Two-stage model for estimating the spatiotemporal distribution of hourly PM1.0 concentrations over central and east China

Wei Wang; Feiyue Mao; Bin Zou; Jianping Guo; Lixin Wu; Zengxin Pan; Lin Zang

doi:10.1016/j.scitotenv.2019.04.134

Two-stage model for estimating the spatiotemporal distribution of hourly PM1.0 concentrations over central and east China

Sci Total Environ. 2019 Jul 20:675:658-666. doi: 10.1016/j.scitotenv.2019.04.134. Epub 2019 Apr 10.

Authors

Wei Wang¹, Feiyue Mao², Bin Zou¹, Jianping Guo³, Lixin Wu¹, Zengxin Pan⁴, Lin Zang⁴

Affiliations

¹ School of Geosciences and Info-Physics, Central South University, China.
² School of Remote Sensing and Information Engineering, Wuhan University, China; State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, China. Electronic address: maofeiyue@whu.edu.cn.
³ State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China.
⁴ State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, China.

PMID: 31039500
DOI: 10.1016/j.scitotenv.2019.04.134

Abstract

Widespread and severe PM_1.0 (particulate matter ≤1.0 μm) pollution in China has a significant negative influence on human health. However, knowledge of the regional spatiotemporal distribution of PM_1.0 has been hindered by sparsely distributed PM_1.0 concentration data. In this work, a two-stage model (linear mixed effect-bagged tree model) was proposed for estimating hourly PM_1.0 pollution levels from July 2015 to June 2017 over central and east China by using Himawari-8 aerosol products and coincident geographic data, meteorology, and site-based PM_1.0 concentrations from ground monitoring network. The cross-validation for the developed model displayed R² and mean absolute error value of 0.80 and 9.3 μg/m³, respectively. Validation demonstrated that the model accurately estimated hourly PM_1.0 concentrations with high R² of 0.63-0.85 and low bias of 8.7-10.1 μg/m³. The estimated PM_1.0 concentrations on daily scale showed peaks with PM_1.0 of 36.9 ± 8.4 μg/m³ at rush hours during daytime. Seasonal distribution displayed that summer was cleanest with an average PM_1.0 of 20.9 ± 6.8 μg/m³ and winter was the most polluted season with an average PM_1.0 of 45.6 ± 16.8 μg/m³. These results indicated that the proposed satellite-based model can estimate reliable spatial distribution of PM_1.0 concentrations over a large-scale region.

Keywords: Bagged tree; Himawari-8; Hourly; LME; PM(1.0).