inventory improvement project uk landfill methane...
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Inventory Improvement Project – UK
Landfill Methane Emissions Model Final Report to Defra and DECC
January 2011
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Report for:
Rebecca Peberdy, Lead Contractor Operations Manager, AEA
Stephen Nelson, Defra.
Helen Champion, DECC
Prepared by:
Dr Dominic Hogg
Ann Ballinger
Hans Oonk
Approved by:
Dr Dominic Hogg
(Director)
Contact Details
Eunomia Research & Consulting Ltd
37 Queen Square
Bristol
BS1 4QS
Tel: 0117 9172250
Web: www.eunomia.co.uk
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EXECUTIVE SUMMARY Eunomia Research & Consulting, with Hans Oonk of OonKay, was asked to review the
MELMod model used to model emissions from landfilling of waste in the UK. The
Specification asked for the review to:
identify and correct any errors, inaccuracies, inconsistencies or out-of-date
information and reduce any areas of uncertainty. Where accurate data and
assumptions are not currently available, estimates of probable ranges should be
provided.
It did not request a review of whether the modelling approach was the right one. The aim was
upon improving data and parameters within the existing model.1
The modelling of landfills is not an exact science, least of all when the attempt is made to
model at a national level. MELMod is a multi-phase model (as is the IPCC‟s Excel model)
which assumes that specific waste materials can be „deconstructed‟ into pools of rapidly,
medium, and slowly degrading carbon (the IPCC, by comparison, assigns a specific decay rate
to each material). Degradation in landfills is likely to be determined partly by the nature of the
materials, but also partly by the mix of materials landfilled, partly by the way in which some
materials are landfilled (either as large homogenous quantities of material, or as „material
mixtures‟) and partly by the local conditions in the landfill itself.
E.1.0 Activity Data A review of the model reveals that insufficient use has been made of the empirical data which
has been generated over the past fifteen years or so (it is also unclear where data from pre-
1995 years originated). The same applies to waste composition.
We have drawn upon data from all 4 countries of the UK to generate a revised dataset for the
last 15 years. Figure E. 1 shows the difference between the current MELMod data and the
proposed figures for municipal solid waste (MSW) (likely to be referred to, henceforth, as
„local authority managed waste‟). Probably reflecting the lack of updating, as well as the fact
that it was not known (when the data was last examined closely) that the landfill tax would
increase as it has done, and that the Landfill Allowances Schemes would have the effect they
have had, the data within MELMod overestimates quantities landfilled in recent years.
The divergence between the proposed figures and those in MELMod regarding non-MSW (i.e.
wastes from commerce, industry, construction and demolition) are even greater than for MSW
(see Figure E. 2). Whilst the data upon which our estimates are based remain of poor quality,
these figures represent an improvement upon the data in MELMod precisely because they
make effective use of those datasets which do exist.
We also built into our proposed changes projections of the quantity of landfilled waste, based
upon work undertaken by HM Treasury and Defra. These show a decline in landfilled MSW
and non-MSW up to the years 2019 and 2015, respectively.
1 At present, MELMod estimates emissions of methane on the basis of parameters used to characterise, for
example, landfill gas capture and oxidation. It does not draw upon data (proxy or otherwise) regarding actual
captures of landfill gas. Our work has centred on changes to the existing model, not proposals for an altogether
different approach.
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These proposals for change, as well as our proposals for a revised waste composition, were
accepted, and have been incorporated within MELMod. As a consequence of this, it became
necessary to develop a „smoothed‟ trajectory for landfilled waste to eliminate discontinuities
in the quantity of degradable organic carbon being landfilled in years before our projections
for MSW and non-MSW commenced (1995 and 1997 respectively).
Figure E. 1: Comparison between MELMod and Proposed
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Figure E. 2 Landfilled Waste, Excluding MSW
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E.2.0 Waste Characteristics The MELMod data regarding the moisture content and the carbon constituents of the waste
were reviewed. As far as biodegradable carbon is concerned, one main source of error in the
data currently used in MELMod is the implied assumption that where degradation is
concerned, it is sufficient to look only at cellulose and hemicellulose content. This is not
correct where materials such as food waste are concerned. In addition, some internal
inconsistencies in the modelling of the degradation of specific wastes were apparent.
These were addressed through reviewing the literature regarding moisture content of specific
biodegradable waste materials and their biochemical constituents (i.e., their fat, sugar,
protein, cellulose, hemicelluloses, lignin, etc. content).
We recommended a revised set of values for moisture and carbon content (as well as the
carbon constituents). These were accepted and incorporated into MELMod.
E.3.0 Degradable Organic Carbon There are ranges of values in the literature for the proportion of organic carbon which is likely
to degrade in landfills. Some studies make use of one value for all materials. However, if the
model is intended to have functionality at the material specific level, then this does not seem
appropriate given that different materials clearly behave differently.
We have reviewed the literature with a view to generating an internally consistent set of
figures for MSW and for C&I wastes. We recommended that the degradable proportion of
carbon be calculated through reference to the lignin and non-lignin fractions of the specific
waste streams. The degradation factors proposed are in line with evidence from work by
Eleazer et al.2 There is an ongoing debate regarding these values, and we expect this to
continue. We believe, however, that the proposal represents an improvement upon the
figures currently within MELMod. The proposal was accepted and the figures in MELMod were
changed accordingly.
E.4.0 Decay Constants (k-values) There are, generally, two approaches to dealing with the rate constants which determine the
pace of decay of biodegradable wastes in landfill. One is to treat the whole mass of waste as
degrading at some „average‟ rate, the other effectively assumes a range of k-values, either for
specific materials or, as in MELMod, for different fractions of each material. Neither approach
is perfect, but the latter at least has the merit of being capable of reflecting the effect on
emissions of (changes in) the composition of waste being landfilled.
MELMod splits specific materials into rapid, medium and slow degrading fractions. The
difference between the rates in the latest version of MELMod is relatively slight, with the rapid
degrading fraction being only marginally above the rates typically used to estimate the rate of
decay for „mixed waste‟ in single phase models. Furthermore, the assignment of carbon to the
rapid, medium and slow degradation categories is, in MELMod, unrelated to specific
constituents of waste.
We made two recommendations:
2 Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal Solid Waste
Components in Laboratory Scale Landfills, Environmental Science and Technology, 31, pp911-917
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1) that the rate constants should be linked to different constituents of the waste; and
2) that as far as rate constants were concerned, the IPPC defaults should be used
(reflecting the fact that, for the rapidly degrading fraction in particular, the rate in
MELMod appears much lower than is the case in most other multi-phase models, and
is close to the average decay rate in models representing mixed waste).
The first recommendation was accepted and reflected in the modelling of the degradation of
specific waste components. The second recommendation was not accepted.
E.5.0 Assignment of Waste to Specific Landfill Types MELMod allows users to specify up to 5 different landfill Types with different performance
levels. Landfilled waste is apportioned across these different Types. Their description
suggests they should behave differently, but for 3 of them, the key behavioural parameters
(gas extraction efficiency and oxidation rate – see below) are identical. Recommendations
regarding how to apportion waste across different site Types are only meaningful if the Types
correspond to sites with different characteristics. The interplay between the classification by
Type, the performance characteristics of each Type, and the apportionment of waste across
Types is crucial in determining overall levels of, for example, gas extraction efficiency.
We proposed a series of „linked‟ recommendations. Regarding the assignment of waste to
specific landfill Types, however, the magnitude of the task (in terms of understanding how, in
past years, landfilled waste has been apportioned across sites with different performance
characteristics) was simply too great for this project. Our recommendations focussed on
making effective use of the Types described in the model. We noted, however, that there
might be a variety of reasons why one might wish to have „additional Types‟ moving forward,
but that this would only be relevant if data allowed for accurate apportionment of waste
across those Types. Some of the apportionment within MELMod suggests quite abrupt, and
unrealistic switches of waste from one Type to another from a given year to the next.
We recommended, therefore, that:
1) The modelled performance (in terms of gas extraction and oxidation rate) of the Types
of landfill within MELMod should be consistent with their description;
2) That the assumptions regarding the proportions of waste being sent to different
landfill types is revised to reflect more gradual transitions of waste away from Type 2
sites;
3) That relevant agencies should seek to apportion waste being landfilled to different
landfill Types based upon the characteristics of the landfill where the material is being
emplaced (notably, in terms of its likely potential to extract / oxidise landfill gas
emissions).
These recommendations were not accepted.
E.6.0 Landfill Gas Extraction Efficiency It is important to appreciate the distinction between instantaneous landfill gas extraction
efficiencies (i.e. those achieved at a given point in time) and integral (or lifetime) extraction
efficiencies (the levels achieved over the life of the landfill). Instantaneous extraction
efficiencies vary over the life of a given landfill and may be close to 100%, especially in later
years post-capping, even where the extraction efficiency over the lifetime of the landfill may
be rather low. Given that MELMod is a national level model, no one knows (and no one knew,
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in past years) when, in the lifetime of a specific landfill, waste is being deposited.
Consequently, in MELMod, the relevant figure for the extraction efficiency is likely to be that
achieved over the lifetime of the site.
For all the Types of site assumed to be accepting waste more recently, relatively high
extraction efficiencies (rising to more than 76%, then flattening off at 75% in future) are used
in MELMod. This is true even for a Type of landfill described as having no gas collection
system in place. These are some of the most significant assumptions within MELMod, yet the
basis for them is not clear.
We made the following recommendations:
1) Because MELMod is not a model based upon a summation of emissions modelled for
each individual landfill, the use of integral collection efficiencies for each landfill Type
is appropriate (rather than, as currently, changing profiles over time for each Type);
2) Since MELMod assumes extraction rates which are the same for each of the landfill
Types (1, 2 and 3) receiving waste since 1980, methane is assumed to be extracted at
high rates (in recent years) even from sites which are described as having no gas
collection system in place. These figures should be changed;
3) In the absence of clear bases for the assumptions used regarding capture rates, and
partly to encourage the generation of information allowing lifetime extraction
efficiencies to be understood, we recommended that the IPCC default figure (20%)
should be used for those sites with gas extraction equipment in place. We
subsequently proposed an amended set of values to reflect three distinct types of
landfill (0% for those with no gas extraction (Type 1), 20% for those with limited gas
extraction equipment (Type 2) and 50% for the most modern landfills (Type 3).
These recommendations were not accepted and so MELMod retains the existing assumptions
regarding gas extraction efficiencies.
E.7.0 Other Recommendations On the basis of a review of literature and consideration of the evidence, a number of other
recommendations were made. These were as follows:
1. We recommend continuing with the 10% figure for oxidation used for Type 3 landfills
in MELMod. This should be kept under review, reflecting literature which suggests this
value may be too low; and
2. There is no strong reason to change the assumption that the methane content of
landfill gas at the 3 newer Types of landfill in MELMod is 50%
3. The same proportion should be extended to cover older Type 4 landfills in the absence
of a far more fundamental overhaul of the modelling of the Type 4 sites since the
presumption that a lower methane concentration would follow from the existence of
partly aerobic conditions ought also to consider that fractions of waste such as lignin
will degrade to a greater extent under such conditions.
The first two were accepted, but the third was not, so no changes were made as a result.
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Contents E.1.0 Activity Data ...................................................................................................................... i
E.2.0 Waste Characteristics .................................................................................................... iii
E.3.0 Degradable Organic Carbon ........................................................................................... iii
E.4.0 Decay Constants (k-values) ............................................................................................ iii
E.5.0 Assignment of Waste to Specific Landfill Types ............................................................. iv
E.6.0 Landfill Gas Extraction Efficiency ................................................................................... iv
E.7.0 Other Recommendations ................................................................................................ v
1.0 Introduction ....................................................................................................................... 1
1.1 Objectives ............................................................................................................................ 1
2.0 Context ............................................................................................................................... 1
3.0 The MELMod Model and the Scope of the Review ........................................................... 2
4.0 Activity Data (Waste Quantities Landfilled and Waste Composition)................................ 4
4.1 Summary and Key Recommendations .............................................................................. 5
5.0 Waste Properties ............................................................................................................... 8
5.1 Summary .............................................................................................................................. 9
6.0 The Proportion of Organic Carbon that is Dissimilable ..................................................... 9
6.1 Summary ........................................................................................................................... 11
7.0 Rate Constants ................................................................................................................ 16
7.1 The Approach Taken by MELMod.................................................................................... 16
7.2 Values Presented Within the Literature .......................................................................... 17
7.3 Rate of Degradation of Different Biochemical Constituents ......................................... 20
7.4 Summary ........................................................................................................................... 21
8.0 Landfill Gas Extraction Rates .......................................................................................... 23
8.1 Introduction and Summary .............................................................................................. 23
8.2 Definition of Extraction Efficiency ................................................................................... 23
8.3 Interpretation .................................................................................................................... 25
8.1 Summary ........................................................................................................................... 31
9.0 Oxidation Rates for Uncaptured Methane ....................................................................... 33
9.1 Basis for Revising the IPCC Default Value ...................................................................... 33
9.2 Summary ........................................................................................................................... 34
10.0 Assignment of Wastes to Types of Landfills ................................................................. 35
11.0 Landfill Types ................................................................................................................ 38
12.0 Landfill Gas Composition ............................................................................................. 42
12.1 Summary ....................................................................................................................... 43
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13.0 Recommendations and Changes Made in MELMod .................................................... 44
13.1 Recommendations ........................................................................................................ 44
14.0 References ................................................................................................................... 50
A.1.0 Chronology of Development of MELMod ...................................................................... 59
A.2.0 Waste Quantities and Composition .............................................................................. 60
A.2.1 Municipal Waste ............................................................................................................ 60
A.2.2 Commercial, Industrial and C&D Waste ....................................................................... 66
A.2.3 Construction and Demolition Wastes ........................................................................... 70
A.2.4 Our Approach ................................................................................................................. 70
A.2.5 Forward Projections ....................................................................................................... 94
A.3.0 Characteristics of Component Waste Streams ............................................................ 96
A.3.1 Moisture Content ........................................................................................................... 96
A.3.2 Organic Carbon Content of Waste Materials ............................................................ 105
A.4.0 Evidence Regarding the Extent of Degradation of Carbon in Landfills ......................115
A.4.1 Dissimilation Factors for MSW from the Literature .................................................. 118
A.4.2 Maximum Degradation under Anaerobic Conditions ............................................... 119
A.4.3 The Influence of Landfill Conditions on Degradation ............................................... 122
A.4.4 Evidence from Landfill Excavation............................................................................. 122
A.4.5 Landfill Model Calibration Studies ............................................................................ 128
A.5.0 Extraction Efficiency: Issues and Evidence ................................................................132
A.5.1 Engineering Considerations on Extraction Efficiency ............................................... 132
A.5.2 Economic and Environmental Optimal Gas Recovery .............................................. 133
A.5.3 Literature on Extraction Efficiency ............................................................................. 134
A.5.4 Other Considerations .................................................................................................. 139
A.6.0 Methane Oxidation Rates ...........................................................................................146
A.6.1 Processes Determining Methane Oxidation ............................................................. 146
A.6.2 Measurement of Methane Oxidation ........................................................................ 147
A.6.3 Results of Measurements .......................................................................................... 148
A.7.0 Methane Content of Landfill Gas ...............................................................................154
A.7.1 The Stoichiometry of Methane Formation ................................................................ 154
A.7.2 The Influence of Landfill Conditions .......................................................................... 154
A.7.3 The Changing Composition of Landfill Gas over Time.............................................. 155
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Glossary
AD Anaerobic Digestion
BAT Best Available Technology
BMP Biological Methane Potential
CDEW Construction Demolition and Excavation Waste
C&D Construction and Demolition
C&I Commercial and Industrial
DCLG Department for Communities and Local Government
DDOC Decomposable Degradable Organic Carbon
DECC Department of Energy and Climate Change
Defra Department for Environment, Food and Rural Affairs
DOC Degradable Organic Carbon
EWC European Waste Catalogue
FOD First Order Decay
GasSim Landfill model developed for the UK Environment Agency
GHGs Greenhouse Gases
HMRC HM Revenue & Customs
HMT HM Treasury
HPLC High Pressure Liquid Chromatography
HWRC Household Waste Recycling Centre
IPCC Intergovernmental Panel on Climate Change
LAC Local Authority Collected
LandGem Landfill model used by USEPA
LAS Landfill Allowance Schemes
LCA Life Cycle Assessment
LFG Landfill Gas
LFGTE Landfill Gas-to-energy
MBT Mechanical Biological Treatment
MELMod Methane Emissions from Landfills Model
MSW Municipal Solid Waste
NIEA Northern Ireland Environment Agency
ORWARE Organic Waste Research lie cycle assessment model (Swedish)
PFA Pulverised fuel ash
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SEPA Scottish Environment Protection Agency
UN-FCCC United Nations Framework Convention on Climate Change
US EPA US Environmental Protection Agency
WAG Welsh Assembly Government
WRATE Waste and Resources Assessment Tool for the Environment.
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1.0 Introduction Eunomia Research & Consulting Ltd („Eunomia‟), along with Hans Oonk of OonKay,
was asked to carry out this project, the Inventory Improvement Project – UK Landfill
Methane Emissions Model. This report presents the findings of the project and our
recommendations. It also details the changes which have been made to the methane
emissions model, MELMod.
1.1 Objectives
The work was undertaken in two phases reflecting the project specification. In the
first phase of work, the objective was to undertake a thorough review of the MELMod
model, and the data and assumptions which were contained within it, in order to
„identify and correct any errors, inaccuracies, inconsistencies or out-of-date
information and reduce any areas of uncertainty.‟ Key areas for investigation were
expected to be:
the emissions factors included for different types of waste (DOC, DDOC)
and rates of decay);
the assumptions around oxidation through the cap (including oxidation rate
if gas escape through cracks and fissures was minimal);
the different categories of waste types (for example food, paper, etc)
included in the model, and how these could be improved to more
accurately reflect emissions, and to allow detailed policy analysis;
the composition of waste sent to landfill; and
the relevance and appropriateness of waste site type definitions.
Following the initial review, decisions were made by Defra & DECC, informed by Peer
Reviews of the initial work, as to which of the recommendations made in the review
should be carried forward.
2.0 Context The context for this Project is one where the UK is striving to reduce emissions of
greenhouse gases (GHGs) by 80% by 2050 (relative to 1990 levels) with interim
budgets as set out below.
Table 2-1: Legislated Carbon Budgets and Split between Traded and Non-traded
Sectors
Budget 1
2008-2012
Budget 2
2013-2017
Budget 3
2018-2022
Carbon budgets (Mt CO2 equ.) 3018 2782 2544
Percentage reductions below 1990
levels 22% 28% 34%
Source: DECC
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It is often stated that „the waste sector‟ contributes 3% of the UK‟s GHG emissions.
The reality is that the emissions referred to are those associated with landfilling, and
they refer to emissions within the UK‟s inventory as reported to the IPCC. The
contribution is significant in the context of the national inventory, but it does not
represent the totality of the impact associated with the management of waste,
whether this is being reported in the manner suggested by the IPCC for national
inventories, or in terms of the global consequences of managing waste.
3.0 The MELMod Model and the Scope of the
Review As the basis for their reporting to the IPCC (and following the Guidance above), most
countries use a model of landfill emission which is similar, in functional form, to the
MELMod model, which is the subject of this review. In essence, these are first-order
exponential decay (FOD) models which are driven by parameters describing either the
whole waste stream (single-phase), or specific sub-streams / materials (multi-phase)
which make up the totality of landfilled waste.
The IPCC proposes three possible approaches (referred to as „Tiers‟) to landfill
modelling. MELMod is compatible with the First Order Decay (FOD - Tier 2)
methodology for estimating methane emissions from Solid Waste Disposal Sites
described in the 2000 edition of the Intergovernmental Panel on Climate Change
(IPCC) Guidelines and with the Tier 3 approach (which allows the use of country-
specific parameter values).
The IPCC acknowledges that its approach is a simple one:
Transformation of degradable material in the SWDS to CH4 and CO2 is by a
chain of reactions and parallel reactions. A full model is likely to be very
complex and vary with the conditions in the SWDS. However, laboratory and
field observations on CH4 generation data suggest that the overall
decomposition process can be approximated by first order kinetics (e.g., Hoeks,
1983), and this has been widely accepted. IPCC has therefore adopted the
relatively simple FOD model as basis for the estimation of CH4 emissions from
SWDS.
It is important, therefore, to understand that the IPCC FOD model is as much a
political construct as it is a scientific one. It has been based around the need to have
some basis for measurement (and comparison between countries) of emissions from
landfill for the reporting of inventories. It has not been based on a desire to develop a
perfect, scientifically accurate model. The model was not designed to enable detailed
policy analysis on the part of the users.
It is interesting to consider how national modelling might be distinct from models
which are based around modelling a specific landfill. A model which seeks to
understand a specific landfill (such as GasSim or the US model LandGem) will
generally be able to consider different phases of a landfill, and how the gas
generation varies over time at that specific site, at the site in question. A national
model could, in principle, do this if it was based upon a bottom up approach,
including a model of each landfill site in the UK. This is not the approach adopted in
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MELMod. As long as this is the case, factors such as „gas extraction rates‟ and
„proportion of carbon degrading which produces methane‟ have to consider what
these might be „on average‟ over the lifetime of a given type of landfill site (since the
model will not show exactly when in the life of the landfill the waste materials are
being deposited). This suggests that national models will need to consider values for
some parameters which reflect „lifetime effects‟.
It is worth stating at the outset that the model being reviewed – MELMod – is a model
which has updated the earlier national assessment model which was, itself,
developed through various iterations. The chronology of the development of MELMod
and its successors is shown in Appendix A.1.0.
It is important to note that the specification did not ask for a review of whether the
modelling approach in MELMod was the right one. The focus was, therefore, upon
improving data and parameters within the model rather than suggesting how the
approach to modelling might be revised.3
The Specification noted that Phase 1 of the work should include suggested
improvements, and the means of verifying the accuracy of these. We take the view
that whilst the review can suggest improvements, verifying the accuracy of these is
extremely difficult for two reasons:
1. The first relates to the ability of any landfill model (whether national or specific
to a given site) to be verified in a meaningful sense. All FOD models will, by
definition, have a similar shaped degradation curve. The exact shape will be
determined largely by the amount of carbon degraded and the rate of decay,
with estimated emissions being affected by the assumptions regarding landfill
gas extracted, and the extent of oxidation of methane at the cap (and in other
ways). In order to even generate the „right‟ modelled estimates, multi-phase
models, such as MELMod, require one to have a good understanding of the
composition of waste being landfilled over time. In the case of the UK, this
situation cannot be said to exist, neither in the past (for all wastes), nor in the
present (for the waste landfilled from commerce, industry, and construction
and demolition). In order to validate any such a model with data from the real
world, as well as having the aforementioned information, it would be
necessary, periodically over time, and during different phases of a landfill‟s
operation, to measure the quantity of gas collected for flaring and for energy
generation, its composition, as well as (simultaneously) measurements of the
fugitive emissions of gas from the landfill. To our knowledge, there has been
no study which fulfils these requirements (and they are unlikely to be met for
many years to come);
2. The second relates to the quality requirements of the IPCC in respect of
reporting. The Specification rightly highlights the possibility that some
3 This is an important point. At present, MELMod estimates emissions of methane on the basis of
parameters used to characterise, for example, landfill gas capture and oxidation. It does not draw
upon data (proxy or otherwise) regarding actual captures of landfill gas. Our work has centred on
changes to the existing model, not proposals for an altogether different approach.
4
suggested improvements to the model might not follow IPCC Guidance. As
importantly, they might not meet IPCC requirements in respect of Inventory
Quality Assurance / Quality Control.4
Reflecting the above, there is no consideration given to validation in this work. The
data which would allow this to take place is not available. This is a field where the
scientific evidence is somewhat fragmentary, and where models seem rather more
prevalent than relevant field measurements.
4.0 Activity Data (Waste Quantities Landfilled
and Waste Composition) MELMod splits the quantities being landfilled between:
1. Municipal Waste; and
2. Commercial and Industrial Waste.
The quantitative data and the assignment of the waste quantities to specific
categories were both closely scrutinised.
In an earlier report on the previous national assessment model, written in 2006, it
was noted:5
Up until 1994 the waste arisings data are the same as that used for the AEA
model (Brown et al., 1999) and are based on waste surveys in the UK using
actual data combined with population data where necessary. After 1994, data
are based on a new study carried out by a UK consultancy ERM for input to
the LQM model, which uses updated waste survey data gathered by the
Environment Agency for 1999. Years between 1995 and 1998 inclusive are
extrapolated backwards from the 1999 data and years ahead of 1999 are
extrapolated based on a projected scenario of waste disposal. The Golder
(2005) model has revised MSW arisings from 2001 based on the Local
Authority Waste Recycling and Disposal (LAWRRD) model (AEA Technology,
2005). The LAWRRD model provides arisings for England and so the data has
been scaled upwards, assuming England represents 83% of the UK's total. A
comparison between the LAWRRD data and actual waste arisings for 2002
and 2003 showed a discrepancy of 2% and 4%, respectively. These
differences are considered insignificant and the LAWRRD model data were
taken to be representative of the current situation.
This paragraph highlights the fact that insufficient use has been made of the
empirical data which has been generated over the past ten to fifteen years or so,
especially in respect of municipal waste (much of which is discussed in Appendix
4 IPCC (2006) IPCC Guidelines for National Greenhouse Gas Inventories (2006). Chapter 3 - Solid
Waste Disposal, http://www.ipcc-nggip.iges.or.jp
5 S. L. Baggott et al (2006) Addendum to UK Greenhouse Gas Inventory, 1990 to 2004, Annual Report
for submission under the Framework Convention on Climate Change, Report RMP/2106, July 2006
5
A.2.0). This was also highlighted by AEA in their review of the data in the national
assessment model (which was adopted for MELMod).6
Similar comments can be made in respect of waste composition. The data in MELMod
for local authority collected waste is outdated, and has been for some time (again,
sources in Appendix A.2.0 highlight the availability of relevant data over the period
during which various revisions to the model were made). Since emissions of methane
in MELMod are related back to waste composition, then how waste composition
changes over time becomes important. This ought to be based upon empirical data
rather than assumption.
It is clear, given the lack of use made of recent data, that both the quantitative figures
and the composition data are in need of updating. Data in MELMod reveal that
municipal waste composition data is still based upon data gathered in the early
1990s, and which was superseded almost ten years ago.
4.1 Summary and Key Recommendations
We have reviewed the available data for municipal waste, commercial and industrial
waste, and construction and demolition waste (see Appendix A.2.0). We have drawn
upon data from all 4 countries of the UK to generate a revised dataset for the last 15
years. This covers municipal solid waste (see Table 4-1) and the non-municipal
fractions (see Table 4-2).
We recommend that the data in MELMod model be updated to include our activity
data and the associated waste compositions. The confidence we have in our
proposals for local authority managed waste is as high as it can be, recognising that
there will always be limitations in this regard.
Where C&D and C&I wastes are concerned, we have had to incorporate rather more
by way of estimates and generalising assumptions. The data remains extremely poor
in terms of its quality, and this applies with special force to our knowledge of the
composition of the waste generated, and being landfilled. Notwithstanding these
points, the data which we have derived is based upon the best data which existed at
the time of writing.
We believe, therefore, that our activity data for C&I and C&D waste constitutes a
significant improvement upon that which exists in the existing model. Sadly, however,
one cannot express a high level of confidence in the overall quality of this data. There
is a pressing need to improve upon the quality of the data which characterises how
much C&I and C&D data there is, what it actually looks like, and how it is managed.
It should be noted that we believe it would be desirable to split the waste streams
down further into household waste, commercial waste, industrial waste and
construction and demolition waste. MELMod would also benefit, in future, from
having a far greater number of rows available to characterise the composition of each
of these waste streams.
6 AEA (2008) Revision of UK Model for Predicting Methane Emissions from Landfills Task 3 Report –
Review of Methodology, Data Quality & Scope for Improvement, Report to Defra, October 2008
6
Table 4-1: Revised Figures for Landfilled Local Authority Managed Waste (Municipal Waste) for the UK (tonnes)
1995/96 1996/1997 1997/1998 1998/1999 1999/2000 2000/2001 2001/2002 2002/2003 2003/2004 2004/2005 2005/2006 2006/2007
Paper 5,988,937 5,325,247 5,075,239 4,511,984 4,159,711 3,655,984 3,769,188 3,760,145 3,633,752 3,546,697 3,245,393 3,046,934
Card 1,921,165 1,703,795 1,616,612 1,432,222 1,316,817 1,151,434 1,255,161 1,315,672 1,322,296 1,353,753 1,301,879 1,282,904
Textiles (and footwear) 594,250 624,561 699,106 737,030 811,593 855,630 886,243 873,827 868,558 852,475 792,825 786,586
Miscellaneous combustibles 330,231 328,500 348,890 352,565 380,331 384,712 464,653 544,342 582,804 646,098 664,723 848,899
Food 5,424,359 5,290,261 5,555,858 5,509,110 5,709,859 5,726,952 6,006,865 6,117,595 5,968,800 6,006,076 5,708,885 5,548,669
Garden 1,870,139 2,467,310 3,229,041 3,834,326 4,589,298 5,231,592 4,922,068 4,398,287 3,782,905 3,053,382 2,250,167 1,475,826
Soil and other organic waste - 163,722 343,728 505,770 684,070 852,760 834,274 785,631 708,675 633,060 533,329 464,987
Wood 988,282 983,604 1,055,427 1,066,339 1,125,196 1,148,878 1,117,572 1,047,798 924,108 793,964 652,900 529,849
Sanitary / disposable nappies 542,623 531,273 559,242 558,828 572,784 578,192 634,909 684,319 701,576 726,589 718,992 740,337
Furniture 356,194 353,423 375,834 377,958 399,551 405,558 424,959 433,783 429,547 426,897 406,137 406,683
Mattresses - - - - - - 10,738 22,030 32,731 43,225 51,074 60,862
Other 8,443,883 7,979,258 8,123,726 7,785,868 7,807,565 7,582,865 7,738,168 7,641,918 7,287,850 6,968,141 6,336,048 6,141,309
TOTAL 26,460,062 25,750,955 26,982,702 26,672,000 27,556,774 27,574,555 28,064,798 27,625,347 26,243,602 25,050,357 22,662,352 21,333,845
Note: It is appreciated that the figures suggest an unjustified level of accuracy – we merely show the figures in their entirety as
calculated for completeness.
Note that furniture and mattresses are treated as composite materials. On a fresh matter basis, furniture in MSW is assumed to
be 62% wood and 5% textiles; mattresses are considered to be 50% textiles (clearly these are only the biodegradable
components).
7
Table 4-2: Suggested Revision to MELMod data, C&I and C&D Wastes (million tonnes)
1997/98 1998/99 1999/2000 2000/2001 2001/2002 2002/2003 2003/2004 2004/2005 2005/2006 2006/2007 2007/2008 2008/2009
Commercial
Paper and Card 9.12 8.92 8.71 8.88 8.70 8.41 7.64 6.76 6.10 5.09 4.95 4.48
General industrial waste
Food 6.17 6.09 6.10 6.32 6.30 6.26 5.91 5.66 5.23 4.94 4.70 4.36
Food effluent / Biodeg Ind Sludges (from
1997) 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.03
Abattoir waste
Misc processes
Other waste
Misc Comb 2.10 2.05 2.02 2.13 2.05 1.97 1.75 1.56 1.37 1.21 1.13 1.00
Furniture 0.08 0.08 0.07 0.07 0.07 0.07 0.06 0.06 0.05 0.05 0.05 0.04
Garden 1.07 1.08 0.99 0.99 1.04 1.03 1.03 1.03 1.00 0.99 0.94 0.89
Sewage sludge
Textiles / Carpet and Underlay 0.91 0.89 0.87 0.92 0.89 0.85 0.76 0.67 0.59 0.52 0.48 0.43
Wood 3.26 3.35 3.10 3.01 3.08 3.04 2.96 2.87 2.75 2.59 2.35 2.04
Sanitary 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.04 0.04 0.04 0.04
Other 47.02 44.89 44.41 42.95 39.53 42.44 45.35 44.41 42.95 40.20 36.87 34.24
Proposed Revision 69.82 67.44 66.36 65.37 61.74 64.17 65.56 63.10 60.13 55.67 51.53 47.56
Note: Furniture is treated as composite materials. On a fresh matter basis, furniture in non-MSW is assumed to be 50% wood.
8
5.0 Waste Properties The crucial part of how MELMod models the gas generated by different materials
when landfilled is the way in which it estimates the quantity of carbon, per tonne of
waste landfilled which is „decomposable degradable organic carbon‟ (DDOC). The way
in which this is calculated is relatively straightforward:
Each material / stream is assigned:
a) a moisture content (% fresh matter) (=A);
b) a proportion of cellulose (=B) and a proportion of hemicellulose (in dry
matter terms) (=C) ; and
c) a proportion of the cellulose and hemicellulose which is considered to
degrade (as % dry matter) (=D, sometimes referred to as DOCf).
The quantity of carbon deemed to degrade per tonne of the material landfilled
is then given by:
DDOC = (1-A) x (B + C) x D x E
where E is the proportion of the mass of cellulose / hemicellulose
deemed to be carbon.
The figures used in MELMod are essentially based upon one piece of work by Morton
Barlaz in 1997. LQM, who were involved in a revision of the national assessment
model, whose parameters MELMod retains, noted:7
The amount of degradable carbon that produces landfill gas is determined
using the mass (expressed on a percentage dry weight basis) and
degradability (expressed as a percentage decomposition) of cellulose and
hemi-cellulose using data provided by Barlaz et al. (1997).
The review by AEA suggested some problems with these figures:
In their revision of the national assessment model in 2002, LQM introduced a
new method of calculating decomposable degradable organic carbon (DDOC),
based on the cellulose and hemicellulose content of waste components
developed by the United States Environmental Protection Agency (US EPA),
with data on key parameters such as moisture content and the fraction of
degradable organic carbon that degrades under landfill conditions (DOCF )
being taken from a variety of published sources. This increased the overall
DDOC available for conversion to methane and was necessary, in LQM‟s view,
because the model developed by AEA (1999) and calibrated against field
measurements of emissions from landfills, underestimated methane
formation. Although a number of references are cited in the LQM report to
support this approach and some parameter values, the report does not
7 LQM (2003) Methane Emissions from Landfill Sites in the UK, Final Report to Defra, January 2003.
9
provide sufficient detail to allow individual values to be checked against the
named sources. This could be a significant source of error, as some of the
values quoted appear to lack consistency. For example, paper and card
components in MSW is said to have a DOCF value of 61.8 per cent, yet the
corresponding value for this component in the C&I waste stream is 85 per
cent.
LQM cite the new approach for calculating DDOC as having been incorporated
into the Environment Agency „WISARD‟ life cycle tool8, the HELGA framework
model and the Environment Agency‟s GasSim model
AEA recommended that further work should be undertaken to determine the reliability
of information in the model that is used to generate estimates of DDOC.
5.1 Summary
Mindful of the existing structure of MELMod, we have sought to understand how the
characteristics of waste streams might be given greater internal consistency, and a
more coherent logical framework. The assumptions from predecessor models reflect
an assumption, for example, that all methane results from degradation of cellulose or
hemicelluloses. For materials such as food, this is likely to lead to underestimation of
the extent to which degradation takes place.
We have reviewed the literature for appropriate values for the moisture content of
different biodegradable components of the waste stream (see Appendix A.3.0), and
have also sought information which characterises the biochemical constituents of
these waste streams (beyond simply the cellulose and hemicellulose content).
The values we recommend for use in MELMod are set out in Table 6-1 below. These
highlight degradable components such as fat, protein, the readily soluble organic
fraction, starch, sugar and fibre. All of these are degradable in landfills, but they are
neither cellulose nor hemicelluloses, which are the only biodegradable components
currently contributing to methane emissions in MELMod.
6.0 The Proportion of Organic Carbon that is
Dissimilable In the current MELMod data, the proportion of degradable carbon which is assumed
to be dissimilated (sometimes labelled DOCf) shows considerable variation between
the municipal waste stream, and the commercial and industrial waste stream. Whilst,
for example, 20% by weight of mixed commercial and industrial waste is assumed to
be carbon which leads to gas generation, only one fraction of municipal waste
reaches double figures in this regard.
8 WISARD has since been superseded by WRATE – Waste and Resources Assessment Tool for the
Environment.
10
Table 6-1: Suggested Values for Moisture (as % fresh matter), and for Biochemical Components (as % dry matter)
Moisture Cellulose Hemicellulose Lignin Fat Protein Readily
Soluble Starch Sugar
Paper 15% 61% 9% 15%
Card 20% 61% 9% 15%
Textiles 20% 20% 20%
Misc combustibles 20% 25% 25%
MSW Food 70% 28% 4% 6% 15% 16% 14% 7%
Garden 55% 19.80% 16% 19.70% 1.50% 25.90%
Wood 17% 41.50% 12% 25.50%
Nappies 65% 47.30%
C&I Food 70% 11% 11% 5% 6% 18% 0 36% 7%
11
There does not appear to be any supporting rationale for these differences given the
similarity in some of the materials across the two streams. Similar concerns around
the internal consistency of these figures have already been raised by AEA.9
We have attempted to address these matters so as to ensure both internal
consistency, and supportable figures for the amount of carbon in different materials
which is likely to degrade. It is worth stating that how one arrives at the appropriate
value of the degradable organic carbon in waste is less important than the values
which ultimately enter the model. MELMod seeks to classify each material into rapid,
medium and slow degrading fractions and our approach suggested below reflects our
views as to how this might best be done (if there are components of each material
which degrade faster or slower, what would be the most plausible rationale for that?).
This is not to imply that this is necessarily the best approach to the modelling.
6.1 Summary
In Appendix A.4.0, we have reviewed dissimilation factors cited within the literature.
We have also reviewed the theoretical extent of the degradation of the different
materials that might be expected under “ideal” anaerobic conditions. We have also
considered the evidence taken from operating landfills.
This body of evidence suggests there are ranges of values in the literature for the
proportion of organic carbon which is likely to degrade in landfills. Single-phase
models effectively make use of one value for all materials. Some multi-phase models
also use a single value for all materials (including the IPCC default model). Other
multi-phase models use a specific value for each material. In the spirit of this
approach, a recent consultation on modelling of landfill emissions in Australia
suggested the factors shown in Table 6-2.10
MELMod has functionality at the material specific level, and policy makers are known
to want to understand the effect of addressing specific materials through waste policy
measures. A single value, therefore, might not be deemed so appropriate given that
different materials clearly behave differently. MELMod also seeks to characterise
each material by component parts, and then assigns the carbon from those parts into
three pools of carbon, each of which has a common decay rate for all materials in the
model. This approach seems to us to be less flexible, and rather more complicated
than it needs to be (suggesting, also, a level of detail in the extent of our knowledge
which does not obviously exist, as the evidence in our review in Appendix A.4.0
suggests). Certainly, one of the factors that affects the extent of biodegradation is the
material itself, with lignin playing a role, but one which is not entirely well understood.
Another factor of relevance is the nature of the landfill itself, with the potential for
9 AEA (2008) Revision of UK Model for Predicting Methane Emissions from Landfills Task 3 Report –
Review of Methodology, Data Quality & Scope for Improvement, Report to Defra, October 2008.
10 Department of Climate Change and Energy Efficiency (Australian Government) (2010) Review of the
NGER (Measurement) Determination, Discussion Paper, August 2010,
http://www.climatechange.gov.au/government/submissions/reporting/~/media/publications/greenh
ouse-report/review-nger-measurement-determination-paper.ashx
12
degradation to theoretical maximum levels likely to vary across the volume of the
landfill. The mix of materials within the landfill, as well as local conditions within a
site, will also affect gas generation.
Table 6-2: DOCf Values for Individual Waste Types Derived from Laboratory
Experiments11
Waste type
Initial total organic
carbon (kg/dry kg)
A
Organic carbon
remaining after
decomposition
(kg/dry kg) B
DOCf (A-B)/A
Newsprint 0.49 0.42 0.15
Office paper 0.40 0.05 0.88
Old corrugated
containers 0.47 0.26 0.45
Coated paper 0.34 0.27 0.21
Branches 0.49 0.38 0.23
Grass 0.45 0.24 0.47
Leaves 0.42 0.30 0.28
Food 0.51 0.08 0.84
Source: Derived by Hyder Consulting 2009 in consultation with Morton Barlaz, in Department of
Climate Change and Energy Efficiency (Australian Government) (2010) Review of the NGER
(Measurement) Determination, Discussion Paper, August 2010,
http://www.climatechange.gov.au/government/submissions/reporting/~/media/publications/greenh
ouse-report/review-nger-measurement-determination-paper.ashx.
In a model such as MELMod, it makes little sense to speak of material specific
degradation factors in isolation from consideration of how the calculation will be
made. If the decision were taken to use the approach we have proposed in respect of
the characteristics of the individual materials (see Section 5.0), then it may make
sense to apply the factor to the biochemical components other than lignin, but taking
into account the role of lignin in (at least in paper and wood) preventing breakdown of
the biodegradable carbon. However, whilst studies have shown that newspapers do
not degrade rapidly in landfills, over very long periods of time, they might, and some
of the literature supports the view that some lignin may degrade over time (and that
this proportion might vary by material).12 Arguably, we have insufficient evidence to
guide us in respect of the behaviour of materials over the very long term.
11 This data appears to have come from a recently published report by Hyder et al (2009); Hyder in
turn cite their source as the US EPA (2006). The US EPA study indicates the original source of the
experimental values to be Eleazer et al, with additional interpretation carried out by Barlaz in 1998.
See: Barlaz M (1998) Carbon Storage During Biodegradation of Municipal Solid Waste Components in
Laboratory Scale Landfills, Global Biogeochemical Cycles, 12, 373-380; US EPA (2006) Solid Waste
Management and Greenhouse Gases: A Life-cycle Assessment of Emissions and Sinks, September
2006; Hyder (2009) Comparative Greenhouse Gas Life Cycle Assessment of Wollert Landfill
12 Over the very long-term, it may be that degradation becomes partially aerobic, and this may explain
why some studies suggest lower concentrations of methane in landfill gas at older sites.
13
To retain consistency with the existing model structure, and based upon the review in
Appendix A.4.0, we make the following recommendations:
The approach taken for most waste fractions should be as follows:
Calculate, from the biochemical constituents (see Table 6-1) and their relative
proportions of carbon (see Table A 22), the amount of carbon in fresh matter
which is deemed degradable. This should be done for non-lignin fractions, and
separately, for lignin;
Assume, bearing in mind that the modelling considers impacts occurring over
the long-term, that
For food waste, 70% of the non-lignin fraction is considered degradable
along with 15% of the lignin (it should be noted that this may be
conservative given, for example, the evidence in Table 6-2);
For garden waste, 65% of the non-lignin fraction is considered
degradable along with 10% of the lignin; and
For all other degradable materials 65% of the non-lignin fraction is
considered degradable along with 5% of the lignin.
For textiles, we propose to retain the existing MELMod assumptions due to the
lack of detailed biochemical data and composition analysis.
The maximum degradation factors indicated here are in line with the evidence from
the landfill reactor experiments undertaken by Eleazer et al.13 Lignin is treated
differently across the different waste materials, reflecting the fact that it appears to
be more readily dissimilable in food and the less woody garden waste materials such
as grasses and leaves. This, in turn, affects the extent of degradation in both the
lignin and the cellulose contained within these materials. The lower degradation
potential for garden waste in comparison to food reflects the mixture of garden waste
materials which will include some more woody materials along with the more readily
degradable grasses and leaves.
There is still considerable uncertainty in these figures, and they should certainly not
be considered „the last word‟ on the matter.
This approach appears to give a more rational means of estimating how much carbon
in a given material will degrade. For comparison, Table 6-3 shows the figures from
MELMod, the IPCC default figures, and those that result from our proposed revisions
to the model. In general, the IPCC default values provide a more internally consistent
and supportable set of values than those currently in MELMod. The most significant
differences between the IPCC values and those that would result from our proposed
revisions to MelMod are seen with respect to wood and textiles, although there is also
some deviation between the values presented for paper and card.
13 Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal Solid Waste
Components in Laboratory Scale Landfills, Environmental Science and Technology, 31, pp911-917
14
Table 6-3: Comparison of Results – MelMod, IPCC and Impact of Proposed Revisions to Model
Waste Fraction
MelMod IPCC Result of
proposed
revision to
MelMod (C
degraded,
FM)
Results comparison
C degraded
as % DM Moisture
C degraded,
FM
C degraded,
FM
Proposed
revisions /
IPCC
MelMod /
IPCC
C&I Paper and card 41.7% 30% 29.2% 20.0% 15.6% 78% 146%
C&I General commercial 31.7% 37% 20.0%
C&I General industrial waste 31.7% 37% 20.0% 7.5% 266%
C&I Food solids 21.1% 65% 7.4% 7.5% 7.8% 105% 99%
C&I Food effluent 21.1% 65% 7.4% 7.5% 7.8% 105% 99%
C&I Abattoir waste 21.1% 65% 7.4%
M Paper and card 19.3% 30% 13.5% 20.0% 15.6% 78% 68%
M Misc. combustible (plus non-inert
fines from 1995) 11.1% 20% 8.9%
C&I Other waste 11.1% 20% 8.9%
M Non-inert fines 11.1% 40% 6.7%
M Putrescible 10.7% 65% 3.7% 43%
Food 7.5% 8.5% 113%
Garden 10.0% 8.7% 87%
C&I Sewage sludge 9.3% 70% 2.8% 2.5% 112%
M Textiles 8.9% 25% 6.7% 12.0% 6.7% 56% 56%
C&I Misc processes 4.4% 20% 3.6%
C&I Construction/demolition 4.3% 30% 3.0%
M Composted Putrescibles 0.4% 30% 0.2%
Wood 21.5% 12.5% 58%
Note: IPCC considers only biodegradable textiles – MELMod appears to treat textiles as one category (i.e. including non-
degradable textiles).
15
For paper, the proposed revisions to MelMod would result in only 78% of the
degradation potential in comparison to that seen under the IPCC model. Evidence
provided by the landfill reactor study suggests that the extent of degradation of paper
and card will vary considerably depending on the type of paper. Whilst nearly 90% of
the cellulose contained within office paper was degraded, the figures for newsprint
and coated paper were 30% and 45% respectively. The degradation potential of card
lies in between the two extremes, with 65% of the cellulose considered degradable.
Eleazer et al did not consider the degradation of textiles. Textiles were, however,
considered as part of the study undertaken by Godley et al which considered
evidence from MBT facilities.14 Their study suggested that only 4% of the volatile
solids contained within the mixed fibre textiles degraded under anaerobic conditions.
The fabric considered in their analysis consisted of mixed fibres that contained
natural fibres along with a plastic coating which would be expected to limit the extent
of degradation.15
Textiles made from solely natural fibres such as cotton, on the other hand, usually
consist largely of cellulose and would be expected to degrade to a much more
significant extent. As is the case for paper, the degradation potential of textiles will be
dependent to a significant extent on the precise composition of the waste textiles
fraction – in this case, the precise mix of natural and mixed fibres contained within
the waste stream. This is unlikely to be known with any detail. In addition, as was
indicated in Section A.3.1.5, there is very little data available with regard to the
biochemical constituents of the range of natural fabrics likely to exist in the waste
stream. As such, our recommendation is to retain the existing MELMod assumptions
with regard to textiles. It is assumed, furthermore, that these characteristics apply to
the whole of the textiles waste stream (not simply biodegradable ones, which is the
case with the IPCC figures).
Appendix A.3.0 similarly confirmed that the biochemical composition of wood is also
highly variable. The characteristics of untreated wood are likely to vary considerably,
whilst those of treated wood are different again. However, even assuming both the
lowest moisture content of that indicated by the literature (of 8% for MDF board)
along with the highest cellulose and hemicellulose content, this would not match the
extent of carbon degradation indicated by IPCC model. The extent of degradation of
wood products therefore appears to have been overstated in the IPCC model.
Finally, it is important to note that the issue of the extent of degradation cannot be
considered independently of the material characteristics, as the two aspects are
inseparable.
14 Godley and Frederickson (2010) Supporting Agency MBT Model Development, May 2010
15 It should also be noted that the anaerobic degradation potentials presented in Godley et al are
typically less than those provided by Eleazer et al for all other degradable types of material
16
7.0 Rate Constants
7.1 The Approach Taken by MELMod
The calculations of DDOC effectively drive the quantity of landfill gas generated. They
do not determine, however, the rate at which the gas is generated (and hence, in
which year of an inventory the emissions will fall).
One possible approach might have been to assume that if the level of gassing of the
material was driven by the two components, cellulose and hemicellulose, then the
assumed rates of degradation might also be related to the proportions of these
constituents present. If this was not the case, then the assumptions might have been
modulated by some relationship to the proportion of lignin in a given material. This
does not, however, appear to be the case with the assumptions contained within
MELMod. MELMod makes no use of lignin content to estimate any effect on
degradation rate, though as the above review highlights, this is not well understood.
The model assigns, for each material, differing proportions of the degrading carbon to
„rapid‟, „medium‟ and „slow‟ degrading fractions, even though the fractions degrading
– cellulose and hemicellulose - are the same for all waste components (because of
assumptions already highlighted previously).
The question arises, therefore, as to what effectively sets the way in which the
different materials have their carbon constituents assigned to the categories:
a) Rapidly degrading organic material;
b) Medium degrading organic material; and
c) Slowly degrading organic material.
Since there are only two organic substances being modelled (cellulose and
hemicellulose), why would the rate not be determined by the relative proportions of
these materials? And if the rate is not determined by this, what is the basis for the
assignment to the different rates of degradation.
A brief examination of the MELMod assumptions also highlights the fact that for the
different components of municipal waste, the figures are neat, round figures (see
Table A.15 in Appendix A.3.0). For commercial and Industrial waste, the figures
appear to be more precise (even though the waste categories are mostly aggregated
streams whose composition is apt to vary).
The previous review by AEA seemed to suggest that the decay rates themselves were
acceptable:
The rates are close to, or within the ranges quoted by the 2006 IPCC
Guidelines […] These rates have been retained in MELMod-UK.
The rates are shown alongside IPCC defaults and ranges in Table 7-1.
17
Table 7-1: Decay Rate Constants.
Waste pool IPCC Default IPCC Range MELMod
RDO 0.185 0.1-0.2 0.116
MDO 0.1 0.06-0.10 0.076
SDO 0.06 (paper/textiles)
0.030 (wood/straw)
0.05-0.07
(paper/textiles)
0.02-0.04
(wood/straw)
0.046
Notes:
The IPCC data refer to wet boreal/temperate climate zones.
7.2 Values Presented Within the Literature
Estimating the values of the decay constant, k, in real landfill conditions is difficult.
The approach adopted in MELMod – in which the decay rates relate to unspecified
parts of each material - would be incredibly difficult to verify. To our knowledge, the
study by Oonk in 1994 (also part of a 1995 measurement report) and a similar
exercise in USA in more arid conditions (by Gregg Vogt) are the only field-studies that
have been performed that shed light upon values for k.16 The study by Oonk
estimated values of 0.1 for „mixed waste‟, or 0.185, 0,1 and 0.03 for fast, moderate
and slowly degrading waste, respectively, when using a multi-phase (i.e. a model with
more than one decay constant) model. This appears to be the only information that
comes from actual field-data, and it is the data upon which the IPCC default values
are based. It also closely reflects what was used in a previous version of the national
assessment model.
In the IPCC methodology report (2006), it is also stated that it might well be the case
that neither single-phase nor multi-phase approaches accurately reflect the reality of
the conditions in a landfill. The truth may lie somewhere in between since multi-phase
models implicitly assume complete independence of degradation of different waste
fractions (i.e. „wood‟ degrades as „wood‟, independent of whether it is landfilled as
part of waste including significant amounts of putrescible material, or as part of an
inorganic matrix), whereas this independence of degradation is, in reality, unlikely to
reflect the reality.
16 Oonk H, Weenk A, Coops O and Luning L (1994) Validation of Landfill Gas Formation Models, Dutch
Organisation for Applied Scientific Research, Report no 94-315; Oonk H and Boom T (1995) Landfill
Gas Formation, Recovery and Emission, TNO-rapport 95-203,; Vogt G., Augenstein D., (1997):
Comparison of models for predicting landfill methane recovery, SCS Engineers, Report File No.
0295028, Reston, Virginia, USA
18
The IPCC Guidelines in 2006 noted the following with regard to the different
approaches available in determining K values:17
There are two alternative approaches to select the half-life (or k value) for the
calculation: (a) calculate a weighted average for t1/2 for mixed MSW (Jensen
and Pipatti, 2002) or (b) divide the waste stream into categories of waste
according to their degradation speed (Brown et al., 1999). The first approach
assumes degradation of different types of waste to be completely dependent
on each other. So the decay of wood is enhanced due to the present of food
waste, and the decay of food waste is slowed down due to the wood. The
second approach assumes degradation of different types of waste is
independent of each other. Wood degrades as wood, irrespective whether it is
in an almost inert SWDS or in a SWDS that contains large amounts of more
rapidly degrading wastes. In reality the truth will probably be somewhere in
the middle. However there has been little research performed to identify the
better one of both approaches (Oonk and Boom, 1995; Scharff et al., 2003)
and this research was not conclusive. Two options of the IPCC spreadsheet
model apply either of above approaches to select the half-life as follows:
Bulk waste option: The bulk waste option requires alternative (a) above, and is
suitable for countries without data or with limited data on waste composition,
but with good information on bulk waste disposed at SWDS. Default values are
estimated as a function of the climate zone.
Waste composition option: The waste composition option requires alternative
(b) and is applicable for countries having data on waste composition.
Specification of the half-life (t1/2) of each component of the waste stream
(IPCC, 2000) is required to achieve acceptably accurate results.
The most obvious discrepancy between the default IPCC values and those suggested
by MELMod is with regard to the fast degrading carbon. Whilst MELMod applies a
maximal degradation speed of 0.116 for rapidly degrading carbon, the comparable
value given by the IPCC is 0.185. In general, MELMod values for decay constants lie
at the lower end of the relevant IPCC ranges.
Table 7-2 presents data from the literature regarding the half life in landfill of the
different carbon types. The half life can be derived from the k value using the
following formula:
Half life = 0.7
k
The shortest half life figures in Table 7-2 therefore represent the most rapidly
degrading substances. As such, the half life figure of 6 years for fast degradable
substances assumed in the GasSim model represents the lowest k value of those
17 IPCC (2006) IPCC Guidelines for National Greenhouse Gas Inventories: Chapter 3 – Solid Waste
Disposal
19
multi-phase models presented in the Table (note, only value for wet boreal and
temperate regions are presented).
Table 7-2: Review of Data on Half Life of Waste Fractions
Model Half life Country
IPCC‐model
12‐23 (slow)1,2
7 (moderate)1
4 (fast degradable)1
MSW Europe
TNO‐model 7 Dutch HHW
GasSim
15 (slow)
9 (moderate)
6 (fast degradable)
HHW UK
Landgem 14 („conventional‟)3
35 („ arid‟)3 MSW USA
Afvalzorg
23 (slow)
7 (moderate)
3 (fast degradable)
Dutch HHW
E‐PRTR (Fr) 10 HHW France
E‐PRTR (Fi)
23 (slow)
14 (moderate)
3.5 (fast degradable)
HHW Finland
Vogt et al. (1997) 17 MSW California
Notes
1. Values for wet boreal and temperate regions. For dry regions and tropical conditions other
k‐values are suggested;
2. Different half‐lives specified for paper‐like materials and wood‐like materials;
3. „Arid‟ refers to regions with less than 625 mm (25 inch) rainfall per year. „Conventional‟ refers
to non‐arid regions.
Given the above discussion, it is worth outlining the basis for the decay rates
assumed within MELMod. This is outlined by LQM, as follows:18
Manley et al (1990a; 1990b) were the first to use three rate constants for
slowly degradable, moderately degradable, and rapidly degradable waste, and
Brown et al. (1999) introduced three rate constants to the National
Assessment Model. Short half-life values for readily degradable waste
introduces an unrealistic and unobserved peaks in gas forecasting models, so
for consistency with the Environment Agency‟s GasSim Model (Environment
Agency, 2002a), the three rate constants have been replaced with GasSim
defaults (see Table 3.1). These have been validated against UK landfills and
are considered appropriate in most UK cases (Environment Agency, 2002a).
The GasSim defaults are on professional experience of UK landfill sites with
varying degrees of saturation. There has been very little research to quantify
18 LQM (2003) Methane Emissions from Landfill Sites in the UK, Final Report to Defra, January 2003.
20
the rate of gas generation, although it is known that the initial hydrolysis step
from the cellulose polymer to the glucose monomer is the rate determining
step. GasSim users are encouraged to use site-specific constants. LQM
considers these default rate constants are suitable for use in the National
Assessment Model, since this model integrates degradation for many landfills,
and so will be less sensitive overall to potentially different waste degradation
rates at different landfills due to site specific differences.
The above statement says on the one hand that a model has been validated, but on
the other, that there has been very little research to quantify rates of gas generation,
and that GasSim users are encouraged to use site specific constants. It is not clear
how the rate constants could be validated given that this could not take place
independently of consideration of what materials are being landfilled (this still being
relatively poorly understood), and which components of those materials are assumed
to be degrading at the different rates.
The rates which were suggested by Brown et al, and which were altered by LQM, are
very similar to those suggested by the IPCC as default values. They are closely aligned
with the only information that comes from actual field measurements.
7.3 Rate of Degradation of Different Biochemical Constituents
In work undertaken for the UK Environment Agency, Godley et al developed a
classification of the biodegradability of specific wastes using evidence obtained from
MBT plant. This is shown in Table 7-3. This classification implies a slower degradation
speed should be applied to textiles in comparison to that of paper, and that green
waste and food should be subject to the same degradation rate.
Table 7-3: Biodegradability Classification Proposed by Godley et al
Waste
% LOI reduction
Anaerobic
digestion
% LOI reduction
Aerobic
composting
Biodegradability
classification according
to % LOI reduction
Food waste 55 80 Fast
Green waste 33 70 Fast
Paper waste 30 40 Medium
Wood waste 7.5 10 Slow
Textiles 3 4 Slow
Fines 33 70 Fast
Source: Godley A and Frederickson J (2010) Supporting Agency MBT Model Development, Report for
the Environment Agency, May 2010
The approach taken in the majority of the analyses indicated above, including the
IPCC default approach, is to apply the rate constants to the different waste fractions.
The approach in MELMod is to apply the degradation speeds to the biochemical
constituents of the waste materials. Although this approach has been used in the
context of modelling the performance of anaerobic digestion plant, evidence from
other literature reviews of published decay factors suggests this has not been done
21
within the context of modelling landfill gas generation.19 One study undertaken by
Dalemo characterises the degradation seen at anaerobic digestion and sewage plant
in which five organic carbon sources were recognised. Data from the study is
presented in Table 7-4.20
Table 7-4: Degradation of Organic Substances in Anaerobic Digestion Plant
Organic substances Rate constant, k days -1
Organics slow 0.001
Carbohydrate, moderate 0.18
Carbohydrate, rapid 0.23
Protein 0.13
Fat 0.13
Source: Dalemo, M (1996) The Modelling of an Anaerobic Digestion Plant and a Sewage Plant in the
ORWARE Simulation Model, Rapport 213, Swedish University of Agricultural Sciences, Uppsala 1996
Note that the rate constants presented here are not comparable to those suggested
for landfill, as those in the Table reflect the situation for anaerobic degradation under
controlled conditions. It would clearly be possible, however, to adapt Dalemo‟s
approach to the degradation that occurs in landfill, by assuming that specific
biochemical fractions are assigned slow, medium and fast rate constants. Dalemo‟s
work suggests an ordering in terms of the rate at which different constituents
degrade. This is the approach we propose below.
7.4 Summary
The foregoing discussion suggests a number of options with regard to the setting of
the rate constants used within the model:
1. Use the rates contained within MELMod without any amendment (applied to
the degradable carbon as calculated above);
2. Use an amended version of the rates contained within MELMod (applied to the
degradable carbon as calculated above), with the rapidly degrading fraction in
particular assigned a higher k-value;
3. Use the IPCC figures for specific materials;
4. As with option 2, but with the assignment of the different biochemical fractions
to 'rapid' (sugars and fats), 'medium' (everything else other than lignin) and
'slow' (lignin, of which we might assume a reduced percentage degrades),
rather than assigning the total carbon content somewhat arbitrarily to 'rapid',
19 Barlaz M A (2004) Critical Review of Forest Products Decomposition in Municipal Solid Waste
Landfills, National Council for Air and Stream Improvement, Bulletin 872
20 Dalemo, M (1996) The Modelling of an Anaerobic Digestion Plant and a Sewage Plant in the
ORWARE Simulation Model, Rapport 213, Swedish University of Agricultural Sciences, Uppsala 1996
22
'medium', 'slow' as is currently the case in MELMod. This mimics the approach
taken by Dalemo with regard to the modelling of AD plant.
Of these, the third and fourth options appear to offer the most promise. The IPCC
figures are based on actual field-data taken from operating landfills. Option 4,
however, allows for a link to be retained between the behaviour of the materials and
their biochemical constituents, and is consistent with the existing model structure.
We recommend that the rate constants be linked to the different biochemical
fractions of the waste. We suggest that the assignment is as follows:
Slow The small proportion of lignin assumed to be degraded over the
long term (calculated as in Section 6.0 above)
Medium Biochemical components other than those above and below
(cellulose, hemicellulose, etc.)
Fast Sugars and Fats
We suggest that as far as rate constants are concerned, the IPPC defaults (see Table
7-1) are used. This reflects the view that for the rapid degrading fraction in particular,
the rate used in MELMod appears much lower than is the case in most other multi-
phase models, and is close to the average decay rate used in single phase models.
23
8.0 Landfill Gas Extraction Rates
8.1 Introduction and Summary
Type 1, Type 2 and Type 3 landfills in MELMod are all assumed to increase their
extraction efficiencies to 76% by 2004. The basis for these figures is unclear.
Type 1 landfills are described as:
„Large modern landfills without gas collection systems. Sites began receiving
waste in 1980 until 2000. No further waste inputs beyond 2000.‟
It seems unclear that sites which are described as having no gas collection system
should be assumed to have such a high extraction rate.
Type 2 landfills are defined as
„Large modern landfills with limited gas collection. Sites began receiving waste
in 1980 until 1999. No further waste inputs beyond 1999‟
It seems unlikely that all such sites – which ceased receiving waste in 1999 - would
achieve the rates being suggested.
Type 3 landfills are defined as:
Large modern landfills with comprehensive gas collection. Sites began
receiving waste in 1986, continuing thereafter.
These sites are likely to have the highest extraction rates of those described in
MELMod. It might still be an open question as to whether, and how many of these
would achieve the stated extraction rates.
In MELMod, Type 1, Type 2 and Type 3 landfills are characterized by exactly the same
parameters. This is a somewhat strange way to make use of the different landfill
types which MELMod includes. To the extent that the differentiation in type is clearly
meant to highlight the difference in, notably, extraction rates, it is surprising that
these different types are all characterized by the same extraction rates. We are
informed that this approach has been inherited by the developers of MELMod from
the national assessment model.
In what follows, we discuss landfill gas extraction from a general standpoint with no
specific emphasis on what might be „the best practice‟. It is important to note, after
all, that not all the gas emitted from landfills in MELMod is from „state of the art‟
landfills. Indeed, there appears to be no readily available information regarding the
amount of waste landfilled at different types of landfills (according to the details of
their gas collection infrastructure – see Section 10.0).
8.2 Definition of Extraction Efficiency
Other than pre-treating waste, landfill gas extraction is one of the main measures to
reduce methane emissions from landfill. The efficiency of landfill gas however is
widely discussed, and this literature survey is intended to bring this discussion one
step further.
24
To begin with, it is important to note that there are different definitions of efficiency in
this respect. One definition refers to „integral efficiency‟, indicating the proportion of
landfill gas that is extracted during the landfill‟s lifetime. The other approach is a
more momentary one, describing this efficiency of a landfill at a given month or in a
given year. These two measures are often mixed up, and this tends to confuse the
discussion.
Hence, although extraction efficiency is defined as ratio of the amount of landfill gas
extracted to the amount generated, there are still two different ways to look at
extraction efficiency:
The efficiency at a single moment in time (hour, day, year); and
The total efficiency integrated over the landfills life-time.
The difference between both is illustrated in Figure 8-1 below, which depicts the
amount of landfill gas generated and extracted in time at a typical landfill (or landfill-
cell). The instantaneous efficiency is the efficiency at a certain moment in time (e.g.
the length of BC divided by AC). The integral efficiency is the ratio of the area beneath
the lower curve to the area beneath the upper curve.
Figure 8-1: Landfill Gas Generation and Extraction in Time at a Typical Landfill
During deposition of the waste, the amount of landfill gas generated increases with
increasing quantities of waste. When the landfill is closed, the amount tends to fall
over time. In some cases landfill gas extraction only starts after exploitation of the
void space has ceased and the cell has reached its final height. In the years after, the
collection efficiency might slowly increase, as gas generation reduces, the cover layer
and its vegetative cover develops and emissions from „short-cuts‟ and hot-spots
25
become less important. After some time the landfill is capped with an impermeable
liner system, after which extraction efficiency becomes almost 100%.21
The example above describes a landfill, where annually the same amount of waste
was landfilled during 10 years. Even with extraction efficiency in the early closed
phase of over 60%, increasing to 80% in the later, closed phase, and almost 100%
when capped, the integral efficiency may only be 38%.
Since MELMod is not a model of „a landfill‟, but a national model for reporting
methane emissions, then it makes no distinction between periods in „a landfill‟s‟
operation. As such, the appropriate extraction rate figure ought to be that which best
represents the integral efficiency. At any given point in time, a significant amount of
fresh waste is present in parts of a landfill, where the void space is still being
exploited; another portion of the waste is in landfills that are recently closed, etc., so
extraction efficiencies will need to reflect the various phases of the sites.
It should be noted that the IPCC-default value of an extraction efficiency of 20% is
based on a view of what integral efficiencies may be.
8.3 Interpretation
As described above, the kind of technology implemented, the moment the technology
is implemented and the day-to-day operation of landfill gas extraction defines
recovery efficiency. The problem is that landfill gas recovery differs from site to site. A
single default methodology for estimating landfill gas recovery therefore is always an
approximate approach.
It is also important to note that the above discussion deliberately does not set out to
describe only „state of the art‟ landfills. Of the methane generated in landfills in 2010,
more than 25% was generated in landfills which, in the current model, ceased to
receive waste in 2000 (and are described – possibly erroneously - as having no gas
extraction system). The modern, Type 3 sites were the source of only around half the
landfill gas generated. Whatever the performance of specific landfill Types, a national
extraction rate in excess of 70% appears rather difficult to justify if the distribution of
waste across landfill types in MELMod is at all accurate (and it may well not be).
A possible way to improve on current methodology would be to distinguish different
levels of technology more carefully than is the case within MELMod at present. Such a
differentiation might move the discussion away from the potential effectiveness of
landfill gas recovery at one or other site Type, and help give more accurate
information regarding what the average level of landfill gas recovery is across the UK.
One of the improvements in MELMod is that there is an additional landfill type which
could be used (whilst three of the five types in MELMod are effectively modelled as
21 Capping of landfills normally takes place when risk of irregular settlements is significantly reduced.
Waste degradation and landfill gas generation is one of the main causes of settlements, so capping is
preferably done in the final stage of waste deposition when most landfill gas has already been
generated.
26
one type at present). This could be further expanded to capture a range of landfill
types.
Below four different levels are described in more detail.
8.3.1 Basic
This level of landfill gas recovery refers to common practice in the 90‟s and is more or
less the system the IPCC default value of 20% (integral efficiency) is based upon. At
the moment, this approach is still common practice in large parts of the world. It was
also common in the UK, and some current emissions will be emitted from sites such
as these. Wells for landfill gas recovery are only dug after a landfill (or a larger area of
a landfill) is closed. At that moment in time, the first waste deposits can be already
over ten years old, and a considerable proportion of landfill gas will have been formed
and emitted prior to landfill gas extraction commencing. Well spacing might not be
especially dense (80-120 meters apart; ~1-2 wells per hectare), and the capacity of
landfill gas utilisation may have governed the effort to maximize landfill gas recovery.
Figure 8-2 below describes the integral efficiency of such a basic system, which is
generally limited to 10-25%.
Figure 8-2: Landfill Gas Recovery Efficiency, Applying a Basic System
8.3.2 State-of-the-art
Growing awareness of factors limiting the overall recovery efficiency resulted in
policies and measures to improve integral recovery efficiency, e.g. by landfill gas
extraction during the exploitation of void space (e.g. by landfilling in smaller
compartments and immediate drilling of wells, once a cell has been completed),
increased well density (2-3 wells per ha), increase of the blower capacity, improved
control the performance of each individual well and emphasizing the necessity of
landfill gas recovery as an environmental measure (thus maximising the recovery
efficiency and flaring what cannot be utilised. In the Netherlands, such a system is
27
considered „state- of-the-art‟ or „best available technology, not exceeding excessive
costs‟ (BAT-NEEC, SenterNovem, 2005).22 23
In a state-of-the-art system part of the gas recovered might not be utilised, simply
because the peak utilization capacity will not be adequate to deal with all landfill
gas.24 Consequently, additional flaring capacity is required.
A state-of-the-art system also requires a careful coordination of landfill construction
and realization of landfill gas extraction. This is only possible when the landfill owner
takes care of extraction (and does not depute this responsibility to e.g. an energy
producing company).
Figure 8-3 below describes the integral efficiency of such a state-of-the-art system,
which is estimated to be 30-60%, depending on, amongst other things, the time that
it takes to fill a compartment, the well density, and the quality of intermediate cover
of closed compartments.
Figure 8-3: Landfill Gas Recovery Efficiency, Applying State-of-the-Art Recovery
22 SenterNovem (2005): Handreiking Methaanreductie Stortplaatsen (Guidelines methane emission
reduction from landfills), SenterNovem (currently AgentschapNL. Dutch Agency for Sustainability,
Innovation and International Trade and Cooperation, Utrecht, The Netherlands.
23 Measures are considered BAT-NEEC by SenterNovem (2005) when overall costs (costs per ton of
methane mitigated; costs are investment and operating costs minus revenues from utilisation) are in
agreement with costs that are accepted by society for greenhouse gas emission reduction elsewhere.
Costs can be related to e.g. current or expected market price for CO2-emission permits.
24 This might open up the possibility to utilize extra gas during a peak with mobile utilization units, e.g.
smaller gas-engines of about 100-250 kWe, which can be used at one landfill for a shorter time and
then relocated to another site. To what extent this also occurs in reality, depends on choices by the
energy producing companies involved.
28
8.3.3 High-end
A number of measures might be taken, that go beyond the state-of-the-art as
described above. Temporary or sacrificial wells might be used to minimize emissions
from the exploitation period, well density might be increased to 4 wells per ha (well
spacing of 50 meters) and beyond. Smaller wells might be used to mitigate emissions
from the slopes. More gas-tight temporary cover materials might be used to minimise
emissions from closed parts.
In general, horizontal temporary wells are preferred to vertical or point-wells.25
However the effectiveness of these additional measures is uncertain. e.g. the region
of influence of sacrificial wells might be limited, especially when they are located near
the surface of the waste (about 1-3 meters), located near a slope or when waste
deposited around such a well is not well compacted. In such a case, under-pressure
on a sacrificial well has to be limited to prevent sucking in ambient air. Experience
with such wells indicates that at least 5 metres of waste is required for proper
functioning temporary wells.26 An alternative is to accept a lower quality (reduced
CH4-content, increased N2, CO2 and within limits O2) of recovered landfill gas.
Figure 8-4 below describes the integral efficiency of such a high-end system, which
could be as high as 60-80%.
Figure 8-4: Landfill Gas Recovery Efficiency, Applying a High-End System
25 Barry D.L., Watts M., Smith R. (2004): Practical gas emission control during landfilling, Proc. Waste
2004 Conf. Integrated Waste Management and Pollution Control: Policy and Practice, Research and
Solutions. Stratford-upon-Avon, UK, 28-30 September 2004, 315-324.
26 SenterNovem (2005): Handreiking Methaanreductie Stortplaatsen (Guidelines methane emission
reduction from landfills), SenterNovem (currently AgentschapNL. Dutch Agency for Sustainability,
Innovation and International Trade and Cooperation, Utrecht, The Netherlands.
29
The potential influence of emissions from the “tail” of landfills that employ even a
high-end gas management system has been indicated in work done by ERM.27 Their
study modelled a range of landfill gas management scenarios using GasSim, with
instantaneous extraction efficiencies of between 75-85% considered in the modelling.
Outputs from the modelling suggested however a range of extraction efficiencies from
44-64% over the lifetime of the landfill (assumed in this case to be 100 years).
The worst performing scenario – Scenario D – assumed an instantaneous extraction
efficiency of 85% where the gas could be actively managed. The relatively low
performance in comparison to other scenarios resulted from assumptions
surrounding the flaring of the gas, with Scenario D considering that a smaller
proportion of the poorer quality landfill gas would be flared towards the end of the
site‟s life.28
8.3.4 Landfill Cells - Bioreactors
Almost complete mitigation of methane emissions might be achieved by covering
landfilled waste within a few months (to a maximum of one year) after it is deposited
and using an impermeable liner (which may have a finite lifetime, and thus be of
lower quality as a final liner system). In this way, landfill cells are created, from which
methane can be recovered at almost 100% efficiency (see Figure 8-5).
However one should realise that by doing this, infiltration of rain is reduced and
biological processes leading to landfill gas might be hampered. This is more likely to
lead to incomplete biodegradation of organic waste resulting in an increased risk for
soil and groundwater pollution in the long run. Landfilling waste in such cells is
recommended only when, simultaneously, measures are taken to complete
biodegradation. Leachate recirculation in such a cell is an obvious method to
stimulate biodegradation, thus turning these landfill cells into bioreactors, with an
integral efficiency that may exceed those suggested above.
27 ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, Final Report
for Defra, December 2006
28 The authors assumed it would be unsafe to flare the gas where the methane content fell below 30%
or where the oxygen content rises above 5%. The study attempted to model this by considering that
gas would not be flared when the gas production decreased below a certain level
30
Figure 8-5: Landfill Gas Recovery Efficiency, applying a State-of-the-Art System
8.3.5 Desirability of an Adapted Default Methodology
The discussion about default values for landfill gas recovery has continued within the
IPCC for more than 10 years. Considering the relatively poor efficiency of basic
systems for landfill gas recovery, the barriers that have to be overcome to achieve
more state-of-the-art landfill gas recovery (as well as the pace with which this can
feed through into a national figure, not least given the dependence of current
emissions on past deposits), and also the observed discrepancy between the national
efficiencies of countries that monitored landfill gas recovery, and countries that
estimated / modelled the efficiency, the IPCC has tended to be conservative in
defining a default value for extraction efficiency.
In theory it is feasible to distinguish different technical approaches to landfill gas
extraction, and define a default value for each group. In combination with an
inventory of how many landfill gas projects fall within each group, and the tonnages of
waste consigned to each, this ought to give an improved estimate of landfill gas
extraction. This still raises questions as to what extraction efficiencies should be
applied to each landfill type. Even an adapted methodology to assess landfill gas
recovery efficiency requires considerable knowledge for its application and the
chance still remains that in practice it will be too optimistic. This reduces the
incentive to actually conduct accurate measurement exercises, and seek to justify
estimates on the basis of empirical data.
It would be desirable for landfills in the UK that are currently in exploitation and which
apply more advanced systems for landfill gas recovery (state-of-the-art or even high-
end) to simply measure and report. The costs for installing systems is large in
comparison to the equipment needed to monitor their effectiveness. Furthermore,
landfills are obliged to report all type of emissions in the framework of E-PRTR (for the
calculation of which they need gas extraction data as well) to local authorities. So the
31
reporting infrastructure from landfill to authorities is also in place. It ought to be
feasible to produce monitored landfill gas collection within a few years for UK and it is
recommended that this system is implemented as soon as possible.29 At present, in
the national inventory report, the emphasis is on interpolation of renewable energy
figures and an estimation of gas extracted for energy recovery from this. The figures
for gas extracted for flaring are essentially estimates.
8.1 Summary
Our review of extraction efficiencies reported in the literature shows that these vary
widely (see Appendix A.5.0). It highlights the fact that the reported extraction
efficiency depends strongly on the point in the landfill‟s life at which the
measurement is made. Often, during the exploitation phase of the site, landfill gas
extraction does not take place. Increasingly, in the UK, landfills are obliged to extract
landfill gas during the exploitation of void space. Technically, this is relatively difficult
and it might hinder normal operations at a landfill, but it can be realised, albeit with a
reduced effectiveness, compared to landfill gas extraction from closed cells.
Extraction efficiency estimates for closed parts of a landfill vary widely and in practice
figures can be found from as low as 10% to more than 90%. Extraction efficiency
depends on factors such as well-spacing, attention of the landfill owner to the system
(control of suction pressure on wells), design-capacity of the extraction system and
utilization and the type and thickness of the cover. It also makes a difference whether
a landfill gas project is designed and operated to extract a renewable energy source
or whether minimization of emissions is the objective.
When the final cover is applied, high landfill gas extraction efficiencies can be
obtained. A relatively small number of measurements at landfills in this phase have
received considerable attention, and efficiencies at this stage are sometimes
interpreted as being possible from all landfills in all phases, or as being
representative of a lifetime / integral extraction efficiency.
Measured efficiencies, especially in the earlier phases of the landfill‟s development,
are generally below modelled efficiencies, and they are usually below estimated
efficiencies. The same may also be true for national efficiencies. UK legislation may
require a high standard of management at landfills, but the same is true of other
jurisdictions, such as Germany, The Netherlands, Denmark, Austria and the USA. The
first four countries have introduced a range of measures to address the landfilling of
organic waste, so that there is little or no methane generation in the exploitation
phase. Data reported to the IPCC suggests countries that actually monitor landfill gas
extraction (The Netherlands, Denmark and Austria) do not perform especially well in
comparison with those who estimate methane extraction (such as UK and Germany)
(see Table 8-1). For estimating national average recovery efficiency, the integral
efficiency is the relevant measure, not the instantaneous efficiency.
29 It would be important to ensure that the reporting mechanism was not based upon a modelled
estimate, but was linked back to actual measurements.
32
Table 8-1: Methane Emissions and Recovery Reported to UN-FCCC and Calculated
National Recovery Efficiency in 2008
Emission (Gg) Recovery (Gg) Efficiency
Austria monitored 74 15 15%
Denmark monitored 15 5 8%
Germany estimated 358 526 57%
The Netherlands monitored 233 44 15%
UK estimated 960 2,561 71%
USA estimated 6,016 6,451 49%
Source: Data retrieved from CRF‟s of individual countries, to be found at:
http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items
/5270.php
For the UK, with considerable amounts of organic waste landfilled each year, with
almost all operational landfills equipped with landfill gas recovery, but with much gas
generation still arising from less well-equipped sites (from historic deposits), there
seem to be few reasons why the national integral extraction efficiency would be
significantly higher than those suggested through monitoring in the Netherlands and
Austria (i.e. 15%). One reason might be that the proportion of waste landfilled in the
UK has remained at higher levels (so that proportionately more waste is landfilled at
newer, better-equipped sites). Even so, the IPCC default of 20% seems no less likely
to be in line with the actual situation than the currently assumed figure of 75%.
It is difficult to separate out this recommendation from the consideration of matters
discussed in Sections 10.0 and 11.0. For this reason, we defer our recommendations
to the end of Section 11.0.
We note, in passing, that it is no doubt tempting to seek to utilise real data on gas
extracted for energy recovery and flaring (or imputed data on the former, and
estimates of the latter, as happens today) as a means to establish a capture rate for
the UK as a whole by using the modelled landfill gas generation as the denominator
in the following identity:
Capture rate = (quantity of methane collected for utilisation +
Quantity of methane collected for flaring) ÷
Modelled quantity of methane generated
Although it might be argued that this is the best that can be done, it assumes that the
denominator (the modelled quantity of methane generated) is accurate. There are
very good reasons (highlighted at the end of Section 4.0 and in Appendix A.2.0) to
believe that it is not. In addition, the approach relies upon estimation of the quantity
of methane extracted for flaring. Consequently, we would discourage discussion of
extraction rates on this basis. The past data on quantities and composition remains
of low quality, and estimations made on the above basis are likely to be similarly so
(and remain so for some time into the future even if the quality of data improves
dramatically for every from here on).
33
9.0 Oxidation Rates for Uncaptured Methane When methane migrates through the top-layer, part of it is oxidized to carbon dioxide.
Although the process of methane oxidation is increasingly well understood, it is still
extremely difficult to quantify, because it depends on the stage and age of the landfill,
climate conditions and on the exact nature of the cover material. Moreover,
heterogeneity of emissions plays an important role. Methane that diffuses in a more
or less homogeneous way through the top-layer may be converted; however, a large
part of the methane may be emitted via so-called hot-spots and short cuts and has
little or no time to oxidize through covering layers.
All four types of landfill in MELMod are estimated to have oxidation rates of 10%. This
is also the IPCC default value.
9.1 Basis for Revising the IPCC Default Value
We have reviewed the literature regarding oxidation rates at landfills. From the review
(see Appendix A.6.0) it is evident that little or no authoritative information exists on
the basis of which the IPPC-default values could be revised. The same conclusion is
drawn by Kühle-Wiedemeijer and Bogon on the basis of a review of methane
oxidation in scientific journals and available grey literature on this topic.30 They
conclude there is no solid basis for the definition of more accurate default-values and
therefore propose values close to the IPCC default (10% when methane flux is higher
than 1,5 g CH4 m-2 hr-1 and 15% oxidation when the flux is lower), but they mention
this may be probably an underestimate. A similar conclusion has also been reached
by Dever in Australia, who has confirmed that short-cuts are likely to significantly
influence the overall oxidation rate.31 Elsewhere the USEPA has suggested a range of
10% to 25%, with clay soils at the lower end of the range and top-soils being at the
higher end.
The CLEAR group (an international group of leading experts on methane oxidation)
discusses improvement of quantification of methane oxidation. Some members of the
group have proposed a draft model in which methane oxidation is either limited by
the amount of methane that is homogeneously emitted, or the maximum oxidation
capacity of the top-layer. Both parameters are estimated as a function of methane
flux, top-layer material, porosity, moisture content and ambient temperature and the
lowest of both is actual methane oxidation. The draft model will be discussed, revised
and defined in more detail by the whole CLEAR group in the near future.32
30 Kühle-Weidemeier M., Bogon H., (2008): Methanemissionen aus passiv entgaste Deponien und der
Ablagerung von mechanisch-biologisch behandelten Abfällen - Emissionsprognose und Wirksamkeit
der biologischen Methanoxidation - Schlussbericht, Wasteconsult international, Langenhagen,
Germany.
31 Dever S. (2010): Personal communication S. Dever, GHD, Melbourne, Australia.
32 Scharff (2010). Personal communication H. Scharff, Afvalzorg, Assendelft, The Netherlands.
34
9.2 Summary
There are only few methane oxidation measurements available, and only a subset of
these can be considered as estimates of an annual average oxidation, measured
under conditions relevant for UK. Most information comes from closed chamber
measurements, which are believed to overestimate actual methane oxidation.
Information seems to indicate that the IPCC-default may be an underestimation of
actual methane oxidation, something that has already been acknowledged by the
IPCC in 2006. However actual methane oxidation on active or recently closed landfills
will most likely be close to these values. It will almost certainly not exceed 30%. At the
moment it is felt there is insufficient information available to assume another
oxidation value than the 10%.
The oxidation rates in MELMod are the same for all 3 types of landfill receiving waste
after 1986. It might be expected that Type 1 landfills, presumably deploying passive
venting, would have a lower oxidation rate through the cap since the rationale is to
allow a ready escape path for the landfill gas to the atmosphere. We would argue,
therefore that the oxidation rate at Type 1 sites should be set to a lower figure of say
5%.
We recommend continuing with the 10% figure for oxidation used for Type 3 landfills
in MELMod. This should be kept under review. There do not appear to be any peer
reviewed UK-based measures of landfill oxidation, not to mention, of the more
conservative 13C plume measurement variety, and across all seasons.
35
10.0 Assignment of Wastes to Types of Landfills As highlighted in Section 8.0 above, MELMod assigns waste landfilled across 4
different landfill Types, with a fifth possibility also available for use. It was highlighted
at the start of Section 8.0 that limited use is being made (in terms of the model‟s
functionality) of these different landfill types in the sense that three of the types of
landfill are assumed to have exactly the same characteristics in all years. This is not
only counter-intuitive (given the description of the landfills), but it is also a missed
opportunity to the extent that one believes (and this seems highly likely) that there
are landfills, with different characteristics, which extract gas to different degrees. The
issue of how different types of landfill might be used is considered in Section 11.0.
SEPA data suggests that even as late as 2004, a significant proportion (close to 50%)
of MSW was being landfilled at sites without gas recovery. The Welsh Waste Strategy,
Wise About Waste, reported that in 2002, it was expected that of 25 landfills
receiving biodegradable waste in Wales, 18 would be equipped with gas recovery for
the purposes of electricity generation, 4 would be equipped with flaring, and another
4 would be equipped only with passive venting. Historically, the data regarding gas
control systems was as shown in Table 10-1. This highlights the fact that as late as
1995, at least in terms of number of sites, more than half either had no gas control or
were passively venting landfill gas.
Table 10-1: Gas Controls at Sites Receiving Biodegradable Wastes in Wales
Total No.
Of
Landfills
No of Landfills
with Flaring
No of Landfills
with Electricity
No of Landfill
with passive
venting
No Controls total
1960 2 1 1 2
1965 3 1 2 3
1970 4 1 3 4
1975 7 1 6 7
1980 8 2 6 8
1985 17 1 3 13 17
1990 22 2 5 15 22
1995 25 6 6 5 8 25
2000 25 9 8 8 0 25
planned 2002 25 4 17 4 0 0
Source: Environment Agency (2002)
Current data in MELMod assumes that after 2000, all waste being landfilled is
disposed of in sites with levels of gas extraction which rise progressively over time. In
2003, a report concerning the national assessment model, MELMod‟s predecessor,
suggested:33
33 LQM (2003) Methane Emissions from Landfill Sites in the UK, Final Report, January 2003.
36
It is considered that with current landfill engineering requirements, all new
waste arising will be emplaced in landfill Type 3 (with comprehensive gas
collection) and no waste has been partitioned to other landfill types since
1999.
The sources mentioned above suggest that it might have been clear that this was not
the case. Furthermore, the report cited above gives no rationale for splitting waste
across the different landfill types. As it happens, this is irrelevant for landfills of Types
1, 2 and 3 as they are currently constituted in MELMod precisely because they
perform in exactly the same way in the model. This does then rather beg the question
as to why any attention at all was given to specifying that waste would be emplaced in
Type 3 landfills beyond a certain date (in the model as it stands, this simply does not
matter).
If we assume that it is a mistake in the model to have modelled each of the landfill
Types 1, 2 and 3 as performing in exactly the same way (and it is difficult to see this
in any other way for reasons discussed at the start of Section 8.0), then one needs to
ask how one should be allocating waste to landfill across the different landfill types.
The following discussion assumes that something more rational should be happening
with different landfill types in terms of their performance (since this is the only way to
bring some sense of order to this discussion).
There are some abrupt discontinuities in the way in which landfilled waste is allocated
across the landfill Types. Table 10-2 shows the radical switch of material from Type 4
to Type 1 landfills in 1980. On the basis of the SEPA data and the WAG information,
the MELMod assumptions might be optimistic in terms of UK landfill emissions since
Type 4 landfills have no gas collection.
Table 10-2: Current MELMod Data Regarding Proportion of Waste Sent to Different
Landfill Types, 1995-2009
1975 1976 1977 1978 1979 1980 1981 1982 1983
Type 1 0% 0% 0% 0% 0% 99.0% 98.0% 96.0% 94.0%
Type 2 0% 0% 0% 0% 0% 1.0% 2.0% 4.0% 6.0%
Type 3 0% 0% 0% 0% 0% 0% 0% 0% 0%
Type 4 100% 100% 100% 100% 100% 0% 0% 0% 0%
Data within MELMod also assumes that the quantity of waste being sent to Type 2
landfills falls from 77% of all waste in 1999, down to zero in 2000 (see Table 10-3).34
Similarly, the quantity sent to Type 3 landfills increases from 18% in 1999 to 100% in
2000 (see Table 10-3).35 It was, perhaps, being assumed that the Landfill Directive
would lead to a dramatic, more or less instantaneous switch in the fate of wastes
34 Type 2 landfills are defined as large modern landfills with limited gas collection. Sites began
receiving waste in 1980 until 1999. No further waste inputs beyond 1999
35 Type 3 landfills are defined as large modern landfills with comprehensive gas collection. Sites began
receiving waste in 1986, continuing thereafter
37
over an unrealistically short period of time. The evidence in support of such a radical
switch has not been provided, and indeed, such evidence as there is appears to
suggest that the assumption is not correct.
Table 10-3: Current MELMod Data Regarding Proportion of Waste Sent to Different
Landfill Types, 1995-2009
1995 1996 1997 1998 1999 2000 2001 2002
Type 1 48.0% 40.0% 30.0% 18.0% 4.0% 0.0% 0.0% 0.0%
Type 2 38.8% 45.5% 54.2% 64.9% 77.6% 0.0% 0.0% 0.0%
Type 3 13% 14% 16% 17% 18% 100% 100% 100%
2003 2004 2005 2006 2007 2008 2009
Type 1 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Type 2 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Type 3 100% 100% 100% 100% 100% 100% 100%
In terms of having a sensible estimate of emissions associated with past deposits, it
would appear absolutely essential to know what quantities of waste were being sent
to landfills with more limited capacity for gas extraction than is assumed in MELMod
for each of the landfills of Types 1, 2 and 3. The basis for doing so is not clear at
present, and is beyond the resources of this project (it would involve reviewing
deposits by site, over time, taking into account the gas collection infrastructure in
place). More generally, it seems appropriate for the relevant agencies to seek, in
future (and as far as possible, to review data from past years with a view to doing the
same for those years), to match data from site returns (in terms of waste landfilled)
with the type of landfill where the waste is being deposited. This makes sense only if
these landfill types are well characterised (notably, in terms of their likely potential to
extract / oxidise landfill gas emissions).
Interestingly, the more one moves towards this type of approach, the stronger the
rationale probably becomes for a more „bottom up‟ model which is based upon each
individual landfill and the waste being deposited there (clearly, there still needs to be
some way of dealing with emissions from past emplacements, but it would be far
from impossible to marry the type of top-down model, using integral extraction
efficiencies, with a bottom up one which might deploy different extraction efficiencies
for different years following emplacement, and for landfills with different levels of
extraction performance).
38
11.0 Landfill Types MELMod provides for 5 different landfill types. In recent years, the data currently in
MELMod has assumed that all landfilled waste is sent to so-called Type 3 landfills,
these being described as „Large modern landfills with comprehensive gas collection.
Sites began receiving waste in 1986, continuing thereafter.‟ There is no
differentiation across Landfill Types 1, 2 and 3 in the model so that their performance
is not in any way aligned with their description.
In principle, it would seem desirable to have, within MELMod, the potential to allow
for user-defined landfill variants to be specified within the model. One does not need
to know, at this time, exactly how the specifications might look to make the case for
the revision in model structure.
We suggested, at the end of Section 8.0, four broad types. However, the key point
would be that the number of Types should reflect the potential to allocate the waste
being emplaced in a given year to landfills of one or other type. It would seem that to
be able to achieve this accurately for past years would require considerable effort
(and indeed, may not be possible). Hence, the current figures are quite crude in the
manner in which they allocate waste to one or other landfill type over time.
In essence, one could perceive a range of arguments for having additional landfill
types:
1. First, and rather obviously, to reflect views as to the variation in performance
of different sites. The model currently „wastes‟ two landfill Types by modelling
them as behaving in exactly the same way as another Type. Presumably, if
these was a reason to assign waste to one or other landfill Type, it was based
upon differences in performance across these Types;
2. Second, to allow one to assign some of the waste already deposited
(historically) in one Type of landfill to a different landfill Type. This might be
desirable where, for example, additional attempts were being made either to
extract methane (low calorific flares, for example) or to alter the oxidation rate
through the cap (for example, through the use of active cover layers). Since it
could not be assumed that this was happening to all waste allocated to a given
landfill Type, it might not be appropriate to alter the characteristics of the
landfill Type concerned. It might be more appropriate to shift that waste into a
different landfill Type altogether (with different extraction efficiency, or
oxidation rate, or both);
3. The third might be for new landfills (or newer regulatory requirements), or to
„split‟ more carefully the landfills receiving waste in recent years into a broader
range of Types than is currently available (let alone, modelled). The discussion
at the end of Section 8.0 may or may not be deemed an appropriate basis for
this;
4. A fourth might be to reflect perceived changes in waste composition. In
respect of the latter, for example, the activity data highlights that landfilled
MSW is likely to have, today, a composition of just under 30% food waste. To
39
the extent that one accepts that food waste degrades relatively rapidly (see
the recommendation at the end of Section 7.0), then the efficiency of
extraction of methane in the exploitation phase becomes quite critical in
determining integral efficiencies of extraction. It might be sensible to assume
different extraction rates, reflecting the extent to which landfill gas is emitted
in the exploitation phase;36 and
5. A fifth reason might be to allow for new landfill concepts, such as cells
receiving only biologically stabilised wastes (for example, from mechanical
biological treatment systems). These might not have high capture rates, but if
they have active cover layers, the oxidation rates could be high.
Therefore, even if these types are not currently used, the model‟s flexibility could be
utilised through allowing for a range of landfill types. There is already one „user
defined‟ Type. There are also three types which are modelled in exactly the same way.
Hence, there is scope for some rationalisation in the model as it stands to allow for
additional landfill types, though this should only be undertaken where there is a
strong rationale (in terms of GHG performance) for doing so, and only if these Types
are not utilised in characterising the historic apportionment of landfilled waste across
different types.
Fundamentally, there is unlikely to be much point in using a very large number of
landfill types if data concerning what wastes are being emplaced in what Types of
landfill is not available in the appropriate form. The number of landfill Types ought to
reflect the ability to make reasonable assumptions in respect of the quantities
emplaced to each of these Types. To do otherwise will simply imply adding
sophistication without necessarily improving the accuracy of the model.
The following recommendations reflect the interlinked factors of Landfill Type, the
quantity of waste assumed to be placed in each Type, and the extraction efficiencies
used in MELMod for each of the landfill Types.
Recommendations:
We recommend that:
1) The modelled performance (in terms of gas extraction and oxidation rate) of
the Types of landfill within MELMod should be consistent with their
description;
2) The assumptions regarding the proportions of waste being sent to different
landfill types is revised to reflect more gradual transitions of waste away from
Type 2 sites (see Table 11-1);
3) That relevant agencies should seek to apportion waste being landfilled to
different landfill Types based upon the characteristics of the landfill where the
36 It should be noted that an alternative model would be to assign material specific extraction
efficiencies for each landfill type. More rapidly degrading wastes would have a lower extraction
efficiency than slower degrading ones, with the differences being greatest at those sites where gas
extraction is not present in the exploitation phase.
40
material is being emplaced (notably, in terms of its likely potential to extract /
oxidise landfill gas emissions).
The current profiling of landfill gas extraction efficiencies, which is used for all landfill
Types, and which rises as shown in Figure 11-1 below, is not supportable, either
through evidence or logic. It could not be a reflection of the integral extraction
efficiency at a given landfill Type (since this would be expected to be, by definition,
constant). It could not, either, reflect a logically coherent view as to how a national
rate would evolve over time since it peaks around 2004 and reaches a steady state
by 2009. It would only be by an astonishing coincidence that a national rate could
flatten off in this way, and so near (in time) in the future, simply because the
emplacement of waste in past years at less well-equipped sites would still be exerting
an influence on the extraction efficiency some way beyond this. Finally, if the graphic
was an attempt to anticipate the evolution of extraction efficiencies on the basis of
expected performance in future, then this would seem to make the extraction rate in
any year endogenous to the nature and quantity of waste being landfilled (if these
assumptions were wrong, the extraction efficiencies would need to change). Such an
approach would render the model extremely inflexible, unless there was a clear
functional relationship linking the proportion of DDOC landfilled in different landfill
Types to the extraction efficiency estimated (and there is not).
4) Because MELMod is not a model which adds together the emissions modelled
for each individual landfill, it is recommended that for each Type of landfill,
there is a single lifetime / integral collection efficiency which does not change
over time. This will incur some small errors, but they are well within the
bounds of what is reasonable to expect from such models;
Figure 11-1: Evolution in Extraction Rates Within MELMod (landfills of Type 1, 2 and3)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
41
Since MELMod assumes extraction rates which are the same for each of the landfill
Types (1, 2 and 3) receiving waste since 1980, methane is assumed to be extracted
at relatively high rates (in recent years) even from sites which are described as having
no gas collection system in place.
5) The extraction efficiency for sites with no gas collection should be set to zero;
6) The extraction rates need to reflect the landfill Type. We suggest a figure of 0%
for Type 1 sites (see above). For Type 2 and 3 sites, it is very difficult to
confidently state what extraction rates should be. Peer reviewers were critical
of our proposal that the extraction rates in MELMod should be changed for
Type 3 landfills to reflect the IPCC default (20%) for integral extraction
efficiency. The position reflected our view, and the intent of IPCC, that
extraction rates should not be overly-optimistic in the absence of clear
justification for higher levels. We suggest figures of 20% for Type 2 landfills
and 50% for Type 3 landfills, the latter figure being somewhat above the
national level of extraction efficiency calculated through reference to the level
of electricity generation from landfill gas.
These recommendations would, if adopted, give rise to the figures as set out in Table
11-1.
Table 11-1: Proposed Revisions Regarding Proportion of Waste Sent to Different
Landfill Types, and Associated Extraction Rates, 1995-2009
1995 1996 1997 1998 1999 2000 2001 2002
Type 1 48.0% 40.0% 30.0% 18.0% 4.0% 0.0% 0.0% 0.0%
Extraction
Efficiency 0% 0% 0% 0% 0% 0% 0% 0%
Type 2 38.8% 45.5% 54.2% 64.9% 77.6% 70% 60 50%
Extraction
Efficiency 20% 20% 20% 20% 20% 20% 20% 20%
Type 3 13% 14% 16% 17% 18% 30% 40% 50%
Extraction
Efficiency 50% 50% 50% 50% 50% 50% 50% 50%
2003 2004 2005 2006 2007 2008 2009
Type 1 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Extraction
Efficiency 0% 0% 0% 0% 0% 0% 0%
Type 2 40% 30% 20% 10% 0.0% 0.0% 0.0%
Extraction
Efficiency 20% 20% 20% 20% 20% 20% 20%
Type 3 60% 70% 80% 90% 100% 100% 100%
Extraction
Efficiency 50% 50% 50% 50% 50% 50% 50%
42
12.0 Landfill Gas Composition Some information regarding landfill gas formation and its composition is given in
Appendix A.7.0. MELMod assumes 50% of the landfill gas by volume is CH4. LQM
confirmed the basis for this assumption, initially made in the National Assessment
Model, in their 2003 report to Defra, as follows:37
The decomposition of cellulose in landfilled waste gives rise to both methane
and carbon dioxide, in approximately equal quantity by volume. The
mechanics of this process are a number of different biochemically mediated
reaction schemes (AFRC, 1988), and so the actual quantity of methane or
carbon dioxide produced by decomposition will vary according to the dominant
microbiological processes. For a single site, the ratio of methane to carbon
dioxide may differ from the typical 50:50 ratio observed. However, in a
situation where the entire UK LFG inventory is being simulated (as in the
National Assessment Model), these differences will tend to even out. For the
purposes of modelling this process, a value of F of 0.5 has been used.[…].
In older uncapped sites, natural diffusion of air through the cover materials
led to a greater degree of aerobic degradation, and thus the proportion of
methane produced changed from 50:50 reflecting the increased carbon
dioxide and reduced methane production. Consequently, it is considered that
for Type 1, 2 and 3 landfills (the more modern designs) the model should be
run with a methane content in LFG of 50%, and so F = 0.5. For Type 4 landfills
(the old unengineered design), a methane content in LFG of 30% has been
used, and so F = 0.3. These settings are identical to those used by Brown et
al. (1999).
The assertion that 50% of landfill gas by volume is methane is widely held, and
appears to be the default assumption in the five models considered in a Canadian
model calibration study.38 However, Afvalzorg assume 56% of the gas to be CH4,
whilst Oonk, in his recently published literature review on CH4 generation from
landfills, indicated a range of possible CH4 concentrations in landfill gas of between
45 and 60% - the latter echoing the range of values proposed in earlier analysis by
Tchobanoglous et al. 39
37 LQM (2003) Methane Emission from Landfill Sites in the UK, Final Report for Defra, January 2003
38 Thompson S, Sawyer J, Bonam R and Valdivia JE (2009) Building a better methane generation
model: Validation models with methane recovery rates from 35 Canadian landfills, Waste
Management, 29, pp2085-2091
39 Oonk H (2010) Literature Review: Methane from Landfills: Methods to Quantify Generation,
Oxidation and Emission, Report for Sustainable Landfill Foundation; Jacobs J and Scharff H (u.d.)
Comparison of Methane Emission Models and Methane Emission Measurements, NV Afvalzorg, The
Netherlands; Tchobanoglous G, Hilary T and Vigil S (1993) Integrated Solid Waste Management:
Integrated Principles and Management Issues, McGraw-Hill, New York
43
12.1 Summary
The discussion in Appendix A.7.0 suggests the main phase of methanogenesis
produces a landfill gas that is relatively high in methane, particularly where the
degradation of fats and proteins is concerned. At this point in the degradation cycle,
the methane concentration may be as high as 60%. What happens during the early
stages landfilling is relatively significant as it is at this point that an appreciable
proportion of the fugitive emission is likely to occur. The degradation of fats and
proteins may also be relatively rapid in comparison to that of the cellulosic materials
and thus might be expected to exert a particular influence during these early stages.
However, in the situation where conditions for methanogenesis are sub-optimal, and
during the latter phases of the operation of the landfill, the relative proportion of
methane can be expected to decrease relative to that of the CO2 such that it may
account for considerably less than 50% of the content of the gas. The proportion of
methane in landfill gas is thus likely to vary considerably throughout the lifetime of
landfill, and will be dependent in part on the long term landfill management regime
and the extent to which optimal conditions for methanogenesis are present.
Current MELMod data assumes that landfill gas generated at Type 4 landfills (the
older uncapped sites) has a methane concentration of 30% reflecting the higher
proportion of aerobic degradation anticipated to occur at such sites. However the lack
of covering material is also likely to allow for greater penetration of moisture into the
lower layers of the landfill, and this would tend to increase methanogenesis thus
increasing the proportion of methane. Furthermore, if it really were the case that
more of the degradation was aerobic, then all of the factors characterising the Type 4
landfills would, logically, have to change. In particular, the degradation of lignin would
be expected to be higher, so that the 30% figure might possibly reflect a smaller
proportion of a higher level of degradation of the materials landfilled. We recommend,
therefore, that in the absence of a complete overhaul of the Type 4 modelling, the
50% figure is used for these sites too. It is not reasonable to consider methane
concentration in isolation from all of the factors characterising degradation in these
landfills, particularly where the underlying rationale relates to the ingress of air.
Recommendation: It is felt that there is no strong reason to change the assumption
that the methane content of landfill gas is 50% for landfill Types 1, 2 and 3 as current
knowledge suggests this to be a reasonable proxy for gas composition over the
lifetime of the landfill.
We recommend that the same proportion be extended to cover Type 4 landfills in the
absence of a far more fundamental overhaul of the modelling of the Type 4 sites.
44
13.0 Recommendations and Changes Made in
MELMod
13.1 Recommendations
On the basis of the work undertaken, a number of recommendations have been
made. We list these below, and also indicate whether the recommendation was
accepted.
Recommendation 1
Regarding activity data and waste composition, we recommended that the data in
MELMod model be updated to include our activity data and the associated waste
compositions. The confidence we have in our proposals for local authority managed
waste is as high as it can be, recognising that there will always be limitations in this
regard.
Where C&D and C&I wastes are concerned, we have had to incorporate rather more
by way of estimates and generalising assumptions. The data remains extremely poor
in terms of its quality, and this applies with special force to our knowledge of the
composition of the waste generated, and being landfilled. Notwithstanding these
points, there is, at least, within the data which we have derived some underlying
rationale for the figures. The same cannot be said for the data in the existing model.
We believe, therefore, that our activity data for C&I and C&D waste constitutes a
significant improvement upon that which exists in the existing model. Sadly, however,
one cannot express a high level of confidence in the overall quality of this data. There
is a pressing need to improve upon the quality of the data which characterises how
much C&I and C&D data there is, what it actually looks like, and how it is managed.
It should be noted that we believe it would be desirable to split the waste streams
down further into household waste, commercial waste, industrial waste and
construction and demolition waste. MELMod would also benefit, in future, from
having a far greater number of rows available to characterise the composition of each
of these waste streams.
This recommendation was accepted. The new activity and composition data has been
used within MELMod.40
When this data was entered into the model, with the changes in the data relating to
the period post 1995, a discontinuity showed up in the amount of degradable organic
carbon being landfilled in the years where new data was entered. Although this does
not translate into major discontinuities in the emissions from landfills (which reflect
the degradable organic carbon landfilled over a number of years), in order to
eliminate these discontinuities, it was decided to „smooth‟ the introduction of the new
40 It was not possible to accommodate in MELMod, under C&I waste, paper and card as two distinct
categories. They were, therefore, characterised as paper (rather than paper and card).
45
data and the phasing out of the old. This is effectively a requirement under IPCC
guidelines.
The rationale for the pre-1995 data was not easy to discern. However, in MELMod,
one notes that in the pre-1997 period, Commercial waste and general industrial
waste make up 75%-84% of all DDOC over time (for the non-MSW / local authority
managed waste). In MELMod, these materials have had their „growth path‟ (or trend
growth) altered in the historic data at various points. In particular:
1. There is a change in the rate of growth of waste in 1965. This appears to be the
first point where there is recognition that industrial waste to landfill might be
declining, though with commercial waste continuing to increase (previously, both
were increasing). In this period (from 1965), DDOC starts to fall
2. There is a further change in 1975. Here, industrial waste to landfill starts to
increase once more. DDOC also starts to turn upward again. From 1975 onwards,
at least until around 1996, the data simply shows an upward trend for all
materials with the exception of construction waste, which in any case is not a
major contributor to DDOC (1.52%, falling to 0.87% in 1995);41
3. In 1996, there is a discontinuity. This is not a large one, but is fairly significant by
comparison with the minimal changes which occur from year to year in the
preceding period (1945 to 1995). There is, in general, a lack of any change over
this period, reflecting, we suspect, the paucity of any data of any quality on this
issue prior to the landfill tax‟s introduction (but arguably, in truth, continuing also
to the present day if one considers composition as a relevant matter, and it clearly
is).
Our approach was to smooth the data from 1975, which is the last point from which it
appears someone in the past discerned the need to change the trend in waste
landfilled. We do not know the reason for this, but presumably, there was one.
The smoothing of the data was achieved in the following way:
1. Some „waste types‟ in MELMod are no longer used post 1996
2. Some new „waste types‟ are used from 1997
3. The category „other‟ essentially contains „non-gassing‟ materials, but in
the pre 1997 period, this quantity is much smaller than post 1997,
mainly because we have effectively sought to identify separately, post-
1996, the „gassing‟ elements of mixed commercial, mixed industrial,
and C&D, leaving a larger „non gassing‟ (other) fraction;
41 Note that the best data available to us suggests that far from declining to 14 million tonnes or so by
1995, the quantity of C&D waste landfilled was around 35 million tonnes in 1997 – a truly massive
discrepancy. The quantity of waste landfilled at the lower rate of tax in 1997 was around 31 million
tonnes, and this excludes a) C&D waste exempt from tax (and reported as such to HMRC) and b) C&D
materials landfilled at sites not registered for tax at all (because they were only receiving untaxed
waste, and so, completely unreported as far as HMRC was concerned).
46
4. For categories in MELMod pre-1997, but not post-1997, we have set
these to decline linearly from their 1975 level to zero
5. For categories not in MELMod pre-1997, but in MELMod in subsequent
years, these increase from zero in 1975 to the level we have estimated
for them in 1997; and
6. For the category „other‟, the numbers from 1975 increase linearly to
the figure we have estimated from 1997.
This gives a smooth decline in DDOC; and a smooth decline in tonnages sent to
landfill, thus eliminating discontinuities. Effectively what happens is that the influence
of our calculations is increasing from 1975 onwards, and from 1975 onwards, the
significance of the previous data is diminished. The data „shades‟ from the previous
figures to those we have estimated.
Recommendation 2
We recommended a revised set of values for moisture and carbon content (as well as
the carbon constituents) for some materials already in MELMod and proposed values
for some materials not in MELMod.
The proposal was accepted and the values incorporated into MELMod.
Recommendation 3
We suggested that the approach taken for most waste fractions, for calculating
DDOC, should be as follows:
Calculate, from the biochemical constituents and their relative proportions of
carbon (see Section 5.0), the amount of carbon in fresh matter which is
deemed degradable. This should be done for non-lignin fractions, and
separately, for lignin;
Assume, bearing in mind that the modelling considers impacts occurring over
the long-term, that
For food waste, 70% of the non-lignin fraction is considered degradable
along with 15% of the lignin (it should be noted that this may be
conservative given, for example, the evidence in Table 6-2);
For garden waste, 65% of the non-lignin fraction is considered
degradable along with 10% of the lignin; and
For all other degradable materials 65% of the non-lignin fraction is
considered degradable along with 5% of the lignin.
For textiles, we propose to retain the existing MELMod assumptions due to the
lack of detailed biochemical data and composition analysis.
These changes were accepted and incorporated into MELMod.42
42 It should be noted that during the final revision of this report, it transpired that an error had been
made in entering the relevant figures, characterising the properties of „textiles‟, into MELMod. This
47
Recommendation 4
Regarding decay constants, we made two recommendations:
1) that the rate constants be linked to the different biochemical fractions of the
waste. We suggest that the assignment is as follows:
a. Slow The small proportion of lignin assumed to be degraded
over the long term (calculated as in Section 6.0 above)
b. Medium Biochemical components other than those above and
below (cellulose, hemicellulose, etc.)
c. Fast Sugars and Fats; and
2) that as far as rate constants were concerned, the IPPC defaults should be
used (reflecting the fact that, for the rapidly degrading fraction in particular,
the rate in MELMod appears much lower than is the case in most other multi-
phase models, and is close to the average decay rate in models representing
mixed waste).
The first recommendation was accepted and reflected in the modelling of the
degradation of specific waste components. The second recommendation was not
accepted.
Recommendation 5
We recommended, in respect of the apportioning of waste to different landfill types,
that:
1) The modelled performance (in terms of gas extraction and oxidation rate) of
the Types of landfill within MELMod should be consistent with their
description;
2) That the assumptions regarding the proportions of waste being sent to
different landfill types is revised to reflect more gradual transitions of waste
away from Type 2 sites;
3) That relevant agencies should seek to apportion waste being landfilled to
different landfill Types based upon the characteristics of the landfill where the
material is being emplaced (notably, in terms of its likely potential to extract /
oxidise landfill gas emissions).
These recommendations were not accepted. It should be noted that some
consideration was given to changing the allocation of waste to different landfill types.
However, this was rejected since the shift of waste into sites described as having no
gas extraction led, perhaps counterintuitively, to an overall reduction in emissions.
This is because the combination of MELMod‟s high capture rate for such sites, and
the assumption regarding 30% concentration of methane in landfill gas, led to an
overall reduction in emissions rather than an increase (partly because
error came to light too late to alter the latest inventory report but will be addressed in subsequent
years through correcting the figures in the model. Our understanding is that this will lead to only a
small change in the inventory.
48
recommendations for change in the parameters characterising such landfills were not
accepted).
Recommendation 6
We made the following recommendations related to gas extraction efficiencies:
1) Because MELMod is not a model based upon a summation of emissions
modelled for each individual landfill, the use of integral collection efficiencies
for each landfill Type is appropriate (rather than, as currently, changing
profiles over time for each Type);
2) Since MELMod assumes extraction rates which are the same for each of the
landfill Types (1, 2 and 3) receiving waste since 1980, methane is assumed to
be extracted at high rates (in recent years) even from sites which are
described as having no gas collection system in place. These figures should be
changed;
3) In the absence of clear bases for the assumptions used regarding capture
rates, and partly to encourage the generation of information allowing lifetime
extraction efficiencies to be understood, we recommended that the IPCC
default figure (20%) should be used for those sites with gas extraction
equipment in place. We subsequently proposed an amended set of values to
reflect three distinct types of landfill (0% for those with no gas extraction (Type
1), 20% for those with limited gas extraction equipment (Type 2) and 50% for
the most modern landfills (Type 3).
These recommendations were not accepted and so MELMod retains the existing
assumptions regarding gas extraction efficiencies.
Recommendation 7
Regarding oxidation rates, we made the following recommendation:
1. We recommend continuing with the 10% figure for oxidation used for Type 3
landfills in MELMod. This should be kept under review, since some literature
suggests this value may be too low
The recommendation was accepted, so no changes were made to MELMod as a
result.
Recommendation 8
Regarding the concentration of methane in landfill gas, we made two
recommendations:
1. There is no strong reason to change the assumption that the methane content
of landfill gas at the 3 newer Types of landfill in MELMod is 50%
2. The same proportion should be extended to cover older Type 4 landfills in the
absence of a far more fundamental overhaul of the modelling of the Type 4
sites since the presumption that a lower methane concentration would follow
from the existence of partly aerobic conditions ought also to consider that
fractions of waste such as lignin will degrade to a greater extent under such
conditions.
49
The first of these was accepted, but the second was not, so no changes were made to
MELMod as a result.
50
14.0 References Abichou, T. & Chanton, J. (2004) Characterization of Methane Flux, Oxidation, and
Bioreactive Cover Systems at the Leon County Landfill, Annual Report- Florida Center
for Solid and Hazardous Waste Management.
Abichou T., Johnson T., Mahieu K., Chanton J.P., Romdhane J., Mansouri I. (2010)
Developing a Design Approach to Reduce Methane Emissions from California
Landfills, Florida State University, USA.
Adams, K. on behalf of the Strategic Forum for Construction (2010) CD & E Waste:
Halving Construction, Demolition and Excavation Waste to Landfill by 2012
Compared with 2008, March 2010
http://www.strategicforum.org.uk/pdf/Waste_Draft_Part%202_22-3-10V4.pdf
ADAS (2009) National Study into Commercial and Industrial Waste Arisings, Final
report for EERA.
AEA (2008) Revision of UK Model for Predicting Methane Emissions from Landfills
Task 3 Report – Review of Methodology, Data Quality & Scope for Improvement,
Report to Defra, October 2008.
AEAT (2003) The Composition of Municipal Waste in Wales, National Assembly for
Wales (NAW)/AEAT Technology - December 2003.
Austrian Energy Agency (u.d.) Wood Fuels: Characteristics, Standards, Production
Technology; NCP (u.d.) Wood as a Fuel: Material for 5EIRES Training Sessions
Baggott, S. L. et al (2006) Addendum to UK Greenhouse Gas Inventory, 1990 to
2004, Annual Report for submission under the Framework Convention on Climate
Change, Report RMP/2106, July 2006.
Baldwin, T.D., Stinson, J., and R. K. Ham.(1998) Decomposition of specific materials
buried within sanitary landfills. Journal of Environmental Engineering, 124 (12):1193-
1202.
Barkdoll A, Nordsedt R and Mitchell D (2001) Large Scale Utilization and Composting
of Yard Waste, University of Florida.
Barlaz M A (2004) Critical Review of Forest Products Decomposition in Municipal
Solid Waste Landfills, National Council for Air and Stream Improvement, Bulletin 872.
Barlaz M A (2006) Forest products decomposition in municipal solid waste landfills,
Waste Management, Issue 26, pp. 321-333.
Barlaz M., Green R.B., Chanton J.P., Goldsmith C.D., Hater G.R. (2004) Evaluation of a
biologically active cover for mitigation of landfill gas emissions, Environ. Sci. Technol.,
38, pp. 4891-4899.
Barlaz, M. A. Ham, R. K. Schaefer, D. M. J. (1989) Journal of Environmental
Engineering . Eng. Div.(Am. Soc. Civ. Eng.) 1989, 115, 1088-1102.
Barry D.L., Watts M., Smith R. (2004) Practical gas emission control during landfilling,
Proc. Waste 2004 Conf. Integrated Waste Management and Pollution Control: Policy
51
and Practice, Research and Solutions. Stratford-upon-Avon, UK, 28-30 September
2004, 315-324.
Beker D and Cornelissen A A J (1999) Chemische Analyse Van Huishoudelijk
Restafval: Resultaten 1994 en 1995, National Institute of Public Health and the
Environment, Nederland.
Bergamaschi, P. C. Lubina, R. Königstedt, H. Fischer, A.C. Veltkamp, and O.
Zwaagstra (1998) Stable isotopic signatures ( 13C, D) of methane from European
landfill sites. J. Geophys. Res. Atmos. 103:8251–8265.
Biocycle (2009) Demonstration Project: Biocycle South Shropshire Ltd Biowaste
Digestor, Report for Defra.
Biomass Energy Centre http://www.biomassenergycentre.org.uk
Boddy L (1983) Microclimate and Moisture Dynamics of Wood Decomposing in
Terrestrial Ecosystems, Soil Biology and Biochemistry, 15, pp146-157.
Boekx, P., Van Cleemput, O., and Villaralvo, I. (1996) Methane emission from a landfill
and the methane oxidising capacity of its covering soil, Soil Biology & Biochemistry,
vol. 28, pp 1397-1405.
Börjesson G., Svensson B. (1997) Seasonal and diurnal methane emissions from a
landfill and their regulation by methane oxidation, Waste Management and Research,
15, pp. 33–54.
Börjesson, G, Jerker Samuelsson, and Jeffrey Chanton (2007) Methane Oxidation in
Swedish Landfills Quantified with the Stable Carbon Isotope Technique in
Combination with an Optical Method for Emitted Methane, Environmental Science
and Technology 2007, 41 (19), pp.6684-6690.
Borjesson, G., J. Chanton, and B.H. Svensson (2001) Methane oxidation in two
Swedish landfill covers measured with carbon-13 and carbon-12 isotope ratios, J.
Environ. Qual. 30, pp. 376–386.
Cabral, A.R., Tremblay, P. & Lefebvre, G. (2004) Determination of the diffusion
coefficient of oxygen for a cover system composed of pulp and paper residues. ASTM
Geotechnical Testing Journal, 27, pp. 184–197
Capita Symonds (2006) Survey of Arisings and Use of Construction, Demolition and
Excavation Waste as Aggregate in Northern Ireland in 2004/05 and 2005/06, Final
Report to the Northern Ireland Environment and Heritage Service, June 2006.
Capita Symonds with Alfatek Redox (2010) Construction, Demolition and Excavation
Waste Arisings, Use and Disposal for England 2008. CON900-001, Final Report to
WRAP.
Cecchi F, Traverso P, Pavan P, Bolzonella D and Innocentia L (2003) Characteristics
of the OFMSW and behaviour of the anaerobic digestion process, in Biomethanization
of the Organic Fraction of Municipal Solid Wastes, Ed. Mata-Alvarez J, Publ. IWA
Publishing.
Centre for a Competitive Waste Industry (2004) Day of Reckoning: Protecting
California Tax-Payers from the Looming Landfill Crisis: Report to the Grassroots
Recycling Network, September 2004.
52
Center for a Competitive Waste Industry (2008) Landfill Gas to Energy Compared to
Flaring.
Chandler, J.A., W.J. Jewell, J.M. Gossett, P.J. Van Soest, and J.B. Robertson (1980)
Predicting methane fermentation biodegradability. Biotechnology and Bioengineering
Symposium No. 10, pp. 93-107.
Chanton, J.P., D.K. Powelson, T. Abichou, and G. Hater. (2008) Improved field
methods to quantify methane oxidation in landfill cover materials using stable isotope
carbon isotopes, Environ. Sci. Technol., 42, pp. 665–670.
Chanton, J.P., Fields, D., Bogner, J., Morcet, M., and Scheutz, C. (2002). A Stable
Isotope Technique for Determining Methane Oxidation in Landfill Covers, Proceedings
SWANA 25th annual landfill gas symposium, March 25-28th, Monterey, California,
published by SWANA, Silver Spring, MD.
Chanton J.P., Powelson D.K., Green R.B. (2009) Methane oxidation in landfill cover
soils, is a 10% default value reasonable? J. Environ. Qual. 38:654–663.
Christophersen, M. and Kjeldsen, P. (1999) Field investigations of lateral gas
migration and subsequent emission at an old landfill; Sardinia 99 Seventh
International Waste Management and Landfill Symposium; IV (79-86); 4-8 October
1999, Cagliari, Italy
Christophersen M., Kjeldsen P., Holst H., Chanton J. (2001): Lateral gas transport in
soil adjacent to an old landfill: factors governing emissions and methane oxidation,
Waste Manag. Res., 19, pp. 595-612.
Chugh, S, Chynoweth, D.P., Clarke, W., Pullammanappallil, P. and V. Rudolph (1999)
Degradation of unsorted municipal solid waste by a leach bed process, Bioresource
Technology, 69, pp103-115.
CLG (1999, 2001, 2003 and 2005 ) Survey of Arisings and Use of Construction,
Demolition and Excavation Waste as Aggregate in England (1999, 2001, 2003 and
2005 reports).
Colberg, P.J., (1988)-Anaerobic microbial degradation of cellulose, lignin, oligolignols,
and monoaromatic lignin derivatives. In Biology of anaerobic microorganisms, ed. A.
J. B. Zehnder, 333-372. New York.
Conrad, H.R., W.P. Weiss, W.O. Odwongo, and W.L. Shockey. (1984) Estimating net
energy of lactation from components of cell solubles and cell walls. J. Dairy Sci.
67:427-436.
Coops O, Lunin L, Oonk H and Weenk A (1995) Validation of Landfill Gas Formation
Models, in Proceedings Sardinia 95, Fifth International Landfill Symposium, Cagliari,
Italy, October 2-6, pp635-646.
Czepiel P.M., Mosher B., Crill P.M., Harris R.C. (1996b) Quantifying the effect of
oxidation on landfill methane emissions, Journal of Geophysical Research. 101,
16721-16729.
Dalemo, M (1996) The Modelling of an Anaerobic Digestion Plant and a Sewage Plant
in the ORWARE Simulation Model, Rapport 213, Swedish University of Agricultural
Sciences, Uppsala 1996.
53
Dalemo, M. (2004) The Modelling of an Anaerobic Digestion Plant and a Sewage
Plant in the Orware Simulation Model: Swedish University of Agricultural Sciences,
Report 213.
Danish Energy Agency (2009) Denmark‟s fifth national communication on climate
change, Danish Energy Agengy, Denmark.
Das K (2007) Co-composting of Alkaline Tissue Digester Effluent with Yard Trimmings,
Waste Management, 28, 1785-1790.
Davidsson A, Gruvberger C, Christensen T, Hansen T and la Cour Jansen J (2007)
Methane Yield in Source-sorted Organic Fraction of Municipal Waste Management,
Waste Management 27 pp.406-14.
Department of Climate Change and Energy Efficiency (Australian Government) (2010)
Review of the NGER (Measurement) Determination, Discussion Paper, August 2010,
http://www.climatechange.gov.au/government/submissions/reporting/~/media/publ
ications/greenhouse-report/review-nger-measurement-determination-paper.ashx
Dehority, B. A. and R. R. Johnson. (1961) Effect of particle size upon the in vitro
cellulose; digestibility of forages by rumen bacteria. Journal of Dairy Science, V
(44):2242-2249.
ECOTEC (2000) Effects of the Landfill Tax – Reduced Disposal of Inert Wastes to
Landfill, Final Report to DETR, January 2000.
Ehrig H and Scheelhaase T (1999) Abschätzung der Restemissionen von Deponien in
der Betriebs und Nachsorgephase auf der Basis realer Überwachungsdaten,
Bergische Universität – Gesamthochschule Wuppertal, Germany.
Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal
Solid Waste Components in Laboratory Scale Landfills, Environmental Science and
Technology, 31, pp911-917.
Environment Agency (2008) Wales Construction And Demolition Waste Arising Survey
2005-06, http://www.environment-
agency.gov.uk/research/library/publications/33979.aspx
Enviros (2003) Environment and Heritage Service: Construction and Demolition
Waste Survey, April 2003.
ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes,
Final Report for Defra, December 2006.
ERM (2008) An updated lifecycle assessment study for disposable and reusable
nappies, Environment Agency Science Report – SC010018/SR2,
http://publications.environment-agency.gov.uk/pdf/SCHO0808BOIR-e-e.pdf
Eunomia (2008) Scoping New Municipal Waste Targets for Wales, Report for the
Welsh Local Government Association and the Welsh Assembly Government.
Fawcett, J D and Ham R K (1986) Refuse analysis data and evaluation for the
Mountain View controlled landfill project, Department of Civil and Environmental
Engineering, The University of Wisconsin – Madison.
Fellner J., Schöngrunder P., Brunner P.H. (2003) Methanemissionen aus Deponien,
Bewertung von Messdaten (METHMES), Technische Universität Wien, Austria.
54
Flemming J, Frandsen S, van Lith S, Korbee R, Yrjas P, Backman R, Obenberger I,
Brunner T and Joller M (2007) Quantification of the Release of Inorganic Elements
from Biofuels, Fuel Processing Technology, 88, pp1118-1128.
Fredenslund A.M., Kjeldsen P., Scheutz C., Lemming G. (2007) BIOCOVER –
Reduction of Greenhouse Gas Emissions from Landfills by Use of Engineered Bio
Covers Eco Tech 2007, 6th International Conference on Technologies for Waste and
Wastewater Treatment, Energy from Waste, Remediation of Contaminated Sites,
Emissions Related to Climate, Kalmar.
Gardner W D, Ximenes F, Cowie A, Marchant JF, Mann S and Dods K (2003)
Decomposition of Wood Products in the Lucas Heights Landfill Facility: Internal
Report, Research and Development Division, State Forests of New South Wales.
Gebert J., Gröngröft A. (2007) Potential and Limitations of Passively Vented Biofilters
for the Microbial Oxidation of Landfill Methane, 2nd BOKU Waste Conference, Vienna,
April 2007.
Gebert J., Rachor I., Gröngröft A. (2009) Column Study for Assessing the Influence of
Soil Compaction on CH4 Oxidation in Landfill Covers, University of Hamburg, Ger-
many.
Godley A, Frederickson J, Lewin K, Smith R and Blakey N (2007) Application of DR4
and BM100 Biodegradability Tests to Treated and Untreated Organic Wastes,
Proceedings of the Eleventh International Waste Management and Landfill
Symposium, Caliari, Italy, October 2007.
Godley A and Frederickson J (2010) Supporting Agency MBT Model Development,
Report for the Environment Agency, May 2010.
Ham R K and Bookter T J (1982) Decomposition of Solid Waste in Test Lysimeters,
Journal of Environmental Engineering, 108, pp1147-1170.
Ham R K, Norman M R and Fritschel P R (1993) Chemical Characteristics of Fresh
Kills Landfill Refuse and Extracts, Journal of Environmental Engineering, 119, pp176-
1195.
Hogg, D. (1999) The Effectiveness of the UK Landfill Tax: Early Indications, in Thomas
Sterner (ed.) (1999) The Market and the Environment: Environmental Implications of
Market-Based Policy Instruments, Cheltenham: Edward Elgar.
Huitric, R., and Kong, D. (2006) Measuring Landfill Gas Collection Efficiencies Using
Surface Methane Concentrations, Solid Waste Association of North America (SWANA)
29th Landfill Gas Symposium, St. Petersburg, FL.
Huitric, R., Kong, D., Scales, L., Maguin, S., and Sullivan, P. (2007) Field Comparison
of Landfill Gas Collection Efficiency Measurements, Solid Waste Association of North
America (SWANA) 30th Landfill Gas Symposium, Monterey, CA.
Hyder Consulting (2009) in consultation with Morton Barlaz, in Department of Climate
Change and Energy Efficiency (Australian Government) (2010) Review of the NGER
(Measurement) Determination, Discussion Paper, August 2010,
http://www.climatechange.gov.au/government/submissions/reporting/~/media/publ
ications/greenhouse-report/review-nger-measurement-determination-paper.ashx
55
IPCC (2006) IPCC Guidelines for National Greenhouse Gas Inventories 2006: Chapter
3 - Solid Waste Disposal, http://www.ipcc-
nggip.iges.or.jp/public/2006gl/pdf/5_Volume5/V5_3_Ch3_SWDS.pdf
IPCC (2006) 2006 Guidelines for National Greenhouse Gas Inventories: Volume 5,
Waste.
Johnson, C. and Worrall, F. (2006) Modelling the fate of carbon from MSW during
incineration, landfill, aerobic digestion and application of CLO to land, Report from
the University of Durham, 28th April 2006.
Jones K L and Grainger J M (1983) Methane Generation and Microbial Activity in a
Domestic Refuse Landfill Site, European Journal Applied Microbiological
Biotechnology, 18, pp242-245.
Julian Parfitt (2002) Analysis of Household Waste Composition and Factors Driving
Waste Increases, Report to the Prime Minister‟s Strategy Unit, November 2002.
http://www.cabinetoffice.gov.uk/media/cabinetoffice/strategy/assets/composition.p
df
Jung, H. G. and K. P. Vogel (1986) Influence of lignin in digestibility of forage cell wall
material. Journal of Animal Science, 62:1703-1712.249.
Kim H (u.d.) Cellulose Synthase Catalytiuc Subunit (Cesa) Genes Associated with
Primary or Secondary Wall Biosythesis in Developing Cotton Fibres, University of New
Orleans.
Kitani O and Hall C (1989) Biomass Handbook, Publ. Gordon and Breach Science
Publishers.
Kühle-Weidemeier M., Bogon H., (2008) Methanemissionen aus passiv entgaste
Deponien und der Ablagerung von mechanisch-biologisch behandelten Abfällen -
Emissionsprognose und Wirksamkeit der biologischen Methanoxidation -
Schlussbericht, Wasteconsult international, Langenhagen, Germany.
Lambert C., Schachermayer E. (2008) Deponiegaserfassung auf österreichischen
Deponien, Zeitreihe 2002 bis 2007, Umwelbundesamt, Austria.
Land Quality Management (2003) Methane Emissions from Landfill Sites in the UK,
Report for Defra, January 2003.
Lohila, A., Laurila, T., Tuovinen, J.P., Aurela, M., Hatakka, J., Thum, T., Pihlatie, M.,
Rinne, J., and T. Vesala (2007) Micrometeorological measurements of methane and
carbon dioxide fluxes at a municipal landfill, Environmental Science and Technology,
41, p. 2717–2722.
LQM (2003) Methane Emissions from Landfill Sites in the UK, Final Report to Defra,
January 2003.
Maurice C., Lagerkvist A. (1997) Seasonal influences of landfill gas emissions,
Sardinia 97 Sixth International Landfill Symposium; IV (87-94); 13-17 October 1997,
Cagliari, Italy
MEL and EnviroCentre (2002) Industrial and Commercial Waste Production in
Northern Ireland, Final Report to the Northern Ireland Environment and Heritage
Service.
56
Michels, M., Hamblin, G. (2006) LFG Collection Efficiency is Improving in Wisconsin,
Waste Management, Cornerstone Environmental Group.
Ministry for the Environment (2007) The 2006/07 National Landfill Census, October
2007, New Zealand.
Mosher, B. W., Czepiel, P.M., Harriss, R.C., Shorter, J.H., Kolb, C.E., McManus, J.B.,
Allwine, E., and Lamb, B.K. (1999) Methane emissions at nine landfill sites in the
northeastern United States, Environmental Science and Technology 33, p. 2088–
2094.
NIEA (2000) Industrial and Commercial Waste Arisings Survey for Northern Ireland,–
Survey Report by the Environment and heritage Service of Northern Ireland.
http://www.ni-environment.gov.uk/waste_arisings_survey_ni_screen.pdf
NIFES (2004) Wood-fuel Seminar: Notes and Worked Examples: Seminar for OPET
Scotland.
Oonk H (2010) Literature Review: Methane from Landfills: Methods to Quantify
Generation, Oxidation and Emission, Report for Sustainable Landfill Foundation.
Oonk H., (2010) Oxidatie van methaan in toplagen van stortplaatsen, naar een betere
kwantificering, OonKAY!, Apeldoorn, The Netherlands.
Oonk H and Boom T (1995) Landfill Gas Formation, Recovery and Emission, TNO-
rapport 95-203.
Oonk H., Weenk A., Coops O., Luning L., (1994) Validation of Landfill Gas Formation
Models, TNO, Dutch organization for Applied Scientific Research, Report No. 94-315.,
Apeldoorn, The Netherlands.
Pfeffer, J. T. and K. A. Khan. (1976) Microbial production of methane from municipal
refuse. Biotechnology and Bioengineering, 18:1179-1191.
Phyllis Database for Biomass and Waste http://www.ecn.nl/phyllis/
Preece, I..A. (1931) Studies on hemicelluloses. IV. The proximate analysis of box-wood
and the nature of its furfuraldehyde-yeilding constituents. Biochemical Journal 25(4)
1304-1318
Price G A, Barlaz M A, Hater G R, (2003) Nitrogen management in bioreactor landfills.
Waste Management, 23, pp675–688.
Resource Futures (2010) Municipal Waste Composition: Review of Municipal Waste
Component Analyses, Report to Defra, WR0119,
http://randd.defra.gov.uk/Document.aspx?Document=WR0119_8662_FRP.pdf
Ress B B, Calvert P P, Pettigre, C A and Barlaz M A (1998) Testing anaerobic
biodegradability of polymers in a laboratory-scale simulated landfill, Environmental
Science & Technology, 32, pp821-827.
Rhew R and M A Barlaz (1995) The effect of lime stabilized sludge as a cover material
on anaerobic refuse decomposition, Journal of Environmental Engineering, ASCE,
121, pp499- 506.
RPS (2008) Review of Municipal Waste Component Analysis (Northern Ireland),
2008.
57
Scharff H and Jacobs J (2006) Applying Guidance for Methane Emission Estimation
for Landfills, Waste Management, 26, pp417-429.
Scharff H., Martha A., v. Rijn D.M.M., Hensen A., Flechard C., Oonk H., Vroon R., de
Visscher A., Boeckx P. (2003) A comparison of measurement methods to determine
landfill methane emissions, NV Afvalzorg, Haarlem, The Netherlands.
Scheutz C., Kjeldsen P., Bogner J.E., De Visscher A., Gebert J., Hilger H.A., Huber-
Humer M., Spokas K. (2009) Microbial methane oxidation processes and
technologies for mitigation of landfill gas emissions, Waste Management & Research,
27: pp. 409–455.
SEAFL (1998) Life Cycle Inventories for Packagings, Volumes I and II, Environmental
Series No. 250/I&II Waste, Berne, Switzerland, Swiss Agency for the Environment,
Forest and Landscape.
SenterNovem (2005): Handreiking Methaanreductie Stortplaatsen (Guidelines
methane emission reduction from landfills), SenterNovem (currently AgentschapNL.
Dutch Agency for Sustainability, Innovation and International Trade and Cooperation,
Utrecht, The Netherlands.
SEPA (2005) Commercial and Industrial Waste Survey 2004/5, Available:
http://www.sepa.org.uk/NWS/data /survey.htm
SEPA (2004) Waste Data Digest 4 (2002 and 2002/3 Data),
http://www.sepa.org.uk/waste/waste_data/waste_data_digest.aspx
SEPA (2007) Scotland Business Waste Survey 2006.
SEPA (2008) Construction and Demolition Wastes in Scotland (2006)
http://www.sepa.org.uk/waste/waste_data/commercial__industrial_waste/construct
ion__demolition.aspx (and similar reports from 2004 and 2005)
SEPA Waste Data Digests (1997/98 – 2008)
http://www.sepa.org.uk/waste/waste_data/waste_data_digest.aspx
SLR (2007) Determination of the Biodegradability of Mixed Industrial and Commercial
Waste Landfilled in Wales, November 2007, Report to Environment Agency Wales.
SKM (2010) Estimates of Landfill Methane Recovered in NZ 1990 to 2012, Report
for the Ministry for the Environment, June 2009.
Spokas K, Bogner J, Chanton JP, Morcet M, Aran C, Graff C, Moreau-Le Golvan Y and
Hebe I (2005) Methane mass balance at three landfill sites: What is the efficiency of
capture by gas collection systems? Waste Management, Issue 26, pp. 516-525.
Stern J.C., Chanton J., Abichou T., Powelson D., Yuan L., Escoriza S., Bogner J., (2007),
Use of a biologically active cover to reduce landfill methane emissions and enhance
methane oxidation, Waste Management 27, pp. 1248–1258.
Stubenberger G, Scharler R, Zahirovic S and Obenberger I (2008) Experimental
Investigation of Nitrogen Species Release from Different Solid Biomass Fuels as a
Basis for Release Models, Fuel, 87, pp793-806.
Suflita J M, Gerba CP, Ham R K, Palmisano A C, Rathje W L and Robinson J A (1992)
The World‟s Largest Landfill: A Multi-disciplinary Investigation, Environmental Science
and Technology, 29, pp2305-2310.
58
Sullivan (2010) Current MSW Industry Position and State-of-the-Practice on LFG
Collection Efficiency, Methane Oxidation, and Carbon Sequestration in Landfills; SCS
Engineers, Sacramento, USA.
Tchobanoglous G, Hilary T and Vigil S (1993) Integrated Solid Waste Management:
Integrated Principles and Management Issues, McGraw-Hill, New York.
Technical Research Centre of Finland (2001) Greenhouse Gas Emissions and
Removals in Finland, Espoo.
Themelis N.J., Ulloa P.A., (2007) Methane generation in landfills, Renewable Energy
32, 1243–1257.
Thompson S, Sawyer J, Bonam R and Valdivia JE (2009) Building a better methane
generation model: Validation models with methane recovery rates from 35 Canadian
landfills. Waste Management, Issue 29, pp. 2085-2091.
Tong, X, L. H. Smith, and P. L. McCarty (1990) Methane fermentation of selected
lignocellulosic materials. Biomass, 21:239-255.
Urban Mines (2009) Welsh C&I Survey 2007/08, Report to WAG.
Umweltbundesamt, (2010) Submission under the United Nations Framework
Convention on Climate Change and the Kyoto Protocol 2010, Umweltbundesamt,
Dessau. Germany.
US-EPA (2010) Inventory of U.S. greenhouse gas emissions and sinks: 1990 – 2008,
US_EPA, Washington, USA.
Van Soest, P.J. (1994) The Nutritional Ecology of the Ruminant, 2nd edition. Cornell
University Press.
VITO (2001) Procesbeschrijving Afvalverwerkingstechnieken: Integrale Miliestudies.
Vogt G., Augenstein D., (1997) Comparison of models for predicting landfill methane
recovery, SCS Engineers, Report File No. 0295028, Reston, Virginia, USA
Wang Y S, Byrd C S and Barlaz M A (1994) Anaerobic Biodegradability of Cellulose
and Hemi-cellulose in Excavated Refuse Samples, Journal of Industrial Microbiology,
13, pp147-153.
WastesWork and AEA (2010) The Composition of Municipal Solid Waste in Scotland,
Final Report for Zero Waste Scotland, April 2010.
White J, Robinson J and Ren Q (2004) Landfill Process Modelling Workshop:
Modelling the Biochemical Degradation of Solid Waste in Landfills, Waste
Management, 24, pp227-240.
Wiley-Liss Dehority, B. A. and R. R. Johnson. 1961. Effect of particle size upon the in
vitro cellulose; digestibility of forages by rumen bacteria. Journal of Dairy Science, V
(44):2242.
Wu B, Taylor C M, Knappe D R, Nanny M A and Barlaz M A (2001) Factors Controlling
Alkybenzene Sorption to Municipal Solid Waste, Environmental Science and
Technology, 35, pp4569-4576.
59
A.1.0 Chronology of Development of MELMod MELMod is a model which has been developed following on from previous landfill
models. This development is summarised in Table A 1 below. The new model -
MELMod-UK (Methane Emissions from Landfills Model) was developed with the aim
of improving usability and rationalising the previous model, focussing on the
functionality and structure of the model. A report was also prepared identifying areas
where improvements in data quality and methodology were required.
Table A 1: Evolution of the UK National Assessment Model of Methane Emissions
from Landfills
Model
authors Key features Comments
ETSU (1996)
Based on two types of landfills
Biodegradable waste characterised by a single rate
constant
Survey to estimate flare capacity.
Utilisation plant based on renewable energy
statistics.
Emission rates for 1990 estimated at ~1.8
million tonnes methane.
AEA (1999)
Based on four types of landfills characterised by
different levels of gas collection and methane
oxidation
Biodegradable waste allocated to rapidly,
moderately and slowly degrading fractions
Methodology developed to allow for retrofitting of
more efficient gas collection to existing landfill sites
Calibration of the model against field
measurements of emissions at a number of
landfills
Emission rates for 1990 estimated at 1.12
million tonnes (90% confidence range 0.7 to
1.5 million tonnes), compared with site
measurements made by NPL and then scaled
up to produce a UK estimate of 1.04 million
tonnes. The model covered the period 1990 to
2012.
Land Quality
Management
Ltd (LQM)
(2003)
Addition of new scenarios and projections for waste
sent to landfill were added
Revised DOC and DOCF parameter values, and rate
constants, adopted using the approach developed
for site specific methane assessment with the
GasSim model
Implemented a mechanistic model for methane
oxidation, allowing much higher rates of oxidation
Incorporated survey data to estimate methane
recovery from utilisation and flare stack capacity.
A new method of calculating DOC, based on
cellulose and hemicellulose content of the
waste was adopted. The revised model
increased the estimate of methane generation
to almost 3 million tonnes in 1990 (compared
with ~1.8 million tonnes methane generated for
the AEA model).
Implementation of the new approach to
methane oxidation and methane recovery
meant that emissions of methane remained
comparable with NPL and AEA estimates. Time
was extended to 2025.
Golder
Associates
(2005)
The time line of the model was extended from
2025 to 2050, with new waste arisings data
New MSW arisings data based on the LAWRRD
model and new C&I waste arisings data were
incorporated from 2005
The module for calculating methane oxidation
introduced by LQM was discontinued and fixed
rates of recovery were introduced from 2005
onwards.
MELMod-UK
Complete rebuild of the model, retaining IPCC 2000
based methodology.
Scenarios for waste arisings and composition
developed.
Removed legacy code and redundant features;
improved logic flow, usability and traceability.
Developed a system for storing input and
output datasets for scenario analysis. Included
the capability of including a new landfill type for
future analysis. Prepared user guide and
documentation sheet.
Source: AEA (2008) Revision of UK Model for Predicting Methane Emissions from Landfills Task 3
Report – Review of Methodology, Data Quality & Scope for Improvement, Report to Defra, October
2008
The new model retains the same functionality as the previous model in terms of how
emissions are calculated.
60
A.2.0 Waste Quantities and Composition This Appendix is intended to highlight the approach, and data sources, used to
update the data within MELMod.
A.2.1 Municipal Waste
The data in MELMod are shown in Table A 2 and Table A 3. The total quantity
landfilled is shown in graphic form in Figure A 1. The following are surprising features
of the quantitative and compositional data:
a) MELMod suggests a pronounced increase in landfilled MSW in the period from
1995 to 2001. This peak bears no resemblance to the reality (see below). In
the second half of the 1990s, the view that commonly prevailed was that:
1. Municipal waste would grow at a fairly rapid rate; and
2. Recycling achievement would be limited.
It was anticipated, therefore, that quantities of landfill would grow significantly
before alternative treatments, mostly incineration, „came in‟ to plug the landfill
diversion „gap‟ required to meet the Landfill Directive targets. Virtually every
aspect of these projections has been shown to be incorrect:
a. Municipal waste has not grown as rapidly as was anticipated, especially
in the years post 2000 (this is recognised by the AEA review43);
b. Recycling rates have proceeded far more quickly to levels beyond those
which had previously been considered very challenging (this is not
recognised by the AEA review, but it might be expected to have
implications for waste composition since not all materials are recycled
to the same extent); and
c. As a consequence, the „hump‟ in landfill has been much less
pronounced than was anticipated;
b) Some special attention appears to have been given to both „stabilised
residues‟ and to „incinerator ash‟ in recent years (with no similar „special
consideration‟ being given to anything else). The provenance of the figures for
incinerator ash and of stabilised residues is unclear. It seems highly unlikely
that 1.13 million tonnes of stabilised waste would be landfilled in 2010. This
would require the capacity for treatments generating such residues to be of
the order of 2 million tonnes, well in excess of the total current capacity for
such facilities.
c) In terms of composition:
43 AEA (2008) Revision of UK Model for Predicting Methane Emissions from Landfills Task 3 Report –
Review of Methodology, Data Quality & Scope for Improvement, Report to Defra, October 2008
61
i. As a general comment, one would expect considerable change in the
composition of waste landfilled over time given the significant increase
in recycling over the period under examination. In addition, the „official‟
view of MSW composition in England moved fairly swiftly away from the
„1995‟ view following the publication of Parfitt‟s review of the
composition of municipal waste for the Strategy Unit in 2002 (relating,
evidently, to data from earlier years).44 This was broadly consistent with
data from a composition study carried out for the Welsh Assembly
Government, updated work for Defra in England, and more recent
analysis for Scottish Government.45 MELMod, on the other hand,
employs outdated composition data from the early 1990s through to
the present day even though the data in the model has been updated
since the publication of Parfitt‟s work. There are also reasons to doubt
the accuracy of earlier datasets since those developed over the last
decade are showing a degree of consistency across the composition of
key biodegradable fractions in the local authority managed waste
stream (paper, card, food and garden waste). The 1995 dataset, on the
other hand, suggests a very different waste composition to that which
was being suggested only 7 years later;
ii. The categories into which waste is split in MELMod are shown in Table
A 2 and Table A 3 below. It is unclear to us why the model would
assume, as MELMod does, that all landfilled putrescibles are
„composted putrescibles‟ from 1995 onwards;
iii. The categories „paper and card‟ and „putrescible‟ are possibly too blunt.
Even the IPCC‟s own model recommends different parameters for food
waste and for garden waste, and there are probably good reasons for
doing so based on the quite different biochemical constituents of the
different „putrescible‟ materials (see Appendix A.3.0 below);46
44 Julian Parfitt (2002) Analysis of Household Waste Composition and Factors Driving Waste Increases,
Report to the Prime Minister‟s Strategy Unit, November 2002.
http://www.cabinetoffice.gov.uk/media/cabinetoffice/strategy/assets/composition.pdf
45 AEAT (2003) The Composition of Municipal Waste in Wales. National Assembly for Wales
(NAW)/AEAT Technology - December 2003.
46 See IPCC (2006) IPCC Guidelines for National Greenhouse Gas Inventories (2006): Chapter 3 - Solid
Waste Disposal, http://www.ipcc-
nggip.iges.or.jp/public/2006gl/pdf/5_Volume5/V5_3_Ch3_SWDS.pdf
62
Table A 2: Quantitative Data for MSW in MELMod
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Paper and card 5.76 6.04 6.31 6.59 6.87 7.63 7.92 8.36 8.30 8.65 8.73 8.51 8.61 8.37 8.07 7.66 6.87 6.35 5.80 4.91 3.95
Dense plastics 0.93 1.00 1.07 1.15 1.22 2.62 2.72 2.88 2.85 2.97 3.44 3.37 3.41 3.31 3.20 3.03 2.72 2.52 2.30 1.94 1.56
Film plastics
(until 1995) 0.86 0.92 0.98 1.04 1.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Textiles 0.47 0.46 0.46 0.45 0.43 0.48 0.50 0.52 0.52 0.54 0.59 0.58 0.58 0.57 0.55 0.52 0.46 0.43 0.39 0.33 0.27
Misc. combustible
(plus non-inert
fines from 1995)
0.98 1.14 1.31 1.49 1.68 1.91 1.98 2.09 2.08 2.16 2.51 2.45 2.48 2.41 2.32 2.20 1.98 1.83 1.67 1.41 1.14
Misc. non-
combustible
(plus inert fines
from 1995)
0.43 0.42 0.41 0.39 0.37 2.14 2.23 2.35 2.33 2.43 2.34 2.28 2.31 2.24 2.16 2.05 1.84 1.70 1.55 1.32 1.06
Putrescible 4.02 4.07 4.12 4.15 4.18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Composted
Putrescibles 0.00 0.00 0.00 0.00 0.00 5.00 5.20 5.49 5.45 5.68 5.62 5.48 5.54 5.39 5.20 4.93 4.42 4.09 3.73 3.16 2.54
Glass 1.72 1.78 1.83 1.88 1.93 2.14 2.23 2.35 2.33 2.43 2.25 2.19 2.22 2.16 2.08 1.97 1.77 1.64 1.50 1.26 1.02
Ferrous metal 1.18 1.18 1.19 1.18 1.18 1.43 1.49 1.57 1.56 1.62 1.48 1.44 1.46 1.42 1.37 1.30 1.16 1.08 0.98 0.83 0.67
Non-ferrous metal
and Al cans 0.19 0.23 0.26 0.29 0.33 0.48 0.50 0.52 0.52 0.54 0.58 0.57 0.57 0.56 0.54 0.51 0.46 0.42 0.39 0.33 0.26
Non-inert fines 1.45 1.45 1.43 1.41 1.38 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Inert fines 0.19 0.15 0.11 0.07 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Incinerator Ash 0.18 0.18 0.18 0.23 0.27 0.15 0.16 0.16 0.16 0.57
Stabilised
Residues 0.03 0.03 0.03 0.03 0.09 0.09 0.16 0.31 0.44 1.13
TOTAL 18.19 18.84 19.47 20.09 20.71 23.83 24.76 26.14 25.94 27.03 27.54 27.08 27.39 26.62 25.74 24.55 21.93 20.37 18.79 16.10 14.17
63
Table A 3: Composition Data for MSW in MELMod
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Paper and card 32% 32% 32% 33% 33% 32% 32% 32% 32% 32% 32% 31% 31% 31% 31% 31% 31% 31% 31% 30% 28%
Dense plastics 5% 5% 5% 6% 6% 11% 11% 11% 11% 11% 12% 12% 12% 12% 12% 12% 12% 12% 12% 12% 11%
Film plastics (until
1995) 5% 5% 5% 5% 5% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Textiles 3% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2%
Misc. combustible
(plus non-inert fines
from 1995) 5% 6% 7% 7% 8% 8% 8% 8% 8% 8% 9% 9% 9% 9% 9% 9% 9% 9% 9% 9% 8%
Misc. non-
combustible
(plus inert fines from
1995) 2% 2% 2% 2% 2% 9% 9% 9% 9% 9% 8% 8% 8% 8% 8% 8% 8% 8% 8% 8% 8%
Putrescible 22% 22% 21% 21% 20% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Composted
Putrescibles 0% 0% 0% 0% 0% 21% 21% 21% 21% 21% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 18%
Glass 9% 9% 9% 9% 9% 9% 9% 9% 9% 9% 8% 8% 8% 8% 8% 8% 8% 8% 8% 8% 7%
Ferrous metal 6% 6% 6% 6% 6% 6% 6% 6% 6% 6% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5%
Non-ferrous metal
and Al cans 1% 1% 1% 1% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2%
Non-inert fines 8% 8% 7% 7% 7% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Inert fines 1% 1% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Incinerator Ash 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 1% 1% 1% 1% 1% 1% 1% 1% 1% 4%
Stabilised Residues 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 1% 2% 3% 8%
64
Figure A 1: Change in Quantity Landfilled
0
5
10
15
20
25
30
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
MSW
/ L
oca
l A
uth
ori
ty C
olle
cte
d W
aste
Lan
dfi
lled
in
th
e U
K (
mill
ion
to
nn
es)
Year
TOTAL MSW Landfilled
iv. The category „Paper and card‟ includes materials with widely varying
biochemical constituents, and thus are recycled (and hence landfilled)
to quite different degrees. Because more up-to-date composition data
exists regarding quantities of waste generated, and quantities recycled,
then in principle, it becomes possible to make use of a more detailed
list of categories.
v. The IPCC model also includes relevant parameters for wood. Wood
does not appear at all in the list of municipal waste materials in
MELMod (other than, presumably, as part of „miscellaneous
combustible‟ material);
vi. Lumping categories into „miscellaneous combustible‟ or „miscellaneous
non-combustible‟ is not especially helpful, and as far as possible, we
take the view that such general categories should be avoided insofar as
they refer to groups of materials which contribute to landfill gas
generation. Included in this category are materials such as nappies,
which the IPCC lists as a separate category (and whose degradation
65
characteristics are deemed very different from those of „wood and
straw‟); and
vii. Stabilised residues (if this refers to biologically stabilised residues) are
not 100% inert, as is assumed in MELMod.47
Taking these matters into account, the MELMod estimate of GHGs from
landfilling of municipal waste is derived, therefore, from modelling of the 6
emboldened categories in Table A 4 below. In practice, the modelling relates
only to 4 categories since „Non-inert fines‟ have been added in to
„miscellaneous combustibles‟ over recent years, and there are no landfilled
„Putrescible‟ materials, only landfilled „Composted putrescibles‟.
Table A 4: Material Categorisation Used in MELMod for Municipal Waste
Municipal Waste Categories
Paper and card Glass
Dense plastics Ferrous metal
Film plastics (until 1995) Non-ferrous metal and Al cans
Textiles Non-inert fines
Misc. combustible (plus non-inert fines from
1995) Inert fines
Misc. non-combustible (plus inert fines from
1995) Incinerator Ash
Putrescible Stabilised Residues
Composted Putrescibles
Of these 4 remaining categories:
i. the way in which activity data is being reported to „composted
putrescibles‟ is incorrect. There are some composted putrescibles
which are landfilled. To the extent that these warrant a separate
category, they ought to be reported under commercial and industrial
waste rather than under municipal / local authority managed waste;
ii. the modelling of paper and card as one category is more blunt than
might be desirable (as it ignores the widely varying lignin content of
different components of the paper and card stream – see Section A.3.2
for further discussion); and
iii. the modelling of the category „miscellaneous combustibles‟ makes it
difficult to understand what is really being modelled (and what the
47 This is especially true in the UK where there is no minimum level of pre-treatment for biologically
stabilised wastes. Instead, the landfill allowance schemes (LASs) allow wastes to be landfilled with
varying potentials to generate methane (though with some variation in policy across England and the
devolved administrations).
66
justification is for the choice of parameters). It also makes it impossible
to understand what the effect might be of removing a sub-category of
„miscellaneous combustibles‟, such as wood, from landfill. The removal
of any „miscellaneous combustible‟ from landfill has the same impact,
whether it is wood, nappies, the food fraction of non-inert fines, or
synthetic rubber.
A.2.2 Commercial, Industrial and C&D Waste
The quality of UK data on commercial waste is rather poor, though attempts are being
made to improve this. In England, which accounts for the majority of C&I waste, only
two significant surveys have been carried out, both on behalf of the Environment
Agency (in 1997 and 2002/3). A further survey is ongoing at the time of writing.
There have been some attempts to understand the nature and quantity of
commercial and industrial waste more recently.48 However, these have not managed
to give a clear picture of the quantity, composition, and management of the
commercial and industrial waste streams.
This poses a challenge to the launch of a review.
Even so, some points do emerge:
a) In every year since 2002, the quantities of general commercial, general
industrial, and C&D waste landfilled have remained constant in MELMod. This
is likely to be correct only by coincidence, as all indications (for example,
landfill tax returns) suggest that something very different is happening to what
the data in MELMod suggests;
b) MELMod data indicates that since 1990, the quantities of general commercial
and general industrial waste landfilled have grown at an identical rate (they
remain in fixed proportions). This seems unlikely given the likely ongoing shift
in total C&I arisings from industrial to commercial over the period, reflecting
the change in the structure of economic activity in the UK.
This highlights the need for some analysis of that data which is available to impart
some rationale to the way in which the figures change over time.
The breakdown of the non-municipal wastes by category leaves, as in the case of
municipal waste, much to be desired (see Table A 5). Consistently, the largest fraction
being landfilled in recent years in MELMod (apart from C&D waste, which MELMod
treats as largely inert – see Table A 15 below) has been „Commercial Waste‟ (see
Table A 6), which represents, presumably, a mixed commercial waste fraction.
The problem with this is that it allows for no change in the characteristics of this large
fraction as progressively more material is recycled from the commercial stream (as
48 ADAS (2009) National Study into Commercial and Industrial Waste Arisings, Final report for EERA;
Urban Mines (2009) Welsh C&I Survey 2007/08, Report to WAG; SEPA (2007) Scotland Business
Waste Survey 2006; MEL and EnviroCentre (2002) Industrial and Commercial Waste Production in
Northern Ireland, Final Report to the Northern Ireland Environment and Heritage Service.
67
seems likely in the wake of rising landfill tax). In other words, removing biodegradable
elements for recycling / composting / digestion would not change how this (large)
mass of material behaves in the model as its composition changes (because the
model does not allow its changing composition to be reflected in its behaviour). It
should be noted that the composition of this waste stream in the total non-municipal
stream remains constant post 2001 (see Table A 7).
It would be desirable to split the commercial waste fraction into component parts as
far as possible, not least since the aim should be to understand how residual
commercial / industrial waste is changing over time, and how initiatives which
improve recycling of specific components of the commercial stream could contribute
to reducing GHG emissions. Having said this, the poor quality of the available data
presents significant obstacles, as we shall see.
Table A 5: Material Categorisation Used in MELMod for Non-municipal Wastes
Non-Municipal Waste Categories
Paper and card Blast furnace and steel slag
General industrial waste Construction/demolition
Food solids Sewage sludge
Food effluent Textiles
Abattoir waste Wood
Misc processes Industrial Putrescibles
Other waste Metals
Power station ash
The same applies to three other major categories, „General Industrial Waste‟,
„Miscellaneous Processes‟ and „Other Waste‟. Along with „Commercial waste‟, these 4
broad categories accounted for more than 30.6 million tonnes of the 38.9 million
tonnes of C&I waste (i.e. excluding construction and demolition wastes) assumed to
be landfilled in 2007 within MELMod (see Table A 6). The categorisation of these
materials, in terms of how they might behave in a landfill, cannot be estimated in any
meaningful way, so as long as the model is set up so that most landfilled waste
reports to these categories, it will not produce accurate results. That having been
said, as long as better data on commercial and industrial waste is not forthcoming –
see below - it remains largely beyond criticism. What one can say is that the modelled
figures are highly unlikely to be correct.
68
Table A 6: Quantitative Data for Commercial, Industrial and Construction and Demolition Wastes in MELMod
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Commercial 14.11 14.23 14.34 14.46 14.58 14.70 14.62 14.35 15.68 15.64 15.60 15.55 15.51 15.51 15.51 15.51 15.51 15.51 15.51 15.51 15.51
Paper and card 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.07 0.19 0.22 0.26 0.30 0.34 0.34 0.34 0.34 0.34 0.34 0.34 0.34 0.34
General industrial waste 8.87 8.89 8.92 8.95 8.97 9.00 9.09 9.17 10.43 10.55 10.66 10.78 10.89 10.89 10.89 10.89 10.89 10.89 10.89 10.89 10.89
Food solids 2.35 2.36 2.37 2.38 2.39 2.40 1.53 0.85 0.41 0.33 0.24 0.16 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08
Food effluent 13.87 13.95 14.02 14.10 14.17 14.25 9.12 5.12 2.55 2.07 1.58 1.10 0.62 0.62 0.62 0.62 0.62 0.62 0.62 0.62 0.62
Abattoir waste 1.40 1.40 1.40 1.40 1.40 1.40 0.92 0.54 0.28 0.23 0.18 0.13 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08
Misc processes 15.07 15.11 15.16 15.21 15.25 15.30 10.75 7.00 4.57 3.99 3.40 2.81 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23
Other waste 1.68 1.69 1.69 1.69 1.70 1.70 3.09 3.83 4.43 4.31 4.19 4.08 3.96 3.96 3.96 3.96 3.96 3.96 3.96 3.96 3.96
Power station ash 6.40 6.42 6.44 6.46 6.48 6.50 5.52 4.56 4.07 3.83 3.59 3.36 3.12 3.12 3.12 3.12 3.12 3.12 3.12 3.12 3.12
Blast furnace and steel
slag 1.77 1.78 1.78 1.79 1.79 1.80 1.82 1.80 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99
Construction/demolition 16.20 15.84 15.48 15.12 14.76 14.40 21.59 25.44 29.27 28.71 28.15 27.59 27.03 27.03 27.03 27.03 27.03 27.03 27.03 27.03 27.03
Sewage sludge 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.12 0.12 0.12 0.12 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11
Textiles
Wood
Industrial Putrescibles
Metals
Total 81.83 81.77 81.72 81.66 81.61 81.56 78.17 72.86 74.01 71.99 69.98 67.96 65.94 65.94 65.94 65.94 65.94 65.94 65.94 65.94 65.94
69
Table A 7: Composition Data for Commercial, Industrial and Construction and Demolition Wastes in MELMod
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Commercial 17.2% 17.4% 17.6% 17.7% 17.9% 18.0% 18.7% 19.7% 21.2% 21.7% 22.3% 22.9% 23.5% 23.5% 23.5% 23.5% 23.5% 23.5% 23.5% 23.5% 15.51
Paper and card 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.1% 0.3% 0.3% 0.4% 0.4% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.34
General industrial waste 10.8% 10.9% 10.9% 11.0% 11.0% 11.0% 11.6% 12.6% 14.1% 14.6% 15.2% 15.9% 16.5% 16.5% 16.5% 16.5% 16.5% 16.5% 16.5% 16.5% 10.89
Food solids 2.9% 2.9% 2.9% 2.9% 2.9% 2.9% 2.0% 1.2% 0.6% 0.5% 0.3% 0.2% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.08
Food effluent 17.0% 17.1% 17.2% 17.3% 17.4% 17.5% 11.7% 7.0% 3.4% 2.9% 2.3% 1.6% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.62
Abattoir waste 1.7% 1.7% 1.7% 1.7% 1.7% 1.7% 1.2% 0.7% 0.4% 0.3% 0.3% 0.2% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.08
Misc processes 18.4% 18.5% 18.6% 18.6% 18.7% 18.8% 13.8% 9.6% 6.2% 5.5% 4.9% 4.1% 3.4% 3.4% 3.4% 3.4% 3.4% 3.4% 3.4% 3.4% 2.23
Other waste 2.1% 2.1% 2.1% 2.1% 2.1% 2.1% 4.0% 5.3% 6.0% 6.0% 6.0% 6.0% 6.0% 6.0% 6.0% 6.0% 6.0% 6.0% 6.0% 6.0% 3.96
Power station ash 7.8% 7.9% 7.9% 7.9% 7.9% 8.0% 7.1% 6.3% 5.5% 5.3% 5.1% 4.9% 4.7% 4.7% 4.7% 4.7% 4.7% 4.7% 4.7% 4.7% 3.12
Blast furnace and steel slag 2.2% 2.2% 2.2% 2.2% 2.2% 2.2% 2.3% 2.5% 2.7% 2.8% 2.8% 2.9% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 1.99
Construction/demolition 19.8% 19.4% 18.9% 18.5% 18.1% 17.7% 27.6% 34.9% 39.6% 39.9% 40.2% 40.6% 41.0% 41.0% 41.0% 41.0% 41.0% 41.0% 41.0% 41.0% 27.03
Sewage sludge 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.11
Textiles
Wood
Industrial Putrescibles
Metals
Total 81.83 81.77 81.72 81.66 81.61 81.56 78.17 72.86 74.01 71.99 69.98 67.96 65.94 65.94 65.94 65.94 65.94 65.94 65.94 65.94 65.94
70
This coincidence is (happily, given the direction of travel in terms of landfilled waste)
not one which has arisen, at least in terms of overall quantities landfilled. We note, in
passing, that in every year since 2002, MELMod has assumed that 38.9 million
tonnes of C&I waste (i.e. excluding the construction and demolition waste element)
was being landfilled. Landfill tax returns show that the total of all active wastes
landfilled (i.e. including all municipal waste landfilled) has been below this figure in all
years since 2007/8. This alone suggests that, given that much of this is likely to be
subject to higher rate tax, MELMod figures probably overstate the quantity of C&I
waste landfilled, perhaps significantly. This is not surprising, perhaps, given that the
last time projections were made, the known future levels of landfill tax were well
below those which have subsequently been announced.
A.2.3 Construction and Demolition Wastes
The figures for landfilled C&D wastes are also shown in Table A 6.
As sorting of the inert fraction from the active fraction has proceeded (in response to
the landfill tax and other initiatives, such as, in England, the mandating of Site Waste
Management Plans for projects in excess of £300,000 by value), the remaining
fraction of C&D waste looks less „inert‟ than was previously the case. Indeed, it
contains, typically, wood, paper and card, and other biodegradable fractions
(sometimes other forms of vegetation).
MELMod does not treat this material as wholly inert (it treats it as 90% inert, though
because of the way in which the dry matter influences the quantity of degradable
carbon, the material is effectively modelled as containing roughly the same amount of
degradable carbon – tonne for tonne – as municipal food waste). It would be
desirable, clearly, to understand how the make-up of residual C&D waste is changing
over time (it does not change at all in MELMod).49
The quantitative data is clearly incorrect and needs updating. The task of
disentangling the composition of C&D waste is clearly challenging.
A.2.4 Our Approach
In order to understand the quantity and composition of waste landfilled, one is
seeking to understand the composition of the waste which:
1. Remains after recycling and composting / anaerobic digestion and reuse;
2. Are residues from treatment / sorting processes;
3. But are not being sent to other means of residual waste management
(incineration, MBT etc.).
49 At the other end of the spectrum, the SEPA Waste Data Digest 10 suggests that mixed C&D waste
landfilled is 60% biodegradable.
71
In the case of local authority collected (LAC) waste, in the ideal case, this composition
calculation would be estimated, for local authority collected waste, at the level of
each local authority since:
1. Each local authority‟s waste composition will be specific to the authority;
2. Its recycling performance will be specific to the authority;
3. Its residual waste composition will, therefore, be specific to the authority; and
4. The destination of each local authority‟s residual waste may or may not be
landfill (and where some or all of it is, it might be that specific fractions – e.g.
residual HWRC waste – are landfilled).
The basis for resorting to this ideal case simply does not exist at present (though with
some care, it might well do so in future – the task is certainly far from impossible).
Similarly, for businesses, the analysis would ideally happen at the level of the
enterprise and would then be grossed up. This is clearly unrealistic, and as we shall
see below, the quality of the currently available data is a very long way indeed from
being able to make even second best (for example, sectoral) approaches possible.
Time series data for arisings, composition and the fate (in terms of treatment /
disposal) of commercial and industrial waste is of extremely poor quality.
A word of caution is also required at this stage. Implicit within MELMod, and its
predecessor, the national assessment model, is that the emissions of methane from
landfill are closely linked to the composition of the waste being landfilled. The same is
implied in other multi-phase models, such as that proposed by the IPCC. There is a
discussion to be had regarding the relative influence of the nature of the landfill, the
nature of the overall mix of material landfilled, and the nature of individual materials
being landfilled in terms of overall emissions.
Our point of departure has been to maintain a model which gives outputs which are
sensitive to waste composition, and which can, as a result, indicate the likely effect of
policies which may target one or more specific materials in the waste stream. As
such, the underlying assumption is that the aim is to improve the accuracy, and the
resolution, of the data already within a model which is seeking to be sensitive to
waste composition.
The approach we have taken is described below.
A.2.4.1 Local Authority Collected Waste
We have concentrated on improving the historic data in MELMod through the
empirical data which exists in Departmental reports and strategies. We have done
this with a view to making improvements in the model more generally. We have taken
the view that in the absence of a „bottom up‟ local authority-specific approach, we
should use a more top down approach. The basic approach is to:
Obtain the most applicable data on the quantity of waste which was generated in the
year in question;
1. Use the most applicable (in the year in question) composition breakdown for
all MSW;;
72
2. Gather data on the quantity and composition of waste which was recycled in
the year (this is not entirely straightforward as some datasets refer only to
waste collected for recycling whilst others refer to waste recycled);
3. Obtain, as a result, a composition of the residual waste;
4. Apply this composition to the tonnage of waste which is landfilled according to
the best available data on MSW.
As far as possible, we have sought to make this approach „country specific‟. We stress
again that we have based this on existing published sources. There are reasons why
one might question the accuracy of some of these (the more so, the further back we
go). We comment on some of these issues in passing but do not offer a complete
critical review of all datasets.
England
For England, the following sources have been used:
1. For quantities generated, Defra statistics (working back in time through
successive tables);50
2. For composition of total MSW, we have used:
a. For 1995, the data in Waste Strategy 2000, which was also the
composition used to report to EUROSTAT the proportion of MSW which
was thought to be biodegradable (it should be noted here that other
DAs chose to base their LAS system accounting on different proportions
from that used in England);
b. For 2000/01, the work of Parfitt undertaken for the Strategy Unit;51
c. For 2006/7 onward, the update of that work by Resource Futures (also
Julian Parfitt‟s work).52
3. The current situation in MELMod is shown in Figure A 2. For the quantities
recycled, the data for the 3 most recent years come from Waste DataFlow.53
For earlier years, the data comes from statistics reported by Defra. The data
are in a more „aggregated‟ form in these earlier years, and we have made
certain assumptions regarding how some categories are split (for example, the
50 In some cases, for older data, it has been necessary to use the Defra reports, and these frequently
report data which is not statistically robust. Some assumptions have been made to fill in these gaps
where necessary.
51 Julian Parfitt (2002) Analysis of Household Waste Composition and Factors Driving Waste Increases,
Report to the Prime Minister‟s Strategy Unit, November 2002.
http://www.cabinetoffice.gov.uk/media/cabinetoffice/strategy/assets/composition.pdf
52 Resource Futures (2010) Municipal Waste Composition: Review of Municipal Waste Component
Analyses, Report to Defra, WR0119,
http://randd.defra.gov.uk/Document.aspx?Document=WR0119_8662_FRP.pdf
53 We are grateful to Isabella Hayes from Defra‟s Waste Statistics branch for her assistance in this
respect.
73
split between paper and card, or the split of „compost‟ between food, garden,
paper and card). These splits have been made based upon a combination of
recent data (i.e. the more recent studies of composition or the more recent
figures from Waste Dataflow) and/or knowledge regarding what systems were
operating in previous years (for example, we know that very little food waste
was being collected from households for composting in the years prior to
2003);
4. This data is used to estimate the composition of residual waste in England.
The quantities of different materials sent to landfill are then based upon this
composition, multiplied by the quantity of waste sent to landfill. This latter
figure comes from Defra statistics.
Figure A 2: Changes in Waste Composition Over Time in MELMod (note the x-axis is
not scaled to the time intervals - this graphic shows the movements over time in key
fractions)
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
1970 1973 1976 1980 1982 1990
Inert fines
Non-ferrous metal and Al cans
Misc. non-combustible (plus inert fines from 1995)
Misc. combustible (plus non-inert fines from 1995)
Textiles
Film plastics (until 1995)
Dense plastics
Ferrous metal
Non-inert fines
Glass
Putrescible
Paper and card
Scotland
For Scotland, the following sources have been used:
74
1. Arisings data has been taken from the SEPA Waste Data Digests;54
2. For composition of total MSW, we have used:
a. Prior to 2006/7, we have used data from the 2002/3 Data Digest. This
data actually applies only to household waste;55
b. After 2006/7, we have used more recent composition data for MSW
from a separate study;56
3. For recycling, by material, we have again drawn on the successive Waste Data
Digests. Note that we have not considered the recycling of materials from
incineration and MBT as the approach here is to understand the composition
of residual waste as sent to all treatment / disposal processes through
subtracting the materials recycled before residual waste treatment / disposal
from the total quantity of material;
This has enabled us to estimate the residual waste composition, and using the Waste
Data Digest estimates of what is landfilled, to estimate the quantity and composition
of landfilled material.
Wales
For Wales, figures from 1996/7 to 2006/7 have been supplied by the Welsh
Assembly Government.57 The methodology used in the figures provided by WAG is
essentially the same as we have used for England. It makes use of the composition
data derived from a study undertaken by AEA for WAG (using this for years back to
1996/7).58 The composition data used for most recent years is an adapted form of
this, and reflects the findings of work undertaken by Eunomia for WAG (in which it
was found that if the AEA composition was used, the capture of specific materials for
recycling was calculated to be in excess of 100%. As a consequence, we adapted the
data to ensure that captures greater than 100% could not be realised).59 The most
recent years have made use of more recent statistics from StatsWales.60
Northern Ireland
For Northern Ireland, the following sources have been used:
54 See Waste Data Digest, http://www.sepa.org.uk/waste/waste_data/waste_data_digest.aspx
55 SEPA (2004) Waste Data Digest 4 (2002 and 2002/3 Data),
http://www.sepa.org.uk/waste/waste_data/waste_data_digest.aspx
56 WastesWork and AEA (2010) The Composition of Municipal Solid Waste in Scotland, Final Report for
Zero Waste Scotland, April 2010.
57 We are grateful to Rhiannon Jones of WAG for supplying this data.
58 AEAT (2003) The Composition of Municipal Waste in Wales. National Assembly for Wales
(NAW)/AEAT Technology - December 2003.
59 See Eunomia (2008) Scoping New Municipal Waste Targets for Wales, Report for the Welsh Local
Government Association and the Welsh Assembly Government.
60 Seethe statswales website at
http://www.statswales.wales.gov.uk/ReportFolders/reportFolders.aspx
75
1. Arisings data for Northern Ireland has been taken from the Municipal Data
Reporting of the Northern Ireland Environment Agency (NIEA).61 For earlier
years, data is scarce. We have estimated mass flows for 1995/96 to 1997/98
using „snippets‟ from the Northern Ireland Waste Strategy;62
2. For composition of total MSW, we have used:
a. Prior to 2006/7, we have used data for household waste from a 2001
study;63
b. After 2006/7, we have used more recent composition data for MSW
from a separate study;64
3. For recycling, by material, we have again drawn on the successive reports from
the Northern Ireland Environment Agency;
This has enabled us to estimate the residual waste composition, and using the NIEA
data regarding what has been landfilled, to estimate both the quantity and
composition of landfilled material.
United Kingdom
Data regarding he total quantity of MSW landfilled are taken from the constituent
countries. As can be seen below (in Figure A 3) the waste quantities into MELMod
appear to have been too low in the early years in the period which we have reviewed,
but too high in years after 2002/3. One possible reason for this is that it was
surprisingly common, in our experience, for analysts to assume that English data (or
England and Wales data) was representative of the UK. Evidently, the more recent
divergences relate to the fact that no one has updated projections initially made back
in the late 1990s.
On composition, the data has presented several challenges. As discussed above for
England, nationally representative composition datasets tend to be produced on an
occasional basis. The material classifications used vary across the countries, and for
any one country, between analyses. As a result, one has to consider the appropriate
classification of materials to use, with a view to the landfill modelling. This also has to
take into account that the way in which materials are categorised in terms of what
has been recycled / composted / digested also varies over time.
This led us to develop a „reduced form‟ for „waste arising‟, „recycled / reused
materials‟ and residual waste. The materials used in this reduced form are shown in
Table A 8. In this classification, everything non-biodegradable falls into the category
„other‟. This includes categories of material currently listed in MELMod, such as
Dense Plastics, Film Plastics, Miscellaneous Non-combustibles, Inert Fines, Glass,
61 See http://www.ni-environment.gov.uk/waste-home/municipal_data_reporting.htm
62 We are grateful to Adrian Fitzpatrick for supplying historic data in electronic form and for guiding us
through the available data, as well as that which is not available.
63 Northern Ireland Household Waste Characterisation Study NI 2000, 2001 (Table 3.1).
64 RPS (2008) Review of Municipal Waste Component Analysis (Northern Ireland), 2008
76
Ferrous metal, Non-ferrous metal and aluminium cans. There seems to be no point at
all in retaining these multiple categories in MELMod when they have no bearing on
methane emissions (hence, the rationale for the encompassing nature of our „Other‟
category).
For England in particular, the treatment of composition data highlighted a key issue:
i. Whether one accepts the 1995 data as being an accurate representation of
waste composition at the time; and
ii. If one does, how should one „engineer‟ the transition from one composition
dataset to another over the period assessed.
One solution considered was to ignore the 1995 dataset altogether and extrapolate
backwards using the more recent composition figures. However, the approach
requested by Defra has been to smooth the transition from one set of composition
estimates to the other over the periods between revisions of the composition data.
This was achieved through linear interpolation between these years of the quantity of
the material landfilled, though normalised back to ensure total landfill quantities
remained as intended in the „raw‟ calculations. This avoids discontinuities in the
quantity of a given waste landfilled from one year to the next owing to sudden
changes in waste composition (which would otherwise result from the use of different
datasets). The „unsmoothed‟ and „smoothed‟ datasets are shown in Note that
furniture and mattresses are treated as composite materials. On a fresh matter
basis, furniture in MSW is assumed to be 62% wood and 5% textiles; mattresses are
considered to be 50% textiles (clearly these are only the biodegradable components).
Figure A 4 and Figure A 5 below.
77
Figure A 3: Comparison between MELMod and Proposed Revision
0
5000000
10000000
15000000
20000000
25000000
30000000
Ton
ne
s M
SW L
and
fille
d
MELMod
Proposed revision
Table A 8: Proposed Material Classifications for Establishing Composition of
Landfilled Waste
Proposed Material Classification
Paper Soil and other organic waste
Card Wood
Textiles (and footwear) Sanitary / disposable nappies
Miscellaneous combustibles Furniture
Food Mattresses
Garden Other
Note that furniture and mattresses are treated as composite materials. On a fresh
matter basis, furniture in MSW is assumed to be 62% wood and 5% textiles;
mattresses are considered to be 50% textiles (clearly these are only the
biodegradable components).
78
Figure A 4: Evolution of Landfilled Local Authority Managed Waste by Waste Type,
Composition „Unsmoothed‟ („000 tonnes)
0
5,000
10,000
15,000
20,000
25,000
Other
Mattresses
Furniture
Sanitary / disposable nappies
Wood
Soil and other organic waste
Garden
Food
Miscellaneous combustibles
Textiles (and footwear)
Card
Paper
Figure A 5: Evolution of Landfilled Local Authority Managed Waste by Waste Type,
Composition „Smoothed‟ Between 1995-2001 („000 tonnes)
0
5,000
10,000
15,000
20,000
25,000
Other
Mattresses
Furniture
Sanitary / disposable nappies
Wood
Soil and other organic waste
Garden
Food
Miscellaneous combustibles
Textiles (and footwear)
Card
Paper
79
In our proposal, we stated our intent
to broaden the categorisation of materials to the extent that:
1. The quality of composition data allows; and
2. The expansion of the list of materials is meaningful.
We went on to say:
In practice, this is likely to lead to:
a) A splitting of „Putrescibles‟ to give separate figures for Garden waste and
Food waste. Collection systems work to target these in different ways, and
the biochemical characteristics of the materials are very different (see
below);
b) Expanding the category „Paper and Card‟ which is too blunt at present. It
fails to recognise the different biochemical composition of the different
paper and card fractions. In particular, newsprint, which is relatively high
in lignin content (and therefore, generally more recalcitrant to degradation
in landfills) is already targeted for collection by recycling operations
because of the quantity available and the value of the material. The
suggestion is that the relative rates of capture of different paper and card
streams will affect the degradability of that fraction of the „Paper and card‟
stream which still finds its way to landfill
c) Inclusion of „wood‟ as a separate category (this does not appear as a
separate category at present, and the relevance to policy of generating
renewable energy from woody wastes suggests a specific focus is
warranted). One problem with „wood‟ is that some wood is also found in
the category recorded as „furniture‟ in most waste analyses. We propose to
make an estimate of the proportion of furniture which is wood, and to set
this as a variable in the model;
d) Inclusion of „nappies‟ as a separate category (this does not appear as a
separate category at present but composition data allows for this to be
done); and
e) Splitting out textiles into non-biodegradable and biodegradable textiles so
as to allow for an estimate of the change which may occur as shifts in
consumption patterns take place;
We would remain indifferent to the aggregation of, for example, plastics as one
group of materials, or glass, etc. because these do not give rise to relevant
emissions. There may be some merit, however, in assessing the picture in respect
of „biodegradable‟ plastics with an eye to the future.
We note also that figures are in place for „Composted putrescibles‟. We believe
this is a relevant category but should be re-labelled „stabilised biowastes‟. One
problem here is that the UK has no defined standard for „stability‟ so that in
future, wastes with varying levels of stability will be consigned to landfill. We
80
propose to investigate the potential for sub-categories of such waste,
representing varying levels of pre-treatment of the waste.
With these categories in place, we would seek to review the available evidence in
respect of waste arisings and waste composition to review data over the past
fifteen years. Eunomia has carried out a number of policy projects over the past
decade where this type of analysis has been necessary. We propose to draw upon
these reports, which are in the public domain, as the basis for such estimates.
We have managed to do this for the MSW stream. We have also kept „furniture‟ as a
separate category. Furniture has been assigned a composition of 5% textiles and 62%
wood. Textiles are reported a „textiles and footwear‟ since this is the category
reported by the main composition analyses.
81
Table A 9: Revised Figures for Landfilled Local Authority Managed Waste (Municipal Waste) for the UK (tonnes)
1995/96 1996/1997 1997/1998 1998/1999 1999/2000 2000/2001 2001/2002 2002/2003 2003/2004 2004/2005 2005/2006 2006/2007
Paper 5,988,937 5,325,247 5,075,239 4,511,984 4,159,711 3,655,984 3,769,188 3,760,145 3,633,752 3,546,697 3,245,393 3,046,934
Card 1,921,165 1,703,795 1,616,612 1,432,222 1,316,817 1,151,434 1,255,161 1,315,672 1,322,296 1,353,753 1,301,879 1,282,904
Textiles (and footwear) 594,250 624,561 699,106 737,030 811,593 855,630 886,243 873,827 868,558 852,475 792,825 786,586
Miscellaneous combustibles 330,231 328,500 348,890 352,565 380,331 384,712 464,653 544,342 582,804 646,098 664,723 848,899
Food 5,424,359 5,290,261 5,555,858 5,509,110 5,709,859 5,726,952 6,006,865 6,117,595 5,968,800 6,006,076 5,708,885 5,548,669
Garden 1,870,139 2,467,310 3,229,041 3,834,326 4,589,298 5,231,592 4,922,068 4,398,287 3,782,905 3,053,382 2,250,167 1,475,826
Soil and other organic waste - 163,722 343,728 505,770 684,070 852,760 834,274 785,631 708,675 633,060 533,329 464,987
Wood 988,282 983,604 1,055,427 1,066,339 1,125,196 1,148,878 1,117,572 1,047,798 924,108 793,964 652,900 529,849
Sanitary / disposable nappies 542,623 531,273 559,242 558,828 572,784 578,192 634,909 684,319 701,576 726,589 718,992 740,337
Furniture 356,194 353,423 375,834 377,958 399,551 405,558 424,959 433,783 429,547 426,897 406,137 406,683
Mattresses - - - - - - 10,738 22,030 32,731 43,225 51,074 60,862
Other 8,443,883 7,979,258 8,123,726 7,785,868 7,807,565 7,582,865 7,738,168 7,641,918 7,287,850 6,968,141 6,336,048 6,141,309
TOTAL 26,460,062 25,750,955 26,982,702 26,672,000 27,556,774 27,574,555 28,064,798 27,625,347 26,243,602 25,050,357 22,662,352 21,333,845
Note: It is appreciated that the figures suggest an unjustified level of accuracy – we merely show the figures in their entirety as
calculated for completeness.
82
In future, it would be desirable to have a better split – both in terms of total arisings
and in terms of recycled materials – of both paper and card. This is because the sub-
categories have such differing biochemical constituents. The collection of data for
recycling, and the way in which composition data is reported, do not always allow a
ready match between the two.
We believe it would make sense in future for MELMod to have a „frontsheet‟ which
models the management of waste materials over time so that the landfilled quantities
„fall out‟ of this sheet.
A.2.4.2 Non-MSW
In embarking on an attempt to improve the data for non-MSW, it was known, at the
outset, that the quality of data would leave a great deal to be desired. It might
reasonably be asked why, given this simple fact, it was felt necessary to seek to
improve this data. There are two reasons for this:
1. The data within MELMod had not been updated to reflect the data that was
being made available over time;
2. The coarse breakdown of C&I and C&D waste within MELMod gave no insight
into what it was assumed was being landfilled from these waste streams. If for
no other reason, then with a view to having improved data in future to input
into the model (in respect of the composition of landfilled waste), the model
could be improved. We sought – on the basis of what little data is available
regarding the composition of C&I and C&D waste in the UK – to break out the
„mixed‟ categories into the key constituent biodegradable materials.
As will become clear, the data regarding both quantities and composition is far from
perfect, but we believe it represents an improvement on the existing data in MELMod,
if only for the reason that it does seek to make the best use of what little data there is
available of this nature.
For the UK as a whole, the information from HMRC on landfill tax receipts probably
provides one of the most reliable sets of data regarding the quantity of material that
has been landfilled. The merit of this data is that it provides a (broadly) consistent
time-series which can be used to generate a time series for quantities of non-MSW
sent to landfill.
It is clear, however, that this data also has its drawbacks. During the course of this
part of our work, the biggest challenge was posed by the inconsistencies across
datasets. We interrogated (and sought to find consistency between - or plausible
explanations for - any differences between) the following datasets:
1. HMRC data on quantities of waste landfilled (standard rate, lower rate and
exempt);
2. Environment Agency and SEPA site returns;
3. Defra reporting to Eurostat under the Waste Statistics Regulation.
The truth remains that one can generate plausible explanations for the differences in
data, but it is not possible to be certain about the magnitude of the contribution of
83
one or other feature of the explanation to explaining the differences between
datasets. It is clear to us that there would be merit in a check on the relevant
datasets to seek to understand which factors explain which discrepancies.
The approach we took is explained in what follows.
Step 1
We gathered all available data for the 4 countries of the UK regarding construction
and demolition wastes. Sources included:
Capita Symonds with Alfatek Redox (2010) Construction, Demolition and
Excavation Waste Arisings, Use and Disposal for England 2008. CON900-001,
Final Report to WRAP
CLG Survey of Arisings and Use of Construction, Demolition and Excavation
Waste as Aggregate in England (1999, 2001, 2003 and 2005 reports)
Environment Agency Site Returns
SEPA (2008) Construction and Demolition Wastes in Scotland (2006)
http://www.sepa.org.uk/waste/waste_data/commercial__industrial_waste/co
nstruction__demolition.aspx (and similar reports from 2004 and 2005)
SEPA Waste Data Digests (1997/98 – 2008)
http://www.sepa.org.uk/waste/waste_data/waste_data_digest.aspx
SEPA Licensed/Permitted Site Returns and Exempt Activity Returns;
Environment Agency (2008) Wales Construction And Demolition Waste Arising
Survey 2005-06, http://www.environment-
agency.gov.uk/research/library/publications/33979.aspx;
Capita Symonds (2006) Survey of Arisings and Use of Construction,
Demolition and Excavation Waste as Aggregate in Northern Ireland in
2004/05 and 2005/06, Final Report to the Northern Ireland Environment and
Heritage Service, June 2006.
Enviros (2003) Environment and Heritage Service: Construction and
Demolition Waste Survey, April 2003.
Katherine Adams on behalf of the Strategic Forum for Construction (2010) CD
& E Waste: Halving Construction, Demolition and Excavation Waste to Landfill
by 2012 Compared with 2008, March 2010
http://www.strategicforum.org.uk/pdf/Waste_Draft_Part%202_22-3-10V4.pdf
Step 2
We used England data (which accounts for the bulk of construction waste in the UK)
as the basis for estimating how the composition of landfilled C&D waste has changed
over time. We used English data because this was the most often surveyed, the data
was tolerably good over a period of time (the first credible data point was from 1999),
and surveys also sought to give some indication of how much waste landfilled was
used at the site and how much was landfilled without being used. The significance of
this is explored below.
84
There is very little data on the composition of C&D waste, either in total, or for the
landfilled fraction. Two sources are:
1. Environment Agency (2008) Wales Construction And Demolition Waste Arising
Survey 2005-06, http://www.environment-
agency.gov.uk/research/library/publications/33979.aspx; and
2. East of England Construction and Demolition Waste Arisings – Final report
2009
The East of England work gives a composition which relates only to „new build
construction and repair and maintenance.‟ It also gives limited break down by
„material‟, focussing instead on the type of product which becomes waste (and it
should be said that this is a more useful classification where the aim is to understand
how best to minimise waste, so it is not intended to be critical of the approach). For
this report, therefore, we have assumed that the Welsh C&D composition can be
applied to the UK. Furthermore, given the absence of any alternative sources (of
which we are aware), we have assumed that this composition has remained constant
since 1997 (the first date at which we have sought to revise the data). This is clearly a
bold assumption but one which we make in the absence of any better information
Taking the Welsh situation in 2005/6 data as a baseline, we examined how much
waste of each different type was sent to landfill in that year. The results are shown in
Table A 10. It should be mentioned that we cross-checked these figures with those
from the East of England study. The figures in that study suggest very low rates of
landfilling for „canteen / office / ad hoc‟ and „mixed‟ wastes. It may be that the
sources of this data are reporting what they are told will happen with their waste
rather than its actual fate. The inert materials, on the other hand, show similarly low
proportions being landfilled across both the Welsh and East of England studies. That
having been said, these components constitute large parts of the C&D stream so
small variations in capture for recycling and recovery can significantly affect the
assumptions regarding the composition of waste landfilled.
We have then used our judgement as to which materials would be recycled /
recovered / re-used on site and to what extent over the period since 1997 basing our
assumptions on the view that in early years, it was likely (because the standard rate
of tax was much lower, but we know that the effect on inert wastes was large) that the
inert fractions would have been recycled / recovered (for example, at sites which
were exempt from waste management licensing, or as now, exempt from
environmental permitting) / re-used at rates closer to their current levels back in
1997 than would the materials which are not inert.65 That having been said, the
proportion of C&D waste being landfilled has not, at least according to the available
data, fallen radically. According to the England data, it has dropped from around 34%
65 See ECOTEC (2000) Effects of the Landfill Tax – Reduced Disposal of Inert Wastes to Landfill, Final
Report to DETR, January 2000; D. Hogg (1999) The Effectiveness of the UK Landfill Tax: Early Indications,
in Thomas Sterner (ed.) (1999) The Market and the Environment: Environmental Implications of Market-
Based Policy Instruments, Cheltenham: Edward Elgar.
85
in 1997 to 26% in 2008. Hence, the extent to which the modelling of radical changes
in recycled quantities proved necessary was limited.
Table A 10: Composition and Management of C&D Wastes in Wales
Material Material % of total
arisings
Proportion of Material
Landfilled
Aggregate 88.4% 9%
Insulation & Gypsum based
materials 1.4% 72%
Hazardous site waste 1.6% 13%
WEB (WEEE, ELV, Batteries) 0.1% 48%
Glass 0.1% 51%
Plastic 0.9% 71%
Paper and Cardboard 0.5% 70%
Wood 3.3% 25%
General site waste 1.3% 67%
Metals 1.5% 13%
Biodegradable waste
(Mainly Green) 1.0% 47%
Total 100.0% 12.7%
Source: Environment Agency (2008) Wales Construction and Demolition Waste Arising Survey 2005-
06, http://www.environment-agency.gov.uk/research/library/publications/33979.aspx
This process effectively gave us a composition of landfilled C&D waste (by deducting
the recycled tonnages from the total quantities).
Step 3
Using the data from all countries, we then applied this composition to all the C&D
waste being landfilled in the UK, drawing on the data sources mentioned in Step 1,
and interpolating data between years where no data was available. The result was a
dataset showing the quantity and composition of C&D waste delivered to landfills.
Step 4
This, however, included material beneficially used at landfill sites.
In one of the more recent reports Capita suggests that the HMRC figures for waste
exempt from landfill tax appear to be an acceptable proxy for the amount of landfilled
C&D material which is beneficially used in landfills:66
66 Capita Symonds with Alfatek Redox (2010) Construction, Demolition and Excavation Waste Arisings,
Use and Disposal for England 2008. CON900-001, Final Report to WRAP.
86
There are therefore good grounds for believing that the 10.6 million tonnes of
waste treated by HMRC as being exempt from Landfill Tax is a very good proxy
for the tonnage of CDEW beneficially used at landfills.
Before accepting this conclusion at face value, however, it is worth comparing
the equivalent HMRC figures for 2005 (i.e. the UK returns multiplied by 0.836
to generate estimates for England) with the estimates generated via the 2005
CDEW survey carried out for DCLG, not least because some wastes gain
exemption from landfill tax because they come from site remediation, and
some tax is deferred (e.g. where waste is used to create a haul road which is
subsequently buried within the landfill, at which point the deferred tax
becomes due).
The 2005 CDEW survey carried out for DCLG generated estimates of 27.75
million tonnes of „hard‟ C&D waste and soil-based waste being used or
disposed of as waste at landfills, of which 4.20 million tonnes were used for
engineering, 5.41 million tonnes were used for capping, and 10.24 million
tonnes although classified as waste, were reckoned to be being used to
restore former quarries (yielding a total estimate of 19.85 million tonnes of
CDEW being beneficially used at landfills). In addition, an estimated 7.90
million tonnes were estimated to have been disposed of as waste at landfills
that were not former quarries. Some 2.70 million tonnes of this may well not
have qualified for the lower rate of landfill tax. On this basis, the total tonnage
qualifying for the lower rate of tax or outright exemption would have been
expected to be 25.05 million tonnes (i.e. 19.85 million tonnes plus 7.90
million tonnes minus 2.70 million tonnes).
Although this figure is clearly higher than HMRC‟s 2005 figure of 23.3 million
tonnes, the difference (of 1.75 million tonnes) is 7.0% of the higher figure and
7.5% of the lower one. Certainly the HMRC-derived figure is comfortably within
the applicable confidence limits attached to the 2005 survey results. On
balance, therefore, the HMRC figures can be treated as providing a very good
indication of the amount of CDEW being beneficially used in landfills.
We, therefore, took HMRC data on „exempt‟ quantities as indicative of material being
beneficially used at landfills. We further assumed that this material was likely to be
comprised of aggregate and soils and that they contributed, in proportion to their
presence in the total waste stream, to this fraction.
Subtracting this from the landfilled waste gave a new quantity and composition of
waste relating to waste which is landfilled, but not beneficially used.
Step 5
In principle, it might be expected that the quantity of waste landfilled at the lower rate
would include:
1. Inert construction and demolition waste;
2. Inert commercial and industrial wastes; and
3. Other sources of inert material being landfilled (wastes from the mining
industry).
87
We compared the remaining quantity of the inert materials with the HMRC reported
quantities landfilled at the lower rate and reviewed the difference between the two
figures. Commercial and industrial wastes which are landfilled, but qualify for the
lower rate of tax (the list of these is shown in Table A 11) were estimated in the
consultation conducted by HMT and HMRC around the landfill tax for 2005. The
figures are shown in Table A 12.
Table A 11: List of Wastes Qualifying for Lower Rate Landfill Tax
Group Description of Material Conditions
Group 1 Rocks and soils Naturally occurring
Group 2 Ceramic or concrete materials
Group 3 Minerals Process or prepared, not used
Group 4 Furnace slags
Group 5 Ash
Group 6 Low activity inorganic compounds
Group 7 Calcium sulphate
Disposed of either at site not
licensed to take putrescible waste
or in containment cell which takes
only calcium sulphate
Group 8 Calcium hydroxide and brine Deposited in brine cavity
Group 9 Water Containing other qualifying material
in suspension
Notes: Group 1 includes clay, sand, gravel, sandstone, limestone, crushed stone, china clay, construction stone, stone from
the demolition of buildings or structures, slate, topsoil, peat, silt and dredgings.
Group 2 comprises only the following–
(a) glass;
(b) ceramics;
(c) concrete.
For these purposes–
(a) glass includes fritted enamel, but excludes glass fibre and glass-reinforced plastic;
(b) ceramics includes bricks, bricks and mortar, tiles, clay ware, pottery, china and refractories;
(c) concrete includes reinforced concrete, concrete blocks, breeze blocks and aircrete blocks, but excludes concrete
plant washings.
Group 3 comprises only the following–
(a) moulding sands;
(b) clays;
(c) mineral absorbents;
(d) man-made mineral fibres;
(e) silica;
(f) mica;
(g) mineral abrasives;
(h) used foundry sand (by extra-statutory concession).
88
For these purposes –
(a) moulding sands excludes sands containing organic binders;
(b) clays includes moulding clays and clay absorbents, including Fuller's earth and bentonite;
(c) man-made mineral fibres includes glass fibres, but excludes glass-reinforced plastic and asbestos.
Group 4 includes–
(a) vitrified wastes and residues from thermal processing of minerals where, in either case, the residue is both fused
and insoluble;
(b) slag from waste incineration.
Group 5–
(a) comprises only bottom ash and fly ash from wood, coal or waste combustion; and
(b) excludes fly ash from municipal, clinical and hazardous waste incinerators and sewage sludge incinerators.
Group 6 comprises only titanium dioxide, calcium carbonate, magnesium carbonate, magnesium oxide, magnesium
hydroxide, iron oxide, ferric hydroxide, aluminium oxide, aluminium hydroxide and zirconium dioxide.
Group 7 includes gypsum and calcium sulphate based plasters, but excludes plasterboard.
Table A 12: Estimates of Commercial and Industrial Wastes Qualifying for Lower Rate
of Landfill Tax (data appears to be for 2005)
The Landfill Tax (Qualifying Material)
Order 1996 Waste material
Estimated tonnage
put to landfill
Group 3 Minerals Used foundry sand* 200,000
Group 4 Furnace slags Furnace slags (thermal
processing of minerals) 670,000
Group 4 Furnace slags Waste incineration slag 314,000
Group 5 Ash Coal fly ash ** 3,000,000
Group 7 Calcium sulphate Gypsums 11,000
Group 8 Calcium hydroxide & brine Brine purification wastes 44,000
TOTAL 4,239,000
Source: Adapted from HM Treasury and HM Revenue & Customs (2009) Modernising Landfill Tax
Legislation, April 2009
http://webarchive.nationalarchives.gov.uk/20100407010852/http://www.hm-
treasury.gov.uk/d/Budget2009/bud09_landfill_tax_964.pdf
Environment Agency Waste Data 2007
*Communities and Local Government (2007) Construction Demolition and Excavation Waste (CDEW)
Survey of arisings and use of alternatives to primary aggregates in England 2005
** Waste & Resources Action Programme (WRAP)/Environment Agency (2008) Waste Protocol
Project- Pulverised fuel ash and furnace bottom ash
In more recent years, this „gap‟ between HMRC figures for material landfilled at the
lower rate of tax and the quantity of non-exempt inert wastes we have estimated was
being landfilled can be explained through reference to the tonnages of PFA and other
slags landfilled. In earlier years, the figures are less easy to reconcile (the reported
89
lower rate tonnages from HMRC are much higher than our estimates could justify67).
There may be reasons for this (for example, the quantity of standard rate materials
mixed with lower rate ones, but passed as lower rate for tax, might have been
relatively high in early years of the tax). In any case, we decided that this was not the
most pressing „discrepancy‟ on the basis that it mainly concerned difficulties in
reconciling data regarding wastes which were likely to be „non-gassing‟ ones. Given
the emphasis of the study, it seemed less pressing than where one could not explain
the discrepancies in wastes responsible for methane generation.
Step 6
Two categories of waste in the Welsh study were „composites‟. These were:
1. General Site Waste; and
2. Paper and Card
For General Site Waste, we assumed 20% would be food and 40% would be paper
and card. As will become clear below, despite our desire to have separate
characteristics for paper and card, this proved not to be possible, so the paper and
card category was kept as one.68
The landfilled quantities of C&D waste were reported under the following headings:
Paper
Card
Food
Garden; and
Other.
Step 7
Data on commercial and industrial waste was gathered from a number of sources.
The period for which we sought data was from 1997 onwards. Sources included:
1. Environment Agency (England and Wales data for 1998/99 and 2002/3;
2. SEPA Waste Data Digests (landfilled quantities in early years, and total
quantities in later years)
3. ADAS (2009) National Study into Commercial and Industrial Waste Arisings,
Final report for EERA;
4. Urban Mines (2009) Welsh C&I Survey 2007/08, Report to WAG;
67 The discrepancies are as high as 8 million tonnes in early years. This is based upon historic figures
from the UK Quality Ash Association and the Environment Agency and SEPA. We take the matter up
again below.
68 There was another reason for this: MELMod does not include a sufficient number of rows (for
different waste materials) to enable us to break down the composition as finely as one might ideally
like.
90
5. SEPA (2007) Scotland Business Waste Survey 2006;
6. MEL and EnviroCentre (2002) Industrial and Commercial Waste Production in
Northern Ireland, Final Report to the Northern Ireland Environment and
Heritage Service.
Other data sources were examined but not used, principally because they suggested
data which was inconsistent, and significantly so, with the available time series (to
the extent that such a time-series could meaningfully be discerned).
Step 8
We interpolated data (usually linear interpolation) between the known data points. In
some cases, the data appeared to give figures which were simply difficult to believe
given all the other available data sources and the trends they were suggesting. So, for
example, the estimated level of waste landfilled under the recent ADAS report seems
much higher than can be explained through either reference to other data points, or
to the trends in landfilled waste suggested by HMRC data.
The data has been used to estimate quantities of commercial and industrial waste
landfilled over the period from 1997. It is worth stating at this juncture that this data
is of extremely low quality. It is hoped that it will improve in the wake of ongoing work
by the Environment Agency.
Step 9
The Environment Agency reported C&I data according to sector or according to „waste
type‟. Unfortunately, as with the data in MELMod, the landfilled quantities relate
mainly to the „mixed‟ waste classifications. The same is true of Environment Agency /
SEPA site return data, which now reports against EWC codes, as well as the data
reported to the Waste Statistics Regulation (where, incidentally, it seems difficult to
reconcile figures on waste quantities, and the way the different types of waste are
managed).
Data concerning commercial waste suggests that recycling rates have barely changed
over the period (remaining broadly constant at around 53%) whilst the landfilling of
industrial waste has fallen from 38% to 26% of the total over the same 1997/8-
2008/9 period. This is a much smaller drop than one might expect (and far lower
than „what is happening on the ground‟ would lead one to expect).69
It is difficult to know exactly how the composition of landfilled industrial waste would
have changed over this period as the proportion landfilled has declined. Industrial
wastes are highly heterogeneous across producers (each sector tends to produce
relatively high proportions of a small range of wastes). Therefore, in the absence of
data (at present) allowing for varying composition over time, we chose to use a
constant composition for the landfilling of industrial waste.
69 Although few studies set out to answer this question, it is quite clear that the offer of, and uptake of,
commercial waste recycling services has increased significantly over the last decade. It is very difficult
to reconcile this widening service roll-out with an unchanging level of commercial waste recycling.
91
Where commercial waste is concerned, the nature of the materials produced as
commercial waste exhibit some commonality across commercial enterprises,
although different enterprises will produce slightly different proportions of those
materials. We set up our approach to model changes in composition over time
through varying recycling rates of specific materials, though as mentioned above, the
recycling rate for commercial waste – at least, according to the best available data –
has barely changed over time. Consequently, limited adjustment of the recycling rates
was required.
The sources used for waste composition were (the data used is shown in Table A 13):
1. For landfilled industrial wastes, a report for the Environment Agency Wales;70
and
2. For the total commercial waste stream, the same report, though adding back
to the landfilled quantities the quantities which it was estimated were being
recycled from the commercial waste stream in the same year. 71
Table A 13: Composition of Commercial and Industrial Wastes Landfilled, Total
Commercial Waste, and Captures of Commercial Waste for Recycling and Recovery
Industrial
Waste
Landfilled
Commercial
Waste
Landfilled
Total
Commercial
waste
Captures for
recycling etc,
(Commercial Waste)
Paper 13.60% 14.90% 18.29% 55.80%
Card 21.80% 20.90% 21.55% 47.37%
Plastics 17.40% 14.80% 10.33% 22.29%
Textiles and Shoes 1.10% 1.20% 0.85% 23.20%
Nappies 0.10% 0.20% 0.11% 0.00%
Wood 4.80% 4.50% 4.15% 41.21%
Carpet and Underlay 3.20% 1.00% 0.54% 0.00%
Furniture 0.20% 0.30% 0.16% 0.00%
OMC [define] 9.80% 5.10% 2.77% 0.00%
MNC [define] 6.60% 2.10% 9.13% 87.52%
Glass 0.90% 4.90% 6.34% 58.05%
Garden 0.40% 1.40% 0.76% 0.00%
Kitchen 12.40% 21.65% 13.53% 13.17%
Oils 0.00% 0.00% 0.97% 100.00%
Metals WEE and potentially haz 6.70% 5.40% 8.47% 65.41%
Biodegradable industrial sludges 0.00% 0.20% 0.72% 84.84%
Fines 1.00% 1.45% 0.79% 0.00%
Healthcare and biological 0.55% 100.00%
Source: SLR (2007) Determination of the Biodegradability of Mixed Industrial and Commercial Waste
Landfilled in Wales, November 2007, Report to Environment Agency Wales
70 See SLR (2007) Determination of the Biodegradability of Mixed Industrial and Commercial Waste
Landfilled in Wales, November 2007, Report to Environment Agency Wales
71 See SLR (2007) Determination of the Biodegradability of Mixed Industrial and Commercial Waste
Landfilled in Wales, November 2007, Report to Environment Agency Wales
92
Step 10
For industrial wastes, as stated above, it was assumed that the composition of
landfilled mixed waste has been constant over time. This mixed waste would most
probably be landfilled separately from inert, non-mixed wastes, especially where
these attract a lower rate of landfill tax. It was necessary, therefore, to deduct, from
the estimated quantity landfilled, an estimate of the quantity of inert, non-mixed
wastes (ash etc.) which are landfilled. Table A 12 above suggests this is in excess of 4
million tonnes. However, we believe this figure is likely to be somewhat higher (given
the difficulties explaining the gulf between HMRC data and site return data / the
results of survey work) and have estimated this figure at 7 million tonnes.
The commercial waste composition was applied to the remaining quantity landfilled in
each year to generate figures regarding the quantity of each material landfilled in any
given year. This is a gross simplification, and one which it is to be hoped can be
replaced over time with more robust information about which materials are being
managed in which way across the UK economy.
For commercial waste, the starting point was the composition for total commercial
waste. The captures of material for recycling / recovery calculated using the same
Welsh report were used to guide how well different fractions of the waste stream were
assumed to be captured in the years since 1997. These captures were adjusted to
ensure that the results were delivering the required recycling rate in each year (in
other words, so that the landfilled quantities reflected the data). As mentioned
previously, limited adjustment was required owing to the relatively constant level of
recycling at the start and end of the period (some variation appears – at least,
according to the data – to have taken place over time).
Step 11
The figures for landfilled commercial and industrial wastes were then aggregated.
These were subsequently added to the figures for construction and demolition
wastes. The results for the quantities landfilled, shown alongside data currently within
MELMod, are shown in Figure A 6. This illustrates how far removed the data within
MELMod appears to have become from the figures suggested by the best data
currently available.
The suggested breakdown, in terms of composition, is as set out in Table A 14.
93
Figure A 6: Data for Landfilled C&I and C&D Waste, MELMod and Proposed Revision
(million tonnes)
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
Lan
dfi
lled
C&
I an
d C
&D
Was
te,
Mill
ion
To
nn
es
Proposed Revision
MELMod
94
Table A 14: Suggested Revision to MELMod data, C&I and C&D Wastes (million tonnes)
1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09
Commercial
Paper and Card 9.12 8.92 8.71 8.88 8.70 8.41 7.64 6.76 6.10 5.09 4.95 4.48
General industrial waste
Food 6.17 6.09 6.10 6.32 6.30 6.26 5.91 5.66 5.23 4.94 4.70 4.36
Food effluent / Biodeg
Ind Sludges (from
1997) 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.03
Abattoir waste
Misc processes
Other waste
Misc Comb 2.10 2.05 2.02 2.13 2.05 1.97 1.75 1.56 1.37 1.21 1.13 1.00
Furniture 0.08 0.08 0.07 0.07 0.07 0.07 0.06 0.06 0.05 0.05 0.05 0.04
Garden 1.07 1.08 0.99 0.99 1.04 1.03 1.03 1.03 1.00 0.99 0.94 0.89
Sewage sludge
Textiles / Carpet and
Underlay 0.91 0.89 0.87 0.92 0.89 0.85 0.76 0.67 0.59 0.52 0.48 0.43
Wood 3.26 3.35 3.10 3.01 3.08 3.04 2.96 2.87 2.75 2.59 2.35 2.04
Sanitary 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.04 0.04 0.04 0.04
Other 47.02 44.89 44.41 42.95 39.53 42.44 45.35 44.41 42.95 40.20 36.87 34.24
Proposed Revision 69.82 67.44 66.36 65.37 61.74 64.17 65.56 63.10 60.13 55.67 51.53 47.56
95
A.2.5 Forward Projections
We were asked by Defra to make forward projections in the model. These projections
are not our own and are based upon Defra / HMRC views as to the likely effects of
policy instruments currently in place. This was carried out separately for commercial
and industrial waste, and for local authority managed waste.
It should be noted that the projections for commercial and industrial waste landfilled
are related to a considerable degree to data from landfill tax returns. We highlighted
above the differences between the landfill tax data and the site returns generated by
the relevant environment agencies. These include the following, and mainly result
from the fact that the data sources are used for different purposes:
1. Persons registrable for landfill tax are required to submit a return to HMRC in
respect of each accounting period and make payment of the tax liability
established by that return. This form also asks that the person submitting the
return provides information on the weight of waste in tonnes, per rate category
(standard, lower, and exempt waste), landfilled in the return period to which
the return relates. A return will normally cover a three month period. In some
instances, schemes are in place to discount the water content of waste and so
therefore the weight recorded does not necessarily correspond with the weight
landfilled;
2. There are definitional differences between the two sets of figures as the HMRC
figures are based on the amounts of waste liable for tax, whereas the site
returns record total waste landfilled. Not all waste is liable for landfill tax, so
some sites which landfill waste may landfill only waste which is not subject to
tax (such as mining and quarrying waste, dredged waste, pet cemeteries,
restoration of landfill sites and quarries taking only inert waste). Where the
sites concerned are only taking these categories of waste they are not
required to register for landfill tax and therefore tonnage from these sites will
not appear in HMRC figures, even as wastes exempt from tax; and
3. The site return data comes from returns from operators of facilities that are
described by the Agency as landfills, but in reality often include some
associated treatment and transfer facilities that divert some of their incoming
waste from disposal to recovery (indeed, some have tax exempt areas for
sorting waste prior to landfilling, so re-export of waste off-site likely takes
place).Sites sitting inside the ring fence of a landfill are covered by
Environmental Permits which are considered by the Agency to have been
primarily aimed at landfilling activity. As a consequence, the materials going to
some treatment and transfer facilities are included within the landfill site
returns made to the Agency by their operators, and effectively overstate the
tonnage of waste actually being disposed of to landfill.
In summary, there are fundamental differences in what the figures cover, and so the
two data sets cannot be directly compared. The HMRC data probably implies an
under-estimate of landfilled quantities whereas the opposite may apply to site returns
data.
96
In making the projections, we have sought to ensure that the quantities and the
composition are consistent with our proposed revisions, and with expectations for
improved recycling and recovery of materials as existing policy instruments take
effect.
The details of the projections are confidential and so are not revealed here. It should
be noted, however, that the projections only affect landfilled quantities in the years to
2019 for MSW and to 2015 for non-MSW. After these years, the landfilled quantities
are assumed to remain constant. We note again that these are not our own
projections.
97
A.3.0 Characteristics of Component Waste
Streams This Appendix reviews the data on moisture content, and on the biochemical
constituents of the component waste streams modelled in MELMod. It goes on to
review the available evidence in terms of these factors as a basis for proposing
alternative figures to those currently used in the model.
There are a number of problems with the figures derived by LQM, which are contained
in MELMod, and which are shown in Table A 15. These are outlined in the Sections
that follow.
A.3.1 Moisture Content
The moisture contents deserve closer examination. For example, paper and card are
rarely characterised as being 30% moisture (see Table A 15). If putrescibles include
both food and garden waste, then other than in a case where the overwhelming
majority was food waste, the 65% moisture figure seems too high.
It is difficult to comment on the miscellaneous combustibles for reasons already
described (the general nature of this category). To the extent, however, that fines are
often approximately 50% food waste, and with food waste being of the order 70%
moisture, the 20% moisture figure is likely to be too low (one can also point out that
the organic component with the lowest moisture content and highest degradable
carbon content – paper and card – is estimated to have 30% moisture. Since
miscellaneous combustibles are the second most degradable fraction, the figure
looks internally inconsistent at least).
The following is a review of alternative data in this respect. A number of sources for
the moisture content and carbon constituents of waste materials exist, both from the
UK and overseas. In some cases considerable variation can be seen in the values
obtained from the different sources, particularly with regard to the moisture content.
What matters is that the moisture content chosen for use is consistent with the way in
which any related composition analysis – used to derive the composition of what is
landfilled - has been carried out. The „as received‟ moisture content of a given
material depends, unsurprisingly, on the exact form in which it is received.72
72 This point was also made in Barlaz review of composition data associated with landfilled waste
materials. See Barlaz M A (2006) Forest products decomposition in municipal solid waste landfills,
Waste Management, Issue 26, pp. 321-333
98
Table A 15: MELMod Parameters for Waste Components
Component RDO MDO SDO Inert
Typ
ica
l w
ate
r co
nte
nt
Ce
llu
lose
co
nte
nt
(pe
r ce
nt
dry
we
igh
t)
He
mi-ce
llu
lose
co
nte
nt
(p
er
ce
nt
dry
we
igh
t)
De
co
mp
osit
ion
(pe
r ce
nt
dry
we
igh
t)
DO
C t
ha
t ca
n d
eco
mp
ose
ca
lcu
late
d f
rom
ce
llu
lose
an
d h
em
ice
llu
lose
co
nte
nt
(DD
OC
)
MSW
Paper and Card 0% 25% 75% 0% 30% 61.2% 9.1% 61.8% 13.5%
Dense plastics 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 0.00%
Film plastics (until 1995) 0% 0% 0% 100% 30% 0.0% 0.0% 0.0% 0.00%
Textiles 0% 0% 100% 0% 25% 20.0% 20.0% 50.0% 6.67%
Misc. combustible (plus non-inert fines from 1995) 0% 100% 0% 0% 20% 25.0% 25.0% 50.0% 8.89%
Misc. non-combustible (plus inert fines from 1995) 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 0.00%
Putrescible 100% 0% 0% 0% 65% 25.7% 13.0% 62.0% 3.73%
Composted Putrescibles 0% 50% 50% 0% 30% 0.7% 0.7% 57.0% 0.25%
Glass 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 0.00%
Ferrous metal 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 0.00%
Non-ferrous metal and Al cans 0% 0% 0% 100% 10% 0.0% 0.0% 0.0% 0.00%
Non-inert fines 100% 0% 0% 0% 40% 25.0% 25.0% 50.0% 6.67%
Inert fines 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 0.00%
Incinerator Ash 0% 0% 0% 100% 0% 0.0% 0.0% 0.0% 0.00%
Stabilised Residues 0% 0% 0% 100% 0% 0.0% 0.0% 0.0% 0.00%
99
Component RDO MDO SDO Inert
Typ
ica
l w
ate
r co
nte
nt
Ce
llu
lose
co
nte
nt
(pe
r ce
nt
dry
we
igh
t)
He
mi-ce
llu
lose
co
nte
nt
(p
er
ce
nt
dry
we
igh
t)
De
co
mp
osit
ion
(pe
r ce
nt
dry
we
igh
t)
DO
C t
ha
t ca
n d
eco
mp
ose
ca
lcu
late
d f
rom
ce
llu
lose
an
d h
em
ice
llu
lose
co
nte
nt
(DD
OC
)
C&I waste
Commercial 15% 57% 15% 13% 37% 76.0% 8.0% 85.0% 19.99%
Paper and card 0% 25% 75% 0% 30% 87.4% 8.4% 98.0% 29.21%
General industrial waste 15% 43% 20% 22% 37% 76.0% 8.0% 85.0% 19.99%
Food solids 79% 10% 0% 11% 65% 55.4% 7.2% 76.0% 7.40%
Food effluent 50% 5% 0% 45% 65% 55.4% 7.2% 76.0% 7.40%
Abattoir waste 78% 10% 0% 12% 65% 55.4% 7.2% 76.0% 7.40%
Misc processes 0% 5% 5% 90% 20% 10.0% 10.0% 50.0% 3.56%
Other waste 15% 35% 35% 15% 20% 25.0% 25.0% 50.0% 8.89%
Power station ash 0% 0% 0% 100% 20% 0.0% 0.0% 0.0% 0.00%
Blast furnace and steel slag 0% 0% 0% 100% 20% 0.0% 0.0% 0.0% 0.00%
Construction/demolition 0% 5% 5% 90% 30% 8.5% 8.5% 57.0% 3.01%
Sewage sludge 100% 0% 0% 0% 70% 14.0% 14.0% 75.0% 2.80%
Textiles (user defined) 100% 0.00%
Wood (user defined) 100% 0.00%
Industrial Putrescible (user defined)s 100% 0.00%
Metals (user defined) 100% 0.00%
100
A.3.1.1 Paper and Card
It may be that the data underpinning MELMod was derived from UK data gained in
the 1990s from the UK National Household Waste Analysis Programme initiated by
the then Department of Environment. This data is shown below, and for none of the
paper / card fractions represented in MELMod does the figure reach the 30% used in
MELMod. Indeed, whilst the average for paper and card is given as 24%, the moisture
content of magazines is much lower. This data is used in the Environment Agency LCA
tool, WRATE, and data from this source is shown in Table A 16.
Table A 16: Moisture Content of Paper and Card
Moisture content %
Newspapers 25.57
Magazines 11.30
Recyclable paper 27.45
Other paper 27.45
Card packaging 26.73
Other card 24.15
Note: WRATE gives generic value for the moisture content of paper and card as 24%
Source: National Household Waste Analysis Programme (data supplied by personal communication
with the Environment Agency)
More recent UK data has been generated by Godley et al. Table A 17 presents
information on moisture content of card and newspaper, along with their loss on
ignition (measures organic content). This suggests a much lower moisture content for
both newspaper and cardboard packaging, although data for wet cardboard confirms
the ability of paper and card to „collect‟ moisture.
Table A 17: Dry and Organic Matter Content of Paper and Card
Dry matter content, %
wet weight
Organic matter content
(Loss on ignition, % dry
weight)
Packaging waste - wet cardboard 44.5% 94.2%
Cardboard packaging 92.3% 90.0%
Newspaper 90.8% 92.8%
Source: Godley A, Frederickson J, Lewin K, Smith R and Blakey N (2007) Application of DR4 and
BM100 Biodegradability Tests to Treated and Untreated Organic Wastes, Proceedings of the Eleventh
International Waste Management and Landfill Symposium, Caliari, Italy, October 2007
101
In developing the Orware simulation model of an Anaerobic Digestion facility, Dalemo
(2004) suggested the moisture content for dry paper was 12%, but assumed
cardboard would have a moisture content of 21%.73
The Austrian Umweltbundesamt, in its waste modelling, uses figures of 15% moisture
for packaging paper and board, and 12.5% moisture for non-packaging paper and
board.74 VITO used a figure of 18% moisture for paper and card.75 A Swiss study used
figures of 15.7% for paper and 22% for packaging board.76
Data from the Netherlands suggests a moisture content for mixed paper and
cardboard of 12% using data from samples taken in the mid 1990s.77
The review appears to confirm that the 30% figure is too high. However, there is some
disagreement in studies as to the extent of the over-estimate. It would be preferable
to have figures for both paper and for card.
We would suggest the following figures for use in the model:
Paper 15% moisture
Card 20% moisture
We believe these are appropriate for both MSW and non-MSW.
A.3.1.2 Food Waste
Data on composition of food waste is available through studies on Anaerobic
Digestion. In some cases data relating to an unspecified mixture of “domestic organic
waste” is given with no information on the relative proportions of food and garden
waste. The data in Table A 18 relates to the moisture content of food waste alone
unless otherwise stated. This data indicates that the moisture content of food waste
fractions varies from 60-80%, with a typical moisture content of 70%.
We suggest that for food waste, the moisture content is set at 70%. This is higher
than in MELMod (which uses lower figures even for food effluent, and for abattoir
wastes).
73 M. Dalemo (2004) The Modelling of an Anaerobic Digestion Plant and a Sewage Plant in the Orware
Simulation Model: Swedish University of Agricultural Sciences, Report 213
74 Personal communication with Wolfgang Stark.
75 VITO (2001) Procesbeschrijving Afvalverwerkingstechnieken: Integrale Miliestudies.
76 SEAFL (1998) Life Cycle Inventories for Packagings, Volumes I and II, Environmental Series No.
250/I&II Waste, Berne, Switzerland, Swiss Agency for the Environment, Forest and Landscape/
77 Beker D and Cornelissen A A J (1999) Chemische Analyse Van Huishoudelijk Restafval: Resultaten
1994 en 1995, National Institute of Public Health and the Environment, Nederland
102
Table A 18: Moisture Content of Food Waste Fractions
Source Description Moisture content
Biocycle Household food waste 72%
Dalemo Household food waste 70%
Canteens, restaurants 70%
NHWAP Household food waste 62%
Cecchi et al Fruit & vegetable markets 80-85%
Household food waste 70-80%
Canteens, restaurants 70-80%
Davidsson et al Household food waste 63-83%
Godley et al Raw vegetable mixture 87%
Sources: Biocycle (2009) Demonstration Project: Biocycle South Shropshire Ltd Biowaste Digestor,
Report for Defra; M. Dalemo (2004) The Modelling of an Anaerobic Digestion Plant and a Sewage
Plant in the Orware Simulation Model: Swedish University of Agricultural Sciences, Report 213; Cecchi
F, Traverso P, Pavan P, Bolzonella D and Innocentia L (2003) Characteristics of the OFMSW and
behaviour of the anaerobic digestion process, in Biomethanization of the Organic Fraction of Municipal
Solid Wastes, Ed. Mata-Alvarez J, Publ. IWA Publishing; National Household Waste Analysis Programme
(data supplied by personal communication with the Environment Agency); Davidsson A, Gruvberger C,
Christensen T, Hansen T and la Cour Jansen J (2007) Methane Yield in Source-sorted Organic Fraction
of Municipal Waste Management, Waste Management 27 pp.406-14; Godley A, Frederickson J, Lewin
K, Smith R and Blakey N (2007) Application of DR4 and BM100 Biodegradability Tests to Treated and
Untreated Organic Wastes, Proceedings of the Eleventh International Waste Management and Landfill
Symposium, Caliari, Italy, October 2007
A.3.1.3 Garden Waste
The literature confirms the considerable variation in the moisture content of garden
waste components. Tree branches, for example, show both diurnal and seasonal
variations in moisture content.78 The annual pattern of branch temperature and
moisture contents consisted of a cold wet winter period when branch moisture
contents are at or above saturation, low temperatures and high rainfall prevent
drying. When temperatures rise in spring the trend is for branches to begin gradually
to dry. During the summer months moisture contents are not constant and vary
considerably from day to day with fairly rapid drying following periods of wetting.
Moisture contents only rarely fell below the fibre saturation point. With the approach
of autumn and winter the overall trend is for a gradual increase in moisture content
but with periods of slow drying occurring whilst temperatures are still high enough to
allow this. Garden waste may also, however, lose moisture in a dry environment.
Table A 19 shows moisture content ranges presented in a range of literature sources.
78 Boddy L (1983) Microclimate and Moisture Dynamics of Wood Decomposing in Terrestrial
Ecosystems, Soil Biology and Biochemistry, 15, pp146-157
103
Table A 19: Moisture Content of Garden Waste Components
Source Description Moisture content
Barkdoll et al Yard waste 30%
Biomass handbook Branches 30-80%
NHWAP Garden waste 58%
Das Mixed branches & leaves 52-59%
Dalemo Park & garden waste 30-40%
Phyllis Grass 20-64%
Straw 15%
Godley et al Grass (lawnmower cuttings) 81%
Greenwaste 59%
Sources: Barkdoll A, Nordsedt R and Mitchell D (2001) Large Scale Utilization and Composting of Yard
Waste, University of Florida; Dalemo M (2004) The Modelling of an Anaerobic Digestion Plant and a
Sewage Plant in the Orware Simulation Model: Swedish University of Agricultural Sciences, Report
213; Das K (2007) Co-composting of Alkaline Tissue Digester Effluent with Yard Trimmings, Waste
Management, 28, 1785-1790; Kitani O and Hall C (1989) Biomass Handbook, Publ. Gordon and
Breach Science Publishers; Phyllis Database for Biomass and Waste http://www.ecn.nl/phyllis/;
National Household Waste Analysis Programme (data supplied by personal communication with the
Environment Agency); Godley A, Frederickson J, Lewin K, Smith R and Blakey N (2007) Application of
DR4 and BM100 Biodegradability Tests to Treated and Untreated Organic Wastes, Proceedings of the
Eleventh International Waste Management and Landfill Symposium, Caliari, Italy, October 2007
It would be desirable to have a more appropriate split of garden waste across
different fractions (MELMod includes information on garden waste only in the
„putrescibles‟ category as part of MSW, which our analysis suggests is now around
88% food waste). However, in the absence of our being able to do this, we suggest
that a figure of 55% would be appropriate, reflecting a mix across the year of wetter
grass, and drier branches and leaves. For the reasons discussed above, this figure
will vary depending upon how, and under what conditions, and at what time of year,
garden waste is collected.
A.3.1.4 Wood
As is the case with garden waste, the moisture content of wood varies enormously.
Wood products from virgin, untreated wood can contain up to 60% moisture. In
contrast, treated waste wood such as packaging material or MDF board has a much
lower moisture content. Data is shown in Table A 20.
104
Table A 20: Moisture Content of Wood Products
Source Description Moisture content
Biomass Energy Centre Virgin wood as received Up to 60%
Austrian Energy Agency Wood fuel (not specified) 10-60%
NCP (Finland) Wood fuel as received 20-65%
NIFES Wholewood & Stemwood as
received 40-55%
Logging residue chip as received 50-60%
Beker and Cornelissen Packaging wood 12%
Stubenberger et al MDF board 8%
Waste wood 17%
Frandsen et al Waste wood 16%
Godley et al Construction wood waste 23%
Source: Biomass Energy Centre http://www.biomassenergycentre.org.uk ; Austrian Energy Agency
(u.d.) Wood Fuels: Characteristics, Standards, Production Technology; NCP (u.d.) Wood as a Fuel:
Material for 5EIRES Training Sessions; NIFES (2004) Wood-fuel Seminar: Notes and Worked Examples:
Seminar for OPET Scotland; Stubenberger G, Scharler R, Zahirovic S and Obenberger I (2008)
Experimental Investigation of Nitrogen Species Release from Different Solid Biomass Fuels as a Basis
for Release Models, Fuel, 87, pp793-806; Beker D and Cornelissen A A J (1999) Chemische Analyse
Van Huishoudelijk Restafval: Resultaten 1994 en 1995, National Institute of Public Health and the
Environment, Nederland; Flemming J, Frandsen S, van Lith S, Korbee R, Yrjas P, Backman R,
Obenberger I, Brunner T and Joller M (2007) Quantification of the Release of Inorganic Elements from
Biofuels, Fuel Processing Technology, 88, pp1118-1128; Godley A, Frederickson J, Lewin K, Smith R
and Blakey N (2007) Application of DR4 and BM100 Biodegradability Tests to Treated and Untreated
Organic Wastes, Proceedings of the Eleventh International Waste Management and Landfill
Symposium, Caliari, Italy, October 2007.
We propose the following figures for waste wood:
1. From the MSW stream, the remaining wood waste being landfilled is likely to
relatively dry. Not all of it, however, will be as dry as prepared pallets. We
suggest, therefore, using the figure for waste wood proposed above, i.e. 17%.
2. For the non-MSW stream, it seems likely that most wood being landfilled will
be of a dry nature, though it is believed that the capture of packaging wood for
re-use and recycling is very high (and data suggests this has been true since
the late 1990s). We propose the same figure of 17%.
A.3.1.5 Textiles
Godley et al examined bedding sheets and knitting wool and both had moisture
contents below 10% (3% and 6% respectively).79 A Dutch study found a similarly low
79 Godley A, Frederickson J, Lewin K, Smith R and Blakey N (2007) Application of DR4 and BM100
Biodegradability Tests to Treated and Untreated Organic Wastes, Proceedings of the Eleventh
International Waste Management and Landfill Symposium, Cagliari, Italy, October 2007
105
figure of 3%.80 The Austrian Umweltbundesamt uses a figure of 18% moisture for
textiles. VITO used a figure of 30% moisture.
Some of this variation would clearly be explained by the nature of the materials
examined, and indeed, which categories were being included under „textiles‟.
However, it seems as though the moisture content would be relatively low. Some
studies do give a much higher moisture content for carpets and rugs, but this
category is kept within „miscellaneous combustibles‟ in this study.
We propose to leave the 20% figure in MELMod unchanged. Please note that this
figure is also applied to footwear since composition analyses generally report the two
together when the household / municipal / local authority controlled waste stream is
being examined.
A.3.1.6 Nappies
For nappies, we show in Table A 21 the composition used by ERM in their life cycle
assessment of nappies. If one assumes the urine remains as a liquid, and if one
assumes the remaining matter is dry (and the unsoiled nappy figures from Godley et
al support this view), then the moisture content is as in the final column of the Table.
VITO suggested a moisture content for sanitary products of 52%.81 The ORWARE
model in Sweden suggested a value of 72% moisture content, much closer to the
values in the ERM study.
Table A 21: Disposable Nappy Composition
Scenario Urine
(kg)
Faeces
(kg)
Plastics
(kg)
Pulp
(kg)
Miscellaneous
(kg)
Total
(kg)
Urine
as %
Total
Original 299 66 84 50 13 482 62%
WRAP Estimate* 596 131 84 50 13 874 68%
Note: WRAP estimate assumes the same urine to faeces split
Source: Eunomia calculations and ERM (2008) An updated lifecycle assessment study for disposable
and reusable nappies, Environment Agency Science Report – SC010018/SR2,
http://publications.environment-agency.gov.uk/pdf/SCHO0808BOIR-e-e.pdf
We propose to use the average of the two studies from the ERM study, a figure of
65% moisture.
80 Beker D and Cornelissen A A J (1999) Chemische Analyse Van Huishoudelijk Restafval: Resultaten
1994 en 1995, National Institute of Public Health and the Environment, Nederland
81 VITO (2001) Procesbeschrijving Afvalverwerkingstechnieken: Integrale Miliestudies.
106
A.3.1.7 Furniture
In our modelling, we suggest that furniture should be treated as being composed of a
specific proportion of both textiles and wood. As such, the category refers essentially
to those materials. We have calculated this based upon a composition which includes
62% wood and 5% textiles (by weight) in municipal waste, and 50% wood (by weight)
when from commercial and industrial waste (the balance, in each case, being non-
biodegradable material).
A.3.1.8 Mattresses
In our modelling, we suggest that mattresses should be treated as being composed of
a specific proportion of textiles. As such, the category refers essentially to textiles. We
have assumed mattresses are 50% textiles by weight, with the balance being non-
biodegradable material).
A.3.1.9 Miscellaneous Combustibles
In our analysis we have tried to maintain the discipline of having only biodegradable
materials in the miscellaneous combustibles. However, the nature of miscellaneous
combustibles makes it difficult to argue strongly for any specific value for moisture
content. We note, however, that a 20% content, as in MELMod, may be quite low as
this is close to the lower end of moisture content for any of the biodegradable
materials reviewed.
A.3.2 Organic Carbon Content of Waste Materials
Data currently in MELMod bases the degradable carbon content of different wastes
upon their cellulose and hemicellulose content. The calculation ignores the fact that
other fractions of carbon clearly exist, which do degrade in landfill. For example, the
degradability of a waste stream consisting entirely of protein would be assumed to be
zero in MELMod even though proteins might degrade quite rapidly under anaerobic
conditions.
For some specific materials, the bulk of the organic matter is not composed solely of
cellulose and hemicellulose, but includes other readily degradable organic molecules
(fats, proteins, etc.), the majority of food wastes being a case in point. MELMod
implies that only 38.7% of dry matter in Putrescible waste is degradable, whilst the
figure is higher for all other biodegradable materials (other than composted
putrescibles). It does raise the question as to what the term „putrescible‟ is really
intended to convey.
It is unclear why the other organic fractions were not taken account of. A report by
AEA Technology stated:82
82 S. L. Baggott et al (2006) Addendum to UK Greenhouse Gas Inventory, 1990 to 2004, Annual
Report for submission under the Framework Convention on Climate Change, Report RMP/2106, July
2006.
107
Cellulose and hemi-cellulose are known to make up approximately 91% of the
degradable fraction, whilst other potential degradable fractions which may
have a small contribution (such as proteins and lipids) are ignored.
The statement is unsupported, and is obviously not true for all waste fractions. In any
(policy) analysis which examines the effect on different materials / waste streams,
overlooking the widely varying contributions made by other biochemical components
is likely to generate erroneous results.
Back in 1997, in a seminal paper, Eleazer et al wrote:83
In previous research with mixed refuse, carbohydrates accounted for 91%of
the stoichiometric methane potential (18). Carbohydrates were the major
organic compounds analyzed in the waste components tested here, and the
relationship between carbohydrate concentration and methane yield is
presented in Figure 3. The relatively weak linear relationship (r2) 0.49) and
failure of the regression line to pass through zero suggest that factors in
addition to carbohydrate concentration influence methane yield.
The „previous work‟ referred to was carried out by Barlaz in 1989.84
In what follows, we seek to understand the organic carbon constituents of the key
materials. It is worth starting by highlighting the fact that for most biodegradable
materials, the carbon content of dry matter is relatively constant. This is because of
the nature of the organic molecules which constitute biodegradable materials.
In doing so, we also have in mind the distinction, in MELMod, between different pools
of carbon which are deemed to degrade at different rates. It makes more sense, in
our view, if these rates can be linked to specific constituents of the degradable
wastes. In other words, as in the ORWARE model, it makes sense to consider the
different decay constants applying to the different biochemical constituents.
It should be noted that both cellulose and hemicellulose are deemed to be composed
of the same proportion of carbon. Table A 22 suggests this is not the case and that
for cellulose and hemicellulose, as well as the other biochemical constituents, the
proportion of carbon in the constituent needs to be considered.
83 W. Eleazer et al (1997) Biodegradability of Municipal Solid Waste Components in Laboratory-scale
Landfills, Environmental Science and Technology, 1997, 31, pp.911-917.
84 M. A. Barlaz, R. K. Ham, D. M. J. Schaefer(1989) Journal of Environmental Engineering . Eng.
Div.(Am. Soc. Civ. Eng.) 1989, 115, 1088-1102.
108
Table A 22: Carbon Content of Cell Wall Components
Component Monomer Carbon Content (%)
Lignin (C9H10O3)n a 65.1
Hemicellulose {(C5H8O4)3.(C5H8O4)2.(C5H8O4.C6H8O6)}n b 44.6
Cellulose (C6H12O6)n c 40
Starch (C6H10O5)n 44.4
Sugar (as sucrose) C12H22O11 42.1
Fats Variable formulae 73-79
(76 as mid-point)
Protein (as amino acids) Variable formulae 25-52 (40 as weighted
average of acids)
Fibre 45 (est)
Readily soluble 45 (est)
It should also be noted that the way in which studies report the biochemical fractions
varies. Importantly, it is clear that the single studies reporting „readily soluble‟ and
„fibre‟ are not referring to lignin in either case.
A.3.2.1 Paper and Card
Barlaz (2006) presented the data shown in Table A 23.85 This confirms the very low
lignin content of office paper in comparison to that of newsprint, coated paper and
card.
Table A 23: Chemical Composition of Paper Products (% Dry Weight) - Barlaz
Newsprint Office paper
Corrugated
card
Coated
paper
Wu Eleazer Wu Eleazer Eleazer Eleazer
Cellulose 48.30% 48.50% 64.70% 87.40% 57.30% 42.30%
Hemicellulose 18.10% 9.00% 13.00% 8.40% 9.90% 9.40%
Lignin 22.10% 23.90% 0.93% 2.30% 20.80% 15.00%
Volatile Solids 98.00% 98.50% 88.40% 98.60% 92.20% 74.30%
C:L
[reference?] 3.00 2.41 83.55 41.65 3.23 3.45
Sources: Wu B, Taylor C M, Knappe D R, Nanny M A and Barlaz M A (2001) Factors Controlling
Alkybenzene Sorption to Municipal Solid Waste, Environmental Science and Technology, 35, pp4569-
4576; Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal Solid
Waste Components in Laboratory Scale Landfills, Environmental Science and Technology, 31, pp911-
917
85 Barlaz M A (2006) Forest products decomposition in municipal solid waste landfills, Waste
Management, Issue 26, pp. 321-333
109
The Dutch database of biomass and waste materials, Phyllis, presents more
information with regard to the composition of newspaper, mixed paper and card. This
is shown in Table A 24.
Table A 24: Chemical Composition of Paper Products (% Dry Weight) - Phyllis
Newsprint Mixed paper Corrugated
Card Min Max Min Max
Cellulose 43% 64% 45% 56% 50%
Hemicellulose 16% 33% 13% 16% 14%
Lignin 21% 27% 16% 21% 15%
Notes:
1. Range across 10 records (some were average measurements from a number a samples)
2. Range across 3 records
Source: Phyllis Database for Biomass and Waste http://www.ecn.nl/phyllis/
More recent data presented by Godley et al reported detailed the chemical
constituents of cardboard packaging waste (in dry matter terms) as 2.7% fat, 11.3%
hemi-cellulose, 42.6% cellulose and 34.0% lignin – the only analysis to suggest any
fat might be present in paper products.86 This presumably reflects the content of the
packaging rather than the packaging itself.
MELMod uses figures of 61% and 9% for cellulose and hemicellulose respectively. We
think these are respectable figures, but that there is an argument for differentiating
paper and card in future. Ideally this would take into account the relative proportions
of different paper and card fractions being recycled.
A.3.2.2 Food Waste
Landfill excavation studies and reactor studies such as those carried out by Barlaz
have focused on “forest products” such as paper, card and lignin; in contrast food
waste – a significant component of the UK waste stream - has received relatively little
attention. The focus on paper products and wood has similarly led to a lack of
consideration of the fat and protein content of biodegradable wastes. Thus Eleazer et
al‟s 1997 study only presented data on the cellulose, hemicellulose and lignin of the
waste materials investigated as part of their study, although food waste was
considered (and in this case, some data with regard to protein was investigated). The
suggestion here is that the food waste sample contains very little fat. No data on
moisture content was provided. The data is shown in Table A 25.
86 Godley A, Frederickson J, Lewin K, Smith R and Blakey N (2007) Characterisation of Untreated and
Treated Biodegradable Wastes, Proceedings of the Eleventh International Waste Management and
Landfill Symposium, Caliari, Italy, October 2007
110
Table A 25: Chemical Composition of Food Waste – Eleazer et al
% dry matter
Cellulose 55.4
Hemicellulose 7.2
Lignin 11.4
Volatile solids 93.8
Note: Report states that cellulose, hemi-cellulose, lignin and protein combined make
up 99% of volatile solids.
Source: Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal Solid
Waste Components in Laboratory Scale Landfills, Environmental Science and Technology, 31, pp911-
917
Data on the chemical constituents of food waste is, however, also available from
research considering the AD of the food waste fraction. A study by Davidsson et al on
AD in Sweden analysed the composition of 17 organic waste samples that contained
only food waste – in Sweden garden waste is composted, and so does not form the
part of the feedstock for source separated AD plant. Data from this study is presented
in Table A 26, and includes total solids content as well as information on the chemical
constituents.
Table A 26: Chemical Composition and Moisture Content of Food Waste Samples
Minimum Maximum Median
Total solids (% wet weight) 17% 37% 30%
Volatile solids (% total solids) 81% 92% 87%
Crude fat (% total solids) 10% 18% 15%
Crude protein (% total solids) 10% 18% 16%
Crude fibre (% total solids) 8% 26% 15%
Starch (% total solids) 10% 19% 14%
Sugar (% total solids) 1% 10% 7%
Source: Davidsson A, Gruvberger C, Christensen T, Hansen T and la Cour Jansen J (2007) Methane
Yield in Source-sorted Organic Fraction of Municipal Waste Management, Waste Management 27
pp.406-14
The previously cited Dutch database Phyllis has data on chemical constituents of food
industry waste although no data is provided with respect to the moisture content of
these samples. The 15 samples consider a very heterogeneous mix of materials;
including residues from fruit and vegetable processing as well as fish meal. This data
is presented in Table A 27.
111
Table A 27: Chemical Composition of Food Industry Waste
Minimum Maximum Median
Cellulose (% dry weight) 0% 50% 12%
Hemicellulose (% dry weight) 0% 51% 12%
Lignin (% dry weight) 0% 40% 6%
Lipids (% dry weight) 6% 18% 7%
Protein (% dry weight) 15% 56% 20%
Starch (% dry weight) 17% 70% 40%
Sugar (% dry weight) 1% 15% 8%
Note: Ranges from 15 samples.
Source: Phyllis Database for Biomass and Waste http://www.ecn.nl/phyllis/
MELMod uses, for putrescibles, figures of 26% for cellulose and 13% for
hemicellulose (dry matter).87 This clearly needs revision as it underplays the presence
of other biodegradable elements. For food from MSW, we propose to use the median
figures from Davidsson et al above for the fat, protein, sugar and starch content. The
remainder of the total volatile solids content is assumed to be cellulose,
hemicellulose and lignin. Values for hemicelluloses, cellulose and lignin are used to
make up the total to 90% organic volatile solids, with the apportionment across these
three in line with the work from Eleazer et al. For C&I wastes, we propose to use the
median values from Phyllis. These, however, sum to more than 100% so we have
normalised them to 95% of total solids.
A.3.2.3 Garden Waste
Eleazer et al considered three garden waste components in their 1997 analysis –
branches, leaves and grass. Data from the study is presented in Table A 28.
87 A review of the GasSim model manual indicates that these are figures used in GasSim for garden
waste (in which case, the moisture content – 65% in GasSim - is too high). For „other putrescibles,
GasSim gives more sensible values of 55.4% cellulose and 7.2% hemicellulose, which are the values
from Eleazer et al above, and closer to what might be expected for food waste (though still omitting
fats, proteins, other sugars, etc.). GasSim also suggests that 76% of this would biodegrade (see Golder
Associates (2006) GasSim User Manual). It is, perhaps, also interesting to note that GasSim‟s
predictions for the composition of landfilled waste – as made in 2006 – were, like MELMod, still based
upon outdated figures regarding composition of landfilled waste. Any validation of GasSim must be
seen in this light (i.e. that the modelled gas generation being „validated‟ was likely based upon an
erroneous estimate of the composition of the material being landfilled).
112
Table A 28: Chemical Composition of Garden Waste Components – Eleazer et al
% dry weight
Grass 1 Grass 2 Leaves Branches
Cellulose 26.5% 25.6% 15.3% 35.4%
Hemicellulose 10.2% 14.8% 10.5% 18.4%
Lignin 28.4% 21.6% 43.8% 32.6%
Volatile solids 85.0% 87.8% 90.2% 96.6%
Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal Solid Waste
Components in Laboratory Scale Landfills, Environmental Science and Technology, 31, pp911-917
Data from Phyllis presents further information on the carbon constituents of different
types of grass, although no data on the chemical constituents of common garden
waste components was available from this source. Data presented in Table A 29
suggests that the proportion of protein is variable, depending on the species of grass.
Table A 29: Chemical Composition of Grasses - Phyllis
Verge grass Switch grass
Cellulose (% dry weight) 20-33% 35-45%
Hemicellulose (% dry weight) 0-20% 26-35%
Lignin (% dry weight) 10-26% 26%
Lipids (% dry weight)
Protein (% dry weight) 3-11%
Starch (% dry weight)
Sugar (% dry weight)
Notes: Verge grass appears to refer to general grass at verges; switchgrass (Panicum virgatum) is a
summer perennial grass that is native to North America
Source: Phyllis Database for Biomass and Waste http://www.ecn.nl/phyllis/
Godley et al also produced figures for garden waste, shown in Table A 30.
113
Table A 30: Chemical Composition of Garden Waste (% total solids)
Fat
Readily
soluble
material
Hemicellulose Cellulose Lignin
Residue
after
ashing
Green
Waste 1.5 25.9 16.0 19.8 19.7 17.1
Note: The sources states that: „Biochemical composition was determined (van Soest et al. 1991,
Effland 1977, Richards 2005) using an adaptation of the Gerhardt Ltd. fibrebag system. Dried, ground
samples, with fine material that would pass through the fibrebags removed, underwent sequential
treatment with petroleum ether, neutral detergent solution, acid detergent solution, cold 72%
sulphuric acid and ashing at 600 ºC. The fractions removed by these processes are nominally
identified as fat, soluble material, hemicellulose, cellulose and lignin respectively. These designations
may not be exclusively composed of the described biochemical classes but be mixtures of different
materials with similar sequential extractive properties by the methodology.‟ The source suggests that
soluble fraction is „readily biodegradable‟.
Source: Godley A, Frederickson J, Lewin K, Smith R and Blakey N (2007) Characterisation of Untreated
and Treated Biodegradable Wastes, Proceedings of the Eleventh International Waste Management
and Landfill Symposium, Caliari, Italy, October 2007
MELMod uses, for putrescibles, figures of 26% for cellulose and 13% for
hemicellulose (dry matter). This clearly needs revision as it underplays the presence
of other biodegradable elements. For garden waste from MSW, we propose to use the
figures from Godley et al above.
A.3.2.4 Wood
Data from Phyllis for the carbon constituents of treated wood and bark is presented in
Table A 31.
Table A 31: Chemical Composition of Wood
Treated wood
Untreated wood
(different types of
bark)
Cellulose (% dry weight) 35-48% 0-30%
Hemicellulose (% dry weight) 7-17% 0-34%
Lignin (% dry weight) 22-29% 0-50%
Lipids (% dry weight) [Why are these
blank - Zero?]
Protein (% dry weight)
Starch (% dry weight)
Sugar (% dry weight)
Source: Phyllis Database for Biomass and Waste http://www.ecn.nl/phyllis/
114
For Box-wood, Preece proposed values of 41.4% for cellulose, 14.1% for
hemicellulose and 26.5% for lignin.88 Interestingly, these lie right in the middle of the
above ranges.
We propose to use the mid-point of the Phyllis values for treated wood.
A.3.2.5 Textiles
For textiles, the data is somewhat more scarce. One study gives a figure of 90%
cellulose and 1.6% lignin.89 Other sources similarly suggest cotton has a cellulose
content of around 90%, along with a low lignin content.90 In the case of the finer
fabrics made from natural fibres the lignin is usually removed as part of the textiles
manufacturing process to improve the flexibility of the fabric. Analysis by Godley et al,
on the other hand, suggests much higher lignin values, but the authors noted that
man-made fibres (in the form of a plastic coating) were effectively included in the
lignin analysis. Their data are presented in Table A 32, but the confounding effect of
man-made fibres, and the absence of information on other biochemical components,
makes this data difficult to use, though the BM100 and DR4 figures reveal
information regarding the biodegradability of the materials which suggests a low
propensity to degrade on the part of the materials examined.
Table A 32: Biodegradability of Selected Textile Wastes
Waste
LOI
content
(%DM)
Lignin content
(%DM)
DR4 test
(mg O/kg LOI)
BM100 test
(l/kg LOI)
Wool 95 33.1 17000 21
Cotton 99 2.1 13000 26
Mean (mixed textiles) 97 17.6 15000 23.5
Notes
The lignin content includes manmade fibres within the lignin analysis
Source: Godley A and Frederickson J (2010) Supporting Agency MBT Model Development, Report for
the Environment Agency, May 2010
No detailed composition analysis exists with regard to the exact proportions of
natural, synthetic and mixed fibre textiles present in the waste stream and
biochemical data is only available for very few of the natural fabrics. We therefore
propose to retain the existing MELMod assumptions with regard to the carbon
88 Preece, I..A. (1931) Studies on hemicelluloses. IV. The proximate analysis of box-wood and the
nature of its furfuraldehyde-yeilding constituents. Biochemical Journal 25(4) 1304-1318
89 C. Johnson and F. Worrall (2006) Modelling the fate of carbon from MSW during incineration,
landfill, aerobic digestion and application of CLO to land, Report from the University of Durham, 28th
April 2006.
90 Kim H (u.d.) Cellulose Synthase Catalytic Subunit (Cesa) Genes Associated with Primary or
Secondary Wall Biosythesis in Developing Cotton Fibres, University of New Orleans
115
constituents. Further discussion with regard to this waste fraction is provided in
Section 6.1. As with moisture content, it should be noted that this figure is also
applied to footwear because the two are often reported together in composition
studies.
A.3.2.6 Nappies
In the ORWARE model, 21% of the dry matter in nappies is believed to be carbon in
the form of cellulose. This equates to a value of around 47% of dry matter as
cellulose. This is only just internally consistent with the composition of nappies
highlighted above. It is assumed, here, that this effectively includes the faeces.
We propose to use this value (47% cellulose) for nappies.
A.3.2.7 Furniture
As for moisture, furniture is treated as a composite in our proposed model (see
Section A.3.1.7 above).
A.3.2.8 Mattresses
As for moisture, mattresses are treated as a composite in our proposed model (see
Section A.3.1.8 above).
116
A.4.0 Evidence Regarding the Extent of
Degradation of Carbon in Landfills In order to make recommendations regarding the modelling of the proportion of
organic carbon that degrades in landfill, a review of the available evidence was
undertaken. The evidence that is presented in this Appendix takes the following
forms:
The anaerobic degradation potential of organic substances, investigated
through:
Laboratory scale landfill reactors;
The degradation that occurs in an anaerobic digester.
Field studies at the landfill involving the excavation of decomposed refuse;
Research calibrating the output from theoretical models that consider landfill
gas generation with field measurements of generation taken at the landfill.
The focus throughout is on the differential behaviour of the different constituent
carbon fractions – cellulose, hemicellulose, lignin, fats and proteins.
There are ranges of values in the literature for the proportion of organic carbon which
is likely to degrade in landfills. Single-phase models effectively make use of one value
for all materials. Some multi-phase models do also (such as the IPCC model).
However, MELMod has functionality at the material specific level, and policy makers
are known to want to understand the effect of addressing specific materials through
waste policy measures. A single value, therefore, does not seem appropriate given
that different materials clearly behave differently.
The figures in MELMod for the dissimilable fraction of degradable organic carbon (or
DDOC) seem to display some internal consistencies. By way of example, the DDOC
figures in MELMod are 98% for commercial and industrial paper and card, but 62%
for municipal paper and card. For mixed commercial waste, the degradable fraction is
85%, but there is no single fraction of the municipal stream (not even the
putrescibles) for which the degradation comes close to this figure. There is a general
lack of consistency across the figures for commercial waste and for municipal waste,
even though the majority of wastes landfilled fall into general categories which cannot
be properly characterised.
In MELMod, the proportion of organic carbon that is considered dissimilable varies
across the different waste fractions. Other models have however applied a DOCf or
DOCm factor to the total organic carbon content of MSW as a whole, to reflect the fact
that the anaerobic degradation process is typically not completed within the
heterogeneous environment of an actual landfill – effectively implying the permanent
sequestration of some of the organic carbon content in the long term.
For each component waste stream / material, in MELMod:
A moisture content is given for the waste (M);
117
A decomposition factor (by dry weight) is specified for the waste (F)
The proportion (by dry weight) that is cellulose is given (C);
The proportion (by dry weight) that is hemicellulose is given (H);
The proportion of the mass of cellulose / hemicellulose that is carbon is given
(Carb)
The equation used to calculate DDOC is then:
DDOC = (1-M) * F * (C + H) * (Carb)
For food waste the values given are:91
M = 65% this is slightly too low (see above)
F = 62% we think this is likely to be low for highly putrescible
materials
C = 25.7%, H = 13% these imply 38.7% of the dry weight is potentially
degradable. This is too low
Carb = 0.444 this is correct.
The important factors, then, are F, C and H. Taken together, these imply that for every
dry tonne of food waste, only
62% * 38.7% = 24%
will degrade in landfill.
Since virtually all food waste consists of some organic matter, the implications would
be that landfills act as significant sequesters of carbon for the future. For every wet
tonne of food waste, the figures imply that only 8.4% is degraded, or that 3.7% is
carbon which is degraded.
Further inspection of the model highlights additional anomalies. In Table A 33 below,
we have calculated the proportion of dry matter of each of the waste streams with
biodegradable content which is assumed to degrade in the landfill, expressed both in
terms of carbon, and in terms of total material degraded. For ease of viewing, we
have ranked these in descending order.
The following comments seem relevant:
94% of paper and card from commercial and industrial waste is assumed to
degrade. This runs counter to much of the experimental logic which suggests that
of the biodegradable materials, paper and card is likely to be sequestered to
some degree in landfills (see later in this Appendix);
91 This is outlined in Land Quality Management (2003) Methane Emissions from Landfill Sites in the
UK, Report for Defra, January 2003.
118
Table A 33: Quantity of Carbon and Total Dry Matter Degraded, Dry Matter Basis
Sourc
e
Carbon degraded
(% d.m.)
Total Material
degraded (% d.m.)
C&I Paper and card 41.68% 93.88%
C&I General commercial 31.70% 71.40%
C&I General industrial waste 31.70% 71.40%
C&I Food solids 21.12% 47.58%
C&I Food effluent 21.12% 47.58%
C&I Abattoir waste 21.12% 47.58%
M Paper and card 19.29% 43.45%
M Misc. comb. (+ non-inert fines from „95) 11.10% 25.00%
C&I Other waste 11.10% 25.00%
M Non-inert fines 11.10% 25.00%
M Putrescible 10.65% 23.99%
C&I Sewage sludge 9.32% 21.00%
M Textiles 8.88% 20.00%
C&I Misc processes 4.44% 10.00%
C&I Construction/demolition 4.30% 9.69%
M Composted Putrescibles 0.35% 0.80%
The difference in modelled behaviour of paper and card from commercial and
industrial waste, and paper and card from municipal waste (94% degraded v 44%
degraded) is difficult to rationalise;
Similar comments might be made concerning the difference between the
modelled behaviour of food solids from the C&I stream, and putrescibles from the
MSW stream (48% v 24%). Explaining these differences is far from straightforward
(not least given the invariant nature of the 48% figure for C&I sourced material
across a range of categories, making the 24% figure for MSW putrescibles seem
inconsistent with the other materials);
The suggestion that mixed commercial waste and mixed industrial waste will
degrade to the tune of 71.4% is difficult to believe when set alongside, for
example, the low figures for food waste, and the fact that mixed commercial and
industrial wastes will include substantial quantities of non-biodegradable material.
These will feature disproportionately strongly in dry matter terms (because the
non-biodegradable materials generally have lower moisture content than the
biodegradable ones). It is, indeed, questionable whether commercial and
industrial waste actually contains 71.4% of biodegradable material at all in dry
matter terms. Even if it did, it would be inconsistent with the degradation levels
posited for individual (this proportion of organic matter degrading would need to
be close to 100% to make this physically possible, whilst the individual
components of the mixed waste are characterised by much lower degradation
rates);
119
Also worthy of note is the fact that C&D waste –much of which will have been inert
in the mid 1990s and before - is reckoned to be, by implication, half as
degradable as MSW „putrescibles‟. Also, textiles in municipal waste are assumed
to be degraded to an almost equal extent to putrescibles in MSW, even though it
is believed that a significant proportion of textiles are not biodegradable.
A.4.1 Dissimilation Factors for MSW from the Literature
Table A 34 presents factors cited in the literature and shows that a range of values
for MSW from 0.5 to 0.8 have been used. Most are applied to the total carbon
content of the waste stream. However the factor recommended by the IPCC varies
depending on whether lignin is included within the total organic carbon content.
The factor of 0.58 suggested by Coops and Oonk has been validated against
measurements of landfill gas extraction. This outlined in more detail in Section A.6.0,
which also discusses attempts by others to assess the validity of this dissimilation
factor through a calibration of model outputs against field measurements.
Table A 34: Dissimilable Carbon Factors for MSW Cited in the Literature
Source Dissimilable carbon factor
Technical Research Centre of Finland (2001)1 0.5
Coops, Oonk et al (1995) 0.58
Afvalzorg (2006) 0.7 – 0.8 (for non-inert waste)
IPCC (2006)2 0.77 (lignin excluded)
0.5 – 0.6 including lignin
Notes
1. Finland also uses a methane correction factor of 0.7 (relates to non-anaerobic conditions)
2. The value of 0.77 was retained from initial guidance developed in 1995, the original objective
of which had been to estimate CH4 emissions from landfills in developing countries. The value
was subsequently adopted by the IPPC without revision following the acceptance of the Kyoto
Protocol (by which time emissions targets had been negotiated).In developing the revised
guidelines in 1999, the authors were explicitly advised by the IPCC not the change the defaults
and thus developed the above factors in order to fit with this stipulation.
Sources: IPCC (2006) 2006 Guidelines for National Greenhouse Gas Inventories: Volume 5, Waste;
Technical Research Centre of Finland (2001) Greenhouse Gas Emissions and Removals in Finland,
Espoo; Coops O, Lunin L, Oonk H and Weenk A (1995) Validation of Landfill Gas Formation Models, in
Proceedings Sardinia 95, Fifth International Landfill Symposium, Cagliari, Italy, October 2-6, pp635-
646; Scharff H and Jacobs J (2006) Applying Guidance for Methane Emission Estimation for Landfills,
Waste Management, 26, pp417-429
120
A.4.2 Maximum Degradation under Anaerobic Conditions
A.4.2.1 Laboratory Studies in Landfill Reactors
Eleazer et al (1997) measured the biodegradability of the major components of MSW
in laboratory-scale (2-L) reactors that were operated to maximise anaerobic
decomposition.92 The study considered a range of paper products as well as selected
plant materials and food waste. Degradation was related to the cellulose,
hemicellulose and lignin content of the materials, and ratios of these three
components both before, and after decomposition were measured (degradation
ratios calculated by dividing the mass of each component recovered from the reactor
by the initial mass) – effectively calculating the proportion of each element
Data from the study are shown in Table A 35. For most materials considered within
the study lignin has a higher degradation ratio, indicating its resistance to anaerobic
decomposition, although the extent of degradation varies – the range of ratios 0.78
to 1.03. This suggests a maximum of 20% of the lignin will degrade under anaerobic
conditions for food and grass.
These ratios were much higher for paper and woody materials – suggesting that here
only 1-5% of the lignin was lost. Although cellulose and hemicellulose were less
resistant to degradation, ratios varied from 0.02 to 0.68 across the different waste
materials, suggesting that between 32-98% of the cellulosic materials decomposed.
The study discussed relationship between the extent of lignification and the
degradation of cellulose. The relationship between these two types of molecule and
their relative degradation is outlined in more detail in Section A.4.4 with reference to
the evidence from landfill excavation studies.
A similar study performed by Chugh et al (1999) performed research to demonstrate
the biodegradation of shredded MSW in a two-stage anaerobic digester operated with
leachate recirculation.93 The study reported volatile solids losses of 55 to 69% for
MSW subjected to two months of anaerobic digestion - on average, measured
methane yields in the reactor system were 75% of the ultimate methane yields as
measured by BMP tests.
92 Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal Solid Waste
Components in Laboratory Scale Landfills, Environmental Science and Technology, 31, pp911-917
93 Chugh, S, Chynoweth, D.P., Clarke, W., Pullammanappallil, P. and V. Rudolph (1999) Degradation of
unsorted municipal solid waste by a leach bed process, Bioresource Technology, 69, pp103-115
121
Table A 35: Methane Yield and Initial and Final Solids Composition Data
Yield CH4
(mL per
dry g)
Composition % dry weight
Cellulose
start:end
Hemi-
cellulose
start:end
Lignin
start:end
Extent of
decom-
position
(%)
CHL:VS
Cellulose Hemi
cellulose Lignin VS
Seed (control) 25.5 23.4 4.7 22.5 48.2 0.18 0.36 0.83 21.8 1.05
Seed 2 (control) 5.8 18.3 3.7 22.1 42.4 0.34 0.69 0.85 6.3 1.05
Grass 144.8 26.5 10.2 28.4 85.0 0.19 0.42 0.78 94.3 0.77
Grass 2 127.6 26.6 14.8 21.6 87.8 Not measured 0.7 - - -
Leaves 30.6 15.3 10.5 43.8 90.2 0.43 0.68 0.90 28.3 0.77
Branch 62.6 35.4 18.4 32.6 96.6 0.52 0.59 0.93 27.8 0.89
Food 300.7 55.4 7.2 11.4 93.8 0.24 0.58 0.80 84.1 0.99
Coated paper 84.4 42.3 9.4 15.0 74.3 0.54 0.58 1.03 39.2 0.90
Old newsprint 74.3 48.5 9.0 23.9 98.5 0.73 0.46 0.99 31.1 0.83
Corrugated card 152.3 57.3 9.9 20.8 98.2 0.36 0.38 0.93 54.4 0.90
Office paper 217.3 87.4 8.4 2.3 98.6 0.02 0.09 0.95 54.6 0.99
MSW 92.0 28.8 9.0 23.1 75.2 0.25 0.22 0.95 58.4 0.81
Notes
1. Average data presented
2. Protein is included along with the CHL in the ratio CHL:VS for food waste
3. Degradation ratios calculated by dividing the mass (of each component) recovered from the reactor by the initial mass
4. The extent of decomposition is the measured methane yield divided by the yield calculated assuming conversion of 100% of the cellulose and
hemicellulose (and protein in the case of food waste) to methane and carbon dioxide.
Source: Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal Solid Waste Components in Laboratory Scale Landfills,
Environmental Science and Technology, 31, pp911-917
122
In a review of the evidence taken from laboratory studies, Barlaz indicated that the
BMP data suggested about 70 to 75% of the degradable solids could be degraded in
a reactor system.94 This was also suggested through studies undertaken by Barlaz,
Ham, and Schaefer (1989) and Barlaz, Schaefer, and Ham (1989) in which 71 and
77% of the cellulose and hemicellulose, respectively, added to a reactor system in the
form of shredded MSW was degraded.
A.4.2.2 Evidence from Studies Focusing on Anaerobic Digestion
Davidsson et al (2006) studied the anaerobic digestion of 17 food waste samples
and found that on average 80% of the total volatile solids content was degraded after
a 15 day period in the digester. 95 These results are not inconsistent with those
suggested by Eleazer et al in the study discussed above, as the latter study
considered digestion over a longer period of time (and therefore suggested 84% of
the total volatile solids would be decomposed). Composition analysis presented by
Davidsson et al indicated that the crude fibre content was between 8-26% of the total
volatile solids content of the food waste samples. These results again suggest that a
significant proportion of the lignin based material is not affected by anaerobic
decomposition but that much of the rest of the volatile solids are degraded under
such conditions.
A.4.2.3 Theoretical and Measured Biological Methane Potential
Research indicates that the relationship between theoretical and measured biological
methane potential (BMP) is not straightforward. Theoretical values can be calculated
either from the element composition (C H O) or the component composition (fats,
proteins etc). These theoretical values are usually found to be higher than those
found through the measured methane potential using laboratory batch tests -
Davidsson et al found on average, measured potentials achieved in these tests
represented 74% of the theoretical value based on element composition and 87% of
the theoretical value, based on component composition calculated by Buswell‟s
formula.96 This difference is likely to reflect, in part, the amount of material used by
the micro-organisms involved within the degradation process.
However Barlaz noted that the ratio of the measured BMP to the theoretical BMP
showed considerable variability.97 It was therefore suggested that variability in the
ratio between measured and theoretical BMP together with the variable nature of
94 Barlaz M A (2004) Critical Review of Forest Products Decomposition in Municipal Solid Waste
Landfills, National Council for Air and Stream Improvement, Bulletin 872
95 Davidsson A, Gruvberger C, Christensen T H, Hansen T L and la Cour Jansen J (2007) Methane Yield
in Source-Sorted Organic Fraction of Municipal Solid Waste, Waste Management, 27, pp406-414
96 This is a formula used to predict the yield of component products from anaerobic digestion based
upon the chemical composition of the degrading material.
97 Barlaz M A (2004) Critical Review of Forest Products Decomposition in Municipal Solid Waste
Landfills, National Council for Air and Stream Improvement, Bulletin 872
123
cellulose decomposition made it difficult to formulate the theoretical maximum
degradation potential of cellulose.
A.4.3 The Influence of Landfill Conditions on Degradation
Environmental conditions influence the extent of degradation occurring in the landfill.
The factors that have most consistently been shown to affect the rate of refuse
decomposition are the moisture content and pH.97 It is generally accepted that refuse
buried in arid climates decomposes more slowly than refuse buried in regions that
receive greater than 20 to 40 inches of annual infiltration into the waste.
The way in which the landfill is managed – with respect to the covering of cells, for
example – also has an important influence on the extent of degradation. This is
discussed further in the next section.
A.4.4 Evidence from Landfill Excavation
In addition to the evidence from the laboratory studies presented above, some
evidence of the differential behaviour of the constituent carbon fractions is available
from field studies undertaken at landfill sites. However the focus of these studies is
largely on paper and wood – the so-called “forest products”.
Much of the work of this nature has been carried out by researchers working with
Barlaz, who has also produced several reviews of the evidence gained through this
type of research.98 These reviews justify the focus on paper and wood products
through citation of data from the US EPA that suggest very high quantities of paper
products within the landfilled waste stream in the US during the late 1990s. This data
suggests the food waste constituted only around 10% for landfilled waste as a whole
when commercial and industrial waste is considered alongside the municipal. The
data further suggests that wood content of the total waste stream is relatively high -
as much as 20% of construction and demolition waste is assumed to be wood.
As a result, landfill excavation studies only consider the relative degradation of
cellulose and lignin. No data is available for the relative decomposition of fats and
proteins from field studies undertaken at landfill sites. This is disappointing since it
seems clear from the review of activity data that food waste is a far more significant
component of landfilled waste in the UK than paper and card.99
A.4.4.1 Cellulose
Evidence taken from landfill field studies considers the degradation of cellulose and
hemi-cellulose relative to that of lignin through an analysis of cellulose to lignin ratios
(C:L) or cellulose + hemi-cellulose ratios (CH:L). These ratios are used to minimise the
98 Barlaz M A (2004) Critical Review of Forest Products Decomposition in Municipal Solid Waste
Landfills, National Council for Air and Stream Improvement, Bulletin 872; Barlaz M A (2006) Forest
products decomposition in municipal solid waste landfills. Waste Management, Issue 26, pp. 321-333
99 The situation in the UK appears to be very different indeed. The current situation suggests that as
much food waste is landfilled as the combined total of wood, paper and card.
124
effect of soil dilution from the daily cover of the landfill that would otherwise
contaminate the samples.
Recent reviews of the evidence produced by Barlaz confirm that there has been a
wide range of studies on the degradability of refuse buried in landfills beginning with
the work of Ham and Bookter in 1982 and concluding with the work of Gardner et al
in 2003.100 These studies are generally consistent in demonstrating that CH:L ratios
can go as low as at least 0.2, and in the case of Wang, Byrd, and Barlaz (1994), as
low as 0.02.
Barlaz notes that many of the older studies overestimated the amount of cellulose
present because they relied upon gravimetric analysis. This tends to lead to an
overstatement of the amount of cellulose since non-cellulosic material is included as
cellulose. This overestimation is more likely to occur in the samples that are the most
decomposed, as the concentration of non-cellulosic recalcitrant material will increase
relative to the cellulose concentration in well decomposed samples. In contrast, the
study by Wang et al used High Pressure Liquid Chromatography (HPLC) which ensures
a more accurate reporting of the cellulose content and also allows for the reporting of
the hemicellulose content. This is suggested by Barlaz as a possible reason for the
very low CH:L ratios indicated by that study in comparison to others.
The values presented above likely represent the maximum extent of degradation. The
older more decomposed samples such as those excavated in Wang et al‟s study were
approximately 20 years old; however, none of the samples taken from the US studies
were more than 30 years old. All represent the conditions in sanitary landfills, in
which waste was covered with soil to discourage vermin rather than with a liner, likely
to keep waste drier and inhibit decomposition.
In presenting these results, Barlaz makes little comment with regard to the
substantial changes in landfill management that occurred in the period leading up to,
and beyond the sampling studies from which these results are presented. The studies
were carried out in the US in the 1990s. Evidence such as that presented above led
to the basis for the 30 year rule in the US – the idea that most of the decomposition
will have occurred during this period, and that landfills would not pose an
100 Ham R K and Bookter T J (1982) Decomposition of Solid Waste in Test Lysimeters, Journal of
Environmental Engineering, 108, pp1147-1170; Jones K L and Grainger J M (1983) Methane
Generation and Microbial Activity in a Domestic Refuse Landfill Site, European Journal Applied
Microbiological Biotechnology, 18, pp242-245; Fawcett, J D and Ham R K (1986) Refuse analysis data
and evaluation for the Mountain View controlled landfill project, Department of Civil and Environmental
Engineering, The University of Wisconsin – Madison; Ham R K, Norman M R and Fritschel P R (1993)
Chemical Characteristics of Fresh Kills Landfill Refuse and Extracts, Journal of Environmental
Engineering, 119, pp176-1195; Suflita J M, Gerba CP, Ham R K, Palmisano A C, Rathje W L and
Robinson J A (1992) The World‟s Largest Landfill: A Multi-disciplinary Investigation, Environmental
Science and Technology, 29, pp2305-2310; Wang Y S, Byrd C S and Barlaz M A (1994) Anaerobic
Biodegradability of Cellulose and Hemi-cellulose in Excavated Refuse Samples, Journal of Industrial
Microbiology, 13, pp147-153; Gardner W D, Ximenes F, Cowie A, Marchant JF, Mann S and Dods K
(2003) Decomposition of Wood Products in the Lucas Heights Landfill Facility: Internal Report,
Research and Development Division, State Forests of New South Wales
125
environmental problem after this time.101 Liners and dry entombment followed in the
US in the early 1990s – along with leachate recirculation (introduced to maximise gas
production), which would be expected to increase the extent of degradation by
ensuring that moisture did not become a limiting factor. However landfill cells are not
permanently covered whilst the landfill is operating – during periods of fill,
decomposition might be expected to occur in a similar way to that seen in the sanitary
landfills described above. Table A 36 therefore presents cellulose lignin ratios of
samples that are less than 10 years old. The majority of samples were taken from
landfills where no leachate circulation was taking place.
Table A 36: Cellulose Lignin Ratios for Samples Less than 10 Years Old
Source Location Approx age
years C:L Comments
Bookter and Ham
(1982)
Wisconsin
6 1.43 Shredded test samples in 4
ft deep cells – cold weather
limited 9 0.57
Los Angeles 2-10 0.6 Moisture limited
New York 2-4 0.87
Fawcett and Ham
(1986)
4 1.2 Higher value - leachate
recirculation. Test cells 50
ft deep 4 1.9
Ham, Norman,
Fritschel (1993) New York 0-5
0.2-3
(median 1.5)
Low gas production
measured
Sources: Ham R K and Bookter T J (1982) Decomposition of Solid Waste in Test Lysimeters, Journal of
Environmental Engineering, 108, pp1147-1170; Fawcett, J D and Ham R K (1986) Refuse analysis
data and evaluation for the Mountain View controlled landfill project, Department of Civil and
Environmental Engineering, The University of Wisconsin – Madison; Ham R K, Norman M R and
Fritschel P R (1993) Chemical Characteristics of Fresh Kills Landfill Refuse and Extracts, Journal of
Environmental Engineering, 119, pp176-1195
What do these ratios imply for the degradation of cellulose, hemi-cellulose and lignin
considered separately? Table A 37 shows CH:L ratios of refuse taken from Barlaz‟s
2006 review. Measurements of cellulose and hemi-cellulose content in these
samples were taken using HPLC. The table also shows indicative ratios for three
scenarios developed on the basis of the maximum degradation evidence presented in
Section A.4.2 - one where 70% of the cellulose and hemicellulose is degraded; one
where 90% of cellulose and hemicellulose is decomposed, and a further scenario
where 50% of the cellulose is degraded but hemicellulose is not considered. In all
cases 5% of the lignin is also assumed to be degraded. The scenarios are developed
in line with the evidence from the landfill excavation studies described above, and, in
the case of the lignin degradation, taking into consideration the lignin degradation
figures presented in Section A.4.2.1). The scenarios indicate the following:
101 Centre for a Competitive Waste Industry (2004) Day of Reckoning: Protecting California Tax-Payers
from the Looming Landfill Crisis: Report to the Grassroots Recycling Network, September 2004
126
1. The median CH:L ratio with 70% degradation of cellulose and hemi-cellulose is
1.10 (with a range of 0.51 – 1.42);
2. The median CH:L ratio with 90% degradation of cellulose and hemi-cellulose is
0.37 (with a range of 0.17 – 0.47);
3. The median C:L ratio with 50% degradation of cellulose is 1.40 (with a range of
0.70 – 2.40).
The first of these two scenarios is suggested as representative of the maximum
degradation that might be expected. The third is presented as representative of the
extent of degradation that might be expected to occur during the pre-cover period.
Table A 37: CH:L and C:L Ratios of Refuse and Indicative Ratios Post Degradation
Barlaz et
al Eleazer
Rhew and
Barlaz Ress et al Barlaz Price et al Barlaz
1989 1997 1995 1998 unpublished 2003 unpublished
Cellulose 51.2 28.8 38.5 48.2 36.7 43.9 54.3
Hemi-
cellulose 8.7 10.6 6.7 10.0 10.8 5.8
Lignin 15.2 23.1 28.0 14.5 13.6 25.1 12.1
CH:L
of refuse
at start
4.2 1.6 1.7 4.1 3.2 2.2 5.4
CH:L with
70% loss
of C & H1 1.24 0.54 0.51 1.27 1.10 0.63 1.42
CH:L with
90% loss
of C & H1 0.41 0.18 0.17 0.42 0.37 0.21 0.47
C:L of
refuse at
start 3.4 1.2 1.4 3.3 2.7 1.7 4.5
C:L with
50% loss
of C 1.8 0.7 0.7 1.7 1.4 0.9 2.4
Note: 5% of the lignin is also assumed to be degraded in each case
Sources: Barlaz M A, Ham R K and Schaefer D M (1989) Mass balance analysis of decomposed refuse
in laboratory scale lysimeter, Journal of Environmental Engineering, ASCE, 11,5 pp1088-1102; Rhew
R and M A Barlaz (1995) The effect of lime stabilized sludge as a cover material on anaerobic refuse
decomposition, Journal of Environmental Engineering, ASCE, 121, pp499- 506; Ress B B, Calvert P P,
Pettigre, C A and Barlaz M A (1998) Testing anaerobic biodegradability of polymers in a laboratory-
scale simulated landfill, Environmental Science & Technology, 32, pp821-827; Price G A, Barlaz M A,
Hater G R, (2003) Nitrogen management in bioreactor landfills. Waste Management, 23, pp675–688
127
A.4.4.2 Lignin
Plant cell wall material is composed of three important constituents: cellulose, lignin,
and hemicellulose. Lignin is particularly difficult to biodegrade, and its presence is
known to further reduce the bioavailability of the other cell wall constituents.
Lignin is both a physical and chemical barrier to microbial attack.102 The molecule is a
complex polymer of phenylpropane units, which are cross-linked to each other with a
variety of different chemical bonds. The presence of lignin reduces the surface area
available to enzymatic penetration and activity, restricting the extent to which the
other cell wall components can be decomposed.
Research carried out at Cornell University has sought to understand the nature of the
bioavailability of lignin in aerobic and anaerobic systems and subsequent impact on
cellulose and hemicellulose, and subsequently postulated mathematical relationships
that considered the effect of lignin on biodegradability in anaerobic systems.
Chandler et al (1980) developed a linear relationship for bioavailability of a substance
in anaerobic systems based on its lignin content.103 Whilst, however, this relationship
was found to make mechanistic sense for materials that had a relatively low lignin
concentration, the model was found to be less good for molecules that had a large
amount of lignin present. In this case, some of the lignin was overlapping other lignin
molecules rather than cellulose, reducing the incremental effect.104 Subsequent
analysis of extensive databases on the maximum digestibility of lignocellulosic
materials in the rumen led to the development of a log-linear relationship which was
found to provide a better fit. An alternative means to calculate the biodegradable
carbon available was therefore proposed by Van Soest:105
10010541.01
100
%76.0
%
%
deg
CellWallCLignin
CellWallCC totalCellWalltotalradablebio
where
Cbiodegradable = Total amount of biodegradable carbon under anaerobic
conditions
102 Colberg, P.J., 1988. Anaerobic microbial degradation of cellulose, lignin, oligolignols, and
monoaromatic lignin derivatives. In Biology of anaerobic microorganisms, ed. A. J. B. Zehnder, 333-
372. New York: Wiley-Liss Dehority, B. A. and R. R. Johnson. 1961. Effect of particle size upon the in
vitro cellulose; digestibility of forages by rumen bacteria. Journal of Dairy Science, V (44):2242-2249.
Tong, X, L. H. Smith, and P. L. McCarty. 1990. Methane fermentation of selected lignocellulosic
materials. Biomass, 21:239-255. Pfeffer, J. T. and K. A. Khan. 1976. Microbial production of methane
from municipal refuse. Biotechnology and Bioengineering, 18:1179-1191
103 Chandler, J.A., W.J. Jewell, J.M. Gossett, P.J. Van Soest, and J.B. Robertson. 1980. Predicting
methane fermentation biodegradability. Biotechnology and Bioengineering Symposium No. 10, pp. 93-
107
104 Conrad, H.R., W.P. Weiss, W.O. Odwongo, and W.L. Shockey. 1984. Estimating net energy of
lactation from components of cell solubles and cell walls. J. Dairy Sci. 67:427-436.
105 Van Soest, P.J. 1994. The Nutritional Ecology of the Ruminant, 2nd edition. Cornell University
Press.
128
Ctotal = Total amount of biodegradable carbon under aerobic condition
Lignin%CellWall = Lignin as % of cell wall components
CellWall% = Sum of Carbon from Lignin and Holocellulose106 as percentage of
Ctotal
Evidence for the reduced bioavailability of cellulose and hemicellulose as a result of
the presence of lignin is available from a number of studies.107 However some
analysis suggests this relationship is far from straightforward. The previously cited
work by Eleazer et al (see Section A.4.2.1) found that the degree of lignification of a
particular component was not a good predictor of the extent of biodegradation. Whilst
the relationship was relatively strong for the paper products it was found that grass -
which is also highly lignified - underwent nearly complete decomposition in the
reactor. The authors noted:108
…. “Apparently, the lignin in grass is not as restrictive to microorganisms as
the lignin in other components such as branches. This result is consistent with
a report by Akin et al. (1995) who stated that “The chemistry of grass
lignocellulose varies considerably from that of wood.””
The differential behaviour of the lignin in grass has been highlighted in other
studies.109 A curvilinear relationship was shown to relate increasing lignin
concentrations to a decrease in the digestibility of cellulose in eight species of grass
(Jung and Vogel 1986).110
Wood products are highly lignified and as such, some studies have suggested very
little anaerobic degradation occurs in a landfill. Recent research by Gardner et al
(2009) suggested that no significant loss of dry mass could be measured in wood
products buried for 19 and 29 years. Where refuse had been buried for 46 years, the
measured loss of carbon (as a percentage of dry biomass) was 8.7% for hardwoods
and 9.1% for softwoods. The authors calculated that this mass loss equated to a loss
106 Barlaz notes that Van Soest fibre determination method suffers from the same shortcomings as the
gravitimetric methods previously cited.
107 Wang Y S, Byrd C S and Barlaz M A (1994) Anaerobic Biodegradability of Cellulose and Hemi-
cellulose in Excavated Refuse Samples, Journal of Industrial Microbiology, 13, pp147-153; Baldwin,
T.D., Stinson, J., and R. K. Ham. 1998. Decomposition of specific materials buried within sanitary
landfills. Journal of Environmental Engineering, 124 (12):1193-1202; Eleazer W E, Odle W S, Wang Y S
and Barlaz M A (1997) Biodegradability of Municipal Solid Waste Components in Laboratory Scale
Landfills, Environmental Science and Technology, 31, pp911-917
108 Eleazer W E, Odle W S, Wang Y S and Barlaz M A (1997) Biodegradability of Municipal Solid Waste
Components in Laboratory Scale Landfills, Environmental Science and Technology, 31, pp911-917
109 Dehority, B. A. and R. R. Johnson. 1961. Effect of particle size upon the in vitro cellulose;
digestibility of forages by rumen bacteria. Journal of Dairy Science, V (44):2242-2249. Tong, X, L. H.
Smith, and P. L. McCarty. 1990. Methane fermentation of selected lignocellulosic materials. Biomass,
21:239-255.
110 Jung, H. G. and K. P. Vogel. 1986. Influence of lignin in digestibility of forage cell wall material.
Journal of Animal Science, 62:1703-1712.
129
of 18% and 17% of their original carbon content, respectively. They further suggested
that these results indicated that the published decomposition factors based on
laboratory research – such as that presented by Eleazer et al (in Section A.4.2.1) -
significantly overestimated the decomposition of wood products in an actual landfill.
The output from this analysis led the authors to consider a maximum DOCf for wood
products of 0.3 if lignin is not considered to be „„degradable”, or a DOCf of 0.18 if
lignin is considered to be „„degradable”.
However, in a previous review of the earlier research published by Gardner et al,
Barlaz noted that their analysis did not cross-reference the decay of the wood in the
landfill with that of any non-wood products and thus provided no indication of what
conditions in the landfill were like. In addition, Barlaz‟s review indicated that the
ultimate extent of decomposition of carbon or mass could not be quantified from the
available data obtained from the study.
A.4.5 Landfill Model Calibration Studies
There have been a number of attempts to reconcile the outputs predicted by landfill
gas generation models with the amount of methane emitted at landfill sites.111 One
such study of gas generation at a number of landfills in Canada attempted to
benchmark the performance of a series of models using two different dissimilation
factors.112 Gas generation measurements taken at the landfills were compared with
that predicted using the following models:
EPER Zero Order Model;
TNO;
The Belgian model;
Scholl Canyon;
LandGEM v2.01.
Of these, the zero order EPER model considers the rate of CH4 production
independently of the amount of substrate remaining or of the biogases already
111 These include: Oonk H and Boom T (1995) Landfill Gas Formation, Recovery and Emission, TNO-
rapport 95-203, Oonk H, Weenk A, Coops O and Luning L (1994) Validation of Landfill Gas Formation
Models, Dutch Organisation for Applied Scientific Research, Report no 94-315; Ehrig H and
Scheelhaase T (1999) Abschätzung der Restemissionen von Deponien in der Betriebs und
Nachsorgephase auf der Basis realer Überwachungsdaten, Bergische Universität – Gesamthochschule
Wuppertal, Germany; Fellner J., Schöngrunder P., Brunner P.H. (2003): Methanemissionen aus
Deponien, Bewertung von Messdaten (METHMES), Technische Universität Wien, Austria; Fredenslund
A.M., Kjeldsen P., Scheutz C., Lemming G. (2007) BIOCOVER – Reduction of Greenhouse Gas
Emissions from Landfills by Use of Engineered Bio Covers Eco Tech 2007, 6th International
Conference on Technologies for Waste and Wastewater Treatment, Energy from Waste, Remediation
of Contaminated Sites, Emissions Related to Climate, Kalmar; Scharff H and Jacobs J (2006) Applying
Guidance for Methane Emission Estimation for Landfills, Waste Management, 26, pp417-429
112 Thompson S, Sawyer J, Bonam R and Valdivia JE (2009) Building a better methane generation
model: Validation models with methane recovery rates from 35 Canadian landfills. Waste
Management, Issue 29, pp. 2085-2091
130
produced, through a consideration of only the waste input from the previous year. The
remaining models all consider waste decay using a first order kinetic equation in a
similar way to that of MELMod.
The study considered 35 out of a total of 52 Canadian landfills, with modelled decay
rates linked to the precipitation rate in each case. Gas collection efficiency was
assumed to be 80%, as all landfills were assumed to be covered with a final clay
cover (this value was taken as it is the mid point between the default 75% recovery
rate assumed by the US EPA, and the 85% recovery rate adopted by the French
Environment Agency following the work of Spokas et al, 2006).
The authors suggested that all the models performed better when a DOCf of 0.5 was
used as opposed to the higher factor of 0.77, and that the Belgium, LandGem v2.01
and the Scholl Canyon models provided the closest estimates in terms of correlation
with total generated in Canadian landfills. The TNO model was found to overestimate
gas generation. A more recent review of the evidence presented in the Canadian
study suggests however that these conclusions need to be treated with caution. In
some of the models reviewed – including the TNO model - landfill gas generation in
volume (m3) per year is apparently mistaken for methane generation in kg per year,
resulting in estimated methane generation which is about 2.5 times too high.113
An earlier study carried out similar analysis comparing landfill gas generation
measurements from three Dutch landfills against the predicted gas production using
six models including the TNO model.114 In this case, a dissimilation factor of 0.58 was
used in the TNO model. On all three sites considered within the study, measured gas
generation was approximately in the centre of the range of estimates produced by the
model. However, the same study also evaluated another Dutch model – that
produced by Afvalzorg - in a similar manner. In the case of the latter model,
dissimilation factors of 0.7-0.8 were used (although these are only applied to the
biodegradable part of the waste). The TNO estimates were, however, higher than the
Afvalzorg estimates despite the use of the lower dissimilation factor. This highlights
the fact that the dissimilation factor is thus only one variable of many to be
considered when comparing the performance of different models against field
measurements taken at landfill sites.
The TNO-model has been validated, both in a comparison with results from landfill
gas extraction (blue dots) and modeled emission estimates (blue circles) (see Figure
A 7). In 2002 TNO carried out some follow-up measurements at landfills with more
industrial waste (generally, containing less carbon per tonne, shown as red dots). The
model appears to show a reasonable agreement between modelled and measured
formation and resulted in a figure for gas generation of about 60 kg methane per
tonne of waste. Based on specific assumptions regarding DOC, this enabled a figure
for DDOC of around 0.58 to be estimated.
113 Oonk H (2010) Literature Review: Methane from Landfills: Methods to Quantify Generation,
Oxidation and Emission, Report for Sustainable Landfill Foundation
114 Scharff H and Jacobs J (2006) Applying Guidance for Methane Emission Estimation for Landfills,
Waste Management, 26, pp417-429
131
At present, in the Netherlands, there is much focus on making landfills more
sustainable, with a desire to force the biological degradation of waste through to
completion. To facilitate this, efforts have been made in detecting either dry or
acidified regions in the waste using geoelectrical methods. An example of a result of
such a measurement for a bioreactor test-cell is given in Figure A 8 below. The
method highlights the conductivity of areas in the cell. A high conductivity (dark blue)
means waste is saturated with leachate with high salt content, whilst a low
conductivity (red) indicates that waste is locally unsaturated. What is not clear is
whether these zones would remain entirely stable over time.
Figure A 7: Plot Illustrating Correspondence Between Calculated and Measured
Landfill Gas Emissions
0
500
1000
1500
2000
2500
3000
0 500 1000 1500 2000 2500 3000
calculated formation (m3 hr-1)
mea
sure
d fo
rmat
ion
(m3 h
r-1)
Nauerna
3e Merwedehaven
Wieringermeer
Braambergen
132
Figure A 8: Diagrammatic Representation of Variation in Conductivity Using Geo-
electrical Tests
133
A.5.0 Extraction Efficiency: Issues and Evidence This Appendix explores some of the issues associated with landfill gas extraction
efficiency, as well as reviewing the evidence from the literature regarding
measurements of extraction efficiency.
A.5.1 Engineering Considerations on Extraction Efficiency
Landfill gas is extracted using gas wells. Vertical wells are most frequently applied,
but horizontal systems or gas trenches are possible as well. A vertical gas well has a
specific region of influence (as indicated in Figure A 9) which often is assumed to be
35-50 m for landfills with household waste. This region of influence is determined by
well-design, the way the well is operated and waste characteristics. A simplified way
to estimate collection efficiency is from the ratio of the total surface of the landfill and
the surface within influence of the wells.
Figure A 9: Regions of Influence of Vertical Wells
well
region of influence
landfill border
Of course the actual regions of influence are not neat circles of a uniform and
predictable size. It is obvious, however, that collection efficiency decreases when
distances between wells increases, when the suction pressure on each individual well
is not optimized on a regular basis or when the permeability of the waste changes,
due to changes in its composition. High efficiencies require a state-of-the art design
of the well system and considerable knowledge and attention on the part of the
operator.
As described above, proper maintenance of the suction pressure on the wells is of
importance. Normally the suction pressure on each individual well can be controlled
with valves in the well-head. With little or no suction pressure on a well, internal
134
pressure in the waste is the main driving force enabling the landfill gas to be
extracted with relative high methane content, but at a low flow-rate. 115
Increasing the suction pressure on the well increases the flow-rate. However suction
pressure cannot be increased in an unlimited manner since air will be sucked in
through cracks and fissures in the top-layer. So, increasing suction pressure results in
an increasing region of influence of a well and increasing amounts of landfill gas
collected, but at the cost of a reduction in the methane content in the gas. Due to
settlements, but also due to precipitation, the permeability of the top-layer changes
continuously. So when high collection efficiencies must be maintained, especially in
the first years after closure, continuous attention to the suction pressure of each well
is required.
A.5.2 Economic and Environmental Optimal Gas Recovery
At a first glance landfill gas extraction is an obvious, win-win technology for
greenhouse gas abatement. Emissions of methane are abated and at the same time
landfill gas is recovered that can be utilized e.g. to generate electricity. As a result, an
important economic incentive exists to reduce methane emissions. However as long
as the economic incentive is the only one driving the recovery of landfill gas, a system
might be obtained that does not extract all the gas that could, technically, be
extracted.
In a landfill gas project driven purely by economics, the capacity for landfill gas
utilization becomes critical. This is illustrated in Figure A 10 below. Landfill gas
projects become less profitable when the utilization (e.g. the size of a gas engine or a
unit to upgrade biogas to natural gas quality) is below its design capacity for long
periods. In such cases, the capacity of the utilization is not always based on the
amount of landfill gas that can be extracted from the outset. The capacity may be
based more on expected quantities of landfill gas over longer term horizons (5 to 10
years). Since gas generation over the longer term is unpredictable, sometimes, low-
estimates of gas generation are used as a design basis for gas extraction.
If the utilization capacity is fixed,116 the economic incentive to extract more than the
amount that can be utilized might be relatively weak. For example, a landfill
compartment immediately after closure might produce 1,000 m3 hr-1. Suppose, for
the sake of argument, that 600 m3 per hr-1 could be extracted. Long-term gas
production may be much lower 500 m3 hr-1 and the utilization capacity might,
115 Due to the continuous process of waste degradation and landfill gas generation, the internal part of
the landfill has a pressure greater than that of the atmosphere. This excess pressure is one of the
factors behind landfill gas emission, but it also helps gas extraction.
116 This is not necessarily the case. Part of the peak might be utilized as well using modular utilization
options, e.g. smaller gas engines of about 100-250 kWe. However in practice this is not easily done
because of limited availability of these gas engines. The willingness of energy producing companies to
invest in such machines will depend a.o. on the long-term possibilities of finding new applications for
such an engine and these long-term possibilities depend on long-term landfill policies
135
therefore, be set somewhat below this at 400 m3 hr-1. So immediately after closure it
is only economically feasible to extract 40% of what is being generated.
Economic considerations might lead to increased well-spacing. When gas wells are
put closer together, the total amount of landfill gas extracted will increase, but the
gas extracted per well might decrease, thus increasing the costs of a cubic metre of
landfill gas extracted. For example, 1 well per ha might extract 200 m3 hr-1, where 2
wells per ha might extract 300 m3 hr-1. The extra gas extraction due to the 2nd well is
only 100 m3 hr-1 and this may or may not be considered cost-effective depending
upon the various factors affecting the overall economics of the site.
Economic considerations also have impact on, for example, maintenance of negative
pressure on suction wells. As shown in Figure A 10, immediately after closure gas is
abundant and one does not have to put that much attention to landfill gas extraction
to fill the utilization capacity. Optimization of landfill gas extraction at this time
requires significant man-power and is costly. As long as the utilization capacity is
filled, it is not cost-effective to optimize landfill gas extraction.
Figure A 10: Landfill Gas Generation and Extraction in Time, Driven by Economy
These types of mechanisms are most likely the reason why average integral extraction
efficiencies are, in practice, likely to be low - in the order of 20%. This may be true
even where – as suggested above – instantaneous extraction efficiencies can be very
high, particularly some years after site closure. It is extremely important to
understand the differences in the performance of landfills over their lifetime, not least
because most measurements cited in the literature have been carried out when sites
are partially or fully closed, and sometimes, a reasonable period after closure (see
Table A 38 below).
A.5.3 Literature on Extraction Efficiency
There is some literature available on extraction efficiencies. In most cases this refers
to the instantaneous extraction efficiency (the ratio of gas extraction and gas
generation at a certain point in time). Only in very few cases is it clearly documented
136
within a study at what phase in the life of the landfill (exploitation phase, early closed
stage, late closed stage or capped) the measured extraction efficiency refers to.
There are several ways to quantify extraction efficiency:
From a ratio of measured amounts of landfill gas extracted and an estimate,
or model, of landfill gas generation. In this case the estimate or model
determines the accuracy of the estimate;
From measurements of extracted amounts and of emissions. In most cases
where emissions are measures, the measurement targets only methane. Since
part of the gas is neither extracted nor emitted, but oxidized, an estimation of
methane oxidation is required (see below). In some cases both methane and
carbon dioxide emissions are measured and since oxidation does not affect
the sum of both (the methane is converted to carbon dioxide by oxidation), this
results in a more reliable measurement of recovery efficiency. In general the
quality of the measurement itself is important as well. Most methane emission
measurements are performed using flux chambers, a method which is known
to underestimate actual emissions; and
Collection efficiency might also be estimated from system design, based on
engineering considerations, preferably done by engineers with experience in
the design of landfill gas systems, who have performed test-extractions, and
who are involved in system optimization in the field.
An overview of collection efficiencies is given in Table A 38. The various studies in the
table are described in more detail below.
Table A 38: Overview of Collection Efficiencies from the Literature
Landfill
type Reference Method
Gas
extraction
efficiency
Remarks
Partial
exploit-
ation
Oonk
(1994)
Engineering
considerations 20%
Based on knowledge of experienced
engineers
Mostly
closed
Oonk
(1995)
MBM-measurements of
CO2 and CH4 11-52% 3 Dutch landfills
Ehrig
(1999)
Engineering
considerations, validated
by comparing extractions
and models
40-60%
German landfills in exploitation and
closed landfills. Validation suggests
efficiency is overestimated
Mosher
(1999)
Static chamber and tracer
plume measurements of
methane
70%
One USA landfill, partly in operation,
partly sealed with a geo-membrane.
Methane oxidation assumptions
unclear
Scharff
(2003)
MBM-measurements of
CO2 and CH4 10-55% 4 Dutch landfills
Michaels
(2006)
Gas extraction compared
to prognosis
75-85%
46-54%
Wisconsin landfills, efficiency
dependent on assumed model for
LFG generation
Lohila
(2007)
Micrometeorological
method 69-78%
Emission reduction upon start-up of
collection at Finnish landfill. Note the
137
Landfill
type Reference Method
Gas
extraction
efficiency
Remarks
applicability of the measurement
method is currently under discussion.
Themelis
(2007)
Gas extraction compared
to prognosis 35%
Average value taken across 25
Californian landfills. Assumptions for
gas generation are very uncertain.
Borjesson
(2007)
CH4 emission and
oxidation measurements 33-64% 4 Swedish landfills
Oonk
(2010)
Gas extraction compared
to prognosis 15% 45%
State of the art & non-state of the art
Dutch landfills
Recently
closed
Oonk
(1994)
Engineering
considerations 45-60%
Based on knowledge of experienced
engineers
Oonk
(1995)
MBM-measurements of
CO2 and CH4 10-80% 9 Dutch landfills, sand cover
Spokas
(2005)
CH4 emission and
oxidation measurements
88-92%
5% 1 French landfill, 30cm clay cover
Borjesson
(2007)
CH4 emission and
oxidation measurements 14-65% 2 Swedish landfills
Less
recently
closed
Oonk
(1994)
Engineering
considerations 60-95%
Based on knowledge of experienced
engineers
Oonk
(1995)
MBM-measurements of
CO2 and CH4 96-100%
2 Dutch landfills, clay and geo-textile
cover
Mosher
(1999)
Static chamber and tracer
plume measurements of
CH4
90%
1 USA landfill. Result somewhat
unreliable due to inaccuracies in
measured extraction
Spokas
(2005)
CH4 emission and
oxidation measurements 84-93%
3 French landfills, clay and geo-textile
caps
Spokas
(2005)
CH4 emission and
oxidation measurements 40% 1 French landfills, geosynthetic clay
Huitric
(2006) CH4 emissions 93-96% 1 Californian landfill 1.5m clay
Huitric
(2007) CH4 emissions 99% Same Californian landfill 5 years later
In 1994 Oonk et al evaluated the performance of a series of landfill gas generation
models.117For this purpose gas generation was estimated from gas extraction at
actual landfill sites (FOD-model, LFG0=186 m3/tonne; k=0.1 y-1).118 Only those landfill
117 Oonk H., Weenk A., Coops O., Luning L., (1994): Validation of Landfill Gas Formation Models, TNO,
Dutch organization for Applied Scientific Research, Report No. 94-315., Apeldoorn, The Netherlands
118 LFG0 is initial landfill gas potential of waste in m3 per ton waste. It is a variation on L0 as used by
US-EPA and IPCC, which describes the initial methane potential per ton waste.
138
gas extraction projects that were considered state-of-the art, and where actual gas
extraction was not limited by the capacity of utilization, were included. Gas extraction
efficiencies were estimated by Grontmij, an experienced engineering company and
were dependent on, inter alia, well distance, cover, landfill geometry and steepness of
slopes.
Oonk et al later described methane and carbon dioxide emission measurement on 21
Dutch landfill sites using a 1D mass-balance method.119 Gas was extracted from a
number of landfills and the emitted amount of methane and carbon dioxide was
compared with landfill gas extraction, yielding extraction efficiencies in Table A 38.
The measurements described by Scharff in 2003 follow on from the measurements
made in the early 90s at four Dutch landfills, and were compared with plume
emission measurements for methane.120
In 1999 Ehrig compared landfill gas extraction with modeled generation at a number
of German landfills, both open and closed using multi-phased models (LFG0=196
m3/ton and k=0,035-0,35 y-1).121 Assuming a recovery efficiency of 40-60%,
extracted amounts were below modelled generation, indicating that either the model
was overestimating landfill gas generation or extraction efficiency was lower than
assumed.
In the same year, Mosher et al reported a summary of methane emissions from nine
landfills in the Northeastern US.122 Emissions were measured by both static
chambers and a tracer flux technique. Two of the landfills collected LFG, making it
possible to compare emissions to collected gas. One of the two landfills was closed
and had a geo-membrane plus soil cover. A collection efficiency of 90.5% was
calculated. The authors indicate that the gas collected was not measured accurately,
which casts some doubt on this value. This collection efficiency is nonetheless likely
to be reasonable from two perspectives. First, this landfill had the lowest emissions of
the sites studied, and, second, the collection efficiency is consistent with other values
in this review. A collection efficiency of 70% was calculated for an active landfill in
which part of the landfill was covered with a geo-membrane but other parts had daily
cover only.
119 Oonk H., Boom T. (1995): Landfill gas formation, recovery and emission, TNO-rapport 95-203, TNO,
Apeldoorn, the Netherlands.
120 Scharff H., Martha A., v. Rijn D.M.M., Hensen A., Flechard C., Oonk H., Vroon R., de Visscher A.,
Boeckx P. (2003): A comparison of measurement methods to determine landfill methane emissions,
NV Afvalzorg, Haarlem, The Netherlands.
121 Multi-phase models, distinguishing fractions with rapid, moderate and slow degradation. Rate
constant of biodegradation, k, varies 0,035 and 0,35 y-1 (half-times of 2 to 20 years). See Ehrig H.-J.,
Scheelhaase T. (1999): Abschätzung der Restemissionen von Deponien in der Betriebs- und
Nachsorgephase auf der Basis realer Überwachungsdaten, Bergische Universität – Gesamthochschule
Wuppertal, Germany.
122 Mosher, B. W., Czepiel, P.M., Harriss, R.C., Shorter, J.H., Kolb, C.E., McManus, J.B., Allwine, E., and
Lamb, B.K. (1999): Methane emissions at nine landfill sites in the northeastern United States,
Environmental Science and Technology 33, p. 2088–2094.
139
Spokas et al. in 2005 carried out closed chamber measurements at 7 spots at 3
French landfills, with known gas extraction.123 Along with the closed chamber
measurements, 13C analyses were made to measure methane oxidation. In this way a
full „fate‟ analysis of methane could be made.
In 2006, Huitric et al describes emission measurements, using closed chambers,
performed in 2002 at a closed landfill site near LA.124 In the analysis methane
oxidation was neglected, so part of the reported extraction efficiency might be
attributed to methane oxidation. A year later Huitric described measurements from
the same landfill, taken 5 years later.125
Michels and Hamblin provided an overview of landfill gas extraction in Wisconsin, all
for landfills with parts still in exploitation.126 In total, extraction compared to modelled
generation (using a first order decay model with LFG0=200 m3/ton and k=0,04 y-1)
increased from about 75 to 85% in the period 2000-2004. However these results are
highly dependent on the assumed rate of biodegradation of waste. When a higher
rate of biodegradation and a slightly reduced LFG-potential are assumed (LFG0=186
m3/ton; k=0,1 y-1 for example) and when an evaluation is made on a landfill by landfill
basis, these efficiencies drop to 46-54% on average.
Börjesson et al subsequently performed tracer plume measurements of methane
emissions along with 13C plume measurements to assess methane oxidation at 6
Swedish landfills.127
Lohila et al reported methane fluxes for a section of a Finnish landfill that included an
active disposal area and a sloped area.128 The active area was covered daily with soil
and construction-and- demolition waste rejects, and the sloped area had a cover that
included 0.2 to 0.5 meters of compost over 0.5 to 2 meters of diamicton and clay.
Three estimates of collection efficiency were reported. First, it was reported that the
mean methane flux over seven days was reduced by 79% when the gas collection
123 Spokas K, Bogner J, Chanton JP, Morcet M, Aran C, Graff C, Moreau-Le Golvan Y and Hebe I (2005)
Methane mass balance at three landfill sites: What is the efficiency of capture by gas collection
systems? Waste Management, Issue 26, pp. 516-525
124 Huitric, R., and Kong, D. (2006): Measuring Landfill Gas Collection Efficiencies Using Surface
Methane Concentrations, Solid Waste Association of North America (SWANA) 29th Landfill Gas
Symposium, St. Petersburg, FL.
125 Huitric, R., Kong, D., Scales, L., Maguin, S., and Sullivan, P. (2007): Field Comparison of Landfill
Gas Collection Efficiency Measurements, Solid Waste Association of North America (SWANA) 30th
Landfill Gas Symposium, Monterey, CA.
126 Michels, M., Hamblin, G. (2006): LFG Collection Efficiency is Improving in Wisconsin, Waste
Management, Cornerstone Environmental Group.
127 Gunnar Börjesson, Jerker Samuelsson, and Jeffrey Chanton (2007) Methane Oxidation in Swedish
Landfills Quantified with the Stable Carbon Isotope Technique in Combination with an Optical Method
for Emitted Methane Environmental Science and Technology 2007, 41 (19), pp.6684-6690.
128 Lohila, A., Laurila, T., Tuovinen, J.P., Aurela, M., Hatakka, J., Thum, T., Pihlatie, M., Rinne, J., and T.
Vesala (2007): Micrometeorological measurements of methane and carbon dioxide fluxes at a
municipal landfill, Environmental Science and Technology, 41, p. 2717–2722.
140
system was turned on. This measurement was made by using methane concentration
data coupled to an eddy covariance method. Another estimate was made by
comparing the mean methane emission to the volume of gas collected and assuming
that methane production was the sum of emissions and collection. This resulted in an
estimate of 69% collection efficiency.
Themelis et al reported methane extraction and estimated methane loss (emission
and oxidation) for 25 Californian landfills in analysis published in 2007.129 Methane
loss was calculated from amounts of waste, assuming direct decomposition and a
production (LFG0) of 122 m3 per ton of waste. Extraction efficiency was estimated as
loss divided by the sum of extraction and loss, and in this way, an average efficiency
is obtained of 35%. The assumption of direct decomposition is a rough one, but might
be a first indicator when landfills are operational for longer times. An overestimation
due to gradually increasing amounts of waste deposited might be compensated by
the relative low assumed LFG0, so the 35% by indicated by the authors might still be
considered an overestimate.130
Recently in 2010 Oonk and Coops evaluated implementation of „state of the art‟
landfill gas extraction at Dutch landfills.131 All of them were still in exploitation, but no
organic waste was being landfilled (the landfills were effectively implementing the
Dutch ban on landfilling of organic waste. Conclusions were that extraction at most
Dutch landfill could be considered state of the art (well distance of about 70 meters,
frequently controlled suction pressure on the wells). The average collection efficiency
of landfills whose collection efficiencies were labelled „good‟ to „very good‟ was 46%
(efficiencies ranged from 20-85%), compared to a modeled level of landfill gas
generation. Landfill gas projects with greater distance between wells or a less
controlled suction pressure on wells were substantially less efficient (15% on
average).
A.5.4 Other Considerations
In the current UK approach, a collection efficiency of 75% is assumed. The
description of MELMod includes the following statement:
“Although the UK‟s level of landfill gas recovery appears to be high in
comparison with other countries, there are grounds for confidence in the UK‟s
overall recovery rate of 70 per cent. With regard to landfill gas utilization,
energy recovery from landfill gas has benefited greatly in the UK as a result of
various initiatives to stimulate electricity production from renewable sources.”
129 Themelis N.J., Ulloa P.A., (2007): Methane generation in landfills, Renewable Energy 32, 1243–
1257
130 When assuming direct decay, landfill gas generation follows waste deposition in a 1 to 1 relation.
When amounts of waste landfilled slowly increase, landfill gas generation increases as well, but in a
somewhat delayed way. Assuming direct decomposition in such a case results in an overestimation of
landfill gas generation.
131 Information from Oonk (2010). The study was performed in 2005 and results are confidential; thus
the details unfortunately can not be disclosed.
141
However in other (north western) European countries this situation is not significantly
different in respect of efforts to control emissions of methane. The situation in these
countries might not be entirely comparable in UK (e.g. these countries significantly
reduced landfilling of organic years in the last 10 years), but similarities are just as
large: most landfills with landfill gas extraction (valid for Denmark and the
Netherlands) still produce significant amounts of gas with good quality; mitigation of
landfill gas emission receives lots attention of both local and national government for
maximised landfill gas recovery (effectuation of this in legislation differs however),
and implemented technology and capabilities of waste treating companies have
developed in the past 20 years.
The difference between measured national collection efficiencies in Denmark, Austria
and the Netherlands at one hand and the UK-estimate at the other hand is sufficiently
large, that a simple statement as in the MELMod description does not suffice. It
needs to be emphasised again that the modelling we are discussing is not a model of
a single landfill with state-of-the-art gas extraction technology. Rather, we should
consider the fact that landfill emissions originate from sites of varying ages, so that it
is no exaggeration to state that the mix of landfills of relevance to emissions from UK
landfills as a whole most likely includes sites with no gas extraction technology, as
well as ones with technologically advanced systems.
In this respect, it might be noted that whilst some of the countries listed below might
be landfilling less biodegradable waste today than the UK, few have enacted bans or
restrictions which exerted their full effect a very long time ago. As such, the argument
that might be played regarding the lower likely extraction efficiencies from these
countries would be consistent with a view that only the most recently built landfills are
capturing large proportions of the generated methane. This would appear to
strengthen the argument against the high extraction rates used in MELMod for three
different landfill types in recent years.
A.5.4.1 Denmark
In Denmark all major and intermediate sized landfills extract landfill gas (Willumsen,
2010).132 The Danish Energy Agency registers the gas amounts recovered at disposal
sites in energy units (TJ) (Danish Energy Agency, 2009)133. For the emission
estimation this amount of gas in energy unit is converted to volume of gas using the
calorific value of 20 MJ per m3.
A.5.4.2 Germany
In Germany, landfill gas collection is obligatory for all landfills for municipal waste,
since 1993 (prescribed in the "TA Siedlungsabfall" of 1993). Collection of gas from
landfills began in the 1980s. In the German report of greenhouse gas emissions to
132 H. Willumsen (2010), personal communication, LFG Consult, Denmark.
133 Danish Energy Agency (2009) Denmark‟s fifth national communication on climate change, Danish
Energy Agency, Denmark.
142
UN-FCCC,134 it is assumed that all landfills that are relevant for methane production
have gas collection. In total 95% of methane is assumed to be produced at landfills
with 60% collection efficiency. However the intention is expressed to base the figure
on actual landfill gas recovery with monitored data in future. No evidence is given for
the assumed collection efficiency used this far.
A.5.4.3 Netherlands
Landfill gas recovery in the Netherlands was given considerable stimulus in the first
half of the „90‟s. In a government backed initiative, feasibility studies were performed
for all closed and open sites larger than few hectares. In those years, energy
distributing companies had significant support, and also targets, for renewable energy
generation, and since landfill gas recovery and utilization was one of the more cost-
effective options, companies were very active in initiating new projects. In 1993
legislation was enforced with the objective to limit methane emissions from the
waste, prescribing landfill gas extraction at all operational landfills (Stortbesluit). As a
result the number of landfills with landfill gas recovery rose from about 10 in 1990 to
over 60 in 1999.
All operational landfills, and most of the medium sized, and virtually all larger, closed
landfills have landfill gas recovery. In the 1993 legislation, it was also recognized that
a large amount of methane is produced and emitted during exploitation, so that the
legislation aimed to ensure gas recovery during the exploitation phase as well.
In this period it was also recognized that landfill gas recovery for energy utilization is
not necessarily an effective system for mitigation of methane (see appendix), and in
2005 best available technology (BAT) for landfill gas recovery was defined with
detailed prescriptions on:
Design basis for landfill gas recovery, capacity of extraction;
Well-laid-out, distance between wells;
Operational regime. Suction pressure on wells, maximum CH4-content in
extracted gas.
In summary, the majority of Dutch landfills that contribute to emissions have landfill
gas recovery.
There has been a great deal of attention to implementation of state of the art
projects, and maximizing emission reduction (rather than maximizing energy
generation from landfilled waste). There are limited amounts of degradable carbon
landfilled in those sites in operation. Even so, despite these efforts, it is calculated
that still no more than 15% of methane overall is extracted.
134 Umweltbundesamt, (2010) Submission under the United Nations Framework Convention on
Climate Change and the Kyoto Protocol 2010, Umweltbundesamt, Dessau. Germany.
143
A.5.4.4 Austria
The development of landfill gas extraction in the 1990s and its stimulation due to the
potential for recovery of renewable energy is not well documented. However in the
1990s landfill gas extraction must have developed significantly, since by 2002, in
total, 61.2 million m3 of landfill gas was extracted and utilized or flared.
Currently, landfill gas recovery is regulated in the “Deponiegasverordnung” from
2004, which obliges operators to have adequate landfill gas extraction, monitoring
and reporting to the legislative authorities. This obligation applies for landfills with
both untreated and pretreated (e.g. MBT) waste. As a result of this legislation all
operational landfills, as well as all medium sized and large closed landfills, have
landfill gas recovery.135
Due to Austrian waste policy, the amount of waste landfilled without pre-treatment
has fallen significantly, and the practice of landfilling untreated waste is now banned.
As a result, landfill gas production is diminishing and landfill gas extraction also fell
back to 43.3 million m3 in 2007.136 To prevent landfill gas projects from closing down
before most of the methane potential is released, the 2008-version of the
“Deponiegasverordnung” prescribes leachate recirculation to enhance gas
production.
The quantification of the amount of methane recovered (as the basis for the inventory
of national emissions) proceeds in a periodic inquiry amongst all Austrian landfill gas
projects. A recent inquiry from 2008 collected amounts recovered in the period 2002-
2007 and obtained responses from 90% of all Austrian landfill gas projects. The total
amount recovered amounted to 15% of the total amount that is generated.
A.5.4.5 USA
In USA, the total amount of landfill gas recovered per year is based on sales of flaring
equipment, a database of landfill gas-to-energy (LFGTE) projects, and a database for
the voluntary reporting of greenhouse gases.137 Specifics of the method are not
revealed, but overall the method results in a nationwide efficiency of almost 50%.
The US landfill industry regards itself as a world leader in landfill gas recovery.
Sullivan et al.138 state:
135 Lambert C. (2010); personal communication.
136 Based on an inquiry amongst all Austrian landfills with landfill gas recovery (Lambert C.,
Schachermayer E. (2008): Deponiegaserfassung auf österreichischen Deponien, Zeitreihe 2002 bis
2007, Umwelbundesamt, Austria). Enquiry had 90% response. No correction of results for amounts
recovered by non-respondents.
137 US-EPA, (2010) Inventory of U.S. greenhouse gas emissions and sinks: 1990 – 2008, US_EPA,
Washington, USA.
138 Sullivan (2010): Current MSW Industry Position and State-of-the-Practice on LFG Collection
Efficiency, Methane Oxidation, and Carbon Sequestration in Landfills; SCS Engineers, Sacramento,
USA.
144
“Further, the US has the most comprehensive requirements for LFG collection
and control in the world, as accomplished through the landfill New Source
Performance Standards (NSPS) under 40 CFR, Part 60, Subpart WWW, as well
as more stringent state regulations such as California Assembly Bill 32‟s
landfill methane rule. These regulations prevent excessive fugitive emissions
by requiring LFG collection and control as well as extensive monitoring for
surface emissions of methane to maximize LFG capture. They also dictate
specific requirements for how comprehensive LFG systems must be designed
and operated.”
Sullivan et al. appear to consider the nationwide figure of 50% as an underestimation
and propose collection efficiencies of 50-85% (mid-range default = 68%) for a landfill
or portions of a landfill that are under daily cover with an active LFG collection
system; 85-99% (mid-range default = 92%) for a landfill or portions of a landfill that
are closed and have active LFG collection system; and 95-99% (mid-range default =
97%) for capped landfills an active LFG collection system. These values are based on
selected information from Table A 38. Only the emission measurements of Spokas et
al. and Huitric, largely at capped landfills, and the Wisconsin database of Michels and
Hamblin are considered as the basis for these views.139
A.5.4.6 New Zealand
SKM developed an approach for the Ministry for the Environment which aimed to
estimate the quantity of methane recovery between 1990 and 2012. This was based
upon a bottom-up methodology, seeking to understand the situation at each
individual landfill, but not involving measurements.140 The work clearly faced a
number of constraints in terms of responses from operators and the absence of
quality data, not least, that of a historical nature (which is important for
understanding current and future emissions).
The report notes:
Where there is no gas flow data, SKM has estimated the collection efficiency
from a number of factors. The estimate is based on the IPCC suggested range
of 10% to 90% collection efficiency and adjusted for known factors (the mean,
50%, was made the default).
139 Spokas K, Bogner J, Chanton JP, Morcet M, Aran C, Graff C, Moreau-Le Golvan Y and Hebe I (2005)
Methane mass balance at three landfill sites: What is the efficiency of capture by gas collection
systems? Waste Management, Issue 26, pp. 516-525; Huitric, R., and Kong, D. (2006): Measuring
Landfill Gas Collection Efficiencies Using Surface Methane Concentrations, Solid Waste Association of
North America (SWANA) 29th Landfill Gas Symposium, St. Petersburg, FL.; Huitric, R., Kong, D., Scales,
L., Maguin, S., and Sullivan, P. (2007): Field Comparison of Landfill Gas Collection Efficiency
Measurements, Solid Waste Association of North America (SWANA) 30th Landfill Gas Symposium,
Monterey, CA.; Michels, M., Hamblin, G. (2006): LFG Collection Efficiency is Improving in Wisconsin,
Waste Management, Cornerstone Environmental Group.
140 SKM (2010) Estimates of Landfill Methane Recovered in NZ 1990 to 2012, Report for the Ministry
for the Environment, June 2009.
145
This does not accurately represent the IPCC view. The IPCC gives no „suggested
range‟. Furthermore, the default chosen is well above what is recommended by the
IPCC.
The reported range for gas collection efficiency in the study is 42-90%. It is difficult to
square this range with the statement in the report that:
Of the 24 landfills that were identified, 17 are currently destroying methane, 3
are planning to destroy methane in the future, 1 destroyed methane in the
past, and we do not know whether or not the remaining 3 landfills will begin
destroying methane in the future. Four of the landfill operator/owners
provided actual gas quantity data while ten landfill operator/owners did not
provide any information.
Figure A 11: Methane Generated and Captured from New Zealand Landfills
Source: SKM (2010) Estimates of Landfill Methane Recovered in NZ 1990 to 2012,
Report for the Ministry for the Environment, June 2009.
The results for New Zealand as a whole are shown in Figure A 11. What is interesting
is that in 2006, the capture rate is assumed to be already approaching 50%. This is
the same year for which a landfill census suggested that only 22% of landfills had gas
collection systems in place (of any sort).141
141 Ministry for the Environment (2007) The 2006/07 National Landfill Census, October 2007.
146
Of course, it is possible that the sites with gas extraction systems in place were the
ones receiving the majority of waste, but given that only 5% of sites in 1998 had gas
collection systems in place, then given also that the historic deposit of waste will
contribute significantly to methane generation 8 years later, the conditions under
which around 22% of landfills would be capturing almost 50% of all emissions in that
year would appear to be very restrictive indeed.
147
A.6.0 Methane Oxidation Rates This Appendix reviews the processes for determining methane oxidation, as well as
evidence from the literature regarding oxidation. The review forms the basis for
recommendations made in the main report.
A.6.1 Processes Determining Methane Oxidation
In recent years substantial attention has been paid to methane oxidation by research
groups around the world. The most important factors determining methane oxidation
are:
The homogeneity at which methane is emitted. At landfills, a large part of the
methane which escapes from the site believed to be is released through short-
cuts. These short cuts are typically cracks and ruptures at the surface or
subsurface, but may also include gas-wells or drainage pipes that are not well
sealed or are leaking. As a result methane emissions are highly heterogeneous
and methane oxidation at hot-spots is most likely much less than oxidation
methane that which is emitted in a more homogeneous way;
The flux of homogeneously emitted methane (the flow of methane from the
bulk of the waste to the bottom of the top-layer in g m-2 hr-1). When this flux
increases, diffusion of oxygen into the top-layer is reduced and methane
oxidation declines as well;142
The porosity of the top-layer. Increased porosity implies on the one hand a
more homogeneous methane emission. On the other hand, oxygen diffusion
into the top-layer is enhanced. So, increased porosity is advantageous to
methane oxidation. Water-logging in periods with high precipitation decreases
porosity;143
The water-content of the top-layer. The oxidation process involves bacterial
action. Bacteria need moisture to be active and bacteriological activity is
favored by moisture. However too much water might block the pores. So there
is an optimum water content of the top-layer;144
142 Scheutz C., Kjeldsen P., Bogner J.E., De Visscher A., Gebert J., Hilger H.A., Huber-Humer M., Spokas
K. (2009): Microbial methane oxidation processes and technologies for mitigation of landfill gas
emissions, Waste Management & Research, 27: pp. 409–455.
143 Gebert J., Rachor I., Gröngröft A. (2009): Column Study for Assessing the Influence of Soil
Compaction on CH4 Oxidation in Landfill Covers, University of Hamburg, Ger-many.
144 Börjesson G., Svensson B. (1997): Seasonal and diurnal methane emissions from a landfill and
their regulation by methane oxidation. Waste Management and Research, 15, pp. 33–54; Cabral, A.R.,
Tremblay, P. & Lefebvre, G. (2004): Determination of the diffusion coefficient of oxygen for a cover
system composed of pulp and paper residues. ASTM Geotechnical Testing Journal, 27, pp. 184–197
148
The temperature of the cover-layer, which is closely connected to ambient
temperatures. At higher temperatures bacteria become more active. Every
10 o C temperature increase means about 2-4-fold increase in methane
oxidation.145
As a result of its moisture and temperature dependency, methane oxidation depends
on average weather conditions. It is, therefore, climate-dependent. Methane oxidation
is thought to be at its maximum effectiveness in temperate to warm conditions with
limited excess rainfall. Methane oxidation is most likely less effective in colder
climates, and under warm but dry conditions.146
For a specific top-layer, oxidation also depends on the season. Methane oxidation is
lower in winter than in summer. This is observed in Nordic countries, such as
Denmark, Sweden, Belgium, and in northerly states of the USA.147
A.6.2 Measurement of Methane Oxidation
Methane oxidation can be measured by 13C analysis of gas samples, obtained by
either closed chambers or plume measurements. The method is based on the fact
that CH4 with 12C is preferably oxidized, compared to methane built from 13C. Upon
oxidation methane is enriched in 13C and the shift in 13C concentration is used to
calculate methane oxidation.
Closed chamber box measurements have to be considered unreliable and tend to
overestimate methane oxidation for two reasons:
Methane emissions exhibit a huge variation from spot to spot and when
performing closed chamber measurements, which makes it hard to obtain a
reliable, average emission. To improve closed-chambers measurements,
protocols are drafted, defining e.g. the intensity of the grid, where emission
measurements have to take place and geostatistical procedures are proposed
to extrapolate such a grid-wise measurement to the whole landfill. Hot-spots
and short cuts will, however, most likely will be missed or under-represented.
Even when a high-intensity measurement is performed on a landfill, and
145 Gebert J., Gröngröft A. (2007): Potential and Limitations of Passively Vented Biofilters for the
Microbial Oxidation of Landfill Methane, 2nd BOKU Waste Conference, Vienna, April 2007
146 Abichou T., Johnson T., Mahieu K., Chanton J.P., Romdhane J., Mansouri I. (2010): Developing a
Design Approach to Reduce Methane Emissions from California Landfills, Florida State University, USA.
147 Christophersen, M. and Kjeldsen, P. (1999): Field investigations of lateral gas migration and
subsequent emission at an old landfill; Sardinia 99 Seventh International Waste Management and
Landfill Symposium; IV (79-86); 4-8 October 1999, Cagliari, Italy; Maurice C., Lagerkvist A. (1997):
Seasonal influences of landfill gas emissions, Sardinia 97 Sixth International Landfill Symposium; IV
(87-94); 13-17 October 1997, Cagliari, Italy; Börjesson, G., Samuelsson J., Chanton J., (2007):
Methane oxidation in Swedish landfills quantified with the stable carbon isotope technique in
combination with an optical method for emitted methane, Environ. Sci. Technol., 41, 6684-6690;
Boekx, P., Van Cleemput, O., and Villaralvo, I. (1996): Methane emission from a landfill and the
methane oxidising capacity of its covering soil, Soil Biology & Biochemistry, vol. 28, pp 1397-1405;
Czepiel P.M., Mosher B., Crill P.M., Harris R.C. (1996b): Quantifying the effect of oxidation on landfill
methane emissions. Journal of Geophysical Research. 101, 16721-16729
149
geostatistical techniques are used for interpolation, therefore, closed chamber
measurements tend to underestimate short-cuts and underestimate methane
emissions (and lead to an overstatement of extraction efficiencies). Similarly
closed box measurements of methane oxidation tend to overestimate
methane oxidation. Short-cuts are places with locally increased methane flux
and therefore reduced or even negligible methane emissions, and when such
short-cuts are missed, these spots with low methane oxidation will not be
considered in the average;
Even when short-cuts are measured, the way methane oxidation
measurements are averaged is a basis for overestimating methane oxidation.
For example, when 90% of emissions takes place on 10% of the landfill
surface and 10 closed chamber measurements are performed, 9
measurements can be expected in a low flux area and only 1 measurement in
a high flux region. So the low flux-area is overrepresented in a simple average;
the 9 measurements, yielding high oxidation, represent only 10% of total
methane flux and 90% of methane is emitted at no or negligible oxidation.
Plume measurements of 13C are considered a more reliable way to measure methane
oxidation. At the moment this is considered state-of-the-art. In this method, 13C is
measured away in the plume on top or away from the landfill. The method however is
not without problems as well. Chanton et al describe three issues affecting the 13C
method, the most important being a by-pass effect.148 However all of the key issues
affecting measurement tend to result in an underestimation of methane oxidation
(whereas the opposite is the case with chamber box measurements).
Mass-balance measurement of oxidation relies on a shift in the CO2/CH4-ratio in
landfill gas, caused by the oxidation of methane to carbon dioxide. Measured
emissions of CO2 and CH4 can be compared with the CO2/CH4-ratio of the landfill gas
as extracted. This method of assessing methane oxidation is also disputable. The
main reasons for this are that other sources and sinks of CO2 are present in the top-
layer of the landfill, e.g. CO2 assimilated by vegetation or CO2 dissolved in rainwater.
Besides, part of the CH4 which is oxidized is used to fuel the growth of the
methanotrophic bacteria and is not released as CO2. Effectively, the carbon is used to
build cell matter.
A.6.3 Results of Measurements
As described above, methane oxidation depends on factors such as climate, the
season and also on the methane flux through the top-layer. So for a reliable
estimation of methane oxidation in the UK, reliable measurements of oxidation are
required in climatic conditions comparable to UK, performed in all seasons, and also
with methane fluxes that are representative for the methane fluxes that exist in the
landfill phases when most methane emissions take place.
148 Chanton, J.P., D.K. Powelson, T. Abichou, and G. Hater. (2008): Improved field methods to quantify
methane oxidation in landfill cover materials using stable isotope carbon isotopes, Environ. Sci.
Technol., 42, pp. 665–670
150
Figure A 12 shows again the landfill gas formation and recovery. The total methane
flux (in m3 per year) through the top-layer is proportional to this. Apart from the
exploitation phase, when the landfill surface area steadily increases, the grey area is
also proportional to the flux, expressed in g CH4 m-2 hr-1. From Figure A 12 it becomes
obvious that national methane oxidation estimates have to be based on oxidation
measurements at landfills in the exploitation phase, or early on following the end of
exploitation.
Figure A 12: Landfill Gas Generation, Recovery and Total Flux through the Top-layer
(in gray) at a Landfill
0
1000000
2000000
3000000
4000000
5000000
6000000
7000000
8000000
9000000
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034
LFG
form
atio
n an
d ex
trac
ted
time
exploitation closed capped
Table A 39 gives an overview of relevant studies determining average methane
oxidation over a period of a year. The studies are described in more detail below.
Chanton et al give a review of measurements for methane oxidation throughout the
world. 149 The vast majority of methane oxidation measurements are performed using
closed chambers, often with very few measurements, rarely using a carefully planned,
or sufficiently tight grid, and rarely interpreted using geostatistical or other methods.
Furthermore, few have been averaged in a particularly sophisticated manner, and
most have been performed at landfills that have been closed for a long time or have
been capped (and where the surface flux is therefore low). The authors pay extra
attention to the small number of year round studies.
149 Chanton J.P., Powelson D.K., Green R.B. (2009): Methane oxidation in landfill cover soils, is a 10%
default value reasonable? J. Environ. Qual. 38:654–663.
151
Table A 39: Summary of Methane Oxidation Measurements from the Literature
Landfill
type Literature source Method
Oxidation
rate Remarks
Mostly
closed
Bergamaschi
(1998)
Closed chambers,
plume
measurements
25%
Interpretation by Chanton et al
(2009), measurements at 4
German / Dutch landfills
Abichou (2004) Closed chambers 23% Fresh waste, daily cover in Florida
Borjesson
(2007)
Plume
measurements 10%
Oonk (2010) Mass-balance
method 10-30% Methodology under discussion
Closed Borjesson
(2001) Closed chambers
26 and
42%
Interpretation by Chanton et al
(2009), two Swedish landfills one
recently closed, the other closed for
20 years
Christophersen
(2001)
Closed chambers,
13C and mass
balance
interpretation
28 and
89%
Interpretation by Chanton et al
(2009), rate dependent on method
of interpretation
Achibou (2004)
& Stern (2007) Closed chambers 19–30%
Three testfields in Florida. Results
dependent on interpretation
Barlaz (2004) Closed chambers 21% Intermediate cover, 3-5 year old
waste
Borjesson
(2007)
Plume
measurements 20%
Oonk (2010) Mass balance
method 20-40% Methodology under discussion
Capped Closed chambers 40% 1 m compacted clay, 0.5 m sand
Bergamaschi et al measured 13C isotopes from 4 landfills in the Netherlands and
Germany, both in the plume and directly from the soil using closed chambers.150 All
landfill were still in operation and had at least one part where fresh waste was
dumped. They observe a significantly higher shift of 13C in the box, compared to the 13C in the plume. On the basis of this, the authors conclude that 70% of all landfill gas
is emitted through short-cuts. On the basis of the results of Bergamaschi et al.,
Chanton et al. estimate methane oxidation to be 84%. This is likely to relate to the
oxidation of the 30% of methane that does pass through the landfill surface in a more
homogeneous way, yielding an overall oxidation of 25%.
150 P. Bergamaschi, C. Lubina, R. Königstedt, H. Fischer, A.C. Veltkamp, and O. Zwaagstra (1998)
Stable isotopic signatures ( 13C, D) of methane from European landfill sites. J. Geophys. Res. Atmos.
103:8251–8265
152
Börjesson et al. measured methane emissions and oxidation (13C) on two Swedish
landfills, using closed chambers. 151 One of the landfills was recently closed, the other
one was closed for almost 20 years. Measurements were performed in August,
February and March for both sites. Methane oxidation in summer was substantially
higher than in winter. Methane oxidation on the top of the landfill (with lower methane
flux) was higher than on the slopes. On the basis of these results, Chanton et al.
estimate average oxidation to be 42% and 26% at the two sites.
Christophersen et al. perform closed chamber measurements throughout the surface
of a Danish landfill, closed over 10 years ago, measuring both CH4 and CO2-
emissions, along with 13C.152 Chanton et al estimate methane oxidation to be 89% on
basis of a shift in CO2/CH4 ratio and 28% on the basis of shift in 13C.
An earlier study by Chanton et al in 2002 used closed chambers to measure methane
emissions from a closed and a capped landfill.153 The closed landfill still gave
significant methane emissions and an oxidation of 4%. Methane emissions from the
capped landfill were considerably less and methane oxidation was 40%.
Abichou and Chanton measured methane oxidation at a Florida landfill, using closed
chambers.154 The methane oxidation was measured at 22.5% for a part with 45-cm-
thick soil layer on top of 7-year-old waste, 11.4% for a 45-cm soil cover on top 14-
year-old waste and 22.7% for fresh waste with daily cover. Later on, methane
oxidation from the same spots was reported to be 30% on an annual average
basis.155 This was however based on 3 measurements, including a number of
observations of 100% methane oxidation, without any attempt to average these
observations on a weighted basis. As a result the regions with 100% oxidation (most
likely representing little to negligible flux) increase the average value of oxidation
considerably, and give what is almost certainly a falsely high value.
Barlaz et al. measured methane emissions and oxidation, using closed chambers on
a soil-covered area on a Kentucky landfill, on top of a temporary cover of 3-5 year old
151 Borjesson, G., J. Chanton, and B.H. Svensson (2001): Methane oxidation in two Swedish landfill
covers measured with carbon-13 and carbon-12 isotope ratios, J. Environ. Qual. 30, pp. 376–386.
152 Christophersen M., Kjeldsen P., Holst H., Chanton J. (2001): Lateral gas transport in soil adjacent to
an old landfill: factors governing emissions and methane oxidation, Waste Manag. Res., 19, pp. 595-
612.
153 Chanton, J.P., Fields, D., Bogner, J., Morcet, M., and Scheutz, C. (2002). A Stable Isotope Technique
for Determining Methane Oxidation in Landfill Covers, Proceedings SWANA 25th annual landfill gas
symposium, March 25-28th, Monterey, California, published by SWANA, Silver Spring, MD.
154 T. Abichou, J. Chanton, (2004) Characterization of Methane Flux, Oxidation, and Bioreactive Cover
Systems at the Leon County Landfill, Annual Report- Florida Center for Solid and Hazardous Waste
Management.
155 Stern J.C., Chanton J., Abichou T., Powelson D., Yuan L., Escoriza S., Bogner J., (2007), Use of a
biologically active cover to reduce landfill methane emissions and enhance methane oxidation, Waste
Management 27, pp. 1248–1258.
153
waste.156 The resulting methane oxidation varied significantly from 0 to 100%. Simple
averaging of all values gave an average of 21% oxidation in the summer period.
Börjesson et al performed measurements at a few landfills in Sweden, as shown in
Figure A 13.157 Some landfills were still in operation while others were recently
closed. The measurement method was based on 13C of the methane in the plume, a
method which can be considered as one of the more reliable methods to quantify
methane oxidation. The authors explicitly paid attention to improved default values
for methane oxidation and propose 10% for active and 20% for closed landfills.
Figure A 13: Methane Oxidation at Swedish Landfills
Source: Börjesson G., Samuelsson J., and Chanton J. (2007) Methane Oxidation in Swedish Landfills
Quantified with the Stable Carbon Isotope Technique in Combination with an Optical Method for
Emitted Methane, Environmental Science and Technology, 41 (19), pp.6684-6690.
Recently Oonk re-evaluated earlier measurements performed by TNO in the period
1991-1994 and in 2002.158 Using a 1D-mass balance method, both CH4 and CO2-
emissions were measured at Dutch landfills. The ratio of both emissions, compared to
the ratio of CH4 and CO2 in the extracted landfill gas, is an indication of oxidation, as
shown in Figure A 14. The measurement method itself is not recognized as a
promising one and in particular the emission measurements of CO2 have limited
accuracy. Also the interpretation of CH4 and CO2-ratio is disputable (see above under
„measurement of methane oxidation‟). However the results in Figure A 14 seem to
156 Barlaz M., Green R.B., Chanton J.P., Goldsmith C.D., Hater G.R. (2004): Evaluation of a biologically
active cover for mitigation of landfill gas emissions, Environ. Sci. Technol., 38, pp. 4891-4899.
157 Börjesson G., Samuelsson J., and Chanton J. (2007) Methane Oxidation in Swedish Landfills
Quantified with the Stable Carbon Isotope Technique in Combination with an Optical Method for
Emitted Methane, Environmental Science and Technology, 41 (19), pp.6684-6690.
158 Oonk H., (2010): Oxidatie van methaan in toplagen van stortplaatsen, naar een betere
kwantificering, OonKAY!, Apeldoorn, The Netherlands; Scharff H., Martha A., v. Rijn D.M.M., Hensen A.,
Flechard C., Oonk H., Vroon R., de Visscher A., Boeckx P. (2003): A comparison of measurement
methods to determine landfill methane emissions, NV Afvalzorg, Haarlem, The Netherlands
154
make sense and indicate a methane oxidation 10-30% oxidation for Dutch landfills in
exploitation and 20-40% oxidation for closed landfills with a maximum of 5-10 kg
CH4/m2/yr. Therefore the validity of this new interpretation of these old
measurements is currently being discussed amongst specialists.
Figure A 14: Methane Oxidation as a Function of Flux to the Top-layer (n.b.
measurements were taken in all seasons, except winter
0
4
8
12
16
20
0 30 60 90 120 150
me
than
e o
xid
atio
n (
kg/m
2/j
r)
methaanflux to the top layer (kg/m2/jr)
100% 30% 20%
10% oxidation
Source: Oonk H., (2010): Oxidatie van methaan in toplagen van stortplaatsen, naar een betere
kwantificering, OonKAY!, Apeldoorn, The Netherlands
The recent analysis by Chanton et al. also discussed the IPCC-default value in a
review that limits itself to peer-reviewed literature.159 They conclude that only 1 out of
10 measurements result in a value of less than 10%. The average of all available
measurements is 35%. It has to be noted that the authors were not especially critical
of the derivation of the measurements and simply took an average of all available
measurements. As such, the average is overly weighted towards measurements
performed using flux chambers, which, as discussed above, is recognized as
inaccurate on larger surfaces and likely to lead to over-estimates.
159 Chanton J P, Powelson D K and Green R B (2009) Methane Oxidation in Landfill Cover Soils, is a
10% Default Value Reasonable? Journal of Environmental Quality, 38, pp 654-663.
155
A.7.0 Methane Content of Landfill Gas This Appendix briefly presents information regarding the formation of methane in
landfills, before discussing key factors which affect the composition of methane in
landfill gas, major constituents of which are carbon dioxide and methane.
A.7.1 The Stoichiometry of Methane Formation
Barlaz describes the stoichiometric relationship for the conversion of cellulose and
hemicellulose to methane, using equations (1) and (2) respectively:160
(C6H10O5)n + nH2O → 3nCO2 + 3nCH4 (1)
(C5H8O4)n + nH2O → 2.5nCO2 + 2.5nCH4 (2)
In each case, equal molar quantities of CO2 and CH4 are produced, implying that
equal quantities of the two gases by volume will also be produced. However, Barlaz
goes on to suggest that landfill gas typically contains more CH4 because CO2 is
partially soluble in water and thus some dissolves in leachate. In addition, the
relationship described in the two equations presented above does not hold true for
fats and proteins, which follow a different chemical conversion route during
methanogenesis. The chemical conversion of protein to CH4 has been described
elsewhere by White et al, and is considered to occur in the following stages:161
C46H77O17N12S+19.95H2O=0.42C69H138O32+5.18CH3-COOH+6.55CO2+12NH3+H2S (1)
C69H138O32+18.5H20=16CH3COOH+27.75CH4+ 9.25CO2 (2)
CH3COOH=CH4+CO2 (3)
These equations suggest that Stage 2 – which also holds true for the degradation of
fats - will result in a higher CH4 yield relative to the CO2 production (albeit that Stage 1
results in the formation of only CO2).
A.7.2 The Influence of Landfill Conditions
The above equations represent the situation for optimal methanogenesis. However
the actual proportion of methane in the gas will vary depending on the extent to which
the conditions required for optimal methanogenesis are present in the landfill.
Methane formation only occurs in moist, airless spaces.162 Whilst an increase in the
moisture content leads to more methane formation, the presence of oxygen, on the
other hand, prevents methane from forming. The proportion of methane in landfill gas
160 Barlaz M A (2004) Critical Review of Forest Products Decomposition in Municipal Solid Waste
Landfills, National Council for Air and Stream Improvement, Bulletin 872
161 White J, Robinson J and Ren Q (2004) Landfill Process Modelling Workshop: Modelling the
Biochemical Degradation of Solid Waste in Landfills, Waste Management, 24, pp227-240
162 Center for a Competitive Waste Industry (2008) Landfill Gas to Energy Compared to Flaring
156
is thus dependent upon the percentage of moisture and the absence of oxygen at any
given time. In a situation where conditions are sub-optimal for methanogenesis, the
resulting CH4 fraction of the landfill gas may be as low as 35%.
As was indicated at the start of this Section, MELMod currently assumes that landfill
gas generated at Type 4 landfills (the older uncapped sites) has a methane
concentration of 30%. This is intended to reflect the higher proportion of aerobic
degradation anticipated to occur at such sites, which would tend to increase the
proportion of CO2 relative to methane. However the lack of covering material is also
likely to allow for greater penetration of moisture into the lower layers of the landfill,
and this would tend to increase methanogenesis.
The oxidation of methane that occurs as the landfill gas passes through the covering
materials will also decrease the amount of methane relative to the CO2 content.
A.7.3 The Changing Composition of Landfill Gas over Time
The composition of landfill gas is likely to vary over the life of landfill, as a
consequence of both the stages of methanogenesis and landfill gas management
practices.
During both the early stages of degradation (such as the acidogenesis phase) and the
early part of the methanogenesis phase, the gas is likely to have a greater proportion
of CO2 in comparison to its methane content.163 Once the main phase of
methanogenesis is underway, the concentration of methane generally increases
relative to that of CO2 – influenced in part by the stoichiometry, as was described in
Section A.7.1. As methanogenesis slows the concentration of CO2 again rises relative
to the amount of methane.
Landfill management practices are also likely to influence the relative proportions of
the two gases over time. Once applied, the permanent cover of the landfill acts as a
barrier to moisture, reducing CH4 formation. At the same time, however, this will also
reduce the availability of leachate within which the remaining CO2 can dissolve.
163 Tchobanoglous G, Hilary T and Vigil S (1993) Integrated Solid Waste Management: Integrated
Principles and Management Issues, McGraw-Hill, New York