Ecosystem Modeling to Identify Low-Cost GHG Mitigation Opportunities in Heterogeneous Bioenergy Landscapes.

Careful siting of bioenergy feedstock cultivation areas and selection of optimal crop management techniques are essential for developing second-generation biofuel supply chains that maximize environmental benefits while minimizing indirect effects on food markets and maintaining economic viability.  Previous work has shown that ecosystem biogeochemical process models can be applied at fine scale to predict biomass yields and ecosystem greenhouse gas (GHG) balances for perennial grasses cultivated across gradients of land quality and under different levels of intensification (i.e., nitrogen fertilizer application), identifying a landscape x management interaction effect on the biogenic GHG intensity of feedstock production (i.e., Mg CO₂eq/Mg biomass produced).  The optimal design and performance of such a system is thus sensitive to underlying landscape heterogeneity, as well as to policy constraints on possible land use changes and to the relative weighting of environmental and economic outcomes.  In this work, high-resolution estimates of switchgrass productivity and associated soil GHG emissions balance (CO₂ and N₂O) are produced by applying the DayCent model spatially and in a third dimension representing management intensity across a real-world biofuel production landscape in the US Great Plains under different land use policy scenarios.  These results are then coupled with a crop production budget and a lifecycle assessment framework in order to identify the implications of different system designs for break-even biomass prices and supply chain lifecycle GHG mitigation.  A multi-criteria optimization approach based on non-market valuation of environmental impacts is employed to identify lowest-cost system GHG mitigation options.  These results and associated sensitivity analyses are useful for quantifying the relative merits of feedstock production on prime vs. marginal lands and associated optimal management practices, and help identify important areas to focus future bioenergy sustainability research efforts.