Impacts of energy consumption, energy structure, and treatment technology on SO2 emissions: A multi-scale LMDI decomposition analysis in China
Impacts of energy consumption, energy structure, and treatment technology on SO2 emissions: A multi-scale LMDI decomposition analysis in China
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DOI：
10.1016/j.apenergy.2016.11.013
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发表时间：
2016-12
期刊：
影响因子：
11.2
通讯作者：
Xue Yang;Shaojian Wang;Wenzhong Zhang;Jiaming Li;YaFeng Zou
中科院分区：
文献类型：
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作者：
Xue Yang;Shaojian Wang;Wenzhong Zhang;Jiaming Li;YaFeng Zou
大气污染对人类健康的危害和对全球生态系统的影响日益受到世界各国的关注。现有的研究虽然关注了污染物排放的原因，但没有区分直接因素和间接因素，结果不一。直接原因是指与能源有关的因素，因为空气污染物主要是由能源利用直接产生的，而间接因素是指社会经济因素，因为这些因素通过影响与能源有关的方面而作用于污染物排放。采用对数平均Divisia指数法，研究了1995-2014年中国能源消费总量、能源结构和治理技术3个主导因素对二氧化硫排放的影响。与以往的研究侧重于工业部门的SO2排放量不同，本研究以SO2排放总量为目标。结果表明，EC的增加是SO2排放量增加的主要原因，而TT的提高在整个研究期间起到了抑制排放的主导作用。与此相反，ES有一个异常轻微的影响，SO2的排放量，由于其微小的变化，在此期间。在区域尺度上，东、中、西部地区EC、ES和TT的相对贡献率差异均随时间逐渐减小，中部地区EC的改善效应最大，东部地区ES的降低效应最大，西部地区TT的抑制效应最大。在省一级，大多数省（60%）的经济增长相对较快，经济调整较慢（即，降低煤炭消费率），只有北京、天津、上海和四川的EC增长相对缓慢，煤炭消费比重下降较快。此外，基于灰色预测模型对2015 - 2020年四种情景下的SO2排放量预测表明，同时控制EC和ES是最有效的SO2减排途径，其次是单独控制EC和ES。
Air pollution is increasingly a focus of concern worldwide due to its adverse impacts on human health and profound influences on global ecosystem. Although the existing studies have paid much attention to the causes of pollutant emissions, they fail to distinguish between direct and indirect factors, yielding the mixed results. Direct causes denote energy-related factors, as air pollutants are mainly produced by energy utilization directly, while indirect elements refer to socio-economic factors, as these factors act on pollutant emissions through affecting energy-related aspects. This paper investigated the impacts of three dominant direct factors: total energy consumption (EC), energy structure (ES) and treatment technology (TT) on sulfur dioxide (SO2) emissions in China during 1995–2014 using the logarithmic mean Divisia Index method. Distinguished from the previous studies which took particular interest in SO2emissions from the industrial sector, this study put the total amount of SO2emissions as the target. The results show that increased EC was the main reason for SO2enhancement, while increasingly advanced TT played a dominant role in inhibiting the emissions throughout the study period. In contrast, ES had an unusually slight effect on SO2emissions due to its minor variation in the meantime. On regional scale, the differences in relative contribution rates (RCRs) of EC, ES and TT among the eastern, central and western regions all gradually decreased over time; EC in central region had the largest improved effect, ES in eastern region held the greatest reduction effect, and TT in western region got the biggest inhibitory effect. At provincial level, most provinces (60%) had relatively quick EC growth and slow ES adjustment (i.e., reducing the coal consumption rate); only Beijing, Tianjin, Shanghai and Sichuan had a relatively slow growth of EC and quick decrease in the percentage of coal consumption. Further, the projection of SO2emissions in four scenarios from 2015 to 2020 based on a grey projection model indicated that controlling both EC and ES would be the most efficient approach to SO2abatement followed by individually controlling EC and ES.