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United States Department of Agriculture

Agricultural Research Service

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Research Project: USDA AGRI AND FORSTRY GREENHOUSE GAS INVENT. AND EVALUATE THE POTENTIAL OF DIFF. CROPPING SYSTEMS, INCL. BIOFUELS, TO MITIGATE GHG EMISSIONS

Location: Soil Plant Nutrient Research (SPNR)

Project Number: 3012-11000-010-02
Project Type: Specific Cooperative Agreement

Start Date: Jul 01, 2009
End Date: Jun 30, 2014

Objective:
To assist ARS in producing the U.S. Agriculture and Forestry Greenhouse Gas Inventory and assess the impacts of different crop management practices at the national scale. These efforts will facilitate collaborative efforts between ARS and CSU to continue simulation model development, testing, and refinement of input data to predict the impacts of changing climate and management on greenhouse gas (GHG) emissions, crop yields and soil carbon content.

Approach:
Major products so far include the 2nd edition of the USDA GHG inventory published in 2008 and development of the GRACEnet data entry template. Major improvements in the 2nd edition of the inventory include more refined partitioning of GHG sinks and sources, better quantification of uncertainty and more accurate emission estimates, and quantification of mitigation potentials. Model improvements, tests, and applications used to generate data for the inventory have been reported in 12 journal and several presentations at meetings and symposia. The DAYCENT model was used to perform life cycle analysis for different biofuel cropping systems and initial tests were conducted to implement high resolution NRI data for future GHG inventory simulations. In addition to producing and improving future editions of the USDA GHG Inventory, general goals for the next 5 years include evaluating biofuel cropping systems and investigating how changes in land use and climate impact crop yields and GHG fluxes. Production and improvement of the U.S. Agriculture and Forestry Greenhouse Gas Inventory requires applying and improving the models used to calculate emissions and their associated uncertainty ranges. Use of more refined model input data, further comparison of model outputs with field measurements, and increased computing capacity lead to more accurate national scale estimates and better characterization of the regional and temporal patterns of emissions. ARS will interact with CSU to incorporate programming expertise, high capacity computing clusters, and data collection into the inventory analyses. CSU will assist ARS in evaluating the impacts and feasibility of different cropping systems, including biofuels by implementing and testing the ability of models to represent the impacts of improved N management technologies and perform regional analysis to identify local best management practices.

Last Modified: 12/27/2014
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