Numerical Simulation Study on the Mechanism of Low-Level Disturbances Disrupting Temperature Inversion and Cross-Scale Diffusion of Pollutants

This research investigates the regulatory mechanisms through which artificial disturbances affect the breakdown of inversion layers and the dispersion of pollutants via numerical simulations, thereby providing theoretical insights for mitigating air pollution during inversion events. By employing a combined simulation approach using the Fluent and ARPS models, we found that low-level disturbances applied at the base of the inversion layer significantly reduced PM2.5 concentrations. Specifically, after 2 hours, reductions at local and regional levels were observed at 30% and 25%, respectively, with further declines to 50% and 45% occurring after 3 hours. This effect is closely associated with an increase in turbulence intensity, and the rate at which PM2.5 concentrations decrease exhibits a significant linear relationship with the rise in turbulent kinetic energy (TKE) (R2 = 0.94). This indicates that enhancing turbulence intensity in the near-surface layer can substantially facilitate pollutant dispersion. Cross-scale simulations reveal the micro-mechanism of 'vortex breaking inversion - pollutant funnel diffusion' and the structural effects of disturbances on urban circulation, such as mixed convection driven by downward airflow and enhanced gradient diffusion. Furthermore, the study addresses the limitations of the existing model, which neglects complex factors such as solar radiation and terrain thermal variations. Future research should aim to integrate multiple physical processes and quantify the relationships between disturbance parameters and pollutants to aid in the formulation of precise air quality management strategies for cities located in complex terrains, including Urumqi.