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Sustainable biofuel operating space: multi-criteria assessment and multi-objective optimization Roberto C. Izaurralde, Xuesong Zhang 4.6-Modeling Joint Global Change Research Institute Pacific Northwest National Laboratory and University of Maryland
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Bioenergy Life-Cycle Analysis (4.6.2) Primary drivers for bioenergy include reducing demand for petroleum and emissions of greenhouse gases. Life-cycle analysis (LCA) estimates the overall contribution of bioenergy system towards meeting these objectives. LCA evaluates the entire process (i.e., field to wheels) including all upstream and downstream energy and material inputs and associated greenhouse gas emissions Evaluate bioenergy pathways that are cost-effective and sustainable relative to net greenhouse gas impact, long-term soil quality, and ecosystem impacts.
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Great Lakes Bio-Energy Research Center: Sustainability Thrust 4. Modeling Bio-Energy Systems
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www.glbrc.org 5 Sustainability Index Establish minima or ideals w 1 w 2 w 3 w 4. w i SiSi Claudio Gratton
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Safe operating space www.glbrc.org 6 Johan RockstrOm (2009, Nature)
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Landscape “services” Claudio Gratton
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An example of watershed planning Handbook for Developing Watershed Plans to Restore and Protect Our Waters (USEPA, 2008)
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www.glbrc.org 9 Multi-objective Optimization Feasible Region Price Time Solutions (Itineraries) Pareto front
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www.glbrc.org 10 Multi-objective Optimization A Multi ALgorithm Genetically Adaptive Method for multiobjective optimization (Vrugt et al. 2007, PNAS)
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www.glbrc.org 11 Zhang et al., (2010, GCB Bioenergy) SEIMF: Spatially-explict Integrative Modeling Framework County Watershed Land use Soils
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Spatially-explicit simulations of N 2 O flux in Michigan RIMA
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www.glbrc.org 13 Optimizing ecosystem services of bioenergy crop configurations Optimization the configuration of the 54 scenarios on 39 10-digit watershed in Michigan RIMA 54^39 (3.65895E+67) Different multi-objectives
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www.glbrc.org 14 SEIMF: Spatially-explict Integrative Modeling Framework
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www.glbrc.org 15 Conclusions Multi-objective optimization can provide promising candidate biofuel crop landscape configurations for multi-criteria assessment of sustainability. Spatially-explicit variables (e.g. carbon and yield) related to LCA assessment Spatially-explicit modeling map can be used to calculate the distance from crop fields to biorefinery and transportation cost for LCA.
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