In recent years, the Chinese government has made tremendous efforts to reduce the emissions of atmospheric pollutants throughout the country. An apparent improvement in air quality was observed in Beijing and its adjacent region during the winter of 2017/2018. However, caution should be taken in directly attributing this improvement to air control actions without taking the effects of climate variability into account. Here, we develop a statistical prediction model that can successfully predict the variability of wintertime PM2.5 concentrations observed over these regions. Our analysis indicates that the remarkable decrease in PM2.5 concentrations over the North China Plain (NCP) observed during the winter of 2017/2018 can be largely explained by changes in meteorological conditions. To clarify which climate factors control the inter-annual variability of wintertime PM2.5 pollution over the NCP, we further reconstructed a 30-year time series of wintertime PM2.5 levels over the NCP over the period of 1988-2017 using our statistical model. Through our analysis, we found that the combined Arctic-tropical climate effects related to the ENSO and Arctic warming controlled the inter-annual variability of wintertime PM2.5 over the NCP. Specifically, the rapid warming of the Barents-Kara Sea region enhances the Siberian High and thus plays an important role in improving the air quality over the NCP during the 2017/2018 wintertime. These results help us understand the role of climate variability in modulating air quality, especially its contributions to the winter of 2017/2018. These results may assist in the evaluation of current air control actions and the revision of relevant policy for the future, which are urgently needed for China.
Keywords: Arctic warming; Inter-annual variability; North China Plain; PM(2.5).
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