LFG Energy Project Development Handbook 2-1 

# 2. Landfill Gas Modeling

Chapter Overview
Landfill gas (LFG) modeling is the practice of fore casting gas generation and recovery based on past and future waste disposal histories and estimates of collection system efficiency. LFG modeling is an important step in the project development process, because it provides an estimate of the amount of recoverable methane that will be available over time to fuel an LFG energy project.
LFG modeling is performed for regulatory and non-regulatory purposes. Regulatory applications of LFG models for U.S. landfills are conducted to estimate emissions of LFG and its constituents, including non-methane organic compounds (NMOCs). These emissions estimates establish the requirements for gas collection and control system installation and operation. The modeler inputs landfill-specific waste disposal estimates but uses values for input variables (e.g., the methane generation rate) as determined by applicable regulations.
Non-regulatory applications of LFG models typically include any of the following:



### C Evaluating LFG energy project feasibility



### C Determining gas collection and cont rol system design requirements



### C Performing due diligence evaluations of potential or actual project performance
This chapter covers non-regulatory LFG modeling applications only. EPA does not intend for the material presented in this handbook to supersede or replace required procedures for preparing LFG models for regulatory purposes. Federal regulations such as the New Source Performance Standards (NSPS) require modeling to determine rule applicab ility and compliance. For regulatory applications, the modeler must use the specific procedures, default values, and test methods prescribed in the rule. Refer to the appropri ate regulations (e.g., the NSPS [40 CFR part 60 subpart WWW] and related documentation ) for details.


## 2.1 Introduction to LandGEM
The most widely used LFG model is EPA’s Landfill Gas Emissions Model (LandGEM). LandGEM is the industry standard model for regulatory and non-regulatory applications in the United States. The latest version of LandGEM (v. 3.02) was released in May 2005. This section provides an introduction to LandGEM and the first order decay equation and variables employed by the model.

The First-Order Decay Equation LandGEM is a first order decay model. First or der decay models assume that landfill methane generation is at its peak shortly after initial wa ste placement (after a short time lag during which anaerobic conditions are established in the landfill). They also assume that landfill methaneLFG Energy Project Development Handbook 2-2 generation then decreases exponentially (i.e., first order decay) as the organic material in the waste decreases as it is degraded by bacteria in the landfill.
LandGEM assumes that landfill methane generation can be projected using the following first order exponential equation:


## Q CH4 

## = k L 

#  

= = n

i j

1 1

1.0 o 

## (M i 

## /10) (e -kt ij 

## )
Where: Q CH4 = estimated methane generation flow rate (in cubic meters [m 3 ] per year or average cubic feet per minute [cfm]) i = 1-year time increment n = (year of the calculation) – (initial year of waste acceptance) j = 0.1-year time increment k = methane generation rate (1/year) L o = potential methane generation capacity (m 3 per megagram [Mg] or cubic feet per ton) M i = mass of solid waste disposed in the i th year (Mg or ton)
t ij = age of the j th section of waste mass disposed in the i th year (decimal years) LandGEM calculates methane generation using the fi rst order decay equation shown above, and it calculates LFG generation by dividing methane generation by the estimated percent methane. The default methane content is 50 percent, which is both the industry standard value and LMOP’s recommended default value.

Model Inputs Of the several variables in the first order decay equation used by LandGEM, only three (M i , L 0 , and k) require user inputs. The user assigns these variables in a “USER INPUTS” worksheet in LandGEM. The following sections describe the three variables and their effects on estimated LFG generation.
Annual Waste Disposal Rates (M i ) . Estimated waste disposal rates are the primary determinant of LFG generation in any first order decay-based mode l, including LandGEM. LandGEM does not adjust annual waste disposal estimates to account for waste composition. Adjustments to account for waste composition are typically handled by adjustments to the L 0 value. Potential Methane Generation Capacity (L 0 ). The potential methane generation capacity, or L 0 , describes the total amount of methane gas potentially produced by a metric ton of waste as it decays. The values of the theoretical and obtainable L 0 range from 6.2 to 270 cubic meters per metric ton or megagram (m 3 /Mg) of waste. 1 Except in dry climates where lack of moisture can limit methane generation, the value for the L 0 depends almost entirely on the type of waste present in the landfill. The higher the organic content of the waste, the higher the value of L 0 . Note that the dry

1 U.S. EPA. 1991. Air Emissions From Municipal Solid Waste Land fills — Background Information for Proposed Standards and Guidelines. EPA-450-3-90-011a. p. 3-22.LFG Energy Project Development Handbook 2-3 organic content of the waste determines the L 0 value, not the wet weight measured and recorded at landfill scalehouses, since water does not generate LFG. Methane Generation Rate Constant (k ) . The methane generation rate constant, k, describes the rate at which waste placed in a landfill decays and prod uces LFG. The k value is expressed in units of year -1 . At higher values of k, the methane generation at a landfill increases more rapidly (as long as the landfill is still receiving waste), and then declin es more quickly after the landfill closes. The value of k is a function of (1) waste moisture content, (2) availability of nutrients for methane-generating bacteria, (3) pH, and (4) temperature. Figure 2-1 shows an example gas curve for a landfill with approximately 2 million tons waste-in-place expected at closure. The potential gas generation was modeled in two scenarios, using identical landfill parameters except that k was varied between a value for arid conditions (0.02 yr -1 ) and a value for wet conditions (0.065 yr -1 ). The graph demonstrates the significant difference in gas generation that can occur based on moisture conditions at the site. 

## Figure 2-1. LFG Generation Variance by k Value

0 500 1,000 1,500 2,000200220072012201720222027203220372042

YearLFG Generation (scfm)

k=0.065

k=0.02

Moisture conditions within a landfill strongly influe nce k values and reflect the climate at the site as well as the contents of disposed waste and landfi ll design and operating practices. Waste decay rates and k values are very low at desert sites, te nd to be higher at sites in wetter climates, and reach maximum levels under moisture enhanced “b ioreactor” conditions. An nual precipitation is often used as a surrogate for waste moisture due to the lack of information on moisture conditions within a landfill. Air temperature can also affect k values, but to a lesser extent. Internal landfill temperatures are relatively independent of outside temperatures and typically remain in the range of approximately 30 to 60°C (85 to 140°F) except at shallow, unmanaged landfills in very coldLFG Energy Project Development Handbook 2-4 climates (e.g., landfills located in areas above 50 degrees latitude). For such landfills, waste decay rates and k values tend to be lower.
The k value can also be expressed as a half-life, t 1/2 . The half-life is the time required for half of the remaining methane generation potential to be produced (i.e., half of the deposited waste to decay and produce LFG).

Refer to the LandGEM User’s Manual for additional details on model use.

Model Outputs
LFG Generation

. After the model inputs are selected, the user can turn to the “RESULTS” worksheet in LandGEM to find model outputs. The outputs include annual waste inputs, waste-in-place, and generation of total LFG, methane, carbon dioxide, and NMOCs. LFG and methane generation estimates are the output parameters that are used for non-regulatory LFG predictions. Once the LFG and methane generation is estimated, the collection efficiency must be estimated to determine the expected amount of LFG available for an LFG energy project. 

## 2.2 Estimating LF G Gas Recovery

Estimating Collection Efficiency Collection efficiency is a measure of the gas collection system’s ability to capture generated LFG. The LFG generation predicted by the model can be multiplied by the percent collection efficiency to estimate the volume of LFG that can be recovered for flaring or use in an LFG energy project. Although rates of LFG capture can be measured, rates of generation in a landfill cannot be measured; therefore, considerable uncertainty exists regarding actual collection efficiencies achieved at landfills.
To help address the uncertainty surrounding collection efficiencies, EPA has published estimates of reasonable collection efficiencies for U.S. landfills that meet U.S. design standards 2 and that have “comprehensive” gas collection sy stems. EPA defines a “comprehensi ve” LFG collection system as a system of vertical wells and/or horizontal collectors providing 100 percent collection system coverage of all areas with waste within one year after the waste is deposited. According to EPA, collection efficiencies at such landfills typically range from 60 to 85 percent, with an average of 75 percent most commonly assumed. 3 Most landfills, particularly those that are still receiving wastes, will have less than 100 percent collection system coverage. In such cases, LFG modelers commonly use a “coverage factor” to adjust the estimated collection efficiency. The coverage factor adjustment is applied by multiplying the collection efficiency by the estimated percentage of the fill areas with

2 Landfills that meet or exceed the requirements in the 40 CFR Parts 257 and 258 RCRA Subtitle D Criteria.

3 U.S. EPA. 1998. Volume 1, Chapter 2, Sect ion 2.4: Municipal Solid Waste Landfills. In AP42 Compilation of Air Pollutant Emission Factors. Fifth Edition. p. 2.4-6. http://www.epa.gov/ttn/chief/ap42/ch02/final/c02s04.pdf

.LFG Energy Project Development Handbook 2-5 wells. This adjustment also should be applied to areas where wells are not fully functioning or are watered in.
Collection efficiency estimates for sites with an operating gas collection and control system are typically based on information regarding current or re cent conditions. Historical and future collection efficiency estimates can be made based on current conditions or other information regarding historical and planned collection system installations/expansions. Collection efficiency usually increases after site closure when disposal operations no longer interfere with LFG system operations and a final cover is installed. Sites without collect ion systems installed are typically assumed to be planning to install a comprehensive system, unless there is site-specific information to suggest a different value.
Estimating LFG Recovery The final step in the modeling process is to calculate LFG recovery based on LandGEM projections of LFG generation and the modeler’s estimated collection efficiency. This step is done outside LandGEM and can be accomplished by setting up a spreadsheet that provides the LFG generation estimates, the collection efficiency estimates, and LFG recovery estimates (product of generation and percent efficiency). Table 2-1 shows a recommended format for displaying results and the waste disposal estimates on which they are based. 

## Table 2-1. LFG Generation and Recovery Projection s Disposal

Rate Wastein-Place LFG Generation Collection Efficiency LFG Recovery Year (tons/year) (tons) (scfm) (m 3 /hr) (%) (scfm) (m 3 /hr)
Year 1 Year 2 Year 3 Year X (final year modeled) scfm: standard cubic feet per minute
The LFG recovery projections can also be displaye d graphically. Both LFG generation and recovery can be displayed as line graphs in an “X-Y scatter” graph, showing LFG flow at 50 percent methane (Y-axis) in each year since the landfill opened (X-a xis). For sites with operating collection systems and recovery data, the graph can be used to display ac tual recovery as dots. The graph can be used to compare projected to actual recove ry for model calibration, which involves adjusting model k and L 0 values so that the projected LFG recovery rates closely match actual recovery. 4 Figure 2-2 shows a

4 This handbook does not cover procedures for model calibration. LMOP recommends seeking the help of an experienced professional LFG modele r to perform model calibration.LFG Energy Project Development Handbook 2-6 sample model output graph for a landfill that open ed in 1980, installed a gas collection system in 2003, 5 and will stop accepting waste at the end of 2011. 

## Figure 2-2. LFG Generation and Recovery Rates

Actual LFG Recover y Projected LFG Recover y LFG Generation 2030 2025 2020 2015 2010 2005 2000 1995 1990 1985 1,200 LFG Flow at 50% Methane (scfm)

1,000

600

400

0 1980

Special Considerations for Bioreactor and Leachate Recirculation Landfills In recent years, certain landfills have been desi gned and managed to deliberately introduce liquids into the waste in a controlled manner. This is done in order to speed up the waste decay process and shorten the time period of LFG generation. Landfills that achieve 40 percent moisture content in the waste through the controlled introduction of liquids (other than leachate and condensate) are considered “bioreactor” landfills according to EPA air regulations. 6 Landfills that introduce liquids (most commonly leachate and condensate) but achieve waste moisture contents less than 40 percent are considered “leachate recirculation” landfills. Bioreactor studies conducted by EPA’s Office of Research and Developmen t provide additional information.
The introduction of liquids into the landfill causes significant increases in waste decay rates and k values. This increase in k will cause gas generation to increase more rapidly while the landfill is receiving waste and decrease more rapidly once disposal stops, but will not change total LFG generation over the long term. Because only the rate of LFG generation is affected, L 0 values should theoretically be unaffected by liquids introducti on. LandGEM provides a default k value of 0.7 for modeling bioreactor landfills (i.e., the “inventory wet” value). LMOP, howe ver, recommends assigning

5 LFG recovery starts at known or projected date of th e installation of the gas collection and control system.

6 “Bioreactor” is defined in the muni cipal solid waste landfill National Em ission Standards for Hazardous Air Pollutants, 40 CFR part 63, subpart AAAA.LFG Energy Project Development Handbook 2-7 a k value of 0.3 for bioreactors based on a University of Florida study completed shortly after LandGEM was released. No single k value is recommended or appropriate for leachate recirculation landfills because the impact of leachate recircula tion on LFG generation varies depending on the amount of liquids added and the moisture content of waste achieved.
Sometimes, only a portion of a landfill’s total si te is designed and operated as a bioreactor or leachate recirculation landfill. In such cases, the bioreactor or leachate recirculation portion should be modeled separately from the remainder of the site, using waste disposal inputs for these areas only.


## 2.3 Model Limitations
Various factors can affect the accuracy of LFG recovery projections:



### C Limited or poor quality disposal data

. Significant model error can be introduced if good disposal data are not available.



### C Atypical waste composition

. Waste composition data are often not available to determine if unusual waste composition is a cause of model inaccuracy.



### C Poor quality flow data and/or inaccurate estimates of collection efficiency used for model calibration. Model calibration requires both accurate estimates of collection efficiency and good quality flow data that are representative of long-term average recovery.



### C Inaccurate assumptions

. Inaccurate assumptions about variables such as future disposal rates, site closure dates, wellfield buildout, ex pansion schedules, or collection efficiencies can result in large errors in predicting future recovery.



### C Limitations due to the structure of LandGEM

. For example, LandGEM cannot accommodate changes in k or L 0 values in the same model run. Changing landfill conditions that cannot be modeled as a result of this limitation include the following:



### < Application of liquids to existing waste



### < Variations in waste composition over time



### < Installation of a geomembrane cover The LFG modeler should be aware of the potential for model error due to the above-listed factors and use appropriately conservative model inputs to avoid significant overestimation of LFG recovery. Accurate estimates that do not overestimate recoverable methane are critical to the proper design and financial success of LFG energy projects.