TY - JOUR
T1 - Mapping out the regional low-carbon and economic biomass supply chain by aligning geographic information systems and life cycle assessment models
AU - Zhao, Guanhan
AU - Jiang, Peng
AU - Zhang, Hao
AU - Li, Lin
AU - Ji, Tuo
AU - Mu, Liwen
AU - Lu, Xiaohua
AU - Zhu, Jiahua
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/9/1
Y1 - 2024/9/1
N2 - The development of biomass faces challenges due to its low energy density and wide dispersion, particularly in the case of agricultural straw, resulting in high supply chain costs. To address these challenges, a comprehensive approach that combines spatial planning with techno-economic analysis (TEA) and life cycle assessment (LCA) was employed to establish an economically sustainable and low-carbon biomass supply chain (BSC) system. The approach encompassed the integration of straw resource and road network data into a Geographic Information System (GIS), which was subsequently utilized to devise TEA and LCA calculation methods leveraging the GIS data. Scenario analysis was performed by adjusting the service radius of the pretreatment center to identify the optimal location of the bioenergy plant, minimize the BSC cost, and reduce the carbon footprint. The results indicated that implementing a service radius of 3–4 km achieved an optimized BSC scenario in the study area, resulting in BSC costs of 375 CNY/t and carbon emissions of 125 kgCO2/t. Overall, this work offers a promising modeling framework for the efficient, economical, and sustainable utilization of bioenergy.
AB - The development of biomass faces challenges due to its low energy density and wide dispersion, particularly in the case of agricultural straw, resulting in high supply chain costs. To address these challenges, a comprehensive approach that combines spatial planning with techno-economic analysis (TEA) and life cycle assessment (LCA) was employed to establish an economically sustainable and low-carbon biomass supply chain (BSC) system. The approach encompassed the integration of straw resource and road network data into a Geographic Information System (GIS), which was subsequently utilized to devise TEA and LCA calculation methods leveraging the GIS data. Scenario analysis was performed by adjusting the service radius of the pretreatment center to identify the optimal location of the bioenergy plant, minimize the BSC cost, and reduce the carbon footprint. The results indicated that implementing a service radius of 3–4 km achieved an optimized BSC scenario in the study area, resulting in BSC costs of 375 CNY/t and carbon emissions of 125 kgCO2/t. Overall, this work offers a promising modeling framework for the efficient, economical, and sustainable utilization of bioenergy.
KW - Biomass supply chain
KW - Carbon footprint
KW - Geographical information system
KW - Spatial planning framework
KW - Techno-economic analysis
UR - http://www.scopus.com/inward/record.url?scp=85195079342&partnerID=8YFLogxK
U2 - 10.1016/j.apenergy.2024.123599
DO - 10.1016/j.apenergy.2024.123599
M3 - 文章
AN - SCOPUS:85195079342
SN - 0306-2619
VL - 369
JO - Applied Energy
JF - Applied Energy
M1 - 123599
ER -