Computational experiments aimed at assessing and predicting the distribution of industrial emissions in the atmospheric basin of the Tashkent region
Keywords:
wind speed, pollution concentration, monitoring, atmosphere, ChirchikAbstract
Based on the developed mathematical software, this paper presents the results of numerical calculations on the task of monitoring and forecasting the concentration of industrial emissions of pollutants (CO2, dust, ammonia) in the city of Chirchik and Tashkent region, performed taking into account wind speeds at different levels at alti tude, as well as stable, unstable and indifferent stratification of the atmosphere over the region under consideration. Evaluation of concentration field distribution at different altitudes was carried out for each pollutant. The influence of wind speed on exceeding the maximum permissible concentration of a substance, and vice versa- on the nature and speed of dispersion of harmful emissions in the surface layer of the atmosphere was also analyzed. Numerical calculations established the ranges of wind speeds at which favorable conditions (entrainment and dispersion of emissions) are observed for Chirchik city, as well as unfavorable conditions when stable areas of air basin pollution are formed over the city and over the territory of Tashkent region as a whole.
References
Shunxiang H, Feng L, Qingcun Z, Fei H and Zifa W Modeling and Optimal Control of Atmospheric Pollution Hazard in Nuclear and Chemical Disasters UTAM Symposium on the Dynamics of Extreme Events Influenced by Climate Change.– Procedia IUTAM 17. P. 79–90.– 2015. DOI: 10.1016/j.piutam.2015.06.012.
Kozii I., Plyatsuk I., Zhylenko T., Hurets l., Y. Bataltsev, Sayenkov D. Development of the Turbulent Diffusion Model of Fine Suspended Substances in the Lower Atmosphere Layer. ISSN 1392–1320 MATERIALS SCIENCE (MEDˇ ZIAGOTYRA).– Vol. 28,– No. 4.– 2022. DOI: 10.5755/j02.ms.30223
U. Im, J. H. Christensen, O. K. Nielsen and others. Contributions of Nordic anthropogenic emissions on air pollution and premature mortality over the Nordic region and the Arctic.– Atmos.Chem.Phys.,19,12975–12992,201. DOI: 10.5194/acp-19-12975-2019
Равшанов Н., Шарипов Д.К. Сопряженная модель нестационарного процесса перено са и диффузии аэрозольных выбросов в атмосфере.– В мире научных открытий. Красноярск,– 2010.– № 6.– С. 67–70.
Губанова Д.П., Кудерина Т.М., Чхетиани О.Г. и др. Экспериментальные исследования аэрозолей в атмосфере семиаридных ландшафтов калмыкии– Ландшафтно геохимический состав аэрозольных частиц. // УДК 502.07, 504.3.054, 550.423, 631.41. Геофизические процессы и биосфера– 2018. Т. 17 № 3. DOI: 10.21455/GPB2018.3-2
Алексеев А.К., Бондарев А.Е. Применение сопряженных уравнений в задачах верифи кации и валидации расчетов– Новые информационные технологии в автоматизиро ванных системах,– 2012. [7] Бондарев А.Е., Галактионов В.А., Чечеткин В.М. Анализ развития концепций и мето дов визуального представления данных в задачах вычислительной физики // Журнал вычислительной математики и математической физики.– 2011. Т. 51, N 4,– С. 669–683.
Fayzullayevich, J.V., Tan, G.F., Alex F.J., Agyeman P.K., Wu Y.J. Improvement of Dust Particle Suction Efficiency by Controlling the Airflow of a Regenerative Air Sweeper.– DOI 10.3390/app12199765. 2022-10-22
М.А. Кучумов Сопряженные задачи переноса и диффузии в проблеме оценки и про гноза состояния окружающей среды.//– 2015. www.bibliofond.ru/view.aspx?id=786131
Meng-Yi Jin a b, Le-Ying Zhang b, Zhong-Ren Peng c d, Hong-Di He a, Prashant Kumar, John Gallagher Effect of medium heterogeneities on reactive dissolution of carbonates // The impact of dynamic traffic and wind conditions on green infrastructure performance to improve local air quality// Science of The Total Environment Volume 917, 20 March– 2024. 170211 //doi.org/10.1016/j.scitotenv.2024.170211
Amorim J.H.– Volumes 461–462, 1 September 2013.– P. 541–551. doi.org/10.1016/j.scitotenv.2013.05.031
Francesco Barbano, Silvana Di Sabatino, Rob Stoll, Eric R. Pardyjak A numerical study of the impact of vegetation on mean and turbulence fields in a European-city neighbourhood // Building and Environment Volume 186, December– 2020. 107293 https://doi.org/10.1016/j.buildenv.2020.107293
Ravshanov N., Nabieva I., Karshiev D. Conjugate Problem for Optimal Placement of Industrial Production Facilities. // International Journal of Theoretical and Applied Issues of Digital Technologies.– P. 15–26. https://doi.org/10.62132/ijdt.v7i2.175– 2024.
Ravshanov N., Tashtemirova N., Karshiyev D.A. Modelirovaniye protsessa rasprostraneniya aerozol’nykh chastits v pogranichnom sloye atmosfery s uchetom ikh pogloshcheniya i zakhvata rastitel’nym pokrovom. Problemy vychislitel’noy i prikladnoy matematiki № 2(56)– 2024.– S. 41–57.
Gongbo Chen, Shanshan Li and etc. A machine learning method to estimate PM2.5 concentrations across China with remote sensing, meteorological and land use information. Science of the Total Environment 636– 2018.– P. 52–60. Doi:10.1016/j.scitotenv. 2018.04.251 0048
Jan Duyzer, Dick van den Hout, Peter Zandveld, Sjoerd van Ratingen Representativeness of air quality monitoring networks. Atmospheric Environment // 104– 2015. 88e. www.elsevier.com/locate/atmosenv
Saurabh Kumar, Shweta Mishra, Sunil Kumar Singh A machine learning-based model to estimate PM2.5 concentration levels in Delhi’s atmosphere.– Heliyon 6– 2020. e05618. www.cell.com/heliyon
Mikalai Filonchyk, Volha Hurynovich, Haowen Yan Shuwen Yang Atmospheric pollution assessment near potential source of natural aerosols in the South Gobi Desert region,–– 2020. China, GIScience Remote Sensing, 57:2,– P. 227-244. DOI: 10.1080/15481603.2020.1715591
Christensen, J.H. “The Danish Eulerian Hemispheric model—A Three-dimensional Air Pollution Model Used for the Arctic.”– 1997. Atmospheric Environment 31 (24):– P. 4169–4191. doi:10.1016/S1352-2310(97)00264-1
Zhou, X., Z. Cao, Y. Ma, L. Wang, R. Wu, and W. Wang.“Concentrations, Correlations and Chemical Species of PM2.5/PM10 Based on Published Data in China: Potential Implications for the Revised Particulate Standard.” Chemosphere 144:– 2016.– P. 518–526
Ravshanov N., Muradov F., Akhmedov D. Mathematical software to study the harmful substances diffusion in the atmosphere. // Ponte.– Vol. 74.– No. 8/1.– 2018.– P. 171–179. DOI: 10.21506/j.ponte.2018.8.13.
Равшанов Н., Таштемирова Н., Мурадов Ф. Исследование существования и единственности решения задачи переноса и диффузии аэрозольных частиц в атмосфере. // Проблемы вычислительной и прикладной математики. Ташкент,– №1(7).– 2017.– С. 54–67.
Равшанов Н., Шафиев Т., Таштемирова Н. Нелинейная математическая модель для мониторинга и прогнозирования процесса распространения аэрозольных частиц в атмосфере. // Вестник ТУИТ.– №2(50).– 2019.– С. 45–60.
Ravshanov N., Nazarov S., Nazarov E. and Boborakhimov B. Development of a mathematical model of aerosol particles’ distribution process in the surface layer of the atmosphere taking into account the earth’s heterogeneous surface. // AIP Conf. Proc. 3004, 060004– 2024. https://doi.org/10.1063/5.0200769
