2023
DOI: 10.1016/j.jclepro.2023.135886
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A spatial approach for integrating GIS and fuzzy logic in multicriteria problem solving to support the definition of ideal areas for biorefinery deployment

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Cited by 7 publications
(2 citation statements)
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“…This quadrant contains two major clusters: greenhouse gases and microalgae. In the same cluster, the topic of bioconversion methods can be utilized to process waste from the agriculture industry to reduce greenhouse gas emissions [124]. The recovery or harvesting stages of microalgae, a photosynthetic organism that can produce biomass, also appear alongside the topic of biofuels, which is the conversion of one type of renewable energy source [125].…”
Section: Thematic Mapmentioning
confidence: 99%
“…This quadrant contains two major clusters: greenhouse gases and microalgae. In the same cluster, the topic of bioconversion methods can be utilized to process waste from the agriculture industry to reduce greenhouse gas emissions [124]. The recovery or harvesting stages of microalgae, a photosynthetic organism that can produce biomass, also appear alongside the topic of biofuels, which is the conversion of one type of renewable energy source [125].…”
Section: Thematic Mapmentioning
confidence: 99%
“…Mishra et al [27] introduced an ARAS tool to choose sustainable biomass crops on PFSs. Da Silva Romero et al [28] discussed a GIS-based fuzzy system for region identification for biorefineries with spatial and multifactor information. Hezam et al [22] developed the SVN-MEREC-SWARA-COPRAS model for selecting bioenergy production technologies (BPTs) with sustainability indicators.…”
Section: Decision Analysis Model For the Biofuel Sectormentioning
confidence: 99%