It is known that individual meteorological factors affect the concentrations of fine particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5), yet the specific meteorological effects found in previous studies are largely inconsistent and even conflicting. This study investigates influences of daily and short term changes in synoptic weather on ground-level PM2.5 concentrations in a large geographical area (75 cities across the contiguous United States (U.S.)) by using ten-year (2001–2010) spatial synoptic classification (SSC) data. We find that in the spring, summer, and fall the presence of the tropical weather types (i.e., dry-tropical (DT) and moist-tropical (MT)) is likely to associate with significantly higher levels of PM2.5 as compared to an all-weather-type-day average, and the presence of the polar weather types (i.e., dry-polar (DP) and moist-polar (MP)) is associated with significantly lower PM2.5 concentrations. The short-term (day to day) changes in synoptic weather types in a region are also likely to lead to significant variance in PM2.5 concentrations. For example, the largest increase in PM2.5 concentration occurs with the synoptic weather type changing from DP-to-MT. Conversely, a MT-to-DP weather type change results in the largest decrease in PM2.5 concentrations. Compared to air temperature, the effects of atmospheric moisture on PM2.5 concentration tend to be subtle, demonstrating that in conjunction with moderate temperature, neither the dry nor the moist air (except moist-moderate (MM) in summer) are associated with significantly high or low PM2.5 concentrations. Finally, we find that the effects of the synoptic weather type on PM2.5 concentrations may vary for different seasons and geographical areas. These findings suggest that interactions between atmospheric factors and seasonal and/or geographical factors have considerable impacts on the PM2.5 concentrations, and therefore should be considered in addition to the SSC when conducting environment health assessments.
- Air quality
- PM concentrations
- Spatial synoptic classification
- Synoptic weather