Spatiotemporal patterns of PM10 concentrations over China during 2005-2016: A satellite-based estimation using the random forests approach

Environmental Pollution
Gongbo ChenYuming Guo

Abstract

Few studies have estimated historical exposures to PM10 at a national scale in China using satellite-based aerosol optical depth (AOD). Also, long-term trends have not been investigated. In this study, daily concentrations of PM10 over China during the past 12 years were estimated with the most recent ground monitoring data, AOD, land use information, weather data and a machine learning approach. Daily measurements of PM10 during 2014-2016 were collected from 1479 sites in China. Two types of Moderate Resolution Imaging Spectroradiometer (MODIS) AOD data, land use information, and weather data were downloaded and merged. A random forests model (non-parametric machine learning algorithms) and two traditional regression models were developed and their predictive abilities were compared. The best model was applied to estimate daily concentrations of PM10 across China during 2005-2016 at 0.1⁰ (≈10 km). Cross-validation showed our random forests model explained 78% of daily variability of PM10 [root mean squared prediction error (RMSE) = 31.5 μg/m3]. When aggregated into monthly and annual averages, the models captured 82% (RMSE = 19.3 μg/m3) and 81% (RMSE = 14.4 μg/m3) of the variability. The random forests model showed much higher...Continue Reading

Citations

Feb 12, 2019·Stroke; a Journal of Cerebral Circulation·Gongbo ChenYuming Guo
Jul 3, 2020·Journal of Environmental Science and Health. Part A, Toxic/hazardous Substances & Environmental Engineering·Mona ElbarbaryJoel Negin
Aug 10, 2019·International Journal of Environmental Research and Public Health·Wenxuan XuXueqian Zhang
May 10, 2020·International Journal of Environmental Research and Public Health·Mona ElbarbaryJoel Negin
Sep 7, 2020·Environmental Pollution·Hongyao YuUNKNOWN Seven Northeastern Cities Study group
Feb 2, 2021·The Science of the Total Environment·Zilong ZhangYuming Guo
Mar 1, 2021·The Science of the Total Environment·Jian HouChongjian Wang
Mar 20, 2021·Clinical Nutrition : Official Journal of the European Society of Parenteral and Enteral Nutrition·Jian HouChongjian Wang
Apr 25, 2021·Environmental Research·Lei WangUNKNOWN China Multi-Ethnic Cohort (CMEC) collaborative group
Jul 16, 2021·Environmental Pollution·Shin ArakiUNKNOWN Japan Environment and Children's Study Group
Aug 4, 2021·Environmental Science and Pollution Research International·Jian HouChongjian Wang
Nov 22, 2019·Environmental Science & Technology·Alexandra ShteinMassimo Stafoggia

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