Temporal and spatial characteristics of turbulent transfer and diffusion coefficient of PM2.5

Abstract

The temporal and spatial characteristics of turbulent transfer and diffusion coefficient of PM2.5 (KC) were investigated by determining the deviation, turbulent flux and form of universal function of PM2.5 mass concentrations. Turbulence and sounding observations from December 8–25, 2019, of three sites, Tuonan, Baoding, and Renqiu stations in the North China Plain were selected. Mean PM2.5 mass fluxes during the intensive observational period of three stations were negative. The spatial distribution of PM2.5 mass flux of three stations showed no obvious tendency. Then, the fact that PM2.5 mass concentrations satisfied the Monin–Obukhov similarity were reconfirmed by examining the relationship between the normalized standard deviation of PM2.5 mass concentrations and stability factor ζ. Thus, the universal functions in the three stations were achieved. The time series and profiles of KC in the three stations were also shown. There was a good inverse correlation between KC and PM2.5 mass concentration which suggested that the influence of turbulent diffusion is remarkably important during observational time even the emission, deposition, secondary transformation can all affect the change of mass concentrations of PM2.5 in the ABL. Changes in KC obviously presented diurnal characteristics. The comparisons of KC and KM and KH suggested that the strength of turbulent PM2.5 mass flux exchange could be weaker or stronger than the strength of turbulent momentum and heat flux exchange at different stations. The magnitude relationship between KC and KH could not be completely determined, so there were limitations in using KH to replace directly KC in the existing numerical weather or climate models. Finally, the spatial distribution of KC at the three stations presented almost symmetrical characteristics from east to west (Tuonan to Renqiu); that is, Baoding always had the lowest KC, and Tuonan and Renqiu stations had higher KCs. The spatial distribution of KC at the three stations corresponded well with that of PM2.5 mass concentrations, and Baoding always had the largest PM2.5 mass concentrations.