For citation:
Shnaider I. A., Kushnikov V. A., Bogomolov A. S. Simulation modeling of atmospheric pollutant dispersion considering dry deposition and the influence of liquid atmospheric precipitation. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2025, vol. 25, iss. 4, pp. 589-599. DOI: 10.18500/1816-9791-2025-25-4-589-599, EDN: WFWDIR
Simulation modeling of atmospheric pollutant dispersion considering dry deposition and the influence of liquid atmospheric precipitation
The article presents the results of developing a mathematical model for computer simulation of atmospheric pollutant dispersion, taking into account dry deposition and the effects of liquid atmospheric precipitation. This development is based on well-known Gaussian and Ermak mathematical models. In our model, to account for these factors under observed atmospheric precipitation, the plume dispersion equation includes a new multiplier. This multiplier is a concentration increase coefficient, proportional to the increase in pollutant plume mass under the influence of liquid precipitation, derived from the Kelvin equation and Raoult's law. The developed model is implemented as a software package that uses data on known emission sources, meteorological conditions, and monitoring results of pollutant concentrations at specific points within an industrial area. Calculations and a comparative assessment of the model's accuracy have been conducted. It is shown that considering dry deposition and precipitation effects allows for more accurate modeling of pollutant dispersion dynamics in the studied data.
- Lee J., Lee S., Son H. A., Yi W. Development of PUFF-Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration. Scientific Reports, 2021, vol. 11, art. 6456. DOI: https://doi.org/10.1038/s41598-021-86039-y
- Ermak D. L. An analytical model for air pollutant transport and deposition from a point source. Atmospheric Environment, 1977, vol. 11, iss. 3, pp. 231–237. DOI: https://doi.org/10.1016/0004-6981(77)90140-8
- Stockie J. M. The mathematics of atmospheric dispersion modeling. SIAM Review, 2011, vol. 53, iss. 2, pp. 349–372. DOI: https://doi.org/10.1137/10080991X
- Alam B., Soppi R. N., Feiz A.-A., Ngae P., Chpoun A., Kumar P. CFD simulation of pollutant dispersion using anisotropic models: Application to an urban like environment under neutral and stable atmospheric conditions. Atmospheric Environment, 2024, vol. 318, art. 120263. DOI: https://doi.org/10.1016/j.atmosenv.2023.120263
- Lin C., Ooka R., Jia H., Parente A., Kikumoto H. Eulerian RANS simulation of pollutant dispersion in atmospheric boundary layer considering anisotropic and near-source diffusivity behavior. Journal of Wind Engineering and Industrial Aerodynamics, 2025, vol. 258, art. 106036. DOI: https://doi.org/10.1016/j.jweia.2025.106036
- Fuchs M. D., Gebler S., Lorke A. The droplet and atmospheric dispersion drift (DAD-drift) model – A modular approach for estimating spray drift at the landscape scale. Environmental Research, 2025, vol. 271, art. 121104. DOI: https://doi.org/10.1016/j.envres.2025.121104
- Chaloupecká H., Nevrlý V., Martiníkova B., Suchánek J., Dostál M., Wild J., Dobeš P., Barabášová M., Jaňour Z. Physical modeling for emergency planning support: Gas dispersion simulations in urban and rural areas. Journal of Loss Prevention in the Process Industries, 2025, vol. 94, art. 105571. DOI: https://doi.org/10.1016/j.jlp.2025.105571
- Lumet E., Rochoux M. C., Jaravel T., Lacroix S. Uncertainty-aware surrogate modeling for urban air pollutant dispersion prediction. Building and Environment, 2025, vol. 267, pt. C, art. 112287. DOI: https://doi.org/10.1016/j.buildenv.2024.112287
- Krassas A., Renda S. M., Mijorski S., de Villiers E., Capra S. Evaluating numerical models for the prediction of pollutant dispersion over Tokyo’s Polytechnic University campus. Journal of Wind Engineering and Industrial Aerodynamics, 2024, vol. 251, art. 105789. DOI: https://doi.org/10.1016/j.jweia.2024.105789
- Pariyar S., Lamichhane B. P., Kafle J. A time fractional advection-diffusion approach to air pollution: Modeling and analyzing pollutant dispersion dynamics. Partial Differential Equations in Applied Mathematics, 2025, vol. 14, art. 101149. DOI: https://doi.org/10.1016/j.padiff.2025.101149
- Jiao H., Takemi T. Using large eddy simulation to investigate pollutant dispersion over stepped roofs. Building and Environment, 2025, vol. 274, art. 112704. DOI: https://doi.org/10.1016/j.buildenv.2025.112704
- Affad E., Saadeddine S., Assou M., Sbaibi A. Effect of the relative humidity on an industrial plume behavior. Global NEST Journal, 2006, vol. 8, iss. 3, pp. 297–305. DOI: https://doi.org/10.30955/gnj.000294
- Jacobson M. Z. Fundamentals of atmospheric modeling. 2nd ed. Cambridge University Press, 2005. 813 p. DOI: https://doi.org/10.1017/CBO9781139165389
- Connolly P. Air quality. Lecture notes for the course EART60101, The University of Manchester. Available at: https://personalpages.manchester.ac.uk/staff/paul.connolly/teaching/eart... (accessed May 1, 2025).
- Shnaider I., Bogomolov A., Lapkovsky R., Kushnikova E. An approach to locating unknown sources of increased air emissions. 2023 16th International Conference Management of large-scale system development (MLSD), 2023, pp. 1–5. DOI: https://doi.org/10.1109/MLSD58227.2023.10303966
- Beychok M. R. Error propagation in stack gas dispersion models. National Environmental Journal, 1996, vol. 6, iss. 1, pp. 33–37.
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