North China frequently experiences severe particulate pollution days (SPPDs, days when the daily mean concentration of particulate matter <2.5 μm (PM2.5) exceeds 150 μg m−3) in boreal winter, which have essential impacts on visibility, ecosystems, human health, and climate. Although stringent clean-air regulations have since been implemented in China, and the annual mean PM2.5 concentration in China decreased by approximately 33% over 2013–2019, unexpected SPPDs still occurred in Beijing during the COVID-19 lockdown period when emissions were extremely low. Therefore, understanding the meteorological mechanisms responsible for the occurrence of SPPDs is important for air-quality management planning.
On April 21, 2022, a study titled "Winter particulate pollution severity in North China driven by atmospheric teleconnections" was published online in Nature Geoscience (https://doi.org/10.1038/s41561-022-00933-2). This research was a collaborationbetween Nanjing University of Information Science & Technology, Georgia Institute of Technology in USA, and Centre for Southern Hemisphere Oceans Research in Australia. The studyidentified the conducive weather patterns (CWPs) that are favorable for the formation of wintertime severe particulate pollution days (SPPDs) in North China by using a weather classification technique. Considering more than 100 climate factors, including atmospheric teleconnections, sea surface temperature and the Arctic sea ice, the dominant climate factors inducing the CWPs for SPPDs are revealed. The EA/WR teleconnection pattern was found to be the dominant climate factor (inducing 36.3% of the observed SPPDs over 2013–2019) that results in CWPs for SPPDs in North China through the propagation of large-scale stationary waves originating from the mid- to high latitudes of the North Atlantic to East Asia via western Europe and western Russia. The Victoria mode (VM) in the North Pacific Ocean were found to be the second predominant climate factor (inducing 18.5% of the observed SPPDs over 2013–2019) leading to SPPDs in North China by a wave train extending from the western North Pacific to the high-latitude North Pacific. The indices of the EA/WR and VM can be used to predict wintertime SPPDs over BTH, offering guidance for emission reduction strategy.
This study was mainly conducted by Nanjing University of Information Science & Technology. ProfessorHong Liao and Associate Professor Jiandong Li, from the School of Environmental Science and Engineering at Nanjing University of Information Science & Technology were the co-corresponding author and first author of the paper, respectively.
