Uncovering PM2.5 transport trajectories and sources at district within city scale

To continuously improve air quality, it is necessary to carry out fine management of air pollution prevention and control. However, research into regional transport of PM2.5 at a smaller spatial scale such as district is limited. In this study, a novel combined method was constructed to simulate and identify the regional transport trajectories and potential sources of PM2.5 concentrations at district scale, based on a hybrid model that integrates the Bayesian maximum entropy (BME) model, Weather Research and Forecast (WRF) and backward trajectory model. Take Tianjin as an example, an analysis of the transport trajectories showed that the air masses from northwest and southwest were the dominant atmospheric transport pathway in all seasons except summer. The number of transport trajectories from northwest and southwest accounted for 42.41% and 40.75% of the total number of transport trajectories. Despite the dominant wind direction in winter was northwest, it can be beneficial to atmospheric transport. This was because northwest trajectories were the long-range pathways, corresponding to fast-moving air masses that facilitate the dispersion of pollutants. On contrast, it is noteworthy that the southwest trajectories were the short-range pathways, resulting in limited diffusion and unfavorable conditions. The major potential cities that were likely contributors of PM2.5 (Weighted Concentration-Weighted Trajectory (WCWT) values greater than 40 mu g m-3) were situated in the southwest. Furthermore, the interdistrict transport results indicated that the primary direction of PM2.5 transport in Tianjin was also from south to north. It is critical that the current layout of Tianjin is adjusted in a timely manner through relocating or phasing out, as the majority of industrial enterprises with severe air pollution in Tianjin are located in the southern districts. This method of combining BME, WRF and backward trajectory can be used for atmospheric environment planning in other similar city and district-scale around the world. It also provides useful insights to policy makers when they formulate pollutants prevention control policies.

Automated summary

To improve air quality, this study developed a novel combined method to simulate and identify the regional transport trajectories and sources of PM2.5 at district scale, using a hybrid model that integrates the Bayesian maximum entropy model, Weather Research and Forecast model, and backward trajectory model. Analysis of transport trajectories in Tianjin showed that air masses from northwest and southwest directions were the dominant pathways for atmospheric transport, except in summer.