Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM 2.5 concentrations over the North China Plain

摘要

China has made great efforts to monitor and control air pollution in the past decade. Comprehensive characterization and understanding of pollutants in three-dimensions are, however, still lacking. Here, we used data from an observation network consisting of 13?aerosol lidars and more than 1000?ground observation stations combined with a data assimilation technique to conduct a comprehensive analysis of extreme heavy aerosol pollution?(HAP) over the North China Plain?(NCP) from November–December?2017. During the studied period, the maximum hourly mass concentration of surface PM 2.5 reached ～390 ? μ g?m ?3 . After assimilation, the correlation between model results and the independent observation sub-dataset was ～50 ?% higher than that without the assimilation, and the root mean square error was reduced by ～40 ?%. From pollution development to dissipation, we divided the HAP in the NCP (especially in Beijing) into four phases: an early phase?(EP), a transport phase?(TP), an accumulation phase?(AP), and a removal phase?(RP). We then analyzed the evolutionary characteristics of PM 2.5 concentration during different phases on the surface and in 3-D space. We found that the particles were mainly transported from south to north at a height of 1–2?km (during EP and RP) and near the surface (during TP and AP). The amounts of PM 2.5 advected into Beijing with the maximum transport flux intensity?(TFI) were through the pathways in the relative order of the southwest? ?southeast? ?east pathways. The dissipation of PM 2.5 in the RP stage (with negative TFI) was mainly from north to south with an average transport height of ～1 ?km above the surface. Our results quantified the multi-dimensional distribution and evolution of PM 2.5 concentration over the NCP, which may help policymakers develop efficient air pollution control strategies.