International Journal of
Advanced Multidisciplinary Application

Volume 3, Issue 3

• Author(s)Marco Trevisan
• AffiliationDepartment of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy
• Page No.104-109
• Volume, Issue & YearVolume 3, Issue 3, March 2026
• Published On2026/03/25
• JournalInternational Journal of Advanced Multidisciplinary Application (IJAMA)
• ISSN No.3048-9350
• DOIhttps://doi.org/10.5281/zenodo.19334478

Article Indexing

Abstract

Rapid urbanisation and industrial expansion in Maharashtra have contributed to persistent deterioration of ambient air quality, generating measurable adverse respiratory health outcomes in exposed populations. This study presents a systematic assessment of six key air pollutants — PM2.5, PM10, NO2, SO2, CO, and ground-level ozone — measured across thirty monitoring stations in Pune, Mumbai, and Nagpur Metropolitan Regions over a twenty-four-month continuous monitoring period. Simultaneously, respiratory morbidity data including incidence rates of asthma exacerbation, chronic obstructive pulmonary disease hospitalisations, and upper respiratory tract infection consultations were extracted from district health records for the same temporal and spatial frame.
Industrial zone monitoring stations recorded PM2.5 levels averaging 124.6 μg/m³, exceeding the WHO annual guideline of 15 μg/m³ by more than eightfold. Urban residential zones recorded lower but still severely elevated levels of 87.4 μg/m³. Distributed lag non-linear model analysis identified a significant lagged association between PM2.5 and PM10 concentrations and respiratory hospital admissions at lags of two to seven days. Every 10 μg/m³ increase in PM2.5 was associated with a 6.8 percent increase in asthma emergency department visits (95% CI 5.2-8.4%) and a 4.3 percent increase in COPD exacerbation hospitalisations (95% CI 3.1-5.5%). The Italian collaborative team's contribution validated the spatiotemporal interpolation methodology using kriging models previously applied in northern Italian industrial corridors.

Keywords: air quality, PM2.5, PM10, respiratory health, Maharashtra, ambient monitoring, DLNM, asthma, COPD, environmental epidemiology

References

1. [1] Burnett, R., et al. (2018). Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter. Proceedings of the National Academy of Sciences, 115(38), 9592-9597.
2. [2] CPCB. (2023). National Ambient Air Quality Status and Trends 2022. Central Pollution Control Board, New Delhi.
3. [3] Gasparrini, A., Armstrong, B., & Kenward, M. G. (2010). Distributed lag non-linear models. Statistics in Medicine, 29(21), 2224-2234.
4. [4] Ghosh, R., Joshi, S. P., Bhardwaj, P., Gopinath, K. P., & Bhatt, A. (2019). Air pollution and health outcomes: A review. International Journal of Environmental Research and Public Health, 16(5), 885-902.
5. [5] Ghude, S. D., et al. (2016). Premature mortality in India due to PM2.5, ozone, and NO2 in the context of the air pollution control interventions. Nature Scientific Reports, 6, 23217.
6. [6] India State-Level Disease Burden Initiative. (2019). The impact of air pollution on deaths, disease burden, and life expectancy across the states of India. Lancet Planetary Health, 3(1), e26-e39.
7. [7] Kulkarni, S. H., & Desai, M. M. (2020). Indoor-outdoor PM2.5 relationships in industrial zones of Pune: Implications for personal exposure estimation. Environmental Science and Pollution Research, 27(12), 13418-13429.
8. [8] MPCB. (2023). Maharashtra Air Quality Monitoring Annual Report 2022-23. Maharashtra Pollution Control Board, Mumbai.
9. [9] Nair, P. R., Patil, S., & Kulkarni, A. (2021). Seasonal variability in respiratory hospital admissions and PM10 concentrations in Pune Metropolitan Region. Journal of Exposure Science and Environmental Epidemiology, 31(4), 712-724.
10. [10] Rajput, P., Sarin, M., Sharma, D., & Singh, D. (2014). Characteristics and emission budget of carbonaceous species from post-harvest agricultural-waste burning in source region of the Indo-Gangetic Plain. Tellus B, 66, 21026.
11. [11] Trevisan, M., Romano, D., & Paneghini, S. (2021). Kriging-based spatial interpolation of PM2.5 for health impact assessment in northern Italian industrial corridors. Atmospheric Environment, 247, 118174.
12. [12] WHO. (2021). WHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide. World Health Organization, Geneva.
13. [13] Xing, Y. F., Xu, Y. H., Shi, M. H., & Lian, Y. X. (2016). The impact of PM2.5 on the human respiratory system. Journal of Thoracic Disease, 8(1), E69-E74.
14. [14] Zhang, Q., et al. (2019). Drivers of improved PM2.5 air quality in China from 2013 to 2017. Proceedings of the National Academy of Sciences, 116(49), 24463-24469.
15. [15] Zhu, S., Selin, N. E., & Bhave, P. V. (2022). Exposure-response functions for short-term health

Explore Our Related Journals

Looking for the right journal for your next manuscript? Explore our international peer-reviewed journals covering engineering, management, computer science, artificial intelligence and multidisciplinary research.