The influence of COVID-19 pandemic on PM2.5 air quality in Northern Taiwan from Q1 2020 to Q2 2021

Sources-attributed contributions to health risks associated with PM2.5-bound polycyclic aromatic hydrocarbons during the warm and cold seasons in an urban area of Eastern Asia

Despite the well-established recognition of the health hazards posed by PM2.5-bound PAHs, a comprehensive understanding of their source-specific impact has been lacking. In this study, the health risks associated with PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) and source-specific contributions were investigated in the urban region of Taipei during both cold and warm seasons. The levels of PM2.5-bound PAHs and their potential health risks across different age groups of humans were also characterized. Diagnostic ratios and positive matrix factorization analysis were utilized to identify the sources of PM2.5-bound PAHs. Moreover, potential source contribution function (PSCF), concentration-weighted trajectory (CWT) and source regional apportionment (SRA) analyses were employed to determine the potential source regions. Results showed that the total PAHs (TPAHs) concentrations ranged from 0.08 to 2.37 ng m-3, with an average of 0.69 ± 0.53 ng m-3. Vehicular emissions emerged as the primary contributor to PM2.5-bound PAHs, constituting 39.8 % of the TPAHs concentration, followed by industrial emissions (37.6 %), biomass burning (13.8 %), and petroleum/oil volatilization (8.8 %). PSCF and CWT analyses revealed that industrial activities and shipping processes in northeast China, South China Sea, Yellow Sea, and East China Sea, contributed to the occurrence of PM2.5-bound PAHs in Taipei. SRA identified central China as the primary regional contributor of ambient TPAHs in the cold season and Taiwan in the warm season, respectively. Evaluations of incremental lifetime cancer risk demonstrated the highest risk for adults, followed by children, seniors, and adolescents. The assessments of lifetime lung cancer risk showed that vehicular and industrial emissions were the main contributors to cancer risk induced by PM2.5-bound PAHs. This research emphasizes the essential role of precisely identifying the origins of PM2.5-bound PAHs to enhance our comprehension of the related human health hazards, thus providing valuable insights into the mitigation strategies.

Photochemical oxidation of VOCs and their source impact assessment on ozone under de-weather conditions in Western Taiwan

The application of statistical models has excellent potential to provide crucial information for mitigating the challenging issue of ozone (O3) pollution by capturing its associations with explanatory variables, including reactive precursors (VOCs and NOX) and meteorology. Considering the large contribution of O3 in degrading the air quality of western Taiwan, three-year (2019-2021) hourly concentration data of VOC, NOX and O3 from 4 monitoring stations of western Taiwan: Tucheng (TC), Zhongming (ZM), Taixi (TX) and Xiaogang (XG), was evaluated to identify the effect of anthropogenic emissions on O3 formation. Owing to the high-ambient reactivity of VOCs on the underestimation of sources, photochemical oxidation was assessed to calculate the consumed VOC (VOCcons) which was followed by the source identification of their initial concentrations. VOCcons was observed to be highest in the summer season (16.7 and 22.7 ppbC) at north (TC and ZM) and in the autumn season (17.8 and 11.4 ppbC) in southward-located stations (TX and XG, respectively). Results showed that VOCs from solvents (25-27%) were the major source at northward stations whereas VOCs-industrial emissions (30%) dominated in south. Furthermore, machine learning (ML): eXtreme Gradient Boost (XGBoost) model based de-weather analysis identified that meteorological factors favor to reduce ambient O3 levels at TC, ZM and XG stations (-67%, -47% and -21%, respectively) but they have a major role in accumulating the O3 (+38%) at the TX station which is primarily transported from the upwind region of south-central Taiwan. Crucial insights using ML outputs showed that the finding of the study can be utilized for region-specific data-driven control of emission from VOCs-sources and prioritized to limit the O3-pollution at the study location-ns as well as their accumulation in distant regions.