Historically, at the time of the first full-scale landfill gas recovery and utilization projects (1975-1980), predictive tools were developed to estimate the theoretical quantity of recoverable CH4 for commercial gas utilization projects (for example see EMCON Associates, 1980). These tools generally had two forms: (1) empirical 'rule of thumb' calculations for the annual recoverable CH4 based on the mass of waste in place, or (2) theoretical firstorder kinetic models of various forms that were used to predict the annual expected CH4 generation and recovery from annual landfilling rates. The original first-order models were site-specific. These models were fine-tuned and field validated with values for CH4 yields and kinetic coefficients that could replicate annual CH4 recovery at particular sites (for example the Scholl Canyon model for a southern California site). It is important to emphasize that, at that time, the focus was on tools for predicting commercially recoverable CH4 with the tacit assumption that both fugitive emissions and lateral migration would be minimized when active gas extraction was implemented.
From the mid- to late 1980s and into the early 1990s, there were still very few field measurements for landfill CH4 emissions in the published literature, although chamber techniques, as well as calculations based on gas concentration profiles and pressure gradients, were beginning to be applied. However, there were two developments that led to the extensive use of the firstorder kinetic models (with default values) to be applied specifically to landfill CH4 emissions, as opposed to their previous application to CH4 generation and recovery. These two developments included the mandated implementation of new comprehensive air-quality regulatory programmes in many developed countries and the 1988 formation of the IPCC, which, by 1991, included the development of the IPCC National Greenhouse Gas Inventories Programme (IPCC-NGGIP). The thinking at the time was that tools based on first-order kinetic models for landfill CH4 generation provided a conservative value (i.e. overestimate) for landfill CH4 emissions for both purposes. In most cases, the 'validation' of the modelling approaches involved a comparison of modelled results to landfill gas recovery data (Peer et al, 1993). Comprehensive Dutch studies in the early 1990s examined a variety of single and multi-component zero-order, first-order and second-order models, concluding that a multi-component first-order model (validated using data from nine full-scale Dutch landfills) was able to model gas recovery within 30-40 per cent of the actual measured recovery (Van Zanten and Scheepers, 1994).
In general, the IPCC Programme requires the development of methods and reporting of national emissions for UNFCCC member countries, with annual reporting requirements for the highly developed countries and less frequent reporting requirements for other countries. As landfills were recognized as one of the many sources of atmospheric CH4 (with early emissions estimates as high as 70Tg CH4 yr-1: Bingemer and Crutzen, 1987), it was therefore necessary to develop, in the absence of comprehensive field measurement programmes, standardized methods for estimating national landfill CH4 emissions. The thinking at the time was that both simple mass balance tools (where CH4 generation was assumed to occur in the same year as waste disposal) and first-order kinetic models with conservative default values (which were more suitable for developed countries with available waste data) could be used to provide conservative (high) estimates for CH4 emissions to the atmosphere.
The comprehensive 1996 IPCC National Inventory Revised Guidelines (IPCC, 1996) allowed both the use of a simple mass balance method as the Tier I default method as well as a Tier II first-order kinetic model (called FOD, or first-order decay model in this context). There were country-to-country differences in the national FOD models deployed under Tier II. Moreover, by 1996, the first study had been published which estimated annual fractional CH4 oxidation - Czepiel et al (1996b), working at the 17ha Nashua New Hampshire landfill without engineered gas recovery, calculated a value of 11 per cent for the Nashua site, based on field measurements of emissions, supporting laboratory incubations for CH4 oxidation, and the application of an annual climatic model. Thus, for developed countries, the 1996 guidelines allowed two subtractions from the estimated annual landfill CH4 generation: a 10 per cent subtraction for CH4 oxidation and the reported landfill CH4 recovery for either flaring or landfill gas utilization projects.
The latest 2006 National Inventory Revised Guidelines include a standardized Tier I multi-component FOD model for landfill CH4 emissions (EXCEL) with default input values for various waste fractions for landfills over a wide range of climatic conditions. Tier II encourages country-specific values. Tier III permits scaling-up of site-specific studies to regional estimates. Tier IV allows more complex site-specific modelling tools. The fraction of landfilled organic carbon that is biodegradable but not expected to degrade in the landfill (typically a conservative estimate of 50 per cent: Bogner, 1992; Barlaz, 1998) is reported as an information item within the waste sector, but credited to the harvested wood products sector (IPCC, 2006).
Some caveats are in order. In general, although the regulatory first-order kinetic models and the current Tier I/Tier II IPCC methodologies function as standardized tools, they cannot, without modification, be expected to replicate CH4 generation or recovery at specific field sites. Historically, first-order kinetic models have continued to be applied for initial estimates for commercial landfill gas recovery projects, then fine-tuned with respect to actual gas recovery when data are available from full-scale systems. Within Kyoto compliance mechanisms, the Tier I FOD models are widely applied for 'baseline' estimates within the approved consolidated landfill gas methodology (ACM0001) for the Kyoto Protocol Clean Development Mechanism (CDM). This 'flexible mechanism' permits entities in developed countries with Kyoto obligations to financially support greenhouse gas reduction projects in developing countries. However, it is important to emphasize that for landfill gas CDM projects, the actual CERs (certified emission reductions) are credited not on the model results but on rigorous site-specific quantification of the CH4 recovered and destroyed. However, there are also several 'avoided methane to landfill' CDM methodologies where CERs from alternative waste management projects (composting, incineration, mechanical-biological treatment) are credited solely on the basis of the waste composition and the model results. Given the many issues with the site-specific application of the FOD models for these 'avoided methane' applications, these methodologies need to be reconsidered with regard to their application after the end of the first Kyoto commitment period (2012).
Numerous field and laboratory studies during the last decade have improved our understanding of the actual range of landfill CH4 emission rates but added to the complexity of interpreting combined CH4 emissions and oxidation processes at specific sites within the context of Equation 15. With respect to oxidation, specifically, the available modelling tools for landfill applications were recently summarized by De Visscher and Spokas, as contributors to Scheutz et al (2009). In general, CH4 oxidation in landfill cover soils is a complex process involving simultaneous transport and microbial oxidation processes. Several types of models currently exist. These include simulation models for CH4 oxidation (for example Czepiel et al, 1996b) where the model simulates properties which cannot be measured directly. Also, existing models can be used to better understand specific aspects of oxidation processes in landfill cover soils; for example, Hilger et al (1999) and Wilshusen et al (2004) used models to understand how the formation of EPSs (extra-polymeric substances) affects transport and oxidation processes. Mahieu et al (2005) used models to understand stable isotope fractionation effects. Rannaud et al (2007) used a model to estimate the depth of CH4 oxidation. Finally, models can be used for prediction or design (for example De Visscher and Van Cleemput, 2003; Park et al, 2004; Rannaud et al, 2007). Typically, existing models have been calibrated with laboratory data and then used to predict or better understand field conditions.
Existing CH4 oxidation models for landfill settings generally fall into three types: empirical models, process-based models and the collision model. Empirical models (for example Czepiel et al, 1996b; Park et al, 2004) are assemblies of empirical equations based on measured data. These require little information on the fundamental microbial and transport processes but should not be extrapolated to other sites where field measurements are lacking. Process-based models (for example Hilger et al, 1999; Stein et al, 2001) combine mass transport equations with CH4 oxidation kinetics in a numerical scheme. Process-based models are potentially the most realistic models, but they generally require a large number of parameters that are difficult to obtain in field settings, which limits their usability. The collision model is an attempt to balance theoretical and empirical modelling by representing the processes occurring in a landfill cover as collisions between gas molecules and the soil (Bogner et al, 1997a).
The latest generation of landfill emission models is departing from the modelling of CH4 generation to simulating the actual soil and microbial processes controlling emissions. Currently, a model is being developed to provide an improved field-validated methodology for landfill CH4 emissions in California in the context of the state greenhouse gas inventory (Bogner et al, 2009; Spokas et al, 2009). This model is a Tier IV model under the current IPCC National Inventory Guidelines (2006) because it uses more complex site-specific methods, after which the results are summed to provide regional totals. This model also accounts for seasonal differences in climatic variables (air temperature, precipitation, solar radiation) and soil microclimate (soil temperature and moisture for layered soils) with respect to their quantitative influence on the seasonality of CH4 oxidation rates in cover soils. Using this model, Figure 11.4 illustrates the comparative effect of seasonal oxidation on CH4 emissions for a 60cm clay soil cover at a hypothetical Midwestern US landfill.
Was this article helpful?