## 3 Results and Discussions
### Analysis of Potential Source Areas of Pollution  
The TraiStat software was utilized to conduct a source apportionment analysis (WPSCF) for PM\({}_{2.5}\) in Chenzhou City. The spatial trajectories of the air masses, calculated using HYSPLIT, were subdivided into grids of 0.5\({}^{\circ}\) by 0.5\({}^{\circ}\). The PM\({}_{2.5}\) benchmark was calibrated against the national standard secondary concentration daily average limit of 75 ug\(\cdot\)m\({}^{-3}\). The season-specific results of the WPSCF computation are depicted in Figure 8.  
Significant variations emerge in the potential origins of PM\({}_{2.5}\) pollution across the seasons in Chenzhou City. During spring, regions with elevated pollution sources predominantly manifest at the confluence of Jiangxi and northwest Guangdong provinces. Notably, a WPSCF exceeding 0.40 is evident in Ganzhou City. Moreover, scattered zones of relatively heightened pollution sources are observed in central Shaanxi, southeastern Gansu, central China, southwestern Shandong, and central Henan. During summer, Chenzhou City exhibits the most subdued PM\({}_{2.5}\) concentrations of all seasons, with the majority of its WPSCF values registering below 0.10. Regions boasting a WPSCF exceeding 0.10 are predominantly clustered in northern Shaoguan. In autumn, the WPSCF across Chenzhou City and its environs spans between 0.10 and 0.40. Elevated WPSCF values (WPSCF \(>\) 0.60) coalesce at the confluence of Anhui, Hubei, and Jiangxi provinces, with peak concentrations pinpointed in the Jingjiang sector of southern Hubei and Jiujiang in western Jiangxi. In winter, the Huaibei region records the most pronounced WPSCF values compared to the other three seasons, with a notable surge in values surpassing 0.60, indicative of a concentrated pollution source distribution. Elevated concentrations predominantly amass at the interface between northwest Guangdong and Chenzhou City, as well as in the central and western precincts of Jiangxi, encompassing the Ganzhou region, and the urban areas of Hubei including Shiyan, Changde, and Changsha. To authenticate the findings of the WPSCF simulation and explore further the impact of potential source regions on PM\({}_{2.5}\) pollution in Chenzhou City, we executed a concentration-weighted trajectory calculation (CWTC) using the initial dataset (Figure 9). A heightened CWTC value indicates a more pronounced contribution to the pollution in the specified area. In this investigation, areas with CWTC values exceeding 75 \(\upmu\)g\(\cdot\)m\({}^{-3}\) are identified as principal contributors to the pollution. The results of the WCWT calculations (Figure 9) align closely with those of the WPSCF analysis. During spring and summer, only a sparse number of potential source regions exhibit WCWT values exceeding 75 \(\upmu\)g\(\cdot\)m\({}^{-3}\). In spring, these elevated value areas are predominantly situated within the confluence of Jiangxi, Guangdong, and Hunan, encompassing the Chenzhou vicinity. Conversely, during summer, these regions with relatively high values predominantly manifest as bands stretching across the central and western expanses of Jiangxi and the southeastern reaches of Hunan. During autumn, the primary zones contributing to pollution (WCWT > 75 \(\upmu\)g\(\cdot\)m\({}^{-3}\)) coalesce at the confluence of Hunan, Jiangxi, Guangdong, and Hubei provinces. Additionally, sporadic elevated values (WCWT  
Figure 8: Seasonal distribution of potential PM\({}_{2.5}\) source areas in Chenzhou City (**(a)** Spring distribution **(b)** Summer distribution **(c)** Autumn distribution **(d)** Winter distribution) (note: the illustration was crafted utilizing ArcGIS software, specifically version 10.2. For further reference, please visit the following URL: [[https://www.arcgis.com/index.html](https://www.arcgis.com/index.html)]([https://www.arcgis.com/index.html](https://www.arcgis.com/index.html)) (accessed on 16 October 2023)). > 90 \(\mathrm{\SIUnitSymbolMicro m^{-3}}\)) emerge in the transitional area between northeastern Shaanxi and Luliang.