Directional spatial spillover effects and driving factors of haze pollution in North China Plain

被引:44
作者
Zhou, Hao [1 ]
Jiang, Mingdong [1 ]
Huang, Yumeng [1 ]
Wang, Qi [1 ]
机构
[1] Peking Univ, Coll Environm Sci & Engn, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
PM2.5; Spatial econometrics; Wind direction; Spatial-temporal variations; North China Plain; PARTICULATE MATTER PM2.5; LONG-RANGE TRANSPORT; TIANJIN-HEBEI REGION; AIR-QUALITY; SOURCE APPORTIONMENT; ECONOMIC-GROWTH; ANTHROPOGENIC FACTORS; URBAN FOREST; NEW-YORK; CITIES;
D O I
10.1016/j.resconrec.2021.105475
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Haze pollution is a serious interregional problem for many countries and wind direction plays a crucial role in the process of pollution transport. Upwind cities have obviously greater impacts on downwind cities due to atmospheric transport. Hence the directions of pollution spillover effects should be emphasized in empirical study to avoid model bias. With the panel data of 44 cities in North China Plain from 2013 to 2017, we constructed a novel wind direction weight matrix to analyze the spatial variations of PM2.5 concentration. The matrix was then incorporated into a spatial panel model to quantitatively evaluate the impacts of socioeconomic and natural factors on PM2.5 concentration. The results show that wind direction dominates the distribution of PM2.5 concentration. The growth of per capita GDP facilitates the reduction of PM2.5 pollution while the increase of the other socioeconomic factors aggravates haze pollution. Besides, natural factors directly or indirectly affect PM2.5 concentration. Particularly, the spillover effects of socioeconomic factors are greater than their local effects. Based on the results, we suggested that investment of air pollution control in a neighboring area may be more effective than in the local city itself. The mechanism of pollutant transport should be fully considered in the fields such as the construction of urban air ducts, industrial layout, and eco-compensation.
引用
收藏
页数:10
相关论文
共 85 条
[1]   Vehicle emissions and PM2.5 mass concentrations in six Brazilian cities [J].
Andrade, Maria de Fatima ;
de Miranda, Regina Maura ;
Fornaro, Adalgiza ;
Kerr, Americo ;
Oyama, Beatriz ;
de Andre, Paulo Afonso ;
Saldiva, Paulo .
AIR QUALITY ATMOSPHERE AND HEALTH, 2012, 5 (01) :79-88
[2]   Quantifying the impact of particle matter on mortality and hospitalizations in four Brazilian metropolitan areas [J].
Andreao, Willian Lemker ;
Pinto, Janaina Antonino ;
Pedruzzi, Rizzieri ;
Kumar, Prashant ;
de Almeida Albuquerque, Taciana Toledo .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2020, 270
[3]   Regional sources of particulate sulfate, SO2, PM2.5, HCl, and HNO3, in New York, NY [J].
Bari, A ;
Dutkiewicz, VA ;
Judd, CD ;
Wilson, LR ;
Luttinger, D ;
Husain, L .
ATMOSPHERIC ENVIRONMENT, 2003, 37 (20) :2837-2844
[4]   Fine particulate matter (PM2.5) in Edmonton, Canada: Source apportionment and potential risk for human health [J].
Bari, Md. Aynul ;
Kindzierski, Warren B. .
ENVIRONMENTAL POLLUTION, 2016, 218 :219-229
[5]   Investigating the Impacts of Urbanization on PM2.5 Pollution in the Yangtze River Delta of China: A Spatial Panel Data Approach [J].
Cheng, Liang ;
Zhang, Ting ;
Chen, Longqian ;
Li, Long ;
Wang, Shangjiu ;
Hu, Sai ;
Yuan, Lina ;
Wang, Jia ;
Wen, Mingxin .
ATMOSPHERE, 2020, 11 (10)
[6]   Identifying the spatial effects and driving factors of urban PM2.5 pollution in China [J].
Cheng, Zhonghua ;
Li, Lianshui ;
Liu, Jun .
ECOLOGICAL INDICATORS, 2017, 82 :61-75
[7]   Tracking ambient PM2.5 build-up in Delhi national capital region during the dry season over 15 years using a high-resolution (1 km) satellite aerosol dataset [J].
Chowdhury, Sourangsu ;
Dey, Sagnik ;
Di Girolamo, Larry ;
Smith, Kirk R. ;
Pillarisetti, Ajay ;
Lyapustin, Alexei .
ATMOSPHERIC ENVIRONMENT, 2019, 204 :142-150
[8]   Determining the trade-environment composition effect: the role of capital, labor and environmental regulations [J].
Cole, MA ;
Elliott, RJR .
JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT, 2003, 46 (03) :363-383
[9]   The environmental Kuznets curve for PM2.5 pollution in Beijing-Tianjin-Hebei region of China: A spatial panel data approach [J].
Ding, Yueting ;
Zhang, Ming ;
Chen, Sai ;
Wang, Wenwen ;
Nie, Rui .
JOURNAL OF CLEANER PRODUCTION, 2019, 220 :984-994
[10]   Direct and spillover effects of urbanization on PM2.5 concentrations in China's top three urban agglomerations [J].
Du, Yueyue ;
Sun, Tieshan ;
Peng, Jian ;
Fang, Kai ;
Liu, Yanxu ;
Yang, Yang ;
Wang, Yanglin .
JOURNAL OF CLEANER PRODUCTION, 2018, 190 :72-83