Spatiotemporal variations and sources of PM2.5 in the Central Plains Urban Agglomeration, China

Abstract

The Central Plains Urban Agglomeration (CPUA) is the largest region in central China and suffers from serious air pollution. To reveal the spatiotemporal variations and the sources of fine particulate matter (PM_2.5, with an aerodynamic diameter of smaller than 2.5 μm) concentrations of CPUA, multiple and transdisciplinary methods were used to analyse the collected millions of PM_2.5 concentration data. The results showed that during 2017 ~ 2020, the yearly mean concentrations of PM_2.5 for CPUA were 68.3, 61.5, 58.7, and 51.5 μg/m³, respectively. The empirical orthogonal function (EOF) analysis suggested that high PM_2.5 pollution mainly occurred in winter (100.8 μg/m³, 4-year average). The diurnal change in PM_2.5 concentrations varied slightly over the season. The centroid of the PM_2.5 concentration moved towards the west over time. The spatial autocorrelation analysis indicated that PM_2.5 concentrations exhibited a positive spatial autocorrelation in CPUA. The most polluted cities distributed in the northern CPUA (Handan was the centre) formed a high-high agglomeration, and the cities located in the southern CPUA (Xinyang was the centre) formed a low-low agglomeration. The backward trajectory model and potential source contribution function were employed to discuss the regional transportation of PM_2.5. The results demonstrated that internal-region and cross-regional transport of anthropogenic emissions were all important to PM_2.5 pollution of CPUA. Our study suggests that joint efforts across cities and regions are necessary.