PubAg

Main content area

Depth Stratification Leads to Distinct Zones of Manganese and Arsenic Contaminated Groundwater

Author:
Ying, Samantha C., Schaefer, Michael V., Cock-Esteb, Alicea, Li, Jun, Fendorf, Scott
Source:
Environmental Science & Technology 2017 v.51 no.16 pp. 8926-8932
ISSN:
1520-5851
Subject:
aquifers, arsenic, basins, dissolved oxygen, drinking water, groundwater, groundwater contamination, humans, manganese, river deltas, watersheds, wells, Bangladesh, Cambodia, China, United States, Yangtze River
Abstract:
Providing access to safe drinking water is a global challenge, for which groundwater is increasingly being used throughout the world. However, geogenic contaminants limit the suitability of groundwater for domestic purposes over large geographic areas across most continents. Geogenic contaminants in groundwater are often evaluated individually, but here we demonstrate the need to evaluate multiple contaminants to ensure that groundwater is safe for human consumption and agricultural usage. We compiled groundwater chemical data from three aquifer regions across the world that have been reported to have widespread As and Mn contamination including the Glacial Aquifer in the U.S., the Ganges-Brahmaputra-Mehta Basin within Bangladesh, and the Mekong Delta in Cambodia, along with newly sampled wells in the Yangtze River Basin of China. The proportion of contaminated wells increase by up to 40% in some cases when both As and Mn contaminants are considered. Wilcoxon rank-sum analysis indicates that Mn contamination consistently occurs at significantly shallower depths than As contaminated wells in all regions. Arsenic concentrations in groundwater are well predicted by redox indicators (Eh and dissolved oxygen) whereas Mn shows no significant relationship with either parameter. These findings illustrate that the number of safe wells may be drastically overestimated in some regions when Mn contamination is not taken into account and that depth may be used as a distinguishing variable in efforts to predict the presence of groundwater contaminants regionally.
Agid:
5789101