Spatiotemporal distributions of surface ozone levels in China from 2005 to 2017: A machine learning approach

• Main Authors: Riyang Liu, Zongwei Ma, Yang Liu, Yanchuan Shao, Wei Zhao, Jun Bi
• Format: Article
• Language: English
• Published: Elsevier 2020-09-01
• Series: Environment International
• Subjects: Surface ozone; MDA8; XGBoost; Spatiotemporal patterns
• Online Access: http://www.sciencedirect.com/science/article/pii/S0160412020317785

In recent years, ground-level ozone has become a severe ambient pollutant in major urban areas of China, which has adverse impacts on population health. However, in-situ measurements of the ozone concentration before 2013 in China are quite scarce, which cannot facilitate the assessment of the long-term trends and effects of ozone pollution. In this study, we used daily maximum 8-hour average (MDA8) ozone observations from 2013 to 2017 combined with concurrent ozone retrievals, aerosol reanalysis, meteorological parameters, and land-use data to establish a nationwide MDA8 prediction model based on the eXtreme Gradient Boosting (XGBoost) algorithm. The model achieves high prediction accuracy compared with other studies, with R2 values for the by-year, site-based, and sample-based cross-validation (CV) schemes of 0.61, 0.64, and 0.78, respectively, at the daily level. External testing with regional measurements from 2005 to 2012 and nationwide data in 2018 have shown that the model is robust and reliable for historical data prediction, with external model testing R2 values ranging from 0.60 to 0.87 at the month level in different years. Using the final estimator, we obtained nationwide monthly mean ozone concentrations from 2005 to 2012 and daily MDA8 ozone concentrations from 2013 to 2017 at a resolution of 0.1° × 0.1°. According to the average number of days exceeding the standard and the average of the 90th percentile of the MDA8 ozone concentrations, the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta, the Pearl River Delta, the Jianghan Plain, the Sichuan Basin, and the Northeast Plain regions were identified as pollution hotspots. During the research period, the overall ozone levels fluctuated slightly, and their trends were not spatially continuous. There was a significant increasing trend in the BTH region by 1.37 (95% CI: 0.46,2.29) μg/m3/year between 2013 and 2017. In 2017, 26.24% of the population lived in areas exceeding the Chinese grade II national air quality standard, which shows that ozone pollution has posed an obvious threat to population health in China. Our products will provide reliable support for future long-term nationwide health impact studies and policy-making for pollution control and prevention.