Co-Occurrence of Metal Contaminants in United States Public Water Systems in 2013–2015

Thompson, Alesha K; Monti, Michele; Gribble, Matthew O.

doi:10.3390/ijerph18157884

Cited by 4 publications

(3 citation statements)

References 22 publications

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“…Because other hazardous oxo-anions and metals co-occur in groundwater naturally, there could be an antagonistic health effect due to long-term exposure to their mixtures. , In addition to arsenic, the public groundwater supply contained detectable levels of selenium, vanadium, and iron. Figure S4 reveals that the unmodified carbon block did not exhibit significant removal of As, Se, V, or Fe within the initial 250 BV of the treatment, prompting the discontinuation of further testing with the unmodified carbon block.…”

Section: Resultsmentioning

confidence: 99%

Sous Vide-Inspired Impregnation of Amorphous Titanium (Hydr)Oxide into Carbon Block Point-of-Use Filters for Arsenic Removal from Water

Farsad,

Marcos-Hernandez,

Sinha

et al. 2023

Environ. Sci. Technol.

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Carbon block filters, commonly employed as point-of-use (POU) water treatment components, effectively eliminate pathogens and adsorb undesirable tastes, odors, and organic contaminants, all while producing no water waste. However, they lack the capability to remove arsenic. Enabling the carbon block to remove arsenic could reduce its exposure risks in tap water. Inspired by Sous vide cooking techniques, we developed a low-energy, low-chemical method for impregnating commercially available carbon block with titanium (hydr)oxide (THO) in four integrated steps: (1) vacuum removal of air from the carbon block, (2) impregnation with precursors in a flexible pouch, (3) sealing to prevent oxygen intrusion, and (4) heating in a water bath at 80 °C for 20 h to eliminate exposure and reactions with air. This process achieved a uniform 13 wt % Ti loading in the carbon block. Our modified carbon block POU filter efficiently removed both arsenate and arsenite from tap water matrices containing 10 or 100 μg/L arsenic concentrations in batch experiments or continuous flow operations. Surprisingly, the THO-modified carbon block removed arsenite better than arsenate. This innovative method, using 70% fewer chemicals than traditional autoclave techniques, offers a cost-effective solution to reduce exposure to arsenic and lower its overall risk in tap water.

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Section: Resultsmentioning

confidence: 99%

Sous Vide-Inspired Impregnation of Amorphous Titanium (Hydr)Oxide into Carbon Block Point-of-Use Filters for Arsenic Removal from Water

Farsad,

Marcos-Hernandez,

Sinha

et al. 2023

Environ. Sci. Technol.

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“…For these elements, a variety of oxidation states is possible under natural aqueous conditions (slightly acidic to slightly alkaline in most settings), and the different states result in species that can have very different solubilities. The similarities in the solubilizing conditions for Cr and V and the opposite solubilizing conditions for As help to explain the concurrences and anti-correlations of certain elements in water supplies [ 15 , 16 , 68 ].…”

Section: Biogeochemical Processesmentioning

confidence: 99%

Towards Understanding Factors Affecting Arsenic, Chromium, and Vanadium Mobility in the Subsurface

Peel

Balogun

Bowers

et al. 2022

Water

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Arsenic (As), chromium (Cr), and vanadium (V) are naturally occurring, redox-active elements that can become human health hazards when they are released from aquifer substrates into groundwater that may be used as domestic or irrigation source. As such, there is a need to develop incisive conceptual and quantitative models of the geochemistry and transport of potentially hazardous elements to assess risk and facilitate interventions. However, understanding the complexity and heterogeneous subsurface environment requires knowledge of solid-phase minerals, hydrologic movement, aerobic and anaerobic environments, microbial interactions, and complicated chemical kinetics. Here, we examine the relevant geochemical and hydrological information about the release and transport of potentially hazardous geogenic contaminants, specifically As, Cr, and V, as well as the potential challenges in developing a robust understanding of their behavior in the subsurface. We explore the development of geochemical models, illustrate how they can be utilized, and describe the gaps in knowledge that exist in translating subsurface conditions into numerical models, as well as provide an outlook on future research needs and developments.

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“…In particular, multiple regression using MLE, herein referred to as censored multiple regression, has been used to predict the spatial distribution of nitrate (e.g., Yen et al 1996;Lichtenberg and Shapiro 1997;Gardner and Vogel 2005;Kaown et al 2007;Fenton et al 2009), chromium (e.g., Coyte et al 2020), and pesticides (e.g., Liu et al 1996aLiu et al , 1996bLiu et al 1997;Larson et al 2004;Nowell et al 2009;Stone and Gilliom 2009;Stackelberg et al 2012). Thompson et al (2021) used censored multiple regression to evaluate metals correlation in the EPA's Unregulated Contaminant Monitoring Rule (UCMR) dataset. These studies do not, however, evaluate the impact of temporal changes in the regression covariates on temporal concentration changes or underlying trends.…”

Section: Introductionmentioning

confidence: 99%

Use of Censored Multiple Regression to Interpret Temporal Environmental Data and Assess Remedy Progress

DiFilippo¹,

Tonkin

Huber

2023

Groundwater

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Many methods to evaluate temporal trends in monitoring data focus on univariate techniques that account for changes in the response variable (e.g., concentration) by means of a single variable, namely time. When predictable site‐specific factors, such as groundwater‐surface water interactions, are associated with or may cause concentration changes, univariate methods may be insufficient for characterizing, estimating, and forecasting temporal trends. Multiple regression methods can incorporate additional explanatory variables, thereby minimizing the amount of unexplained variability that is relegated to the “error” term. However, the presence of sample results that are below laboratory reporting limits (i.e., censored) prohibits the direct application of the standard least‐squares method for multiple regression. Maximum likelihood estimation (MLE) for multiple regression analysis can enhance temporal trend analysis in the presence of censored response data and improve characterizing, estimating, and forecasting of temporal trends. Multiple regression using MLE (or censored multiple regression) was demonstrated at the U.S. Department of Energy Hanford Site where analyte concentrations in groundwater samples are negatively correlated with the stage of the nearby Columbia River. Incorporating a time‐lagged stage variable in the regression analysis of these data provides more reliable estimates of future concentrations, reducing the uncertainty in evaluating the progress of remediation toward remedial action objectives. Censored multiple regression can identify significant changes over time; project when maxima and minima of interest are likely to occur; estimate average values and their confidence limits over time periods relevant to regulatory compliance; and thereby improve the management of remedial action monitoring programs.

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Co-Occurrence of Metal Contaminants in United States Public Water Systems in 2013–2015

Cited by 4 publications

References 22 publications

Sous Vide-Inspired Impregnation of Amorphous Titanium (Hydr)Oxide into Carbon Block Point-of-Use Filters for Arsenic Removal from Water

Sous Vide-Inspired Impregnation of Amorphous Titanium (Hydr)Oxide into Carbon Block Point-of-Use Filters for Arsenic Removal from Water

Towards Understanding Factors Affecting Arsenic, Chromium, and Vanadium Mobility in the Subsurface

Use of Censored Multiple Regression to Interpret Temporal Environmental Data and Assess Remedy Progress

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