Geographical Analysis of the Interplay Between Air Pollutants and Meteorological Factors in Bhiwadi Town
Keywords:
Air Quality, Meteorological Factors, Trend Analysis, Pearson’s Correlation, Urban Development, Environmental Policy, Health Impacts
Abstract
Air quality serves as a critical measure globally for evaluating current air pollution levels and their associated health risks. In India, many regions experience alarmingly high concentrations of key air pollutants. This study explores the relationship between specific air pollutants (NO₂, SO₂, and PM₁₀) and meteorological parameters (temperature, relative humidity, precipitation, and air pressure) in Bhiwadi town over a five-year period, from January 2019 to December 2023. Using data from two RSPCB air monitoring stations, a comprehensive statistical analysis was conducted, including trend assessments and Pearson's correlation coefficients, to examine interactions between pollutants and weather variables. The analysis revealed notable seasonal variations and significant correlations. For instance, PM₁₀ levels were heavily influenced by precipitation and wind speed, while NO₂ and SO₂ demonstrated strong associations with air pressure. These findings emphasize the critical role of meteorological factors in shaping air pollution levels and offer valuable insights for formulating policies aimed at improving air quality in Bhiwadi town. The study highlights the pressing need for effective measures to address severe urban air pollution in developing nations, with far-reaching implications for public health and environmental sustainability.References
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5. Manju, A., Kalaiselvi, K., Dhananjayan, V., Palanivel, M., Banupriya, G., Vidhya, M., Karunamoorthy, P., & Ravichandran, B. (2018). Spatio-seasonal variation in ambient air pollutants and influence of meteorological factors in Coimbatore, Southern India. Air Quality, Atmosphere & Health, 11. https://doi.org/10.1007/s11869-018-0617-x
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7. Rahman, M. M., Paul, K. C., Hossain, M. A., Ali, G. G. M. N., Rahman, M. S., & Thill, J.-C. (2021). Machine Learning on the COVID-19 Pandemic, Human Mobility and Air Quality: A Review. IEEE Access, 9, 72420-72450. https://doi.org/10.1109/ACCESS.2021.3079121
8. Ruhela, M., Maheshwari, V., Ahamad, F., & et al. (2022). Air quality assessment of Jaipur city Rajasthan after the COVID-19 lockdown. Spatial Information Research, 30(4), 597-605. https://doi.org/10.1007/s41324-022-00456-3
9. Salam, A., Ullah, B., & Islam, S. (2013). Carbonaceous species in total suspended particulate matters at different urban and suburban locations in the Greater Dhaka region, Bangladesh. Air Quality, Atmosphere, & Health, 11(8), 925–935. https://doi.org/10.1007/s11869-011-0166-z
10. Zhang, Q., Qiu, Z., Chung, K., & Huang, S. (2014). Link between environmental air pollution and allergic asthma: East meets West. Journal of Thoracic Disease, 7(1). https://jtd.amegroups.org/article/view/3582
Published
2024-08-30
How to Cite
Dr Sangeeta Chaudhary. (2024). Geographical Analysis of the Interplay Between Air Pollutants and Meteorological Factors in Bhiwadi Town. Revista Electronica De Veterinaria, 25(2), 803 - 810. https://doi.org/10.69980/redvet.v25i2.1540
Section
Articles
