Socioeconomic factors of PM2.5 concentrations in 152 Chinese cities: Decomposition analysis using LMDI

被引:147
作者
Zhang, Yu [1 ]
Shuai, Chenyang [2 ]
Bian, Jing [1 ]
Chen, Xi [3 ]
Wu, Ya [1 ]
Shen, Liyin [1 ]
机构
[1] Chongqing Univ, Fac Construct Management & Real Estate, Int Res Ctr Sustainable Built Environm, Chongqing, Peoples R China
[2] Univ Michigan, Sch Environm & Sustainabil, Ann Arbor, MI 48109 USA
[3] Univ Hong Kong, Dept Real Estate & Construct, Fac Architecture, Pokfulam, Hong Kong, Peoples R China
关键词
Public health; PM2.5; Impact factor; LMDI; Urban China; PARTICULATE MATTER PM2.5; AIR-POLLUTION EMISSIONS; KEY IMPACT FACTORS; ENERGY-CONSUMPTION; CARBON EMISSION; ECONOMIC-GROWTH; CO2; EMISSIONS; ENVIRONMENTAL EFFICIENCY; REGIONAL DIFFERENCES; INFLUENTIAL FACTORS;
D O I
10.1016/j.jclepro.2019.01.322
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As a typical component in particulate matter, respirable suspended particles (PM2.5) can cause increased morbidity and mortality from cystic fibrosis, cardiovascular and respiratory diseases. China, with the largest population in the world, is challenged with sever PM2.5 concentration, particularly in the urban area. Understanding the key factors influencing PM2.5 concentration is the basic step for taking targeted measures. Previous studies have identified the key impact factors on PM2.5 concentration in only a few selected cities, which barely contributes to China's PM2.5 concentration reduction. Therefore, this study aims to identify the key impact factors of PM2.5 concentration in 152 Chinese cities in eastern, central, and western China by using Logarithmic Mean Divisia Index (LMDI) method. The findings of the study are as follows: emission intensity (EI) inhibited the PM2.5 concentration of 137 cities (i.e. 90.13% of the152 cities); energy intensity (EnI) depressed that of 99 cities (i.e. 65.13%); economic output (EO) stimulated that of 120 cities (i.e. 78.95%); and population (P) spurred that of 124 cities (i.e. 81.58%). This is the first study that provides a full picture of the key impact factors on Chinese urban PM2.5 concentration. The identified key impact factors can serve as the evidence and guidance for the authorities of China's cities to tailor their strategies towards PM2.5 concentration reduction. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:96 / 107
页数:12
相关论文
共 82 条
[1]  
Air Pollution in World, 2018, AIR POLL WORLD REAL
[2]   Relationships among carbon emissions, economic growth, energy consumption and population growth: Testing Environmental Kuznets Curve hypothesis for Brazil, China, India and Indonesia [J].
Alam, Md. Mahmudul ;
Murad, Md. Wahid ;
Nornanc, Abu Hanifa Md. ;
Ozturk, Ilhan .
ECOLOGICAL INDICATORS, 2016, 70 :466-479
[3]   Decomposition analysis for policymaking in energy: which is the preferred method? [J].
Ang, BW .
ENERGY POLICY, 2004, 32 (09) :1131-1139
[4]  
[Anonymous], 2018, CHIN EN STAT YB
[5]  
[Anonymous], 2009, Sina News
[6]  
[Anonymous], 2005, Air quality guidelines - global update 2005
[7]   Coupling between Chemical and Meteorological Processes under Persistent Cold-Air Pool Conditions: Evolution of Wintertime PM2.5 Pollution Events and N2O5 Observations in Utah's Salt Lake Valley [J].
Baasandorj, Munkhbayar ;
Hoch, Sebastian W. ;
Bares, Ryan ;
Lin, John C. ;
Brown, Steven S. ;
Millet, Dylan B. ;
Martin, Randal ;
Kelly, Kerry ;
Zarzana, Kyle J. ;
Whiteman, C. David ;
Dube, William P. ;
Tonnesen, Gail ;
Jaramillo, Isabel Cristina ;
Sohl, John .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2017, 51 (11) :5941-5950
[8]  
Binzhou Development and Reform Commssion, 2018, BINZH 13 5 YEAR EN P
[9]   Comparative analysis on the socioeconomic drivers of industrial air pollutant emissions between Japan and China: Insights for the further-abatement period based on the LMDI method [J].
Chang, Miao ;
Zheng, Ji ;
Inoue, Yukiko ;
Tian, Xin ;
Chen, Qing ;
Gan, Tiantian .
JOURNAL OF CLEANER PRODUCTION, 2018, 189 :240-250
[10]  
Changzhi Development and Reform Commssion, 2018, NEWS CHANGZH