Cargando…
Spatio-temporal analysis of air quality and its relationship with major COVID-19 hotspot places in India
The COVID-19 pandemic spread worldwide, such as wind, with more than 400,000 documented cases as of March 24(th), 2020. In this regard, strict lockdown measures were imposed in India on the same date to stop virus spread. Thereafter, various lockdown impacts were observed, and one of the immediate e...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846885/ https://www.ncbi.nlm.nih.gov/pubmed/33553572 http://dx.doi.org/10.1016/j.rsase.2021.100473 |
Sumario: | The COVID-19 pandemic spread worldwide, such as wind, with more than 400,000 documented cases as of March 24(th), 2020. In this regard, strict lockdown measures were imposed in India on the same date to stop virus spread. Thereafter, various lockdown impacts were observed, and one of the immediate effects was a reduction in air pollution levels across the world and in India as well. In this study, we have observed approximately 40% reduction in air quality index (AQI) during one month of lockdown in India. The detailed investigations were performed for 14 major hotspot places where the COVID-19 cases were >1000 (as of 1(st) June 2020) and represents more than 70% associated mortality in India. We assessed the impact of lockdown on different air quality indicators, including ground (PM(2.5), PM(10), NO(2), SO(2), O(3), and AQI) and tropospheric nitric oxide (NO(2)) pollutants, through ground monitoring stations and Sentinel-5 satellite datasets respectively. The highest reductions were noticed in NO(2) (-48.68%), PM(2.5) (-34.84%) and PM(10) (-33.89%) air pollutant (unit in μg/m(3)) post-lockdown. Moreover, tropospheric NO(2) (mol/m(2)) concentrations were also improved over Delhi, Mumbai, Kolkata, Thane, and Ahmedabad metro cities. We found strong positive correlation of COVID-19 mortality with PM(10) (R(2) = 0.145; r = 0.38) and AQI (R(2) = 0.17; r = 0.412) pollutant indicators that significantly improved next time point. The correlation finding suggests that long-term bad air quality may aggravate the clinical symptoms of the disease. |
---|