Characterization of regional cold-hydrothermal inflows enriched in arsenic and associated trace-elements in the southern part of the Duero Basin (Spain), by multivariate statistical analysis

Sci Total Environ. 2017 Sep 1:593-594:211-226. doi: 10.1016/j.scitotenv.2017.03.071. Epub 2017 Mar 24.

Abstract

Naturally occurring arsenic in groundwater exceeding the limit for potability has been reported along the southern edge of the Cenozoic Duero Basin (CDB) near its contact with the Spanish Central System (SCS). In this area, spatial variability of arsenic is high, peaking at 241μg/L. Forty-seven percent of samples collected contained arsenic above the maximum allowable concentration for drinking water (10μg/L). Correlations of As with other hydrochemical variables were investigated using multivariate statistical analysis (Hierarchical Cluster Analysis, HCA and Principal Component Analysis, PCA). It was found that As, V, Cr and pH are closely related and that there were also close correlations with temperature and Na+. The highest concentrations of arsenic and other associated Potentially Toxic Geogenic Trace Elements (PTGTE) are linked to alkaline NaHCO3 waters (pH≈9), moderate oxic conditions and temperatures of around 18°C-19°C. The most plausible hypothesis to explain the high arsenic concentrations is the contribution of deeper regional flows with a significant hydrothermal component (cold-hydrothermal waters), flowing through faults in the basement rock. Water mixing and water-rock interactions occur both in the fissured aquifer media (igneous and metasedimentary bedrock) and in the sedimentary environment of the CDB, where agricultural pollution phenomena are also active. A combination of multivariate statistical tools and hydrochemical analysis enabled the distribution pattern of dissolved As and other PTGTE in groundwaters in the study area to be interpreted, and their most likely origin to be established. This methodology could be applied to other sedimentary areas with similar characteristics and problems.

Keywords: Arsenic; Chromium; Hydrochemistry; Multivariate statistical analysis; Uranium; Vanadium.