Contrasting Turbulent Transport of PM 2.5 and Conventional Scalars during Pollution Episodes over the North China Plain
Year: 2026
Type: preprint
Abstract: . Understanding turbulent transport similarities between PM2.5 and conventional scalars and the origins of their differences is essential for assessing particulate turbulent diffusion relationships. Using intensive wintertime observations in Dezhou, North China Plain, we developed a retrieval method that selects visibility–PM2.5 relationships for individual pollution episodes. This improves applicability across episodes compared with a single fixed relationship and yields PM2.5 mass concentration fluctuations and turbulent fluxes. Estimates were more sensitive to relationship selection under low visibility, highlighting the importance of accounting for episode differences. Comparisons with CO2, water vapour, and temperature revealed similar variance-scaling exponents but markedly lower normalized vertical transport efficiency for PM2.5. Under unstable stratification, normalized standard deviations of all four scalars approximately followed (-z/L)⁻¹ᐟ³ scaling. PM2.5 had the largest fitted coefficient, indicating stronger fluctuations relative to its flux scale, and weaker correlations with vertical velocity under both unstable and stable conditions. Strong instantaneous PM2.5 transport events were less directionally organized than those of conventional scalars, with upward and downward contributions cancelling each other. Flux contributions at different frequencies also showed stronger cancellation between opposing directions. These event and frequency characteristics jointly explain the lower normalized vertical transport efficiency of PM2.5. Our findings demonstrate that similar variance-scaling exponents can coexist with different transport efficiencies, extending scalar comparisons to net flux formation. They provide observational evidence for assessing shared turbulent diffusion relationships for particulate matter and conventional scalars in air quality models and improving PM2.5 turbulent diffusion parameterizations.
Institutions: Lanzhou University, Peking University
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225426510