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Daily soil/dust ingestion rates typically used in exposure and risk assessments are based on tracer element studies, which have a number of limitations and do not separate contributions from soil and dust. This article presents an alternate approach of modeling soil and dust ingestion via hand and object mouthing of children, using EPA's SHEDS model. Results for children 3 to <6 years old show that mean and 95th percentile total ingestion of soil and dust values are 68 and 224 mg/day, respectively; mean from soil ingestion, hand‐to‐mouth dust ingestion, and object‐to‐mouth dust ingestion are 41 mg/day, 20 mg/day, and 7 mg/day, respectively. In general, hand‐to‐mouth soil ingestion was the most important pathway, followed by hand‐to‐mouth dust ingestion, then object‐to‐mouth dust ingestion. The variability results are most sensitive to inputs on surface loadings, soil‐skin adherence, hand mouthing frequency, and hand washing frequency. The predicted total soil and dust ingestion fits a lognormal distribution with geometric mean = 35.7 and geometric standard deviation = 3.3. There are two uncertainty distributions, one below the 20th percentile and the other above. Modeled uncertainties ranged within a factor of 3–30. Mean modeled estimates for soil and dust ingestion are consistent with past information but lower than the central values recommended in the 2008 EPA Child‐Specific Exposure Factors Handbook. This new modeling approach, which predicts soil and dust ingestion by pathway, source type, population group, geographic location, and other factors, offers a better characterization of exposures relevant to health risk assessments as compared to using a single value.

The purpose of this article is to describe a standard set of age groups for exposure assessors to consider when assessing childhood exposure and potential dose to environmental contaminants. In addition, this article presents examples to show how the age groups can be applied in children's exposure assessments. A consistent set of childhood age groups, supported by an underlying scientific rationale, will improve the accuracy and comparability of exposure and risk assessments for children. The effort was undertaken in part to aid the U.S. Environmental Protection Agency (EPA) in implementing such regulatory initiatives as the 1997 Presidential Executive Order 13045, which required all federal agencies to ensure that their standards take into account special risks to children. The standard age groups include: birth to <1 month; 1 to <3 months; 3 to <6 months; 6 to <12 months; 1 to <2 years; 2 to <3 years; 3 to <6 years; 6 to <11 years; 11 to <16 years; and 16 to <21 years. These age groups reflect a consideration of developmental changes in various behavioral, anatomical, and physiological characteristics that impact exposure and potential dose. It is expected that the availability of a standard set of early‐life age groups will inform future analyses of exposure factors data as well as guide new research and data collection efforts to fill knowledge gaps.

Communities are concerned over pollution levels and seek methods to systematically identify and prioritize the environmental stressors in their communities. Geographic information system (GIS) maps of environmental information can be useful tools for communities in their assessment of environmental‐pollution‐related risks. Databases and mapping tools that supply community‐level estimates of ambient concentrations of hazardous pollutants, risk, and potential health impacts can provide relevant information for communities to understand, identify, and prioritize potential exposures and risk from multiple sources. An assessment of existing databases and mapping tools was conducted as part of this study to explore the utility of publicly available databases, and three of these databases were selected for use in a community‐level GIS mapping application. Queried data from the U.S. EPA's National‐Scale Air Toxics Assessment, Air Quality System, and National Emissions Inventory were mapped at the appropriate spatial and temporal resolutions for identifying risks of exposure to air pollutants in two communities. The maps combine monitored and model‐simulated pollutant and health risk estimates, along with local survey results, to assist communities with the identification of potential exposure sources and pollution hot spots. Findings from this case study analysis will provide information to advance the development of new tools to assist communities with environmental risk assessments and hazard prioritization.

A probabilistic model (SHEDS‐Wood) was developed to examine children's exposure and dose to chromated copper arsenate (CCA)‐treated wood, as described in Part 1 of this two‐part article. This Part 2 article discusses sensitivity and uncertainty analyses conducted to assess the key model inputs and areas of needed research for children's exposure to CCA‐treated playsets and decks. The following types of analyses were conducted: (1) sensitivity analyses using a percentile scaling approach and multiple stepwise regression; and (2) uncertainty analyses using the bootstrap and two‐stage Monte Carlo techniques. The five most important variables, based on both sensitivity and uncertainty analyses, were: wood surface residue‐to‐skin transfer efficiency; wood surface residue levels; fraction of hand surface area mouthed per mouthing event; average fraction of nonresidential outdoor time a child plays on/around CCA‐treated public playsets; and frequency of hand washing. In general, there was a factor of 8 for the 5th and 95th percentiles and a factor of 4 for the 50th percentile in the uncertainty of predicted population dose estimates due to parameter uncertainty. Data were available for most of the key model inputs identified with sensitivity and uncertainty analyses; however, there were few or no data for some key inputs. To evaluate and improve the accuracy of model results, future measurement studies should obtain longitudinal time‐activity diary information on children, spatial and temporal measurements of residue and soil concentrations on or near CCA‐treated playsets and decks, and key exposure factors. Future studies should also address other sources of uncertainty in addition to parameter uncertainty, such as scenario and model uncertainty.

Concerns have been raised regarding the safety of young children who may contact arsenic residues while playing on and around chromated copper arsenate (CCA)‐treated wood playsets and decks. Although CCA registrants voluntarily canceled the production of treated wood for residential use in 2003, the potential for exposure from existing structures and surrounding soil still poses concerns. The EPA's Office of Research and Development developed and applied the probabilistic Stochastic Human Exposure and Dose Simulation model for wood preservatives (SHEDS‐Wood) to estimate children's absorbed dose of arsenic from CCA. Skin contact with, and nondietary ingestion of, arsenic in soil and wood residues were considered for the population of children in the United States who frequently contact CCA‐treated wood playsets and decks. Model analyses were conducted to assess the range in population estimates and the impact of potential mitigation strategies such as the use of sealants and hand washing after play events. The results show predicted central values for lifetime annual average daily dose values for arsenic ranging from 10−6 to 10−5 mg/kg/day, with predicted 95th percentiles on the order of 10−5 mg/kg/day. There were several orders of magnitude between lower and upper percentiles. Residue ingestion via hand‐to‐mouth contact was determined to be the most significant exposure route for most scenarios. Results of several alternative scenarios were similar to baseline results, except for the scenario with greatly reduced residue concentrations through hypothetical wood sealant applications; in this scenario, exposures were lower, and the soil ingestion route dominated. SHEDS‐Wood estimates are typically consistent with, or within the range of, other CCA exposure models.

Because of their mouthing behaviors, children have a higher potential for exposure to available chemicals through the nondietary ingestion route; thus, frequency of hand‐to‐mouth activity is an important variable for exposure assessments. Such data are limited and difficult to collect. Few published studies report such information, and the studies that have been conducted used different data collection approaches (e.g., videography versus real‐time observation), data analysis and reporting methods, ages of children, locations, and even definitions of "mouthing." For this article, hand‐to‐mouth frequency data were gathered from 9 available studies representing 429 subjects and more than 2,000 hours of behavior observation. A meta‐analysis was conducted to study differences in hand‐to‐mouth frequency based on study, age group, gender, and location (indoor vs. outdoor), to fit variability and uncertainty distributions that can be used in probabilistic exposure assessments, and to identify any data gaps. Results of this analysis indicate that age and location are important for hand‐tomouth frequency, but study and gender are not. As age increases, both indoor and outdoor hand‐to‐mouth frequencies decrease. Hand‐to‐mouth behavior is significantly greater indoors than outdoors. For both indoor and outdoor hand‐to‐mouth frequencies, interpersonal, and intra‐personal variability are ∼60% and ∼30%, respectively. The variance difference among different studies is much bigger than its mean, indicating that different studies with different methodologies have similar central values. Weibull distributions best fit the observed data for the different variables considered and are presented in this article by study, age group, and location. Average indoor hand‐to‐mouth behavior ranged from 6.7 to 28.0 contacts/hour, with the lowest value corresponding to the 6 to <11 year olds and the highest value corresponding to the 3 to <6 month olds. Average outdoor hand‐to‐mouth frequency ranged from 2.9 to 14.5 contacts/hour, with the lowest value corresponding to the 6 to <11 year olds and the highest value corresponding to the 6 to <12 month olds. The analysis highlights the need for additional hand‐to‐mouth data for the <3 months, 3 to <6 months, and 3 to <6 year age groups using standardized collection and analysis because of lack of data or high uncertainty in available data. This is the first publication to report Weibull distributions as the best fitting distribution for hand‐to‐mouth frequency; using the best fitting exposure factor distribution will help improve estimates of exposure. The analyses also represent a first comprehensive effort to fit hand‐to‐mouth frequency variability and uncertainty distributions by indoor/outdoor location and by age groups, using the new standard set of age groups recommended by the U.S. Environmental Protection Agency for assessing childhood exposures. Thus, the data presented in this article can be used to update the U.S. EPA's Child‐Specific Exposure Factors Handbook and to improve estimates of nondietary ingestion in probabilistic exposure modeling.