A new graphic methodology to interpret the multivariate data analysis of hydrochemical data in orphan mine areas

作者：Marques A L^*; Ribeiro L; Roqueni N; Fernandez J J; Loredo J

来源：Journal of Geochemical Exploration, 2018, 191: 43-53.

DOI：10.1016/j.gexplo.2018.06.001

• Hydrochemistry
• River pollution
• PCA
• Mining-influenced water

Orphan mine areas around the world are sources of potential toxic elements (PTEs) in environmental compartments. The weathering of sulphide minerals plays an important role in PTEs' fate, especially in humid climates. Orphan metal mines in Asturias are principal sources of water metal(oid) pollution in small watersheds. Several abandoned mercury mines were found in the upper Nalon Catchment. Small mining-impacted watersheds exhibit significant metal(oid) pollution, especially arsenic (As), from the seepage of mine waste and metallurgical slug dumps. Low flow and high metal(oid) pollution are characteristic of small mining-impacted watersheds, in contrast to high flow and low metal(oid) s content in principal streams. The systematic monitoring of surface water across watersheds showed that mine-influenced water (MIW) was found in several micro basins in the study area. Circumneutral water, calcium sulphate type, predominant in mine-polluted areas did not generate social alarm by its non-acid character, even presenting high concentrations of metal(oid) s. Multivariate data analysis of the surface water dataset was conducted to delimitate polluted waters and to reduce it to the most important parameters, as hydrochemical factor (defined by relation of As, Pb, Zn, SO4, ... vs OD and pH) or base ion-exchange water. A new graphic representation for principal components from multivariate analysis is defined to explain water quality evolution using the concept of multivariate facies, which is a visual way of PCA interpretation.

• 出版日期2018-8