Constraints on Hf and Zr mobility in high-sulfidation epithermal systems: formation of kosnarite, KZr2(PO4)3, in the Chaquicocha gold deposit, Yanacocha district, Peru

Deditius, Artur P.; Utsunomiya, Satoshi; Sánchez-Alfaro, Pablo; Reich, Martín; Ewing, Rodney C.; Kesler, Stephen E.

doi:10.1007/s00126-015-0586-z

Cited by 4 publications

(1 citation statement)

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“…Yanacocha is a well-known mining district in Cajamarca, Perú, characterized by an extensive disseminated gold mineralization [1]. Therefore, the operations and processes used to obtain this metal have an important environmental impact over superficial waters like rivers, which are an important source for people, livestock and plantations [2].…”

Section: Introductionmentioning

confidence: 99%

Grey Clustering Method for Water Quality Assessment to Determine the Impact of Mining Company, Peru

Delgado¹,

Achata²,

Valdivia³

et al. 2021

IJACSA

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Mining operations have a significant impact on environment, where the quality of water is an important affected issue that need to be controlled. In that way, the Grey Clustering Method based on center-point triangular whitenization weight (CTWF), is an artificial intelligence criterion that evaluates water samples according to selected parameters, in order to realize an effective water quality assessment. In the present study, the analysis is made on the Crisnejas River Basin, by using fifteen monitoring points based on an investigation realized by the National Water Authority (ANA) in 2019, based on the Peruvian law (ECA) about water quality standards. The results reveal that almost all of the monitoring points on the Crisnejas River Basin were classified as "irrigation of vegetables unrestricted", but only one point was classified as "animal drink", which is ubicated in an urbanized area. This implies that mining discharges are being well treated by the company, but another deal is the contamination generated in towns. Further, the present study might be helpful to audit processes made by the state or companies, to justify the quality of surface waters using a more accurate methodology.

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Section: Introductionmentioning

confidence: 99%