Water Quality Assessment from an Environmental Liability Applying Grey Clustering and Harmonic Mean

Water Quality Assessment from an Environmental Liability Applying Grey Clustering and Harmonic Mean

© 2023 by IJETT Journal
Volume-71 Issue-10
Year of Publication : 2023
Author : Alexi Delgado, Juan Costa Valencia, Jhosimar Paz Salva, Antony De la cruz
DOI : 10.14445/22315381/IJETT-V71I10P226

How to Cite?

Alexi Delgado, Juan Costa Valencia, Jhosimar Paz Salva, Antony De la cruz, "Water Quality Assessment from an Environmental Liability Applying Grey Clustering and Harmonic Mean," International Journal of Engineering Trends and Technology, vol. 71, no. 10, pp. 296-304, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I10P226

AbstractThe monitoring of the quality of the mine tailings from the La Tahona mining waste dump in 2018, located east of the city of Hualgayoc, is an important issue that must be analyzed, as it still represents a severe risk to the health of the city's inhabitants. In this way, the Grey Clustering method provides an alternative to evaluate the level of contamination of the sources near the mining tailings, taking into account the monitoring data with file number 0038-2018-DSEM-CMIN, carried out by the Directorate of Environmental Supervision in Energy and Mines of the Environmental Evaluation and Oversight Agency (OEFA), analyzing seven parameters of Prati index and Environmental Quality Standard, pH, Zinc, Suspended Solids, Arsenic, Lead, Iron and Cadmium. The results showed that the monitoring points of the water bodies near the effluent to the environmental liabilities of La Tahona were classified as high risk, which means that the efforts made to remediate the mentioned liabilities by the General Directorate of Mines of the Ministry of Energy and Mines (MINEM) do not comply with the quality parameters. Finally, the results obtained may be of help to OEFA, MINEM and the authorities of the Cajamarca region of Peru in the search for the correct treatment of the tailings effluents mentioned above.

Grey clustering, Environmental liability, Water quality.


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