Spatiotemporal variation characteristics of PM_2.5 across Shanghai in 2018

Background Long-term exposure to PM_2.5 poses a serious threat to human health. The spatial variability in air pollution within a large city is resulted from complex causes of air pollution. It will lead to exposure misclassification if a single measurement is used to evaluate exposure in epidemiological studies.

Objective This study aims to understand the pollution levels of PM_2.5 and potential causes of spatiotemporal variability and analyze the spatial distribution characteristics of PM_2.5 in Shanghai.

Methods Twenty fixed monitoring sites were selected in Shanghai in 2018, including regional background, urban background, and street-level sites. Three two-week PM_2.5 samples were measured during winter, summer, and fall per site, and the average concentrations in the year and the three seasons for each site were calculated using continuous measurements at one routine background site 2km away from the national automatic monitoring station as a reference. Spatiotemporal variation analysis and variance apportionment analysis were conducted. PM_2.5 concentrations in different seasons were estimated by ordinary Kriging interpolation method, and their precisions were evaluated by leave one out cross validation (LOOCV).

Results The annual average calibrated concentration of PM_2.5 was 39.87 μg·m^-3, and the average calibrated concentration was higher in autumn and winter than in summer. There were no significant differences between different site types across the year (Ps>0.05). In addition, 83.84% of the overall PM_2.5 variances were attributable to the variability among sites and 16.16% to the variability of seasons. The PM_2.5 spatial variability in different seasons was mostly determined by differences among sites. The coefficient of determination (R²) by Kriging interpolation model ranged from 0.33 to 0.85, and the LOOCV root mean squared error ranged from 4.88 to 8.41 μg·m^-3. PM_2.5 concentration trend surface showed that the area with high-concentration pollution was located in the western region of Shanghai.

Conclusion The PM_2.5 concentration exhibits a distinct spatiotemporal variation trend that the level is higher in winter and autumn than in summer, and higher in the western area than in the eastern area of Shanghai. Kriging interpolation can provide a spatial analysis on PM_2.5 exposure.