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Modeling pH changes and electrical conductivity in surface water as a result of mining activities

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Category: Content №1 2024

Last Updated on 29 February 2024

Published on 30 November -0001

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Authors:

K.C.Aluwong*, orcid.org/0009-0001-9426-540X, Department of Mining Engineering, University of Jos, Plateau, Nigeria; School of Materials and Mineral Resources Engineering, Universiti Sains Malaysia, Parit Buntar, Malaysia

M.H.M.Hashim*, orcid.org/0000-0003-0263-7446, School of Materials and Mineral Resources Engineering, Universiti Sains Malaysia, Parit Buntar, Malaysia

S.Ismail, orcid.org/0000-0003-3080-7836, School of Materials and Mineral Resources Engineering, Universiti Sains Malaysia, Parit Buntar, Malaysia

S.A.Shehu, orcid.org/0000-0001-9022-1277, Department Civil and Mining Engineering, Confluence University of Science and Technology, Osara, Nigeria

^* Corresponding authors e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (1): 122 - 129

https://doi.org/10.33271/nvngu/2024-1/122

Abstract:

Purpose. To develop comprehensive models for predicting the pH and electrical conductivity of surface water in Maiganga coal mine and environs affected by mining activities.

Methodology. The research utilizes a combination of in-situ measurement, laboratory analysis, modeling technique using Ansys Workbench and Linear Regression for predicting the content of pollutants. In-situ measurement/data collection in the upstream and downstream were carried out to evaluate the potential impact of mining activities on surface and ground water quality. Electrical conductivity and pH were measured on the samples that were collected using Oakton 5/6 pH meter and TDS/EC meter.

Findings. According to the results, the regression statistics model of pH and electrical conductivity (EC) shows that the predicted values have a pH range of 4.7–7.05 and a mean pH value of 5.5. In contrast, while the EC ranges from 454.52 to 2,720.68 s/cm (EC) with a mean value of 905 µs/cm of the downstream flow which is completely dependent on the mine inlet (pH-in and EC-in). The findings show a direct correlation between surface water pH, electrical conductivity, and mining activities in the Maiganga coal mine area and their detrimental effects on the ecosystem and water quality.

Originality. The results were obtained directly from the mine site during field visit and can be compared to data from active coal mine sites.

Practical value. The detrimental effect of the results of mining activities can be controlled if monitoring sensors are introduced at mines’ effluent outlet to alert the mine management of possible danger in real time.

Keywords: Maiganga coal mine, pH, electrical conductivity, predictive modeling, surface water, environmental monitoring

References.

1. Lizama-Allende, K., Rámila, C. D. P., Leiva, E., Guerra, P., & Ayala, J. (2022). Evaluation of surface water quality in basins of the Chilean Altiplano-Puna and implications for water treatment and monitoring. Environmental Monitoring and Assessment, 194(12), 926. https://doi.org/10.1007/s10661-022-10628-1.

2. Stephen Northey, Gavin Mudd, Timothy Werner, Nawshad Haque & Mohan Yellishetty (2018). Sustainable water management and improved corporate reporting in mining. Water Resources and Industry, 21, 1-21. https://doi.org/10.1016/j.wri.2018.100104.

3. Obiadi, I. I., Obiadi, C. M., Akudinobi, B. E. B., Maduewesi, U. V., & Ezim, E. O. (2016). Effects of coal mining on the water resources in the communities hosting the Iva Valley and Okpara Coal Mines in Enugu State, Southeast Nigeria. Sustainable Water Resources Management, (2), 207-216. https://doi.org/10.1007/s40899-016-0061-8.

4. Nienie, A. B., Sivalingam, P., Laffite, A., Ngelinkoto, P., Otamonga, J. P., Matand, A., & Poté, J. (2017). Seasonal variability of water quality by physicochemical indexes and traceable metals in suburban area in Kikwit, Democratic Republic of the Congo. International Soil and Water Conservation Research, 5(2), 158-165. https://doi.org/10.1016/j.iswcr.2017.04.004.

5. Zaghloul, A., Saber, M., Gadow, S., & Awad, F. (2020). Biological indicators for pollution detection in terrestrial and aquatic ecosystems. Bulletin of the National Research Centre, 44(1), 1-11. https://doi.org/10.1186/s42269-020-00385-x.

6. Mathur, A. (2016). Conductivity: Water Quality Assessment. International Journal of Engineering Research & Technology, 3(3), 1-3. https://doi.org/10.17577/IJERTCONV3IS03028.

7. Suleiman, M. A., Owolabi, T. O., Adeyemo, H. B., & Olatunji, S. O. (2018). Modeling of autoignition temperature of organic energetic compounds using hybrid intelligent method. Process Safety and Environmental Protection, (120), 79-86. https://doi.org/10.1016/j.psep.2018.08.031.

8. Zhu, G., Wu, X., Ge, J., Liu, F., Zhao, W., & Wu, C. (2020). Influence of mining activities on groundwater hydrochemistry and heavy metal migration using a self-organizing map (SOM). Journal of Cleaner Production, (257), 120664. https://doi.org/10.1016/j.jclepro.2020.120664.

9. Akhtar, N., Syakir Ishak, M. I., Bhawani, S. A., & Umar, K. (2021). Various natural and anthropogenic factors responsible for water quality degradation: A review. Water, 13(19), 2660. https://doi.org/10.3390/w13192660.

10. Onsachi, J. M., Dibal, H. U., & Daku, S. S. (2016). The Maiganga Coal Mine Drainage and Its Effects on Water Quality, North Eastern Nigeria. International Journal of Emerging Trends in Science and Technology, 3(7), 4324-4333.

11. Lacorte, S., Bono-Blay, F., & Cortina-Puig, M. (2012). Sample Homogenization. Comprehensive Sampling and Sample Preparation, 65-84. https://doi.org/10.1016/b978-0-12-381373-2.00006-5.

12. El Hosry, L., Sok, N., Richa, R., Al Mashtoub, L., Cayot, P., & Bou-Maroun, E. (2023). Sample preparation and analytical techniques in the determination of trace elements in food: A review. Foods, 12(4), 895. https://doi.org/10.3390/foods12040895.

13. Kur, A., Alaanyi, A. T., & Awuhe, S. T. (2019). Determination of quality of water used by students of college of education, Katsina-Ala through physical and electro-chemical parameters. Science World Journal, 14(1), 78-83.

14. ANSYS Fluent (2018). ANSYS Fluent Tutorial Guide 18. ANSYS Fluent Tutorial Guide, 18, (15317), 724-746.

15. Magdalinos, T. (2022). Least squares and IVX limit theory in systems of predictive regressions with GARCH innovations. Econometric Theory, 38(5), 875-912. https://doi.org/10.1017/S0266466621000086.

16. Ewing, R., & Park, K. (2020). Basic quantitative research methods for urban planners. Routledge. https://doi.org/10.4324/9780429325021.

17. Chicco, D., Warrens, M. J., & Jurman, G. (2021). The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. PeerJ Computer Science, 7, e623. https://doi.org/10.7717/peerj-cs.623.

18. WHO (2020). World Health Statistics. World Health, 1-177.

19. Son (2015). Nigerian Standard for Drinking Water Quality. Standards Organisation of Nigeria.

20. WHO (2002). Guidelines for drinking-water quality. World Health Organization.

21. Daud, M. K., Nafees, M., Ali, S., Rizwan, M., Bajwa, R. A., Shakoor, M. B., & Zhu, S. J. (2017). Drinking water quality status and contamination in Pakistan. BioMed research international, (2017), 7908183. https://doi.org/10.1155/2017/7908183.

22. Shrestha, I. (2018). Influence of demographic factors on job satisfaction of financial institutions workforce of Nepal. Journal of Business and Management, 5, 74-79.

23. Gyawali, A. (2017). Impact of employee participation on job satisfaction, employee fairness perception and organizational commitment: A case of Nepalese commercial banks. Saptagandaki Journal, (8), 1-13. https://doi.org/10.3126/sj.v8i0.18457.

24. Tharu, R. P. (2019). Multiple regression model fitted for job satisfaction of employees working in saving and cooperative organization. International Journal of Statistics and Applied Mathematics, 4(4), 43-49. https://doi.org/10.22271/maths.

25. Msimbira, L. A., & Smith, D. L. (2020). The roles of plant growth promoting microbes in enhancing plant tolerance to acidity and alkalinity stresses. Frontiers in Sustainable Food Systems, (4), 106. https://doi.org/10.3389/fsufs.2020.00106.

26. Aikman, P. C., Henning, P. H., Humphries, D. J., & Horn, C. H. (2011). Rumen pH and fermentation characteristics in dairy cows supplemented with Megasphaera elsdenii NCIMB 41125 in early lactation. Journal of dairy science, 94(6), 2840-2849. https://doi.org/10.3168/jds.2010-3783.

27. Rostern, N. T. (2017). The effects of some metals in acidified waters on aquatic organisms. Fish & Ocean Opj, 4(4), 555-645. https://doi.org/10.19080/OFOAJ.2017.04.555645.

28. Spyra, A. (2017). Acidic, neutral and alkaline forest ponds as a landscape element affecting the biodiversity of freshwater snails. The Science of Nature, (104), 1-12. https://doi.org/10.1007/s00114-017-1495-z.

29. Zaynab, M., Al-Yahyai, R., Ameen, A., Sharif, Y., Ali, L., Fatima, M., & Li, S. (2022). Health and environmental effects of heavy metals. Journal of King Saud University-Science, 34(1), 101653. https://doi.org/10.1016/j.jksus.2021.101653.

30. Weiskopf, S. R., Rubenstein, M. A., Crozier, L. G., Gaichas, S., Griffis, R., Halofsky, J. E., ..., & Whyte, K.P. (2020). Climate change effects on biodiversity, ecosystems, ecosystem services, and natural resource management in the United States. Science of the Total Environment, (733), 137782. https://doi.org/10.1016/j.scitotenv.2020.137782.

31. United Nations. Department of Economic and Social Affairs (2022). The Sustainable Development Goals: Report 2022. UN. Retrieved from https://unstats.un.org/sdgs/report/2022/The-Sustainable-Development-Goals-Report-2022.pdf.

32. Mishra, U. S., & Padhi, B. (2021). Sustaining the sustainable development goals. Economic and Poltrical Weekly, 56(34), 30-31.

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