Assessment of Switchgrass-Based Bioenergy Supply Using GIS-Based Fuzzy Logic and Network Optimization in Missouri (U.S.A.)

Huynh Truong Gia Nguyen,Pankaj Lal,Pralhad Burli,Taylor Wieczerak,Erik Lyttek

doi:10.3390/en13174516

Huynh Truong Gia Nguyen, Pankaj Lal + Show 3 more

Open Access

https://doi.org/10.3390/en13174516

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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 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.

Highlights

Bioenergy has been recognized as one of the sustainable alternatives to fossil fuels, and the quantification of bioenergy potential is an essential field of research
In scenario 1, where only marginal land, fallow, and idle crops were selected, the suitable area accounted for approximately 4755.6 hectares, equivalent to a 74% increase in current switchgrass plantings
We used the combination of fuzzy logic and network optimization to evaluate potential switchgrass-based biomass supply and applied the InVEST ecosystem service approach to validate our selection for land cover transitions in Missouri

Summary

Introduction

Bioenergy has been recognized as one of the sustainable alternatives to fossil fuels, and the quantification of bioenergy potential is an essential field of research. The design of the biomass supply chain is a major stumbling block for bioenergy and includes three spatially interlinked elements, including (i) resource assessment, (ii) logistic planning, and (iii) biorefinery design [1] Perennial biomass crops, such as switchgrass (Panicum virgatum L.), face adoption challenges owing to the considerable time required to establish the plant and uncertainties associated with land-use change and price fluctuations [2,3,4]. An inadequate volume of potential biomass feedstocks presents a barrier; Richard et al suggested that ethanol production at the commercial level is challenged by the low density of biomass feedstock across the landscape [5,6] This situation has led investments in the bioenergy industry to be described as a chicken-and-egg problem, wherein investment in feedstock processing and fuel production is not forthcoming due to uncertainty in feedstock supply, while farmers. For applying network analyses in the case study, we used a detailed street map, which was extracted from ESRI_DM (2005), clipped to the preliminary potential area, and projected to the WGS

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