Main Article Content
Abstract
Concerning ecological integrity, public health, and climate change, air quality is a crucial environmental concern. In emerging nations like India, in particular, rapid industrialization and urbanization have had a major negative impact on the quality of the air. Not an exception to this tendency is Meerut, a well-known city in the state of Uttar Pradesh. This study compares data from various locations, including industrial areas, commercial areas, residential areas, and roadside, to identify trends and potential sources of air pollution. It then evaluates the air quality at a few selected areas in Meerut City. The sampling of the air was performed monthly starting from January 2024 to June 2024 using the high-volume respirable dust sampler (Envirotech-ETC APM 415 BL) with a gaseous attachment. The study focuses on major air pollutants that are known to have negative impacts on both human health and the ecosystem, such as carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM10 and PM2.5). The data was processed to calculate the Air Quality Index (AQI) to rank the studied sites based on pollution and to make the data understandable to the common people. The obtained results revealed that at all the studied sites, values of PM10 (107.0-116.6 µg/m³) were found beyond the standard values of National Ambient Air Quality Standards (NAAQ) values of 100 µg/m³, and the values of the rest of the analyzed parameters {PM2.5 (50.6-59.4 µg/m³), NO₂ (29.7-33.1 µg/m³), SO₂ (9.1-10.3 µg/m³), and CO (0.9 µg/m³)} were found within the NAAQ standard. Among all the parameters, PM10 was considered as the criteria pollutant because the subindex (Si) of PM10 (1.07-1.17) was found highest at all the sites. The subindex (Si) of CO (0.22-0.95) was found to be the lowest among all the studied parameters. Based on the AQI, we found the overall quality of air in the study area to be moderately polluted.
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References
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References
Ahamad, F., Bhutiani, R., & Ruhela, M. (2022). Environmental Quality Monitoring Using Environmental Quality Indices (EQI) Geographic Information System (GIS) and Remote Sensing: A Review. GIScience for the Sustainable Management of Water Resources, 331-348. DOI: https://doi.org/10.1201/9781003284512-21
Almetwally, A. A., Bin-Jumah, M., & Allam, A. A. (2020). Ambient air pollution and its influence on human health and welfare: an overview. Environmental Science and Pollution Research, 27, 24815-24830. DOI: https://doi.org/10.1007/s11356-020-09042-2
Babayemi, J. O., Ogundiran, M. B., & Osibanjo, O. (2016). Overview of environmental hazards and health effects of pollution in developing countries: a case study of Nigeria. Environmental Quality Management, 26(1), 51-71. DOI: https://doi.org/10.1002/tqem.21480
Bagtasa, G., & Yuan, C. S. (2020). Influence of local meteorology on the chemical characteristics of fine particulates in Metropolitan Manila in the Philippines. Atmospheric Pollution Research, 11(8), 1359-1369. DOI: https://doi.org/10.1016/j.apr.2020.05.013
Chen, S., Guo, C., & Huang, X. (2018). Air pollution, student health, and school absences: Evidence from China. Journal of Environmental Economics and Management, 92, 465-497. DOI: https://doi.org/10.1016/j.jeem.2018.10.002
Choo, G. H., Seo, J., Yoon, J., Kim, D. R., & Lee, D. W. (2020). Analysis of long-term (2005–2018) trends in tropospheric NO2 percentiles over Northeast Asia. Atmospheric Pollution Research, 11(8), 1429-1440. DOI: https://doi.org/10.1016/j.apr.2020.05.012
Dai, W., Gao, J., Cao, G., & Ouyang, F. (2013). Chemical composition and source identification of PM2. 5 in the suburb of Shenzhen, China. Atmospheric Research, 122, 391-400. DOI: https://doi.org/10.1016/j.atmosres.2012.12.004
Franceschi, F., Cobo, M., & Figueredo, M. (2018). Discovering relationships and forecasting PM10 and PM2. 5 concentrations in Bogotá, Colombia, using artificial neural networks, principal component analysis, and k-means clustering. Atmospheric Pollution Research, 9(5), 912-922. DOI: https://doi.org/10.1016/j.apr.2018.02.006
Greenstone, M., & Hanna, R. (2014). Environmental regulations, air and water pollution, and infant mortality in India. American Economic Review, 104(10), 3038-3072. 10.1257/aer.104.10.3038 DOI: https://doi.org/10.1257/aer.104.10.3038
Gulia, S., Mittal, A., & Khare, M. (2018). Quantitative evaluation of source interventions for urban air quality improvement-A case study of Delhi city. Atmospheric Pollution Research, 9(3), 577-583. DOI: https://doi.org/10.1016/j.apr.2017.12.003
Gurjar, B. R., Butler, T. M., Lawrence, M. G., & Lelieveld, J. (2008). Evaluation of emissions and air quality in megacities. Atmospheric environment, 42(7), 1593-1606. DOI: https://doi.org/10.1016/j.atmosenv.2007.10.048
Kulshreshtha, N., Kumar, S., & Vaishya, R. C. (2021). Assessment of trace metal concentration in the ambient air of the Prayagraj City during Diwali festival—a case study. Environmental Monitoring and Assessment, 193, 1-12. DOI: https://doi.org/10.1007/s10661-021-08932-3
Kumar, P., Gulia, S., Harrison, R. M., & Khare, M. (2017). The influence of odd–even car trial on fine and coarse particles in Delhi. Environmental Pollution, 225, 20-30. DOI: https://doi.org/10.1016/j.envpol.2017.03.017
Kumar, R., Gupta, P., & Jangid, A. (2020). An empirical study towards air pollution control in Agra, India: a case study. SN Applied Sciences, 2, 1-11. DOI: https://doi.org/10.1007/s42452-020-03826-4
Levy, H., Horowitz, L. W., Schwarzkopf, M. D., Ming, Y., Golaz, J. C., Naik, V., & Ramaswamy, V. (2013). The roles of aerosol direct and indirect effects in past and future climate change. Journal of Geophysical Research: Atmospheres, 118(10), 4521-4532. DOI: https://doi.org/10.1002/jgrd.50192
Li, H., Wang, J., & Yang, H. (2020). A novel dynamic ensemble air quality index forecasting system. Atmospheric Pollution Research, 11(8), 1258-1270. DOI: https://doi.org/10.1016/j.apr.2020.04.010
Licbinsky, R., Faimon, J., Tanda, S., Hegrova, J., Goessler, W., & Uberhuberova, J. (2020). Changes in the elemental composition of particulate matter in a speleotherapeutic cave. Atmospheric Pollution Research, 11(7), 1142-1154. DOI: https://doi.org/10.1016/j.apr.2020.04.008
Meti. T., & Kumar, M. (2023) India’s New Delhi blanketed by toxic haze, world’s most polluted city again. Reuters. Published November 3, 2023. https://www.reuters.com/world/india/ air-pollution-indias-new-delhi-turns-severe-some-schoolsshut-2023-11-03/
Nasir, H., Goyal, K., & Prabhakar, D. (2016). Review of air quality monitoring: case study of India. Indian Journal of science and technology, 9(44), 1-8. DOI: https://doi.org/10.17485/ijst/2016/v9i44/105255
Naveen, V., & Anu, N. (2017). Time series analysis to forecast air quality indices in Thiruvananthapuram District, Kerala, India. International Journal of Engineering Research and Application, 7(6), 66-84. DOI: https://doi.org/10.9790/9622-0706036684
Pan, Y., Chen, S., Qiao, F., Ukkusuri, S. V., & Tang, K. (2019). Estimation of real-driving emissions for buses fueled with liquefied natural gas based on gradient boosted regression trees. Science of the Total Environment, 660, 741-750. DOI: https://doi.org/10.1016/j.scitotenv.2019.01.054
Punsompong, P., & Chantara, S. (2018). Identification of potential sources of PM10 pollution from biomass burning in northern Thailand using statistical analysis of trajectories. Atmospheric Pollution Research, 9(6), 1038-1051. DOI: https://doi.org/10.1016/j.apr.2018.04.003
Rajak, R., & Chattopadhyay, A. (2020). Short and long-term exposure to ambient air pollution and impact on health in India: a systematic review. International journal of environmental health research, 30(6), 593-617. DOI: https://doi.org/10.1080/09603123.2019.1612042
Rao, M. N., & Rao, H. V. N. (1986). Air pollution, TATA Mc GrawHill publishing company, New Delhi.
Ruhela, M., Maheshwari, V., Ahamad, F. Kamboj, V. (2022b). Air quality assessment of Jaipur city Rajasthan after the COVID‑19 lockdown. Spatial Information Research 30, 597–605, DOI: https://doi.org/10.1007/s41324-022-00456-3
Ruhela, M., Sharma, K., Bhutiani, R., Chandniha, S. K., Kumar, V., Tyagi, K., Ahamad, F. and Tyagi, I. (2022a). GIS‑based impact assessment and spatial distribution of air and water pollutants in mining area. Environmental Science and Pollution Research, 29(21), 31486-31500. DOI: https://doi.org/10.1007/s11356-021-18009-w
Samek, L., Stegowski, Z., Styszko, K., Furman, L., & Fiedor, J. (2018). Seasonal contribution of assessed sources to submicron and fine particulate matter in a Central European urban area. Environmental Pollution, 241, 406-411. DOI: https://doi.org/10.1016/j.envpol.2018.05.082
Saxena, A., & Shekhawat, S. (2017). Ambient air quality classification by grey wolf optimizer-based support vector machine. Journal of environmental and public health, 2017(1), 3131083. DOI: https://doi.org/10.1155/2017/3131083
Shao, Z., Fu, H., Li, D., Altan, O., & Cheng, T. (2019). Remote sensing monitoring of multi-scale watersheds impermeability for urban hydrological evaluation. Remote Sensing of Environment, 232, 111338. DOI: https://doi.org/10.1016/j.rse.2019.111338
Soni, M., Payra, S., & Verma, S. (2018). Particulate matter estimation over a semi-arid region Jaipur, India using satellite AOD and meteorological parameters. Atmospheric Pollution Research, 9(5), 949-958. DOI: https://doi.org/10.1016/j.apr.2018.03.001
Srivastava, R. K., Hall, R. E., Khan, S., Culligan, K., & Lani, B. W. (2005). Nitrogen oxides emission control options for coal-fired electric utility boilers. Journal of the Air & Waste Management Association, 55(9), 1367-1388. DOI: https://doi.org/10.1080/10473289.2005.10464736
USEPA, (2008). Integrated Science Assessment for Oxides of Nitrogen-Health Criteria. U.S. Environmental Protection Agency: 2008.
Wang, Z., Zhong, S., Peng, Z. R., & Cai, M. (2018). Fine-scale variations in PM2. 5 and black carbon concentrations and corresponding influential factors at an urban road intersection. Building and Environment, 141, 215-225. DOI: https://doi.org/10.1016/j.buildenv.2018.04.042
https://www.greenpeace.org/static/planet4-india-stateless/2024/03/ 44a856c8-2023_world_air_quality_report.pdf
Xu, X., Tong, T., Zhang, W., & Meng, L. (2020). Fine-grained prediction of PM2. 5 concentrations based on multisource data and deep learning. Atmospheric Pollution Research, 11(10), 1728-1737. https://doi.org/10.1016/j.apr.2020.06.032. DOI: https://doi.org/10.1016/j.apr.2020.06.032
Zhang, H., Dong, H., Ren, M., Liang, Q., Shen, X., Wang, Q., ... & Huang, C. (2020). Ambient air pollution exposure and gestational diabetes mellitus in Guangzhou, China: A prospective cohort study. Science of the Total Environment, 699, 134390. DOI: https://doi.org/10.1016/j.scitotenv.2019.134390
Zhao, W. C., Cheng, J. P., Yu, Z. Y., Tang, Q. L., Cheng, F., Yin, Y. W., & Wang, W. H. (2013). Levels, seasonal variations, and health risks assessment of ambient air pollutants in the residential areas. International Journal of Environmental Science and Technology, 10, 487-494. DOI: https://doi.org/10.1007/s13762-013-0178-3
Ziauddin, A., & Siddiqui, N. A. (2006). Air quality index (AQI)-A tool to determine ambient air quality. Pollution research, 25(4), 885.