Bounding Analysis of Drinking Water Health Risks from a Spill of Hydraulic Fracturing Flowback Water

A bounding risk assessment is presented that evaluates possible human health risk from a hypothetical scenario involving a 10,000‐gallon release of flowback water from horizontal fracturing of Marcellus Shale. The water is assumed to be spilled on the ground, infiltrates into groundwater that is a source of drinking water, and an adult and child located downgradient drink the groundwater. Key uncertainties in estimating risk are given explicit quantitative treatment using Monte Carlo analysis. Chemicals that contribute significantly to estimated health risks are identified, as are key uncertainties and variables to which risk estimates are sensitive. The results show that hypothetical exposure via drinking water impacted by chemicals in Marcellus Shale flowback water, assumed to be spilled onto the ground surface, results in predicted bounds between 10⁻¹⁰ and 10⁻⁶ (for both adult and child receptors) for excess lifetime cancer risk. Cumulative hazard indices (HI_CUMULATIVE) resulting from these hypothetical exposures have predicted bounds (5th to 95th percentile) between 0.02 and 35 for assumed adult receptors and 0.1 and 146 for assumed child receptors. Predicted health risks are dominated by noncancer endpoints related to ingestion of barium and lithium in impacted groundwater. Hazard indices above unity are largely related to exposure to lithium. Salinity taste thresholds are likely to be exceeded before drinking water exposures result in adverse health effects. The findings provide focus for policy discussions concerning flowback water risk management. They also indicate ways to improve the ability to estimate health risks from drinking water impacted by a flowback water spill (i.e., reducing uncertainty).     

Evaluating the Potential for a Helicobacter pylori Drinking Water Guideline

Helicobacter pylori is a microaerophilic, gram‐negative bacterium that is linked to adverse health effects including ulcers and gastrointestinal cancers. The goal of this analysis is to develop the necessary inputs for a quantitative microbial risk assessment (QMRA) needed to develop a potential guideline for drinking water at the point of ingestion (e.g., a maximum contaminant level, or MCL) that would be protective of human health to an acceptable level of risk while considering sources of uncertainty. Using infection and gastric cancer as two discrete endpoints, and calculating dose‐response relationships from experimental data on humans and monkeys, we perform both a forward and reverse risk assessment to determine the risk from current reported surface water concentrations of H. pylori and an acceptable concentration of H. pylori at the point of ingestion. This approach represents a synthesis of available information on human exposure to H. pylori via drinking water. A lifetime risk of cancer model suggests that a MCL be set at <1 organism/L given a 5‐log removal treatment because we cannot exclude the possibility that current levels of H. pylori in environmental source waters pose a potential public health risk. Research gaps include pathogen occurrence in source and finished water, treatment removal rates, and determination of H. pylori risks from other water sources such as groundwater and recreational water.     

Regional Risk Assessment for Point Source Pollution Based on a Water Quality Model of the Taipu River,China

Point source pollution is one of the main threats to regional environmental health. Based on a water quality model, a methodology to assess the regional risk of point source pollution is proposed. The assessment procedure includes five parts: (1) identifying risk source units and estimating source emissions using Monte Carlo algorithms; (2) observing hydrological and water quality data of the assessed area, and evaluating the selected water quality model; (3) screening out the assessment endpoints and analyzing receptor vulnerability with the Choquet fuzzy integral algorithm; (4) using the water quality model introduced in the second step to predict pollutant concentrations for various source emission scenarios and analyzing hazards of risk sources; and finally, (5) using the source hazard values and receptor vulnerability scores to estimate overall regional risk. The proposed method, based on the Water Quality Analysis Simulation Program (WASP), was applied in the region of the Taipu River, which is in the Taihu Basin, China. Results of source hazard and receptor vulnerability analysis allowed us to describe aquatic ecological, human health, and socioeconomic risks individually, and also integrated risks in the Taipu region, from a series of risk curves. Risk contributions of sources to receptors were ranked, and the spatial distribution of risk levels was presented. By changing the input conditions, we were able to estimate risks for a range of scenarios. Thus, the proposed procedure may also be used by decisionmakers for long‐term dynamic risk prediction.     

Risk Characterization of Methyl tertiary Butyl Ether (MTBE) in Tap Water

Methyl tertiary butyl ether (MTBE) can enter surface water and groundwater through wet atmospheric deposition or as a result of fuel leaks and spills. About 30% of the U.S. population lives in areas where MTBE is in regular use. Ninety-five percent of this population is unlikely to be exposed to MTBE in tap water at concentrations exceeding 2 ppb, and most will be exposed to concentrations that are much lower and may be zero. About 5% of this population may be exposed to higher levels of MTBE in tap water, resulting from fuel tank leaks and spills into surface or groundwater used for potable water supplies. This paper describes the concentration ranges found and anticipated in surface and groundwater, and estimates the distribution of doses experienced by humans using water containing MTBE to drink, prepare food, and shower/bathe. The toxic properties (including potency) of MTBE when ingested, inhaled, and in contact with the skin are summarized. Using a range of human toxic potency values derived from animal studies, margins of exposure (MOE) associated with alternative chronic exposure scenarios are estimated to range from 1700 to 140,000. Maximum concentrations of MTBE in tap water anticipated not to cause adverse health effects are determined to range from 700 to 14,000 ppb. The results of this analysis demonstrate that no health risks are likely to be associated with chronic and subchronic human exposures to MTBE in tap water. Although some individuals may be exposed to very high concentrations of MTBE in tap water immediately following a localized spill, these exposures are likely to be brief in duration due to large-scale dilution and rapid volatilization of MTBE, the institution of emergency response and remediation measures to minimize human exposures, and the low taste and odor thresholds of MTBE which ensure that its presence in tap water is readily detected at concentrations well below the threshold for human injury.     

Treating and Drinking Well Water in the Presence of Health Risks from Arsenic Contamination: Results from a U.S. Hot Spot

The Safe Drinking Water Act of 1974 regulates water quality in public drinking water supply systems but does not pertain to private domestic wells, often found in rural areas throughout the country. The recent decision to tighten the drinking water standard for arsenic from 50 parts per billion (ppb) to 10 ppb may therefore affect some households in rural communities, but may not directly reduce health risks for those on private wells. The article reports results from a survey conducted in a U.S. arsenic hot spot, the rural area of Churchill County, Nevada. This area has elevated levels of arsenic in groundwater. We find that a significant proportion of households on private wells are consuming drinking water with arsenic levels that pose a health risk. The decision to treat tap water for those on private wells in this area is modeled, and the predicted probability of treatment is used to help explain drinking water consumption. This probability represents behaviors relating to the household's perception of risk.     

Using the CAUSE Model to Understand Public Communication about Water Risks: Perspectives from Texas Groundwater District Officials on Drought and Availability

Public communication about drought and water availability risks poses challenges to a potentially disinterested public. Water management professionals, though, have a responsibility to work with the public to engage in communication about water and environmental risks. Because limited research in water management examines organizational communication practices and perceptions, insights into research and practice can be gained through investigation of current applications of these risk communication efforts. Guided by the CAUSE model, which explains common goals in communicating risk information to the public (e.g., creating Confidence, generating Awareness, enhancing Understanding, gaining Satisfaction, and motivating Enactment), semistructured interviews of professionals (N = 25) employed by Texas groundwater conservation districts were conducted. The interviews examined how CAUSE model considerations factor in to communication about drought and water availability risks. These data suggest that many work to build constituents’ confidence in their districts. Although audiences and constituents living in drought‐prone areas were reported as being engaged with water availability risks and solutions, many district officials noted constituents’ lack of perceived risk and engagement. Some managers also indicated that public understanding was a secondary concern of their primary responsibilities and that the public often seemed apathetic about technical details related to water conservation risks. Overall, results suggest complicated dynamics between officials and the public regarding information access and motivation. The article also outlines extensions of the CAUSE model and implications for improving public communication about drought and water availability risks.     

Feeling at Risk Matters: Water Managers and the Decision to Use Forecasts

Experts contend that weather and climate forecasts could have an important role in risk management strategies for community water systems. Yet, most water managers make minimal use of these forecasts. This research explores the determinants of the use of weather and climate forecasts by surveying managers of community water systems in two eastern American states (South Carolina and the Susquehanna River Basin of Pennsylvania). Assessments of the reliability of weather and climate forecasts are not driving their use as water managers who find forecasts reliable are no more likely to use them than are managers who find them unreliable. Although larger systems and those depending on surface water are more likely to use forecasts for some (but not all) purposes, the strongest determinant of forecast use is risk perceptions. Water managers who expect to face problems from weather events in the next decade are much more likely to use forecasts than are water managers who expect few problems. Their expectations of future problems are closely linked with past experience: water managers who have had problems with specific types of weather events (e.g., flood emergencies) in the last 5 years are likely to expect to experience problems in the next decade. Feeling at risk, regardless of the specific source of that weather-related risk, stimulates a decision to use weather and climate forecasts.     

Risk Perception and Human Health Risk in Rural Communities Consuming Unregulated Well Water in Saskatchewan,Canada

Rural communities dependent on unregulated drinking water are potentially at increased health risk from exposure to contaminants. Perception of drinking water safety influences water consumption, exposure, and health risk. A community‐based participatory approach and probabilistic Bayesian methods were applied to integrate risk perception in a holistic human health risk assessment. Tap water arsenic concentrations and risk perception data were collected from two Saskatchewan communities. Drinking water health standards were exceeded in 67% (51/76) of households in Rural Municipality #184 (RM184) and 56% (25/45) in Beardy's and Okemasis First Nation (BOFN). There was no association between the presence of a health exceedance and risk perception. Households in RM184 or with an annual income >$50,000 were most likely to have in‐house water treatment. The probability of consuming tap water perceived as safe (92%) or not safe (0%) suggested that households in RM184 were unlikely to drink water perceived as not safe. The probability of drinking tap water perceived as safe (77%) or as not safe (11%) suggested households in BOFN contradicted their perception and consumed water perceived as unsafe. Integration of risk perception lowered the adult incremental lifetime cancer risk by 3% to 1.3 × 10^?5 (95% CI 8.4 × 10^?8 to 9.0 × 10^?5) for RM184 and by 8.9 × 10^?6 (95% CI 2.2 × 10^?7 to 5.9 × 10^?5) for BOFN. Probability of exposure to arsenic concentrations >1:100,000, negligible cancer risk, was 23% for RM184 and 22% for BOFN.     

Considering the Risk of Infection by Cryptosporidium via Consumption of Municipally Treated Drinking Water from a Surface Water Source in a Southwestern Ontario Community

Through the use of case‐control analyses and quantitative microbial risk assessment (QMRA), relative risks of transmission of cryptosporidiosis have been evaluated (recreational water exposure vs. drinking water consumption) for a Canadian community with higher than national rates of cryptosporidiosis. A QMRA was developed to assess the risk of Cryptosporidium infection through the consumption of municipally treated drinking water. Simulations were based on site‐specific surface water contamination levels and drinking water treatment log₁₀ reduction capacity for Cryptosporidium. Results suggested that the risk of Cryptosporidium infection via drinking water in the study community, assuming routine operation of the water treatment plant, was negligible (6 infections per 10¹³ persons per day—5th percentile: 2 infections per 10¹⁵ persons per day; 95th percentile: 3 infections per 10¹² persons per day). The risk is essentially nonexistent during optimized, routine treatment operations. The study community achieves between 7 and 9 log₁₀Cryptosporidium oocyst reduction through routine water treatment processes. Although these results do not preclude the need for constant vigilance by both water treatment and public health professionals in this community, they suggest that the cause of higher rates of cryptosporidiosis are more likely due to recreational water contact, or perhaps direct animal contact. QMRA can be successfully applied at the community level to identify data gaps, rank relative public health risks, and forecast future risk scenarios. It is most useful when performed in a collaborative way with local stakeholders, from beginning to end of the risk analysis paradigm.     

Do Reports on Drinking Water Quality Affect Customers' Concerns? Experiments in Report Content

The Safe Drinking Water Act Amendments of 1996 required U.S. utilities to report on drinking water quality to their customers annually, beginning in fall 1999, on the assumption that such reports would alert them to quality problems and perhaps mobilize pressure for improvement. A random sample of New Jersey customers read alternative versions of a water quality report, in an experiment on reactions to water quality information under U.S. Environmental Protection Agency (USEPA) rules. Experiment design was 2 x 3 + 1: two versions each--one with, one without, a violation of a health standard--of a report that was (1) Qualitative (without water quality numbers, thus not meeting USEPA rules); (2) Basic, with minimal information meeting the rules; or (3) Extended, adding reading aids and utility performance information; plus a control instrument without any hypothetical report. Results of ANOVA suggest the reports will have less effect than hoped or feared. These manipulations were successful: people reading the Qualitative versions were less likely to say that the report gave the amounts of substances found in the water, and those reading Violation versions were more likely to report a violation of a health standard. The main differences in responses to the report involved the judged adequacy of the information, and to a lesser extent responses on a Concern scale (constructed from measures of concern, judged risk, clean-up intentions, distrust of utility information, and doubt that the utility was doing all it could to improve water quality). Overall judgments of water quality and utility performance did not change, either relative to the controls or in before versus after responses. Qualitative reports performed worse than others, confirming the decision to have utilities report actual contaminant levels. Extended reports did only slightly better than the Basic versions on these measures. Many respondents had trouble identifying the presence or absence of substance amounts or violations, despite their seeming obviousness (e.g., in a "bottom line" summary on the front page of each report), suggesting many were not processing this information carefully. However, the pattern of responses for those who accurately identified the presence or absence of substance amounts or violations did not differ substantially from that for the group as a whole. Generic risk beliefs (serious local environmental problems; lack of control over risks to one's health) dominated demographic variables, attitudes toward utility water quality or trustworthiness, and the content and format of water quality reports in influencing concern about drinking water quality. Previous empirical and theoretical evidence for lack of change in public risk attitudes due to one-time or infrequent communications--e.g., role of personal experience, perseverance of prior trust or distrust--seems to be confirmed for annual water quality reports.     

Agent‐Based Modeling to Simulate Contamination Events and Evaluate Threat Management Strategies in Water Distribution Systems

In the event of contamination of a water distribution system, decisions must be made to mitigate the impact of the contamination and to protect public health. Making threat management decisions while a contaminant spreads through the network is a dynamic and interactive process. Response actions taken by the utility managers and water consumption choices made by the consumers will affect the hydraulics, and thus the spread of the contaminant plume, in the network. A modeling framework that allows the simulation of a contamination event under the effects of actions taken by utility managers and consumers will be a useful tool for the analysis of alternative threat mitigation and management strategies. This article presents a multiagent modeling framework that combines agent‐based, mechanistic, and dynamic methods. Agents select actions based on a set of rules that represent an individual's autonomy, goal‐based desires, and reaction to the environment and the actions of other agents. Consumer behaviors including ingestion, mobility, reduction of water demands, and word‐of‐mouth communication are simulated. Management strategies are evaluated, including opening hydrants to flush the contaminant and broadcasts. As actions taken by consumer agents and utility operators affect demands and flows in the system, the mechanistic model is updated. Management strategies are evaluated based on the exposure of the population to the contaminant. The framework is designed to consider the typical issues involved in water distribution threat management and provides valuable analysis of threat containment strategies for water distribution system contamination events.     

Measuring the Dynamic Efficiency Costs of Regulators' Preferences: Municipal Water Utilities in the Arid West

Evidence suggests that municipal water utility administrators in the western US price water significantly below its marginal cost and, in so doing, inefficiently exploit aquifer stocks and induce social surplus losses. This paper empirically identifies the objective function of those managers, measures the deadweight losses resulting from their price‐discounting decisions, and recovers the efficient water pricing policy function from counterfactual experiments. In doing so, the estimation uses a “continuous‐but‐constrained‐ control” version of a nested fixed‐point algorithm in order to measure the important intertemporal consequences of groundwater pricing decisions.     

An Overview of a Multimedia Benchmarking Analysis for Three Risk Assessment Models: RESRAD, MMSOILS, and MEPAS

Multimedia modelers from the United States Environmental Protection Agency (EPA) and the United States Department of Energy (DOE) collaborated to conduct a detailed and quantitative benchmarking analysis of three multimedia models. The three models—RESRAD (DOE), MMSOILS (EPA), and MEPAS (DOE)—represent analytically-based tools that are used by the respective agencies for performing human exposure and health risk assessments. The study is performed by individuals who participate directly in the ongoing design, development, and application of the models. Model form and function are compared by applying the models to a series of hypothetical problems, first isolating individual modules (e.g., atmospheric, surface water, groundwater) and then simulating multimedia-based risk resulting from contaminant release from a single source to multiple environmental media. Study results show that the models differ with respect to environmental processes included (i.e., model features) and the mathematical formulation and assumptions related to the implementation of solutions. Depending on the application, numerical estimates resulting from the models may vary over several orders-of-magnitude. On the other hand, two or more differences may offset each other such that model predictions are virtually equal. The conclusion from these results is that multimedia models are complex due to the integration of the many components of a risk assessment and this complexity must be fully appreciated during each step of the modeling process (i.e., model selection, problem conceptualization, model application, and interpretation of results).     

Risk Estimation and Value-of-Information Analysis for Three Proposed Genetic Screening Programs for Chronic Beryllium Disease Prevention

Genetic differences (polymorphisms) among members of a population are thought to influence susceptibility to various environmental exposures. In practice, however, this information is rarely incorporated into quantitative risk assessment and risk management. We describe an analytic framework for predicting the risk reduction and value-of-information (VOI) resulting from specific risk management applications of genetic biomarkers, and we apply the framework to the example of occupational chronic beryllium disease (CBD), an immune-mediated pulmonary granulomatous disease. One described Human Leukocyte Antigen gene variant, HLA-DP beta 1*0201, contains a substitution of glutamate for lysine at position 69 that appears to have high sensitivity (approximately 94%) but low specificity (approximately 70%) with respect to CBD among individuals occupationally exposed to respirable beryllium. The expected postintervention CBD prevalence rates for using the genetic variant (1) as a required job placement screen, (2) as a medical screen for semiannual in place of annual lymphocyte proliferation testing, or (3) as a voluntary job placement screen are 0.08%, 0.8%, and 0.6%, respectively, in a hypothetical cohort with 1% baseline CBD prevalence. VOI analysis is used to examine the reduction in total social cost, calculated as the net value of disease reduction and financial expenditures, expected for proposed CBD intervention programs based on the genetic susceptibility test. For the example cohort, the expected net VOI per beryllium worker for genetically based testing and intervention is $13,000, $1,800, and $5,100, respectively, based on a health valuation of $1.45 million per CBD case avoided. VOI results for alternative CBD evaluations are also presented. Despite large parameter uncertainty, probabilistic analysis predicts generally positive utility for each of the three evaluated programs when avoidance of a CBD case is valued at $1 million or higher. Although the utility of a proposed risk management program may be evaluated solely in terms of risk reduction and financial costs, decisions about genetic testing and program implementation must also consider serious social, legal, and ethical factors.     

Health care costs tied to many issues

Although, in 1990, the United States spent about $750 billion (12.2 percent of the Gross National Product) on health care, 31-37 million people in this country are uninsured. Another 4 million people are thought to be underinsured. We have one of the highest infant mortality rates among developed industrialized nations and rank 19th in health care and well-being among those nations. Our life expectancy is lower than those of some third-world countries. The United States and South Africa are the only two industrialized nations without a national health care policy. In spite of these statistics, U.S. health care costs continue to rise and, by the year 2000, are expected to reach $1.5 trillion (15 to 17.5 percent of the GNP. Per capita spending on health care will reach $5,515 by the year 2000, compared with $2,425 in 1990 and $1,016 in 1980.     

Using Probabilistic Modeling to Evaluate Human Exposure to Organotin in Drinking Water Transported by Polyvinyl Chloride Pipe

The leaching of organotin (OT) heat stabilizers from polyvinyl chloride (PVC) pipes used in residential drinking water systems may affect the quality of drinking water. These OTs, principally mono- and di-substituted species of butyltins and methyltins, are a potential health concern because they belong to a broad class of compounds that may be immune, nervous, and reproductive system toxicants. In this article, we develop probability distributions of U.S. population exposures to mixtures of OTs encountered in drinking water transported by PVC pipes. We employed a family of mathematical models to estimate OT leaching rates from PVC pipe as a function of both surface area and time. We then integrated the distribution of estimated leaching rates into an exposure model that estimated the probability distribution of OT concentrations in tap waters and the resulting potential human OT exposures via tap water consumption. Our study results suggest that human OT exposures through tap water consumption are likely to be considerably lower than the World Health Organization (WHO) "safe" long-term concentration in drinking water (150 μg/L) for dibutyltin (DBT)—the most toxic of the OT considered in this article. The 90th percentile average daily dose (ADD) estimate of 0.034 ± 2.92 × 10⁻⁴μg/kg day is approximately 120 times lower than the WHO-based ADD for DBT (4.2 μg/kg day).     

Reassessing the human health benefits from cleaner air

Recent proposals to further reduce permitted levels of air pollution emissions are supported by high projected values of resulting public health benefits. For example, the Environmental Protection Agency recently estimated that the 1990 Clean Air Act Amendment (CAAA) will produce human health benefits in 2020, from reduced mortality rates, valued at nearly $2 trillion per year, compared to compliance costs of $65 billion ($0.065 trillion). However, while compliance costs can be measured, health benefits are unproved: they depend on a series of uncertain assumptions. Among these are that additional life expectancy gained by a beneficiary (with median age of about 80 years) should be valued at about $80,000 per month; that there is a 100% probability that a positive, linear, no-threshold, causal relation exists between PM(2.5) concentration and mortality risk; and that progress in medicine and disease prevention will not greatly diminish this relationship. We present an alternative uncertainty analysis that assigns a positive probability of error to each assumption. This discrete uncertainty analysis suggests (with probability >90% under plausible alternative assumptions) that the costs of CAAA exceed its benefits. Thus, instead of suggesting to policymakers that CAAA benefits are almost certainly far larger than its costs, we believe that accuracy requires acknowledging that the costs purchase a relatively uncertain, possibly much smaller, benefit. The difference between these contrasting conclusions is driven by different approaches to uncertainty analysis, that is, excluding or including discrete uncertainties about the main assumptions required for nonzero health benefits to exist at all.     

Sensitivity and Uncertainty Studies of the CRAC2 Computer Code

We have studied the sensitivity of health impacts from nuclear reactor accidents, as predicted by the CRAC2 computer code, to the following sources of uncertainty: (1) the model for plume rise, (2) the model for wet deposition, (3) the meteorological bin-sampling procedure for selecting weather sequences with rain, (4) the dose conversion factors for inhalation as affected by uncertainties in the particle size of the carrier aerosol and the clearance rates of radionuclides from the respiratory tract, (5) the weathering half-time for external ground-surface exposure, and (6) the transfer coefficients for terrestrial foodchain pathways. Predicted health impacts usually showed little sensitivity to use of an alternative plume-rise model or a modified rain-bin structure in bin-sampling. Health impacts often were quite sensitive to use of an alternative wet-deposition model in single-trial runs with rain during plume passage, but were less sensitive to the model in bin-sampling runs. Uncertainties in the inhalation dose conversion factors had important effects on early injuries in single-trial runs. Latent cancer fatalities were moderately sensitive to uncertainties in the weathering half-time for ground-surface exposure, but showed little sensitivity to the transfer coefficients for terrestrial foodchain pathways. Sensitivities of CRAC2 predictions to uncertainties in the models and parameters also depended on the magnitude of the source term, and some of the effects on early health effects were comparable to those that were due only to selection of different sets of weather sequences in bin-sampling.     

Moral Utility Theory: Understanding the motivation to behave (un)ethically

Moral Utility Theory provides an integrative framework for understanding the motivational basis of ethical decision making by modeling it as a process of subjective expected utility (SEU) maximization. The SEUs of ethical and unethical behavioral options are proposed to be assessed intuitively during goal pursuit, with unethical conduct emerging when the expected benefits of moral transgressions outweigh the expected costs. A key insight of the model is that any factors that increase the value of a goal—including incentives, framings, and mindsets—can motivate misbehavior by increasing the SEU of unethical conduct. Although Moral Utility Theory emphasizes the automatic and habitual nature of most SEU appraisals, it also describes a mechanism for initiating the deliberative moral reasoning process: the experience of moral uncertainty. Moral uncertainty is proposed to occur when the SEUs of ethical and unethical behaviors are similar in magnitude, thereby activating the behavioral inhibition system and motivating the allocation of attentional resources toward the decision process. This framework bridges the gap between affective and cognitive perspectives on ethical decision making by identifying automatic evaluations as a central driver of moral decisions while also specifying when and how moral reasoning processes are initiated. By combining dual-process models of morality with well-validated principles from the science of motivation, Moral Utility Theory provides theoretical parsimony and formal modeling potential to the study of ethical decision making. The framework also suggests practical strategies—from employee selection and training to goal setting and compensation systems—for encouraging ethical behavior in organizations.     

Water Adherence Factors for Human Skin

On incidental dermal exposure to chemicals in water, a key exposure factor is the amount of water adhering to skin. Although soil adherence factors have been developed for risk assessment, measurements of water adherence on human skin have not been described. In the Environmental Protection Agency's (EPA's) dermal risk assessment guidance, dermal dose from environmental exposures is based upon the flux rate across the skin, which assumes that an unlimited amount of chemical is available for absorption. This assumption is applicable to certain exposure scenarios such as swimming and bathing. However, exposures to contaminated water frequently involve scenarios where the available chemical is limited by the amount of water adhering to the skin, for example, during accidental splashes. We conducted studies in human volunteers to investigate water adherence per unit area of skin after brief contact with water. In two sets of experiments, either water was applied with a micropipette to 10‐cm² areas of the lower leg, foot, and hand, or the foot and hand were briefly immersed in water. In males, using a micropipette, water adherence ranged from 1.93 (foot) to 7.13 μL/cm² (lower leg). In females, it ranged from 1.10 (lower leg) to 4.83 μL/cm² (hand). Hand and foot immersion resulted in relatively higher values of 6.89 and 5.17 μL/cm², respectively, in males, and 5.40 and 6.39 μL/cm² in females. Water adherence was affected by amount of body hair and type of exposure. Water adherence factors can be used to calculate the applied dose per unit area for exposures involving intermittent water contact.