Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang, Jiangxi, 330022, China.
School of Geography and Environment, Jiangxi Normal University, Nanchang, Jiangxi, 330022, China.
Environ Sci Pollut Res Int. 2018 Apr;25(10):9600-9614. doi: 10.1007/s11356-018-1306-x. Epub 2018 Jan 22.
This study is the first attempt to investigate the drivers of Chinese industrial SO and NO emissions from both periodic and structural perspectives through a decomposition analysis using the logarithmic mean Divisia index (LMDI). The two pollutants' emissions were decomposed into output effects, structural effects, clean production effects, and pollution abatement effects. The results showed that China's industrial SO discharge increased by 1.14 Mt during 2003-2014, and the contributions from the four effects were 23.17, - 1.88, - 3.80, and - 16.36 Mt, respectively. Likewise, NO discharge changed by - 3.44 Mt over 2011-2014, and the corresponding contributions from the four effects were 2.97, - 0.62, - 1.84, and - 3.95 Mt. Thus, the output effect was mainly responsible for the growth of the two discharges. The average annual contribution rates of SO and NO from output were 14.33 and 5.97%, respectively, but pollution abatement technology presented the most obvious mitigating effects (- 10.11 and - 7.92%), followed by the mitigating effects of clean production technology (- 2.35 and - 3.7%), and the mitigation from the structural effect was the weakest (- 1.16 and - 1.25%, respectively), which meant pollutant reduction policies related to industrial structure adjustment should be a long-term measure for the two discharges. In addition, the sub-sectors of I20 (manufacture of raw chemical materials and chemical products), I24 (manufacture of non-metallic mineral products), and I26 (smelting and pressing of non-ferrous metals) were the major contributors to both discharges. Thus, these sub-sectors should be given priority consideration when designing mitigation-related measures. Last, some particular policy implications were recommended for reducing the two discharges, including that the government should seek a technological discharge reduction route.
本研究首次尝试从周期性和结构性角度，利用对数平均迪氏指数（LMDI）分解分析，研究中国工业 SO 和 NOx 排放的驱动因素。将两种污染物的排放分解为产出效应、结构效应、清洁生产效应和污染减排效应。结果表明，2003-2014 年中国工业 SO 排放量增加了 1.14 Mt，四个效应的贡献分别为 23.17、-1.88、-3.80 和-16.36 Mt。同样，2011-2014 年 NOx 排放量变化了-3.44 Mt，四个效应的贡献分别为 2.97、-0.62、-1.84 和-3.95 Mt。因此，产出效应是导致两种排放增长的主要因素。SO 和 NOx 的平均年排放贡献率分别为 14.33%和 5.97%，但污染减排技术的减排效果最为明显（-10.11%和-7.92%），其次是清洁生产技术的减排效果（-2.35%和-3.7%），结构效应的减排效果最弱（-1.16%和-1.25%），这意味着与工业结构调整相关的污染物减排政策应成为两项排放物的长期措施。此外，I20（基础化学原料和化学制品制造）、I24（非金属矿物制品制造）和 I26（有色金属冶炼和压延加工）等子行业是这两种排放物的主要贡献者。因此，在制定相关减排措施时，应优先考虑这些子行业。最后，提出了一些减少这两种排放物的具体政策建议，包括政府应寻求技术减排途径。
