Vol. 39, issue 03, article # 7

Abstract:

Air pollution modelling in mountainous regions is a relevant challenge due to the complex interaction of topography with atmospheric dynamics and uncertainty in emission data This paper presents the results of atmospheric pollution modeling for carbon monoxide (CO) in complex mountainous terrain, using the Kislovodsk region as a case study. The study used the mesoscale meteorological model WRF and the chemical transport model CHIMERE. The results were validated against instrumental measurements carried out at the High-Mountain Scientific Station of A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences. It is shown that refining the EMEP emission database by incorporating local features of the road network (density and road types) and their daily/weekly dynamics allows the spatial distribution of pollution sources to more closely approximate the actual layout of the region's road network, and also improves the accuracy of reproducing the daily cycle of CO concentrations. An experiment was conducted to quantitatively assess the contribution of orographic factors to the overall pollution level. It was established that the complex terrain of the region accounts for 20–50% of the average CO concentration level, creating zones of pollutant accumulation and dispersion. Statistical analysis demonstrates satisfactory agreement between the modeling results and observational data. The study confirms the feasibility and effectiveness of the WRF-CHIMERE modeling system in monitoring and analyzing atmospheric air quality in resort regions with complex topography. The results can serve a foundation for fundamental and applied scientific research aimed at studying the mechanisms behind the formation of periods with adverse environmental conditions. The air quality modeling can be used by local government authorities for such tasks as urban planning, optimization of road networks, and the development of recreational areas taking into account orographic conditions, as well as for improving regional environmental monitoring systems.

Keywords:

air pollution, chemical transport model, air quality, carbon monoxide, orography, vehicle emissions

Figures:

References:

1. Rafaj P., Kiesewetter G., Gül T., Schöpp W., Cofala J., Klimont Z., Purohit P., Heyes C., Amann M., Borken-Kleefeld J., Cozzi L. Outlook for clean air in the context of sustainable development goals // Glob. Environ. Chang. 2018. V. 53. P. 1–11. DOI: 10.1016/j.gloenvcha.2018.08.008.
2. World Health Statistics 2021: Monitoring Health for the SDGs, Sustainable Development Goals. USA, 2021. URL:ttps://iris.who.int/server/api/core/bitstreams/4339a2a8-d8bc-4f73-8570-204b08c9264f/content (last access: 28.12.2025).
3. Pope C., Thun M.J., Namboodiri M.M., Dockery D.W., Evans J.S., Speizer F.E., Heath Jr.C.W. Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults // Am. J. Respir. Crit. Care Med. 1995. N 151. P. 669–674. DOI: 10.1164/ajrccm/151.3_Pt_1.669.
4. Sun Y., Zhuang G., Wang Y., Han L., Guo J., Dan M., Zhang W., Wang Z., Hao Z. The air-borne particulate pollution in Beijing – concentration, composition, distribution and sources // Atmos. Environ. 2004. V. 35, N 38. P. 5991–6004. DOI: 10.1016/j.atmosenv.2004.07.009.
5. Bell M., Peng R., Dominici F. The exposure-response curve for ozone and risk of mortality and the adequacy of current ozone regulations // Environ Health Perspect. 2006. V. 114, N 4. P. 532–536. DOI: 10.1289/ehp.8816.
6. Downs S., Schindler C., Liu S., Keidel D., Bayer-Oglesby L., Brutsche M., Gerbase M., Keller R., Künzli N., Leuenberger P., Probst-Hensch N., Tschopp J.-M., Zellweger J-P., Rochat T., Schwartz J., Ackermann-Liebrich U. Reduced exposure to PM₁₀ and attenuated age-related decline in lung function // N. Engl. J. Med. 2006. V. 23, N 357. P. 2338–2347. DOI: 10.1056/nejmoa073625.
7. Hvidtfeldt U. Sorensen M., Geels C., Ketzel M., Khan J., Tjonneland A., Overvad K., Brandt J., Raaschou-Nielsen O. Long-term residential exposure to PM_2.5, PM₁₀, black carbon, NO₂, and ozone and mortality in a Danish cohort // Environ. Int. 2019. V. 2, N 123. P. 265–272. DOI: 10.1016/j.envint.2018.12.010.
8. Vsemirnaya organizatsiya zdravookhraneniya. WHO, 2024. URL: https: //data.who.int/ru/indicators/i/80BEA0B /E2FC6D7 (data obrashcheniya: 28.12.2025).
9. Choi Y., Wang Y., Zeng T., Cunnold D., Yang E., Martin R., Edgerton E. Springtime transitions of NO₂, CO, and O₃ over North America: Model evaluation and analysis // J. Geophys. Res.: Atmos. 2008. V. D20, N 113. DOI: 10.1029/2007JD009632.
10. Yoo J., Jeong M., Kim D., Stockwell W., Yang J., Shin H., Lee S. Spatiotemporal variations of air pollutants (O₃, NO₂, SO₂, CO, PM₁₀, and VOCs) with land-use types // Atmos. Chem. Phys. 2015. V. 18, N 15. P. 10857. DOI: 10.5194/acp-15-10857-2015.
11. Rajak R., Chattopadhyay A. Short and long-term exposure to ambient air pollution and impact on health in India: A systematic review // Int. J. Environ. Res. Public. Health. 2019. P. 1–25. DOI: 10.1080/09603123.2019.1612042.
12. Liang L., Gong P. Urban and air pollution: A multi-city study of long-term effects of urban landscape patterns on air quality trends // Sci. Rep. 2020. V. 1, N 10. P. 1–13. DOI: 10.1038/s41598-020-74524-9.
13. Fritze J. Introduction // National Research Council and National Academy of Engineering (ed.) Urbanization, Energy, and Air Pollution in China. Washington: The National Academies Press, 2004. P. 1–8. DOI: 10.17226/11192.
14. Liu Y., Wu J., Yu D., Hao R. Understanding the patterns and drivers of air pollution on multiple time scales: The case of Northern China // Environ. Manag. 2018. N 61. P. 1048–1061. DOI: 10.1007/s00267-018-1026-5.
15. Головко А.Г., Клецова В.А., Ромащенко Д.Д., Башкиров Л.Н., Акишина С.В., Ладохина Е.М., Неробелов Г.М. Исследование чувствительности модели WRF-Chem к учету детализированной городской среды Санкт-Петербурга // Школа молодых ученых: тез. докл. 3–6.10.2024 г. СПб.: РГГМУ, 2024. С. 12–14.
16. Nerobelov G., Virolainen Ya., Ionov D., Polyakov A., Rozanov Ye. WRF-Chem modeling of tropospheric ozone in the coastal cities of the gulf of Finland // Atmosphere. 2024. V. 15, N 7. P. 775. DOI: 10.3390/atmos15070775.
17. Konovalov I.B., Golovushkin N.A., Zhuravleva T.B., Nasrtdinov I.M., Uzhegov V.N., Beekmann M. Primenenie model'nogo kompleksa CHIMERE–WRF dlya izucheniya radiatsionnykh vozdeistvii sibirskogo dymovogo aerozolya v Vostochnoi Arktike // Optika atmosf. i okeana. 2023. V. 36, N 2. P. 129–139. DOI: 10.15372/AOO20230208; Konovalov I.B., Golovushkin N.A., Zhuravleva T.B., Nasrtdinov I.M., Uzhegov V.N., Beekmann M. Application of the CHIMERE-WRF model complex to study the radiative effects of Siberian smoke aerosol in the Eastern Arctic // Atmos. Ocean. Opt. 2023. V. 36, N 4. P. 337–347.
18. Konovalov I.B., Golovushkin N.A. Model'nyi analiz mekhanizmov formirovaniya polupryamogo radiatsionnogo effekta sibirskogo dymovogo aerozolya v Arktike // Optika atmosf. i okeana. 2024. V. 37, N 2. P. 127–137. DOI: 10.15372/AOO20240206; Konovalov I.B., Golovushkin N.A. Model analysis of origination of semidirect radiative effect of Siberian biomass burning aerosol in the Arctic // Atmos. Ocean. Opt. 2024. V. 37, N 3. P. 382–393.
19. Vil'fand R.M., Kirsanov A.A., Revokatova A.P., Rivin G.S., Surkova G.V. Prognoz peremeshcheniya i transformatsii zagryaznyayushchikh veshchestv v atmosfere s pomoshch'yu modeli COSMO-ART // Meteorol. gidrol. 2017. N 5. P. 31–40.
20. Kuznetsova I.N., Nakhaev M.I., Kirsanov A.A., Borisov D.V., Tkacheva Yг.V., Rivin G.S., Lezina E.A. Testirovanie i perspektivy tekhnologii prognozirovaniya zagryazneniya vozdukha s primeneniem khimicheskikh transportnykh modelei CHIMERE i COSMO-Ru2ART // Gidrometeorologicheskie issledovaniya i prognozy. 2022. N 4. P. 147–170. DOI: 10.37162/2618-9631-2022-4-147-170.
21. Andreev V.V., Arshinov M.Yu., Belan B.D., Belan S.B., Gordyushkin V.A., Davydov D.K., Demin V.I., Dudorova N.V., Elansky N.F., Ivanov R.V., Ivlev G.A., Kozlov A.V., Konovaltseva L.V., Korenskiy M.Yu., Kotel’nikov S.N., Kuznetsova I.N., Lapchenko V.A., Lezina E.A., Marchenko O.O., Obolkin V.A., Postylyakov O.V., Potemkin V.L., Savkin D.E., Semutnikova E.G., Senik I.A., Stepanov E.V., Tolmachev G.N., Fofonov A.V., Khodzher T.V., Chelibanov I.V., Chelibanov V.P., Shirotov V.V., Shtabkin Yu.A., Shukurov K.A. Kontsentratsiya troposfernogo ozona na territorii Rossii v 2023 year // Optika atmosf. i okeana. 2024. V. 37, N 8. P. 688–698. DOI: 10.15372/AOO20240809; Andreev V.V., Arshinov M.Yu., Belan B.D., Belan S.B., Gordyushkin V.A., Davydov D.K., Demin V.I., Dudorova N.V., Elansky N.F., Ivanov R.V., Ivlev G.A., Kozlov A.V., Konovaltseva L.V., Korenskiy M.Yu., Kotel’nikov S.N., Kuznetsova I.N., Lapchenko V.A., Lezina E.A., Marchenko O.O., Obolkin V.A., Postylyakov O.V., Potemkin V.L., Savkin D.E., Semutnikova E.G., Senik I.A., Stepanov E.V., Tolmachev G.N., Fofonov A.V., Khodzher T.V., Chelibanov I.V., Chelibanov V.P., Shirotov V.V., Shtabkin Yu.A., Shukurov K.A. Tropospheric ozone concentration in Russia in 2023 // Atmos. Ocean. Opt. 2024. V. 37, N 6. P. 849–864.
22. Nerobelov  G.M., Timofeev Yu.M., Smyshlyaev S.P., Foka S.Ch., Imkhasin Kh.Kh Sravneniya rezul'tatov chislennogo modelirovaniya i izmerenii soderjaniya СО₂ v atmosfere Sankt-Peterburga // Izv. RAN. Fiz. atmosf. i okeana. 2023. V. 59, N 3. P. 322–335. DOI: 10.31857/S0002351523020050.
23. Shalygina I.Yu., Kuznetsova I.N., Nakhaev M.I., Borisov D.V., Lezina E.A. Effektivnost' korrektsii emissii dlya raschetov khimicheskoi transportnoi modeli CHIMERE v Moskovskom regione // Optika atmosf. i okeana. 2020. V. 33, N 6. P. 441–447. DOI: 10.15372/AOO20200604.
24. Kahraman A., Sivri N. Comparison of metropolitan cities for mortality rates attributed to ambient air pollution using the AirQ model // Environ. Sci. Pollut. Res. 2022. N 29. P. 43034–43047. DOI: 10.1007/s11356-021-18341-1.
25. Vasin V.A., Efimenko N.V., Granberg I.G., Savinykh V.V., Povolotskaya N.P., Mkrtchyan R.I., Ginzburg A.S., Golitsyn G.S., Jerlitsina L.I., Kortunova Z.V., Maksimenkov L.O., Pogarskii F.A., Rubinshtein K.G., Senik I.A., Sklyar A.P. Nekotorye osobennosti izucheniya svyazi serdechno-sosudistykh zabolevanii s ekologicheskimi i meteorologicheskimi faktorami na nizkogornykh kurortakh Rossii // Vrach skoroi pomoshchi. 2009. N 5. P. 61–62.
26. Granberg I., Golitsyn G., Pogarski F., Istoshin N., Efimenko N. Abrupt weather changes and atmospheric pollution influence on sickness and death rates (for Moscow and Caucasian Mineral Waters regions) // Proc. ISRSE. 2009. N 5. P. 1042–1045.
27. Golitsyn G.S., Granberg I.G., Efimenko N.P., Povolotskaya N.P. Atmosfera i zdorov'e // Zemlya i Vselennaya. 2009. N 3. P. 27–36.
28. Makosko A.A., Matesheva A.V. Zagryaznenie atmosfery i kachestvo jizni naseleniya v XXI veke: ugrozy i perspektivy. M.: Rossiiskaya akademiya nauk, 2020. 258 p.
29. Bessagnet B., Menut L., Lapere R., Couvidat F., Jaffrezo J.-L., Mailler S., Favez O., Pennel R., Siour G. High resolution chemistry transport modeling with the on-line CHIMERE-WRF model over the French Alps – analysis of a feedback of surface particulate matter concentrations on mountain meteorology // Atmosphere. 2020. V. 11, iss. 6. P. 565. DOI: 10.3390/atmos11060565.
30. Bessagnet B., Thapa N., Bajga D., Sahu R., Saikia A., Cholakian A., Menut L., Siour G., Wangchuk T., Crippa M., Gurung K. High resolution air quality simulation in the Himalayan valleys, a case study in Bhutan // Atmos. Chem. Phys. 2025. N 25. P. 18675–18696. DOI: 10.5194/acp-25-18675-2025.
31. Gosudarstvennyi doklad o sostoyanii sanitarno-epidemiologicheskogo blagopoluchiya naseleniya v Stavropol'skom krae v 2023 year. Stavropol': Upravlenie Rospotrebnadzora po Stavropol'skomu krayu, 2024. 180 p.
32. Belousov V., Belikov I., Moiseenko K., Skorokhod A. Variations of organic and inorganic atmospheric boundary layer gaseous species by observations in Moscow and Zvenigorod // Rus. J. Earth Sci. V. 23. P. ES0206. DOI: 10.2205/2023ES02SI06.
33. Wolf T., Esau I., Reuder J. Analysis of the vertical temperature structure in the Bergen valley, Norway, and its connection to pollution episodes // J. Geophys. Res.: Atmos. 2014. N 119. P. 10.645–10.662. DOI: 10.1002/2014JD022085.
34. Menut L., Cholakian A., Pennel R., Siour G., Mailler S., Valari M., Lugon L., Meurdesoif Y. The CHIMERE chemistry-transport model v2023r1 // Geosci. Model Dev. 2024. N 17. P. 5431–5457.
35. Skamarock W., Klemp J., Dudhia J., Gill D., Barker D., Duda M., Huang X-Y., Wang W., Powers J. A Description of the Advanced Research WRF Version 2: NCAR Technical Note, Colorado. 2005. N NCAR/TN–468+STR. URL: https://www.research-gate.net/publication/284890700_A_description_ of_the_advanced_research_WRF_Version_2_Tech_Rep_NCARTN_468STR.
36. Derognat C., Beekmann M., Baeumle M., Martin D., Schmidt H. Effect of biogenic volatile organic compound emissions on tropospheric chemistry during the atmospheric pollution over the Paris area (Esquif) campaign in the Ile-de-France region // Atmos. Environ. 2003. N 24. P. 481–518.
37. Tkacheva Yu.V. Metodika interpolyatsii kusochno-lineinykh dannykh ob emissiyakh avtotransporta na regulyarnuyu model'nuyu setku // Gidrometeorologicheskie issledovaniya i prognozy. 2018. N 2. P. 170–180.
38. Shalygina I.Yu., Nakhaev M.I., Kuznetsova I.N., Konovalov I.B., Zakharova P.V. Regional'naya adaptatsiya bazy dannykh vybrosov zagryaznyayushchikh veshchestv v atmosferu // Gidrometeorologicheskie issledovaniya i prognozy. 2018. N 3. P. 33–45.
39. Dore A., Carslaw D., Braban C., Cain M., Chemel C., Conolly C., Derwent R.G., Griffiths S.J., Hall J., Hayman G., Lawrence S., Metcalfe S.E., Redington A., Simpson D., Sutton M.A., Sutton P., Tang Y.S., Vieno M., Werner M., Whyatt J.D. Evaluation of the performance of different atmospheric chemical transport models and inter-comparison of nitrogen and sulphur deposition estimates for the UK // Atmos. Environ. 2015. V. 119. P. 131–143. DOI: 10.1016/j.atmosenv.2015.08.008.
40. Prank M., Sofiev M., Tsyro S., Hendriks C., Semeena V., Francis X., Butler T., Denier van der Gon H., Friedrich R., Hendricks J., Kong X., Lawrence M., Righi M., Samaras Z., Sausen R., Kukkonen J., Sokhi R. Evaluation of the performance of four chemical transport models in predicting the aerosol chemical composition in Europe in 2005 // Atmos. Chem. Phys. 2016. V. 16. P. 6041–6070. DOI: 10.5194/acp-2015-102.
41. Schaap M., Cuvelier C., Hendriks C., Bessagnet B., Baldasano J.M., Colette A., Thunis P., Karam D., Fagerli H., Graff A., Kranenburg R., Nyiri A., Pay M.T., Rouïl L., Schulz M., Simpson D., Stern R., Terrenoire E., Wind P. Performance of European chemistry transport models as function of horizontal resolution // Atmos. Environ. 2015. V. 112. Р. 90–105. DOI: 10.1016/j.atmosenv.2015.04.003.