Numerical modeling of the transport and diffusion of pollutant particles taking into account airflow characteristics and temperature
DOI:
https://doi.org/10.71310/pcam.1_63.2025.03Keywords:
mathematical model, finite-difference scheme, heat transfer, moisture transfer, raw cottonAbstract
The article considers the results of experimental and numerical studies of atmospheric pollution processes in industrial zones. The proposed mathematical model helps to solve problems related to monitoring and forecasting the state of the environment in industrial zones, as well as making decisions on protection against the negative impact of anthropogenic factors. studies the physicochemical properties of substances involved in the process of dispersion in the atmosphere. In the process of diffusion, the particle diameter, temperature and wind speed are taken into account. To check the adequacy of the developed mathematical model, computational experiments were carried out on a computer. Analysis of the computational experiments showed that with an increase in wind speed, the concentration of pollutants around the source is not observed, and the area of their distribution expands over time. When the speed of air masses in the atmosphere exceeds the critical value, diffusion of the substance occurs only due to the effect of transition to the atmosphere. Changes in the concentration of pollutants in the layers of the atmosphere over time depending on the actual wind speed are also noted.
References
Samad A., Garuda S., Vogt U. And Yang B. 2023. Air pollution prediction using machine learning techniques – An approach to replace existing monitoring stations with virtual monitoring stations // Atmospheric Environment Volume 310, 1 October 119987, https://doi.org/10.1016/j.atmosenv.2023.119987
Zezhi Peng and etc. 2024. Application of machine learning in atmospheric pollution research: A state-of-art review // Science of The Total Environment Volume 910, 1 February 168588, https://doi.org/10.1016/j.scitotenv.2023.168588
Holden H., Hvistendahl K., Lie K. 2000. Operator splitting methods for degenerate convection–diffusion equations II: numerical examples with emphasis on reservoir simulation and sedimentation // Computational Geosciences. – Vol. 4, -No. 4. – P. 287–322.
Daniel Vallero. Fundamentals of Air Pollution // Discusses various aspects of pollutant behavior, including dispersion and deposition. – P. 149–150.
Allen D.T., et al. 2012. A study of the atmospheric chemistry of volatile organic compounds during high-performance wind tunnel experiments. // Environmental Science Technology, 46(5), – P. 3064–3070.
Sahlgren B., et al. 2016. The impact of urbanization on the dispersion of pollutants. // Urban Climate, 15, – P. 129–145.
Kozii I., Plyatsuk I., Zhylenko T., Hurets l., Y. Bataltsev, Sayenkov D. 2022. Development of the Turbulent Diffusion Model of Fine Suspended Substances in the Lower Atmosphere Layer. // ISSN 1392–1320 MATERIALS SCIENCE (MEDŽIAGOTYRA). – Vol. 28, – No. 4. DOI: 10.5755/j02.ms.30223
Sharan M., Gopalakrishnan S.G. 2003. Mathematical modeling of diffusion and transport of pollutants in the atmospheric boundary layer // January pure and applied geophysics. – vol. 160. – Issue 1-2. – P. 357–394.
Ravshanov N., Sharipov D.K., Ahmedov D.D. 2015. Modelirovanie processa zagrjaznenija okruzhajushhej sredy s uchetom rel’efa mestnosti i pogodno-klimaticheskih faktorov // Informacionnye tehnologii modelirovanija i upravlenija. – Voronezh, – No. 3(93). – P. 222–234.
Ravshanov N., Serikbaev B., Serikbaeva Je. 2010. Metodologija zashhity jekosistem ot istochnikov zagrjaznenija // Stiinta Agricola. – Kishinjov, – No. 1. – P. 68–73.
Bastelberger S., Krieger U. K., Luo B., and Peter T. 2017. Diffusivity measurements of volatile organics in levitated viscous aerosol particles // Atmos. Chem. Phys., 17, – P. 8453–8471. https://doi.org/10.5194/acp-17-8453-2017,
Champion D., Hervet H., Blond G., Le Meste M., and Simatos D. 1997. Translational diffusion in sucrose solutions near their glass transition temperature. // J. Phys. Chem. 101, – P. 10674–10679.
Nozière B., Kalberer M., Claeys M., Allan J., D’Anna B., Decesari S., Finessi E., Glasius M., Grgić I., Hamilton J.F., Hoffmann T., Iinuma Y., Jaoui M., Kahnt A., Kampf C.J., Kourtchev I., Maenhaut W., Marsden N., Saarikoski S., Schnelle-Kreis J., Surratt J.D., Szidat S., Szmigielski R., and Wisthaler A. 2015. The Molecular Identification of Organic Compounds in the Atmosphere: State of the Art and Challenges, // Chem. Rev., 115, – P. 3919–3983. https://doi.org/10.1021/cr5003485,
Liang M.Z., Chao Ye, Tu Yu, and Xu Te 2023. “Vehicle pollutant dispersion in the urban atmospheric environment: A review of mechanism, modeling and application,” // Atmosphere (Basel)
Zhou H., Song W., and Xiao K. 2022. “Flow and hazardous gas dispersion by using WRFCFD coupled model under different atmospheric stability conditions,” Atmosphere (Basel)
Ekkachai T. and Suttida W. 2021. “Modeling and numerical experiments of air pollution on a complex modeling and numerical experiments of air pollution on a complex terrain,” // J. Phys.: Conf. Ser. 1850, 1–12.
Sharipov D.K., Toshtemirova N., Narzullaeva N. 2016. Chislennoe modelirovanie processa rasprostranenija vrednyh veshhestv v atmosfere s uchetom rel’efa mestnosti // Problemy vychislitel’noj i prikladnoj matematiki. – No. 1(3). – P. 60–71.
Ravshanov N., Nabieva I., Zhaparov B.T. 2024. Soprjazhennaja zadacha dlja optimal’nogo razmeshhenija promyshlennyh obektov // Problemy vychislitel’noj i prikladnoj matematiki. – No. 3(57). – P. 91–105.
Haertel P. 2019. “A Lagrangian ocean model for climate studies,” Climate 7 (41), – P. 1–24.
Hosoi F. and Omasa K. 2007. “Factors contributing to accuracy in the estimation of the woody canopy leaf-area density profile using 3D portable lidar imaging,” // J. Exp. Botany 58, – P. 3464–3473.
Kawka M., Struzewska J., and Kaminski J.W. 2023. “Downscaling of regional air quality model using Gaussian plume model and random forest regression,” Atmosphere 14, 1171
Kim B.Y., Wayson R.L., and Fleming G.G., 2006. “Development of traffic air quality simulation model,” Transp. Res. Record – P. 73–81.
Ravshanov N., Nabieva I. 2024. Modelirovanie transporta toksichnyh zagrjaznjajushhih veshhestv v atmosfere // Sbornik tezisov pervoj mezhdunarodnoj nauchno-tehnicheskoj konferencii «Sovremennye problemy fiziki, jenergetiki i teplotehniki» Dekabr’ 5, – P. 251–253.
Kodirov K.R., Nabieva I., Nasrullayev P.A. 2023. Zararli moddalarni atmosferada tarqalish jarayonini fizik xususiyatlarini sonli tadqiq qilish // Sovremennoe sostojanie i Perspektivy razvitija cifrovyh Tehnologij i iskusstvennogo Intellekta Sbornik dokladov mezhdunarodnoj nauchno-tehnicheskoj konferencii Buhara, 27-28 sentjabrja 2024 g. – P. 303–309.
Ravshanov N., Nabieva I.S. 2024. Matematicheskoe modelirovanie processa rasprostranenija vrednyh veshhestv v atmosfere s uchetom temperatury, fizicheskih i himicheskih svojstv // Mezhdunarodnyj zhurnal teoreticheskih i prikladnyh voprosov cifrovyh tehnologij. – No. 7(4) – P. 27–32.
