The role of temporal scales in extracting dominant meteorological drivers of major airborne pollutants

Abstract

The influence of individual meteorological factors on different airborne pollutants has been widely studied. However, few studies have considered the effect of temporal scales on the extracted pollutant-meteorology association. Based on convergent cross mapping (CCM), we compared the influence of major meteorological factors on PM2.5, PM10 and O3 concentrations in 2020 at the 3 and 24h scales respectively. In terms of the extracted dominant meteorological factor, the consistence between the analysis at the 3 and 24h scales was relatively low, suggesting a large difference even from a qualitative perspective. In terms of the mean p value, the effect of temporal scale on PM (PM2.5 and PM10)-meteorology association was consistent, yet largely different from the temporal-scale effect on O3. Temperature was the most important meteorological factor for PM2.5, PM10 and O3 across China at both the 3 and 24h scales. For PM2.5 and PM10, the extracted PM-temperature association at the 24h scale was stronger than that at the 3h scale. Meanwhile, for summer O3, due to strong reactions between precursors, the extracted O3-temperature association at the 3h scale was much stronger. Due to the discrete distribution, the extracted association between all pollutants and precipitation was much weaker at the 3h scale. Similarly, the extracted PM-wind association was notably weaker at the 3h scale. Due to precursor transport, summertime O3-wind association was stronger at the 3h scale. For atmospheric pressure, the pollutant-pressure association was weaker at the 3h scale except for summer, when interactions between atmospheric pressure and other meteorological factors were strong. From the spatial perspective, pollutant-meteorology associations at 3 and 24h were more consistent in the heavily polluted regions, while extracted dominant meteorological factors for pollutants demonstrated more difference at 3 and 24h in the less polluted regions. This research suggests that temporal scales should be carefully considered when extracting natural and anthropogenic drivers for airborne pollution.