1a.Objectives (from AD-416):
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.
1b.Approach (from AD-416):
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.
This was the final year of this project. This year the computer model was updated with additional user features. These updates included: integrated Google Map functionality for site selection and improved the flow/calculation of the model algorithms. Samples from a field site in Indianapolis were analyzed to allow further field validation data to be collected. Discussions have been ongoing with international collaborators to collect data for model validation.
This project relates directly to Objective 2a and 2b of the parent research project.