sustainable biofuel operating space: multi-criteria assessment and multi-objective optimization
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Sustainable biofuel operating space: multi-criteria assessment and multi-objective optimization. Bioenergy Life-Cycle Analysis (4.6.2). Primary drivers for bioenergy include reducing demand for petroleum and emissions of greenhouse gases. - PowerPoint PPT PresentationTRANSCRIPT
Sustainable biofuel operating space: multi-criteria assessment and multi-objective optimization
Roberto C. Izaurralde, Xuesong Zhang
4.6-ModelingJoint Global Change Research InstitutePacific Northwest National Laboratory and University of Maryland
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.
Great Lakes Bio-Energy Research Center: Sustainability Thrust 4. Modeling Bio-Energy
Systems
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Sustainability Index
Establish minima or ideals
w1
w2
w3
w4
.
.
.
wi
SiClaudio Gratton
Safe operating space
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Johan RockstrOm (2009, Nature)
Landscape “services”
Claudio Gratton
An example of watershed planning
Handbook for Developing Watershed Plans to Restore and Protect Our Waters (USEPA, 2008)
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Multi-objective Optimization
Feasible Region
Time
Pareto front
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Multi-objective Optimization
A Multi ALgorithm Genetically Adaptive Method for multiobjective optimization (Vrugt et al. 2007, PNAS)
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Zhang et al., (2010, GCB Bioenergy)
SEIMF: Spatially-explict Integrative Modeling Framework
County
Watershed
Land use
Soils
Spatially-explicit simulations of N2O flux in Michigan RIMA
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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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SEIMF: Spatially-explict Integrative Modeling Framework
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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.