ESSIC / CICS-MD Professor Zhanqing Li and Graduate Assistant II Tianning Su recently published a paper in Atmospheric Chemistry and Physics titled “Relationships between the planetary boundary layer height and surface pollutants derived from lidar observations over China: regional pattern and influencing factors”.
This paper discusses the frequency of severe air pollution episodes in China, analyzing the relationship between planetary boundary layer height (PBLH) and surface pollutants. With this improved understanding of aerosol-planetary boundary layer interactions, the authors hope to improve the ability to forecast surface air pollution. An abstract from the study authors is provided below.
Zhanqing Li is an AOSC-ESSIC professor who has engaged in a wide range of studies concerning climate change, atmospheric physics, and the terrestrial and atmospheric environment.
Air pollution in China has been frequently reported and is a top public concern to the most populated country. This study attempts to tackle the problem by sorting out key factors influencing surface pollutants usually measured in mass of particulates less than 2.5 micrometers (PM2.5). By analyzing the frequency of severe air pollution episodes across China at ~1600 surface stations, the relationship between planetary boundary layer height (PBLH) and surface pollutants (PM2.5) is thoroughly investigated with an emphasis on its spatial and temporal patterns to help identify fundamental influencing factors. PM2.5 is found to be correlated with PBL under certain circumstances such as in low-altitude regions (plains, basin) during winter under calm conditions, but least affected by PBL in highland during summer and strong winds. A closer relationship is established between PM2.5 normalized by aerosol optical depth (AOD) that can be measured both from space and on the ground. These findings can improve our understanding of the complex interactions between air pollution, boundary layer, and horizontal transport, and may further improve the ability to monitor and forecast surface air pollution using a combination of satellite and routine meteorological measurements.