|
|
|
| Driving force for the variation of pollution discharge in the Chinese industrial department: An empirical study based on pollution data during the 12th five-year plan period |
| KUAI Peng1, SHU Ke-dong1, CHENG Run-he2 |
1. School of Economics, Hefei University of Technology, Hefei 230002, China;
2. School of Environment, Beijing Normal University, Beijing 100875, China |
|
|
|
|
Abstract Based on the LMDI model, variations of industrial pollutant emission during the 12th five-year plan period were decomposed into three driving factors in terms of scale, structure and intensity effects. The results showed that scale effect was the main driving force for the reduction of industrial pollutant. Specifically, there was a countrywide movement of reducing the outdated and excess industrial capacities during the past 5 years, which had suppressed the unordered industrial expansion, thus lowered the growth of pollutant emission. The structure effect was not as significant as the scale effect, however, there was only little difference between them, which indicated that the adjustment of industrial structures had also caused positive effects. The intensity effect was relatively not significant. Based on the above results, it was suggested that the government pay more attentions to the scale effects during the 13th five-year plan period. Meanwhile, in consideration of the marginal cost of scale effect that would obviously keep on increasing, long-term mechanism such as industrial structure adjustment or techniques innovation was in need.
|
|
Received: 05 November 2017
|
|
|
|
Corresponding Authors:
蒯鹏,讲师,pengkuai@hfut.edu.cn
E-mail: pengkuai@hfut.edu.cn
|
|
|
|
| Cite this article: |
|
KUAI Peng,SHU Ke-dong,CHENG Run-he. Driving force for the variation of pollution discharge in the Chinese industrial department: An empirical study based on pollution data during the 12th five-year plan period[J]. CHINA ENVIRONMENTAL SCIENCECE, 2018, 38(6): 2392-2400.
|
|
|
|
| URL: |
| http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2018/V38/I6/2392 |
| [1] |
中国国家统计局,环境保护部.中国环境统计年鉴,2012~2016[R]. 北京:中国统计出版社, 2012-2016.
|
| [2] |
Ang B W. LMDI decomposition approach:A guide for implementation[J]. Energy Policy, 2015,86:233-238.
|
| [3] |
Jiang J J, Ye B, Xie D J, et al. Provincial-level carbon emission drivers and emission reduction strategies in China:Combining multi-layer LMDI decomposition with hierarchical clustering[J]. Journal of Cleaner Production, 2017,169:178-190.
|
| [4] |
Mousavi B, Lopez N S A, Biona J B M, et al. Driving forces of Iran's CO2 emissions from energy consumption:An LMDI decomposition approach[J]. Applied Energy, 2017,206:804-814.
|
| [5] |
Jeong K, Kim S. LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector[J]. Energy Policy, 2013,62(9):1245-1253.
|
| [6] |
涂正革,谌仁俊.工业化、城镇化的动态边际碳排放量研究——基于LMDI"两层完全分解法"的分析框架[J]. 中国工业经济, 2013,9:31-43.
|
| [7] |
Achour H, Belloumi M. Decomposing the influencing factors of energy consumption in Tunisian transportation sector using the LMDI method[J]. Transport Policy, 2016,52:64-71.
|
| [8] |
Chong C H, Liu P, Ma L W, et al. LMDI decomposition of energy consumption in Guangdong Province, China, based on an energy allocation diagram[J]. Energy, 2017,133:525-544.
|
| [9] |
顾阿伦,何崇恺,吕志强.基于LMDI方法分析中国产业结构变动对碳排放的影响[J]. 资源科学, 2016,38(10):1861-1870.
|
| [10] |
张平淡,朱松,朱艳春.环保投资对中国SO2减排的影响——基于LMDI的分解结果[J]. 经济理论与经济管理, 2012,(7):84-94.
|
| [11] |
Levinson A. Technology, international trade, and pollution from U.S. Manufacturing[J]. American Economic Review, 2009,99(5):2177-2192.
|
| [12] |
刘满芝,杨继贤,马丁,等.基于LMDI模型的中国主要大气污染物的空间差异及其影响因素分析[J]. 资源科学, 2015,37(2):0333-0341.
|
| [13] |
梁赛,张天柱.多种政策对经济-环境系统的综合作用分析[J]. 中国环境科学, 2014,34(3):793-800.
|
| [14] |
Ang B W, Choi K H. Decomposition of aggregate energy and gas emission intensities for industry:a refined Divisia index method[J]. Energy Journal, 1997,18(3):59-73.
|
| [15] |
国家统计局工业统计司.中国工业统计年鉴,2012~2016[R]. 北京:中国统计出版社, 2012-2016.
|
|
|
|
