This project collected PM2.5 to analyze mass and chemical speciation concentrations at the six stations in Taiwan. The PM2.5 mass and chemical speciation concentrations increased from the east through the north to the central and south of Taiwan for the sampling days ended by November 2022. The three most frequently occurring high PM2.5 concentration days for stations were in the order of the Chiayi, Xiaogang, and Douliu stations. The resolved chemical speciation characteristics persistently revealed the importance of controlling NOx pollution sources. The high PM2.5 concentration days were largely due to bad environmental ventilation causing pollutant accumulations, although some sampling days were influenced by transboundary transport. The summed metal elemental concentration of each station at Xiaogang, Chiayi, and Douliu was higher than that of each station at the Zhongming, Banqiao, and Hualien stations, with various high-concentration metal elements indicating multiple sources. Among relatively high-concentration metal elements were those characterized by the emissions from coal burning, iron and steel manufacturing, and vehicles. Comparing 2022 to 2017 for all stations, the PM2.5 mass and major chemical speciation concentrations were all reduced, with the highest reduction fraction in EC followed by SO42- and NH4+, and the lowest in OC, and thus a rise of OC in PM2.5 proportion. The quarterly spatial distribution showed that Q1 was the highest quarter of the PM2.5 mass and major chemical speciation concentrations followed by Q4 and Q2 in most stations for the most recent six years. The highest summed metal elemental concentrations in Q1~Q3 were frequently in 2021 and Q4 in 2019 for the most recent six years. The quarterly contributions of pollution factors of PMF receptor modeling showed that the highest concentration in Q1 was predominantly contributed by “Nitrate” followed by “Sulfate” and “Vehicle Emissions” in all stations from 2017 to 2022. This fact implies that SO42- and OC must also be controlled in addition to NO3-. For the high PM2.5 concentration days, the highest average concentration of chemical species was NO3- for the four stations south of the Zhongming (included) in the most recent six years. Therefore, controlling the precursor pollution sources of NO3- is crucial to reducing the high PM2.5 concentration days. A rise in PM2.5 mass concentration in 2021 can be partly accounted for by the influence of dry weather in Q1 at the Douliu, Chiayi, and Xiaogang stations. The high spatial similarity of PM2.5, SO42-, and OC at the Douliu, Chiayi, and Xiaogang stations may indicate an influence of regional pollution sources. In contrast, the low spatial similarity of NO3- among all stations implies the predominant influence of local pollution sources. In summary, this project analyzed the temporal and spatial distributions of the PM2.5 mass and chemical speciation concentrations. It summarized 2017~2022 data to clear out the variation trends of the influential factors and PM2.5 mass and chemical speciation concentrations. The direction for controlling pollution sources is also provided in the study results.

PM2.5 chemical speciation, Temporal and spatial distributions, PM2.5 pollution sources, Atmospheric visibility