Abstract
Oil and natural gas production has been an important economic booster in the recent past. However, unconventional methods have risen environmental health concerns. This study presents preliminary results of heavy metal concentrations in water (surface and groundwater) around oil and natural gas drilling sites in East-West Godavari districts of A.P, India. A total of 36 samples, 24 surface water (SW) and 12 groundwater (GW), were collected to evaluate the distribution of pH, EC, TDS, As, Cd, Cr, Cu, Mo, Ni, Pb, Zn, and radiogenic elements (U, Th). Results acquired were treated with principal component analysis (PCA)/factor analysis (FA), hierarchical cluster analysis (HCA), and regression coefficient analysis to identify a collective contamination source. Mean concentrations obtained for surface and groundwater were 7.60 and 7.34 for pH, 4048 and 2964 mg/L for TDS, 8.50 and 5.91 µs/cm for EC, 11.5 and 10.7 μg/L for As, 14.6 and 10.8 μg/L for Cr, 0.60 and 0.70 μg/L for Cd, 18.6 and 29.1 μg/L for Cu, 3.00 and 4.20 μg/L for Mo, 19.9 and 24.8 for Ni, 15.2 and 13.4 μg/L for Pb, 4.60 and 3.10 μg/L for Th, 1.00 and 8.30 μg/L for U, and 187 and 348 μg/L for Zn respectively. FA recognized four factors accountable for data structure elucidating 86.23% of the total variance in SW, four factors in GW explaining 91.6%, and permitted to assemble particular parameters based on collective features. As, Cd, Cu, Mo, Pb, and U were linked and well-ordered by diverse origins with related influence from anthropogenic and geogenic sources. This study describes the importance and efficacy of multivariate statistical methods for evaluation and understanding the data to get better evidence about the water quality.
Similar content being viewed by others
Data Availability
This is a new data generated out of the study.
References
Ammar, F. H., Chkir, N., Zouari, K., Hamelin, B., Deschamps, P., & Aigoun, A. (2014). Hydro-geochemical processes in the complexe terminal aquifer of southern Tunisia: An integrated investigation based on geochemical and multivariate statistical methods. Journal of African Earth Sciences, 100, 81–95. https://doi.org/10.1016/j.jafrearsci.2014.06.015
Carlon, C., Critto, A., Marcomini, A., & Nathanail, P. (2001). Risk-based characterization of the contaminated industrial site using multivariate and geostatistical tools. Environmental Pollution, 111, 417–427. https://doi.org/10.1016/S0269-7491(00)00089-0
Carter, K. E., Hakala, J. A., Hammack, R. W. (2013) Hydraulic fracturing and organic compounds-uses, disposal and challenges. SPE-165692-MS. https://doi.org/10.2118/165692-MS
Colborn, T., Kwiatkowskiwski, C., Schultz, K., & Bachran, M. (2011). Natural gas operation from a public health perspective. Human and Ecological Risk Assessment: International Journal, 17(5), 1039–1056. https://doi.org/10.1080/10807039.2011.605662
Govil, P. K., & Krishna, A. K. (2018). Soil and water contamination by potentially hazardous elements: A case history from India. Elsevier BV. https://doi.org/10.1016/B978-0-444-63763-5.00023-9
Govil, P. K., Sorlie, J. E., Sujatha, D., Krishna, A. K., Murthy, N. N., & Mohan, K. R. (2012). Assessment of heavy metal pollution in lake sediments of Katedan Industrial Development Area, Hyderabad, India. Environment and Earth Science, 66, 121–128. https://doi.org/10.1007/s12665-011-1212-8
Groundwater brochure (2013) Krishna district, West Godavari district and East Godavari district, Central Ground Water Board, Ministry of Water Resources, Southern region, Hyderabad.
Howladar, M. F., Al Numanbakth, M. A., & Faruque, M. O. (2017). An application of water quality index (WQI) and multivariate statistics to evaluate the water quality around Maddhapara Granite Mining Industrial Area, Dinajpur, Bangladesh. Environmental Systems Research, 6, 13. https://doi.org/10.1186/s40068-017-0090-9
Hussain Qaiser, M. S., Ahmad, I., Ahmad, S. R., Afzal, M., & Qayyum, A. (2019). Assessing Heavy Metal Contamination in Oil and Gas Well Drilling Waste and Soil in Pakistan. Polish Journal of Environmental Studies, 28, 785–793. https://doi.org/10.15244/pjoes/85301.
Igibah, C. E., & Tanko, J. A. (2019). Assessment of urban groundwater quality using Piper trilinear and multivariate techniques: A case study in the Abuja, North-central, Nigeria. Environmental Systems Research, 8, 14. https://doi.org/10.1186/s40068-019-0140-6
Krishna, A. K., & Mohan, K. R. (2014). Risk assessment of heavy metals and their source distribution in waters of a contaminated industrial site. Environmental Science and Pollution Research, 21, 3653–3669. https://doi.org/10.1007/s11356-013-2359-5
Liu, C. W., Lin, K. H., & Kuo, Y. M. (2003). Application of factor analysis in the assessment of groundwater quality in a Blackfoot disease area in Taiwan. Science of the Total Environment, 313, 77–89. https://doi.org/10.1016/S0048-9697(02)00683-6
McKenna, J. E., Jr. (2003). An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis. Environmental Modelling and Software, 18, 205–220. https://doi.org/10.1016/S1364-8152(02)00094-4
Mrazovac, S., & Miloradov-Vojinovi, M. (2011). Correlation of main physicochemical parameters of some groundwater in northern Serbia. Journal of Geochemical Exploration, 108, 176–218. https://doi.org/10.1016/j.gexplo.2011.01.005
Nagireddi, S. R. (2007). Distribution of iron in the surface and groundwaters of East Godavari district, Andhra Pradesh, India. Environmental Geology, 2007(52), 1455–1465. https://doi.org/10.1007/s00254-006-0584-7
Okoro, E. E., Okolie, A. G., Sanni, S. E., & Omeje, M. (2020). Toxicology of heavy metals to subsurface lithofacies and drillers during drilling of hydrocarbon wells. Scientific Reports, 10(1), 6152.
Omo-Irabor, O. O., Olobaniyi, S. B., Oduyemi, K., & Akunna, J. (2008). Surface and groundwater water quality assessment using multivariate analytical methods: A case study of the Western Niger Delta, Nigeria. Physics and Chemistry of the Earth, 33, 666–673. https://doi.org/10.1016/j.pce.2008.06.019
Pichtel, J. (2016). Oil and Gas production wastewater: Soil contamination and pollution prevention. Applied and Environmental Soil Science, Article ID 2707989, 24 pages, https://doi.org/10.1155/2016/2707989
Reghunath, R., Murthy, T. R. S., & Raghavan, B. R. (2002). The utility of multivariate statistical techniques in hydrogeochemical studies: An example from Karnataka, India. Water Research, 36, 2437–2442. https://doi.org/10.1016/S0043-1354(01)00490-0
Renato, I. S. A., Carolina, S. M., Cassio, F. B., Brisa, M. F., Nadal, M., Sierra, J., & Josep, L. D. (2018). Segura-Muñoz SI (2018) Water quality assessment of the Pardo River Basin, Brazil: A multivariate approach using limnological parameters, metal concentrations and indicator bacteria. Archives of Environmental Contamination and Toxicology, 75, 199–212. https://doi.org/10.1007/s00244-017-0493-7
Sasikaran, S., Sritharan, K., Balakumar, S., & Arasaratnam, V. (2012). Physical, chemical and microbial analysis of bottled drinking water. Ceylon Medical Journal, 57, 111–116.
Simeonov, V., Stratis, J. A., Samara, C., Zachariadis, G., Voutsa, D., Anthemidis, A., Sofoniou, M., & Kouimtzis, T. H. (2003). Assessment of the surface water quality in Northern Greece. Water Research, 37, 4119–4124. https://doi.org/10.1016/S0043-1354(03)00398-1
Singh, K. P., Malik, A., Mohan, D., & Sinha, S. (2004). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India): a case study. Water Research, 38, 3980–3992.
Shrestha, S., & Kazama, F. (2007) Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji river basin, Japan. Environmental Modelling and Software, 22(4):464–475.
SPSS® (Statistical Package for Social Studies) version 6.1, USA. (1995). Professional statistics 6.1, 385, Marija J. Norusis/SPSS Inc., Chicago.
Tokatli, C. (2013). Use of statistical methods in water quality assessment: A Case Study of Balkan Arboretum Area in Trakya University (Edirne, Turkey). Journal of Applied Biological Sciences, 7(3): 79–83. www.nobel.gen.tr
Tokatli, C., Çiçek, A., Emiroglu, O., Arslan, N., Kose, E., & Dayioglu, H. (2014). Statistical approaches to evaluate the aquatic ecosystem qualities of a significant mining area: Emet stream basin (Turkey). Environmental Earth Sciences, 71, 2185–2197. https://doi.org/10.1007/s12665-013-2624-4
Wagh, V. M., Panaskar, D. B., Varade, A. M., Mukate, S. V., Gaikwad, S. K., Pawar, R. S., Muley, A. A., & Aamalawar, M. L. (2016). Major ion chemistry and quality assessment of the groundwater resources of Nanded tehsil, a part of southeast Deccan Volcanic Province, Maharashtra, India. Environmental Earth Sciences, 75(21), 1418. https://doi.org/10.1007/s12665-016-6212-2
Vega, M., Pardo, R., Barrado, E., & Debán, L. (1998). Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research, 32, 3581–3592.
Acknowledgements
The three anonymous reviewers are profusely thanked for their constructive comments that have significantly improved the scientific quality of the manuscript. The authors are thankful to Dr. V. M. Tiwari, Director, CSIR-NGRI for his permission to publish this paper. This work was supported by the UGC-JRF fellowship, and the MLP-6406-28 (DSS) project funds were utilized to conduct fieldwork. Our sincere thanks are also to Dr. D. Srinivasa Sarma for his continuous support and encouragement. Thanks are also due to Dr. M. Satyanarayanan for extending the HR-ICP-MS analytical facility. This study forms a part of DBM’s doctoral thesis. This is CSIR-NGRI contribution No. NGRI/Lib/2022/Pub-30.
Author information
Authors and Affiliations
Contributions
D. Babu Mallesh: sample collection, preparation and data interpretation. A. Keshav Krishna: sample analysis, data interpretation, and overall monitoring and assisted in drafting and revising the manuscript. B. Dasaram: sample preparation protocols.
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Highlights
1. The present study was conducted to investigate distribution of heavy metals in water (surface and groundwater).
2. To monitor the quality of the groundwater by applying basic quality testing and the drilling activities in the study area.
3. This study describes the importance and efficacy of multivariate statistical methods for evaluation and understanding the data to get better evidence about the water quality.
4. It would also help in designing a strategy to control the backwater chemicals generated and spread of pollutants in the study environment.
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.
About this article
Cite this article
Dasari, B.M., Aradhi, K.K. & Banothu, D. Evaluation of Heavy Metal Contamination and their Distribution in Waters Around Oil and Natural Gas Drilling Sites. Water Air Soil Pollut 234, 442 (2023). https://doi.org/10.1007/s11270-023-06426-1
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11270-023-06426-1