Measurement report: Spatiotemporal and policy-related variations of PM.sub.2.5 composition and sources during 2015-2019 at multiple sites in a Chinese megacity

A thorough understanding of the relationship between urbanization and PM.sub.2.5 (fine particulate matter with aerodynamic diameter less than 2.5 µm) variation is crucial for researchers and policymakers to study health effects and improve air quality. In this study, we selected a rapidly developing Chinese megacity, Chengdu, as the study area to investigate the spatiotemporal and policy-related variations of PM.sub.2.5 composition and sources based on long-term observation at multiple sites. A total of 836 samples were collected from 19 sites in winter 2015-2019. According to the specific characteristics, 19 sampling sites were assigned to three layers. Layer 1 was the most urbanized area and referred to the core zone of Chengdu, layer 2 was located in the outer circle of layer 1, and layer 3 belonged to the outermost zone with the lowest urbanization level. The average PM.sub.2.5 concentrations for 5 years were in the order of layer 2 (133 µg m.sup.-3) > layer 1 (126 µg m.sup.-3) > layer 3 (121 µg m.sup.-3). Spatial clustering of the chemical composition at the sampling sites was conducted for each year. The PM.sub.2.5 composition of layer 3 in 2019 was found to be similar to that of the other layers 2 or 3 years ago, implying that urbanization levels had a strong effect on air quality. During the sampling period, a decreasing trend was observed for the annual average concentration of PM.sub.2.5, especially at sampling sites in layer 1, where the stricter control policies were implemented. The SO42-/NO3- mass ratio at most sites exceeded 1 in 2015 but dropped to less than 1 since 2016, reflecting decreasing coal combustion and increasing traffic impacts in Chengdu, and these values can be further supported by temporal variations of the SO42- and NO3- concentrations. The positive matrix factorization (PMF) model was applied to quantify PM.sub.2.5 sources. A total of five sources were identified, with average contributions of 15.5 % (traffic emissions), 19.7 % (coal and biomass combustion), 8.8 % (industrial emissions), 39.7 % (secondary particles), and 16.2 % (resuspended dust). From 2015 to 2019, a dramatic decline was observed in the average percentage contributions of coal and biomass combustion, but the traffic emission source showed an increasing trend. For spatial variations, the high coefficient of variation (CV) values of coal and biomass combustion and industrial emissions indicated their higher spatial difference in Chengdu. High contributio