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Published April 8, 2021 | Version v1
Dataset Open

Application of turbulent diffusion term of aerosols in mesoscale model

  • 1. Nanjing University of Information Science and Technology

Description

The presence of unfavorable meteorological conditions triggers pollution, and then further weakens turbulence, especially in the stable boundary layer (SBL), which is a frequent situation in heavy pollution episodes in China. The inapplicability of the classical Monin-Obukhov similarity theory (MOST) and the uncertainty of the planetary boundary layer height can lead to large deviation of turbulent diffusion in the SBL in numerical simulations. However, in current mesoscale models, no term has been used to accurately describe the turbulent diffusion of aerosols. Therefore, we use the Mixing-Length theory to obtain the turbulent diffusion term of aerosols based on high-resolution observational data, and, for the first time, embed this term into a mesoscale model, which makes the turbulent diffusion process of aerosols more truly depicted. Results from a two-way coupled atmospheric-chemistry mesoscale model demonstrate that the turbulent diffusion term of aerosols can improve the problem of overestimated PM2.5 concentration in Eastern China.

Notes

Funding provided by: NSFC Project*
Crossref Funder Registry ID:
Award Number: U19A2044

Funding provided by: National Key Project of MOST*
Crossref Funder Registry ID:
Award Number: 2016YFC0203306

Funding provided by: Atmospheric Pollution Control of the Prime Minister Fund*
Crossref Funder Registry ID:
Award Number: DQGG0104

Funding provided by: Key Projects of Fundamental Scientific Research Fund of CAMS*
Crossref Funder Registry ID:
Award Number: 2017Z001

Funding provided by: NSFC Project
Crossref Funder Registry ID:
Award Number: U19A2044

Funding provided by: National Key Project of MOST
Crossref Funder Registry ID:
Award Number: 2016YFC0203306

Funding provided by: Atmospheric Pollution Control of the Prime Minister Fund
Crossref Funder Registry ID:
Award Number: DQGG0104

Funding provided by: Key Projects of Fundamental Scientific Research Fund of CAMS
Crossref Funder Registry ID:
Award Number: 2017Z001

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