gaseous (SO2 equiv.) 0.1 0.3 -16.3 to -18.5 -16.2 to -18.5Toxicity Metals non carcinogens (Pb equiv.) 0.1 0.1 -0.3 to -0.3 -0.3 to -0.3
Toxicity Particulates & aerosols (PM10 equiv) 9.1 10.1 -60.5 to -70.0 -60.2 to -69.8Toxicity Smog (ethylene equiv.) 0.3 0.3 -3.3 to -3.8 -3.3 to -3.8
Black smoke (kg dust eq.) 0.2 0.4 -7.5 to -8.6 -7.5 to -8.6Fertilisation -0.1 -0.1 2.3 to 2.6 2.3 to 2.6
Traffic accidents (risk equiv.) 0.1 0.1 4.6 to 5.2 4.6 to 5.2Traffic Congestion (car km equiv.) 0.1 0.1 6.5 to 7.4 6.5 to 7.4
Traffic Noise (car km equiv.) 0.4 0.4 1.3 to 1.4 1.3 to 1.4Water Quality Eutrophication (P equiv.) 0.0 0.0 -0.2 to -0.2 -0.2 to -0.2
Disaminity (kg LF waste equiv.) 37.0 10.1 10.0 to 6.3 2.7 to 1.7TOTAL EXTERNALITIES 47.7 22.8 -85.7 to -104.0 -92.4 to -108.2INTERNAL COSTS 152.2 153.1 86.7 to 77.7 87.0 to 77.9TOTAL SOCIAL COSTS 199.9 175.9 1.0 to -26.2 -5.5 to -30.3
Bring Bring
Landfill Incineration73-83% 73-83%
Graph 41 : Glass – low population density: Total social costs
Glass - Low Population DensityTotal Social Cost
-50.0
0.0
50.0
100.0
150.0
200.0
250.0
Landfill Incineration Bring scheme / landfill Bring scheme /incineration
Scenario
To
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(E
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per
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nn
e)
Table 23 : Glass – high population density: Internal costs, external costs and total social costs
Collection method N/A N/ARecycling rate 0.0 0.0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 0.3 0.8 -11.4 to -25.0 -11.1 to -24.9Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0
Acidification (Acid equiv.) 0.0 0.1 -1.7 to -3.6 -1.6 to -3.6Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0
Toxicity Gaseous (SO2 equiv.) 0.1 0.3 -9.6 to -20.9 -9.5 to -20.9Toxicity Metals non carcinogens (Pb equiv.) 0.1 0.1 -0.2 to -0.4 -0.2 to -0.4
Toxicity Particulates & aerosols (PM10 equiv) 7.9 8.8 -33.3 to -81.4 -32.8 to -81.3Toxicity Smog (ethylene equiv.) 0.2 0.2 -2.0 to -4.5 -2.0 to -4.5
Black smoke (kg dust eq.) 0.2 0.3 -4.4 to -9.6 -4.3 to -9.6Fertilisation -0.1 -0.1 1.4 to 3.0 1.3 to 3.0
Traffic accidents (risk equiv.) 0.2 0.2 1.2 to 2.4 1.2 to 2.4Traffic Congestion (car km equiv.) 8.2 8.2 33.6 to 63.4 33.7 to 63.4
Traffic Noise (car km equiv.) 0.2 0.2 0.6 to 1.0 0.6 to 1.0Water Quality Eutrophication (P equiv.) 0.0 0.0 -0.1 to -0.3 -0.1 to -0.3
Disaminity (kg LF waste equiv.) 37.0 10.1 21.5 to 3.3 5.9 to 0.9TOTAL EXTERNALITIES 54.1 29.1 -4.4 to -72.6 -18.9 to -74.9INTERNAL COSTS 172.5 173.3 123.8 to 66.9 124.2 to 67.0TOTAL SOCIAL COSTS 226.6 202.4 119.4 to -5.7 105.4 to -7.9
Bring Bring
Landfill Incineration42-91% 42-91%
Graph 42 : Glass – high population density: Total social costs
Glass - High Population DensityTotal Social Cost
-50.0
0.0
50.0
100.0
150.0
200.0
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6.3 Main findings:
For low population density, a bring scheme achieving a recycling rate of 73-83% is the optimumsystem for the scenarios modelled. For high population density, a bring scheme achieving a recyclingrate of 42-91% is the optimum system for the scenarios modelled.
6.4 Sensitivity analysis
6.4.1 Methodological choices6.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impactresults, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied). The graphs below show that the general conclusions are not changed byapplying different economic valuations.
Graph 43 : Glass – low population density: Sensitivity of the results to the external economicvaluations applied
Glass - Low Population DensitySensitivity analysis on variations in economic valuations applied
-800.0-700.0
-600.0-500.0-400.0
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Graph 44 : Glass – high population density: Sensitivity of the results to the external economicvaluations applied
Glass - High Population DensitySensitivity analysis on variations in economic valuations applied
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6.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium.Even where equivalent waste management practices are compared internal costs can vary considerablybetween Member States, depending on a range of factors such as cost of living and geographicalconsiderations (mountainous regions, island populations, etc.). In this part of the sensitivity analysis,the effect on the results of considering a +/-20% variation in internal costs is investigated. The resultsare presented in the graph below, which shows that the general conclusions drawn are not sensitive tothis parameter.
Graph 45 : Glass – low population density: Sensitivity of the results to the internal economic costsconsidered
Glass - Low Population DensitySensitivity analysis on variations in Internal Costs
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Graph 46 : Glass – high population density: Sensitivity of the results to the internal economic costsconsidered
Glass - High Population DensitySensitivity analysis on variations in Internal Costs
-50,0
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6.4.1.3 Inclusion of employment as an impact category
The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis. The general conclusions drawn are not affected by the inclusionof this impact category.
Graph 47 : Glass – low population density: Sensitivity of the results to the addition of employment asan impact category
Glass - Low Population DensityTotal Social Cost
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Graph 48 : Glass – high population density: Sensitivity of the results to the addition of employment asan impact category
Glass - High Population DensityTotal Social Cost
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6.4.2 Scenario and modelling choices
Findings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.
Table 24 : Summary of sensitivity analysis of scenario and modelling choices for glassParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model
Combined heat and powerNo influence No influence
Incineration modelOffset electricity
No influence No influence
Transport distancesMSW collection round
Kerbside collection roundCollection from bring bank
Transport from sorting plant toreprocessor
No influence No influence
Transport distanceConsumer transport to bring
bank
No influence No influence
Alternative LCI data Not considered Not consideredAlternative reprocessingoptions
Not considered Not considered
The results are generally robust to the parameters investigated in the sensitivity analysis. However, itshould be noted that alternative LCI data has not been investigated. Also, no consideration ofalternative reprocessing options has been made. Alternative reprocessing options may be crucial forcountries to achieve higher recycling rates where an imbalance in supply and demand exists.
7 PE Film from commercial and industrial sources
7.1 Scenarios considered
The table below summarises the parameters considered for the baseline scenarios modelled.
Table 25 : Scenarios considered for PE filmSelective collection scheme Recycling rate achieved MSW waste management
optionScenario 1 None 0% LandfillScenario 2 None 0% IncinerationScenario 3 Separate collection 70-90% LandfillScenario 4 Separate collection 70-90% Incineration
7.2 Results of the cost benefit analysis for PE film
Table 26 : PE film: Internal costs, external costs and total social costs
Collection method N/A N/ARecycling rate 0.0 0.0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 0.4 39.8 -15.6 to -20.2 -3.8 to -16.2Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0
Acidification (Acid equiv.) 0.1 -1.3 -3.0 to -3.8 -3.4 to -4.0Toxicity Carcinogens (Cd equiv) 0.0 -0.1 0.0 to 0.0 0.0 to 0.0
Toxicity Gaseous (SO2 equiv.) 0.2 -4.6 -7.8 to -10.0 -9.2 to -10.5Toxicity Metals non carcinogens (Pb equiv.) 0.1 -0.5 4.8 to 6.1 4.6 to 6.1
Toxicity Particulates & aerosols (PM10 equiv) 9.6 -50.0 -111.5 to -146.1 -129.4 to -152.0Toxicity Smog (ethylene equiv.) 0.2 -0.4 -15.3 to -19.8 -15.5 to -19.9
Black smoke (kg dust eq.) 0.2 -4.3 -8.5 to -11.0 -9.9 to -11.4Fertilisation -0.1 0.0 5.0 to 6.5 5.1 to 6.5
Traffic accidents (risk equiv.) 0.2 0.2 0.2 to 0.3 0.2 to 0.3Traffic Congestion (car km equiv.) 8.2 8.2 12.0 to 13.0 12.0 to 13.0
Traffic Noise (car km equiv.) 0.2 0.2 0.3 to 0.3 0.3 to 0.3Water Quality Eutrophication (P equiv.) 0.0 -0.1 -0.4 to -0.5 -0.4 to -0.5
Disaminity (kg LF waste equiv.) 37.0 13.3 11.1 to 3.7 4.0 to 1.3TOTAL EXTERNALITIES 56.1 0.4 -128.7 to -181.5 -145.4 to -187.1INTERNAL COSTS 255.2 217.2 42.0 to -18.9 30.6 to -22.7TOTAL SOCIAL COSTS 311.3 217.6 -86.7 to -200.4 -114.8 to -209.8
Recycling Recycling
Landfill Incineration70-90% 70-90%
Graph 49 : PE film: Total social costs
PE Film from commercial and industrial sourcesTotal Social Cost
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7.3 Main findings:
Where landfill is the MSW option, recycling of source separated material (achieving a recycling rate of70-90%) is the optimum waste management system for the scenarios considered.Where incineration is the MSW option, recycling of source separated material (achieving a recyclingrate of 70-90%) is the optimum waste management system for the scenarios considered.
7.4 Sensitivity analysis
7.4.1 Methodological choices7.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same impact results, butapplying different impact assessment valuations (see Annex 4 for a list of maximum and minimumvaluations applied).
The graphs show that the results achieved and conclusions drawn are not sensitive to the economicvaluations applied to environmental impacts.
Graph 50 : PE film: Sensitivity of the results to the external economic valuations applied
PE Film from commercial and industrial sourcesSensitivity analysis on variations in economic valuations applied
-2500.0
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7.4.1.2 Internal costsInternal costs can vary considerably between Member States, depending on a range of factors such ascost of living and geographical considerations (mountainous regions, island populations, etc.). Toaccount for this variation, the dependency of the internal costs on the results have been investigated.The effect on the results of considering a +/-20% variation in internal costs is presented in the graphbelow. The graph shows that the results are not sensitive to this parameter.
Graph 51 : PE film: Sensitivity of the results to the internal economic costs considered
PE Film from commercial and industrial sourcesSensitivity analysis on variations in Internal Costs
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7.4.1.3 Inclusion of employment as an impact category
The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis. The graph shows that the results achieved and conclusionsdrawn are not sensitive to inclusion of this external impact category.
Graph 52 : PE film: Sensitivity of the results to the inclusion of employment as an impact category
PE film Total Social Cost when including employment as an impact category
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7.4.2 Sensitivity analysis: Scenario and modelling choices
Findings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.
Table 27 : Summary of sensitivity analysis of scenario and modelling choices for PE filmParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model
Combined heat and powerIncineration costs reducedNo effect on the relativestanding of scenarios
No effect on the choice ofoptimal scenario
Incineration modelOffset electricity
Incineration costs reducedNo effect on the relativestanding of scenarios
No effect on the choice ofoptimal scenario
Transport distancesCollection for landfill and
incinerationCollection for recycling
No effect on the relativestanding of scenarios
No effect on the choice ofoptimal scenario
Offset virgin production – saveratio considered
No effect on the relativestanding of scenarios
No effect on the choice ofoptimal scenario
8 Corrugated board from industrial sources
8.1 Scenarios considered
The table below summarises the parameters considered for the baseline scenarios modelled.
Table 28 : Scenarios considered for corrugated boardSelective collection scheme Recycling rate achieved MSW waste management
optionScenario 1 None 0% LandfillScenario 2 None 0% IncinerationScenario 3 Separate collection 70-90% LandfillScenario 4 Separate collection 70-90% Incineration
8.2 Results of the cost benefit analysis for corrugated board
This section presents and discusses the results of the cost benefit analysis for corrugated board.
Table 29 : Corrugated board: Internal costs, external costs and total social costs
Collection method N/A N/ARecycling rate 0.0 0.0Residual waste management option Landfill IncinerationExeternalities
GWP (kg CO2 eq.) 32.3 16.9 24.1 to 21.8 19.5 to 20.2Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0
Acidification (Acid equiv.) -0.2 -0.4 -0.4 to -0.5 -0.5 to -0.6Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0
Toxicity Gaseous (SO2 equiv.) -0.7 -1.6 -1.3 to -1.5 -1.6 to -1.6Toxicity Metals non carcinogens (Pb equiv.) 0.0 -0.2 -0.2 to -0.2 -0.2 to -0.2
Toxicity Particulates & aerosols (PM10 equiv) 2.6 -14.1 -26.1 to -34.3 -31.1 to -36.0Toxicity Smog (ethylene equiv.) 1.8 -0.1 -0.2 to -0.8 -0.8 to -1.0
Black smoke (kg dust eq.) -0.3 -1.4 -1.9 to -2.4 -2.2 to -2.5Fertilisation -0.2 0.0 0.4 to 0.5 0.4 to 0.5
Traffic accidents (risk equiv.) 0.1 0.1 0.1 to 0.2 0.1 to 0.2Traffic Congestion (car km equiv.) 1.3 1.3 8.2 to 10.2 8.2 to 10.2
Traffic Noise (car km equiv.) 0.1 0.1 0.1 to 0.0 0.1 to 0.1Water Quality Eutrophication (P equiv.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0
Disaminity (kg LF waste equiv.) 37.0 11.2 11.3 to 4.0 3.6 to 1.4TOTAL EXTERNALITIES 73.9 11.8 14.0 to -3.1 -4.7 to -9.4INTERNAL COSTS 148.8 154.8 84.5 to 66.2 86.3 to 66.8TOTAL SOCIAL COSTS 222.7 166.6 98.5 to 63.0 81.7 to 57.4
Recycling Recycling
Landfill Incineration70-90% 70-90%
Graph 53 : Corrugated board: Total social costs
Corrugated Board from industrial sourcesTotal Social Cost
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8.3 Main findings:
Where landfill is the MSW option, recycling of source separated material (achieving a recycling rate of70-90%) is the optimum waste management system for the scenarios considered.Where incineration is the MSW option, recycling of source separated material (achieving a recyclingrate of 70-90%) is the optimum waste management system for the scenarios considered.
8.4 Sensitivity analysis
8.4.1 Methodological choices8.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impactresults, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied).
The graph shows that the results achieved and conclusions that can be drawn are highly sensitive to theeconomic valuations applied.
Graph 54 : Corrugated board: Sensitivity of the results to the external economic valuations applied
Corrugated Board from industrial sourcesSensitivity analysis on variations in economic valuations applied
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8.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium.Even where equivalent waste management practices are compared internal costs can vary considerablybetween Member States, depending on a range of factors such as cost of living and geographicalconsiderations (mountainous regions, island populations, etc.). In this part of the sensitivity analysis,the effect on the results of considering a +/-20% variation in internal costs is investigated. The resultsare presented in the graph below.
The graph shows that the results achieved and conclusions that can be drawn are not sensitive to thisparameter.
Graph 55 : Corrugated board: Sensitivity of the results to the internal economic costs considered.
Corrugated Board from industrial sourcesSensitivity analysis on variations in Internal Costs
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8.4.1.3 Inclusion of employment as an impact category
The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis.
The graph shows that the results achieved and conclusions that can be drawn are not sensitive to thisparameter.
Graph 56 : Corrugated board: Sensitivity of the results to the addition of employment as an impactcategory
Corrugated boardTotal Social Cost when including employment as an impact category
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8.4.2 Scenario and modelling choices
Findings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.
Table 30 : Summary of sensitivity analysis of scenario and modelling choices for corrugated boardParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model
Combined heat and powerTotal social cost of incinerationreducedNo effect on the relativestanding of scenarios
No effect on choice of optimumsystem
Incineration modelOffset electricity
Total social cost of incinerationreducedNo effect on the relativestanding of scenarios
No effect on choice of optimumsystem
Transport distancesCollection for landfill or
incinerationCollection for recycling
No effect on the relativestanding of scenarios
No effect on choice of optimumsystem
Reprocessing overseasAddition of a distance of
1000 km by ocean ship
No effect on the relativestanding of scenarios
No effect on choice of optimumsystem
Annex 11: Presentation of the Global recycling targets per MemberState
This section presents the results of the targets calculation per Member State.
The 16 first pages concern the calculation of the minimum recycling targets, i.e. applying the lowest
recycling rate of the ranges to the packaging mix described in annex 6. The 16 last pages concern
the calculation of the maximum recycling targets per Member State, i.e. applying the highest
recycling rate of the ranges to the packaging mix described in annex 6.
The calculation methodology is described in the main report in chapter 3.4.
Minimum recycling ratesAUSTRIA 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 75 33LDPE films 55 29Other 20 4
Wood 60 29Steel 4 3Cardboard 384 233glass 47 22Other 0 0
Total 570 320
Global Target Industrial waste 56%
landfill Inc. landfill Inc.Household waste 47% 0% 37% 16%
Plastics 112 25PET bottles 20 70% 35% 59% 59% 13LPDE films 24 0% 0% 0% 0% 0HDPE bottles 24 57% 28% 48% 48% 13other 44 0% 0% 0% 0% 0
Steel 69 15% 80% 40% 80% 24aluminium total 9 2Wood 0 0% 0% 0% 0% 0Cardboard total 98 61% 61% 55% 55% 57composites liquid beverage cartons 23 0% 0% 0% 0% 0
mainly based on plastic 4 0% 0% 0% 0% 0mainly based on cardboard 5 0% 0% 0% 0% 0mainly based on Aluminium 3 0% 0% 0% 0% 0
Glass 183 73% 73% 42% 42% 104Other 0 0% 0% 0% 0% 0
Total 506 211
Global Target Household waste 42%
Total 1,076 532
Global target (Industrial + Household waste) 49%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
21%
50%
0% 55%0%
80%
0%0%
0%0%0%
0%
50%
64%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Minimum recycling ratesBelgium 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 91 32LDPE films 42 22Other 49 10
Wood 168 80Steel 56 43Cardboard 371 226glass 4 2Other 14 0
Total 704 382
Global Target Industrial waste 54%
landfill Inc. landfill Inc.Household waste 7% 7% 43% 43%
Plastics 162 34PET bottles 44 70% 35% 59% 59% 26LPDE films 43 0% 0% 0% 0% 0HDPE bottles 18 57% 28% 48% 48% 8other 57 0% 0% 0% 0% 0
Steel 80 15% 80% 40% 80% 47aluminium total 14 3Wood 0 0% 0% 0% 0% 0Cardboard total 153 61% 61% 55% 55% 85composites liquid beverage cartons 20 0% 0% 0% 0% 0
mainly based on plastic 3 0% 0% 0% 0% 0mainly based on cardboard 5 0% 0% 0% 0% 0mainly based on Aluminium 2 0% 0% 0% 0% 0
Glass 330 73% 73% 42% 42% 153Other 0 0% 0% 0% 0% 0
Total 768 322
Global Target Household waste 42%
Total 1,472 704
Global target (Industrial + Household waste) 48%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
Low High
Optimised recycling/reuse targetLow packaging amount
Percentage of population living in areas where population density is L/H and waste are I/L
0% 50%0% 0%
High packaging amount5% 95%
0% 55%0% 21%
0% 64%
0% 50%0% 80%
Minimum recycling ratesDENMARK 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 109 38LDPE films 51 27Other 58 12
Wood 84 40Steel 11 8Cardboard 314 191glass 0 0Other 0 0
Total 518 278
Global Target Industrial waste 54%
landfill Inc. landfill Inc.Household waste 0% 66% 0% 34%
Plastics 63 38PET bottles 5 70% 35% 59% 59% 2LPDE films 20 0% 0% 0% 0% 0HDPE food bottles 17 57% 28% 48% 48% 6other 21 0% 0% 0% 0% 0
Steel 37 15% 80% 40% 80% 30aluminium total 7 2Wood 9 0% 0% 0% 0% 0Cardboard total 121 61% 61% 55% 55% 71composites liquid beverage cartons 0 0% 0% 0% 0% 0
mainly based on plastic 1 0% 0% 0% 0% 0mainly based on cardboard 1 0% 0% 0% 0% 0mainly based on Aluminium 1 0% 0% 0% 0% 0
Glass 176 73% 73% 42% 42% 110Other 0 0% 0% 0% 0% 0
Total 416 221
Global Target Household waste 53%
Total 934 499
Global target (Industrial + Household waste) 53%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 64%0% 50%0% 0%
0% 21%0% 55%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
0% 50%0% 80%
Minimum recycling ratesFINLAND 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 48 17LDPE films 22 12other 26 5
Wood 0 0Steel 18 13Cardboard 192 117glass 6 3Other 0 0
Total 264 150
Global Target Industrial waste 57%
landfill Inc. landfill Inc.Household waste 58% 0% 40% 2%
Plastics 37 11PET bottles 6 70% 35% 59% 59% 4LPDE films 17 0% 0% 0% 0% 0HDPE bottles 15 57% 28% 48% 48% 8other 0 0% 0% 0% 0% 0
Steel 14 15% 80% 40% 80% 4aluminium total 2 0Wood 0 0% 0% 0% 0% 0Cardboard total 18 61% 61% 55% 55% 10composites liquid beverage cartons 29 0% 0% 0% 0% 0
mainly based on plastic 4 0% 0% 0% 0% 0mainly based on cardboard 7 0% 0% 0% 0% 0mainly based on Aluminium 0 0% 0% 0% 0% 0
Glass 50 73% 73% 42% 42% 30Other 0 0% 0% 0% 0% 0
Total 162 56
Global Target Household waste 35%
Total 425 206
Global target (Industrial + Household waste) 48%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
Low High
Optimised recycling/reuse targetLow packaging amount
Percentage of population living in areas where population density is L/H and waste are I/L
0% 50%0% 0%
High packaging amount5% 95%
0% 55%0% 21%
0% 64%
0% 50%0% 80%
Minimum recycling ratesFRANCE 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 730 232LDPE films 260 137Other 470 95
Wood 1,690 803Steel 280 213Cardboard 3,100 1,885glass 960 456Other 0 0
Total 6,760 3,588
Global Target Industrial waste 53%
landfill Inc. landfill Inc.Household waste 22% 8% 32% 39%
Plastics 902 197PET bottles 250 70% 35% 59% 59% 148LPDE films 140 0% 0% 0% 0% 0HDPE bottles 100 57% 28% 48% 48% 48other 412 0% 0% 0% 0% 0
Steel 350 15% 80% 40% 80% 187aluminium total 36 8Wood 10 0% 0% 0% 0% 0Cardboard total 872 61% 61% 55% 55% 495composites liquid beverage cartons 120 0% 0% 0% 0% 0
mainly based on plastic 18 0% 0% 0% 0% 0mainly based on cardboard 28 0% 0% 0% 0% 0mainly based on Aluminium 15 0% 0% 0% 0% 0
Glass 2,550 73% 73% 42% 42% 1,308Other 0 0% 0% 0% 0% 0
Total 4,901 2,195
Global Target Household waste 45%
Total 11,661 5,783
Global target (Industrial + Household waste) 50%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 55%
0% 64%0% 50%0% 0%
50%0% 80%
0% 21%0%
Minimum recycling ratesGERMANY 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 870 301LDPE films 384 202Other 486 98
Wood 1,969 935Steel 654 497Cardboard 4,350 2,645glass 88 42Other 0 0
Total 7,930 4,419
Global Target Industrial waste 56%
landfill Inc. landfill Inc.Household waste 16% 10% 44% 30%
Plastics 628 130PET bottles 100 70% 35% 59% 59% 58LPDE films 175 0% 0% 0% 0% 0HDPE bottles 152 57% 28% 48% 48% 72other 201 0% 0% 0% 0% 0
Steel 358 15% 80% 40% 80% 187aluminium total 62 11Wood 0 0% 0% 0% 0% 0Cardboard total 978 61% 61% 55% 55% 553composites liquid beverage cartons 209 0% 0% 0% 0% 0
mainly based on plastic 32 0% 0% 0% 0% 0mainly based on cardboard 48 0% 0% 0% 0% 0mainly based on Aluminium 26 0% 0% 0% 0% 0
Glass 3,512 73% 73% 42% 42% 1,758Other 14 0% 0% 0% 0% 0
Total 5,867 2,638
Global Target Household waste 45%
Total 13,798 7,058
Global target (Industrial + Household waste) 51%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 55%
0% 64%0% 50%0% 0%
50%0% 80%
0% 21%0%
Minimum recycling ratesGREECE 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 129.4 35LDPE films 27.8 15Other 101.6 21
Wood 38.3 18Steel 107.8 82Cardboard 402.7 245glass 118.1 56Other 21.6 0
Total 818 436
Global Target Industrial waste 53%
landfill Inc. landfill Inc.Household waste 41% 0% 59% 0%
Plastics 232 33PET bottles 35 70% 35% 59% 59% 22LPDE films 25 0% 0% 0% 0% 0HDPE bottles 21 57% 28% 48% 48% 11other 152 0% 0% 0% 0% 0
Steel 87 15% 80% 40% 80% 26aluminium total 14 4Wood 0 0% 0% 0% 0% 0Cardboard total 302 61% 61% 55% 55% 174composites liquid beverage cartons 25 0% 0% 0% 0% 0
mainly based on plastic 4 0% 0% 0% 0% 0mainly based on cardboard 6 0% 0% 0% 0% 0mainly based on Aluminium 3 0% 0% 0% 0% 0
Glass 145 73% 73% 42% 42% 79Other 0 0% 0% 0% 0% 0
Total 818 316
Global Target Household waste 39%
Total 1,635 752
Global target (Industrial + Household waste) 46%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 55%
0% 64%0% 50%0% 0%
50%0% 80%
0% 21%0%
Minimum recycling ratesIRELAND 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 52 15LDPE films 13 7Other 39 8
Wood 0 0Steel 10 8Cardboard 242 147glass 52 25Other 31 0
Total 387 194
Global Target Industrial waste 50%
landfill Inc. landfill Inc.Household waste 49% 2% 48% 1%
Plastics 117 12PET bottles 11 70% 35% 59% 59% 7LPDE films 11 0% 0% 0% 0% 0HDPE bottles 9 57% 28% 48% 48% 5other 86 0% 0% 0% 0% 0
Steel 21 15% 80% 40% 80% 6aluminium total 8 1Wood 0 0% 0% 0% 0% 0Cardboard total 50 61% 61% 55% 55% 29composites liquid beverage cartons 8 0% 0% 0% 0% 0
mainly based on plastic 1 0% 0% 0% 0% 0mainly based on cardboard 2 0% 0% 0% 0% 0mainly based on Aluminium 1 0% 0% 0% 0% 0
Glass 59 73% 73% 42% 42% 34Other 32 0% 0% 0% 0% 0
Total 300 82
Global Target Household waste 27%
Total 687 276
Global target (Industrial + Household waste) 40%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 64%0% 50%0% 0%
0% 21%0% 55%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
0% 50%0% 80%
Minimum recycling ratesITALY 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 591 204LDPE films 261 137Other 330 67
Wood 2,295 1,090Steel 223 170Cardboard 2,875 1,748glass 60 28Other 0 0
Total 6,043 3,240
Global Target Industrial waste 54%
landfill Inc. landfill Inc.Household waste 26% 2% 66% 6%
Plastics 1,309 368PET bottles 426 70% 35% 59% 59% 261LPDE films 248 0% 0% 0% 0% 0HDPE bottles 215 57% 28% 48% 48% 107other 420 0% 0% 0% 0% 0
Steel 247 15% 80% 40% 80% 91aluminium total 57 10Wood 109 0% 0% 0% 0% 0Cardboard total 1,300 61% 61% 55% 55% 737composites liquid beverage cartons 10 0% 0% 0% 0% 0
mainly based on plastic 2 0% 0% 0% 0% 0mainly based on cardboard 2 0% 0% 0% 0% 0mainly based on Aluminium 1 0% 0% 0% 0% 0
Glass 2,189 73% 73% 42% 42% 1,110Other 0 0% 0% 0% 0% 0
Total 5,227 2,316
Global Target Household waste 44%
Total 11,270 5,556
Global target (Industrial + Household waste) 49%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 50%0% 80%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 21%0% 55%
0% 64%0% 50%0% 0%
max
Minimum recycling ratesLUXEMBOURG 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 5 2LDPE films 2 1Other 3 1
Wood 9 4Steel 3 2Cardboard 19 12glass 0 0Other 1 0
Total 36 20
Global Target Industrial waste 54%
landfill Inc. landfill Inc.Household waste 10% 24% 20% 46%
Plastics 7 1PET bottles 2 70% 35% 59% 59% 1LPDE films 2 0% 0% 0% 0% 0HDPE bottles 1 57% 28% 48% 48% 0other 2 0% 0% 0% 0% 0
Steel 2 15% 80% 40% 80% 1aluminium total 0.5 0Wood 0 0% 0% 0% 0% 0Cardboard total 11 61% 61% 55% 55% 7composites liquid beverage cartons 1 0% 0% 0% 0% 0
mainly based on plastic 0 0% 0% 0% 0% 0mainly based on cardboard 0 0% 0% 0% 0% 0mainly based on Aluminium 1 0% 0% 0% 0% 0
Glass 17 73% 73% 42% 42% 9Other 0 0% 0% 0% 0% 0
Total 40 19
Global Target Household waste 46%
Total 77 38
Global target (Industrial + Household waste) 50%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 50%0% 80%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 21%0% 55%
0% 64%0% 50%0% 0%
Minimum recycling ratesNL 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 256 82LDPE films 92 49Other 164 33
Wood 379 180Steel 118 90Cardboard 1,128 686glass 23 11Other 0 0
Total 1,905 1,049
Global Target Industrial waste 55%
landfill Inc. landfill Inc.Household waste 6% 6% 44% 44%
Plastics 235 63PET bottles 67 70% 35% 59% 59% 39LPDE films 59 0% 0% 0% 0% 0HDPE bottles 51 57% 28% 48% 48% 24other 58 0% 0% 0% 0% 0
Steel 92 15% 80% 40% 80% 54aluminium total 10.4 3Wood 0 0% 0% 0% 0% 0Cardboard total 447 61% 61% 55% 55% 249composites liquid beverage cartons 47 0% 0% 0% 0% 0
mainly based on plastic 7 0% 0% 0% 0% 0mainly based on cardboard 11 0% 0% 0% 0% 0mainly based on Aluminium 6 0% 0% 0% 0% 0
Glass 436 73% 73% 42% 42% 200Other 0 0% 0% 0% 0% 0
Total 1,291 569
Global Target Household waste 44%
Total 3,196 1,618
Global target (Industrial + Household waste) 51%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 64%
0% 50%0% 80%
0%
High packaging amount5% 95%
0% 55%0% 21%
Low High
Optimised recycling/reuse targetLow packaging amount
Percentage of population living in areas where population density is L/H and waste are I/L
0% 50%0%
Minimum recycling ratesPORTUGAL 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 24 13LDPE films 24 13Other 0 0
Wood 7 3Steel 20 15Cardboard 75 45glass 22 10Other 4 0
Total 152 87
Global Target Industrial waste 57%
landfill Inc. landfill Inc.Household waste 36% 4% 55% 5%
Plastics 289 104PET bottles 106 70% 35% 59% 59% 66LPDE films 98 0% 0% 0% 0% 0HDPE bottles 75 57% 28% 48% 48% 38other 10 0% 0% 0% 0% 0
Steel 81 15% 80% 40% 80% 28aluminium total 14.6 2Wood 0 0% 0% 0% 0% 0Cardboard total 198 61% 61% 55% 55% 114composites liquid beverage cartons 12 0% 0% 0% 0% 0
mainly based on plastic 2 0% 0% 0% 0% 0mainly based on cardboard 3 0% 0% 0% 0% 0mainly based on Aluminium 2 0% 0% 0% 0% 0
Glass 314 73% 73% 42% 42% 171Other 0 0% 0% 0% 0% 0
Total 915 418
Global Target Household waste 46%
Total 1,067 505
Global target (Industrial + Household waste) 47%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 50%0% 80%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 21%0% 55%
0% 64%0% 50%0% 0%
Minimum recycling ratesSPAIN 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 411 123LDPE films 125 66Other 286 58
Wood 443 211Steel 43 33Cardboard 1,627 989glass 0 0Other 177 0
Total 2,702 1,356
Global Target Industrial waste 50%
landfill Inc. landfill Inc.Household waste 51% 4% 42% 3%
Plastics 601 160PET bottles 159 70% 35% 59% 59% 101LPDE films 130 0% 0% 0% 0% 0HDPE bottles 112 57% 28% 48% 48% 58other 200 0% 0% 0% 0% 0
Steel 235 15% 80% 40% 80% 71aluminium total 41.5 9Wood 0 0% 0% 0% 0% 0Cardboard total 828 61% 61% 55% 55% 483composites liquid beverage cartons 117 0% 0% 0% 0% 0
mainly based on plastic 18 0% 0% 0% 0% 0mainly based on cardboard 27 0% 0% 0% 0% 0mainly based on Aluminium 15 0% 0% 0% 0% 0
Glass 1,523 73% 73% 42% 42% 899Other 19 0% 0% 0% 0% 0
Total 3,423 1,621
Global Target Household waste 47%
Total 6,125 2,977
Global target (Industrial + Household waste) 49%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 64%
0% 50%0% 80%
0%
High packaging amount5% 95%
0% 55%0% 21%
Low High
Optimised recycling/reuse targetLow packaging amount
Percentage of population living in areas where population density is L/H and waste are I/L
0% 50%0%
Minimum recycling ratesSWEDEN 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 40 14LDPE films 19 10Other 21 4
Wood 0 0Steel 53 40Cardboard 370 225glass 60 28Other 0 0
Total 523 308
Global Target Industrial waste 59%
landfill Inc. landfill Inc.Household waste 26% 47% 9% 18%
Plastics 94 19PET bottles 19 70% 35% 59% 59% 10LPDE films 25 0% 0% 0% 0% 0HDPE bottles 22 57% 28% 48% 48% 9other 27 0% 0% 0% 0% 0
Steel 9 15% 80% 40% 80% 6aluminium total 7.5 5Wood 0 0% 0% 0% 0% 0Cardboard total 150 61% 61% 55% 55% 89composites liquid beverage cartons 40 0% 0% 0% 0% 0
mainly based on plastic 6 0% 0% 0% 0% 0mainly based on cardboard 9 0% 0% 0% 0% 0mainly based on Aluminium 5 0% 0% 0% 0% 0
Glass 111 73% 73% 42% 42% 72Other 0 0% 0% 0% 0% 0
Total 433 190
Global Target Household waste 44%
Total 956 498
Global target (Industrial + Household waste) 52%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 50%0% 80%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 21%0% 55%
0% 64%0% 50%0% 0%
Minimum recycling ratesUK 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 587 207LDPE films 273 144Other 314 64
Wood 670 318Steel 217 165Cardboard 3,373 2,051glass 350 166Other 40 0
Total 5,237 2,907
Global Target Industrial waste 56%
landfill Inc. landfill Inc.Household waste 13% 3% 69% 15%
Plastics 1,084 240PET bottles 252 70% 35% 59% 59% 151LPDE films 190 0% 0% 0% 0% 0HDPE bottles 183 57% 28% 48% 48% 89other 459 0% 0% 0% 0% 0
Steel 533 15% 80% 40% 80% 234aluminium total 108.0 30Wood 0 0% 0% 0% 0% 0Cardboard total 420 61% 61% 55% 55% 235composites liquid beverage cartons 51 0% 0% 0% 0% 0
mainly based on plastic 7 0% 0% 0% 0% 0mainly based on cardboard 11 0% 0% 0% 0% 0mainly based on Aluminium 6 0% 0% 0% 0% 0
Glass 1,848 73% 73% 42% 42% 868Other 0 0% 0% 0% 0% 0
Total 4,068 1,606
Global Target Household waste 39%
Total 9,305 4,513
Global target (Industrial + Household waste) 49%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
Low High
0%0%
areas where population density is L/H and waste are I/LPercentage of population living in
0%
0% 50%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 50%
55%0% 21%
0% 64%0% 80%
Minimum recycling ratesEU 2000 Amount of Amount of waste
Material Application waste to be recycled
Industrial waste 1000 t/year 1000 t/yearPlastics Total 4,018 1,348
LDPE films 1,651 869Other 2,367 479
Wood 7,812 3,711Steel 1,818 1,382Cardboard 18,823 11,444glass 1,789 850Other 289 0
Total 34,549 18,735
Global Target Industrial waste 54%
landfill Inc. landfill Inc.Household waste 27% 12% 41% 20%
Plastics 5,871 1,374PET bottles 1,502 70% 35% 59% 59% 887LPDE films 1,205 0% 0% 0% 0% 0HDPE bottles 1,015 57% 28% 48% 48% 487other 2,150 0% 0% 0% 0% 0
Steel 2,214 15% 80% 40% 80% 1,022aluminium total 391.6 96
cans 140 31% 76% 45% 76% 72other rigid and semi-rigid 131 0% 50% 6% 50% 24flexible 121 0% 0% 0% 0% 0
Wood 128 0% 0% 0% 0% 0Cardboard total 5,947 61% 61% 55% 55% 3,411composites liquid beverage cartons 710 0% 0% 0% 0% 0
mainly based on plastic 109 0% 0% 0% 0% 0mainly based on cardboard 165 0% 0% 0% 0% 0mainly based on Aluminium 86 0% 0% 0% 0% 0
Glass 13,445 73% 73% 42% 42% 7,288Other 65 0% 0% 0% 0% 0
Total 29,132 13,191
Global Target Household waste 45%
Total 63,681 31,926
Global target (Industrial + Household waste) 50%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 55%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 50%0%
21%0%0% 50%0% 80%
64%
Low High
0%0%
areas where population density is L/H and waste are I/LPercentage of population living in
Maximum recycling ratesAUSTRIA 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 75 47LDPE films 55 39Other 20 8
Wood 60 40Steel 4 3Cardboard 384 292glass 47 37Other 0 0
Total 570 420
Global Target Industrial waste 74%
landfill Inc. landfill Inc.Household waste 47% 0% 37% 16%
Plastics 112 30PET bottles 20 80% 45% 69% 69% 15LPDE films 24 0% 0% 0% 0% 0HDPE bottles 24 67% 38% 58% 58% 15other 44 0% 0% 0% 0% 0
Steel 69 60% 80% 60% 80% 43aluminium total 9 3Wood 0 0% 0% 0% 0% 0Cardboard total 98 71% 71% 65% 65% 66composites liquid beverage cartons 23 0% 0% 0% 0% 0
mainly based on plastic 4 0% 0% 0% 0% 0mainly based on cardboard 5 0% 0% 0% 0% 0mainly based on Aluminium 3 0% 0% 0% 0% 0
Glass 183 83% 83% 91% 91% 160Other 0 0% 0% 0% 0% 0
Total 506 302
Global Target Household waste 60%
Total 1,076 722
Global target (Industrial + Household waste) 67%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0%0%
0%0%0%
0%
70%
80%
41%
83%
0% 75%0%
90%
Maximum recycling ratesBelgium 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 91 49LDPE films 42 30Other 49 19
Wood 168 112Steel 56 48Cardboard 371 282glass 4 3Other 14 0
Total 704 494
Global Target Industrial waste 70%
landfill Inc. landfill Inc.Household waste 7% 7% 43% 43%
Plastics 162 40PET bottles 44 80% 45% 69% 69% 30LPDE films 43 0% 0% 0% 0% 0HDPE bottles 18 67% 38% 58% 58% 10other 57 0% 0% 0% 0% 0
Steel 80 60% 80% 60% 80% 56aluminium total 14 3Wood 0 0% 0% 0% 0% 0Cardboard total 153 71% 71% 65% 65% 101composites liquid beverage cartons 20 0% 0% 0% 0% 0
mainly based on plastic 3 0% 0% 0% 0% 0mainly based on cardboard 5 0% 0% 0% 0% 0mainly based on Aluminium 2 0% 0% 0% 0% 0
Glass 330 83% 83% 91% 91% 297Other 0 0% 0% 0% 0% 0
Total 768 497
Global Target Household waste 65%
Total 1,472 991
Global target (Industrial + Household waste) 67%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 80%
0% 70%0% 90%
0%
High packaging amount5% 95%
0% 75%0% 41%
Low High
Optimised recycling/reuse targetLow packaging amount
Percentage of population living in areas where population density is L/H and waste are I/L
0% 83%0%
Maximum recycling ratesDENMARK 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 109 59LDPE films 51 36Other 58 23
Wood 84 56Steel 11 9Cardboard 314 239glass 0 0Other 0 0
Total 518 363
Global Target Industrial waste 70%
landfill Inc. landfill Inc.Household waste 0% 66% 0% 34%
Plastics 63 40PET bottles 5 80% 45% 69% 69% 3LPDE films 20 0% 0% 0% 0% 0HDPE food bottles 17 67% 38% 58% 58% 8other 21 0% 0% 0% 0% 0
Steel 37 60% 80% 60% 80% 30aluminium total 7 2Wood 9 0% 0% 0% 0% 0Cardboard total 121 71% 71% 65% 65% 83composites liquid beverage cartons 0 0% 0% 0% 0% 0
mainly based on plastic 1 0% 0% 0% 0% 0mainly based on cardboard 1 0% 0% 0% 0% 0mainly based on Aluminium 1 0% 0% 0% 0% 0
Glass 176 83% 83% 91% 91% 151Other 0 0% 0% 0% 0% 0
Total 416 276
Global Target Household waste 66%
Total 934 639
Global target (Industrial + Household waste) 68%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 70%0% 90%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 41%0% 75%
0% 80%0% 83%0% 0%
Maximum recycling ratesFINLAND 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 48 26LDPE films 22 16other 26 10
Wood 0 0Steel 18 15Cardboard 192 146glass 6 4Other 0 0
Total 264 192
Global Target Industrial waste 73%
landfill Inc. landfill Inc.Household waste 58% 0% 40% 2%
Plastics 37 13PET bottles 6 80% 45% 69% 69% 4LPDE films 17 0% 0% 0% 0% 0HDPE bottles 15 67% 38% 58% 58% 9other 0 0% 0% 0% 0% 0
Steel 14 60% 80% 60% 80% 9aluminium total 2 1Wood 0 0% 0% 0% 0% 0Cardboard total 18 71% 71% 65% 65% 12composites liquid beverage cartons 29 0% 0% 0% 0% 0
mainly based on plastic 4 0% 0% 0% 0% 0mainly based on cardboard 7 0% 0% 0% 0% 0mainly based on Aluminium 0 0% 0% 0% 0% 0
Glass 50 83% 83% 91% 91% 43Other 0 0% 0% 0% 0% 0
Total 162 78
Global Target Household waste 48%
Total 425 270
Global target (Industrial + Household waste) 63%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 80%
0% 70%0% 90%
0%
High packaging amount5% 95%
0% 75%0% 41%
Low High
Optimised recycling/reuse targetLow packaging amount
Percentage of population living in areas where population density is L/H and waste are I/L
0% 83%0%
Maximum recycling ratesFRANCE 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 730 371LDPE films 260 186Other 470 184
Wood 1,690 1,124Steel 280 239Cardboard 3,100 2,356glass 960 757Other 0 0
Total 6,760 4,847
Global Target Industrial waste 72%
landfill Inc. landfill Inc.Household waste 22% 8% 32% 39%
Plastics 902 232PET bottles 250 80% 45% 69% 69% 173LPDE films 140 0% 0% 0% 0% 0HDPE bottles 100 67% 38% 58% 58% 58other 412 0% 0% 0% 0% 0
Steel 350 60% 80% 60% 80% 243aluminium total 36 10Wood 10 0% 0% 0% 0% 0Cardboard total 872 71% 71% 65% 65% 583composites liquid beverage cartons 120 0% 0% 0% 0% 0
mainly based on plastic 18 0% 0% 0% 0% 0mainly based on cardboard 28 0% 0% 0% 0% 0mainly based on Aluminium 15 0% 0% 0% 0% 0
Glass 2,550 83% 83% 91% 91% 2,259Other 0 0% 0% 0% 0% 0
Total 4,901 3,326
Global Target Household waste 68%
Total 11,661 8,173
Global target (Industrial + Household waste) 70%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
70%0% 90%
0% 41%0%
0% 80%0% 83%0% 0%
0% 75%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Maximum recycling ratesGERMANY 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 870 466LDPE films 384 275Other 486 191
Wood 1,969 1,309Steel 654 559Cardboard 4,350 3,306glass 88 69Other 0 0
Total 7,930 5,709
Global Target Industrial waste 72%
landfill Inc. landfill Inc.Household waste 16% 10% 44% 30%
Plastics 628 155PET bottles 100 80% 45% 69% 69% 68LPDE films 175 0% 0% 0% 0% 0HDPE bottles 152 67% 38% 58% 58% 87other 201 0% 0% 0% 0% 0
Steel 358 60% 80% 60% 80% 244aluminium total 62 13Wood 0 0% 0% 0% 0% 0Cardboard total 978 71% 71% 65% 65% 651composites liquid beverage cartons 209 0% 0% 0% 0% 0
mainly based on plastic 32 0% 0% 0% 0% 0mainly based on cardboard 48 0% 0% 0% 0% 0mainly based on Aluminium 26 0% 0% 0% 0% 0
Glass 3,512 83% 83% 91% 91% 3,123Other 14 0% 0% 0% 0% 0
Total 5,867 4,186
Global Target Household waste 71%
Total 13,798 9,895
Global target (Industrial + Household waste) 72%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
70%0% 90%
0% 41%0%
0% 80%0% 83%0% 0%
0% 75%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Maximum recycling ratesGREECE 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 129.4 60LDPE films 27.8 20Other 101.6 40
Wood 38.3 25Steel 107.8 92Cardboard 402.7 306glass 118.1 93Other 21.6 0
Total 818 576
Global Target Industrial waste 70%
landfill Inc. landfill Inc.Household waste 41% 0% 59% 0%
Plastics 232 39PET bottles 35 80% 45% 69% 69% 25LPDE films 25 0% 0% 0% 0% 0HDPE bottles 21 67% 38% 58% 58% 13other 152 0% 0% 0% 0% 0
Steel 87 60% 80% 60% 80% 52aluminium total 14 6Wood 0 0% 0% 0% 0% 0Cardboard total 302 71% 71% 65% 65% 204composites liquid beverage cartons 25 0% 0% 0% 0% 0
mainly based on plastic 4 0% 0% 0% 0% 0mainly based on cardboard 6 0% 0% 0% 0% 0mainly based on Aluminium 3 0% 0% 0% 0% 0
Glass 145 83% 83% 91% 91% 127Other 0 0% 0% 0% 0% 0
Total 818 428
Global Target Household waste 52%
Total 1,635 1,004
Global target (Industrial + Household waste) 61%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
70%0% 90%
0% 41%0%
0% 80%0% 83%0% 0%
0% 75%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Maximum recycling ratesIRELAND 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 52 25LDPE films 13 9Other 39 15
Wood 0 0Steel 10 8Cardboard 242 184glass 52 41Other 31 0
Total 387 258
Global Target Industrial waste 67%
landfill Inc. landfill Inc.Household waste 49% 2% 48% 1%
Plastics 117 14PET bottles 11 80% 45% 69% 69% 8LPDE films 11 0% 0% 0% 0% 0HDPE bottles 9 67% 38% 58% 58% 6other 86 0% 0% 0% 0% 0
Steel 21 60% 80% 60% 80% 13aluminium total 8 2Wood 0 0% 0% 0% 0% 0Cardboard total 50 71% 71% 65% 65% 34composites liquid beverage cartons 8 0% 0% 0% 0% 0
mainly based on plastic 1 0% 0% 0% 0% 0mainly based on cardboard 2 0% 0% 0% 0% 0mainly based on Aluminium 1 0% 0% 0% 0% 0
Glass 59 83% 83% 91% 91% 51Other 32 0% 0% 0% 0% 0
Total 300 114
Global Target Household waste 38%
Total 687 372
Global target (Industrial + Household waste) 54%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 70%0% 90%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 41%0% 75%
0% 80%0% 83%0% 0%
Maximum recycling ratesITALY 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 591 316LDPE films 261 187Other 330 130
Wood 2,295 1,526Steel 223 191Cardboard 2,875 2,185glass 60 47Other 0 0
Total 6,043 4,265
Global Target Industrial waste 71%
landfill Inc. landfill Inc.Household waste 26% 2% 66% 6%
Plastics 1,309 432PET bottles 426 80% 45% 69% 69% 304LPDE films 248 0% 0% 0% 0% 0HDPE bottles 215 67% 38% 58% 58% 129other 420 0% 0% 0% 0% 0
Steel 247 60% 80% 60% 80% 152aluminium total 57 15Wood 109 0% 0% 0% 0% 0Cardboard total 1,300 71% 71% 65% 65% 867composites liquid beverage cartons 10 0% 0% 0% 0% 0
mainly based on plastic 2 0% 0% 0% 0% 0mainly based on cardboard 2 0% 0% 0% 0% 0mainly based on Aluminium 1 0% 0% 0% 0% 0
Glass 2,189 83% 83% 91% 91% 1,943Other 0 0% 0% 0% 0% 0
Total 5,227 3,409
Global Target Household waste 65%
Total 11,270 7,674
Global target (Industrial + Household waste) 68%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 70%0% 90%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 41%0% 75%
0% 80%0% 83%0% 0%
max
Maximum recycling ratesLUXEMBOURG 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 5 3LDPE films 2 2Other 3 1
Wood 9 6Steel 3 2Cardboard 19 15glass 0 0Other 1 0
Total 36 26
Global Target Industrial waste 70%
landfill Inc. landfill Inc.Household waste 10% 24% 20% 46%
Plastics 7 2PET bottles 2 80% 45% 69% 69% 1LPDE films 2 0% 0% 0% 0% 0HDPE bottles 1 67% 38% 58% 58% 0other 2 0% 0% 0% 0% 0
Steel 2 60% 80% 60% 80% 2aluminium total 0.5 0Wood 0 0% 0% 0% 0% 0Cardboard total 11 71% 71% 65% 65% 8composites liquid beverage cartons 1 0% 0% 0% 0% 0
mainly based on plastic 0 0% 0% 0% 0% 0mainly based on cardboard 0 0% 0% 0% 0% 0mainly based on Aluminium 1 0% 0% 0% 0% 0
Glass 17 83% 83% 91% 91% 15Other 0 0% 0% 0% 0% 0
Total 40 26
Global Target Household waste 66%
Total 77 52
Global target (Industrial + Household waste) 68%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 70%0% 90%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 41%0% 75%
0% 80%0% 83%0% 0%
Maximum recycling ratesNL 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 256 130LDPE films 92 66Other 164 64
Wood 379 252Steel 118 101Cardboard 1,128 858glass 23 18Other 0 0
Total 1,905 1,360
Global Target Industrial waste 71%
landfill Inc. landfill Inc.Household waste 6% 6% 44% 44%
Plastics 235 75PET bottles 67 80% 45% 69% 69% 46LPDE films 59 0% 0% 0% 0% 0HDPE bottles 51 67% 38% 58% 58% 29other 58 0% 0% 0% 0% 0
Steel 92 60% 80% 60% 80% 65aluminium total 10.4 3Wood 0 0% 0% 0% 0% 0Cardboard total 447 71% 71% 65% 65% 294composites liquid beverage cartons 47 0% 0% 0% 0% 0
mainly based on plastic 7 0% 0% 0% 0% 0mainly based on cardboard 11 0% 0% 0% 0% 0mainly based on Aluminium 6 0% 0% 0% 0% 0
Glass 436 83% 83% 91% 91% 392Other 0 0% 0% 0% 0% 0
Total 1,291 829
Global Target Household waste 64%
Total 3,196 2,188
Global target (Industrial + Household waste) 68%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 80%
0% 70%0% 90%
0%
High packaging amount5% 95%
0% 75%0% 41%
Low High
Optimised recycling/reuse targetLow packaging amount
Percentage of population living in areas where population density is L/H and waste are I/L
0% 83%0%
Maximum recycling ratesPORTUGAL 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 24 17LDPE films 24 17Other 0 0
Wood 7 5Steel 20 17Cardboard 75 57glass 22 17Other 4 0
Total 152 113
Global Target Industrial waste 75%
landfill Inc. landfill Inc.Household waste 36% 4% 55% 5%
Plastics 289 122PET bottles 106 80% 45% 69% 69% 76LPDE films 98 0% 0% 0% 0% 0HDPE bottles 75 67% 38% 58% 58% 45other 10 0% 0% 0% 0% 0
Steel 81 60% 80% 60% 80% 50aluminium total 14.6 3Wood 0 0% 0% 0% 0% 0Cardboard total 198 71% 71% 65% 65% 133composites liquid beverage cartons 12 0% 0% 0% 0% 0
mainly based on plastic 2 0% 0% 0% 0% 0mainly based on cardboard 3 0% 0% 0% 0% 0mainly based on Aluminium 2 0% 0% 0% 0% 0
Glass 314 83% 83% 91% 91% 276Other 0 0% 0% 0% 0% 0
Total 915 584
Global Target Household waste 64%
Total 1,067 697
Global target (Industrial + Household waste) 65%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 70%0% 90%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 41%0% 75%
0% 80%0% 83%0% 0%
Maximum recycling ratesSPAIN 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 411 201LDPE films 125 89Other 286 112
Wood 443 295Steel 43 37Cardboard 1,627 1,236glass 0 0Other 177 0
Total 2,702 1,770
Global Target Industrial waste 66%
landfill Inc. landfill Inc.Household waste 51% 4% 42% 3%
Plastics 601 187PET bottles 159 80% 45% 69% 69% 117LPDE films 130 0% 0% 0% 0% 0HDPE bottles 112 67% 38% 58% 58% 70other 200 0% 0% 0% 0% 0
Steel 235 60% 80% 60% 80% 144aluminium total 41.5 14Wood 0 0% 0% 0% 0% 0Cardboard total 828 71% 71% 65% 65% 565composites liquid beverage cartons 117 0% 0% 0% 0% 0
mainly based on plastic 18 0% 0% 0% 0% 0mainly based on cardboard 27 0% 0% 0% 0% 0mainly based on Aluminium 15 0% 0% 0% 0% 0
Glass 1,523 83% 83% 91% 91% 1,319Other 19 0% 0% 0% 0% 0
Total 3,423 2,229
Global Target Household waste 65%
Total 6,125 3,999
Global target (Industrial + Household waste) 65%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 80%
0% 70%0% 90%
0%
High packaging amount5% 95%
0% 75%0% 41%
Low High
Optimised recycling/reuse targetLow packaging amount
Percentage of population living in areas where population density is L/H and waste are I/L
0% 83%0%
Maximum recycling ratesSWEDEN 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 40 22LDPE films 19 13Other 21 8
Wood 0 0Steel 53 45Cardboard 370 281glass 60 47Other 0 0
Total 523 395
Global Target Industrial waste 76%
landfill Inc. landfill Inc.Household waste 26% 47% 9% 18%
Plastics 94 23PET bottles 19 80% 45% 69% 69% 12LPDE films 25 0% 0% 0% 0% 0HDPE bottles 22 67% 38% 58% 58% 11other 27 0% 0% 0% 0% 0
Steel 9 60% 80% 60% 80% 7aluminium total 7.5 5Wood 0 0% 0% 0% 0% 0Cardboard total 150 71% 71% 65% 65% 104composites liquid beverage cartons 40 0% 0% 0% 0% 0
mainly based on plastic 6 0% 0% 0% 0% 0mainly based on cardboard 9 0% 0% 0% 0% 0mainly based on Aluminium 5 0% 0% 0% 0% 0
Glass 111 83% 83% 91% 91% 95Other 0 0% 0% 0% 0% 0
Total 433 234
Global Target Household waste 54%
Total 956 629
Global target (Industrial + Household waste) 66%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 70%0% 90%
Percentage of population living in areas where population density is L/H and waste are I/L
Low High
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 41%0% 75%
0% 80%0% 83%0% 0%
Maximum recycling ratesUK 2000 Amount of Amount of waste
Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year
Plastics Total 587 319LDPE films 273 196Other 314 123
Wood 670 446Steel 217 186Cardboard 3,373 2,563glass 350 276Other 40 0
Total 5,237 3,789
Global Target Industrial waste 72%
landfill Inc. landfill Inc.Household waste 13% 3% 69% 15%
Plastics 1,084 283PET bottles 252 80% 45% 69% 69% 176LPDE films 190 0% 0% 0% 0% 0HDPE bottles 183 67% 38% 58% 58% 107other 459 0% 0% 0% 0% 0
Steel 533 60% 80% 60% 80% 339aluminium total 108.0 37Wood 0 0% 0% 0% 0% 0Cardboard total 420 71% 71% 65% 65% 277composites liquid beverage cartons 51 0% 0% 0% 0% 0
mainly based on plastic 7 0% 0% 0% 0% 0mainly based on cardboard 11 0% 0% 0% 0% 0mainly based on Aluminium 6 0% 0% 0% 0% 0
Glass 1,848 83% 83% 91% 91% 1,658Other 0 0% 0% 0% 0% 0
Total 4,068 2,594
Global Target Household waste 64%
Total 9,305 6,384
Global target (Industrial + Household waste) 69%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
Low High
0%0%
areas where population density is L/H and waste are I/LPercentage of population living in
0%
0% 70%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 83%
75%0% 41%
0% 80%0% 90%
Maximum recycling ratesEU 2000 Amount of Amount of waste
Material Application waste to be recycled
Industrial waste 1000 t/year 1000 t/yearPlastics Total 4,018 2,111
LDPE films 1,651 1,182Other 2,367 929
Wood 7,812 5,195Steel 1,818 1,555Cardboard 18,823 14,306glass 1,789 1,411Other 289 0
Total 34,549 24,577
Global Target Industrial waste 71%
landfill Inc. landfill Inc.Household waste 27% 12% 41% 20%
Plastics 5,871 1,626PET bottles 1,502 80% 45% 69% 69% 1,037LPDE films 1,205 0% 0% 0% 0% 0HDPE bottles 1,015 67% 38% 58% 58% 589other 2,150 0% 0% 0% 0% 0
Steel 2,214 60% 80% 60% 80% 1,472aluminium total 391.6 122Wood 128 0% 0% 0% 0% 0Cardboard total 5,947 71% 71% 65% 65% 4,006composites liquid beverage cartons 710 0% 0% 0% 0% 0
mainly based on plastic 109 0% 0% 0% 0% 0mainly based on cardboard 165 0% 0% 0% 0% 0mainly based on Aluminium 86 0% 0% 0% 0% 0
Glass 13,445 83% 83% 91% 91% 11,811Other 65 0% 0% 0% 0% 0
Total 29,132 19,036
Global Target Household waste 65%
Total 63,681 43,613
Global target (Industrial + Household waste) 68%
data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data
0% 75%
Optimised recycling/reuse targetLow packaging amount High packaging amount
5% 95%
0% 83%0%
41%0%0% 70%0% 90%
80%
Low High
0%0%
areas where population density is L/H and waste are I/LPercentage of population living in
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6FHQDULRV�FRQVLGHUHGIn order to investigate the potential costs and benefits of refillable PET beverage bottles, the purchase of 1000 litresof product by the consumer is compared for single trip and refillable bottles. The analysis relates to 1.5 litrebottles. The weight of a refillable bottle is assumed to be 0.084 kg1. The weight of a single trip bottle is assumedto be 0.039 kg2.
It is assumed that costs and burdens of transport will increase linearly as distance between filler and end marketincreases. In order to compare the costs and benefits of single trip and refillables over a range of distances, eightwide-ranging scenarios have been modelled. These are listed in the table below:
6FHQDULRV�FRQVLGHUHG�IRU�VLQJOH�WULS�DQG�UHILOODEOH�3(7�EHYHUDJH�ERWWOHV
Scenario Distance to market* Number of uses Recycling rateReuse Scenario 1 0km 5 (i.e. every 6th bottle is new)Reuse Scenario 2 1800km 5 (i.e. every 6th bottle is new)Reuse Scenario 3 0km 20 (i.e. every 21st bottle is new)Reuse Scenario 4 1800km 20 (i.e. every 21st bottle is new)Single trip scenario 1 0km 20%Single trip scenario 2 1800km 20%Single trip scenario 3 0 km 80%Single trip scenario 4 1800 km 80%*Distance to market = distance from filler to distribution centre*Transport from distribution centre to supermarket / retail outlet is assumed to be a 100 km round trip for allscenarios
The following assumptions have been made in order to simplify the analysis:♦ The common elements between the reusable and single trip bottles have been ignored. These include caps,
labels, and tertiary packaging♦ Returnable bottles are assumed to be packed in reusable crates (99,4% reuse)♦ Single trip bottles are packed in cartonboard trays with plastic film overwrap (100% to recycling)♦ The return rate for the refillable PET bottles is 100%. All losses occur during the washing and refilling
process.♦ For single trip PET bottles, the portion that is not recycled is split evenly between landfill and incineration
1 ³/LIH� &\FOH� $VVHVVPHQW� RI� 3DFNDJLQJ� 6\VWHPV� IRU� %HHU� DQG� 6RIW� 'ULQNV�� 'LVSRVDEOH� 3(7� %RWWOHV´� DanishEnvironmental Protection Agency, 19982 ³/LIH� &\FOH� $VVHVVPHQW� RI� 3DFNDJLQJ� 6\VWHPV� IRU� %HHU� DQG� 6RIW� 'ULQNV�� 'LVSRVDEOH� 3(7� %RWWOHV´� DanishEnvironmental Protection Agency, 1998
&DOFXODWLRQ�RI�LQWHUQDO�FRVWVThe internal costs used for the analysis are listed in the table below.
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3ULPDU\�SURGXFWLRQ�FRVWV��(XUR�SHU�����O�SURGXFW�SXUFKDVHG�E\�FRQVXPHU�
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)LOOHUV�FRVWV������OLWUHV�RI�SURGXFW�SXUFKDVHG�E\�FRQVXPHU�
WUDQVSRUW�GLVWDQFH�IURP�ILOOHU�WR�GLVWULEXWRU��NP�
FRVW�RI�ZDVWH�PDQDJHPHQW��SHU�WRQQH�RI�3(7�
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System 1 0km 0.20 666.67 68.09 0.00 0.00 0.00 443.60 11.53 79.63System 2 1800km 0.20 666.67 68.09 518.69 0.00 1800.00 443.60 11.53 598.31System 3 0km 0.80 666.67 68.09 0.00 0.00 0.00 783.20 20.36 88.46System 4 1800km 0.80 666.67 68.09 518.69 0.00 1800.00 783.20 20.36 607.14
number of uses return rate
transport to market (all round distance from filling to market and back again) (km)
Frequency of bottle replacement
Number of new bottles per 1000l product purchased by consumer
new PET bottles required for 1000l product purchased by consumer (kg)
Cost of primary production per 1000l
GLVWULEXWLRQ�DQG�KDQGOLQJ�LQFOXGLQJ�UHWXUQ�WULS��SHU�����OLWUHV�SURGXFW�SXUFKDVHG�filler
Cost of collection/sorting (per 1000litres of product purchased by consumer)
Waste management of non-reused bottles
System 1 5.00 100% 0.00 5.00 133.33 11.20 12.60 0.00 60.84 3.84System 2 5.00 100% 3600.00 5.00 133.33 11.20 12.60 940.53 60.84 3.84System 3 20.00 100% 0.00 20.00 33.33 2.80 50.39 0.00 60.84 0.96System 4 20.00 100% 3600.00 20.00 33.33 2.80 50.39 940.53 60.84 0.96
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The external costs of each scenario are presented in the table below:
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ObservationsThe transportation distance plays a much more important role than the number of uses :
• DELTA = 2.53 ¼�EHWZHHQ���DQG����XVHV• DELTA = 99.43 ¼�IRU������NP��L�H�����¼�IRU�����NP�
The external costs are small compared to the internal costs (5-10%)
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HeadingNameRefillables System 1
Refillables System 2
Refillables System 3
Refillables System 4
GWP (kg CO2 eq.) 0.32 3.32 0.16 3.16Ozone depletion (kg CFC 11 eq.) 0.00 0.00 0.00 0.00Acidification (Acid equiv.) 0.06 0.24 0.02 0.20Toxicity Carcinogens (Cd equiv) 0.00 0.01 0.00 0.01Toxicity Gaseous (SO2 equiv.) 0.20 0.76 0.06 0.62Toxicity Metals non carcinogens (Pb equiv.) 0.03 0.12 0.01 0.10Toxicity Particulates & aerosols (PM10 equiv) 5.85 50.31 4.03 48.49Toxicity Smog (ethylene equiv.) 0.26 1.89 0.10 1.74Black smoke (kg dust eq.) 0.16 0.84 0.06 0.74Fertilisation -0.09 -0.90 -0.04 -0.85Traffic accidents (risk equiv.) 0.13 2.02 0.12 2.01Traffic Congestion (car km equiv.) 2.80 47.41 2.71 47.32Traffic Noise (car km equiv.) 0.23 3.28 0.19 3.25Water Quality Eutrophication (P equiv.) 0.01 0.07 0.00 0.07Disaminity (kg LF waste equiv.) 0.00 0.00 0.00 0.00
Total external cost 9.95 109.38 7.42 106.84Internal costs 234.80 1175.34 106.05 1046.58
Total social cost 244.76 1284.72 113.47 1153.43
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GWP (kg CO2 eq.) 1.16 2.59 0.66 2.09Ozone depletion (kg CFC 11 eq.) 0.00 0.00 0.00 0.00Acidification (Acid equiv.) 0.22 0.30 0.11 0.19Toxicity Carcinogens (Cd equiv) 0.00 0.00 0.00 0.00Toxicity Gaseous (SO2 equiv.) 0.81 1.10 0.40 0.69Toxicity Metals non carcinogens (Pb equiv.) 0.24 0.28 0.15 0.19Toxicity Particulates & aerosols (PM10 equiv) 9.00 32.93 6.30 30.23Toxicity Smog (ethylene equiv.) 1.25 1.96 0.62 1.33Black smoke (kg dust eq.) 0.54 0.85 0.27 0.58Fertilisation -0.34 -0.67 -0.18 -0.51Traffic accidents (risk equiv.) 0.09 1.08 0.10 1.09Traffic Congestion (car km equiv.) 2.06 25.39 2.12 25.46Traffic Noise (car km equiv.) 0.15 1.75 0.20 1.79Water Quality Eutrophication (P equiv.) 0.03 0.06 0.02 0.05Disaminity (kg LF waste equiv.) 0.51 0.51 0.13 0.13
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5HVXOWV�RI�WKH�FRVW�EHQHILW�DQDO\VLVThe results of analysis are presented in the three graphs below. The graphs present the internal costs and externalcosts and total social costs (i.e. the sum of the internal and external costs) for each scenario as a function ofdistance to market.
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returnables (5reuses)
returnables (20reuses
single trip (42%recycling)
"single trip (91%recycling)
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returnables (5 reuses)
returnables (20 reuses
single trip (42%recycling)
single trip (91%recycling)
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returnables (5 reuses)
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c
,QLWLDO�FRQFOXVLRQV�From an internal cost perspective:♦ Single trip PET bottles are always preferable to refillables
From an external cost perspective:♦ Refillables are preferable to single trip bottles up until approximately 30km♦ Above approximately 150km, single trip bottles are preferable♦ Between 30 and 1500km, the preferred option is dependent on the number of reuses achieved by the refillables
and the recycling rate achieved for the single trip bottles
From a total social cost perspective:♦ Single trip bottles are always preferable to refillables whatever distance is considered.♦ Internal costs outweight the external costs. The eco-efficiency of switching from single trip without recycling
to single trip with recycling is in any case considerably higher than switching from single trip to refillable (thisswitch might even be negative,as soon as the distance exceeds 100-200 km).
6XPPDU\�RI�VHQVLWLYLW\�DQDO\VLV�UHVXOWVThe results achieved and conclusions drawn are sensitive to the economic valuations applied and the internal costsapplied.
5HILOODEOH�DQG�VLQJOH�WULS�*ODVV�EHYHUDJH�ERWWOHV�IURP�KRXVHKROGVRXUFHIn this section, the results for glass refillable and single trip beverage bottles are explained. For other cases studies,the main results, conclusions and the implications of the sensitivity analysis are presented only.
6FHQDULRV�FRQVLGHUHGIn order to investigate the potential costs and benefits of refillable glass beverage bottles, the purchase of 1000 l ofproduct by the consumer is compared for single trip and refillable bottles. The analysis relates to 330 ml bottles.The weight of a refillable bottle is assumed to be 0.33kg, with the weight of a single trip bottle assumed to be 0.22kg.
It is assumed that costs and burdens of transport will increase in a linear manor as distance between filler and endmarket increases. In order to compare the costs and benefits of single trip and refillables over a range of distances,eight wide-ranging scenarios have been modelled. These are listed in the table below:
Scenarios considered for single trip and refillable glass beverage bottles
Scenario Distance to market* Number of reuses Recycling rateReuse Scenario 1 0km 5 (i.e. every 6th bottle is
new)Reuse Scenario 2 1800km 5 (i.e. every 6th bottle is
new)Reuse Scenario 3 0km 20 (i.e. every 21st bottle is
new)Reuse Scenario 4 1800km 20 (i.e. every 21st bottle is
new)Recycling scenario 1 0km 42%Recycling scenario 2 1800km 42%Recycling scenario 3 0km 91%Recycling scenario 4 1800km 91%*Distance to market = distance from filler to distribution centre*Transport from distribution centre to supermarket/retail outlet is assumed to be a 100 km round trip for allscenarios
The following assumptions have been made in order to simplify the analysis:♦ Common elements between the reusable and single trip bottles have been ignored. These include – the caps,
labels, and transport packaging.♦ the Returnable bottles are assumed to be packed in reusable plastic crates (99.4% reuse)♦ the single trip bottles are packed in Cartonboard trays with plastic film over wrap 100% of which goes to
material recycling♦ The return rate for the refillable glass bottle is assumed to be100%. All losses occur during the washing and
refilling process.♦ For single trip glass bottles, the portion that is not recycled is split evenly between landfill and incineration
&DOFXODWLRQ�RI�LQWHUQDO�FRVWVThe internal costs used for the analysis are listed in the table below.
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System 1 0km 0.42 3030.30 666.67 132.53 10.20 223.43 0.00 0.00 124.01 82.67 448.83System 2 1800km 0.42 3030.30 666.67 132.53 10.20 223.43 1800.00 2988.00 124.01 82.67 3436.83System 3 0km 0.91 3030.30 666.67 132.53 10.20 223.43 0.00 0.00 66.98 44.65 410.81System 4 1800km 0.91 3030.30 666.67 132.53 10.20 223.43 1800.00 2988.00 66.98 44.65 3398.81
number of reuses return rate
transport to market (all round distance from filling to market and back again) (km)
Frequency of bottle replacement
Number of new bottles per 1000l product purchased by consumer
new glass bottles required for 1000l product purchased by consumer (kg)
Cost of glass production (1000litres purchased product)
transport from glass factory to fillers (1000litres of product purchased by consumer)
Fillers costs (1000litres of product purchased by consumer)
transport from fillers to distribution (per 1000litres product purchased by
Cost of deposit infrastructure (per 1000litres of product purchased by consumer)
transport from deposit to sorting plant (per 1000litres product purchased by
sorting before washing (costs per 1000l product purchased by consumer)
transport from sorting to fillers (euro per 1000litres product purchased by
washing (Eurp per 1000l product purchased by consumer)
Waste management of non-reused bottles
Total costs Euro per 1000litres product purchased by consumer)
System 1 5.00 100% 0.00 5.00 606.06 200.00 39.76 3.06 71.58 0.00 27.62 4.01 11.70 0.00 75.15 16.26 ������
System 2 5.00 100% 3600.00 5.00 606.06 200.00 39.76 3.06 71.58 2988.00 27.62 4.01 11.70 2988.00 75.15 16.26 �������
System 3 20.00 100% 0.00 20.00 151.52 50.00 9.94 0.77 71.58 0.00 27.62 4.01 11.70 0.00 75.15 4.06 ������
System 4 20.00 100% 3600.00 20.00 151.52 50.00 9.94 0.77 71.58 2988.00 27.62 4.01 11.70 2988.00 75.15 4.06 �������
System 5 5.00 50% 0.00 2.50 1212.12 400.00 79.52 6.12 71.58 0.00 55.25 2.01 5.85 0.00 37.58 32.52 ������
System 6 5.00 50% 3600.00 2.50 1212.12 400.00 79.52 6.12 71.58 2988.00 55.25 2.01 5.85 1494.00 37.58 32.52 �������
System 7 20.00 50% 0.00 10.00 303.03 100.00 19.88 1.53 71.58 0.00 55.25 2.01 5.85 0.00 37.58 8.13 ������
System 8 20.00 50% 3600.00 10.00 303.03 100.00 19.88 1.53 71.58 2988.00 55.25 2.01 5.85 1494.00 37.58 8.13 �������
&DOFXODWLRQ�RI�H[WHUQDOLWLHVThe environmental models for each option were constructed using Pira International’s LCI/LCIA software PEMS.The life cycle inventory is then compiled. The environmental impacts associated with the inventory data set arethen calculated. To achieve this, the inventory data are characterised according to the potential impact categoriesthat they contribute to, and then multiplied by classification values. Finally, the impact assessment data ismultiplied by the economic valuations (as listed in annex 4) to achieve the external cost of each impact category
The external costs of each scenario are presented in the table below:
External costs: Glass refillables
External cost: Glass single trip
HeadingName 5HXVH�6\VWHP�� 5HXVH�6\VWHP�� 5HXVH�6\VWHP�� 5HXVH�6\VWHP��
GWP (kg CO2 eq.) 2.87 8.29 0.95 6.38Ozone depletion (kg CFC 11 eq.) 0.00 0.00 0.00 0.00Acidification (Acid equiv.) 0.24 0.58 0.09 0.43Toxicity Carcinogens (Cd equiv) 0.01 0.02 0.00 0.02Toxicity Gaseous (SO2 equiv.) 0.84 1.84 0.33 1.33Toxicity Metals non carcinogens (Pb equiv.) 1.45 1.60 0.34 0.50Toxicity Particulates & aerosols (PM10 equiv) 77.00 157.21 22.25 102.46Toxicity Smog (ethylene equiv.) 1.19 4.14 0.40 3.35Black smoke (kg dust eq.) 0.75 1.97 0.27 1.49Fertilisation -0.66 -2.13 -0.21 -1.68Traffic accidents (risk equiv.) 0.25 3.66 0.23 3.64Traffic Congestion (car km equiv.) 5.91 86.39 5.43 85.92Traffic Noise (car km equiv.) 0.40 5.91 0.37 5.88Water Quality Eutrophication (P equiv.) 0.05 0.17 0.02 0.14Disaminity (kg LF waste equiv.) 0.00 0.00 0.00 0.00
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GWP (kg CO2 eq.) 15.98 18.39 9.87 12.29Ozone depletion (kg CFC 11 eq.) 0.00 0.00 0.00 0.00Acidification (Acid equiv.) 2.03 2.18 1.14 1.29Toxicity Carcinogens (Cd equiv) 0.03 0.04 0.03 0.03Toxicity Gaseous (SO2 equiv.) 10.16 10.61 5.12 5.57Toxicity Metals non carcinogens (Pb equiv.) 3.26 3.33 3.14 3.21Toxicity Particulates & aerosols (PM10 equiv) 209.88 245.62 187.86 223.60Toxicity Smog (ethylene equiv.) 5.52 6.84 4.39 5.71Black smoke (kg dust eq.) 6.59 7.13 4.22 4.77Fertilisation -3.14 -3.79 -2.39 -3.04Traffic accidents (risk equiv.) 0.21 1.72 0.27 1.78Traffic Congestion (car km equiv.) 7.88 43.75 9.31 45.17Traffic Noise (car km equiv.) 0.23 2.68 0.33 2.78Water Quality Eutrophication (P equiv.) 0.42 0.47 0.36 0.41Disaminity (kg LF waste equiv.) 6.14 6.14 1.06 1.06
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5HVXOWV�RI�WKH�FRVW�EHQHILW�DQDO\VLVThe results of analysis are presented in the three graphs below. The graphs present the internal costs and externalcosts and total social costs (i.e. the sum of the internal and external costs) for each scenario as a function ofdistance to market.
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Internal costs - returnables versus single trip (assuming 100% return rate)
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400.00
500.00
600.00
700.00
800.00
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Distance to market (km)
returnables (5reuses)
returnables (20reuses
single trip (42%recycling)
"single trip (91%recycling)
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500.000
600.000
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returnables (20reuses
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single trip (91%recycling)
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returnables (20 reuses
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,QLWLDO�FRQFOXVLRQV�From an internal cost perspective:♦ Refillables are preferable to single trip bottles up until approximately 100km♦ Above approximately 150km, single trip bottles are preferable♦ Between 100 and 150km, the preferred option is dependent on the number of reuses achieved by the refillables
and the recycling rate achieved for the single trip bottles
From an external cost perspective:♦ Refillables are preferable to single trip bottles up until approximately 2400km♦ Above 4200km, single trip bottles are preferable♦ Between 2400 and 42000km, the preferred option is dependent on the number of reuses achieved by the
refillables and the recycling rate achieved for the single trip bottles
From a total social cost perspective:♦ Refillables are preferable to single trip bottles up until approximately 175km♦ Above approximately 280km, single trip bottles are preferable♦ Between 175 and 280km, the preferred option is dependent on the number of reuses achieved by the refillables
and the recycling rate achieved for the single trip bottles
6XPPDU\�RI�VHQVLWLYLW\�DQDO\VLV�UHVXOWVThe results achieved and conclusions drawn are sensitive to the economic valuations applied and to the internalcosts applied.
The distances over which the refillable bottles are a preferred option are sensitive to the return rate assumed. At areturn rate of less than 50% the refillables are no longer preferable from a total social cost perspective for anydistance.