Spatiotemporal trend analysis for fine particulate matter concentrations in China using high-resolution satellite-derived and ground-measured PM2.5 data

Kaixu Bai; Mingliang Ma; Ni-Bin Chang; Wei Gao

doi:10.1016/j.jenvman.2018.12.071

Spatiotemporal trend analysis for fine particulate matter concentrations in China using high-resolution satellite-derived and ground-measured PM_2.5 data

J Environ Manage. 2019 Mar 1:233:530-542. doi: 10.1016/j.jenvman.2018.12.071. Epub 2018 Dec 27.

Authors

Kaixu Bai¹, Mingliang Ma², Ni-Bin Chang³, Wei Gao⁴

Affiliations

¹ Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China; School of Geographic Sciences, East China Normal University, Shanghai 200241, China. Electronic address: kxbai@geo.ecnu.edu.cn.
² Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China; School of Geographic Sciences, East China Normal University, Shanghai 200241, China.
³ Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA.
⁴ Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China; School of Geographic Sciences, East China Normal University, Shanghai 200241, China; USDA UV-B Monitoring and Research Program, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA; Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80523, USA.

PMID: 30594898
DOI: 10.1016/j.jenvman.2018.12.071

Abstract

Atmospheric fine particulate matters (PM_2.5) have raised global concerns because of their markedly adverse effects on public health and environmental quality. In parallel with technological variations and social changes in the evolving industrialization pathways in China, there is an acute need to evaluate the long-term spatiotemporal trend of PM_2.5 concentrations across China after years of elevation. Toward this end, an integrated high-resolution satellite-derived (1998-2016) and ground-measured (2015-2017) PM_2.5 data base was applied. Satellite-derived annual mean PM_2.5 grids were firstly validated via comparison with collocated surface in situ PM_2.5 measurements and were then used for trend analyses. The estimated linear trends from gridded PM_2.5 data indicated that PM_2.5 concentrations in China increased mainly before 2008 and have decreased since then, with prominent decreases observed primarily in south China. To corroborate the satellite-based PM_2.5 trend estimations, surface in situ PM_2.5 measurements from the period from 2015 to 2017 were applied to further evaluate the decreasing rate after 2014, at which time the Chinese "Air Pollution Prevention and Control Action Plan" was enforced. The results revealed that the national mean PM_2.5 concentrations decreased by about 6.5 μg/m³ from 2015 to 2017, with prominent decreases (by a rate of 5-10 μg/m³ per year) observed primarily associated with large PM_2.5 concentrations in Central China, North China, Northeast China, and East China during the period from October to December. Our systematic trend assessment provides a deepened understanding of PM_2.5 variations across China in the past few years in association with the newly promoted action plan and offers a brief guideline for relevant policy making in the future.

Keywords: Air quality; Emission control; Fine particulate matter; PM(2.5); Trend analysis.

MeSH terms

Air Pollutants*
Air Pollution*
China
Environmental Monitoring
Particulate Matter

Substances

Air Pollutants
Particulate Matter