Insights into quantitative evaluation technology of PM2.5 transport at multi–perspective and multi–spatial and temporal scales in the north China plain

Abstract

Cross-border transport is a crucial factor affecting air quality, while how to quantify the transport contribution through different technologies at multi–perspective and multi–scale have not been fully understood. This study established three quantification techniques, and conducted a systematic assessment of PM2.5 transport over the North China Plain (NCP) based on numerical simulations and vertical observations. Results suggested that the annual local emissions, inter–urban and outer–regional transport contributed 44.5%–64.6%, 15.2%–27.9% and 18.0%–28.2% of total surface PM2.5 concentrations, respectively, with transport intensity stronger in July and April, yet weaker in January and October. The southwest–northeast, northeast–southwest, and southeast–northwest were three prevailing transport directions near the surface. By comparison, the annual PM2.5 transport contribution below the atmospheric boundary layer height increased by 16.8%–24.5% in Beijing, Tianjin and Shijiazhuang, with inter–urban and outer–regional contribution of 29.8%–32.1% and 18.5%–23.1%. Furthermore, observed fluxes from fixed-point and vehicle-based mobile lidar were in good agreement with the simulated flux. PM2.5 net flux intensity varied with height, with generally larger at the middle- and high-altitude layer than that of low-altitude layer. In the early, during and late period of haze peak formation (Stage Ⅰ, Ⅱ, Ⅲ, respectively), the largest absolute flux intensity on average was Stage Ⅱ (566.7 t/d), followed by Stage Ⅲ (307.0 t/d) and Ⅰ (191.4 t/d). Besides, external transport may dominate the second concentration peak, while local emissions may play a more vital role in the first and third peaks. It has been noted that joint prevention and control measures should be proposed 1–2 days before reaching PM2.5 extremes. These findings could improve our understanding of transport influence mechanism of PM2.5 and propose effective emission reduction measures in the NCP region.