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Dynamic and network slack-based measure analysis of China's regional energy and air pollution reduction efficiencies

机译:基于动态和网络松弛的中国区域能源和空气污染减排效率测度分析

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摘要

China's rapid development over the past few decades has resulted in significant environmental pollution from CO2, SO2 and NO2 emissions amongst others, all of which can adversely affect human health. However, past efficiency analyses have tended to discuss energy efficiency and environmental efficiency separately, or have discussed ways in which governments can reduce pollution at the source. In other words, previous analyses of China's energy efficiency have only been focused on one-stage, and very few studies have integrated the environment, government pollution reductions, and economic development in the analysis. Therefore, to fill this research gap, this study examined the first and second-stage energy and air pollution reduction efficiencies in thirty Chinese provinces and municipalities from 2013 to 2016 using a dynamic, network slack-based measure (DNSBM) model, in which labor, fixed assets and energy consumption were the input variables in the first production stage, GDP was the output variable, and CO2, SO2, and NO2 emissions were the link variables, and in the second treatment stage, pollution treatment investment was the input variable, the CO2, SO2, and NO2 emissions reductions were the output variables, and energy consumption/GDP was the carryover variable.It was found that; (1) Beijing, Shanghai, Guizhou, Hainan and Qinghai had the best performances over the 4 years, and Shaanxi, Shandong, Fujian, Jilin, Liaoning and Xinjiang had the worst performances and therefore had the greatest need for improvements; (2) the overall provincial efficiencies were generally relatively low and significant improvements were needed however, there were large differences between the provinces/municipalities; (3) the overall air pollution reduction efficiency governance in the second stage was low, indicating that more effective measures were needed to improve environmental efficiency and that the dynamic developments in government regulations and governance had resulted in a policy implementation lag; and (4) in 21 provinces, the first-stage productivity was significantly higher than the second-stage treatment productivity, indicating that the treatment stage needed to be strengthened. (C) 2019 Elsevier Ltd. All rights reserved.
机译:在过去的几十年中,中国的飞速发展导致了CO2,SO2和NO2排放等严重的环境污染,所有这些都会对人类健康产生不利影响。但是,过去的效率分析趋向于分别讨论能源效率和环境效率,或者讨论了政府从源头减少污染的方式。换句话说,以前对中国能源效率的分析只集中于一个阶段,很少有研究将环境,政府减少污染和经济发展纳入分析。因此,为填补这一研究空白,本研究使用动态的基于网络松弛的测度(DNSBM)模型研究了2013年至2016年中国三十个省市的第一阶段和第二阶段减少能源和空气污染的效率,其中劳动力,固定资产和能源消耗是第一生产阶段的输入变量,GDP是产出变量,CO2,SO2和NO2排放是联系变量,而在第二处理阶段,污染处理投资是输入变量,研究发现,CO2,SO2和NO2排放量的减少是产出变量,能源消耗/ GDP是结转变量。 (1)四年来北京,上海,贵州,海南和青海的表现最佳,而陕西,山东,福建,吉林,辽宁和新疆的表现最差,因此最需要改进; (2)总体上省级效率较低,需要进行重大改进,但是省/市之间差异很大; (3)第二阶段的总体空气污染减排效率治理水平低,表明需要采取更有效的措施来提高环境效率,并且政府法规和治理的动态发展导致政策实施滞后; (4)在21个省中,第一阶段的生产率显着高于第二阶段的处理生产率,这表明需要加强处理阶段。 (C)2019 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Journal of Cleaner Production》 |2020年第1期|119546.1-119546.16|共16页
  • 作者

  • 作者单位

    Sichuan Univ Business Sch Wangjiang Rd 29 Chengdu 610064 Peoples R China;

    Soochow Univ Dept Econ 56 Kueiyang St Sec 1 Taipei 100 Taiwan;

    Finance Dept Sichuan Prov Nanxin Rd 37 Chengdu 610064 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Air pollutant emissions reduction; CO2; Dynamic and network SBM (DNSBM); Treatment;

    机译:减少空气污染物排放;二氧化碳动态和网络SBM(DNSBM);治疗;
  • 入库时间 2022-08-18 05:20:28

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