Arsenic is a known human carcinogen and relevant environmental contaminant in drinking water systems. Publicly available data at the NCDHHS represent a volume of historical arsenic analyses in North Carolina domestic well waters performed under stringent EPA guidelines that remain largely unanalyzed. A primary goal of this research was to identify trends in areas of North Carolina with elevated arsenic concentrations in monitored domestic well waters. We revealed arsenic trends by county in monitored wells over time as well as estimated concentrations in unmonitored locations. The geocoding methods developed in this study data enabled a comprehensive report of over 4,000 yearly arsenic measurements with geographical coordinates from 1998-2007 and over 10,000 from 2008 to present, a substantial increase relative to the USGS and EPA ambient monitoring systems. Specifically, the number of records analyzed represents a 600-fold increase from samples collected by the USGS (USGS 2010
) and more than three times the number of records analyzed in other studies North Carolina wells (Pippin 2005
; Kim et al. in press
). The substantial increase in recent well sampling is likely due to state legislation adopted in 2008 that requires every newly constructed well be tested. These types of monitoring programs, as evidenced here, are successful to ensuring increased awareness of well water contaminants and protected health of individual homeowners.
A notable result of this study is the surprisingly high levels of arsenic (up to 806 μg/L) that were detected in some homeowners’ domestic wells. In addition, more than 1,436 (2.25%) of wells exceeded the EPA standard. Some of the top-ranked counties identified here as most frequently exceeding the EPA MCL have not previously been highlighted in nation- or statewide studies (Welch et al. 1999
) including Anson, Montgomery, Dare, Alexander, Cleveland, and Currituck Counties. We identify historical trends in counties along the Carolina terrane and through comprehensive temporal assessment reveal that arsenic levels have been elevated for over a decade. In some of these counties, greater than 50% of the population use domestic wells (Kenny et al. 2009
). Importantly, some of the identified counties of concern have rapidly growing populations (US Census Bureau 2006
), which compounded by an arsenic-prone geology may have public health implications for residents. Simultaneously, rural areas are more likely to lack connection to a municipal drinking water system. By ranking based on percentage of population at risk we identify counties where county-level well monitoring programs may be cost-effective. By integrating information on population size in these counties, we show Union and Stanly continue to rank among the most at-risk county populations. Our data confirm increased concentrations of arsenic in counties located along the Carolina terrane and highlight elevated levels over a decade-long period. In addition, the counties of Stanly and Union have large populations (roughly 26,000 and 49,000 individuals) relying on private well water sources. Currently, no epidemiologic literature has investigated the health impact of arsenic in these populations.
This study presents a new approach to assigning geographical coordinates when sample locations are described by inconsistent recorded information. It was evident from the spatial locations of GPS data that GPS device use was not uniform across the state. It was necessary, therefore, to increase the number of geocoded locations using additional information (Classes II-IV) to avoid bias and provide more accurate spatial representations. As such, we applied a four-step geocoding process and error estimation scheme that increased the available geographic coordinates of ~3,000 to more than 63,000 well analyses. We increased the knowledgebase using available locational information to assign geographic coordinates of domestic wells based on four spatial classes: GPS, street address, zip code, and county. As an example, we tripled the number of successfully geocoded points used in previous analyses over comparable geographic areas and timeframes (Pippin 2005
; Kim et al. in press
). Additionally, while others have shown that multi-stage geocoding methods improved the match rate compared to single-step methods (Lovasi et al. 2007
), to our knowledge, the present study is one of the first to use GPS locations to systematically quantify and account for geocoding location error. We present a widely applicable method of systematically determining acceptable match scores resulting from the multi-stage address geocoding procedure that serves as an alternative to a minimum match score determined a priori
(Yang et al. 2004
The general BME framework has been applied to arsenic levels in Bangladesh groundwaters to estimate aqueous concentrations where data are not available (Serre et al. 2003
). In this study, we apply the BME framework to U.S. groundwaters and incorporate location error into a novel arsenic estimation process, which aggregates monitored arsenic levels to a county level observation scale (~11km). To the best of our knowledge, this is the first study that accounts for locational error. The cross-validation analysis shows that the BME approach presented in this work more accurately predicts arsenic than conventional modeling approaches. Within this framework, the county observation scale refines well-to-well variation and we would not expect to find the high concentrations seen in individual monitored wells (e.g. up to 806 μg/L). By narrowing the scope to counties of interest in the southwestern Piedmont we identified southeastern Union County and the border between Stanly and Montgomery Counties as areas of special concern. The levels documented in this study indicate areas of arsenic contamination at nearly twice the EPA standard-a level estimated to double the risk of bladder and lung cancer (NRC 2001
). The local observation scale enables our predictive maps to be useful for public health screening purposes by identifying areas where the risk of arsenic exposure is high and by providing a science-based criterion for cost-effective monitoring of wells.
Through our analyses of over 60,000 geocoded well locations we were able to more accurately assess spatial and temporal arsenic trends in both monitored wells and estimates at unmonitored locations across North Carolina. We found that areas near the eastern coast and along the Carolina terrane have high prevalence of arsenic contamination in private wells. The presence of arsenic in the Carolina terrane has been confirmed by geological studies in this area (Foley et al. 2001
) and is supported by models that incorporate geologic determinants (Kim et al. in press
). Abundant literature details the sources of groundwater arsenic contamination through anthropogenic factors including agricultural or industrial practices (Foley and Ayuso 2008
; Jackson et al. 2006
; Appleyard et al. 2004
; Embrick et al. 2005
), yet, much of arsenic contamination highlighted in this study is thought to be naturally occurring due to the underlying geology (Foley et al. 2001
; Welch et al. 2000
; Duker et al. 2005
). The Carolina terrane, however, does not underlie each of the top ten counties (Pender, Dare, and Currituck Counties for instance) and it is possible that a combination of anthropogenic and natural sources may contribute to arsenic contamination, however additional studies are warranted. Currently, no EPA Superfund National Priorities List or Toxic Release Inventory sites are listed in these three counties that would indicate substantial anthropogenic contribution to environmental arsenic concentrations. Moreover, while an EPA superfund site is located in Haywood County with reported historical use of arsenical pesticides, no wells in that county that exceeded the EPA standard.
Studies like this one represent a major step towards arsenic surveillance in contaminated areas. To lessen the risk of exposure to arsenic in drinking water, recommended preventative measures include point-of-use removal, modification of well depth, and/or use of an alternate water source (Alaerts and Khouri 2004
; Pratson et al. 2010
). These solutions are rarely cost-effective, however, and may not be feasible in rural areas. Simple cost-effective technologies for mitigating arsenic are not widely available, and, in lieu of federal or state water quality regulation of domestic wells, the best mitigation is in the form of well water testing programs. Trivalent (As3+: arsenite) and pentavalent (As5+: arsenate) arsenic most commonly occur in natural waters (Duker et al. 2005
; Feng et al. 2001
). Due to the variable toxicity of arsenic species (As3+ being more toxic), additional studies are warranted to determine the distribution of individual arsenic species in drinking water. Targeted monitoring is crucial in reducing the financial cost of testing for speciated arsenic in every monitored well and the methods developed here can be applied to this end towards arsenic in other regions as well as to other contaminants of concern to public health.
The compounding of environmental and social factors means residents could be at increased risk for health effects from arsenic. Additional studies are warranted to further ascertain the sources of and biogeochemical behavior of arsenic in unstudied regions of North Carolina and to help reduce exposures among at risk populations. By identifying regions of contamination through studies such as this one, cost-effective monitoring programs can target at risk populations to protect public health and help to shape state and local water monitoring policies (Miranda et al. 2011
). Moving forward we anticipate research that will integrate these findings with biomonitoring and health outcome data to substantiate risks posed to populations in arsenic endemic areas. The next steps to protecting individuals include community education in at risk areas and biomonitoring of those populations most at risk including children and pregnant women.