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Impact of meteorological parameters on soil radon at Kolkata, India: investigation using machine learning techniques

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Abstract

The daily soil radon activity has been measured continuously over a year with BARASOL BMC2 probe at a measuring site of Jadavpur University Campus in Kolkata, India. The dependency of soil radon activity with different atmospheric parameters such as soil temperature, soil pressure, humidity, air temperature, and rainfall has been also analyzed. The whole study period is divided in four seasons as proposed by the Indian Meteorological Department (IMD). Minimum soil radon level has been observed during the winter season (December–February). On the other hand, higher soil radon level has been observed both for summer and monsoon. Except soil pressure, all other variables have shown positive correlation with soil radon activity. Among five variables, soil temperature has been the most significant variable in terms of correlation with soil radon level whereas maximum humidity has been the least significant correlated variable. It has been observed that considerable reduction of soil radon level occurred after four heavy rainfall events during the study period. The combined effect of these multi-parameters on soil radon gas has been evaluated using machine learning methods like principal component regression (PCR), support vector regression (SVR), random forest regression (RF), and gradient boosting machine (GBM). In terms of performances, RF and GBM have performed much better than SVR and PCR. More robust and consistent results have been obtained for GBM during both training and testing periods.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors are grateful to Dr. Sunando Kumar Patra for his valuable opinions about machine learning techniques. Author Javed Akhter would like to thank University Grants Commission (UGC), India for sponsoring him through the Dr. D.S. Kothari Post-Doctoral Fellowship Scheme.

Funding

The financial support has been given by University Grants Commission (UGC), India, for to purchasing the instrument for this present study through the UPE-II program and the Jadavpur University (Physics department) provided all kinds of help during the measurement period.

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Authors and Affiliations

  1. Nuclear and Particle Physics Research Centre, Department of Physics, Jadavpur University, Kolkata, 700032, West Bengal, India

    Arindam Kumar Naskar, Mahasin Gazi, Mitali Mondal & Argha Deb

  2. School of Studies in Environmental Radiation and Archaeological Sciences, Jadavpur University, Kolkata, 700032, West Bengal, India

    Arindam Kumar Naskar, Mahasin Gazi, Mitali Mondal & Argha Deb

  3. Department of Physics, Bangabasi Evening College, Kolkata, 700009, West Bengal, India

    Arindam Kumar Naskar

  4. Department of Atmospheric Sciences, University of Calcutta, 51/2 Hazra Road, Kolkata, 700019, India

    Javed Akhter

  5. Apollo Multispeciality Hospitals, 58 Canal Circular Road, Kolkata, 700054, India

    Mahasin Gazi

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  1. Arindam Kumar Naskar
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  2. Javed Akhter
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Contributions

All the authors contributed to the study conception and design. Material preparation and data collection were performed by Arindam Kumar Naskar, and data analysis was performed by Arindam Kumar Naskar and Javed Akhter. The first draft of the manuscript was written by Arindam Kumar Naskar and Javed Akhter, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Argha Deb.

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Naskar, A.K., Akhter, J., Gazi, M. et al. Impact of meteorological parameters on soil radon at Kolkata, India: investigation using machine learning techniques. Environ Sci Pollut Res 30, 105374–105386 (2023). https://doi.org/10.1007/s11356-023-29769-y

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