Skip to main content

Advertisement

Log in

Unveiling the Surge: Exploring Elevated Air Pollution Amidst the COVID-19 Era (2019–2020) through Spatial Dynamics and Temporal Analysis in Delhi

  • Published:
Water, Air, & Soil Pollution Aims and scope Submit manuscript

Abstract

This comprehensive study delves into the complex issue of air pollution in Delhi, with a specific focus on the levels of PM2.5, PM10, NO2, and O3 during 2019 and 2020 across all four seasons. By analyzing primary data and employing advanced GIS techniques, the research not only quantifies pollution levels before and during the COVID-19 pandemic but also identifies high-risk areas and establishes a clear link between pollution and public health. The study reveals that 2019 witnessed more severe pollution levels compared to 2020, with PM2.5 and PM10 consistently exceeding WHO guidelines. Notably, PM10 levels breached Air Quality Index (AQI) standards, particularly during the winter season when it peaked at 67.99 µg/m3 and increased post-monsoon due to crop burning. Surprisingly, summer 2019 exhibited PM2.5 levels surpassing those of winter, underscoring the impact of reduced vehicle emissions during the summer months, while winter pollution levels remained relatively stable. The COVID-19 lockdowns in 2020 led to a substantial reduction in summer AQI by up to 58.00%, emphasizing the role of human activities in air quality. However, the study also indicates that monsoon AQI varied across different areas, with some experiencing higher emissions. Winter and post-monsoon AQI fluctuated by up to 24%, reinforcing the importance of continuous monitoring and source control measures. This research highlights the crucial role of Geographic Information Systems (GIS) in data analysis and informed decision-making for mitigating air pollution in Delhi. Its findings provide valuable insights for policymakers, offering guidance on promoting sustainability, public health, and a cleaner environment. In summary, the integration of GIS-driven pollution mapping aids in understanding and addressing the complex issue of air quality, ultimately contributing to a healthier and more environmentally friendly Delhi.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Data Availability

Not applicable.

References

  • Ahmadipour, F., Sari, A. E., & Bahramifar, N. (2019). Characterization, concentration and risk assessment of airborne particles using car engine air filter ( Case study : Tehran metropolis). Environmental Geochemistry and Health, 41, 2649–2663.

    Article  CAS  Google Scholar 

  • Akolkar. (2016). National air quality index. Central Pollution Control Board, 82, 1–44.

    Google Scholar 

  • Badarinath, K. V. S., Sharma, A. R., Kharol, S. K., & Prasad, V. K. (2009). Variations in CO, O3 and black carbon aerosol mass concentrations associated with planetary boundary layer (PBL) over tropical urban environment in India. J Atmos Chem, 62(1), 73–86. https://doi.org/10.1007/S10874-009-9137-2

    Article  CAS  Google Scholar 

  • Ban, Y., Liu, X., Yin, Z., Li, X., Yin, L.,... Zheng, W. (2023). Effect of urbanization on aerosol optical depth over Beijing: Land use and surface temperature analysis. Urban Climate, 51, 101655. https://doi.org/10.1016/j.uclim.2023.101655

  • Blessy, A., John Paul, J., Gautam, S., et al. (2023). IoT-Based air quality monitoring in hair salons: Screening of hazardous air pollutants based on personal exposure and health risk assessment. Water, Air, and Soil Pollution, 234, 336. https://doi.org/10.1007/s11270-023-06350-4

    Article  CAS  Google Scholar 

  • Budakoti, S., & Singh, C. (2021). Examining the characteristics of planetary boundary layer height and its relationship with atmospheric parameters over Indian sub-continent. Atmospheric Research, 264, 105854. https://doi.org/10.1016/J.ATMOSRES.2021.105854

    Article  Google Scholar 

  • Chattopadhay, S., Dey, P., & Michael, J. (2014). Dynamics and growth dichotomy of urban villages: Case study Delhi. International Journal for Housing Science & Its Applications, 38(2), 81–94.

  • Chen, J., Liu, Z., Yin, Z., Liu, X., Li, X., Yin, L.,... Zheng, W. (2023). Predict the effect of meteorological factors on haze using BP neural network. Urban Climate, 51, 101630. https://doi.org/10.1016/j.uclim.2023.101630

  • Childs, C. (2004). Interpolating surfaces in ArcGIS spatial analyst. ArcUser, July-September, 3235(569), 32–35.

    Google Scholar 

  • Clifford, A., Lang, L., Chen, R., Anstey, K. J., & Seaton, A. (2016). Exposure to air pollution and cognitive functioning across the life course–a systematic literature review. Environmental Research, 147, 383–398.

    Article  CAS  Google Scholar 

  • Cobbold, A. T., Crane, M. A., Knibbs, L. D., Hanigan, I. C., Greaves, S. P., & Rissel, C. E. (2022). Perceptions of air quality and concern for health in relation to long-term air pollution exposure, bushfires, and COVID-19 lockdown: A before-and-after study. The Journal of Climate Change and Health, 6, 100137.

    Article  Google Scholar 

  • Dubey, A., & Rasool, A. (2023). Impact on air quality Index of India due to lockdown. Procedia Computer Science, 218, 969–978. https://doi.org/10.1016/j.procs.2023.01.077

    Article  Google Scholar 

  • Gadhavi, H., & Jayaraman, A. (2010). Absorbing aerosols: Contribution of biomass burning and implications for radiative forcing. Annales Geophysicae, 28(1), 103–111. https://doi.org/10.5194/ANGEO-28-103-2010

    Article  Google Scholar 

  • Gautam, S. (2020a). COVID-19: Air pollution remains low as people stay at home. Air Quality, Atmosphere and Health, 13, 853–857. https://doi.org/10.1007/s11869-020-00842-6

    Article  CAS  Google Scholar 

  • Gautam, S. (2020b). The Influence of COVID-19 on Air Quality in India: A Boon or Inutile. Bulletin of Environment Contamination and Toxicology, 104, 724–726. https://doi.org/10.1007/s00128-020-02877-y

    Article  CAS  Google Scholar 

  • Gautam, S., & Hens, L. (2022). Omikron: Where do we go in a sustainability context? Environment, Development and Sustainability, 24, 4491–4492. https://doi.org/10.1007/s10668-022-02207-8

    Article  Google Scholar 

  • Gautam, A. S., Dilwaliya, N. K., Srivastava, A., Kumar, S., Bauddh, K., Siingh, D., Shah, M. A., Singh, K., & Gautam, S. (2021a). Temporary reduction in air pollution due to anthropogenic activity switch-off during COVID-19 lockdown in northern parts of India. Environment, Development and Sustainability, 23(6), 8774–8797. https://doi.org/10.1007/s10668-020-00994-6

    Article  Google Scholar 

  • Gautam, S., Samuel, C., Gautam, A. S., et al. (2021b). Strong link between coronavirus count and bad air: A case study of India. Environment, Development and Sustainability, 23, 16632–16645. https://doi.org/10.1007/s10668-021-01366-4

    Article  Google Scholar 

  • Gautam, A. S., Kumar, S., Gautam, S., Anand, A., Kumar, R., Joshi, A., Bauddh, K., & Singh, K. (2021c). Pandemic induced lockdown as a boon to the Environment: Trends in air pollution concentration across India. Asia-Pacific Journal of Atmospheric Sciences. https://doi.org/10.1007/s13143-021-00232-7

    Article  Google Scholar 

  • Ghude, S. D., Chate, D. M., Jena, C., Beig, G., Kumar, R., Barth, M. C., ... & Pithani, P. (2016). Premature mortality in India due to PM2. 5 and ozone exposure. Geophysical Research Letters, 43(9), 4650–4658.

  • Gurjar, B. R., Ravindra, K., & Nagpure, A. S. (2016). Air pollution trends over Indian megacities and their local-to-global implications. Atmospheric Environment, 142, 475–495.

    Article  CAS  Google Scholar 

  • Hansen, C. A., Barnett, A. G., Jalaludin, B. B., & Morgan, G. G. (2009). Ambient air pollution and birth defects in Brisbane, Australia. Plos One, 4(4), e5408.

    Article  Google Scholar 

  • Hari, M., Sahu, R. K., Tyagi, B., & Kaushik, R. (2021). Reviewing the crop residual burning and aerosol variations during the COVID-19 pandemic hit year 2020 over North India. Pollutants, 1(3), 127–140.

    Article  Google Scholar 

  • Joshi, S. K., Gupta, S., Sinha, R., Densmore, A. L., Rai, S. P., Shekhar, S., ... & van Dijk, W. M. (2021). Strongly heterogeneous patterns of groundwater depletion in Northwestern India. Journal of Hydrology, 598, 126492.

  • Kerimray, A., Baimatova, N., Ibragimova, O. P., Bukenov, B., Kenessov, B., Plotitsyn, P., & Karaca, F. (2020). Assessing air quality changes in large cities during COVID-19 lockdowns: The impacts of traffic-free urban conditions in Almaty, Kazakhstan. Science of the Total Environ, 730, 139179. https://doi.org/10.1016/J.SCITOTENV.2020.139179

    Article  CAS  Google Scholar 

  • Kumar, P., Jain, S., Gurjar, B. R., Sharma, P., Khare, M., Morawska, L., & Britter, R. (2013). New directions: Can a “blue sky” return to Indian megacities? Atmospheric Environment, 71, 198–201.

    Article  CAS  Google Scholar 

  • Kumar, A., Singh, D., Singh, B. P., Singh, M., Anandam, K., Kumar, K., & Jain, V. K. (2015a). Spatial and temporal variability of surface ozone and nitrogen oxides in urban and rural ambient air of Delhi-NCR, India. Air Quality, Atmosphere and Health, 8, 391–399.

    Article  Google Scholar 

  • Kumar, P., Khare, M., Harrison, R. M., Bloss, W. J., Lewis, A., Coe, H., & Morawska, L. (2015b). New directions: Air pollution challenges for developing megacities like Delhi. Atmospheric Environment, 122, 657–661.

    Article  CAS  Google Scholar 

  • Kumar, R. P., Samuel, C., Raju, S. R., et al. (2022). Air pollution in five Indian megacities during the Christmas and New Year celebration amidst COVID-19 pandemic. Stochastic Environmental Research and Risk Assessment, 36, 3653–3683. https://doi.org/10.1007/s00477-022-02214-1

    Article  Google Scholar 

  • Kumari, P., & Toshniwal, D. (2020). Impact of lockdown measures during COVID-19 on air quality– A case study of India. International Journal of Environmental Health Research, 00(00), 1–8. https://doi.org/10.1080/09603123.2020.1778646

    Article  CAS  Google Scholar 

  • Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., & Pozzer, A. (2015). The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature, 525(7569), 367–371.

    Article  CAS  Google Scholar 

  • Li, Q., Miao, Y., Zeng, X., Tarimo, C. S., Wu, C.,... Wu, J. (2020). Prevalence and factors for anxiety during the coronavirus disease 2019 (COVID-19) epidemic among the teachers in China. Journal of Affective Disorders, 277, 153–158. https://doi.org/10.1016/j.jad.2020.08.017

  • Li, X., Wang, F., Al-Razgan, M., Mahrous Awwad, E., Zilola Abduvaxitovna, S., Li, Z.,... Li, J. (2023). Race to environmental sustainability: Can structural change, economic expansion and natural resource consumption effect environmental sustainability? A novel dynamic ARDL simulations approach. Resources Policy, 86, 104044. https://doi.org/10.1016/j.resourpol.2023.104044

  • Mahato, S., Pal, S., & Ghosh, K. G. (2020). Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India. Science of the Total Environment, 730, 139086. https://doi.org/10.1016/j.scitotenv.2020.139086

    Article  CAS  Google Scholar 

  • Nagpure, A. S., Ramaswami, A., & Russell, A. (2015). Characterizing the spatial and temporal patterns of open burning of municipal solid waste (MSW) in Indian cities. Environmental Science & Technology, 49(21), 12904–12912.

    Article  CAS  Google Scholar 

  • Nair, V. S., Moorthy, K. K., Alappattu, D. P., Kunhikrishnan, P. K., George, S., Nair, P. R., Babu, S. S., Abish, B., Satheesh, S. K., Tripathi, S. N., Niranjan, K., Madhavan, B. L., Srikant, V., Dutt, C. B. S., Badarinath, K. V. S., & Reddy, R. R. (2007). Wintertime aerosol characteristics over the Indo-Gangetic Plain (IGP): Impacts of local boundary layer processes and long-range transport. Journal of Geophysical Research: Atmospheres, 112(D13), 13205. https://doi.org/10.1029/2006JD008099

    Article  CAS  Google Scholar 

  • Pagano, P., De Zaiacomo, T., Scarcella, E., Bruni, S., & Calamosca, M. (1996). Mutagenic activity of total and particle-sized fractions of urban particulate matter. Environmental Science & Technology, 30(12), 3512–3516.

    Article  CAS  Google Scholar 

  • Patz, J. A., Gibbs, H. K., Foley, J. A., Rogers, J. V., & Smith, K. R. (2007). Climate change and global health: Quantifying a growing ethical crisis. Eco Health, 4, 397–405.

    Google Scholar 

  • Peng, F., & Zou, B. A. (2012). GIS -based environmental justice analysis of ambient air pollution: A comparison between urban and rural areas. Advanced Materials Research, 610–613, 3679. https://doi.org/10.4028/www.scientific.net/AMR.610-613.3676(2012)

    Article  Google Scholar 

  • Prabhu, V., Soni, A., Madhwal, S., Gupta, A., Sundriyal, S., Shridhar, V., Sreekanth, V., & Mahapatra, P. S. (2020). Black carbon and biomass burning associated high pollution episodes observed at Doon valley in the foothills of the Himalayas. Atmospheric Research, 243, 105001. https://doi.org/10.1016/J.ATMOSRES.2020.105001

    Article  CAS  Google Scholar 

  • Pradhan, S. S., & Panigrahi, S. (2023). Delhi air quality index forecasting using statistical and machine learning models. In AIP Conference Proceedings (Vol. 2705, No. 1). AIP Publishing.

  • Sass, V., Kravitz-Wirtz, N., Karceski, S. M., Hajat, A., Crowder, K., & Takeuchi, D. (2017). The effects of air pollution on individual psychological distress. Health & Place, 48, 72–79.

    Article  Google Scholar 

  • Selvadass, S., Paul, J. J., Bella Mary I, T., et al. (2022). IoT-Enabled smart mask to detect COVID19 outbreak. Health and Technology, 12, 1025–1036. https://doi.org/10.1007/s12553-022-00695-2

    Article  Google Scholar 

  • Sethi, J. K., & Mittal, M. (2020). Monitoring the impact of air quality on the COVID-19 fatalities in Delhi, India: Using machine learning techniques. Disaster Medicine and Public Health Preparedness, 16(2), 604–611. https://doi.org/10.1017/dmp.2020.372

    Article  CAS  Google Scholar 

  • Shaik, D. S., Kant, Y., Mitra, D., Singh, A., Chandola, H. C., Sateesh, M., Babu, S. S., & Chauhan, P. (2019). Impact of biomass burning on regional aerosol optical properties: A case study over northern India. Journal of Environmental Management, 244, 328–343. https://doi.org/10.1016/J.JENVMAN.2019.04.025

    Article  Google Scholar 

  • Sharma, P., Sharma, P., Jain, S., & Kumar, P. (2013). An integrated statistical approach for evaluating the exceedence of criteria pollutants in the ambient air of megacity Delhi. Atmospheric Environment, 70, 7–17.

    Article  CAS  Google Scholar 

  • Singh, V., Biswal, A., Kesarkar, A. P., Mor, S., & Ravindra, K. (2020). High resolution vehicular PM10 emissions over megacity Delhi: Relative contributions of exhaust and non-exhaust sources. Sci of the Total Environ, 699, 134273.

    Article  CAS  Google Scholar 

  • Srivastava, S., Kumar, A., Bauddh, K., Gautam, A. S., & Kumar, S. (2020). 21-Day Lockdown in India Dramatically Reduced Air Pollution Indices in Lucknow and New Delhi, India. Bulletin of Environmental Contamination and Toxicology, 105(1), 9–17. https://doi.org/10.1007/s00128-020-02895-w

    Article  CAS  Google Scholar 

  • Tiwari, & Colls, J. (2010). Air pollution: Measurement, modelling & mitigation (3rd ed.). Routledge Taylor & Francis Group.

    Google Scholar 

  • World Health Organization (WHO), 2016 - global urban ambient air pollution database (Update 2016). https://www.who.int/data/gho/data/themes/air-pollution/who-air-qualitydatabase/2016#:~:text=Air%20quality%20database%3A%20Update%202016&text=According%20to%20the%20latest%20urban,that%20percentage%20decreases%20to%2056%25.

  • Xu, X., Qin, N., Zhao, W., Tian, Q., Si, Q., Wu, W., ... & Duan, X. (2022). A three-dimensional LUR framework for PM2. 5 exposure assessment based on mobile unmanned aerial vehicle monitoring. Environmental Pollution, 301, 118997.

  • Yin, L., Wang, L., Huang, W., Liu, S., Yang, B.,... Zheng, W. (2021). Spatiotemporal analysis of Haze in Beijing based on the multi-convolution model. Atmosphere, 12(11), 1408. https://doi.org/10.3390/atmos12111408

  • Yin, L., Wang, L., Zheng, W., Ge, L., Tian, J., Liu, Y.,... Liu, S. (2022). Evaluation of empirical atmospheric models using Swarm-C satellite data. Atmosphere, 13(2), 294. https://doi.org/10.3390/atmos13020294

  • Zhou, F., Yang, J., Wen, G., Ma, Y., Pan, H., Geng, H., ... & Xu, C. (2022). Estimating spatio-temporal variability of aerosol pollution in Yunnan Province, China. Atmospheric Pollution Research, 13(6), 101450.

Download references

Acknowledgements

The authors are thankful to the CPCB New Delhi, NETRA New Delhi and Karunya Institute of Technology and Sciences, for their guidance and unstinted support for this study.

Funding

None.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study's conception and design. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sneha Gautam.

Ethics declarations

Ethical Approval

Not applicable.

Consent to Participate

Not applicable.

Consent to Publish (Missing)

Not applicable.

Competing Interests

This study was not financially supported by any public or private institution. Moreover, the authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agarwal, S., Praveen, G., Gautam, A.S. et al. Unveiling the Surge: Exploring Elevated Air Pollution Amidst the COVID-19 Era (2019–2020) through Spatial Dynamics and Temporal Analysis in Delhi. Water Air Soil Pollut 234, 756 (2023). https://doi.org/10.1007/s11270-023-06766-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11270-023-06766-y

Keywords

Navigation