中国西部地区先进制造业碳足迹及隐含碳转移预测研究

Research on carbon footprint and embodied carbon transfer prediction of advanced manufacturing industries in western China

  • 摘要: 为揭示中国西部地区先进制造业的碳足迹特征与隐含碳转移格局并预测未来趋势,基于投入产出分析框架,构建双比例平衡-交叉熵法补全区域投入产出表;结合区域与多区域两类投入产出模型,利用能源消费数据对西部先进制造业的碳足迹与碳转移进行测算,构建WOA-灰色神经网络模型预测2030年演化趋势。结果显示:西部地区先进制造业碳足迹呈显著的区域与行业差异,四川、贵州、甘肃等制造业大省碳排放水平较高,主要集中于非金属矿物制品业和通用设备制造业,而高技术制造业排放较低,显示出低碳转型潜力;2030年内蒙古、四川、贵州等重工业集聚省份碳足迹增长明显,青海、宁夏等地趋于平稳,区域间碳排放差距逐步缩小,整体呈现出趋同化演进趋势;隐含碳转移表现出资源型省份向制造业省份输出、上游高耗能向中下游制造环节传导的特征,形成省份内循环—区域扩散的碳流网络,绿色转型压力集中于资源输出省份和中游制造环节。建议我国西部地区先进制造业的低碳转型通过区域协同、行业分层与跨省份碳补偿的机制联动推进,实现能源结构优化、技术路径差异化与碳责任公平分担的协同减排格局。

     

    Abstract: To reveal the carbon footprint characteristics, embodied carbon transfer patterns, and future trends of advanced manufacturing industries in western China, this study established a row and column scaling-cross entropy (RAS-CE) method within an input-output analysis framework to complete regional input-output tables. By integrating regional and multi-regional input-output models with energy consumption data, we measured the carbon footprint and embodied carbon transfers of advanced manufacturing industries in western China. A whale optimization algorithm-grey neural network model (WOA-GNN) was further developed to forecast their evolution trend toward 2030. The results showed that the carbon footprint of advanced manufacturing industries in western China exhibited pronounced regional and industrial disparities, with provinces possessing large manufacturing bases such as Sichuan, Guizhou, and Gansu recording the highest carbon emission levels, mainly concentrated in the non-metallic mineral products industry and the general equipment manufacturing industry. In contrast, the high-technology manufacturing industries generated relatively lower emissions, indicating substantial potential for low-carbon transformation. By 2030, the carbon footprint in heavy-industry-concentrated provinces including Inner Mongolia, Sichuan, and Guizhou is projected to increase significantly, whereas emissions in Qinghai and Ningxia are expected to remain relatively stable. Interregional carbon emission disparities are likely to narrow, indicating a convergence trend. Embodied carbon transfer was characterized by carbon outflows from resource-based provinces to manufacturing-oriented provinces and by transmission from upstream energy-intensive sectors to downstream manufacturing stages, forming a carbon flow network featuring "intra-provincial circulation and interregional diffusion" with green transition pressures concentrated in resource-exporting provinces and intermediate manufacturing sectors. Finally, we suggested that the low-carbon transformation of advanced manufacturing industries in western China should be promoted through coordinated regional actions, tiered industrial strategies, and cross-provincial carbon compensation mechanisms to achieve a synergistic emission reduction pathway integrating energy structure optimization, differentiated technological routes, and equitable allocation of carbon responsibility.

     

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