Investigation of aerosol deposition using an improved advection-diffusion Eulerian deposition model

\nParticle deposition has a significant effect on air quality and human health. By knowing the deposition mechanisms, more effective control measures can be taken to reduce the health risks of particulate matter such as dust and anthropogenic aerosol. Accurate modeling of aerosol deposition mechanisms is an important step in solving air pollution problems. This study uses Computational Fluid Dynamics (CFD) to predict particulate matter deposition. A modified advection-diffusion model is used to identify the deposition mechanisms and predict the particle deposition rate. This model considers particle displacement toward the surface through many mechanisms such as Brownian and eddy diffusion, thermophoresis, turbophoresis, etc. It covers a much more comprehensive range of deposition mechanisms than other Eulerian models. Besides, it works under both laminar and turbulent airflow. The results show that the modeling results performed in this work are in excellent agreement with the experimental results reported in other research.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-10-11
DOI
https://doi.org/10.1051/e3sconf/202457503005/pdf
Primary Topic
Particle Dynamics in Fluid Flows
Type
article
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article

Investigation of aerosol deposition using an improved advection-diffusion Eulerian deposition model

Springer Link (Chiba Institute of Technology)
Particle Dynamics in Fluid Flows
article

Investigation of aerosol deposition using an improved advection-diffusion Eulerian deposition model

article en

Abstract

\nParticle deposition has a significant effect on air quality and human health. By knowing the deposition mechanisms, more effective control measures can be taken to reduce the health risks of particulate matter such as dust and anthropogenic aerosol. Accurate modeling of aerosol deposition mechanisms is an important step in solving air pollution problems. This study uses Computational Fluid Dynamics (CFD) to predict particulate matter deposition. A modified advection-diffusion model is used to identify the deposition mechanisms and predict the particle deposition rate. This model considers particle displacement toward the surface through many mechanisms such as Brownian and eddy diffusion, thermophoresis, turbophoresis, etc. It covers a much more comprehensive range of deposition mechanisms than other Eulerian models. Besides, it works under both laminar and turbulent airflow. The results show that the modeling results performed in this work are in excellent agreement with the experimental results reported in other research.\n

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 59%
Particle Dynamics in Fluid Flows
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