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United States Department of Agriculture

Agricultural Research Service

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Research Project: International Field Validation of a New Ipcc "tier Iv" Inventory Model for Landfill Methane Emissions

Location: Soil and Water Management Research

Project Number: 3640-12000-008-10
Project Type: Reimbursable

Start Date: Jan 01, 2011
End Date: Jun 30, 2013

Objective:
1. To develop an improved methane inventory model for the U.S. by expanded field validation of the CALMIM model (California Landfill Methane Inventory Model) using existing emissions/oxidation data from U.S. research projects (i.e.,WMX; Veolia). CALMIM is the first model of its type accounting for annual soil microclimate conditions and prediction of the impact of microbial methane oxidation activity of greenhouse gas emission. 2. To develop an improved methane inventory model for international application under the current IPCC National Inventory Methodology for Waste (IPCC, 2006) using existing field measurements for landfill methane emissions and oxidation by several research groups in Europe, Australia, and Africa.

Approach:
Based on a high level of U.S. and international interest in improved methods to replace historic landfill methane generation modeling with a model specifically for emissions inclusive of seasonal methane oxidation, this proposed project is a cost-effective extension and expansion of the model developed under a prior project (ARS project # 3645-11000-003-01R, Improved GHG Inventory Methods for California). As developed, the freely-available user-friendly JAVA model for California (CALMIM, California Landfill Methane Inventory Model) is an IPCC (Intergovernmental Panel on Climate Change) “Tier IV” model using “advanced methods” for site-specific emissions which are summed to provide regional inventory data. As a logical follow-up, we are now proposing to facilitate a broader U.S. and international field validation with a structured project to match existing and continuing international datasets for emissions and oxidation to the existing model, and fine-tune the modeling, as appropriate, for application to the U.S. as a whole and internationally.

Last Modified: 8/22/2014
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