Details

Autor(en) / Beteiligte

• Kolluru, Soma Sekhara Rao
• Nagendra, S. M. Shiva
• Patra, Aditya Kumar
• Gautam, Sneha
• Alshetty, V. Dheeraj
• Kumar, Prashant

Titel

Did unprecedented air pollution levels cause spike in Delhi’s COVID cases during second wave?

Ist Teil von

• Stochastic environmental research and risk assessment, 2023-02, Vol.37 (2), p.795-810

Ort / Verlag

Berlin/Heidelberg: Springer Berlin Heidelberg

Erscheinungsjahr

2023

Link zum Volltext

Quelle

Springer Online Journals Complete

Beschreibungen/Notizen

• The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM 2.5 : 67 µg m −3 (lockdown) versus 81 µg m −3 (pre-lockdown); PM 10 : 171 µg m −3 versus 235 µg m −3 ; CO: 0.9 mg m −3 versus 1.1 mg m −3 ) except ozone which increased during the lockdown period (57 µg m −3 versus 39 µg m −3 ). The variation in pollutant concentrations revealed that PM 2.5 , PM 10 and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.