Master Thesis
Environmental
performance of European
waste management
Focus on global warming
Author: Julie Clavreul
Supervisor: Thomas H. Christensen
July 2009
Environmental performance of European waste management
Preface
This Master Thesis concludes my Master in Environmental Engineering at DTU (Technical University
of Denmark). The work has been carried out at the Department of Environmental Engineering of DTU
between February and July 2009 and accounts for 30 ECTS credits.
First of all, I would like to thank my supervisor Thomas Højlund Christensen for his guidance, his very
pertinent advices and his constant support all along this Master Thesis. I also would like to thank him
for the opportunity to work on a scientific paper related to this topic, which was a rewarding
experience.
Secondly, I am very grateful to 3R manager and PhD fellow Emmanuel Gentil for his very useful
advices and feedbacks on my work, but also for extending my reflection on multiple related subjects.
I would also like to thank him for a both captivating and pleasant joint work on the scientific article.
Finally, my thanks and appreciation go naturally to DTU Environment and especially to the PhD
fellows of the Residual Resource group, who shared with me their helpful understanding of waste
management in various parts of my project.
Kgs Lyngby, July 2009,
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Abstract
The European Union has introduced several directives aiming at developing more sustainable waste
managements in its member states (MS). In particular the waste framework directive defines the
priority that MS should give to different waste strategies (waste hierarchy). In spite of these common
directives, a broad range of practices is still observable, between MS still relying mostly on the
traditional use of landfills and others with more complex waste management systems (WMS), that
include biological treatment and material and energy recovery.
The objective of this study is to assess environmental impacts of the management of one tonne of
municipal solid waste (MSW) in different MS. A life-cycle approach is undertaken using the EDIP97
methodology. The impacts on global warming are examined in details, followed by assessments of
other non-toxic impact categories (stratospheric ozone depletion, acidification, nutrient enrichment,
photochemical ozone formation) and toxic ones (ecotoxicity in soil and water, human toxicity in air,
soil and water and stored ecotoxicity in soil and water). The modelling and calculations are
performed using the life cycle assessment model EASEWASTE, developed for waste management at
the Technical University of Denmark (DTU).
The study is limited to six countries, chosen to get a good overview of waste management practices
in Europe. Germany (DE) is characterized by a high recycling rate and large use of incineration and
mechanical biological treatment (MBT), due to a ban on the landfilling of organic waste. Having also
implemented this kind of ban, Denmark (DK) relies highly on the use of high performance
incinerators and has a good recycling rate. The United Kingdom (UK) has almost the same recycling
rate as DK but its treatment of residual waste is highly relying on the use of high performance
landfills. France (FR) is characterized by an almost equal distribution between material recovery
(recycling and composting), incineration and landfilling. Still mostly based on landfilling, waste
managements in Greece (GR) and Poland (PL) present different recycling rates. For all countries,
three different assumptions were implemented for energy systems (electricity and heat): one based
on average country mixes and two based on marginal productions from natural gas and hard coal.
The results in all impact categories show high variability between WMS. Concerning global warming,
greenhouse gas (GHG) emissions range from -401 kg CO2-eq / tonne MSW (Normalized: -46 mPE) for
Germany to 90 kg CO2-eq / tonne MSW (11 mPE) for Greece, with energy system assumed to be
average country mixes. Thus the different choices in WMS lead to both high benefits and loads on
global warming. Recycling gives high benefits to all WMS, especially for paper and aluminium. The
benefits from incineration depend highly on the energy recovery efficiency of the incinerator: DK
always obtains high benefits, whereas France and Germany, which have lower energy recoveries,
present mainly environmental loads and only get a small benefit with the energy system assumption
of hard coal. In the same way, the UK is the only MS getting benefits from landfills, because these
were modelled with high gas collection, utilization and oxidation rates. With lower rates, FR, GR and
PL get high direct emissions of methane, leading to high impacts on global warming. The energy
recovery at landfills has also an influence but minor compared to the landfill gas collection. MBT
gives high benefits to both DE and PL, because of the high amounts of recovered energy from the
refuse derived fuel (RDF) they produce. In reality, quality criteria will determine if the RDF can be
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combusted in a power plant and thus directly substitute hard coal, as modelled in this study.
Transport has only a minor impact compared to the other processes.
The assessments of the other impact categories show similar results due to the correlation between
most impact categories and energy. Thanks to material (especially aluminium) and energy recoveries,
all WMS present benefits for acidification, nutrient enrichment, human toxicity in soil and chronic
ecotoxicity in water. Loads for human toxicity in water are observed and due to the mercury
contained in waste and released by incineration or use on land. Besides, all WMS present loads
concerning stored ecotoxicity, which assesses the potential hazard of metals remaining in landfills
after 100 years.
Finally, the study shows the influence of external and internal parameters on environmental
performances of WMS. Among the external ones, the most influent is the energy system assumption.
It determines the benefits from energy recovery and is thus primary for the incineration’s
performances. Waste composition has also an influence on the results, especially in terms of
methane potential (for direct methane emissions at landfills), of LHV (for energy recovery when
combusted) and of heavy metal content (for all toxic impacts). Yet in most of the cases, the waste
industry can decide on internal parameters which have large influences on environmental
performances. The study shows that the landfill gas collection rate and the energy recovery at
incinerator are particularly important.
In general, the study shows that the waste hierarchy is valid, as the countries recycling the most
obtain the highest benefits in almost all impact categories and the ones using landfilling for residual
waste treatment get the lowest ones. Yet the choice between material and energy recovery is not
very clear, as the ranking depends highly on the energy system assumption. Thus the study shows
that the waste hierarchy should be considered as a general and flexible ranking of waste
management options, and that policymaking should rely more on life cycle analysis, which enables to
take lots of internal and external parameters into consideration and to build the most accurate
picture of waste management systems.
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Glossary
AC: acidification
BMW: biodegradable municipal waste
CFC: chlorofluorocarbons
CO2: carbon dioxide
DE: Germany
DK: Denmark
EASEWASTE: environmental assessment of solid waste systems and technologies
EC: European Council
EDIP: environmental Design of Industrial Products
EU (or EU-27): European Union. It includes the following countries:
-
EU-15 (entered the EU before 1st May 2004): Austria, Belgium, Denmark, Finland, France,
Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden and the
United Kingdom
-
EU-12: Bulgaria, Czech Republic, Cyprus, Estonia, Hungary, Latvia, Lithuania, Malta, Poland,
Romania, Slovenia and the Slovak Republic.
ET: ecotoxicity (in soil: ETs and water: ETwc)
FOD: first order decay
FR: France
GR: Greece
GHG: greenhouse gas
GW: global warming
GWF: global warming factor (explained in beginning of section V)
GWP: global warming potential
HT: human toxicity (in air: HTa, soil: HTs, water: HTw)
IPCC: International Panel on Climate Change
ISO: International organization for standardization
LCA: life cycle assessment
LCI: life cycle inventory
LCIA: life cycle impact assessment
LHV: lower heating value
MBP: mechanical Biological Pretreatment
MBS: mechanical Biological Stabilisation
MBT: mechanical Biological Treatment
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MS: member state
MSW: municipal solid waste
NE: nutrient enrichment
NMVOC: non-methane volatile organic compounds
NOx: nitrogen oxide
OD: ozone depletion
PAH: polycyclic aromatic hydrocarbons
PE: person equivalent (mPE: 10-3 person equivalent))
PL: Poland
POF: photochemical ozone formation
RDF: refuse derived fuels
SE: stored ecotoxicity (in soil: SEs and water: SEw)
SNCR: selective non catalytic reduction
SO2: sulphur dioxide
TS: total solids
UK: United Kingdom
UNFCCC: United Nations Framework Convention on Climate Change
VS: volatile solids
WC: water content
WEEE: waste electrical and electronic equipment
WMS: waste management system
WW: wet waste
WWTP: waste water treatment plant
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Table of Content
PREFACE.............................................................................................................................................................. 2
ABSTRACT........................................................................................................................................................... 3
GLOSSARY........................................................................................................................................................... 5
TABLE OF CONTENT........................................................................................................................................ 7
PART I -
INTRODUCTION........................................................................................................................... 9
PART II -
BACKGROUND ........................................................................................................................10
II.1.
MANAGEMENT OF MUNICIPAL SOLID WASTE .........................................................................................10
Importance of waste management .................................................................................................................10
The challenge of municipal solid waste (MSW) ............................................................................................11
MSW amounts in the EU ...............................................................................................................................11
EU directives on management of municipal waste........................................................................................12
Effects of the EU policy: management of MSW in member states.................................................................13
II.2.
LIFE CYCLE ASSESSMENT ......................................................................................................................16
Introduction to LCA ......................................................................................................................................16
LCIA with the EDIP method..........................................................................................................................16
II.3.
LCA IN WASTE MANAGEMENT ..............................................................................................................18
Introduction...................................................................................................................................................18
The EASEWASTE modelling tool ..................................................................................................................19
II.4.
FOCUS ON GLOBAL WARMING................................................................................................................19
PART III -
GOAL AND SCOPE DEFINITION.........................................................................................20
III.1. GOAL.....................................................................................................................................................20
III.2. SCOPE....................................................................................................................................................20
Functional unit ..............................................................................................................................................20
System boundaries and assumptions .............................................................................................................21
Time scale......................................................................................................................................................22
Technological scope ......................................................................................................................................22
PART IV -
MODELLING ASSUMPTIONS ..............................................................................................24
IV.1. CHOICE OF COUNTRIES ..........................................................................................................................24
IV.2. WASTE COMPOSITION ............................................................................................................................25
Distribution in waste fractions ......................................................................................................................25
Composition of waste fractions .....................................................................................................................27
IV.3. ENERGY SYSTEMS .................................................................................................................................28
Marginal or average productions? ...............................................................................................................28
Data for average country mixes ....................................................................................................................28
Data for marginal energy productions..........................................................................................................29
IV.4. WASTE MANAGEMENT SYSTEMS ...........................................................................................................30
Share between recycling, landfilling and incineration..................................................................................30
Sorting efficiencies for recycling...................................................................................................................30
Sorting efficiencies for composting ...............................................................................................................31
Handling of residues (after source separation of recyclables)......................................................................32
Generic mass flows of waste management systems .......................................................................................32
IV.5. WASTE MANAGEMENT TECHNOLOGIES..................................................................................................34
Incineration ...................................................................................................................................................34
Landfill ..........................................................................................................................................................35
Mechanical biological treatment (MBT) .......................................................................................................38
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Composting ...................................................................................................................................................39
Recycling .......................................................................................................................................................40
Collection and Transport ..............................................................................................................................41
IV.6. DATA QUALITY ANALYSIS .....................................................................................................................41
Data uncertainty............................................................................................................................................41
Modelling limitations ....................................................................................................................................42
PART V -
RESULTS .......................................................................................................................................43
V.1.
IMPACTS ON GLOBAL WARMING ...........................................................................................................43
GWF based on average country mixes for energy production ......................................................................43
GWF based on marginal energy production .................................................................................................45
V.2.
SENSITIVITY ANALYSES FOR GLOBAL WARMING FACTORS...................................................................48
Key parameters for incineration ...................................................................................................................48
Key parameters for landfill ...........................................................................................................................49
MBT...............................................................................................................................................................53
Recycling processes.......................................................................................................................................54
V.3.
ALL IMPACT CATEGORIES ......................................................................................................................56
Non-toxic impact categories..........................................................................................................................56
Toxic impact categories.................................................................................................................................58
Sensitivity analysis: use of average country mixes for energy production ....................................................61
PART VI -
DISCUSSION .............................................................................................................................63
VI.1. TECHNOLOGIES’ PERFORMANCES ..........................................................................................................63
Incineration ...................................................................................................................................................63
Landfill ..........................................................................................................................................................64
Recycling .......................................................................................................................................................64
Composting ...................................................................................................................................................65
MBT...............................................................................................................................................................65
Transport.......................................................................................................................................................65
VI.2. PERFORMANCES OF EU COUNTRIES .......................................................................................................65
Internal versus external parameters..............................................................................................................65
How relevant is the waste hierarchy in the studied WMS? ...........................................................................67
Profiles of the countries and recommendations ............................................................................................68
VI.3. DO GWF GIVE A GOOD OVERVIEW OF SYSTEMS’ ENVIRONMENTAL PERFORMANCES?...........................69
PART VII -
CONCLUSION ..........................................................................................................................71
Take home messages .....................................................................................................................................71
Further work .................................................................................................................................................72
REFERENCES.....................................................................................................................................................73
APPENDIXES ......................................................................................................................................................77
APPENDIX 1: EASEWASTE MODEL ..................................................................................................................77
APPENDIX 2: LITERATURE RESEARCH ON WASTE COMPOSITIONS .......................................................................78
APPENDIX 3: MASS FLOWS OF THE SIX WASTE MANAGEMENT SYSTEMS .............................................................80
APPENDIX 4: PROCESSES USED IN THE EASEWASTE MODEL............................................................................83
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Part I -
Introduction
In the European Union (EU), approximately 250 million tonnes municipal solid waste (MSW) are
produced each year. Their management leads to both detrimental impacts on the environment and
beneficial ones when the resources they contain are well exploited. (EEA, 2009)
The management of MSW is now subject to many EU directives and has shown over the past few
years its ability to adapt to the increasing demands of society concerning environment. Yet, in spite
of common general rules, the 27 member states (MS) still present a large range of waste policy
implementations. For example they prioritize material or energy recovery.
This study aims at building waste management scenarios representing selected MS, in order to assess
and compare their impacts on the environment. The study uses the life cycle assessment (LCA) model
EASEWASTE, developed at the Department of Environmental Engineering of DTU (Lyngby, Denmark)
to assess the management systems in a life cycle assessment perspective.
A special focus on global warming is presented, due to the high concerns about possible
consequences of this impact. Indeed, the large quantities of greenhouse gases that have been and
that will keep on being released into the atmosphere are expected to cause a global rise of
temperatures, leading to a number of unwanted consequences on climate. Impacts on other nontoxic and toxic impact categories are also assessed.
In Section II, a general introduction to the management of MSW and to the method of life cycle
assessment is presented. The goal and scope of the study are formalized in Section III, while
modelling assumptions are described in details in Section IV. Results are presented in Section V and
discussed in Section VI.
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Part II II.1.
Background
Management of municipal solid waste
Importance of waste management
Following for several years the MS’ economic growth, the amount of waste generated in the EU has
significantly increased over the last decades. Today, each European citizen produces around 4 tonnes
of waste each year when taking into consideration wastes coming from all activities (EEA, 2009). This
means that approximately 2 billions tonnes of waste need to be handled each year (European
Commission, 2009).
The collection, transport and treatment of this large amount of waste generate substantial emissions
to air, water and soil and thus contribute to various impacts on the environment and human health.
For example, for global warming, reports to United Nations Framework Convention on Climate
Change (UNFCCC) place the management of post-consumer waste and waste water as the 4th largest
sector for anthropogenic GHG emissions in the EU-15, contributing to 2.6 % of total emissions. It
should be noted that these figures, reported every year to the UNFCCC by the European
environmental agency (EEA) include disposal on land, wastewater treatment and incineration
without energy recovery.
The sector has also shown significant improvements over the last decades, as these GHG emissions
have decreased by 39 % from 171 Tg CO2-eq in 1990 to 105 Tg CO2-eq in 2007(Kitou et al., 2009).
Figure 1 presents the change in EU-15 emissions of GHG by sector and gas between 1990 and 2003.
Negative changes on the figure indicate fewer GHG emissions and so improvements. The waste
sector appears to be the second best improvement, after the reduction of fugitive emissions. It has a
particularly major impact on emissions of methane, one of the six GHG included in the Kyoto
Protocol, as this substance is produced in large amounts at landfills.
Figure 1: Change in EU-15 emissions of greenhouse gases by sector and gas between 1990 and 2003 (EEA,
2005)
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These data collected by UNFCCC give an interesting view on the waste sector but not an entirely
representative one. First they only relate to post-consumer waste, meaning that emissions from
management of industrial or C&D wastes are accounted in the industrial sector. Secondly, they only
account for emissions from disposal on land and incineration without energy, while any emission
coming from installations also producing energy is counted as part of the energy sector. Last but not
least, the data reported to UNFCCC represent GHG emissions during one year, they include for
example emissions from landfilling that occurred decades ago.
Thus the scope of these reports is fundamentally different from the one of LCA studies, which
investigates the impacts of today’s management of a certain amount of waste. This will be explained
into more details in Section III.2.
The challenge of municipal solid waste (MSW)
MSW is the fourth largest waste stream: it accounts for around 12 % of total waste generated in
Europe. Indeed waste coming from the construction and demolition sector represents almost half of
the total quantity, and is followed by waste originating from manufacturing industries and mining
and quarrying.
However, in spite of this relatively small quantity compared to other sectors, the study of municipal
waste management appears very interesting for several reasons. First because of its complexity due
to its high heterogeneity and its different characteristics (e.g. methane potential, recyclable content
and hazardousness). The second reason is the quantity of available and robust statistical data,
compared to the other sectors.
MSW amounts in the EU
Today every European citizen throws away on average 520 kg of household waste per year, making
the total amount of municipal waste arising to approximately 250 million tonnes per year (EEA,
2009). This total European waste generation and trends can be observed as the upper line in Figure
2. The graph shows how amounts of generated waste have been constantly increasing for years and
how this tendency is not expected to change in the future. However, the figure also shows the part
of this waste being landfilled (the darker pink area). A sustained decrease in municipal waste
landfilling can be observed over the years, which suggests a better management of this waste. This
decrease, and especially the decrease in the landfilling of biodegradable municipal waste (BMW)
(white line on the figure), is partly the consequence of a number of policy decisions made by the
European Union over the last decades, as explained in the following paragraph.
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Figure 2: Historical and projected generation and landfilling of municipal waste in the EU-25 (EEA, 2007)
EU directives on management of municipal waste
The EU policy aims at developing more sustainable waste managements in its MS, including more
protection of the environment and a better use of resources. Its general goals can be summarized
into seven key principles:
-
Waste management hierarchy;
-
Self-sufficiency of the European Community and if possible of member states;
-
Best available technique not entailing excessive cost (BATNEEC): emissions from waste
treatment facilities should be reduced as much as economically possible;
-
Proximity principle;
-
Precautionary principle;
-
Producer responsibility;
-
Polluter pays principle. (European Commission, 2008)
The EU policy is constituted of the waste framework directive (WFD) and several specific directives
on particular waste streams.
Waste Framework Directive (WFD)
The WFD (Directive 2008/98/EC) aims at establishing a harmonized framework for waste
management over the EU. According to the WFD, a hierarchy in waste management is established
and requires that all MS encourage “in order of priority:
-
prevention or reduction of waste production and its harmfulness;
-
recovery of waste, including recycling, re-use or reclamation, or the use of waste as a source
of energy; and
-
as a final resort, safe disposal.“ (European Commission, 2008)
An other used version of the waste hierarchy is shown in Figure 3.
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Figure 3: Waste hierarchy
The WFD includes several obligations to MS in the planning of waste management systems,
regulations related to them and in the reporting to the Commission.
Landfill Directive
The Council Directive 99/31/EC, also called Landfill Directive, aims to prevent and reduce as far as
possible negative effects on the environment from landfilling of waste, in particular the pollution of
surface water, groundwater, soil and air, and on the global environment, including the greenhouse
effect, as well as any resulting risk to human health, from the landfilling of waste, during the whole
lifecycle of the landfill (European Council, 1999).
In particular, this directive requires the progressive diminution of the quantity of BMW being
landfilled in all MS. This aims at reducing the emissions of methane, a strong greenhouse gas, from
landfills. By 2006, the amount of landfilled waste should be less than 75 % of the total amount of
waste produced in 1995, in 2009 less than 50 % and in 2016 less than 35 %. The directive includes 4
year derogation for MS landfilling more than 80 % of their municipal waste in 1995 (e.g. Greece and
the UK).
Thematic strategy on the prevention and recycling of waste
This is one of the seven thematic strategies programmed by the 6th Environmental Action Plan for
the period 2002-2012. The general goal of this strategy is that Europe becomes a recycling society
with less waste and better use of waste as a resource. The thematic strategy includes notably an
obligation for all MS to develop national waste prevention programmes and the necessity of
focussing waste policies on improving the way resources are used. (European Commission, 2005c)
This need for an integrated approach of the use of resource in Europe, by applying life-cycle thinking,
is also highlighted in the thematic strategy on the sustainable use of natural resources. (European
Commission, 2005b)
Effects of the EU policy: management of MSW in member states
The results of the implementation of the EU policy are presented in Figure 4 (amounts of waste
recycled, incinerated and landfilled) and Figure 5 (Greenhouse gas emissions from MSW
management) together with projected trends.
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Figure 4: Generation and management of municipal waste in Europe per capita (EEA, 2008) 1
Figure 5: Trends and projections of greenhouse gas emissions from management of municipal waste in the
European Union (EEA, 2008)
It can be observed on Figure 4 that quantities of MSW to be managed are still expected to increase a
lot, in spite of the incentives towards more waste prevention and minimization. Yet, due to the
Landfill Directive, amounts of waste landfilled are expected to decrease in EU-27. The figure
concerning EU-121 shows that these MS might have difficulties to reduce this amount, even if the
relative share of landfilling is expected to decrease compared with incineration and recycling.
1
EU-15: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg,
Netherlands, Portugal, Spain, Sweden and the United Kingdom. EU-12: Bulgaria, Czech Republic,
Cyprus, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovenia and the Slovak
Republic.
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In general, material and energy recovery is increasing considerably. This enables high avoided
emissions of greenhouse gases, thanks to avoided virgin material production and substituted energy
production. These avoided emissions can be observed in Figure 5 as the difference between direct
and net emissions. This graph shows that, in spite of growing direct emissions due to larger amounts
of waste treated (yellow line), net emissions (orange line) are clearly decreasing, making
management of municipal waste in the EU a smaller contribution to GHG emissions.
As it is observed in Figure 4, MS are not at the same stage of implementation of EU Directives. To get
a more precise view of how each of them treats its MSW, Eurostat aggregates and publishes
statistical data on treatment of MSW annually. Data for 2007 are presented in Figure 6.
Very different profiles appear on this graph. The most obvious variation is the relative share of
landfilling, as it varies from 1 % (in Germany) to 100 % (in Romania and Bulgaria). This also shows the
different levels of development in waste management: when the countries’ policies move towards
reduction of landfilling (from the right to the left on the graph), the diversity of waste management
increases. A shift in technologies is observed tending towards waste management systems reducing
their impacts on the environment and generating more value from waste.
Figure 6 indicates that recycling seems to be the first alternative replacing landfill, as almost all MS
have implemented it. Composting and incineration are also well represented.
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Figure 6: Rates of landfilling, incineration, recycling and composting of MSW in EU-27 countries, 2007
(Eurostat, 2009)
There is a high variability in today’s management of MSW and it is expected to remain for some
years. However this figure does not show the high variability of the technologies and in their
environmental performances. For example, the environmental performances of landfills can vary a
lot from one facility to the other. To assess that, other statistical data should be looked for. This
combination of variations in system and process-specific parameters is at the base of this study.
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II.2.
Life cycle assessment
Introduction to LCA
As one of the many expressions of society’s increasing focus on environmental issues, life cycle
assessment (LCA) deals more particularly with the effects of one system (which can be either a
product or a service) on the environment. The goal of this approach, also called “from cradle to
grave”, consists in accounting all potential impacts that can be assigned to the system during all
stages of its “life cycle”: extraction of raw materials, production of the product, use and final
disposal, including transport. Results can be used for different purposes, e.g. the comparison of two
options or the optimization of a product.
LCA, which appeared in the 1980s, is now part of the ISO 14000 standards on environmental
management. In this study, the EDIP (Environmental Design of Industrial Products) methodology was
used. This method was developed under the EDIP program which was sponsored by the Danish EPA
and whose team included representatives of five major Danish industrial companies and of the DTU.
The methodology is described in detail in (Wenzel et al., 2001).
According to the ISO standard, LCA consists in four main phases (Hauschild et al., 2009):
-
Goal and scope definition, where the purpose of the study is explained, as well as the
questions it should answer. Then the scope definition should give a precise description of the
system(s) studied, the service(s) it provide(s), its boundaries and which impacts will be
studied.
-
Life cycle inventory (LCI), where all input data are collected, described and their quality
assessed. All processes’ in- and outputs are quantified, they can be for example energy, raw
materials or substances to the environment.
-
Life cycle impact assessment (LCIA) which consists in accounting all potential impacts on
selected impact categories. This is usually done in three steps: characterization (each
exchange with the environment is translated into a contribution to environmental impacts),
normalization (all contributions are put on a common scale making it possible to compare
with impacts of other products) and weighting (each impact category is given a relative
importance and all impact assessments can be summed up).
-
Interpretation where results are analyzed and discussed. Sensitivity and uncertainty analysis
can help to understand which parameters are the most crucial. The questions raised in the
goal and scope definition should be answered.
LCIA with the EDIP method
The life cycle impact assessment (LCIA) was conducted using the EDIP method. This is the Danish
midpoint method originally developed for product design and described in (Wenzel et al., 2001).
Impact categories used in this study are presented in Table 2.
Life cycle inventories (LCI) of all processes describe emissions of substances to different
compartments of the environment. Each emission of one substance to one compartment is
associated to an impact assessment factor for each impact category, corresponding to its potential
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contribution to that impact category. All characterization factors used in this study come from EDIP
1997. Finally for each impact category, the impact potential of the system is the sum of the impact
potentials of all emissions of the system.
The EDIP 97 impact assessment factors were used for all impact categories except for global
warming, for which the most recent IPCC set of values was used (IPCC, 2007). Global warming
potentials (GWP) of the key gas generated by the waste management industry are shown in Table 1.
Table 1: Examples of GWP (100 years) (IPCC, 2007)
GWP (g CO2 /
g substance)
Substance
Formula
Carbon Dioxide
Carbon Monoxide
Methane
CO2
CO
CH4
1
2
25
Nitrous oxide
N2O
298
Three emissions to soil were modified from the original EDIP97 LCIA methodology: the ones of iron,
aluminium and manganese which were put to zero. Indeed, it was considered that in the EDIP
method they are assessed in their most toxic form, while in reality it would rarely happen in a soil
environment.
When the contributions of the product to the impact categories are known (characterisation), it is
easier to interpret and compare them if they are put on a common scale. This is done in the
normalization step. The normalization factors used in this study are the ones from EDIP97 and are
shown in Table 2. They rely on the principle of the person-equivalent (PE): results of the system are
compared to the impacts of one person during one year. To obtain these factors, the total emissions
in a region over a year are divided by the number of inhabitants of the region. These personequivalents depend mainly on the geographical scale taken into account (because an average
European person and an average person in the world do not emit the same amounts) and on the
year of reference. For global impacts (i.e. global warming and ozone depletion), global emissions
were considered, whereas for regional impacts, European emissions per European citizen were used.
The reference year is 1994. (Hauschild, 2009)
Table 2: Normalization factors EDIP97 (Hauschild, 2009)
Impact category
Global Warming (GW)
Stratospheric Ozone Depletion (OD)
Acidification (AD)
Nutrient Enrichment (NE)
Photochemical Ozone Formation (POF)
Ecotoxicity in soil (ETs)
Ecotoxicity in water, chronic (ETwc)
Human Toxicity in Air (HTa)
Human Toxicity in soil (HTs)
Human Toxicity in water (HTw)
Stored Ecotoxicity in soil (SEs)
Stored Ecotoxicity in water (SEw)
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Factor
Unit
8700 Kg CO2-eq / pers / year
0.103 Kg CFC11-eq / pers / year
74 Kg SO2-eq / pers / year
119
25
9.64 105
3.52 105
6.09 1010
127
5 104
506
1.14 107
Kg NO3- -eq / pers / year
Kg C2H4-eq / pers / year
m3 soil / pers / year
m3 water / pers / year
m3 air / pers / year
m3 soil / pers / year
m3 water / pers / year
m3 soil / pers / year
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It can be noted that two impact categories were added to the usual ones of the EDIP method: stored
ecotoxicities in soil and water. They were introduced to quantify the impacts of long-term emissions
of toxic metals or highly persistent organic compounds from landfills that can occur over thousands
of years. The quantities of these hazardous compounds that remain in the landfill after 100 years are
calculated and each compound is given the same assessment factors as for “normal” ecotoxicity.
Normalization factors are based on Danish figures. (Hauschild et al., 2008)
In this study, no weighting was performed. Weighting consists in giving each impact category a
weighting factor representing the wishes of stakeholders involved in the study. Actually, when
proceeding to weighting, some uncertainty is added and the results are less transparent so it was
decided to use only normalized values, to reduce inherent uncertainty.
II.3.
LCA in waste management
Introduction
Taking advantage of a well-established use of LCA in industrial production, waste management
industries have understood how useful this tool could become for them. Indeed the complexity of
waste management systems has considerably increased, with growing numbers of treatment options
and several different waste streams. Moreover society’s expectations towards less negative impacts
on the environment and on human health, and better use of resources brought the need for a
relevant methodology to account them.
Life cycle perspective enables the quantification of the environmental impacts related to various
waste management options. It gives comprehensive and detailed information to decision makers and
helps them to identify priorities, see the environmental issues at stake and find the solutions giving
the maximum benefits to the environment. This need for life cycle considerations in waste
management was outlined by the European Commission’s Thematic Strategy on the prevention and
recycling of waste. (European Commission, 2005a)
From a practical perspective, the point of view taken in LCA of waste management system is different
from the one used in product LCAs, as shown on Figure 7. While the product LCA considers impacts
occurring during the four stages of a product’s life cycle (raw material extraction, production, use and
disposal), LCA of waste management focuses only on the final management. In most cases, the
impacts of upstream processes (e.g. manufacturing and use of products before they become waste)
are not accounted, as the objective is often to compare two waste management options. This is
called the “zero burden approach”: waste entering the system is not given any credit or burden. For
example, the energy used to produce plastic is not accounted for in waste LCA, although its
incineration might give credits to the system. This should be kept in mind carefully when looking at
the results of any LCA on waste management. Indeed waste management systems present often high
credits, so that one could think that the more waste is produced, the higher the benefits for the
environment. In fact, if upstream impacts of products before they become waste were accounted, no
credit would be observed: the best option is still to produce less waste.
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Environmental performance of European waste management
Figure 7: Boundaries of life cycle inventory of products versus waste management (Hauschild et al., 2009)
The EASEWASTE modelling tool
The life cycle screening is carried out with the use of the LCA waste model EASEWASTE. EASEWASTE
is a LCA model developed for waste management at DTU, in collaboration between the Solid waste
research group and the LCA research group. It stands for “Environmental Assessment of Solid Waste
Systems and Technologies”.
The model includes several process modules (e.g. incineration plant, landfill) that can be assembled
in scenarios. In these scenarios, waste is modelled from waste generation to final disposal and all
impacts can be assessed. In case of material or energy recovery, the system credits the resources and
the environmental impacts saved. EASEWASTE includes a number of default technologies in its
database but processes can also be built by the modeller. The model is shown in Appendix 1 and
described in details in (Kirkeby et al., 2005). More information is given in the manual available at
www.easewaste.dk.
II.4.
Focus on global warming
The increase of GHG concentrations in the atmosphere and the already observed global warming of
the Earth’s surface have raised concerns about GHG emissions from human activities.
In reaction to the scientific findings of the last decades, policy making is taking more and more these
emissions into consideration. The evidence is the agreement taken by lots of countries to reduce
their GHG emissions by signing the Kyoto protocol under the UNFCCC. The 15 member states of the
EU in 2002 signed this treaty and the EU agreed to reduce on average 8 % of its GHG emissions of
1990 in the period 2008-2012.
In this context, all industry sectors are facing new requirements in terms of GHG emissions, and in
particular the waste industry. This is why it was decided to focus this study on the performances of
waste management systems towards global warming. Furthermore, the study of these impacts also
gives a good overview on the performances of waste management systems towards other
environmental impacts, especially for the ones related to energy and resource consumption.
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Environmental performance of European waste management
Part III - Goal and scope definition
III.1.
Goal
The goal of this study is to perform a comparative assessment of the environmental performances of
municipal waste management in different MS of the EU. The objective of the study is to build and
compare the environmental profiles of selected waste management systems (WMS) for 2007, based
on statistical data of these countries. The environmental performances towards both toxic and nontoxic impact categories will be assessed, focusing on the analysis of global warming.
The study will first consist in identifying key parameters that have impact on the WMS performances.
These parameters are of two kinds:
-
external to the waste management system e.g. energy system in the country and waste
compositions;
-
internal to the waste management system e.g. energy recoveries at the incineration plants
and gas collection rate at landfill.
The purpose is then to build scenarios representing the selected WMS, assess and compare them
from a life-cycle perspective taking into account all impacts on the environment from the collection
of waste to its final disposal. The analysis of the LCIA should give information both on the relative
environmental performances of the selected countries and on which parameters have the greatest
influence.
The results of this study should help in understanding the main differences between the
managements of municipal waste in the selected countries and their environmental performances.
They could be extrapolated to other MS. It is expected that these results point out which parameters
have the highest influence on these performances and if some external factors have major impacts
on the results. Finally, this could be used by decision-makers to get a holistic view of where to focus
their efforts and potential for improvement.
Finally, it should be carefully noted that the results of this study rely on many assumptions described
further and that they should not be extrapolated or used without paying special attention to these
assumptions.
III.2.
Scope
Functional unit
The functional unit considered here is the management of 1 tonne of collected municipal solid waste.
In the EU, MSW refers to “waste from households, as well as other waste, which because of its
nature or composition, is similar to waste from household” (European Council, 1999). Behind this
theoretical definition, many differences can be observed between all countries. In this study,
municipal waste was considered as all waste collected by municipalities. It can originate from
households, small commercial activities and offices. It includes mixed (or residual) waste as well as
separately collected materials coming both from drop-of containers, recycling stations or
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Environmental performance of European waste management
individually-collected. It includes packaging waste (glass, paper, cardboard, plastics and metals) and
organic waste (garden and kitchen waste) and excludes bulky waste. The waste composition varies
from country to country and will be described further in detail.
System boundaries and assumptions
The system boundaries include all operations from the collection of the municipal waste to its final
disposal; they are shown in Figure 8. Collection and transport are indicated by the arrows and
included in the study.
Figure 8: System boundaries
It can be observed that no materials recovery facility (MRF) was modelled in the WMS. Statistical
data were considered from a national point of view and residual waste directly routed to the
treatment facilities. In reality, MRF would have an impact, mainly due to electricity consumption. In
this study, all recycled quantities were considered as source-sorted to simplify the modelling. They
are directly transported to recycling facilities. In reality, recycling quantities come from various
sources, including outputs of MRFs and metal sorting after incineration.
Collection of the waste was assumed to be achieved solely by curbside collection, no individual
transport at drop-of containers or recycling stations was included.
Construction, maintenance and decommission of the waste treatment facilities were not taken into
account because of a lack of consistent data.
All used energies include production and distribution of the energy carrier.
Recycling was considered to be performed in a European market, implying two major assumptions:
the same recycling processes were taken for all countries and a default transport distance of 100
kilometres was assumed for all recyclables.
Concerning incineration, only the landfilling of incinerator bottom ashes was taken into account,
meaning that the handling of fly ashes and air pollution control residues were not considered. It is
not expected that fly ash landfilling have any significant impact because it is assumed to be deposited
in a salt mine.
Concerning landfills, carbon sequestration was taken into account. It means that the biogenic carbon
that has entered the landfill and not left it after 100 years, as CO2 or CH4, is counted as “sequestrated
carbon” and gives a credit to the system for global warming. It is actually considered that the
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Environmental performance of European waste management
anaerobic conditions of the landfill prevent this biogenic carbon from degrading completely and
releasing carbon dioxide into the atmosphere. The system is credited for this sequestrated carbon
with a characterization factor of -44/12 kg CO2-eq / kg C.
Time scale
The time scale related to the impacts is 100 years, indicating that all impacts occurring in the 100
years following the management of the waste are accounted. The impact assessment of the two
“Stored ecotoxicity” impact categories is an exception, as these assess impacts of potential emissions
of substances out of landfills after 100 years.
The other time scale important to mention is how long the results of the study should be considered
as valid. This depends mainly on the obsolescence of the technologies and more generally of the
changes in waste management. Considering that this study relies on today’s average technologies
and as improvements in waste management can be expected for 10 years from 2007.
Technological scope
As the aim of the study was to assess how one tonne of municipal waste is treated today, an attempt
was made to define and use technologies reflecting today’s implemented level of technology.
Concerning the emissions from landfills, it is important to clarify the method adopted in this study for
accounting them, as it is different from the methodology of the Intergovernmental Panel on Climate
Change (IPCC). To report yearly emissions from landfills, the IPCC guidelines suggest that first order
decay (FOD) equations are used to calculate the cumulative emissions of the landfilling of waste since
1950, during the reporting year. This is illustrated on Figure 9 where each year’s emissions are shown
in different colours and cumulated (IPCC, 2006). The emissions accounted by the IPCC methodology
for 2007 are represented by the blue rectangle.
The LCA methodology, used in this study, focuses on the impacts of the management of a certain
quantity of waste in 2007. These impacts are calculated and integrated for the following 100 years.
The emissions accounted by this methodology are represented by the area inside the red line in
Figure 9.
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Environmental performance of European waste management
Figure 9: Hypothetical emissions of landfill methane using first order decay equations. IPCC methodology to
account for emissions during 2007 is shown by the blue rectangle, while LCA methodology to account for
emissions from the landfilling of waste in 2007 is presented in red (generated from IPCC 2006 guidelines and
IPCC Spreadsheet for Estimating Methane emissions from Solid Waste Disposal Sites) (IPCC, 2006)
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Environmental performance of European waste management
Part IV - Modelling assumptions
All modelling assumptions are described in this section, beginning by the choice of the studied
countries, followed by a description of external factors (waste composition and energy systems), the
characteristics of each waste management system and of technologies.
The scenarios were modelled using statistical data from different sources (e.g. Eurostat, ISWA). It was
attempted to draw a fair representation of today’s waste management systems using state-of-the-art
technologies. Due to obvious difficulties in obtaining country averages for data, the model is
constituted of scenarios which are approximations of the selected countries based on available data.
They do not claim to be real pictures of the selected countries.
IV.1.
Choice of countries
Due to difficulties to present a detailed study of the whole EU-27, it was decided to limit the study to
a smaller but representative number of countries. Six countries of different profiles were chosen to
get a good overview of waste management practices in Europe.
Germany focuses its waste policy on separate collection, which gives to this country a very high
recycling rate (46 %). A specific ban on the landfilling of organic waste (with organic content higher
than 3 %) was introduced in the 1990s and results now in the lowest landfilling rate in the EU (less
than 1 %). As a consequence, two pre-treatment strategies have emerged: mechanical biological
treatment (MBT) and incineration.
Denmark, also with a specific ban on landfilling, has mainly focused its waste policy on incineration
of mixed municipal waste and high performance incinerators. The recycling rate is good (24 %).
The United Kingdom has almost the same recycling rate as Denmark (22 %) but has chosen for many
years to rely on the landfilling with high performances landfills, even if the country is changing this
policy, due to European directives.
France is characterized by an almost equal distribution between material recovery (recycling and
composting), incineration and landfilling. Besides, its average electricity production is mostly based
on nuclear power and thus emits very little carbon dioxide.
As shown in Figure 6, still a large number of member states are characterized by a high use of
landfills, such as Greece with its 83 % landfill rate. Further, Greek waste is characterized by a high
organic content, a factor that might have influence on the global warming performances of its waste
management system.
Poland has also a high landfilling rate but this country has introduced for some years the use of
mechanical biological treatment. The Polish recycling rate is the lowest of the six studied MS (6 %).
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Environmental performance of European waste management
IV.2.
Waste composition
The focus of this study is on the management of municipal solid waste which includes all waste
collected by municipalities: household waste (including garden waste) but also similar waste coming
from small businesses.
Distribution in waste fractions
Specific waste compositions for each of the six countries were researched upon in literature. Waste
compositions include six waste fractions: paper/cardboard, organic, plastics, glass, metals and others,
as these are the main data found in literature. Specific distributions inside these waste fractions are
described further. It should be noted that the definitions of municipal waste are different depending
on countries and sources, and are not well described for all sources.
A literature review was performed and a table summarizes the values found in Appendix 2. The
sources included:
-
The OECD data, which are regularly aggregated from national agencies and are the main
primary data used in studies. Reports by EUROSTAT are directly based on these sources;
-
Reports found in literature, including the IPCC guidelines for greenhouse gas inventories;
-
Databases: the ELCD database (by the European Commission – Joint Research Centre) which
comprises life cycle inventories of several systems and uses waste compositions; and the
EASEWASTE database developed by the Department of Environmental Engineering at DTU.
The waste compositions of the six countries used in this study were derived from these data. The
values, in bold, correspond to the averages data used taking into consideration the robustness of
each source and its consistency with the other sources.
The numbers show how data differ from one source to the other. The main difference is how waste is
defined: it is considered as municipal waste, household waste or even sometimes only separate
collection. Also the methods for sampling and analyzing the waste are not specified and can thus
produce very different results.
The chosen waste compositions are presented in Figure 10 and Table 3. The vertical error bars show
the maximal and minimal values presented in Appendix 2. Even if it was not specified in each study, it
was decided to consider that the organic fraction included garden waste.
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Environmental performance of European waste management
70
60
50
Denmark
40
France
30
Germany
Greece
20
Poland
UK
10
0
Glass
Metals
Organic
Other
Paper/
Cardboard
Plastics
Figure 10: MSW compositions (in %) used in this study with vertical error bars showing minimal and maximal
values found in the literature (den Boer et al., 2005; EASEWASTE, 2008; Eggleston et al., 2006; European
Commission Joint Research Centre, 2005; Eurostat, 2003; Fisher et al., 2006; Koneczny et al., 2007; OECD,
2007; Sander, 2008; Smith et al., 2001)
As garden waste often benefits from separate collection and treatment, it was decided to divide the
organic fraction into two sub-categories: kitchen and garden waste. Table 3 shows how this was
performed.
To calculate the fraction of garden waste separately collected, different sources were used for each
country. In Denmark, 18 % of collected municipal waste is garden waste (Danish Ministry of the
Environment, 2008) whereas in France and in Germany this is 10 % (ADEME, 2007; BMU, 2007). In
the UK, it was assumed that 12 % of collected waste was garden waste (Fisher et al., 2006).
Concerning Greece and Poland, it was considered that only garden waste was composted (meaning
that no kitchen waste was separately collected) (European Compost Network, 2009), so the fraction
of municipal waste being garden waste equals the fraction of municipal waste being composted
presented in the Eurostat statistics (See Figure 13): 2 % for Greece and 4 % for Poland.
These values concerned separately-collected garden waste. Then it was assumed that among the
remaining organic waste, 10 % was non-separately collected garden waste and 90 % was kitchen
waste.
Table 3: Waste compositions used in the study (%)
Country
Glass
Metals
Organic: Garden
Separ.
collected
Denmark
France
Germany
Greece
Poland
UK
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6
12
14
5
10
8
5
5
5
4
4
6
18
10
10
2
4
12
Residual
2
2
1
4
3
2
Organic:
Kitchen
19
19
13
41
28
15
Other
20
18
14
14
22
21
Paper/
Cardboard
Plastics
23
25
33
21
18
26
7
9
10
9
11
10
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Environmental performance of European waste management
As very few specific data were found concerning the distribution between ferrous and non-ferrous
metals for each country, it was decided to apply the same ratio for all countries. Values found in the
literature concerning the proportion of aluminium among “Metals” were ranging from 25 % to 35 %
(EASEWASTE, 2008; Fisher et al., 2006; Sander, 2008; Smith et al., 2001). Thus the ratio chosen here
was: 1/3 of metal is aluminium and 2/3 is ferrous material (Iron and steel).
Concerning the distribution between paper and cardboard, a common share ratio was chosen for all
countries: 50 % of cardboard, 50 % of paper.
Composition of waste fractions
Table 4 presents the characteristics of each fraction in terms of heating value, methane potential,
water content, volatile solid fraction and biological and fossil carbon content. The values were
extracted from the database of EASEWASTE by calculating the weighted averages for each waste
fraction. In this waste composition, the fraction “Other” contains 15 % textile, 1 % batteries, 67 %
miscellaneous combustibles and 17 % miscellaneous non-combustibles. The terms used to
characterize a waste composition (e.g. TS, VS) are explained in Figure 11. It should be noted that the
waste composition modelled does not include bulky waste.
Table 4: Composition of each waste fraction (EASEWASTE, 2008)
Heating
value
(GJ /
tonne
TS)
Lower
heating
value
(GJ/tonne
ww)
CH4 Pot.
3
(m CH4 /
tonne
VS )
Cardboard
Glass
Aluminium
Ferrous
metals
Organic:
Garden
Organic:
Kitchen
Other
16.92
0
9.28
13.63
0
8.03
0
Paper
Plastics
C
Biologi
cal (%
TS)
C
Fossil
(% TS)
9.82
100
72.69
42.41
0
6.42
2.05
0
13.20
0
100
0
0
52.20
76.83
23.17
43.06
0.78
70.42
29.58
94.20
5.80
49.02
0.45
32.92
18.51
81.49
79.01
20.99
23.40
26.93
158.11
0
9.51
10.89
90.49
89.11
80.77
95.27
19.23
4.73
38.67
0.40
0.19
79.32
H2O
(%)
TS
(%)
VS
(% TS)
154.81
0
0
19.43
6.89
13.51
80.57
93.11
86.49
90.18
0
27.31
0
0
10.60
89.40
14.31
7.47
114.60
47.80
19.57
5.79
435.66
21.20
17.27
14.25
38.21
12.89
34.05
Ash
(% TS)
Figure 11: Definition of terms used to characterize a waste composition
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Environmental performance of European waste management
IV.3.
Energy systems
Marginal or average productions?
The choice of the energy used in the systems (whether for consumption or substitution) is crucial, for
impact assessment of global warming but also for other impact categories. Two approaches can be
chosen for both electricity and heat productions: the use of average or marginal data. The first one
refers to an attributional approach where the purpose is to take a snapshot of a situation. On the
contrary, the second one takes a consequential approach: the consumption and production of energy
in the waste management system are considered as having a consequence on the energy system.
Thus, the challenge here is to determine which technology is consumed or substituted.
In this study, it was chosen to look at the results obtained with the two approaches: the average
mixes of each country and marginal energy productions, to understand the influence of this choice
on the results. The marginal energy sources used in the different countries are difficult to find
because they are regional and the ratio of sources of energy can change on a daily basis (Münster et
al., 2009). Thus it was decided to study two types of marginal electricity and heat productions: from
hard coal and from natural gas, as it was considered that the actual marginal energy production in
the six countries would be a mix of these two in different ratios.
Data for average country mixes
The average productions of electricity and heat were adapted to each country. For the electricity
country mixes, processes from the Ecoinvent database were imported in EASEWASTE. The names of
the processes are presented in Appendix 4. The processes used describe the transmission of high
voltage electricity in 2004/05 and include transmission losses through the network (ecoinvent
Centre, 2007). Table 5 shows country mixes for electricity production in 2006, it can be assumed that
these are very close to the data used to build the Ecoinvent processes.
Concerning heat country mixes, data from the International Energy Agency (IEA) was used for the
share between the energy sources in 2006 (IEA, 2009). Table 6 presents the country mixes used for
heat production. Then, average heat production processes were calculated based on processes from
the Ecoinvent database (V2.0) (list of the Ecoinvent processes names in Appendix 4).
Table 5: Country mixes for electricity production in 2006 (IEA, 2009)
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Environmental performance of European waste management
Table 6: Country mixes for heat production in 2006 (IEA, 2009)
NB: Original data also included other sources which accounted for less than 0.5% or were not specified
Data for marginal energy productions
For electricity production, processes were also based on the Ecoinvent database. They correspond to
electricity outputs of average hard coal and natural gas power plants in year 2000. Names of the
Ecoinvent processes used are in Appendix 4.
Figure 12 shows the final GHG emissions of the electricity and heat mixes for each of the six countries
and for the two marginal energy productions. Contributions of carbon dioxide, methane and nitrous
oxide are also presented and it should be noted that only gases from fossil origin are presented. The
GWP used to characterize methane and nitrous oxides emissions are from IPCC (2007)(IPCC, 2007)
(See Table 1).
0.3
N2O
kg CO2-eq / MJ
CH4
CO2
0.2
0.1
0
DK
FR
DE
GR
PL
UK Gas Coal DK
Electricity production
FR
DE
GR
PL
UK Gas Coal
Heat production
Figure 12: GHG emissions from electricity and heat production: average country mixes and marginal
productions based on natural gas and hard coal (in kg CO2-eq/MJ)
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Environmental performance of European waste management
IV.4.
Waste management systems
Share between recycling, landfilling and incineration
General data about management of MSW were looked for in literature. Eurostat gives the amounts
of municipal waste going to the different treatment facilities (incineration, landfilling, recycling and
composting) in all EU countries in 2007. These data may not cover exactly the same kind of waste in
all countries but they were found the most reliable and complete ones for all studied countries. They
are presented in Figure 13.
These data constitute the base of the six scenarios as they are used for distributing MSW to the
different technologies.
2%
14%
18%
18%
4%
6%
15%
16%
12%
22%
24%
Compost.
46%
5%
34%
83%
Recycling
90%
57%
1%
Landfill
Incin.
53%
36%
Denmark
France
35%
Germany
0%
0%
Greece
Poland
9%
UK
Figure 13 : Management of municipal waste in 2007 (Eurostat, 2009)
Sorting efficiencies for recycling
In this study, recycling and composting are modelled using exclusively source sorting of the materials,
these materials being then transported to recycling and composting facilities. This is a simplification
as everything is considered to be sorted at source and no MRF is modelled. In reality, recyclables are
also collected in other ways than separate collection: they can be for example sorted out in a MRF, in
a MBT or after incineration, in the case of metals.
Sorting efficiencies were calculated for each material fraction based on general recycling and
composting rates given by Eurostat (Figure 13) and according to the chosen waste compositions
(Table 3).
To distribute the recycling rates among the four categories of recyclables (glass, metals,
paper/cardboard and plastics), specific data for each country were looked for but none were
considered consistent enough to be used in this study. Instead of this, it was decided to apply the
same relative recycling contributions to all countries: of the total quantity of collected recyclables,
59 % is paper/cardboard, 17 % glass, 12 % metals and 12 % plastics. These values were adapted from
(Skovgaard et al., 2008).
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Sorting efficiencies were then used in the LCA model to evaluate each material recycling. They were
calculated using the two following equations (here explained for the glass fraction):
QRecyled_Glass = Recycling_rate*Relative_recycling Glass*Qtotal
QRecycled_Glass = Sorting_eff Glass*QGlass = Sorting_eff Glass*Glass_fraction*Qtotal
Where - QRecycled_Glass is the quantity of glass that is recycled (in kg),
- Recycling_rate is the percentage of MSW that is recycled (Figure 13) (in %),
- Relative_recycling Glass is the relative recycling contribution of Glass compared to the other
recyclables (in %),
- QTotal is the total quantity of waste (in kg),
- Sorting_eff Glass is the percentage of organic waste going to the composting plant (in %),
- Glass_fraction is the fraction of glass in municipal waste (in %).
Thus: Sorting_eff Glass =
Recycling_rate*Relative_recycling Glass
Glass_fraction
Final sorting efficiencies used in this study are shown in Table 7.
Table 7: Sorting efficiencies of Glass, Metals, Paper/Cardboard and Plastics (%)
Glass
Denmark
France
Germany*
Greece
Poland
UK
68
23
56
51
10
47
Metal
Paper/
Cardboard
58
38
100
45
18
44
62
38
82
42
20
50
Plastic
41
21
55
20
7
26
*: The sorting efficiency of metal in Germany was found rising up to 110 %. This is due to the very high recycling rate in this
country. Yet, it was chosen to keep the methodology used as it seemed to be the most realistic one, and to put this sorting
efficiency to 100 %.
Sorting efficiencies for composting
For composting, the method is similar. It was assumed that the composting rate given by Eurostat
concern primarily garden waste and partly kitchen waste. For France and Germany, as the
composting rate exceeds the separately-collected garden waste fraction, a fraction of the kitchen
waste was considered to be source-sorted and transported to composting facilities, the same
formula as above was used to calculate sorting efficiencies of kitchen waste. Also the use of
anaerobic digestion was considered too marginal to be modelled in this study.
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Table 8: Separate collection of garden and kitchen waste
Waste composition (%)
Garden waste
Sep.
Denmark
France
Germany
Greece
Poland
UK
18
10
10
2
4
12
Nonsep.
2
2
1
4
3
2
Kitchen
waste
19
19
13
41
28
15
Sorting efficiency (%)
Composting
rate (%)
Garden
waste
18
14
18
2
4
12
Kitchen
waste
90
83
91
33
57
86
0
21
62
0
0
0
Handling of residues (after source separation of recyclables)
After separate collection of recyclables and compostables, the residues have to be treated. The data
given by Eurostat concerning the relative share of incineration and landfilling (Figure 13) were used,
but two more information were added:
•
Denmark and Germany have introduced special legislation about authorized waste into landfills.
In Denmark, the landfilling of waste that can be incinerated was banned in 1997 (EIONET, 2007a),
while in Germany, organic-containing waste was banned from landfills in 2005 (EIONET, 2007b).
Thus, in this study, no biodegradable waste is modelled to landfills of these two countries.
•
The use of mechanical biological treatment (MBT) of municipal waste is particularly important in
two of the six studied countries and was thus modelled, even if data from Eurostat did not
specify the use of MBT. In Germany, the capacity reached 7.1 million tonnes treated in MBT per
year in 2007 (BMU, 2009), equivalent to 13 % of total municipal solid waste or 38 % of total
residual waste (after source-collection of recyclables), adapted from (Eurostat, 2009). In Poland:
the total amount of MSW being treated in MBT is estimated to be 10 % of total municipal waste
(Steiner, 2005). Although the number of MBT plants might increase in the other countries in the
next years, the current quantities being treated were estimated as too marginal to be modelled.
(Steiner, 2005).
Generic mass flows of waste management systems
Figure 14 shows the generic model of the mass flows in the six waste management systems. The
values of waste compositions (C), sorting efficiencies (S), share of residual treatment facilities (M)
and quantities in final treatment (F) are described in Table 9. Specific mass flows for each MS are
presented in more details in Appendix 3.
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Figure 14: Generic model of the waste management systems
Table 9: Input data with mass flows
Label
DK
FR
DE
GR
Waste composition (% of MSW)
Glass
C3
6
12
14
5
Metal
C4
5
5
5
4
Organic: Sep
18
10
10
2
C2
Garden
Non-sep
2
2
1
4
Organic: Kitchen w.
C1
19
19
13
41
Others
C0
20
18
14
14
Paper
C5
23
25
33
21
Plastics
C6
7
9
10
9
Sorting efficiencies (%)
Glass
S3
68
23
56
51
Metal
S4
58
38
100
45
Paper
S5
62
38
82
42
Plastics
S6
41
21
55
20
Organic: Garden
S2
90
83
91
33
Organic: Kitchen
S1
21
62
Management of residues (%)
Landfill
M1
9
49
100
Incineration
M2
91
51
62
MBP
M3
29
MBS
M4
9
Quantities in final treatment (for 1000 kg entering the system)
Landfill
F1
52
343
831
Incineration
F2
526
356
227
MBT
F3
107
MBS
F4
32
Composting
F5
180
140
180
20
Recycling(Glass)
F6
41
28
78
25
Recycling(Metal)
F7
29
19
50
18
Recycling(Pap/Card)
F8
143
95
271
88
Recycling(Plastic)
F9
29
19
55
18
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UK
Sources
10
4
4
3
28
22
18
11
8
6
12
2
15
21
26
10
Own estimations
based on several
sources
10
18
20
7
57
-
47
44
50
26
86
-
Own estimations
based on Eurostat
data, waste
compositions and
waste management
89
8
3
86
14
-
800
76
23
40
10
7
36
8
568
92
120
38
26
130
26
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Environmental performance of European waste management
IV.5.
Waste management technologies
The names of all processes used in the model are listed in Appendix 4.
Incineration
Incineration process, flue gas cleaning and handling of residues
In this study, all incineration plants were modelled with the same generic process, the energy
recovery being the only country-specific parameter. The generic process used in all scenarios is based
on publicly available data from the incineration plant of Aarhus in 2006. This grate incineration
technology is combined with mixed flue gas cleaning: two lines with semi-dry and one with wet flue
gas cleaning. Nitrogen oxides are removed by SNCR (Selective Non Catalytic Reduction) while dioxins
and mercury are removed with activated carbon. All lines are combined with heat and electricity
productions with efficiencies described in the next chapter.
Bottom ashes, which represent more than 10 % of the input weight, are sent to a mineral waste
landfill. As this waste is inorganic, no methane is produced and only effects from operational
activities and leaching (e.g. of metals) are expected. The other residues (APC residues, fly ash) are not
treated further. Fly ash is assumed to have no significant impact because it is disposed of in deep salt
mines.
Energy recovery
It was decided to adapt the energy recovery to each country’s situation. Indeed several studies
showed that this parameter was of primary importance due to a high share of fossil energies in
today’s European energy mixes (Fisher et al., 2006; Smith et al., 2001).
The main source of information found on this topic was the State-of-the-art report by ISWA (2006)
listing all MSW incineration plants with a capacity of more than 15 tonnes/day or 10,000
tonnes/year. For each plant, information concerning amounts incinerated, flue gas cleaning, residues
and amounts of energy produced and sold are given. Yet data are incomplete for some countries
(e.g. France and the UK) and should thus be considered with care. However, as these are the most
consistent and complete country-specific data found, they were used here to model the energy
recovery at incinerators in each country.
Table 10 presents the average quantities of electricity and heat sold per tonne of waste in 2004 in all
incineration plants with a capacity of more than 15 tonnes/day or 10,000 tonnes/year (ISWA, 2006).
Then, to calculate the average energy recovery for each country, the average LHV of the waste input
in all incinerators producing energy was calculated (based on the available data). The LHV is only
used to calculate the energy recovery and is different from the one used for the modelling of this
study. Finally the energy recovery was obtained by dividing the total electricity and heat recovered
by the average LHV of the input waste.
The data should be taken with care as they are incomplete for several countries (e.g. France and UK).
Furthermore, it appears that concerning a large part of incinerators, municipal waste was coincinerated with other waste such as industrial waste for example, and sometimes other fuels are
input and may thus contribute to the energy recovery. Yet as the information about these coJulie Clavreul
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Environmental performance of European waste management
incineration is almost non-existent, it was decided to consider that the quantities incinerated had
similar LHV to the ones of municipal waste.
Here the sold energy was considered, and not the produced one. Indeed it was considered that if
energy was produced but not sold, no energy production was substituted. It is the same if energy is
produced and utilized at the incineration plant. Thus, to stay consistent with this assumption, no
energy inputs to the incinerators were modelled.
Finally, it should be noted that these data were collected for 2004 so technologies may have been
improved since then.
Table 10: Energy sold by incineration plants in 2004 (ISWA, 2006)
Country
Sold Electricity
Denmark
France*
Germany
Greece
Poland
UK*
MWh /
tonne
0.39
0.13
0.26
0
0
0.5
GJ /
tonne
1.40
0.47
0.94
0
0
1.80
Sold Heat
MWh /
tonne
2.05
0.57
0.55
0
0
0.06
GJ /
tonne
7.38
2.05
1.98
0
0
0.22
Average LHV of
input waste of the
incinerators
producing energy
GJ / tonne
10.7
8.7
9.7
9.0
Energy recoveries
(sold energy)
Electricity
13.1 %
5.4 %
9.6 %
0%
0%
20.0 %
Heat
69.0 %
23.6 %
20.4 %
0%
0%
2.4 %
NB: Original data concerning UK were for Great Britain. Greece and Poland do not have incineration.
*: incomplete data
Landfill
The same landfill was used in all countries, where three parameters were adapted to the countries:
the gas collection, utilization and oxidation rates. As explained before, in this study, no
biodegradable waste is sent to landfills of Denmark and Germany.
Description of the model
The process used models a conventional landfill including a bottom liner, leachate collection system,
a top soil cover and gas collection and utilization systems. General parameters are given in Table 11.
Leachate generation directly reflects the infiltration of rainwater. The collected leachate is sent to a
wastewater treatment plant, while the uncollected one reaches the below groundwater.
Landfill gas generation
Due to anaerobic conditions in conventional landfills, degradation of the organic content of MSW
leads to the generation of large quantities of methane. In the EASEWASTE model of landfills, this gas
generation is based on the methane potential of the landfilled waste and is distributed over four
time periods:
-
Period 1: [0-2], 1 % of the gas potential is generated. This is the operation period, when the
landfill is being filled;
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Environmental performance of European waste management
-
Period 2: [2-5], 4 % of the gas potential is generated;
-
Period 3: [5-45], 80 % of the gas potential is generated. This is the most active period.
-
Period 4: [45-100], 4 % of the gas potential is generated. During this period, the landfill is
usually not any more monitored.
Table 11: General parameters used in the landfill model
Parameter
Diesel consumption in truck
Electricity consumption
Landfill height
Methane removal at flare/electricity production
Efficiency of electricity production
Leachate generation, period [0-10] years
Leachate generation, period [10-100] years
Leachate collection, period [0-10] years
Leachate collection, period [10-45] years
Leachate collection, period [45-100] years
Value
2
8
20
97
35
450
300
95
90
80
Unit
L / tonne
kWh
m
%
%
mm / yr
mm / yr
%
%
%
Gas collection, utilization and oxidation rates
This landfill gas, whose GWP is 25 times higher than CO2, should be oxidized before reaching the
atmosphere in order to reduce the impact of landfill on global warming (IPCC, 2007). In the
EASEWASTE model of the conventional landfill, landfill gas is collected with a “gas collection rate”.
The collected gas is then combusted with energy recovery (in electricity or CHP generators) or
without (in flares). The proportion of collected gas being used to produce energy is called here the
gas utilization rate. In this study, only electricity production is considered. The uncollected gas passes
through the top cover, where depending on the available oxygen, a proportion of methane is
oxidized before being released into the atmosphere. The oxidation rate expresses the percentage of
uncollected gas being oxidized. Figure 15 gives a graphical overview of these terms.
Figure 15: The three key parameters of the conventional landfill
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The objective was to find sets of these three rates (gas collection, utilization and oxidation)
representing the most realistically the landfills in use today in the four countries. Results of the
impact assessment of the landfills will be very sensitive to the assumptions on these three
parameters (Fisher et al., 2006).
Specific data on methane recovery at landfills in current use are difficult to obtain. The first idea was
to use the methane emissions reported every year by each country to the UNFCCC; details about
amounts of emitted and recovered methane at landfills are given in these documents. But these data
appear to include all emissions currently happening from all landfills and thus include emissions from
old landfills, most of them being closed (Kitou et al., 2007; Olendrzynski et al., 2005). So as the scope
of this study is to assess the impacts of landfilling today one tonne of waste, only characteristics of
currently operational landfills should be considered, making it impossible to use these UNFCCC data.
The difference of scope with the IPCC methodology is also explained in Section III.2.
Thus, a literature review was conducted to see how other studies define these three rates. Values
are shown in Table 12.
Table 12: Literature review of gas collection, utilization and oxidation rates (values for 100 years periods)
Parameter
Value Comments
Source
Gas collection rate
75 %
(Fisher et al., 2006)
70 %
For UK
(Smith et al., 2001)
50 %
For DK, FR, DE, GR
(Smith et al., 2001)
20 %
Default value of IPCC guidelines of 2006 (Skovgaard et al., 2008)
Gas utilization rate
Gas oxidation rate
60 %
0%
10 %
10 %
10 %
40 80 %
While 30% is flared and 10% vented
Default IPCC value for managed and
unmanaged landfills
Default IPCC value for managed sites
covered with methane oxidizing material
(e.g. soil and compost)
Assumption based on IPCC default
values
Based on a study
Taking into account the link between
methane flow and oxidation rates: the
faster the methane leaves the landfill,
the smaller the oxidation rate
(Smith et al., 2001)
(Eggleston et al., 2006)
(Eggleston et al., 2006)
(Fisher et al., 2006)
(Smith et al., 2001)
(Manfredi et al., 2009)
Based on this small literature review, it was decided to build an average EU Directive-compliant
landfill with gas collection efficiency of 50 % (over 100 years) and utilization of collected gas for
electricity of 60 %. The oxidation of uncollected gases was assumed to be 25 %.
However, as the UK presents a high amount of high quality landfills with high gas collection and
utilization, it was chosen to model UK’s landfills with 70 % collection rate and 80 % utilization rate. As
the collection rate is higher, methane flows are supposed to be smaller and thus a 30 % oxidation
rate was set (Manfredi et al., 2009).
Gas collection rates were presented over a 100 year-period but in reality the collection is restricted
to approximately 43 years. Indeed, at the beginning, when the landfill is in operation, there is a
period (here estimated to 2 years) where gas cannot be practically collected, and after a certain time
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Environmental performance of European waste management
(here estimated to 43 years), methane flows have become so low that it is impractical to collect
them. The 43-year gas collection phase is supposed to enable the collection of the major part of the
generated gas. With the above description of gas generation distribution, when reducing the gas
collection period from 100 years to 43 years, the gas collection efficiency has to be increased by a
factor of 100/84. Table 13 shows all values used to model the gas collection, utilization and oxidation
at landfills in each country.
Table 13: Modelling of gas collection and utilization in landfills
Country
Denmark *
France
Germany *
Greece
Poland
UK
Gas
collection
(over 100
years)
0%
50 %
0%
50 %
50 %
70 %
Gas
collection
(between year
2 and 45) **
0%
60 %
0%
60 %
60 %
83 %
Collected gas
Electricity
production
60 %
60 %
60 %
80 %
Uncollected gas
Flaring
40 %
40 %
40 %
20 %
Oxidation rate
in top cover
25 %
25 %
25 %
30 %
*: as explained above, landfills of Denmark and Germany do not accept any organic waste
**: No collection in periods [0-2] and [45-100] (years).
Mechanical biological treatment (MBT)
Mechanical biological treatment is a technology that combines a biological treatment (composting or
anaerobic digestion) with a mechanical separation (sorting facility). It is mainly used in Germany,
Austria and Italy. There are two main reasons behind the decision of using an MBT: it can be to lower
the content of biodegradable compounds in the pre-treated waste before landfilling it, or to produce
refuse derived fuels (RDF) with high LHV and low content in heavy metals and harmful substances
and to produce energy from their combustion.
The most common MBT in Germany is the mechanical biological pretreatment (MBP) with 31 plants.
The main objective there is to pretreat MSW so that it fulfils legal requirements to enter landfills.
During the biological process, organic matter is degraded which will in particular minimize landfill gas
formation. In the other kinds of MBTs, the main goal is to produce RDFs. Recyclables and a minor
residual fraction are also produced.
In this study, two processes were used to model the use of MBT: mechanical biological pretreatment
(MBP) and stabilisation (MBS) with the respective share: 77 % and 23 %, adapted from (BMU, 2009).
The two models use composting as biological treatment. They were developed recently at the
Department of Environmental Engineering of DTU, based on data from two German facilities.
It should be noted that normally MBT plants sort important quantities of recyclables (mainly metals),
but in this study it was decided that the total amount of recyclables was sorted at source, for
practical modelling reasons. The amounts normally sorted out in MBT are thus included in this source
sorting.
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Both MBT processes use transfer coefficients for the mechanical sorting and VS degradation rates for
the composting process; these are specified for 48 waste fractions. Input and output data of the
whole MBT plants are described in Table 14.
The MBP plant is modelled as a MRF followed by a composting treatment, while the MBS is modelled
as a biological drying, where a high amount of water is evaporated, followed by a mechanical
separation. The quantity of RDF recovered at the end of the process is slightly higher for the MBS
(55-70 % of the input mass) than for the MBP (50-60 % of the input mass). Besides, the MBP has two
other outputs: 6 to 9 % of inerts and around 25 % of stabilized waste, while only inert waste comes
out of the MBS (around 15 %).
Table 14: Input and output of the two MBT plants (EASEWASTE, 2008)
Unit /
MBP
MBS
tonne
Inputs
Natural gas
MJ
97
130
Electricity
MJ
144
433
3
Water
m
0.116
Diesel
L
1.6
Sulphuric acid
kg
3.5
Outputs
Wastewater
N2O
NMVOC
Dust
Dioxin
3
m
g
g
g
g
20
29
4.6
5 10-6
1.32
0.96
55
16.6
-
RDF are sent to a combined heat and power plant with semi-dry flue gas cleaning. They substitute for
combustion of hard coal. The inert waste is routed to a mineral waste landfill, where no gas
generation is expected. Actually very few impacts are expected from this landfill, apart from small
electricity and diesel consumptions for operational needs.
Stabilized waste originating from the MBP plant is sent to a specific landfill. The CH4 potential is
defined by the modeller at 8 Nm3/tonne, as the waste has already been composted. Leachate is
collected and sent to a WWTP, but due to small amounts of methane generated, no gas collection
system is modelled. Carbon sequestration is included in the calculations.
Composting
All organic waste amounts collected separately are routed to a tunnel composting plant. During the
composting process, 64 % of the volatile solid content of garden waste is degraded, while this is 75 %
for kitchen waste. 71 % of the nitrogen content is lost, as ammonia (NH3: 98.5 %), nitrous oxide (N20:
1.4 %) and nitrogen (N2: 0.1 %). It was assumed that 0.2 % of degraded carbon during the composting
process was methane. The gas cleaning is assumed to remove 99 % of ammonia and 95 % of
methane before release to the atmosphere. Furthermore, the plant needs 53.4 kWh/tonne of
electricity.
The compost produced is sold as a fertilizer for agricultural and horticultural purposes. A 100 %
substitution of P and K fertilizers was assumed, while this was 20 % for nitrogen. It is thus assumed
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Environmental performance of European waste management
that the 80 % remaining are supplied by other means by the farmer. Carbon binding of 14 % was
assumed over 100 years. (EASEWASTE, 2008)
Recycling
Recycling of the six waste fractions considered in the study (aluminium, cardboard, ferrous metals,
glass, paper, plastic) was assumed to be done with the same technologies in all countries, using the
same electricity production. The reason is that recycling is supposed to take place on a European
market.
In EASEWASTE, all recycling processes are modelled in the same way:
-
inputs and emissions specific to the recycling process,
-
Two substitution ratios (in %), which reduce the benefits of avoided virgin material
production:
-
•
“Substituted amount”, which takes into accounts the material loss during the
recycling process. For example, in the aluminium recycling process used in the study,
21 % of the collected scrap is lost during the recycling process, the “substituted
amount” ratio is 79 %.
•
“Avoided production”, which quantifies the loss of material grade. In the case of
cardboard for example, the loss of fiber quality of the recycled material implies to
add 10 % of virgin material in the process and thus the avoided amount is only 90 %.
Inputs and outputs specific to the associated virgin material production process.
The six processes used are described in Table 15, including for each of them the two used
substitution ratios. The emission factors for global warming are also detailed in the table, they were
calculated using GWP from IPCC (2007). They include environmental loads from direct emissions at
the recycling process as well as benefits from the substitution of virgin material production. The net
total is the sum of the two emission factors.
Table 15: Data of recycling processes (EASEWASTE, 2008)
Waste fraction
Substituted
amount
Avoided
production
Emission factor
for global warming
(kg CO2-eq / tonne material)
Direct
Avoided
Net
total
Aluminium
79 %
100 %
763
-8988
-8225
Cardboard
100 %
90 %
604
-708
-104
102 % (*)
100 %
1298
-2980
-1681
Glass
99 %
100 %
466
-719
-253
Paper
84 %
100 %
393
-1292
-899
Plastic
90 %
90 %
734
-1494
-759
Ferrous metals
*: To produce 1 kg of steel sheet, 0.98 kg steel scrap is needed because virgin steel is added in the
process
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Collection and Transport
Collection refers to the emptying of all bins in the truck, while transport includes transports both just
after collection of the last bin to the point of unloading and between waste facilities. In EASEWASTE,
both groups of processes are modelled as fuel consumptions, shown in Table 16 and here it was
chosen to model fuel combustion according to a EURO IV standard.
It should be noted that all transport of recyclables is limited to 100 km, even if studies have shown
that large quantities were exported out of Europe and that this change of assumption could make
the recycling process easily become a load to the environment.
Table 16: Fuel consumptions for collection and transport
Collection
Waste stream
(L diesel /
tonne)
Residual waste
- to landfill
3
- to incinerator
- to MBP plant
Source-segregated glass
6
Source-segregated metal
6
Source-segregated paper and cardboard
4
Source-segregated plastic
8
Source-segregated organics
6
RDF from MBT to power plant
MBP-stabilized waste to landfill
Bottom ash to mineral landfill
Compost to use-on-land
-
IV.6.
Transport
( L diesel /
tonne / km)
0.10
0.13
0.13
0.10
0.20
0.10
0.04
0.03
0.06
0.06
Distance of
transportation
(km)
50
15
35
100
100
100
100
35
200
40
70
25
Data quality analysis
The model presents two types of uncertainties: the ones related to data collection and the modelling
assumptions. Some uncertainties are subject to sensitivity analyses later in the report.
Data uncertainty
One of the main data uncertainties is the general waste management in the six MS provided by
Eurostat. Indeed it is not sure that the data were collected and aggregated in the same way in all
countries. For example, the German recycling rate seems particularly high compared to the other
countries, and it could happen that there are counted more material fractions than in these other
MS. These data give the distribution between the different treatment options and may thus have a
high influence on the results. Yet, this was the most complete and consistent source of information
found on the subject.
In the same way, data on waste composition were difficult to find and to compare between different
datasets and studies. They might also not cover the same waste fractions, but the comparison of
different sources enabled to get quite accurate waste compositions.
The energy recoveries at incineration plants were all based on the same report by (ISWA, 2006),
which was found to be the most complete source for the four MS. Yet the data are incomplete for
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Environmental performance of European waste management
two MS (France and UK) and seem to cover co-incineration of other waste streams than MSW, that
might have higher LHV for example.
Performances of recycling processes rely on life cycle inventories, which can originate from many
sources leading to uncertainty. A specific study comparing different datasets could show the range of
variation between LCI.
Modelling limitations
The landfills’ performances are not based on statistical data, as these were not found in literature. So
it is assumed that all landfills found in all MS are compliant with EU Directives, which might be an
optimistic assumption.
Also landfill gases were assumed to be used solely for electricity production. Actually, heat is also
produced in many landfills (Swedish waste management, 2009)and benefits from energy recovery
might be different if modelling also heat production.
The scope of the study is on the impacts of the management of one tonne of collected MSW. Thus it
does not take into account effects of for example waste minimization or home composting.
All RDF were supposed to be sent to a hard coal-fired power plant whereas it might not be possible
to do so. Indeed these plants have special requirements in terms of LHV, content of heavy metals and
harmful compounds. For example, the chlorine content is scrutinized because of corrosion issues in
the combustion chamber and of toxic impacts. If not accepted at usual power plants, they might be
sent to special power plants or incinerators, obtaining different benefits from energy recovery.
Anaerobic digestion was not modelled because of too low quantities treated but benefits from this
technology could appear to be quite high.
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Part V -
Results
Results of life cycle impacts assessments are presented first for global warming and then for all
impacts categories. The environmental profiles of the studied countries are presented in both cases,
followed by sensitivity analyses. When analyzing the graphs, it should be kept in mind that positive
values are detrimental impacts on the environment whereas negative values show beneficial impacts
originating from material and energy substitutions.
Global warming factors (GWF)
Potential impacts on global warming are presented using Global Warming Factors (GWF) which are
defined as emission factors multiplied by global warming potentials (GWP). They express the
potential contributions of WMS to global warming in terms of kg CO2-equivalent per tonne of waste.
GWF can be either positive (load), negative (savings) or neutral. An emission factor, as commonly
used in the literature, describes any emission from a process expressed as an amount emitted per
characteristic unit.
V.1.
Impacts on Global Warming
The impact assessments obtained for the six countries with the use of average country mixes for
energy productions is presented and analyzed first, followed by the results obtained with marginal
energy productions from hard coal and gas. They all use the characterisation factors of IPCC (2007),
presented in Table 1.
The normalized results, in person-equivalent (PE), can be observed in the following chapter together
with the other environmental impacts.
GWF based on average country mixes for energy production
Figure 16 presents GWF from the management of 1 tonne of waste in the six countries, using average
energy mixes.
A first look at the net totals of the countries gives an overview of the variability of the performances
across European MS: they range from -401 kg CO2-eq (Normalized: -46 mPE) for Germany to 90 kg
CO2-eq (11 mPE) for Greece. Waste management systems can be both a benefit and a load for the
environment, depending on several choices in the waste management.
The same observation can be done when considering single technologies’ results: both incineration
and landfills present net totals in the benefits and in the loads parts, depending on the country
where they are placed. There can be both internal and external reasons to these major variations:
-
For the incineration, the reason can be found mainly in two parameters: the energy recovery
(for electricity and heat production) and the carbon intensity of the country mix. This will be
explained in more details when comparing results with different energies in the next chapter.
-
Concerning landfills’ results, it can be observed that they are beneficial only in the country
where a high-quality landfill was modelled: the UK. The collection, utilization and oxidation
rates seem to have high influences and this will be looked into more details in the sensitivity
analysis (See Part V.2. ).
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200
kg CO2-eq / tonne MSW
0
-200
-400
-600
Denmark
France
Germany
Greece
Poland
Collection
Transport
Landfill
Paper
Alu
Steel
Glass
Cardboard
Composting
Incineration
MBT
Net total
UK
Plastic
Figure 16: GWF of the management of 1 tonne of MSW, using average energy mixes
The difference between results obtained for landfills in Poland and Greece seems worth focusing on.
Indeed the GWF of Greek landfills is found more than 3 times higher than for the Polish ones,
whereas the two countries landfill almost the same amount of waste in landfills having the same
characteristics. Explanations can be found in the waste compositions of the two countries and will be
explained in more details in a sensitivity analysis.
Concerning Denmark and Germany, no biological MSW is sent to landfills due to regulation bans, and
thus almost no GHG emission can be observed for these countries’ landfills.
It can be observed that the GWF from recycling are perfectly proportional to the recycling rates used
for each country. This was expected for two reasons:
-
first because the distribution of recycling rates among material fractions were the same in all
MS (for example 12 % of recyclable materials are metals, and 17 % are glass),
-
Then because the same recycling processes were used in all MS, including electricity
production.
Among recycling processes, the greatest benefits are observed for aluminium and paper, with
respectively 37 % and 30 % of beneficial GWF from recycling. Paper presents high benefits because of
the large quantities recovered: 59 % of recovered materials are paper in this model. Concerning
aluminium, it is different: in spite of relatively small recovered amounts, its recycling avoids high
energy consumption during production of virgin material, giving the system high credits. Then, steel
and plastic give quite high benefits (respectively 15 % and 10 % of benefits from recycling), while
glass and cardboard give the least benefits to the systems. Yet these results are highly sensitive to
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the substitution ratios and the emissions factors used for all recycling and virgin material production
processes. This will be scrutinized in the sensitivity analysis (Chapter V.2. ).
GWF of composting show that this process is a load to the environment in all countries, even if this
load is very small compared to the other processes’ results. Results are almost proportional to the
composting rates, slightly modulated by each country’s electricity production. The analysis of the
results shows that the main impact comes from nitrous oxide (N2O) emitted during the composting
process.
MBT gives to both Germany and Poland high benefits for global warming. This is because all the
produced RDF were considered to be sent to a coal-fired power plant (co-incineration) and thus
directly substituting the combustion of hard coal. In reality, the quality of the RDF will determine
whether it can be sent to a power plant or if it should go to an incinerator. This important parameter
will be investigated in the sensitivity analysis (Chapter V.2. ).
Finally, transport and collection appear to give a relatively small load to all systems. It should be kept
in mind that transport distances for recycling were fixed to 100 km, indicating that for example no
transport out of the EU was considered.
GWF based on marginal energy production
Figure 17 shows the GWF of the management of 1 tonne of MSW in the six countries, using different
energy productions: the average country mixes (used also in the previous part) and marginal
productions from hard coal and natural gas. Contributions of recycling and composting processes
were compiled as well as contributions of transport and collection, in order to make the figure more
readable. Net emissions can be observed in Figure 18.
First, the countries’ GWF show an interesting variation between the uses of the three energy system
assumptions. These variations are mostly due to changes in results of incineration and landfill.
Recycling processes were not modelled with country specific energy system assumption because it
was considered that recycling was taking place in a European market. Transport and collection do not
use electricity or heat and concerning MBT, GWF are mainly linked to the use of RDF, which were in
all scenarios sent to the same hard coal-fired power plant.
The results of incineration seem to be the most sensitive to the choice of energy production. When
using marginal production from coal, this process becomes beneficial in France, Germany and the UK.
This shows the importance of the energy system assumption on results, and more especially of its
carbon intensity. Besides, when having a coal-based energy production, Denmark’s benefits exceed
by far the ones of Germany. This shows that in this case, the combination of medium recycling rates
and a high energy recovery at incinerators give better results than a system with very high recycling
rate.
Results of landfills are less sensitive to the carbon intensity of the energy system. This is due to the
lower amounts of substituted energy but also to the major contribution of direct methane emissions
from landfills.
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Figure 18 shows net totals of the management of 1 tonne of MSW in the six countries and compare
them to the GHG emissions from the production of 1 GJ of electricity in all scenarios. This was done
to see how the LCIA were dependent on the carbon intensity of the used electricity production. The
same study can be done with heat.
The figure shows that for all countries, the results of the LCIA of waste management are very linked
to the energy system assumption. The more carbon intensive the country mix, the higher the
substitution and thus the higher benefits for the waste management system.
It can be noted that the carbon intensity of the Polish electricity production is higher than the one of
production from hard coal. This is due to the high use of brown coal (also called lignite) in this
country, which produces energy with a higher carbon content than hard coal. So Poland is the only
MS presenting fewer benefits for global warming with marginal coal-based energy production than
with its average country mix. This difference is due to fewer emissions avoided from energy recovery
at landfills.
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Environmental performance of European waste management
400
kg CO2-eq / tonne MSW
200
0
MBT
Incineration
-200
Landfill
Rec/Comp
-400
Transport
-600
-800
Av
Gas
Coal
Av
Gas
Coal
Av
Gas
Coal
Av
Gas
Coal
Av
Gas
Coal
Av
Gas
Coal
Figure 17: GHG emissions from the management of 1 tonne MSW, with different energy system assumptions: average and marginal from coal and gas (kg CO2-eq/tonne MSW)
200
kg CO2-eq
0
-200
Management
of 1 ton MSW
-400
Substitution of
1 GJ Elec
-600
-800
Av
Gas
Coal
Av
Gas
Coal
Av
Gas
Coal
Av
Gas
Coal
Av
Gas
Coal
Av
Gas
Coal
Figure 18: GHG emissions from the management of 1 tonne MSW (Net totals) and of the substitution of 1 GJ of electricity (in kg CO2-eq)
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V.2.
Sensitivity analyses for Global Warming Factors
The aim of these sensitivity analyses is dual:
-
It should first enable to determine the largest uncertainties in the model,
-
And it should then give advices on where to concentrate efforts if improvements of the
environmental performances are wanted.
The processes presenting the most important GWF (direct or avoided) are tested here: incineration
plants, landfill, MBT and recycling processes. No sensitivity analysis was performed on composting
because the GWF of this waste treatment were very small compared to other processes.
All sensitivity analyses are based on the same methodology (except for the analysis of the influence
of waste composition on landfill performances):
-
One scenario is chosen as a baseline for performing the sensitivity analysis: the country is
chosen so that its net total results are highly dependent on the process tested.
-
The most important parameters of each process are chosen.
-
The parameters are changed to extreme values which are chosen to reflect realistic
alternatives, found in literature and present in this study.
-
The effects of the changes are observed on the net total result of the country.
All variations of parameters are done independently. The energy system assumption of all scenarios
is marginal production from hard coal, so that the results are less dependent on the country mixes
and extrapolations to other countries’ cases are easier.
Key parameters for incineration
The sensitivity analysis on parameters of the incineration plant was performed on the scenario of
Denmark, as this country uses the most incineration and because Figure 17 showed how the results
from incineration had a major influence on this country’s net result.
Modelling the parameters’ variations
The most important parameters were found to be the energy recovery (for both electricity and heat
and the lower heating value (LHV) and percentage of fossil carbon (% Fossil-C) in the waste.
The water content of the waste was not tested but was indirectly accounted for in the sensitivity
analysis on LHV of the waste, as LHV is the subtraction of the higher heating value by the energy
needed to burn the water content of the waste.
For the three parameters (energy recovery, LHV, % fossil carbon), the values corresponding to the
five other countries were used. The minimal and maximal values used to model the other countries
were used to obtain the extreme GWF. For example, the LHV of the residual waste in the 6 countries
was calculated and the extreme values were found to be 10.3 GJ/tonne (for Greece) and 13.6
GJ/tonne (for Germany).
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Results
Net totals of Denmark’s waste management system are shown in Figure 19, together with net results
obtained with the extreme values, shown by the deviation bars.
Elec/Heat recoveries
(%)
LHV (GJ/tonne)
% Fossil-C (kg C/kg
ww)
kg CO2-eq / tonne MSW
0
-200
5 / 24
-400
18.3 %
-600
10.3
-800
13 / 69
11.4
13.6
11.4 %
10.6 %
-1,000
Figure 19: Influence of some incinerators’ parameters on a country’s performance: net total results for
Denmark (marginal coal), with deviation bars showing results obtained with extreme values
The sensitivity analysis shows how the energy recovery has a major influence on the country’s
results. This was also shown in Figure 16 where only Denmark, the country with the highest energy
recovery, presented a beneficial incineration. This high dependency of the energy recovery on the
results is also linked to the use of marginal production from coal: if substituting a less carbonintensive electricity production (for example the country mix of France), variability of the results
would be lower.
The LHV and the percentage of fossil carbon in waste also have a non-negligible role. Indeed the use
of other countries’ values induces a change in Denmark’s net result of up to 20 % for LHV and 18 %
for % Fossil-C.
Key parameters for landfill
Gas collection, utilization and oxidation rates
Greece was chosen as the baseline scenario because it is the country whose landfills have the largest
impact as shown in Figure 17.
Modelling the parameters’ variations
In EASEWASTE, the efficiency of the landfills, in terms of GWF, is mainly defined by the following
three parameters:
-
the collection rate, characterizing the ability at collecting the landfill gas generated;
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-
the utilization rate, characterizing how the gas collected is then treated: here the utilization
was exclusively defined as an electricity production. It was considered in the study that the
non-utilized gas was flared;
-
the oxidation rate, characterizing the ability of the top cover at oxidizing the uncollected
methane when emitted from the landfill.
Please note that, as explained in Section IV.5. the collection rate refers here to the collection during
the active period i.e. from year 2 to year 45. To obtain the collection rate over 100 years, the rate
should be multiplied by 84/100.
The sensitivity analysis was performed with the following extreme values:
-
Collection rate: from 0 %, illustrating the worst case scenario, to 83 %, which is the collection
rate applied to UK’s landfills.
-
Utilization rate: from 0 %, the case where all the collected gas is simply flared, to 80 %, the
utilization rate applied to UK’s landfills.
-
Oxidation rate: from 0 %, the worst case scenario, to 50 %, the double of the value in Greek
landfills.
Results
Net totals of Greece’s waste management system were plotted in Figure 20, together with net results
obtained with the extreme values, shown by the deviation bars.
600
0%
kg CO2-eq / tonne MSW
400
200
60 %
0%
0%
60 %
25 %
80 %
0
50 %
83 %
-200
Collection rate
Utilization rate
Oxidation rate
Figure 20: Influence of some landfill’s parameters on a country performance: net total results for Greece
(marginal coal), with deviation bars showing results obtained with extreme values
The results show how the collection rate has a crucial role in the total net result of a country where
landfilling is so important. The effect of a variation of this rate is far more important than for the two
other rates. This is due to the double role of this parameter:
-
It reduces the amounts of methane escaping the landfill,
-
And it increases the amount of gas available for utilization (here electricity production).
The utilization rate has a minor influence compared to the collection rate. This result is directly linked
to the carbon intensity of the substituted electricity production, here from 100 % hard coal.
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The oxidation rate has a non-negligible impact: assuming no oxidation in the top cover makes the
Greek net total double, while doubling it (to 50 %) makes the Greek waste management system
become slightly beneficial (GWF of -7 kg CO2-eq / tonne MSW).
When looking at the combination of these three parameters, the high uncertainty of landfills results
is evident. It also confirms what was noticed in Chapter V.1. : the high collection rate applied to UK’s
landfills makes the landfills become beneficial when applied to Greece. To see how the LCIA would
be if UK’s landfills had been modelled identical as the one in France, Greece and Poland, the three
parameters were progressively lowered to these countries’ ones (See Figure 21). In all columns, the
net total of all other processes is presented in blue, while the results of landfills are detailed in
energy substitution, energy use and system emissions. The first column shows the baseline scenario
of UK. In the second column, the oxidation rate is lowered to the EU-average landfill’s value. Then in
columns 3 and 4, utilization and collection rates are also lowered to the values used in the other
countries.
The direct system emissions are a credit to the system in the three first cases due to carbon
sequestration, while they become loads when lowering the gas collection rate in the fourth column.
The figure shows that if UK’s landfills had been modelled like the other countries, almost no benefit
would have been observed in GWF concerning this process.
kg CO 2-eq / tonne MSW
100
0
System emissions
Energy substitution
Energy use
Other processes
Net total
-100
-200
-300
-400
83/80/30
83/80/25
83/60/25
60/60/25
Gas collection rate / Utilisation rate / Oxidation rate (%)
Figure 21: GWF of UK’s landfills (detailed into energy use, energy substitution and system emissions) and net
total of the other processes, when applying different landfill parameters
Waste composition of landfilled waste
As shown in Figure 16, results of Greek and Polish landfills show high variability, whereas almost the
same amount of MSW was put in landfills of same performances in terms of gas collection, utilization
and oxidation rates. Thus, a possible link between these results and the waste composition was
investigated. Indeed, the waste composition used to model Greece has a particularly high organic
content (47 %) leading to a high methane potential in the landfilled waste, compared to Poland.
For this analysis, no parameter was changed but a detailed analysis of the results of the two
countries’ landfills was performed. In Figure 22, the same amount of waste (1000 kg) of Greek and
Polish wastes was placed in the same landfill. The methane potentials of both residual wastes are
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150
400
100
200
50
3
600
CH4 potential: Nm / tonne
kg CO 2-eq / tonne landfilled
presented by a point (scale on the right y-axis), while GWF of landfills are detailed into benefits
(electricity production and carbon sequestration) and loads (direct methane emissions, direct other
emissions and energy use).
0
0
-200
-50
-400
-100
Greece
Poland
Electricity production (CO2 emissions mainly)
Energy use (CO2 emissions mainly)
Direct other emissions at landfill
Direct methane emissions at landfill
Carbon sequestration
CH4 potential
Figure 22: GWF of the landfilling of 1 tonne of Greek and Polish waste
According to Figure 22, waste composition, especially the methane potential of the waste landfilled,
is an essential parameter for landfills’ performances. When this potential decreases from 80 to 61
Nm3/tonne (24 % decrease), the net GWF of the landfill decreases from 233 to 77 kg CO2-eq / tonne
waste landfilled (67 % decrease).
Even if the high methane potential of Greek waste leads to a higher electricity production, it also
induces higher direct emissions of methane. These direct emissions have a high impact as the GWF of
methane is 25 times higher than the one of carbon dioxide. Thus this GWF cannot be offset by the
gain due to the higher electricity production.
Moreover, the effect is intensified by another parameter. The content in paper and cardboard of the
Polish residual waste is slightly higher than the Greek one, because Greece has more source sorting
of these materials. So carbon sequestration, which is calculated as the initial quantity of biogenic
carbon entering the landfill minus the carbon emitted as CO2 or CH4, is found to be higher for Poland
than for Greece. Indeed paper and wood products have in general a quite high ability to sequester
carbon.
Finally, methane potential is important for direct methane emissions from landfills, so countries with
high organic content should focus on collecting landfill gas, for recovering energy but even more for
avoiding direct emissions.
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MBT
Germany was chosen as this country presents the highest benefits from MBT (See Figure 17).
Modelling the parameters’ variations
The GWF were found mainly dependent on the benefits from energy recovery from RDF combustion.
So different options for the handling of RDF were investigated. RDF are usually sent to coincineration in power plants or cement kiln, or to incineration. In this study, they were assumed to be
all sent to a hard coal power plant. In reality, power plants and cement kilns were not primarily
designed for burning waste fractions, so the RDF have to fulfil some quality criteria to determine if
they are accepted in these installations. The RDF quality requirements include for example minimum
LHV and maximum chlorine content. This substance induces in particular corrosion problems in the
combustion chamber, and toxic impacts. If quality criteria are not respected, RDF can be sent to
classical or RDF dedicated incineration plants, where the benefits will depend on the energy
recovery. It is important to realize that the energy produced at the incinerator substitutes average
(or marginal) energy production in the country, whereas at power plant or at cement kiln RDF
directly substitutes coal.
These are the options modelled for this sensitivity analysis:
-
Two power plants using hard coal and brown coal, based on (Gendebien et al., 2003);
-
One cement kiln normally hard coal-fired, based on (Gendebien et al., 2003);
-
Three incineration plants with different energy recoveries (all based on the incineration
technology used in this study):
o One without energy recovery,
o One with the energy recovery used for German incinerators in this study (Elec: 9.6 %,
Heat: 20.4 % of LHV),
o One with a high energy recovery: electricity 30 %, and heat: 70 % of LHV.
Results
Net totals obtained for the different options for the handling of RDF applied to the German WMS are
shown in Figure 23. It should be noted that the incineration without energy recovery and the one
with a very high one are two extreme scenarios which are not expected to happen; they only show
the possible range of variation between all choices. The real possible decisions are expected to be
among the four possibilities in the middle.
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Environmental performance of European waste management
Incineration
without
energy
recovery
Incineration
(Elec 9.6%,
Heat 20.4%)
Power plant
Hard coal
Power plant
Brown coal
Cement kiln
Hard coal
Incineration
with high
energy
recovery
kg CO 2-eq / tonne MSW
0
-200
-400
-600
Figure 23: Influence of handling of RDF from MBT on country performance, net total for Germany with the
different possible options (marginal coal)
The GWF of the four possible options are varying from around -350 to -550 kg CO2-eq per tonne of
German MSW. This range is quite large. However, it should be noted that the option chosen in the
study (the hard coal fired power plant, into a frame in Figure 23) obtains a GWF in the middle of this
range.
The first option, incineration without energy recovery, is the only one giving a load to the WMS (84
kg CO2-eq), while the incineration with energy recovery used to model Germany in this study gives a
small benefit (- 6 kg CO2-eq). Combustion at hard and brown coal power plants give respectively GWF
of -103 and -127 kg CO2-eq, while combustion at the cement kiln offers significantly higher benefits (187 kg CO2-eq). The incineration with high energy recovery (30 % electricity and 70 % heat) gives the
highest benefits (- 210 kg CO2-eq). This sensitivity analysis shows that the final destination of RDF has
a large influence on the net GWF of a WMS, and in particular the energy recovery efficiency.
Recycling processes
Germany was chosen for this sensitivity analysis because this country presents the highest benefits
from recycling as shown in Figure 17.
Modelling the parameters’ variations
The net result of each recycling process depends on several parameters: carbon intensity of the
recycling process, carbon intensity of the substituted virgin material production and substitution
ratio. Only an analysis on the substitution ratio is presented because it indirectly reflects the carbon
intensities of the virgin and secondary materials productions.
The substitution ratio of each recycling process varies from 50 % to 100 %.A substitution ratio of 50 %
indicates that of the collected recyclable, only 50 % will be effectively recycled, while in the 100 %
case, all the collected amounts are recycled.
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Results
Figure 24 shows total net results for the German WMS. Each column shows the effect of a change of
the substitution ratio of one of the six recyclables. For each recyclable, the whole column (light +
dark colours) shows the net total for the German waste management system. The lightest colour
rectangle is the contribution of the considered material recycling in this net total of Germany. Thus
the darkest colour rectangle represents the German net total after subtraction of the net result of
the considered recyclables. The substitution ratios used in the study are indicated at the bottom of
each column and deviation bars show net totals obtained for substitution ratios of 50 % and 100 %.
Paper
Alu
Steel
Plastic
Glass
Cardboard
0
kg CO 2 -eq / tonne MSW
-100
-200
-300
-400
-500
84 %
79 %
>99 %
81 %
99 %
90 %
-600
Figure 24: Influence of recycling substitution ratios on net totals of Germany, vertical error bars show
substitution ratios varying from 50 % to 100 %.
The sensitivity of substitution ratios is quite important compared to the net total GWF, especially for
paper and aluminium. This is because these two recycling processes give the largest GWF benefits to
the system. It can be observed that a 50 % substitution ratio applied to these two recycling processes
still makes them more beneficial than the four other recyclables. On the contrary, for glass and
cardboard, a 50 % substitution ratio makes the considered recycling process become a load for the
environment.
Yet, when comparing these results to the ones of the previous sensitivity analyses, these parameters
seem less sensitive.
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V.3.
All impact categories
After a focus on the countries’ performances towards global warming, the other impact categories
are assessed here, to provide a more comprehensive picture of WMS.
The impact assessments for the six countries are presented in Figure 25 for non-toxic impact
categories and Figure 28 for toxic impact categories. A look at the two figures gives a first idea of the
variability of results between countries. LCIA were all performed using marginal energy production
from hard coal, so that the results are less dependant on country mixes and more directly related to
the waste management.
It can be observed that impact assessment results are found approximately 10 times higher for toxic
categories than for non-toxic ones. This is a normal observation in LCAs performed with the EDIP97
method. Therefore, results of toxic and non-toxic categories are presented separately. This is also
due to the level of confidence in the assessment of these two groups of impact categories: the
assessments of non-toxic categories are quite broadly recognized, whereas the method used to
characterize toxic impacts differs a lot from one LCIA method to another.
Non-toxic impact categories
Figure 25 shows normalized impact assessments of non-toxic impact categories of the management
of 1 tonne MSW in the six countries, using marginal energy productions from hard coal.
GW
OD
AC
NE
POF
0.02
0
PE
-0.02
-0.04
-0.06
DK
FR
DE
GR
PL
UK
-0.08
-0.1
Figure 25: Normalized impact assessment of the management of 1 tonne of MSW, Non-toxic impact
categories, for all countries (marginal energy production from hard coal)
Firstly, the observation of the results makes it reasonable to neglect the effects of the considered
waste management systems on ozone depletion (OD) and photochemical ozone formation (POF).
These impact potentials are mainly linked to the use of landfill through the emissions of CFCs (for
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OD) and methane (for POF). It should also be noted that the emission of CFCs from landfills is
modelled as process-specific in EASEWASTE, meaning that the waste composition has no effect on
the calculations. Thus conclusions on this impact category are difficult to draw. The two impact
categories are further disregarded.
On the contrary, acidification (AC) and nutrient enrichment (NE) will be focused on as the systems
show higher absolute values and a high variability between countries. Details of the contribution of
all processes to acidification and nutrient enrichment are presented in Figure 26 and Figure 27.
Impact potentials are here mainly due to air emissions of NOx for NE, and SO2 and to a smaller extend
NOx for AC. These emissions are closely related to fuel combustion and thus to energy consumption
and production.
Acidification (AC)
All WMS present net benefits for acidification, and very few processes appear as loads to the
environment. This means that direct emissions are outweighed by the benefits from energy and
material recovery. But depending on the country, the largest benefits are observed for recycling or
energy recovery. Indeed, in Denmark, energy recovery at incineration gives by far larger benefits
than recycling while in Germany this is the opposite.
For energy recovery, substitution of electricity production gives more benefits than the one of heat
production. Concerning recycling, the main benefits come from aluminium (44 %), plastic (31 %) and
paper (12 %).
0.01
0.00
-0.01
MBT
Recycling
Composting
Landfill
Incineration
Transport
Sum
-0.02
PE
-0.03
-0.04
-0.05
-0.06
-0.07
-0.08
-0.09
DK
FR
DE
GR
PL
UK
Figure 26: Contribution of each process to acidification (marginal energy production from hard coal)
Nutrient enrichment (NE)
Concerning nutrient enrichment, all WMS also present benefits, mainly due to recycling and energy
recovery. Yet the benefits from energy recovery are much less visible than for acidification. The
reason lies in the direct emissions of SO2 and NOx at waste treatment facilities: energy recovery at
incinerators and at landfills avoids large emissions of SO2 from coal combustion, while these
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processes emit almost no SO2. On the contrary, NOx emissions are also avoided when producing
energy but these compounds are emitted in considerable quantities at incinerator and landfill. NOx
are emitted during combustion of waste at incinerators and during combustion of landfill gas and
diesel in trucks at landfills. This explains why energy recovery has a more important contribution for
acidification than for nutrient enrichment.
Thus recycling benefits become more important for nutrient enrichment. Recycling gives the highest
benefits in all countries except Denmark where the high energy recovery at incineration still gives
higher benefits than recycling. The waste fractions giving the highest benefits when recycled are
here: plastic (37 %), aluminium (34 %) and paper (19 %).
Transport, composting and landfills in France, Greece and Poland are loads to the environment for
nutrient enrichment. The first two are linked to direct emissions of NOx during combustion of diesel
and production of electricity, while the landfills’ potentials are highly due to direct emissions of
phosphate and ammonia to freshwater surfaces.
0.01
PE
0.00
MBT
Recycling
Composting
Landfill
Incineration
Transport
Sum
-0.01
-0.02
-0.03
DK
FR
DE
GR
PL
UK
Figure 27: Contribution of each process to nutrient enrichment (marginal energy production from hard coal)
Toxic impact categories
Figure 28 shows normalized impact assessments for toxic impact categories of the management of 1
tonne MSW in the six countries, using marginal energy productions from hard coal.
Impact potentials on ecotoxicity in soil (ETs), human toxicity in air (HTa) were found in the
magnitudes of respectively 10-4 and 10-3 and were thus considered as negligible compared to the
other toxic impact categories.
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ET s
ET wc
HT a
HT s
HT w
SE s
SE w
0.3
0.2
0.1
PE
DK
0
FR
-0.1
DE
GR
-0.2
PL
UK
-0.3
-0.4
-0.5
-0.6
Figure 28: Normalized impact assessment of the management of 1 tonne of MSW, Toxic impact categories,
for all countries (marginal energy production from hard coal)
Impact potentials on chronic ecotoxicity in water (ETwc), human toxicity in water (HTw) and in soil
(HTs) were investigated in more details, to know by which substances and processes they were
caused. Figure 29 shows contributions of processes to each country’s impact potentials.
0.2
ETwc
HTw
HTs
0.1
0.0
PE
-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
DK
FR
DE
GR
Transport
PL
UK
Incineration
DK
FR
Landfill
DE
GR
PL
Composting
UK
DK
Alu. Rec.
FR
DE
Other rec.
GR
PL
UK
MBT
Figure 29: Detailed normalized impact potentials on chronic ecotoxicity in water (ETwc), human toxicity in
soil (HTs) and in water (HTw) (marginal energy production from hard coal)
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Chronic Ecotoxicity in water (ETwc)
ETwc is mainly due to emissions of toxic metals (e.g. aluminium, copper, zinc, cadmium, lead and
mercury) and persistent organic substances, especially PAH (Polycyclic Aromatic Hydrocarbons) and
dioxins.
All countries show net benefits for this impact category, due to two processes: aluminium recycling
and incineration. The recycling of aluminium avoids large emissions of PAH to freshwater surfaces,
which come from the anode consumption during production (International Aluminium Institute,
2007). Thus, contrary to what was expected, the reason for these high benefits is not only the high
energy consumption avoided but direct emissions during the production process.
At incineration plants, the energy recovery substitutes energy production from hard coal and thus
avoids emissions of aluminium (substance) to freshwater surfaces, which accounts for more than
90 % of the benefits of energy recovery. For example, at the Danish incinerator, the benefits of this
avoided emission of aluminium allows the offset of the impacts of the emissions of PAH (to fresh
surfacewaters) and mercury and dioxins (to air) due to the incineration process.
At landfills, the benefits of energy recovery are not high enough to offset the direct emissions of
PAH, copper and zinc to freshwater. In all countries, the potentials of this process are almost equal to
zero.
Human Toxicity in soil (HTs)
Here again, benefits are observed for all countries and mainly due to energy recovery and aluminium
recycling. Energy recovery gives benefits to both landfills and incineration because of avoided
emissions of benzene to the air (more than 80 % of the benefits) and to a smaller extend aluminium
and mercury. The higher quantities recovered at incineration give more credits to this treatment
option. Direct emissions at both facilities give a detrimental impact of approximately 10 % of the
benefits due to energy recovery. These direct emissions are almost exclusively mercury emissions to
the air for incineration, while for landfills, emissions of arsenic and vinyl chloride are the main
contributors.
The recycling of aluminium gives important benefits to all systems because of avoided emissions of
fluoride to air, which arise from the molten bath necessary for aluminium virgin production
(International Aluminium Institute, 2007).
Human Toxicity in water (HTw)
The impact potentials are here almost all loads to the environment and mainly due to mercury
emissions, to soil or to air. All direct impacts are related to the mercury content of the waste.
When used on farm land, the mercury content of compost leads to direct emissions of this substance
to soil. When combusted, the mercury content of residual waste is emitted to air, which can be
observed here for MBT and incineration. Impacts of MBT are due to the combustion of RDF at power
plant. This coal-fired power plant is modelled with less flue gas cleaning than the incineration plant.
Indeed, in the model, after RDF combustion, 25 % of its mercury content is emitted to the air,
whereas this is only 3.5 % for incineration plants. This is why high detrimental impact potentials are
observed here for MBT.
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Incineration has also a detrimental impact on HTw in three countries out of four. The energy
recovery at incinerators substitutes mercury emissions from energy production based on coal
assumption, but only Denmark’s energy recovery is high enough to offset the impacts of emissions of
mercury due to the combustion of the mercury content of waste.
Stored Ecotoxicity (SEs and SEw)
Stored ecotoxicity expresses the potential hazard of having metals in a landfill over thousands of
years. Thus these impact categories focus on the potential ecotoxicological impacts beyond 100
years.
The two stored ecotoxicity categories vary simultaneously. The one in water is around ten times
higher than the one in soil. Stored ecotoxicity in water is mainly due to copper, cadmium and lead.
This impact potential is independent of the handling of residual waste as, whether they are
incinerated, composted or directly buried, they will ultimately all end in a landfill. Thus differences
must only be due to compositions of residual wastes, which depend itself on the initial waste
composition and the source separation (for recycling).
Sensitivity analysis: use of average country mixes for energy production
The sensitivity analysis performed on the influence of the energy system assumption regarding GWF
showed that this parameter had a particularly high impact on Denmark’s results (See Chapter V.1. ).
Thus the sensitivity analysis of this parameter on all impact categories will be only presented for this
country, comparing the results obtained with average country mix and marginal production from
coal.
Besides, the analysis will only focus on three non-toxic and three toxic impact categories:
acidification, global warming, nutrient enrichment, chronic ecotoxicity in water and human toxicities
in water and soil. As shown previously the other impact categories were found negligible compared
to these ones, apart from stored ecotoxicity which does not have link with energy production of the
country. Figure 30 presents the normalized impact potentials for the six impact categories using two
possible energy substitutions (average mix and 100 % hard coal marginal).
The change of electricity production in the Danish scenario only influences the impact potentials of
incineration, as the other processes used in the Danish management system use little electricity or,
for recycling, do not use the country’s specific energy system. It should be noted that an energy
recovery from landfilling would have shown similar variations of results as the same energy system
would have been substituted.
Each impact potential is linked to the emission of particular substances when producing energy: GHG
for global warming, nitrogen oxides for nutrient enrichment, sulphur dioxide for acidification,
mercury, PAH and heavy metals for toxic categories (simplified). And, in Denmark –and in lots of
European countries- the average country mix presents lower emissions of these substances than
production from hard coal, because of the use of “cleaner” energy productions in the country mixes.
This is why larger benefits are observed when substituting energy production from coal.
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PE
0.02
0.00
-0.02
-0.04
-0.06
-0.08
-0.10
Composting
Acid. Av
Acid. Coal
GW Av
GW Coal
NE Av
NE Coal
Incineration
Recycling
PE
Landfill
0.2
Transport
0.0
-0.2
-0.4
-0.6
Etwc Av
Etwc Coal
HTw Av
HTw Coal
HTs Av
HTs Coal
Figure 30: Normalized impact potentials for Denmark using average energy production (Av) and marginal
from hard coal (Coal) (for acidification, global warming, nutrient enrichment, chronic ecotoxicity in water,
human toxicities in water and soil)
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Part VI - Discussion
In this discussion, the aim was to get a better understanding from the process scale to the system
scale (country level). A first part focuses on single technologies’ performances, while the second one
presents both profiles of the countries and recommendations for future improvements. In a third
part, an attempt is made to link GWF to impact assessment in the other impact categories, to assess
whether GWF is a robust indicator of environmental performances of WMS.
As explained before, the discussion will focus on three non-toxic impact categories (global warming,
acidification, nutrient enrichment) and four non-toxic ones (chronic ecotoxicity in water, human
toxicities in water (chronic) and soil, stored ecotoxicity in water).
VI.1.
Technologies’ performances
The analysis of the study’s results enables to gain a good insight into each technology’s
environmental performances and gives ideas on which parameters to focus on.
Incineration
Energy recovery at incineration plants is the most important parameter to determine their
environmental performances. It gives high benefits in all six impact categories and has a significant
range of variation between the different countries. For example, net GWF of incineration were found
both detrimental and beneficial in the different countries: in Denmark, the benefits from energy
substitution are high enough to outweigh impacts of direct emissions from incineration, while in
France, Germany and the UK, energy recovery were too low to do so (with energy systems based on
average country mixes).
A decisive external parameter is the quality of the substituted energy production, in terms of
emissions of fossil carbon (for global warming), sulphur dioxide (for acidification), NOx (for
acidification and nutrient enrichment), mercury and other heavy metals (for toxic impact categories).
For example, with the energy system assumption based on average country mixes, net total GWF of
French incineration is clearly a load to the environment due to the low carbon content of French
average energy production, whereas with the energy system assumption of hard coal, the process
becomes beneficial.
The environmental performances of incineration are also influenced by the composition of the waste
incinerated, especially by the lower heating value and the fossil carbon content. Besides, mercury
content of the waste has a direct consequence on mercury emissions to the air and thus on some
toxic impact categories.
Performances of the flue gas cleaning system, e.g. for mercury, dioxins and nitrogen oxides removal,
have a role in the impact assessment, especially for toxic impact categories. Even if this parameter
was not studied in details in this study, direct emissions of these compounds were scrutinized.
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Landfill
The environmental performances of landfills are mainly linked to two processes: direct gaseous
emissions (found here to have a major influence on GWF) and electricity substitution (giving benefits
in almost all categories).
Direct emissions of methane have a high influence on GWF due to the large quantities produced and
potentially emitted to the atmosphere. The sensitivity analysis showed how important the gas
collection rate is to determine these emissions: changing it from 0 % to 83 % makes the Greek net
GWF vary from + 500 to - 100 kg CO2-eq /tonne waste. The reason for that is the double role of this
parameter in the model: it reduces direct emissions and increases the potential for energy recovery.
Gas utilization and oxidation rates have also important roles, each on one of the two performance
factors: one solely on electricity production, the other solely on methane oxidation before release
into the atmosphere.
Waste composition has also a major influence on environmental performances of landfills, especially
for methane potential: a sensitivity analysis compared Greek and Polish compositions of waste
landfilled and showed that reducing this parameter from 80 to 60 Nm3 / tonne lead to a reduction of
67 % of the landfill’s GWF.
For all impacts, the electricity substitution from energy recovery leads to quite high benefits in
different impact categories, even if they are much smaller than benefits from energy recovery at
incineration plants.
Finally landfills presented higher benefits than expected, especially for GWF, mainly because of
carbon sequestration. Indeed only a few studies account and credit carbon sequestration.
Recycling
In this study, recycling was modelled with the same technologies using the same energy productions
in all MS. Thus all benefits from recycling were directly proportional to inventories of each
technology and recycling rates given by Eurostat.
All recycling processes presented benefits in most of the impact categories. The recyclable giving the
highest benefits were: aluminium, paper (because of high quantities recovered), plastic and steel.
Benefits from aluminium recycling are coming from virgin material substitution and in particular:
-
the high energy consumption avoided for virgin material production, especially for GW, AC
and NE. This includes in particular the separation of bauxite to produce aluminium.
-
some emissions specific to the production of this material: emissions of PAH at anode
consumption and emissions of fluoride from the molten bath, leading respectively to
impacts on ETwc and HTs.
It should be carefully noted that all recycling results rely on life cycle inventories and that this is a
very sensitive parameter. Indeed different LCI databases can show high variability and should be
focused on in further research (Merrild et al., 2008).
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Composting
Composting was not found very visible in all impact assessments, in spite of relatively high quantities
treated. This indicates that loads and benefits of this technology were more or less equal. Yet small
loads to the environment are observed, due to energy utilization and to the mercury content of
compost for the load observed for HTw.
MBT
The use of MBT gives high credits to systems in energy-related impact categories (mainly for GW, AC,
NE) because of direct substitution of coal. Yet, the quality of the RDF generated at MBT is a crucial
parameter. For example, too high chlorine contents will make the RDF unusable in a power plant due
to corrosion issues and toxic impacts. The sensitivity analysis showed how results were highly
dependent on the final destination of RDF, making German net total GDP vary from -350 to -550 kg
CO2-eq / tonne MSW. As the quality of flue gas cleaning modelled at power plants was lower than at
incinerator, high mercury emissions to air were observed, causing impacts on human toxicity in
water.
Finally, the co-incineration of RDF in power plant or cement kiln presents the advantages of
substituting fossil fuels very effectively, but major drawbacks are observed for toxic impacts of
emissions of heavy metals, due to the usually poor flue gas cleaning in these installations. Thus
improvements in energy efficiency of incinerators and flue gas cleaning at coincineration power
plants should reduce the range of variability of LCIA and offer a suitable option for RDF combustion
concerning both non-toxic and toxic impacts.
Transport
A load due to transport was observed for GW, AC, NE and ETwc, that can account for up to 10 % of
the net impact. It should be noted that the distance for recycling was set to 100 km but that in reality
it could take place much further.
VI.2.
Performances of EU countries
Internal versus external parameters
The study showed that environmental performances were highly correlated to two kinds of
parameters: internal ones (e.g. energy recovery efficiency, landfill gas collection) and external ones
(here energy country mixes and waste compositions). The first ones are determined by the waste
management system, whereas the waste industry has no influence on the second ones.
Influence of external parameters
Energy recovery gives high credits in many impact categories and is thus central for determining the
environmental impacts of waste management systems. Thus the properties of the energy substituted
are very important, in terms of emissions of CO2, SO2, NOx and heavy metals. For example, French
average electricity production has a low carbon-content which gives far less benefits to waste
management systems compared to the substitution of Danish average electricity production. Even
when taking the marginal approach, results will be very different if the marginal energy production
was identified as hard coal-based or natural gas-based. For example, the Danish incinerator obtains
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more than twice as much benefit when substituting coal-based energy production compared to the
gas-based one.
The importance of waste composition depends on the treatment chosen. The highest influence
observed in this study was for landfills: the organic content of landfilled MSW and thus its methane
potential lead to higher direct methane emissions which made the landfills’ performances much
worse for the country having the highest methane potential. The sensitivity analysis on the landfilled
waste composition also highlighted the role of paper content in the landfill waste, as this waste
fraction has a quite high ability to sequester carbon.
Heavy metal content of MSW has high influence on toxic impact assessment when it is combusted,
composted and disposed on land, or landfilled. Mercury was found by far the heavy metal leading to
the largest loads to the environment. The impacts from combustion were actually found higher at
power plants where RDF were sent than at incineration plants due to less flue gas cleaning. Yet, the
mercury content can be reduced at source by sorting batteries out of residual waste through for
example awareness campaigns. Concerning landfills, heavy metals, and more especially copper,
cadmium and lead, gave the most important loads for stored ecotoxicity in water.
Influence of internal parameters
Beside these external parameters, waste management industry can decide on many internal key
parameters which have large influence on the results. In lots of cases, external parameters are
actually closely linked to internal ones and the waste industry has many means of adapting to
externalities, especially the ones related to waste composition:
-
For incineration, a variation of the LHV of waste from 11.4 to 13.6 GJ / tonne made the
quantity of recovered energy increase of 20 %. But the energy efficiency of the incinerator
in terms of energy recovery showed a higher influence on the results.
-
For landfills, the methane potential of Greek waste induced direct methane emissions
approximately 20 % higher in that country compared to Poland. But the sensitivity analysis
performed on landfill gas collection rate showed how this was the key parameter for
landfills’ performances. In the Greek case, increasing that rate to the value used in the UK’s
landfills made the Greek landfill become beneficial for global warming.
-
In the same way, by increasing sorting efficiencies of metals, and especially batteries, the
heavy metal content of residual waste can be lowered dramatically. This will significantly
decrease detrimental effects on toxic impact categories.
Finally the energy systems of the countries have the highest influence on results. The waste
management industry has almost no influence on them, as these rather depend on the countries’
energy policies. But as performances of the WMS rely deeply on them, a special attention should
always be paid to this external parameter when looking at the results of LCA studies.
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How relevant is the waste hierarchy in the studied WMS?
This is a difficult question, as the answer depends again on the energy substitution assumption:
average country mix, marginal hard coal-based or marginal natural gas-based energy productions.
First of all, the priority of prevention, minimization and reuse will not be discussed here as they are
out of the scope of this work. Indeed this study looked at the impacts of the management of one
tonne of waste collected by municipalities.
In general, the study showed that the waste hierarchy was valid. Countries with high recycling rates
(DK, DE, UK) obtained the best environmental gains in almost all impact categories, due to material
substitutions. Also, in general, the countries using landfills for residual waste treatment (FR, GR, PL,
UK) generally have higher detrimental impacts on the environment compared to Denmark and
Germany. Yet the strict classification between waste management strategies might be questioned in
regards to some results.
Material or energy recovery?
When the energy substitution was assumed to be average country mixes or marginal from gas,
Germany obtained higher benefits in GWF than Denmark, whereas the Danish system was found
much more beneficial than the German one when energy substitution was assumed to come from
hard coal-fired power plants. The reason is that Denmark treats more than 50 % of its MSW by
incineration and that its incinerators are very efficient. Thus the carbon content of the energy
substituted influences a lot this country’s results.
The same conclusions can be drawn for the other impact categories. When considering average
country mixes, the high German recycling rate leads to larger benefits in the system, while when
considering marginal production from coal, Denmark obtains higher benefits due to a combination of
high energy recovery at incineration plants and good recycling rates.
So these results indicate that when average country mix is used, material recovery gives higher
environmental benefits, while it is energy recovery when marginal energy production is used.
Comparing performances of landfills and incinerators
The high performances of the UK’s landfills in terms of gas collection, utilization and oxidation
generate substantial benefits in terms of GWF. The study even showed that the UK’s management
system was better than the French one, which uses incineration and landfilling in an almost 50-50
share for the treatment of its residual waste. The difference between the two countries is actually
higher than the difference due to their recycling rates, showing that the UK’s average landfill give
higher benefits than the French average incinerator. Thus, the comparison between a high-quality
landfill and a low-quality incinerator inverts the waste hierarchy.
Relevance of the waste hierarchy
The study showed that the waste hierarchy is generally valid but should be considered as a general
and flexible ranking of waste management options. As advised by the European Commission in the
thematic strategy on the prevention and recycling of waste, policymaking should be based on life
cycle analysis, integrating all key parameters that have an influence on of waste management
systems’ environmental performances (European Commission, 2005a).
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Profiles of the countries and recommendations
Germany obtains large environmental benefits from its high recycling rate (46 %) and it seems
difficult to improve this rate. Thus this MS could focus efforts on raising the energy recovery
efficiency of its incineration plants.
Contrary to what was expected, waste management systems of Denmark and the UK have somehow
the same environmental profiles: a good recycling rate (respectively 24 and 22 %) and residual waste
treatment facilities with very high performances: the Danish incinerator was modelled with an
electricity recovery of 13 % combined with a heat recovery of 69 %, while the UK’s landfills had a gas
collection rate of 70 % (over 100 years) and an utilization rate of 80 % for electricity production. The
only difference between the two countries’ performances is that energy recovery at incineration
plants is much higher, giving Denmark larger benefits. In these countries, it seems difficult to improve
further the performances of these residual waste treatment facilities, so they could focus on
improving the recycling.
The French waste management system was modelled as almost equally distributed between material
recovery, energy recovery and disposal at landfills. Its environmental profile shows average benefits
in almost all impact categories, related mainly to recycling and incineration. An increase in the
recycling rate and then in the energy recovery could be the most effective decisions for improving
this waste management system’s environmental performances.
Presenting the lowest recycling rate of the six countries studied (4 %), Poland should focus on
improving this factor so that it will get larger benefits in most of the impact categories.
As Greece already uses landfills at a very high rate (83 %) and due to the high organic content of its
MSW, the cheapest and the first decision should be to focus on improving its landfills’ performances
especially their gas collection. Another solution could be to have less organic waste entering the
landfills by sorting out this waste before being landfilled. This could be achieved with the use of MBT
or by sorting more at source and having this waste composted or digested in an anaerobic digester.
More generally, the focus should be put on both increasing recycling rates, especially for heavy
metals, and energy recovery at incineration and/or gas collection at landfills.
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VI.3.
Do GWF give a good overview of systems’ environmental
performances?
The analysis of the results showed that many impact assessments are closely linked to energy
consumption and substitution. These connections are summarized in Table 17.
Table 17: Connection to energy use and production of impact categories
Impact category
Related to energy?
Elec / Heat
Yes
Transport
Yes
Acidification
Nutrient enrichment
Yes
Yes
Chronic ecotoxicity in
water (ETwc)
Global warming
Substance
emitted
Other major
contributions
CO2
Direct CH4 emissions
from landfills
Little
Yes
SO2 , NOx
NOx
Direct NOx emissions
from combustion
Yes
Yes
Heavy metals
Aluminium recycling:
avoided PAH emissions
Human Toxicity in soil
(HTs)
Yes
No
Benzene,
Heavy metals
Human toxicity in water
(HTw)
Yes
No
Mercury
Stored ecotoxicity in
water (Sew)
No
No
-
Aluminium recycling:
avoided fluoride
emissions
Direct mercury emissions
to air (incineration, RDF)
and soil (use of compost)
Landfill: heavy metals
Thus all the impact categories, except stored ecotoxicity, are highly related to the consumption and
production of energy, but through different emissions (CO2, SO2, NOx benzene and heavy metals). But
are these emissions of different pollutants linked? Does an increase of energy consumption leads to
comparable increases for these emissions? To assess this, emissions of three pollutants (SO2, NOx and
mercury) were plotted as a function of the CO2 emissions, for the production of 1 MJ of electricity by
the eight energy productions used in this study (six average country mixes and the two marginal) in
Figure 31.
From the figure, it can be observed that the emissions of the three pollutants SO2, NOx and mercury
are pretty much following the emissions of CO2. For example, an increase in a GWF due to energy use
should be associated with increases in impacts on AC, NE, ETwc, HTs and HTw.
So the GWF gives a good first estimation of the environmental performances of a waste management
system, if it is kept in mind that it is the only impact category taking into account the landfills’
performances in terms of methane emissions. To get a more accurate view of the other impact
potentials, direct emissions presented in the last column of Table 17 as well as avoided processspecific emissions related to aluminium recycling should be looked into more details. Only impact
potentials on stored ecotoxicity have no link to GW, as they are only due to heavy metal content of
residual waste.
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1.5
150
PL
GR, Hard coal
Hg
1.0
100
UK, DE, Nat. Gas, DK
0.5
50
0.0
µg Hg emitted / MJ
mg SO2 and NOx emitted / MJ
SO2
Nox
0
0.0
0.1
0.2
0.3
0.4
Kg fossil-CO2 emitted / MJ
Figure 31: Emissions of SO2, NOx (left y-axis) and mercury (right y-axis) to the air as a function of emissions of
CO2, for the production of 1 MJ of electricity, with the 8 datasets used in this study.
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Part VII - Conclusion
The study presented an impact assessment of the treatment of one tonne of MSW today in different
European member states. The differences in waste management and technologies’ performances
lead to a quite broad range of impact assessments for many impact categories, including global
warming.
The sensitivity analyses showed how some parameters were particularly central: these are both
external (e.g. the energy production of country) and internal (e.g. energy recovery or landfill gas
collection).
Take home messages
-
Recycling gives important benefits, and more particularly for aluminium and paper. Savings from
aluminium recycling are mainly linked to energy use and process-specific emissions during virgin
material production of aluminium.
-
Energy recovery at incinerator and landfill gives high environmental benefits in many impact
categories if energy recovery efficiency and landfill gas collection rate are high enough to
outweigh impacts from direct emissions. These benefits are very linked to the energy substituted.
-
Energy and material recoveries have comparable impact savings, if the energy recovery at the
incinerator is efficient. The energy and material substitutions (external parameters) will
determine whether one gives the highest benefits or the other.
-
At landfills, it is essential to collect the methane as efficiently as possible, to limit detrimental
impacts on global warming. The energy recovery and the oxidation rate in the top cover have also
significant roles.
-
Mechanical biological treatment offer good opportunities: obtaining RDF with both high LHV and
low metal content which allows for direct coal substitution at power plant, while decreasing the
organic content of residual waste which reduces landfill gas emission potential. Yet the RDF have
to fulfil particular quality criteria (e.g. chlorine and heavy metals contents).
-
Waste composition has a relatively small influence compared to other parameters. For
incineration, the LHV of the waste is quite important but the decisive factor is the energy
recovery efficiency. For landfills, the organic content of the waste is correlated to direct methane
emissions, but the key parameter is the landfill gas collection efficiency.
-
Energy substitution is of primary importance when assessing waste management systems. The
substituted technology should always be looked at carefully or several representative options
should be compared like in this study. The quality of energy is important in terms of carbonintensity but also sulphur, nitrogen oxides, benzene and mercury emissions.
-
All impact assessments except stored ecotoxicities are much linked to energy consumption and
production, so GWF is a relatively robust indicator of environmental performances of waste
management systems. Yet, some emissions of pollutants are specific to impact categories, e.g.
mercury and NOx emissions at incineration and avoided specific emissions from aluminium
recycling.
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Further work
The study highlighted questions and identified uncertainties that should be addressed in further
work, in order to get a more accurate assessment of the environmental performance of waste
management in Europe.
First, considering the large influence of the energy production in results of almost all impact
categories, a more detailed analysis of the energy systems of the member states would reduce the
uncertainty on that external parameter. Moreover a study to determine the marginal energy
production in all countries would be necessary to perform a consequential LCA.
Benefits from recycling being quite high, a comparative study on different life cycle inventories of
recycling processes would be essential to determine more precisely the uncertainties and potentially
reduce them. Besides, a study of marginal recycling technologies would be of interest for a
consequential LCA.
Only municipal solid waste was considered in this study, but as it represents approximately 12 % of
all waste generated in the EU, a look at the other waste streams could demonstrate more accurately
the impacts of waste management and its potential benefits if managed appropriately.
Finally, environmental assessment of waste management systems is only one of the three
constituent parts of sustainable development. A study on social and economic issues should bring a
more comprehensive insight on the issue of waste management.
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Appendixes
Appendix 1: EASEWASTE model
From www.easewaste.dk. (Kirkeby et al., 2005)
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Appendix 2: Literature research on waste compositions
Table 18 : MSW compositions in European countries found in the literature (NB: in bold are shown the waste
compositions used in this study)
Country
EU 15
EU 27
EU
Eastern Eur.
Northern Eur.
Southern Eur.
Western Eur.
ES-GR-PT
AT-DE-IT-LUNL-SE-CH
BE-DK
FR-UK-FI-NOIR
Denmark
Pap. /
Organic Plastic
Cardb.
Glass
29
18
29
21.8
30.6
17
27.5
22
31
31
31
30.1
23.8
36.9
24.2
46
8
12
8
6.2
13
11
5
11
10
8
11
23
35
20
Metal
Total
6
15
31
15
26.8
12
10.6
11
15
99
100
99
98.5
94.4
64.5
62.7
100
7
8
27
100
41
7
5
26
99
32
26
11
11
20
100
27
22
29
55
0.8
4
5
2
6
3
32
14
99.8
100
10.6
45.8
9.1
2.9
3.3
28.3
100
20
28
23
20
21
23
30
25
22
24
25
25
41
37
34
33
47
43
39
32
31
30
25
37
38
30
29
31
23
18
14
24
5
7
7
9
9
10
10
9
6
11
11
9
3
10
22
10
4
9
6
10
11
11
12
12
12
13
13
12
22
18
12
14
2
2
5
3
3
4
6
7
9
4
4
5
8
2
5
5
24
11
20
26
26
22
17
10
13
18
18
18
3
16
12
14
102
100
100
100
101
100
100
100
100
100
100
100
100
101
99
100
France
Germany
5
3
5
3.6
7
Other
Year
2000 (Sander, 2008) 2
(Sander, 2008)
1999 (Smith et al., 2001)3
2000
2000 (Eggleston et al.,
2000 2006)
2000
(European
Commission Joint
Research Centre,
2005) 4
2003 (OECD, 2007) 5
1985 (OECD, 2007)
(Koneczny et al.,
2003
2007)
2000 (Smith et al., 2001)
2005 (EASEWASTE, 2008)
2002
2000
1995 (OECD, 2007)
1989
1985
1980
1998 (Eurostat, 2003)
2000 (Smith et al., 2001)
1993
6
2000 (OECD, 2007)
2002
2
Data originate from a report of 2007 by OECD
3
Based on OECD data from 1999
4
Different sources were aggregated to build these waste compositions, especially EUROSTAT reports
5
Separate collection only
6
Separate collection only
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Greece
Poland
UK
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20
20
19
18
20
21
10
47
49
58
52
47
47
38
9
9
7
10
9
9
10
5
5
3
3
5
5
12
5
5
4
3
5
4
8
16
14
9
14
16
14
23
102
102
100
100
102
100
101
1997
1995 (OECD, 2007)
1985
1996 (Eurostat, 2003)
2000 (Smith et al., 2001)
9
37.5
11
11
2.1
29.4
100
2004
20.1
33
13.5
11.1
3.4
18.9
100
23
18
18
18
32
32
18
26
35
35
31
35
20
21
40
29
12
11
12
7
11
11
8
10
5
10
5
6
8
9
7
8
3
4
4
3
8
8
8
6
23
22
30
30
21
19
19
21
101
100
100
99
100
100
100
100
1990 (OECD, 2007)
(den Boer et al.,
2005)
(Koneczny et al.,
2003
2007)
2000 (Smith et al., 2001)
2005
2003
1997
2000
2000
(Sander, 2008)
(Fisher et al., 2006)
(Eurostat, 2003)
(Smith et al., 2001)
(OECD, 2007)
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Appendix 3: Mass flows of the six waste management systems
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Appendix 4: Processes used in the EASEWASTE model
Table 19 : Names of the processes used in the model
Electricity
Average country mix
Hard Coal
Natural Gas
Heat
Hard coal
Oil
Natural gas
Biomass
Waste
Incineration
Incinerator
Bottom ash
Electricity, High voltage, production DK, at grid/DK S
Electricity, Hard coal, at power plant/UCTE S
Electricity, Natural gas, at power plant/UCTE S
Ecoinvent
(V2.0)
Heat, at hard coal industrial furnace 1-10MW/RER S
Heat, heavy fuel oil, at industrial furnace 1MW/RER S
Heat, natural gas, at industrial furnace >100 kW/RER S
Heat, mixed chips from forest, at furnace 1000kW/CH S
Heat from waste, at municipal waste incineration plant/CH S
Ecoinvent
(V2.0)
Incineration, grate furnace, Aarhus, DK, 2006 (wet & semidry)
(EASEWASTE,
Bottom ash (MSWI)-landfill, Europe, up-to-date, 2008, 100 2008)
years
Landfill
Landfill
Conventional, Household waste, CHP energy recovery, 100 (EASEWASTE,
years, Generic
2008)
MBT
MBP
MBP, part 1/2, 2006, Germany (household waste)
MBP, part 2/2, 2006 Germany (household waste)
MBS
MBS dry-stabilate plant [Germany 2008]
RDF combustion
RDF-fired CHP plant-semi dry flue gas cleaning
Landfill after MBP
Landfill after MBT
Bottom ash (MSWI)-landfill, Europe, up-to-date, 2008, 100
years
Inert waste
Composting
Composting plant
Use on land
(EASEWASTE,
2008)
Composting, tunnel (Green waste), Treviso, IT
(EASEWASTE,
Composted digestate as fertilizer on farm land (plant farming), 2008)
DK, 2005
Recycling
Aluminium
Cardboard
Steel
Glass
Paper
Plastic
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Aluminium scrap to reprocessed aluminium (remelting),
Europe, 2000
*Paper (Different paper and board qualities) to cardboard
cores, tubes, liner and paper Skjern Papirfabrik A/S, Dk, 2005
(EASEWASTE,
Steel scrap to steel sheets, DK, 1992
2008)
Glass cullet to new products (remelting), Europe, 1990
Paper (Mixed high quality paper) to fine paper, Maglemlle +
Dalum, DK, 2007
Plastic (PE) to granulate, DK, 2000
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