Stable and transport indices applied to winter air pollution over the Yangtze River Delta, China.

Abstract

Previous studies have developed a stable weather index (SWI) based on meteorological elements that adequately represent PM2.5 pollution over the North China Plain (NCP). However, the SWI performs poorly over the Yangtze River Delta (YRD) region because air pollution over this region is affected not only by stagnant weather (STAG) but also by transport (TRANS). For example, air pollutants can be transported from the NCP to the YRD by cold fronts. In this study, an obliquely rotated principal component analysis in the T-model is applied to classify the synoptic patterns of winter weather over the YRD region from 2013 to 2018. Among the four identified synoptic patterns, two of which cause TRANS, one pattern is most likely to cause STAG, and one pattern can lead to either STAG or TRANS depending on the location of high pressure around Shandong province. Due to the large contribution (63%) of TRANS to the total PM2.5 pollution events, a transport pollution index (TPI) is constructed to describe the transport features of PM2.5 pollution over the YRD region. Our results show that, when considering the SWI alone, the correlation coefficients between the SWI and ln(PM2.5) range from 0.50 to 0.57 in the main cities of the YRD. Excitingly, when considering both the TPI and SWI (TPI+SWI), the correlation coefficients increase significantly to 0.63-0.78, suggesting that TPI+SWI better reflects the wintertime PM2.5 pollution level over the YRD region. In addition, satisfactory performance in validation also suggests that TPI+SWI can increase the accuracy of evaluating and forecasting of PM2.5 pollution episodes over regions downstream of source emissions.