Estimation of Short-Term and Long-Term Ozone Exposure Levels in Beijing–Tianjin–Hebei Region Based on Geographically Weighted Regression Model

Abstract

In recent years, ozone (O3) concentration has shown a decreasing trend in the Beijing–Tianjin–Hebei (BTH) region in China. However, O3 pollution remains a prominent problem. Accurate estimation of O3 exposure levels can provide support for epidemiological studies. A total of 13 variables were combined to estimate short- and long-term O3 exposure levels using the geographically weighted regression (GWR) model in the BTH region with a spatial resolution of 1 × 1 km from 2017 to 2020. Five variables were left in the GWR model. O3 concentration was positively correlated with temperature, wind speed, and SO2, whereas is was negatively correlated with precipitation and NO2. Results showed that the model performed well. Leave-one-out cross-validation (LOOCV) R2 for short- and long-term simulation results were 0.91 and 0.71, and the values for RMSE were 11.14 and 3.49 μg/m3, respectively. The annual maximum 8 h average O3 concentration was the highest in 2018 and the lowest in 2020. Decreasing concentrations of major precursors of O3 due to the regional joint prevention and control may be the reason. O3 concentration was high in the southeast of the BTH region, including in Hengshui, Handan, Xingtai and Cangzhou.