Skip to main content
SpringerLink
Log in

Five-Year Fine Particulate Matter Assessment over a Western Indian Megacity

  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

The variability of PM2.5 concentrations obtained from the air quality monitoring stations (AQMS) established at six different environments of the Pune Metropolitan Region (PMR), situated in the western part of India, is analyzed for the period 2014–2018. The PM2.5 concentrations showed an increasing trend at almost all locations within the city during the 5 years. Significant features observed were that the green/background location showed a declining trend in PM2.5 concentrations. However, the city's industrial area indicated an increase in PM2.5 concentrations over the years. The seasonal bivariate plot of PM2.5 showed that the winter season has the highest concentration, and also at low wind speeds a high concentration was observed, indicative of the local sources. Concentrated weighted trajectory analysis indicated that regional sources due to long-range transport also played a role in the PM2.5 mass concentration. The wavelet power spectrum of PM2.5 showed 2–4 day oscillations and 30–50 day oscillations associated with Madden-Julian oscillations.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data Availability

Data can be made available on request.

References

  • Anand, V., Korhale, N., Rathod, A., & Beig, G. (2019). On processes controlling fine particulate matters in four Indian megacities. Environmental Pollution. https://doi.org/10.1016/j.envpol.2019.113026

    Article  Google Scholar 

  • Beegum, S. N., Moorthy, K. K., Babu, S. S., Reddy, R., & Gopal, K. R. (2009). Large scale modulations of spectral aerosol optical depths by atmospheric planetary waves. Geophysical Research Letters, 36, 1–5. https://doi.org/10.1029/2008GL036509

    Article  Google Scholar 

  • Beig, G., Chate, D. M., Sahu, S. K., Parkhi, N. S., Srinivas, R., Ali, K., Ghude, S. D., Yadav, S., & Trimbake, H. K. (2015). System of Air Quality Forecasting and Research (SAFAR- INDIA). GAW Report No. 217. World Meteorological Organization Global Atmosphere Watch.

    Google Scholar 

  • Beig, G., Sahu, S. K., Anand, V., Bano, S., Maji, S., Rathod, A., Korhale, N., Sobhana, S. B., Parkhi, N., Mangaraj, P., Srinivas, R., Peshin, S. K., Singh, S., Shinde, R., & Trimbake, H. K. (2021). India’s Maiden air quality forecasting framework for megacities of divergent environments: The SAFAR-project. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2021.105204

    Article  Google Scholar 

  • Bisht, D. S., Dumka, U. C., Kaskaoutis, D. G., Pipal, A. S., Srivastava, A. K., Soni, V. K., Attri, S. D., Sateesh, M., & Tiwari, S. (2015). Carbonaceous aerosols and pollutants over Delhi urban environment: Temporal evolution, source apportionment and radiative forcing. Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2015.03.083

    Article  Google Scholar 

  • Calvo, A. I., Alves, C., Castro, A., Pont, V., Vicente, A. M., & Fraile, R. (2013). Research on aerosol sources and chemical composition: Past, current and emerging issues. Atmospheric Research, 120–121, 1–28. https://doi.org/10.1016/j.atmosres.2012.09.021

    Article  Google Scholar 

  • Carslaw, D. C., & Beevers, S. D. (2013). Characterising and understanding emission sources using bivariate polar plots and k-means clustering. Environmental Modelling and Software, 40, 325–329. https://doi.org/10.1016/j.envsoft.2012.09.005

    Article  Google Scholar 

  • Chen, J., Zhu, L., Fan, P., Tian, L., & Lafortezza, R. (2016). Do green spaces affect the spatiotemporal changes of PM2.5 in Nanjing? Ecological Processes, 5, 10. https://doi.org/10.1186/s13717-016-0052-6

    Article  Google Scholar 

  • Chen, X., Yin, L., Fan, Y., Song, L., Ji, T., Liu, Y., Tian, J., & Zheng, W. (2020). Temporal evolution characteristics of PM2.5 concentration based on continuous wavelet transform. Science of the Total Environment, 699, 134244. https://doi.org/10.1016/j.scitotenv.2019.134244

    Article  Google Scholar 

  • Chowdhury, S., & Dey, S. (2016). Cause-specific premature death from ambient PM2.5 exposure in India: Estimate adjusted for baseline mortality. Environment International, 91, 283–290. https://doi.org/10.1016/j.envint.2016.03.004

    Article  Google Scholar 

  • Collineau, S., & Brunet, Y. (1993). Detection of turbulent coherent motions in a for- estcanopy Part 2: Time-scales and conditional averages. Boundary Layer, 66, 49–73.

    Article  Google Scholar 

  • Fuzzi, S., Baltensperger, U., Carslaw, K., Decesari, S., Denier Van Der Gon, H., Facchini, M. C., Fowler, D., Koren, I., Langford, B., Lohmann, U., Nemitz, E., Pandis, S., Riipinen, I., Rudich, Y., Schaap, M., Slowik, J. G., Spracklen, D. V., Vignati, E., Wild, M., Williams, M., et al. (2015). Particulate matter, air quality and climate: Lessons learned and future needs. Atmospheric Chemistry and Physics, 15, 8217–8299. https://doi.org/10.5194/acp-15-8217-2015

    Article  Google Scholar 

  • Gama, C., Monteiro, A., Pio, C., Miranda, A. I., Baldasano, J. M., & Tchepel, O. (2018). Temporal patterns and trends of particulate matter over Portugal: A long-term analysis of background concentrations. Air Quality, Atmosphere & Health, 11, 397–407. https://doi.org/10.1007/s11869-018-0546-8

    Article  Google Scholar 

  • Guttikunda, S. K., Goel, R., & Pant, P. (2014). Nature of air pollution, emission sources, and management in the Indian cities. Atmospheric Environment. https://doi.org/10.1016/j.atmosenv.2014.07.006

    Article  Google Scholar 

  • Jerrett, M., Turner, M. C., Beckerman, B. S., Pope, C. A., van Donkelaar, A., Martin, R. V., Serre, M., Crouse, D., Gapstur, S. M., Krewski, D., Diver, W. R., Coogan, P. F., Thurston, G. D., & Burnett, R. T. (2017). Comparing the health effects of ambient particulate matter estimated using ground-based versus remote sensing exposure estimates. Environmental Health Perspectives, 125, 552–559. https://doi.org/10.1289/EHP575

    Article  Google Scholar 

  • Li, C., Dai, Z., Liu, X., & Wu, P. (2020). Transport pathways and potential source region contributions of PM.25 in weifang: Seasonal variations. Applied Sciences. https://doi.org/10.3390/APP10082835

    Article  Google Scholar 

  • Mahapatra, P. S., Sinha, P. R., Boopathy, R., Das, T., Mohanty, S., Sahu, S. C., & Gurjar, B. R. (2018). Seasonal progression of atmospheric particulate matter over an urban coastal region in peninsular India: Role of local meteorology and long-range transport. Atmospheric Research, 199, 145–158. https://doi.org/10.1016/j.atmosres.2017.09.001

    Article  Google Scholar 

  • Mallik, C. (2019). Anthropogenic sources of air pollution. In P. Saxena & V. Naik (Eds.), Air pollut. sources, impacts control (pp. 6–25). CAB International. https://doi.org/10.1079/9781786393890.0006

    Chapter  Google Scholar 

  • Mukherjee, A., & Agrawal, M. (2017). World air particulate matter: Sources, distribution and health effects. Environmental Chemistry Letters, 15, 283–309. https://doi.org/10.1007/s10311-017-0611-9

    Article  Google Scholar 

  • Pal, S., & Devara, P. C. S. (2012). A wavelet-based spectral analysis of long-term time series of optical properties of aerosols obtained by lidar and radiometer measurements over an urban station in Western India. Journal of Atmospheric and Solar-Terrestrial Physics, 84–85, 75–87. https://doi.org/10.1016/j.jastp.2012.05.014

    Article  Google Scholar 

  • Panicker, A. S., & Shaima, N. (2021). Aerosol oscillations over different emission regions in India. Pure & Applied Geophysics, 178(2021), 4097–4105. https://doi.org/10.1007/s00024-021-02833-9

    Article  Google Scholar 

  • Pant, P., Habib, G., Marshall, J. D., & Peltier, R. E. (2017). PM2.5exposure in highly polluted cities: A case study from New Delhi, India. Environmental Research, 156, 167–174. https://doi.org/10.1016/j.envres.2017.03.024

    Article  Google Scholar 

  • Pant, P., Lal, R. M., Guttikunda, S. K., Russell, A. G., Nagpure, A. S., Ramaswami, A., & Peltier, R. E. (2019). Monitoring particulate matter in India: Recent trends and future outlook. Air Quality, Atmosphere & Health, 12, 45–58. https://doi.org/10.1007/s11869-018-0629-6

    Article  Google Scholar 

  • Ramachandran, S., Ghosh, S., Verma, A., & Panigrahi, P. K. (2013). Multiscale periodicities in aerosol optical depth over India. Environmental Research Letters. https://doi.org/10.1088/1748-9326/8/1/014034

    Article  Google Scholar 

  • Sandeep, K., Panicker, A. S., Gautam, A. S., Safai, P. D., Beig, G., Nainwal, H. C., Bisht, D. S., & Das, S. (2021). Observations of black carbon and albedo over a Central Himalayan Glacier (Satopanth): Preliminary results. Journal of Atmospheric and Solar-Terrestrial Physics. https://doi.org/10.1016/j.jastp.2021.105580

    Article  Google Scholar 

  • Srinivas, R., Panicker, A. S., Parkhi, N. S., Peshin, S. K., & Beig, G. (2016). Sensitivity of online coupled model to extreme pollution event over a mega city Delhi. Atmospheric Pollution Research, 7, 25–30. https://doi.org/10.1016/j.apr.2015.07.001

    Article  Google Scholar 

  • Sumesh, R. K., Rajeevan, B. K., Resmi, A. B. E., & Unnikrishnan, K. B. C. (2017). Particulate matter concentrations in the Southern Tip of India: temporal variation meteorological influences, and source identification CAIPEEX View Project Climatologies, Agrometeorology and Image Processing Techniques View Project Particulate Matter Concentrations in the Southern Tip of India: Temporal Variation, Meteorological Influences, and Source Identification. Earth Systems and Environment. https://doi.org/10.1007/s41748-017-0015-9

    Article  Google Scholar 

  • Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological society, 79(1), 61–78.

    Article  Google Scholar 

  • Tyagi, B., Singh, J., & Beig, G. (2020). Seasonal progression of surface ozone and NOx concentrations over three tropical stations in North-East India. Environmental Pollution, 258, 113662. https://doi.org/10.1016/j.envpol.2019.113662

    Article  Google Scholar 

  • Wang, Y. Q., Zhang, X. Y., & Draxler, R. R. (2009). TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data. Environmental Modelling and Software, 24, 938–939. https://doi.org/10.1016/j.envsoft.2009.01.004

    Article  Google Scholar 

  • WHO. (2020). Ambient (outdoor) air pollution in cities database, report. Geneva: World Health Organization.

    Google Scholar 

  • Wood, S. N. (2006). Generalized additive models. An introduction with R (Vol. 1). Chapman and Hall/CRC.

    Book  Google Scholar 

  • Zeri, M., Carvalho, V. S. B., Cunha-Zeri, G., Oliveira-Junior, J. F., Lyra, G. B., & Freitas, E. D. (2016). Assessment of the variability of pollutants concentration over the metropolitan area of Sao Paulo, Brazil, using the wavelet transform. Atmospheric Science Letters, 17, 87–95.

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the Director, Indian Institute of Tropical Meteorology (IITM), Pune, for the encouragement and support of this work. IITM is funded by MoES, Government of India. The authors also extend thanks to SAFAR for the data generation used in this manuscript.

Funding

IITM is funded by MoES, Government of India.

Author information

Authors and Affiliations

  1. Indian Institute of Tropical Meteorology, Ministry of Earth Sciences (MoES), Pashan, Pune, 411008, India

    Vrinda Anand, Nikhil Korhale, Abhilash S. Panicker & B. S. Murthy

  2. Savitribai Phule Pune University, Pune, India

    Vrinda Anand & Nikhil Korhale

  3. National Institute of Advanced Studies (NIAS), Indian Institute of Science (IISc) Campus, Bangalore, India

    Gufran Beig

Authors
  1. Vrinda Anand
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nikhil Korhale
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abhilash S. Panicker
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gufran Beig
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. B. S. Murthy
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

VA carried out the data analysis and writing the original draft of the manuscript. NK carried out the data analysis. ASP edited, reviewed and finalized the manuscript and conceptualized the manuscript. GB supervised the whole study and administered the project.

Corresponding author

Correspondence to Vrinda Anand.

Ethics declarations

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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

Anand, V., Korhale, N., Panicker, A.S. et al. Five-Year Fine Particulate Matter Assessment over a Western Indian Megacity. Pure Appl. Geophys. 180, 1099–1111 (2023). https://doi.org/10.1007/s00024-023-03235-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-023-03235-9

Keywords

Search

Navigation