Human Exposure and Atmospheric Sciences
SHEDS case studies: Examples of impact
EPA scientists have developed a number of Stochastic Human Exposure and Dose Simulation (SHEDS) models and modules which can simulate exposures to single and multiple chemicals over time for a population via multiple sources and pathways. SHEDS models have been used in a number of case studies and also by EPA for cumulative exposure assessments to support regulatory decisions. Below are examples of impact.
Case Study: Using SHEDS model to assess children’s exposure to chromated copper arsenate
After concerns were raised regarding human health effects from exposure to wood surfaces treated with Chromated Copper Arsenate (CCA), CCA registrants voluntarily elected to discontinue its use in December 2003. Regulation at the time, however, allowed for existing stocks of CCA-treated wood to be used until they were depleted. Further, CCA could still be found in many existing structures, including children’s playground equipment.
EPA scientists developed a new wood preservative scenario module for the Stochastic Human Exposure and Dose Simulation model (SHEDS-Wood), which they used to estimate exposures to toxic substances for children who frequently contact playsets and decks treated with CCA. SHEDS-Wood was applied to model several exposure pathways for CCA, including skin absorption and hand-to-mouth ingestion.
Results and impact
EPA’s SHEDS-Wood model results were used by the EPA Office of Pesticide Programs to estimate potential health risks for children exposed to residential decks and play structures treated with CCA. This research provided the data needed to advise the public on how to limit children’s health risks from existing treated wood structures such as playsets and decks.
- A probabilistic arsenic exposure assessment for children who contact CCA-treated playsets and decks, part 1: Model methodology, variability results, and model evaluation
- A probabilistic arsenic exposure assessment for children who contact CCA-treated playsets and decks, part 2: Sensitivity and uncertainty analysis
Case Study: Modeling exposure to food-borne contaminants
Humans consume a wide variety of different foods, and this often varies by demographic group and region. In the past, human diet models examined average consumption over 24-hour periods, giving researchers a general idea of the kinds of things people eat and what chemicals they are exposed to. However, this approach left significant uncertainty about specific food groups and items, making it difficult for scientists to precisely identify potential sources of chemical exposure.
EPA scientists designed a sophisticated dietary module for the Stochastic Human Exposure and Dose Simulation (SHEDS-Dietary), which simulates individual “eating events” (such as meals and snacks) and uses detailed recipes for each food item recorded in a large survey database. The model can also be paired with dose models in order to predict how ingested chemicals will amass in various parts of the human body.
Results and impact
SHEDS-Dietary provides more advanced dietary exposure analyses for researchers and regulators than previous methods were able to generate. SHEDS-Dietary has been used to inform EPA risk assessments for organophosphates found in pesticides, N-Methyl Carbamate insecticides, and the synthetic pesticides known as pyrethroids. These risk assessments will enable policymakers to make better decisions regarding acceptable levels and uses of these substances.
Case Study: Modeling human exposure to air pollutants
Knowing how and where people are exposed to air pollution is important both for identifying people at risk of health impacts from air pollution and for reducing that risk. However, understanding human exposure to air pollution is not as simple as taking a measurement of outside air at a given location. For example, people spend the majority of their time indoors at home, work, and school, where levels of air pollutants may differ from those measured outdoors. In addition, many different factors influence human exposure to air pollution, including where a person lives or works, and how much time is spent there.
Human exposure models that estimate exposure to air pollution are valuable decision-making tools for air quality managers and risk assessors. The models are used to better understand how exposures vary between people (e.g. children vs. adults), as well as over time. While air monitoring can provide actual real-world data, the information is limited to a particular time and location. Models, on the other hand, offer a way of predicting exposures under different conditions.
With human exposure models, investigators can examine a variety of scenarios to find out what the impact might be on actual exposures, such as lower air pollutant concentrations from emission reductions or more time spent in places with high pollutant concentrations (e.g. commuting).
EPA scientists have developed two different Stochastic Human Exposure and Dose Simulation (SHEDS) models that address specific kinds of air pollutant exposure. SHEDS-ATOX looks at exposures to toxic chemicals in the air, and SHEDS-PM is used to predict exposures to particulate matter. The SHEDS models account for variations in the demographics of populations, time people spend in different locations, and pollutant concentrations in locations being studied.
The primary databases used in SHEDS include demographic data from the U.S. Census; human activity pattern data from diary records; and data from human exposure measurement studies. Ambient air concentrations used as inputs in the SHEDS models can be from air monitoring data or from air quality models such as EPA’s Community Multi-scale Air Quality (CMAQ) modeling system.
Results and Impact
EPA research using SHEDS-PM found that exposure to outdoor particulate matter (PM) while indoors is an important contributor to a person’s total exposure to PM. However, the amount of exposure was found to vary across age groups due to differences in people’s activities.
Case studies where the SHEDS model has been applied in combination with other air quality models have also demonstrated how these modeling tools can be used together to improve estimates of exposure to air pollutants, especially those that vary within an urban area due to location and type of sources. EPA scientists are refining and applying the SHEDS model to understand exposures to a mixture of air pollutants that occur simultaneously, such as particles, air toxics and criteria gases from vehicle exhaust. EPA scientists have also used SHEDS-ATOX as part of a study to track the effectiveness of air quality control measures in New Haven, Conn.
SHEDS-PM and SHEDS-ATOX are additionally providing exposure information for EPA health studies on air pollution, including studies of associations between mortality, asthma, and birth outcomes with particulate matter.
- Combining Regional- and local-scale air quality models with exposure models for use in environmental health studies
- A population exposure model for particulate matter: Case study results for PM2.5 in Philadelphia, PA.
- A source-to-dose assessment of population exposures to fine PM and ozone in Philadelphia, PA, during a summer 1999 episode.