School of Environment, Nanjing Normal University, Nanjing, 210023, China.
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development, Nanjing Normal University, Nanjing, 210023, China.
Environ Sci Pollut Res Int. 2022 Jan;29(2):2555-2565. doi: 10.1007/s11356-021-15741-1. Epub 2021 Aug 9.
Cities are faced with various kinds of pollution issues in the process of economic development, among which industrial pollution has become the most terrifying environmental issue in recent years, so that industrial pollution control should be emphasized. Finding out the key factors influencing industrial pollutant emissions is the basis of taking corresponding measures. Previous studies only focused on one pollutant without a comparative analysis of the contribution of influencing factors to multiple pollutants. Therefore, this study aims to identify the key influencing factors of industrial pollutants in Nanjing, Suzhou, Xuzhou, and Taizhou in Jiangsu Province during the years 2008-2018 by using the logarithmic mean Divisia index (LMDI) method. The results from decomposition indicate the following. (1) Emission intensity (EI) and energy efficiency (EE) are negative factors for decreasing industrial pollutant emissions, while the economic output (EO) and population (P) are positive factors for increasing industrial pollutant emissions. (2) Emission intensity has the most significant influence to industrial wastewater in decreasing emissions; energy efficiency makes the biggest contribution to industrial solid waste in decreasing emissions, economic output and population contribute the most to industrial solid waste in increasing emissions. (3) Nanjing has the highest contribution rate of emission intensity and population, and the contribution rate of energy efficiency and economic output to Taizhou is the highest. Identifying the key driving factors of different pollutants can serve as evidence and guidance for urban environmental governance, therefore reducing emissions ulteriorly, and achieving sustainable development.
城市在经济发展过程中面临着各种污染问题，其中工业污染已成为近年来最可怕的环境问题，因此应强调工业污染控制。找出影响工业污染物排放的关键因素是采取相应措施的基础。以前的研究仅关注一种污染物，而没有对多种污染物的影响因素的贡献进行比较分析。因此，本研究旨在通过对数平均迪氏指数（LMDI）方法，识别 2008-2018 年期间江苏省南京、苏州、徐州和泰州的工业污染物的关键影响因素。分解结果表明：（1）排放强度（EI）和能源效率（EE）是减少工业污染物排放的负因素，而经济产出（EO）和人口（P）是增加工业污染物排放的正因素。（2）排放强度对工业废水排放量减少的影响最大；能源效率对工业固体废物排放量减少的贡献最大，经济产出和人口对工业固体废物排放量增加的贡献最大。（3）南京的排放强度和人口的贡献率最高，而泰州的能源效率和经济产出对其的贡献率最高。识别不同污染物的关键驱动因素可以为城市环境治理提供证据和指导，从而进一步减排，实现可持续发展。
