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In addition to the Taiwan Strait, the geographical channel effect (GCE) has been observed in the Taipei Basin during winters. This study explored the potential links amongst GCE phenomena in the basin, fine particulate matter (PM2.5) events, and position of the continental high-pressure system (CHPS). Principal component analysis was applied to classify the CHPS distribution patterns influencing PM2.5 concentrations and meteorological parameters in the Taipei metropolis. In addition, non-parametric Kruskal–Wallis and Dwass–Steel–Critchlow–Fligner tests were applied to compare the parameters amongst distinct groups. Moreover, track analysis was utilised to trace the trajectories of air masses. The merged Dark Target Aerosol Angstrom Exponent (Ocean), Deep Blue Aerosol Angstrom Exponent (Land), and Aerosol Optical Depth (AOD) 3 km (Land and Ocean) of Terra/MODIS and Aqua/MODIS were used to confirm the connection of long-range PM2.5 transport. Two features in the atmospheric environment induce double GCEs: (1) wind direction below 90° in most of the upwind area of the Taisumi and Xindian River Basins; (2) CHPS centres moved across 110° E. Double GCEs can reduce the magnitude of PM2.5 air pollution and shape the distribution of PM2.5; however, they cannot prevent PM2.5 events. [ABSTRACT FROM AUTHOR]

On 4 June 2021, short-duration extreme precipitation occurred in Taipei. Within 2 h, over 200 mm of rainfall accumulated in the Xinyi district. In this study, advanced data assimilation technology (e.g., hybrid data and 3D variations) was incorporated to develop a high-resolution, small-scale (e.g., northern Taiwan) data assimilation forecast system, namely the weather research and forecast-grid statistical interpolation (WRF-GSI) model. The 3D wind field data recorded by the Doppler wind lidar system of Taipei Songshan Airport were assimilated for effective simulation of the extreme precipitation. The results revealed that the extreme rainfall was caused by the interaction between the northeast wind incurred by a front to the north of Taiwan, a humid southerly wind generated by Typhoon Choi-wan, and the regional sea–land breeze circulation. For the Xinyi district, the WRF-GSI_lidar model reported accumulated rainfall 30 mm higher than that in the non-assimilated experiment (WRF-GSI_noDA), indicating that the WRF-GSI model with lidar observation was improved 15% more than the nonassimilated run.

Long-range transport (LRT) can carry air pollutants to downwind areas. However, studies about the impacts of LRT on bacterial communities are few. This study investigated the influence of Asian dust storms (ADS) and frontal pollution (FP) on bacterial communities in ambient air using next-generation sequencing (NGS) and Terminal Restriction Fragment Length Polymorphism (T-RFLP). Air samples were collected at Cape Fugui (CF) and National Taiwan University (NTU) in northern Taiwan before (or background days), during, and after LRTs from November 2013 to March 2015. The richness, H index, and evenness increased during FPs and then decreased after FPs. During and after ADS and FP, the prevalence of the phylum Proteobacteria decreased, but that of Firmicutes increased. The dominant class of Proteobacteria changed from Alphaproteobacteria on background days to Betaproteobacteria during LRTs. At the genus level, the high abundance of Ralstonia and Bacillus during FP and Clostridium during ADS were detected at both locations. Additionally, Ralstonia was dominant at CF during ADS. In conclusion, FP and ADS both changed the bacterial community. The indicator genus was Clostridium and Ralstonia for ADS as well as Bacillus and Ralstonia for FP. Given the potential health threats posed by the bioaerosols transported, people should avoid outdoor activities during LRTs.