School of Business Administration, Northeastern University, Shenyang 110169, China.
Int J Environ Res Public Health. 2021 Mar 12;18(6):2914. doi: 10.3390/ijerph18062914.
Based on the extended STIRPAT model and panel data from 2005 to 2015 in 20 industrial sectors, this study investigates the influential factors of carbon intensity, including employee, industry added value, fixed-assets investment, coal consumption, and resource tax. Meanwhile, by expanding the spatial weight matrix and using the Spatial Durbin Model, we reveal the spatiotemporal characteristics of carbon intensity. The results indicate that Manufacturing of Oil Processing and Coking Processing (S7), Manufacturing of Non-metal Products (S10), Smelting and Rolling Process of Metal (S11), and Electricity, Gas, Water, Sewage Treatment, Waste and Remediation (S17) contribute most to carbon intensity in China. The carbon intensity of 20 industrial sectors presents a spatial agglomeration characteristic. Meanwhile, industry added value inhibits the carbon intensity; however, employee, coal consumption, and resource tax promote carbon intensity. Finally, coal consumption appears to have spillover effects, and the employee has an insignificant impact on the carbon intensity of industrial sectors.
基于扩展的 STIRPAT 模型和 2005 年至 2015 年 20 个工业部门的面板数据，本研究调查了包括员工、工业增加值、固定资产投资、煤炭消耗和资源税在内的碳强度影响因素。同时，通过扩展空间权重矩阵并使用空间杜宾模型，揭示了碳强度的时空特征。结果表明，石油加工和焦化加工制造业（S7）、非金属制品制造业（S10）、金属冶炼和轧制加工业（S11）以及电力、燃气、水、污水处理、废物和修复业（S17）对中国的碳强度贡献最大。20 个工业部门的碳强度呈现出空间集聚特征。同时，工业增加值抑制了碳强度，而员工、煤炭消耗和资源税则促进了碳强度。最后，煤炭消耗存在溢出效应，而员工对工业部门的碳强度影响不显著。
