Modeling Landfill Biogas Generation for Different Countries

Alex Stege, SCS Engineers

March 9, 2006

Landfill Methane to Markets Workshop

Delhi, India

2

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

2

3

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

3

4

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

4

5

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

5

6

Model Inputs

� Historic and projected waste disposal rates

� Methane decay rate (“k”)

� Methane generation potential (“Lo”)

� Collection efficiency

6

7

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”

7

8

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)

8

9

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”)

9

10

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

10

11

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

11

12

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%

12

13

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

13

14

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

14

15

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

15

16

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

16

17

PhitsanulokPhitsanulok LandfillLandfill

Thailand Landfill Site Visits

KampangKampang PhetPhet ControlledControlled Dump SiteDump Site

17

18

NonthaburiNonthaburi Open Dump SiteOpen Dump Site

Thailand Landfill Site Visits

NonthaburiNonthaburi Open Dump SiteOpen Dump Site

18

19

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

19

20

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

20

21

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

21

22

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

22

23

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

23

24

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

24

25

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)

25

26

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)

26

27

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

27

28

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

28

29

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

29