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. A thorough understanding of the relationship between urbanizationand PM2.5 (fine particulate matter with aerodynamic diameter less than2.5 µm) variation is crucial for researchers and policymakers tostudy health effects and improve air quality. In this study, we selected arapidly developing Chinese megacity, Chengdu, as the study area toinvestigate the spatiotemporal and policy-related variations of PM2.5composition and sources based on long-term observation at multiple sites. Atotal of 836 samples were collected from 19 sites in winter 2015–2019.According to the specific characteristics, 19 sampling sites were assignedto three layers. Layer 1 was the most urbanized area and referred to the corezone of Chengdu, layer 2 was located in the outer circle of layer 1, andlayer 3 belonged to the outermost zone with the lowest urbanization level.The average PM2.5 concentrations for 5 years were in the order oflayer 2 (133 µg m−3) &gt; layer 1 (126 µg m−3) &gt; layer 3 (121 µg m−3). Spatial clustering of the chemical composition at the sampling sites was conducted for eachyear. The PM2.5 composition of layer 3 in 2019 was found to be similar to that of the other layers 2 or 3 years ago, implying thaturbanization levels had a strong effect on air quality. During the samplingperiod, a decreasing trend was observed for the annual average concentration of PM2.5, especially at sampling sites in layer 1, where the stricter control policies were implemented. TheSO42-/NO3- mass ratio at most sites exceeded 1 in 2015but 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 PM2.5 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 contributions of resuspended dust occurred at sites with intensive construction activities, such as subway and airport construction. Combining the PMF results, we developed the source-weighted potential source contribution function (SWPSCF) method for source localization. This new method highlighted the influences of spatial distribution for source contributions, and the effectiveness of the SWPSCF method was evaluated.

atmospheric chemistry and physics

Measurement report: Spatiotemporal and policy-related variations of PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; composition and sources during 2015–2019 at multiple sites in a Chinese megacity