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

Abstract. China has made great efforts to monitor and control air pollution in the past decade. Comprehensive characterization and understanding of pollutants in three-dimension (3-D) 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 an 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 μg m⁻³. After assimilation, the correlation between model results and the independent observation sub-dataset was ~50 % higher than the 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.