优化农村地区作物残茬收集模式,降低运输成本和碳排放

Zi-Han Tang, Chen Liang, Ruo-Chen Zhang
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引用次数: 0

摘要

生物质收集的成本优化对于提高其利用率是必不可少的,特别是在农作物残茬(CRs)生物质丰富而能源通常短缺的农村地区。然而,由于农村居民点分布的离散性,CRs收集相关的经济和环境成本的增加已成为限制其应用的关键因素。因此,本研究提出了在考虑运输成本和碳减排的前提下,优化农村CRs收集空间格局的方法。基于多场景选址-分配模型,构建生物质资源点和能源设施的cr收集模式。富晋县的实证研究发现,随着cr收集距离阈值(CDT)的增加,运输成本和碳减排潜力趋于增加并逐渐收敛。当CDT为15 km时,CRs收集空间格局的运输成本和碳减排综合效益最大,运输成本为898,104元,碳减排潜力为501,627.5 t。最优收集空间格局实现了研究区647个生物质原料资源点和196个村庄的收集-利用空间匹配,使CRs的总开发利用率达到84%。研究区25%的村庄可以通过cr独立满足其供暖需求,75%的村庄需要考虑混合能源供暖。该方法可为农村生物质资源的分布式开发和可持续利用提供规划和决策支持。
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Optimizing crop residues collection patterns in rural areas to reduce transportation costs and carbon emissions
Cost optimization of biomass collection is indispensable for its increased utilization, especially in rural areas where crop residues (CRs)-based biomass is in abundance and energy is usually in short supply. However, due to the discrete distribution of rural settlements, the increasing economic and environmental costs associated with CRs collection have become key factors limiting its application. Therefore, this study proposes a method for optimizing the spatial pattern of CRs collection in rural areas while also considering transportation costs and carbon emissions reduction. Based on a multi-scenario location–allocation model, a CRs collection pattern was constructed for biomass resource points and energy facilities. An empirical study in Fujin County found that as CRs collection distance threshold (CDT) increased, transportation costs and carbon emissions reduction potential tended to increase and gradually converge. When the CDT was taken for 15 km, the spatial pattern of CRs collection maximized the overall benefits of transportation costs and carbon emissions reduction, with a transportation cost of 898,104 yuan and a carbon emissions reduction potential of 501,627.5 t. The optimal spatial pattern for collection achieved the collection-utilization spatial matching of 647 biomass feedstock resource points and 196 villages in the study area, resulting in the exploitation of 84% of CRs in total. 25% of villages in the study area can independently meet their heating needs through CRs, and 75% need to consider mixed energy sources for heating. This method can support planning and decision-making for the distributed development and sustainable utilization of biomass resources in rural areas.
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