【摘要】 践行绿色发展理念,推进工业碳减排是湖南省实施"一带一部"战略的有效途径。运用非期望产出超效率SBM-DEA模型对湖南省14个市州2007—2016年的工业碳减排潜力进行测算,运用面板数据模型对碳减排压力大中小地区的碳减排影响因素进行分析。结果表明:因地域因素、产业结构、工业结构等差异,湖南各市州工业二氧化碳排放量和碳减排潜力各不相同;长沙等3市州,工业节能减排成效好、减排潜力小;长沙要加速科技发展带动经济发展,张家界和湘西州要加强绿色旅游业发展;湘潭等5市州,二氧化碳排放量较多,工业碳排放潜力大;湘潭、常德、益阳、郴州、娄底,要优化产业结构,推动资本要素高质量深化发展;株洲等6市,工业碳减排潜力居中;株洲、衡阳、邵阳、岳阳、永州、怀化,要通过技术改造、产业转型升级等举措达到节能减排效果。更多还原

【Abstract】 Implementing the concept of green development and promoting industrial carbon emission reduction are effective ways for Hunan Province to implement the "one belt, one department" strategy. In this paper, the unexpected output super-efficiency SBM-DEA model is applied to calculate the industrial carbon emission reducing potential of 14 cities in Hunan Province from 2007 to 2016. The panel data model is used to analyze the influencing factors of carbon emission reduction in small and medium-sized areas under pressure of carbon emission reduction. The results show that due to regional factors, industrial structure, manufacturing structure and other differences, the industrial carbon dioxide emissions and carbon emission reduction potential of Hunan provinces are different. In Changsha and other three cities,there is a good effect of industrial energy conservation andemission reduction, and the emission reduction potential is small; Changsha should accelerate the development of science and technology to promote economic development,Zhangjiajie and Xiangxi region should strengthen green tourism development; Xiangtan and other 5 cities have more carbon dioxide emissions and larger industrial carbon emissions; Xiangtan, Changde, Yiyang, Chenzhou, Loudi, should optimize the industrial structure, to promote the high quality and deepening development of capital elements; Zhuzhou and other six cities, industrial carbon emission reduction potential are in the middle; Zhuzhou, Hengyang, Shaoyang,Yueyang, Yongzhou, Huaihua should through technological reformation, industrial transformation and upgrading to achieve the goal of energy saving and emission reduction.更多还原