2020
DOI: 10.3390/en13174516
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Assessment of Switchgrass-Based Bioenergy Supply Using GIS-Based Fuzzy Logic and Network Optimization in Missouri (U.S.A.)

Abstract: 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 … Show more

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Cited by 4 publications
(2 citation statements)
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“…A base point describes the location of the depot, whose accessibility is determined by a cut-off distance. We used a distance of 150 miles (240 km) as suggested by the Federal Motor Carrier Safety Administration (FMCSA) for a truck carrying agricultural products [84]. This represents a Euclidean distance specifying a radius within which the feasibility and profitability of feedstock supply are most likely.…”
Section: Resultsmentioning
confidence: 99%
“…A base point describes the location of the depot, whose accessibility is determined by a cut-off distance. We used a distance of 150 miles (240 km) as suggested by the Federal Motor Carrier Safety Administration (FMCSA) for a truck carrying agricultural products [84]. This represents a Euclidean distance specifying a radius within which the feasibility and profitability of feedstock supply are most likely.…”
Section: Resultsmentioning
confidence: 99%
“…More complex zoning models have integrated GIS applications and different approaches such as life cycle assessment (LCA) for the sustainable bioenergy planning of agriculture residues, taking into account its environmental impact potential [36] and dynamic yield simulation models; for determining regional bioenergy potentials [37], fuzzy logic, network optimization, and dynamic yield simulation models; and for determining regional bioenergy potentials [38].…”
Section: Introductionmentioning
confidence: 99%