Satellite-Based Estimates of Daily NO2 Exposure in China Using Hybrid Random Forest and Spatiotemporal Kriging Model

作者：Yu Zhan, Yuzhou Luo, Xunfei Deng, Kaishan Zhang, Minghua Zhang, Michael L. Grieneisen, Baofeng Di · 发表于：Environmental Science & Technology · 年份：2018 · DOI：10.1021/acs.est.7b05669 · 被引用次数：256 · 研究领域：Air Quality and Health Impacts、Air Quality Monitoring and Forecasting、Impact of Light on Environment and Health

A novel model named random-forest-spatiotemporal-kriging (RF-STK) was developed to estimate the daily ambient NO 2 concentrations across China during 2013–2016 based on the satellite retrievals and geographic covariates. The RF-STK model showed good prediction performance, with cross-validation R 2 = 0.62 (RMSE = 13.3 μg/m 3 ) for daily and R 2 = 0.73 (RMSE = 6.5 μg/m 3 ) for spatial predictions. The nationwide population-weighted multiyear average of NO 2 was predicted to be 30.9 ± 11.7 μg/m 3 (mean ± standard deviation), with a slowly but significantly decreasing trend at a rate of −0.88 ± 0.38 μg/m 3 /year. Among the main economic zones of China, the Pearl River Delta showed the fastest decreasing rate of −1.37 μg/m 3 /year, while the Beijing-Tianjin Metro did not show a temporal trend ( P = 0.32). The population-weighted NO 2 was predicted to be the highest in North China (40.3 ± 10.3 μg/m 3 ) and lowest in Southwest China (24.9 ± 9.4 μg/m 3 ). Approximately 25% of the population lived in nonattainment areas with annual-average NO 2 > 40 μg/m 3 . A piecewise linear function with an abrupt point around 100 people/km 2 characterized the relationship between the population density and the NO 2, indicating a threshold of aggravated NO 2 pollution due to urbanization. Leveraging the ground-level NO 2 observations, this study fills the gap of statistically modeling nationwide NO 2 in China, and provides essential data for epidemiological research and air quality management.