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A spatial analytical model for strategic- decision making for bioenergy production from agricultural lignocellulosic resources
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Sättar Ezzati *   |
| Gorgān University of Agricultural and Natural Sciences, Gorgan, , s_ztt@yahoo.com |
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Abstract: (71 Views) |
Agricultural practices often generate significant quantities of lignocellulosic residues (e.g., crop stalks), which are frequently abandoned or burned, leading to adverse environmental impacts. Wisely collection and conversion of these residues into bioenergy could offer a twofold benefit: reducing environmental harm and partially displacing fossil fuels. The study aimed at evaluating the potential of lignocellulosic biomass from agricultural activities in Golestān province as a sustainable source for renewable energy production; and estimating the transportation costs associated with the biomass feedstock within the context of a pilot project. To do so, we employed satellite image processing to generate land-use maps and identify the spatial distribution of biomass supply sources from four major crops (wheat, soybean, rice, and rapeseed) and estimate the available biomass volume from each crop in energy units (kWh). Subsequently, an optimization model was developed to design a biomass-to-energy supply chain network for the study area. The overall classification accuracy and kappa coefficients for wheat and rapeseed were 82% and 0.74, respectively. Soybean and rice classifications achieved 76% and 0.63 accuracy, respectively. Area estimation identified 84,104 farms exceeding 2 ha, encompassing a total area of 468,000 ha. This represents an 11% bias compared to statistics provided by the Iran's Ministry of Agriculture organization for the same period. The optimistic scenario suggests a potential harvest of 3.8 million kWh of energy from the identified farms. The optimization model determined three bioenergy plants over the area of extent with a total cost of US$1.821 billion.
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| Keywords: Residue biomass, modeling, transportation, site selection, optimization |
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Full-Text [PDF 897 kb]
(33 Downloads)
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Type of Study: Research |
Subject:
Energy and Environment
Received: 2024/04/30 | Accepted: 2025/07/21 | Published: 2024/11/30
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