Research and Application of County-Town Scale Air Pollution Tracing Method
This study proposes an integrated source apportionment framework that synergistically integrates pollution source classification, atmospheric dispersion modeling, backward trajectory analysis, weighted trajectory clustering, and forward contribution estimation to accurately target peak reduction at localized air pollution hotspots. Applied at the County-Town Scale in Beijing, this method was employed to investigate pollution episodes at the Tongzhou Dongguan monitoring site. Source classification relied on a pollution fingerprint database and temporal concentration profiles, while local contributions were quantified through combined air quality modeling and monitoring data. Forward and backward trajectory analyses enabled the identification of potential source regions and key contributors. Results indicate that construction dust, road dust, and emissions from the catering industry were the dominant local sources, with construction and road dust contributing most prominently to PM2.5 concentrations. Furthermore, abnormal PM2.5 increases were closely linked to low boundary layer height, weak winds, and high humidity, emphasizing the role of meteorological conditions in pollution accumulation. The proposed framework proves effective in pinpointing local pollution sources and offers a scientific basis for targeted air quality management at finer spatial scales.