Identifying the contributions of multiple driving forces to PM10-2.5 pollution in urban areas in China

Shuang Zhao; Shiliang Liu; Xiaoyun Hou; Robert Beazley; Yongxiu Sun

doi:10.1016/j.scitotenv.2019.01.256

Identifying the contributions of multiple driving forces to PM_10-2.5 pollution in urban areas in China

Sci Total Environ. 2019 May 1:663:361-368. doi: 10.1016/j.scitotenv.2019.01.256. Epub 2019 Jan 23.

Authors

Shuang Zhao¹, Shiliang Liu², Xiaoyun Hou¹, Robert Beazley³, Yongxiu Sun¹

Affiliations

¹ School of Environment, State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China.
² School of Environment, State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China. Electronic address: shiliangliu@bnu.edu.cn.
³ Department of Natural Resources, College of Agriculture and Life Sciences, Fernow Hall 302, Cornell University, Ithaca, NY 14853, USA.

PMID: 30716626
DOI: 10.1016/j.scitotenv.2019.01.256

Abstract

Economic development and urban expansion have accelerated particulate matter pollution in urban areas in China. Particulate matter-driven haze poses a serious threat to human beings from a public health point of view. Substantial evidences had linked adverse health effects with exposures to PM_2.5, but recent research indicated that PM_10-2.5 also had great risk. However, the relative contributions of driving forces to PM_10-2.5 pollution are not well understood in the urban areas in China, and no targeted policies have been regulated to control the pollution. In this study, we quantified the contributions of potential driving factor across China with the structural equation model (SEM). Our results showed that in 2015 and 2016, the annual average concentrations of PM_10-2.5 in the 290 prefecture-level cities with a mean value of 36 and 35 μg/m³, respectively. Industrial scale contributed more to PM_10-2.5 pollution than city size and residents' activities in urban areas based on SEM results. Driving forces included in our model could explain 42% of variations in PM_10-2.5 pollution, which indicated that there existed influences from other anthropogenic sources and natural sources. Eleven targeted recommendations were then proposed to control PM_10-2.5 pollution based on our mechanism analysis. Findings from our study are beneficial to control PM_10-2.5 pollution on a national scale, and also can provide a theoretical basis for the formulation of PM_10-2.5 pollution control policy in China.

Keywords: Anthropogenic source; Driving force; Mechanism analysis; National scale; PM(10–2.5) pollution.