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Identifying Driving Factors of Jiangsu’s Regional Sulfur Dioxide Emissions: A Generalized Divisia Index Method

机译:识别江苏区域二氧化硫排放的驱动因素:广义Divisia指数法

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摘要

The Chinese government has made some good achievements in reducing sulfur dioxide emissions through end-of-pipe treatment. However, in order to implement the stricter target of sulfur dioxide emission reduction during the 13th “Five-Year Plan” period, it is necessary to find a new solution as quickly as possible. Thus, it is of great practical significance to identify driving factors of regional sulfur dioxide emissions to formulate more reasonable emission reduction policies. In this paper, a distinctive decomposition approach, the generalized Divisia index method (GDIM), is employed to investigate the driving forces of regional industrial sulfur dioxide emissions in Jiangsu province and its three regions during 2004–2016. The contribution rates of each factor to emission changes are also assessed. The decomposition results demonstrate that: (i) the factors promoting the increase of industrial sulfur dioxide emissions are the economic scale effect, industrialization effect, and energy consumption effect, while technology effect, energy mix effect, sulfur efficiency effect, energy intensity effect, and industrial structure effect play a mitigating role in the emissions; (ii) energy consumption effect, energy mix effect, technology effect, sulfur efficiency effect, and industrial structure effect show special contributions in some cases; (iii) industrial structure effect and energy intensity effect need to be further optimized.
机译:中国政府在通过管道末端处理减少二氧化硫排放方面取得了一些良好的成就。但是,为了在“十三五”期间实施更严格的二氧化硫减排目标,有必要尽快找到新的解决方案。因此,确定区域二氧化硫排放的驱动因素,制定更加合理的减排政策具有重要的现实意义。本文采用一种独特的分解方法,即广义Divisia指数法(GDIM),来调查江苏省及其三个地区在2004-2016年间区域工业二氧化硫排放的驱动力。还评估了每个因素对排放变化的贡献率。分解结果表明:(i)促进工业二氧化硫排放量增加的因素是经济规模效应,工业化效应和能源消耗效应,而技术效应,能源混合效应,硫效率效应,能量强度效应和产业结构效应在排放中起缓解作用; (ii)在某些情况下,能源消耗效应,能源混合效应,技术效应,硫效率效应和产业结构效应发挥了特殊作用; (三)产业结构效应和能源强度效应需要进一步优化。

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