STATISTICAL ASSESSMENT OF THE DYNAMICS OF CHANGES IN THE PM10 AND PM2.5 LEVEL IN THE AIR OF URBANIZED AREAS

EP.
2023;
: сс.256-262
1
Національний університет “Львівська політехніка”
2
Lviv Polytechnic National University,
3
Lviv National Polytec Lviv Polytechnic National University

This 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.

1. Adamchuk, 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.

2. Aguilera, 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

https://doi.org/10.1016/j.envint.2022.107719

3. Feng, 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

https://doi.org/10.1016/j.ecoenv.2022.114444

4. Han, 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

https://doi.org/10.1016/j.envpol.2023.121727

5. Jia, 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

https://doi.org/10.3390/su151310509

6. Jia, 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

https://doi.org/10.1016/j.jenvman.2022.116535

7. Karimian, 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

https://doi.org/10.1016/j.envres.2022.114465

8. Massey, 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

https://doi.org/10.1016/j.buildenv.2011.07.018

9. Qi, 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

https://doi.org/10.1016/j.jenvman.2022.116671

10. Tian, 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

https://doi.org/10.1016/j.scitotenv.2016.03.107