Statistical assessment of the dynamics of changes in the PM10 and PM2.5 level in the air of urbanized areas

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dc.citation.epage262
dc.citation.issue4
dc.citation.journalTitleЕкологічні проблеми
dc.citation.spage256
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorSabadash, Vira
dc.contributor.authorLopushansky, Oleksiy
dc.contributor.authorLysko, Vitaliy
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2024-04-03T08:00:47Z
dc.date.available2024-04-03T08:00:47Z
dc.date.created2023-02-28
dc.date.issued2023-02-28
dc.description.abstractThis article addresses the issue of atmospheric pollution caused by solid particles in urban environments. The presence of PM10 and PM2,5 particles in the air of major cities and industrial areas worldwide has been examined. An evaluation of atmospheric pollution levels with PM10 and PM2,5 particles in Kostopil, considering current air quality standards in Ukraine and the European Union, has been conducted. The authors employed the gravimetric method to measure the levels of suspended dust particles (PM10 and PM2,5) in Kostopil from autumn 2022 to winter 2023. The study revealed an excessive amount of fine dust particles in the city's air, exceeding the maximum permissible values outlined in regulatory laws by 2.1-2.7 times. Furthermore, the monitoring of changes in suspended dust particle levels showed peak values of PM10 = 1.15 mg/m³ in January and PM2,5 = 0.96 mg/m³ in December. The results of the statistical analysis of particle level distribution in Kostopil's urban areas indicated the statistical significance of certain distribution parameters, specifically SW-W and D for PM10 and PM2,5 particle classes.
dc.format.extent256-262
dc.format.pages7
dc.identifier.citationSabadash V. Statistical assessment of the dynamics of changes in the PM10 and PM2.5 level in the air of urbanized areas / Vira Sabadash, Oleksiy Lopushansky, Vitaliy Lysko // Environmental Problems. — Lviv : Lviv Politechnic Publishing House, 2023. — Vol 8. — No 4. — P. 256–262.
dc.identifier.citationenSabadash V. Statistical assessment of the dynamics of changes in the PM10 and PM2.5 level in the air of urbanized areas / Vira Sabadash, Oleksiy Lopushansky, Vitaliy Lysko // Environmental Problems. — Lviv : Lviv Politechnic Publishing House, 2023. — Vol 8. — No 4. — P. 256–262.
dc.identifier.doidoi.org/10.23939/ep2023.04.256
dc.identifier.issn2414-5950
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/61655
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofЕкологічні проблеми, 4 (8), 2023
dc.relation.ispartofEnvironmental Problems, 4 (8), 2023
dc.relation.referencesAdamchuk, O.S., & Gulay, L.D. (2015). Ecological analysis of the state of atmospheric air within the Kostopil district of the Rivne region. Bulletin of the Lviv State University of Life Safety, 12, 114-118.
dc.relation.referencesAguilera, R., Luo, N., Basu, R., Wu, J., Clemesha, R., Gershunov, A., & Benmarhnia, T. (2023). A novel ensemble-based statistical approach to estimate daily wildfire-specific PM2, 5 in California (2006–2020). Environment International, 171, 107719. doi: https://doi.org/10.1016/j.envint.2022.107719
dc.relation.referencesFeng, S., Huang, F., Zhang, Y., Feng, Y., Zhang, Y., Cao, Y., & Wang, X. (2023). The pathophysiological and molecular mechanisms of atmospheric PM2, 5 Affecting cardiovascular health: A review. Ecotoxicology and Environmental Safety, 249, 114444. doi: https://doi.org/10.1016/j.ecoenv.2022.114444
dc.relation.referencesHan, L,, Yang, X,, Zhang, P,, Xiao, Q,, Cheng, S,, Wang, H, & Zheng, A, (2023). Temporal variations of urban re-suspended road dust characteristics and its vital contributions to airborne PM2, 5/PM10 during a long period in Beijing. Environmental Pollution, 330, 121727. doi: https://doi.org/10.1016/j.envpol.2023.121727
dc.relation.referencesJia, N., Li, Y., Chen, R., & Yang., H. (2023). A Review of Global PM 2,5 Exposure Research Trends from 1992 to 2022. Sustainability, 15(13), 10509. doi: https://doi.org/10.3390/su151310509
dc.relation.referencesJia, W., Li, L., Lei, Y., & Wu, S. (2023). Synergistic effect of CO2 and PM2, 5 emissions from coal consumption and the impacts on health effects. Journal of Environmental Management, 325, 116535. doi: https://doi.org/10.1016/j.jenvman.2022.116535
dc.relation.referencesKarimian, H., Li, Y., Chen, Y., & Wang, Z. (2023). Evaluation of different machine learning approaches and aerosol optical depth in PM 2,5 predictions, Environmental Research, 216, 114465. https://doi.org/10.1016/j.envres.2022.114465
dc.relation.referencesMassey, D., Kulshrestha, A., Masih, J., & Taneja., ABEJ. (2012). Seasonal trends of PM10, PM5, 0, PM2, 5 & PM1, 0 in indoor and outdoor environments of residential homes located in North-Central India. Building and Environment, 47, 223-231. doi: https://doi.org/10.1016/j.buildenv.2011.07.018
dc.relation.referencesQi, G., Wei, W., Wang, Z., Wang, Z., & Wei, L. (2023). The spatial-temporal evolution mechanism of PM2,5 level based on China's climate zoning. Journal of Environmental Management, 325, 116671. doi: https://doi.org/10.1016/j.jenvman.2022.116671
dc.relation.referencesTian, Y., Shi, G., Huang-Fu, Y. Q., Song, D. L., Liu, J. Y., Zhou, L. D., & Feng, Y. C. (2016). Seasonal and regional variations of source contributions for PM10 and PM2,5 in urban environment. Science of the Total Environment, 557, 697–704. doi: https://doi.org/10,1016/j,scitotenv,2016,03,107
dc.relation.referencesenAdamchuk, O.S., & Gulay, L.D. (2015). Ecological analysis of the state of atmospheric air within the Kostopil district of the Rivne region. Bulletin of the Lviv State University of Life Safety, 12, 114-118.
dc.relation.referencesenAguilera, R., Luo, N., Basu, R., Wu, J., Clemesha, R., Gershunov, A., & Benmarhnia, T. (2023). A novel ensemble-based statistical approach to estimate daily wildfire-specific PM2, 5 in California (2006–2020). Environment International, 171, 107719. doi: https://doi.org/10.1016/j.envint.2022.107719
dc.relation.referencesenFeng, S., Huang, F., Zhang, Y., Feng, Y., Zhang, Y., Cao, Y., & Wang, X. (2023). The pathophysiological and molecular mechanisms of atmospheric PM2, 5 Affecting cardiovascular health: A review. Ecotoxicology and Environmental Safety, 249, 114444. doi: https://doi.org/10.1016/j.ecoenv.2022.114444
dc.relation.referencesenHan, L,, Yang, X,, Zhang, P,, Xiao, Q,, Cheng, S,, Wang, H, & Zheng, A, (2023). Temporal variations of urban re-suspended road dust characteristics and its vital contributions to airborne PM2, 5/PM10 during a long period in Beijing. Environmental Pollution, 330, 121727. doi: https://doi.org/10.1016/j.envpol.2023.121727
dc.relation.referencesenJia, N., Li, Y., Chen, R., & Yang., H. (2023). A Review of Global PM 2,5 Exposure Research Trends from 1992 to 2022. Sustainability, 15(13), 10509. doi: https://doi.org/10.3390/su151310509
dc.relation.referencesenJia, W., Li, L., Lei, Y., & Wu, S. (2023). Synergistic effect of CO2 and PM2, 5 emissions from coal consumption and the impacts on health effects. Journal of Environmental Management, 325, 116535. doi: https://doi.org/10.1016/j.jenvman.2022.116535
dc.relation.referencesenKarimian, H., Li, Y., Chen, Y., & Wang, Z. (2023). Evaluation of different machine learning approaches and aerosol optical depth in PM 2,5 predictions, Environmental Research, 216, 114465. https://doi.org/10.1016/j.envres.2022.114465
dc.relation.referencesenMassey, D., Kulshrestha, A., Masih, J., & Taneja., ABEJ. (2012). Seasonal trends of PM10, PM5, 0, PM2, 5 & PM1, 0 in indoor and outdoor environments of residential homes located in North-Central India. Building and Environment, 47, 223-231. doi: https://doi.org/10.1016/j.buildenv.2011.07.018
dc.relation.referencesenQi, G., Wei, W., Wang, Z., Wang, Z., & Wei, L. (2023). The spatial-temporal evolution mechanism of PM2,5 level based on China's climate zoning. Journal of Environmental Management, 325, 116671. doi: https://doi.org/10.1016/j.jenvman.2022.116671
dc.relation.referencesenTian, Y., Shi, G., Huang-Fu, Y. Q., Song, D. L., Liu, J. Y., Zhou, L. D., & Feng, Y. C. (2016). Seasonal and regional variations of source contributions for PM10 and PM2,5 in urban environment. Science of the Total Environment, 557, 697–704. doi: https://doi.org/10,1016/j,scitotenv,2016,03,107
dc.relation.urihttps://doi.org/10.1016/j.envint.2022.107719
dc.relation.urihttps://doi.org/10.1016/j.ecoenv.2022.114444
dc.relation.urihttps://doi.org/10.1016/j.envpol.2023.121727
dc.relation.urihttps://doi.org/10.3390/su151310509
dc.relation.urihttps://doi.org/10.1016/j.jenvman.2022.116535
dc.relation.urihttps://doi.org/10.1016/j.envres.2022.114465
dc.relation.urihttps://doi.org/10.1016/j.buildenv.2011.07.018
dc.relation.urihttps://doi.org/10.1016/j.jenvman.2022.116671
dc.relation.urihttps://doi.org/10,1016/j,scitotenv,2016,03,107
dc.rights.holder© Національний університет “Львівська політехніка”, 2023
dc.rights.holder© Sabadash V., Lopushansky O., Lysko V., 2023
dc.subjectsolid particles
dc.subjectfine dust
dc.subjectPM10
dc.subjectPM2.5
dc.subjectair pollution
dc.subjectenvironment
dc.titleStatistical assessment of the dynamics of changes in the PM10 and PM2.5 level in the air of urbanized areas
dc.typeArticle

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Environmental Problems. – 2023. – Vol. 8, No. 4