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Bioenergy has been globally recognized as one of the sustainable alternatives to fossil fuels. An assured supply of biomass feedstocks is a crucial bottleneck for the bioenergy industry emanating from uncertainties in land-use changes and future prices. Analytical approaches deriving from geographical information systems (GIS)-based analysis, mathematical modeling, optimization analyses, and empirical techniques have been widely used to evaluate the potential for bioenergy feedstock. In this study, we propose a three-phase methodology integrating fuzzy logic, network optimization, and ecosystem services assessment to estimate potential bioenergy supply. The fuzzy logic analysis uses multiple spatial criteria to identify suitable biomass cultivating regions. We extract spatial information based on favorable conditions and potential constraints, such as developed urban areas and croplands. Further, the network analysis uses the road network and existing biorefineries to evaluate feedstock production locations. Our analysis extends previous studies by incorporating biodiversity and ecologically sensitive areas into the analysis, as well as incorporating ecosystem service benefits as an additional driver for adoption, ensuring that biomass cultivation will minimize the negative consequences of large-scale land-use change. We apply the concept of assessing the potential for switchgrass-based bioenergy in Missouri to the proposed methodology.


Published Citation

Nguyen, Huynh Truong Gia, Erik Lyttek, Pankaj Lal, Taylor Wieczerak, and Pralhad Burli. "Assessment of switchgrass-based bioenergy supply using GIS-based fuzzy logic and network optimization in Missouri (USA)." Energies 13, no. 17 (2020): 4516.