This new method highlighted the influences of spatial distribution for source contributions, and the effectiveness of the SWPSCF method was evaluated.

Combining the PMF results, we developed the source-weighted potential source contribution function (SWPSCF) method for source localization. High contributions of resuspended dust occurred at sites with intensive construction activities, such as subway and airport construction. 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. 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. A total of five sources were identified, with average contributions of 15.5вЂ‰% (traffic emissions), 19.7вЂ‰% (coal and biomass combustion), 8.8вЂ‰% (industrial emissions), 39.7вЂ‰% (secondary particles), and 16.2вЂ‰% (resuspended dust). The positive matrix factorization (PMF) model was applied to quantify PM 2.5 sources. SO 4 2 - / NO 3 - mass ratio at most sites exceeded 1 in 2015Д«ut 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 SO 4 2 - and NO 3 -Д¬oncentrations. Period, a decreasing trend was observed for the annual average concentration of PM 2.5, especially at sampling sites in layerВ 1, where the stricter control policies were implemented.

Urbanization levels had a strong effect on air quality. The PM 2.5 composition of layerВ 3 in 2019 was found to be similar to that of the other layers 2 or 3 years ago, implying that Spatial clustering of the chemical composition at the sampling sites was conducted for each The average PM 2.5 concentrations for 5В years were in the order of LayerВ 3 belonged to the outermost zone with the lowest urbanization level. Zone of Chengdu, layerВ 2 was located in the outer circle of layerВ 1, and LayerВ 1 was the most urbanized area and referred to the core Total of 836 samples were collected from 19 sites in winter 2015вЂ“2019.ДЄccording to the specific characteristics, 19 sampling sites were assigned

Investigate the spatiotemporal and policy-related variations of PM 2.5Д¬omposition and sources based on long-term observation at multiple sites. Rapidly developing Chinese megacity, Chengdu, as the study area to Study health effects and improve air quality. A thorough understanding of the relationship between urbanizationДЄnd PM 2.5 (fine particulate matter with aerodynamic diameter less thanДў.5 Вµm) variation is crucial for researchers and policymakers to

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