Abstract
Many rural communities rely on dug wells as a primary source of drinking water. This well water is usually untreated, susceptible to natural and anthropogenic contamination, and rarely tested. Well networks near industrial waste sites like coal ash impoundments of coal-fired power plants, may be at higher risk of contamination from waste sites. Coal ash constituents, including trace metals and metalloids, are able to deposit and move through the environment. Using data provided by the Altamaha Riverkeepers (ARK) for 64 wells in Juliette, GA, we sought first, to characterize well contamination from toxic metals, including hexavalent chromium, arsenic, and lead, and second, to investigate contaminant associations with spatial factors including distance and elevation. We found that distance and elevation exhibited negative correlations with a majority of contaminants, including boron, cobalt, and strontium (<-0.20). Results did not exhibit positive correlations above 0.20. Linear regression models found significant negative associations between distance and well depth with boron, cobalt, and strontium. Spatial mapping of hexavalent chromium, barium, and strontium found that the majority of wells in the upper threshold for each contaminant were located between 2-4 miles northeast of the center of the coal ash impoundment. This study suggests that elevation and distance from a coal ash impoundment are significantly associated with specific decreased metal contaminant levels in wells in Juliette, GA. Understanding the nature and extent of metal contamination in drinking water sources is critical to safeguarding public health and the well-being of communities.
Table of Contents
Introduction Metals and Human Health Coal Ash Ponds Spatial factors of coal ash contamination Study Motivation and Study Area Regional Geology and Hydrogeology Study Objective Methods Water Sample Collection and Assessment Data Preparation Data Analysis Statistics and mapping tools Results Descriptive well water quality and spatial parameters Correlations between metals detected in wells Linear regression of metals on the basis of spatial parameters Spatial distribution of major well water samples Discussion Conclusion and recommendations
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