Extreme fine particulate matter events in Taiwan Island related to synoptic weather patterns
2021
Lai, Li-Wei
Extreme fine particulate matter (PM₂.₅) events heavily impact residents, incurring high social and medical costs. As such, it is important to understand the characteristics of extreme PM₂.₅ events. This study used hourly PM₂.₅ and meteorological data to elucidate the effects, and predict the occurrence of these extreme weather events in Taiwan. The results show that synoptic conditions are unique for extreme PM₂.₅ events. During the maximum mean PM₂.₅ concentrations, weather conditions in Taiwan were dominated by synoptic weather patterns and the north-easterly monsoon. The maximum mean surface air pressure indicator had also occurred at this time. The azimuth of the resultant surface air pressure was 36.8° + 7.6°, while 96.2% of winds were in the north-north-easterly and north-easterly direction. The back trajectories suggest that the cold continental high air pressure system introduced dry and cold air masses with PM₂.₅. The SIₘₐₓ (μg/m³/h), relative humidity (%), global solar radiation (MJ/m²), visibility (km), weather type I, and weather type II predictor variables of the multi-regression model accounted for 80.6% of the variance in the magnitude of maximum hourly PM₂.₅ events. Extreme PM₂.₅ events were related to synoptic weather characteristics including type, strength, and position. The new quantitative variables aid the development of an efficient alarm system for extreme PM₂.₅ events that will help protect public health.
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