49-3 Soil Biogeochemical Modeling for Optimal GHG-Mitigating Biomass Feedstocks.

See more from this Division: Agriculture and Natural Resources Science for Climate Variability and Change: Transformational Advancements in Research, Education and Extension
See more from this Session: Carbon, Nitrogen, Energy and Water Footprints In Agriculture Production: Changing Practices and Opportunities
Monday, October 22, 2012: 1:35 PM
Duke Energy Convention Center, Junior Ballroom B, Level 3
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John L. Field, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, Thai N. Dinh, School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK and Keith Paustian, Natural Resource Ecology Laboratory/Department of Soil and Crop Science, Colorado State University, Fort Collins, CO
Biofuels are actively promoted in the United States as a strategy for improving domestic energy security and reducing greenhouse gas (GHG) emissions in the transportation sector, and sustainability standards associated with domestic biofuel mandates require that future production of conventional, advanced, and cellulosic biofuels meets GHG mitigation targets as evaluated through standardized lifecycle assessment (LCA) techniques.  LCA of first-generation biofuels is complicated by the need to consider nonpoint source emissions of CO2, N2O, and CH4 associated with feedstock cultivation, emissions that vary with local climate, soil type, land use history, and farm management practices.  This spatial variability and associated uncertainties are expected to be even greater for new dedicated biomass crops (e.g. switchgrass, Miscanthus) for cellulosic ethanol production.   We present a spatially-explicit LCA methodology based on the DayCent soil biogeochemistry model capable of accurately evaluating feedstock cultivation emissions for both conventional and cellulosic biofuels.  This methodology considers soil GHG emissions associated with crop switching and agricultural intensification/extensification, as well as the embodied emissions of agricultural inputs and fuels used for field operations and biomass transport to a centralized collection point (biorefinery or transportation hub).  Model results are incorporated into a biomass production cost analysis.  A heuristic optimization routine then identifies optimal cultivation areas and collection point location, facilitating the design of bioenergy landscapes that maximize GHG emissions mitigation at lowest possible cost.  Preliminary analysis results are presented for an illustrative case study of switchgrass production to supply a commercial-scale cellulosic ethanol plant currently under construction in the Great Plains.  This case study supports a larger effort to mobilize this methodology into a web-based, user-friendly tool allowing farmers, academics, and biorefinery facility owners to investigate the effects of management choices and facility siting on system GHG performance, and advancing the state-of-the-art for regulatory assessment tools in the bioenergy sector.
See more from this Division: Agriculture and Natural Resources Science for Climate Variability and Change: Transformational Advancements in Research, Education and Extension
See more from this Session: Carbon, Nitrogen, Energy and Water Footprints In Agriculture Production: Changing Practices and Opportunities