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Modeling Landfill Biogas Generation for Different Countries
Alex Stege, SCS Engineers
March 9, 2006
Landfill Methane to Markets Workshop
Delhi, India
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PresentationTopics
� Landfill biogas modeling overview
� Challenges of international biogas modeling
� Lessons learned from LMOP biogas modeling projects: Mexico and Thailand
� Using biogas modeling to evaluate suitability of landfills in India for project development
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Need for InternationalLandfill Biogas Modeling
� Ratification of Kyoto Protocol has accelerated pace of landfill biogas project development, particularly in developing countries (CDM)
� U.S. EPA’s Methane to Markets Partnership will further promote landfill biogas-to-energy projects internationally
� Good estimates of landfill biogas recovery needed to evaluate project feasibility and economics – Methane emission reductions – large source of
revenue – International landfill biogas modeling in infancy –
large source of error in evaluating projects
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Landfill Biogas Generation
� Factors affecting amount of landfill biogas production: – amount of waste
– type of waste
– age of waste
– moisture content
– temperature
– pH
– site conditions
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Landfill Biogas Model
� Most widely used model is the U.S. EPA’s “Landfill gas generation model” (LandGEM)
� Model equation estimates annual landfill biogas generation
� Model estimates annual landfill biogas recovery
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Model Inputs
� Historic and projected waste disposal rates
� Methane decay rate (“k”)
� Methane generation potential (“Lo”)
� Collection efficiency
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Model Equation
� Landfill biogas generation equation:
n
∑ 2 k L0 M e-kti i=1
where:
k = refuse decay rate (1/yr) L0 = methane generation potential (m3/tonne)
M = mass of waste deposited (tonnes) in year “i” ti = age of waste (years) in year “i”
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Model Inputs – Methane Generation Potential (Lo)
� “L0” – methane generation potential (units = m3
methane per metric tonne of waste) – Total amount of methane 1 tonne of waste produces
– Is mainly a function of waste composition – amount of organic waste
� Range of observed values: - 0 - 312 m3 methane/tonne of waste
- U.S. EPA default for U.S. landfills is 100 m3/tonne (not 170 m3/tonne, which is regulatory value)
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Model Inputs – Rate Constant (k)
� “k” – refuse decay rate constant (units = 1/year)– Sets rate of waste decay and methane production
– Influenced by waste moisture – use annual rainfall
� Range of observed values: – 0.01/year (desert landfills) to 0.4/year (“bioreactors”)
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Effect of Varying k
LF
G F
low
at
50%
Met
han
e (m
3/h
r)
Biogas Generation from a 24,000,000 Tonne Landfill
25,000
20,000
15,000
10,000
5,000
0
1990 1995 2000 2005 2010 2015 2020 2025 2030
k=0.16 k=0.08 k=0.04
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Model Inputs – Collection Efficiency
� Collection efficiency = Amount of landfill biogas collectedAmount of landfill biogas generated
� Collection efficiency based on: – Type of facility (landfill vs. dump)
– Type/design of collection system
– Extent collection system covers waste volume
– Waste characteristics – permeability
– Collection system operation
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Landfill Biogas Recovery Rate
� Landfill biogas recovery = landfill biogas generation x collection efficiency
� Achievable collection efficiencies at disposal sites: – Engineered and sanitary landfills: ~60-90%
– Open and controlled dump sites: ~30-60%
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Challenges of International Landfill Biogas Modeling
� Differences in waste composition – Developing countries have higher % of food waste
and plastics
– Developed countries have more paper and wood
– Effects on model parameters (k and L0)
– U.S. based first order model (LandGEM) may be less accurate for developing countries
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Challenges of International Landfill Biogas Modeling
� Differences in landfill design & operations – developing countries: – Excess rainfall infiltration
– Often shallow sites; limited soil cover
– Effects on timing of landfill biogas generation
– Effects on achievable collection efficiency
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LMOP Landfill Biogas Model for Mexico
� Partnership between U.S. Government and Mexico.
� Model is based on the LandGEM, with modifications to the k and Lo values to be suitable for Mexico’s landfills.
� Model use demonstrated at Monterrey workshop in December 2003 – Model and user’s manual provided
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Thailand Project� Partnership with World Bank
� Evaluated project feasibility through the preparation of landfill biogas models for 56 disposal sites
� World Bank Landfill Biogas Training Workshop, Bangkok: April 29-30, 2004 – Presented results of modeling work – Conducted workshop on landfill biogas utilization
� Landfill site visits: April and May 2004
� Revisions to models for selected sites based on observed site conditions
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PhitsanulokPhitsanulok LandfillLandfill
Thailand Landfill Site Visits
KampangKampang PhetPhet ControlledControlled Dump SiteDump Site
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NonthaburiNonthaburi Open Dump SiteOpen Dump Site
Thailand Landfill Site Visits
NonthaburiNonthaburi Open Dump SiteOpen Dump Site
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Lessons Learned: Model Problem #1
� Model less accurate when waste stream is very different from U.S.
� Very high food waste (56%) component in Thai waste causes very rapid decay – Food waste includes high water (inert) weight, which
requires using a lower Lo
– Use of a low k may under-estimate peak and over-project long-term potential after site closure
– Use of high k may over-estimate peak
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Solution to Model Problem #1
� Adjust Lo to account for water (inert) weight as well as organic content of waste – U.S. default Lo = 100 m3/tonne
– Thai Lo = 78.4 m3/tonne
– Delhi Lo = 64.3 m3/tonne
– Mumbai Lo = 68.7 m3/tonne
� Develop composite model with 3 k values: – Fast-decay organic waste (food); k = 0.1 to 0.4
– Medium-decay organic waste (paper); k = 0.02 to 0.08
– Slow-decay organic waste (textiles); k = 0.005 to 0.02
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Lessons Learned:Model Problem #2� Model less accurate when landfill design (dump
sites) very different from U.S.
� Site visits found broad, shallow fill areas and/or little soil cover – Delays in start of anaerobic conditions
– Problems and/or delays in achieving expected collection efficiency
– LandGEM assumes generation follows 1 year lag after waste placement, with no waste decay during this period
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Solution to Model Problem #2
� Incorporate delays in landfill biogas generation and recovery into model – Assume aerobic waste decay until adequate waste
depth or soil cover to create anaerobic conditions
– Assume additional delays in new sites until waste depth adequate for installing extraction wells
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Lessons Learned:Model Problem #3
� Leachate buildup common problem in developing countries
� High rainfall and waste moisture content, and poor runoff control lead to liquid build-up – Vertical extraction wells become ineffective when filled
with leachate
– Significant declines in collection efficiency
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Solution to Model Problem #3
� Need to use conservative model collection efficiency assumptions
� Field investigations (pump test) can indicate extent of leachate problem
� Modifications to collection system design to address leachate problems: – Equip vertical wells with leachate pumps
– Greater reliance on horizontal collectors
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Assessing Project Potential –Gorai Landfill, Mumbai
LANDFILL GAS RECOVERY POTENTIALGORAI LANDFILL, MUMBAI, INDIA
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000 L
FG
Flo
w a
t 5
0%
CH
4 (
m3
/ho
ur)
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
CE
Rs
per
Yea
r (t
on
nes
CO
2e)5000 m
3/hr = ~44 million m
3/year
1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025
LFG Recovery Potential - Composite (3-k) Model
LFG Recovery Potential - Simple Model (k=0.10)
Predicted LFG Recovery (65-75% of potential)
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Assessing Project Potential –Gazipur Landfill, Delhi
LANDFILL GAS RECOVERY POTENTIALGAZIPUR LANDFILL, DELHI, INDIA
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000 L
FG
Flo
w a
t 50
% C
H4
(m3/
hou
r)
0
50,000
100,000
150,000
200,000
CE
Rs
per
Yea
r (t
onn
es C
O2e
)
4000 m3/hr = ~35 million m
3/year
1985 1990 1995 2000 2005 2010 2015 2020 2025
LFG Recovery Potential - Composite (3-k) Model
LFG Recovery Potential - Simple Model (k=0.04)
Predicted LFG Recovery (75% of potential)
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Conclusions
� LMOP providing technical assistance workshops promoting international landfill biogas projects – Development of an landfill biogas model for Mexico – Landfill biogas modeling and project feasibility
assessment for Thailand sites – Model can be applied to India sites – Gorai and
Gazipur examples
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Conclusions
� Large uncertainties in international landfill biogas modeling despite growing demand – Need models to account for varying waste
composition and site characteristics
– Collection efficiency estimates need to account for leachate in extraction wells
– Field testing can provide site-specific information and lower uncertainties
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Next Steps and for More Information
� Market/tailor LMOP’s international landfill biogas model and training to developing countries (www.methanetomarkets.org)
� Mexico landfill biogas model available at: www.epa.gov/lmop/international.htm
� World Bank information on Thailand available at: www.worldbank.or.th
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