Spatial and Temporal Characterization of Fluoride and Arsenic in the Southern Part of the Aguascalientes Valley Aquifer, Mexico
摘要
High arsenic and fluoride concentrations in water destined for human consumption sourced from groundwater is a worrying global problem, as these elements cause multiple health concerns for those who are chronically exposed to them. The Aguascalientes Valley aquifer, located in the state of Aguascalientes, Mexico is the principal source of drinking water in this semi-arid region since there are few natural superficial water sources, supplying up to 94% of the water demand for agriculture, municipal, and industrial uses. In last decades, several studies have found that the concentration of fluoride and arsenic, assumed to be of geogenic origins, surpasses drinking water limits (DWL), potentially posing a public health problem. However, these published studies have been few and far between. Therefore, this study aims to characterize and synthesize the spatial and temporal variations of the concentrations of these contaminants based on the available historical data of Aguascalientes Valley aquifer over a period of 19 years. The concentrations were mapped spatially, using Kriging interpolation between the data points at the sampling wells and generating a different map for every semester. A statistic evaluation was also carried out to determine maximum and mean concentrations during this time period. The maximum concentration of fluoride was found at 14.78 mg/L; of arsenic, 0.0955 mg/L. The mean concentration over the period was determined at 2.30 ± 1.43 mg/L for fluoride and 0.0126 ± 0.0080 mg/L for arsenic. These results indicate that the water sourced from this aquifer can potentially pose a serious health problem for the inhabitants of the region. The concentrations of the contaminants exceed the DWL for fluoride in 68% of wells and for arsenic in 63% of wells. It is important to monitor these concentrations consistently, as well as to implement techniques, such as mathematical and geochemical modeling, to improve the understanding of the origin of As and F, and that may allow to predict the behavior of these contaminants in the future.