Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/66638
Title: Driving forces of Chinese primary air pollution emissions : an index decomposition analysis
Authors: Lyu, W
Li, Y
Guan, DB
Zhao, HY
Zhang, Q
Liu, Z
Keywords: China
PM2.5
Emission drivers
Index decomposition analysis
Divisia index
Issue Date: 2016
Publisher: Elsevier
Source: Journal of cleaner production, 1 Oct. 2016, v. 133, p. 136-144 How to cite?
Journal: Journal of cleaner production 
Abstract: Emissions of the fine particulate matters (diameter of 2.5 mu m or less) caused by both the primary particle emissions and the precursor emission sources such as sulfur dioxide and nitrogen oxides, have contributed significantly to poor urban air quality in China, and have attracted tremendous public attention over the past few years. This study provides an interdisciplinary study to investigate the key contributors driving air pollution emissions changes in China from 1997 to 2012, by applying the Logarithmic Mean Divisia Index method. The decomposition results are presented in both multiplicative and additive approaches to show the relative and absolute contribution of each factor in affecting emission changes. Changes in total particulate matter emissions are attributed to variations in primary particle, sulfur dioxide and nitrogen oxides emissions. It is manifested that the economic growth effect and energy intensity effect have always been the two key drivers in affecting the changes in air pollutant emissions over the period. The effects of emission efficiency, production structure and population growth contribute less significantly to overall emission changes, and the impacts of different factors vary among different pollutants. Since current strategies and policies in combatting particulate matter emissions are inefficient, this paper provides a guideline for the Chinese Government to deal with the air pollution problem for sustainable development in China.
URI: http://hdl.handle.net/10397/66638
ISSN: 0959-6526
DOI: 10.1016/j.jclepro.2016.04.093
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