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Human Exposure and Atmospheric Sciences


EPA scientists are developing methods, models and tools for measuring and predicting the sources and impacts of human exposure to contaminants encountered in everyday activities. Our scientists have developed models that predict how humans are exposed to chemicals and how these chemicals are absorbed into and accumulate in various organs in the body to form a dose. This information on dose can be combined with toxicity data to evaluate cumulative risk from multiple chemicals.

EPA scientists are also conducting research to evaluate relationships between air pollution sources, exposures and potential health impacts. Additionally community mapping and assessment tools are being developed by EPA scientists in partnership with communities and tribes. These tools are expected to increase the availability and accessibility of science for risk ranking and understanding the environmental health consequences of community-based decisions.

Investigating the Human Exposome
EPA scientists are evolving their research from a targeted "one exposure, one adverse effect" approach towards a broader "discovery" approach that incorporates the concept of the human "exposome" as the counterpart to the human genome. The human exposome is defined as all of the environmental chemicals, human metabolites, chemical metabolites, metabolic reaction products, as well as the byproducts and biochemistry of the symbiotic microorganisms in our gut. Unlike the human genome, which stays essentially unchanged from birth to death, the exposome changes constantly in response to the environment around you, your health state and activity, diet, and metabolic processes.

Tools to access bioavailability and bioaccessibility of arsenic and lead in contaminated soils
EPA scientists are developing rapid, reliable, inexpensive methods for assessing the bioavailability of arsenic and lead in contaminated soils. One of these methods involves the use of mice to mimic how the human digestive system absorbs arsenic. EPA scientists are also working on a chemical extraction laboratory method that mimics the human gastrointestinal system. Scientists plan to use the mouse method to validate the new lab method. If successful, researchers will be able to determine the bioavailability of these contaminants without having to rely on animal testing at all.

EPA’s ExpoCast Database
EPA’s ExpoCast database consolidates human exposure data from studies that have collected chemical measurements from homes and child care centers. Data include the amounts of chemicals found in food, drinking water, air, dust, indoor surfaces and urine. ExpoCast users can obtain summary statistics of exposure data and download datasets. EPA scientists are continuing to add internal and external chemical exposure data and advanced user interface features to ExpoCast. Users are able to link and compare the data in ExpoCast with EPA’s ToxCast database to gain greater understanding about chemical exposure and toxicity.

Consolidated Human Activity Database (CHAD)
EPA scientists have compiled detailed data on human behavior from 19 separate studies into EPA’s Consolidated Human Activity Database (CHAD). The database includes a total of more than 30,000 individual study days of detailed human behavior, with each day broken down into individual hours and activity types. The data also include demographic information which allows researchers to examine specific groups within the general population and how their unique behavior patterns influence their exposures to chemicals. Scientists at EPA, other government agencies, academia, and the private sector routinely use CHAD data in human exposure and health studies, and in models used for exposure and risk assessments that protect human health.

Understanding exposures in children’s environments
To protect children’s health, EPA scientists have conducted a series of studies to provide a better understanding of the chemical sources, pathways and routes of exposure, and other exposure factors that contribute most to children’s exposures to chemicals. EPA scientists are considering several factors in this research, including the influence of everyday environments, normal behaviors, and normal consumer product use in homes. Understanding these factors is necessary to inform key strategies for reducing children’s exposures to potentially harmful elements.

Computational atmospheric chemistry helps EPA scientists forecast future atmospheric conditions
EPA scientists have developed an innovative computational chemistry-based method called COMPCHEM that is used for predicting lifetimes and fates of atmospheric compounds. COMPCHEM consists of a set of well-established, state of the science, quantum chemistry and gas phase kinetic codes, all of which have been used in numerous studies reported in peer-reviewed literature. It is anticipated that COMPCHEM will be a cost effective tool for supplementing atmospheric chemistry data generated through laboratory studies.

Sophisticated test chambers used to simulate atmospheric conditions
EPA scientists are using experimental laboratory studies to gather and assess data on atmospheric gas phase and particulate phase chemistry in order to determine the effects that various source emissions have on humans and ecosystems. Researchers are also working on the construction and development of a new, mobile photochemical reaction chamber to be used to study the toxicity of combustion emission sources. Research results are anticipated improve understanding of how atmospheric reactions and transformations influence the toxicity of air pollutant mixtures.

Air pollution near roadways
EPA researchers are partnering with the University of Michigan on a study of the impact of vehicle emissions on near-road air quality, human exposures, and potential health effects in asthmatic children. The Near-Road Exposures to Urban Air Pollutants Study (NEXUS) is being conducted as part of EPA’s larger research program on roadway air pollution and its potential health effects. The study design will help tease out the health effects of particulate matter from diesel-burning truck and car exhaust. Particulate matter and other pollutants are being measured immediately next to the roadways and at various distances from them, to study how pollutant concentrations change as distance from the roadway increases.

Stochastic Human Exposure and Dose Simulation Model (SHEDS)
EPA’s Stochastic Human Exposure and Dose Simulation model (known as SHEDS) allows scientists to estimate total exposures and risks people face from chemicals encountered in everyday activities. SHEDS can estimate the range of total chemical exposures in a population from different exposure pathways (inhalation, skin contact, dietary and non-dietary ingestion) over different time periods, given a set of demographic characteristics. The model enhances estimates of exposure in many different contexts, and has been used to inform EPA human health risk assessments and risk management decisions.

Biomonitoring: An exposure science tool
EPA scientists are developing a suite of biomonitoring tools for assessing human exposures to environmental chemicals and their likely health responses. Specifically, EPA scientists are working to identify the chemicals to which humans are most commonly exposed; exposure levels across various groups of people; and the likely biological responses of individuals following exposure. EPA scientists have developed a biomonitoring framework for integrating and interpreting existing data, and designing new studies to answer specific research questions.

Development of Federal Reference and Equivalent Methods for measuring key air pollutants
EPA researchers are continually evaluating potential new Federal Reference Methods and Federal Equivalent Methods to foster innovation and improved measurement of atmospheric pollutants. The methods are tested in the lab and field. The scientists keep up-to-date on current air pollution sensor technologies, including availability and commercialization of emerging technologies. Adopting new technologies improves EPA’s ability to measure air pollution in new ways and locations.

Apps & Sensors for use in Human Exposure & Community Monitoring Studies
Smart phone applications and hand-held monitoring devices, or Apps and Sensors, are being developed world-wide that have the capability of detecting various air pollutants. Through collaborations with outside developers, EPA exposure scientists are working on the development, improvement, and application of these newly emerging environmental Apps and Sensors. App and Sensor technology has the potential to advance the paradigm of how air quality measurements are gathered, while reducing the cost and expense of their collection.

MicroTrac – Personal time-activity modeling
EPA scientists have developed MicroTrac, a computer model that uses GPS data on location and speed to estimate the time people spend in various “microenvironments” such as inside and outside their home, school, workplace, and motor vehicle. Using MicroTrac with personal GPS devices, accelerometers, and health monitors in exposure and health effects studies will allow scientists to link the location and activities of study participants with air pollution measurements and measures of health effects during a study.

Air Pollution Exposure Model for Individuals (EMI)
Air pollution health studies help scientists understand potential health risks people face from air pollution exposure. However, because of the cost and participant burden associated with indoor and personal air monitoring, health studies often estimate exposures using outdoor ambient measurements from central site air monitors. Unfortunately, these ambient concentration levels do not necessarily reflect personal exposures since indoor air pollutant levels can differ from ambient levels. This potential exposure error can increase the uncertainty of air pollution health risks estimated in health studies. To reduce this potential error, EPA scientists have developed an exposure model for individuals (EMI) who are participating in air pollution health studies.

Community-Focused Exposure and Risk Screening Tool (C-FERST)
In an effort to enhance community-based cumulative risk assessments, EPA exposure scientists have developed the Community-Focused Exposure and Risk Screening Tool (C-FERST) — a community mapping, information access, and assessment tool. C-FERST is expected to increase the availability and accessibility of science for risk ranking and understanding the environmental health consequences of community based decisions. It will incorporate the latest research estimating human exposures to toxic substances in the environment. In doing so, C-FERST will assist communities with the challenge of identifying and prioritizing environmental health issues and potential actions.

Tribal-Focused Environmental Risk and Sustainability Tool (Tribal-FERST)
EPA scientists are collaborating with tribes and partners to develop the Tribal-Focused Environmental Risk and Sustainability Tool (Tribal-FERST), designed to provide the best available human health and ecological science to tribes across the country. T-FERST is a community mapping, information access, and assessment tool designed to help assess risks and assist in decision making within tribal communities.

Systems Reality Modeling
EPA scientists are conducting the Systems Reality Modeling Project, which uses new and emerging technology to develop tools to help people understand chemicals in their environments and the risks they pose to health. This project uses smartphone barcode-scanning capabilities, computer game environments, and social media such as Facebook and Twitter to collect data on human activities and chemicals in the home. The data will be used to create detailed models of exposure. The scientists are developing custom-built smartphone apps to make data collection faster and more cost-effective. Ultimately, this research will provide scientists with a fast and inexpensive way to model chemical exposures and human behavior, and provide the general public with apps and other tools to find information about chemicals in their environments.

Positive Matrix Factorization (PMF) Model
EPA’s Positive Matrix Factorization (PMF) Model is one of several receptor models developed by EPA scientists that provide scientific support for current ambient air quality standards and implementation of those standards by identifying and quantifying the relative contributions that various air pollution sources contribute to ambient air quality in a community or region. Users of EPA’s PMF model provide files of sample species concentrations and uncertainties which the model uses to calculate the number of sources types, profiles, relative contributions, and a time-series of contributions.

Unmix 6.0 Model
EPA’s Unmix 6.0 Model is one of several receptor models developed by EPA scientists that provide scientific support for current ambient air quality standards and implementation of those standards by identifying and quantifying the relative contributions that various air pollution sources contribute to ambient air quality in a community or region. Users of EPA’s PMF model provide files of sample species concentrations and uncertainties which the model uses to calculate the number of sources types, profiles, relative contributions, and a time-series of contributions.

Providing air quality data for CDC’s National Environmental Public Health Tracking Network
EPA scientists are collaborating with the Centers for Disease Control and Prevention (CDC) on a CDC initiative to build a National Environmental Public Health Tracking (EPHT) network. Working with state, local and federal air pollution and health agencies, the EPHT program is facilitating the collection, integration, analysis, interpretation, and dissemination of data from environmental hazard monitoring, and from human exposure and health effects surveillance. These data provide scientific information to develop surveillance indicators, and to investigate possible relationships between environmental exposures, chronic disease, and other diseases, that can lead to interventions to reduce the burden of these illnesses. An important part of the initiative is air quality modeling estimates and air quality monitoring data, combined through Bayesian modeling, that can be linked with health outcome data.

EPA's Exposure Related Dose Estimating Model (ERDEM)
ERDEM is a physiologically-based pharmacokinetic (PBPK) and pharmacodynamic (PD) modeling system, developed by EPA scientists to predict how chemicals move through and concentrate in human tissues and body fluids. With ERDEM, scientists are able to examine how chemical exposures impact organs and tissues in the human body and determine how long they will take to be naturally processed or expressed. The ERDEM framework provides the flexibility for scientists to use either existing models or build new PBPK and PBPK/PD models to address specific science questions.

Chlordane Pesticide Dataset
EPA scientists have developed a dataset that compiles chlordane measurements from published literature in one place. The dataset provides researchers with a useful resource that taps into peer reviewed published results, summarizing and organizing the data into a user friendly tool. The dataset compiles about 2,400 enantiomer-specific measurements for five pairs of chlordane enantiomers. It consolidates information that may be useful for scientists interested in studying trends, estimating exposure and toxicity of mixtures, developing methods, and modeling enantiomers.

Consolidated Pesticide Information Dataset (CPI)
EPA scientists have developed a dataset of basic information on approximately 1,700 pesticides. The dataset was gathered from multiple sources and is in spreadsheet format. It contains a total of twenty fields, including chemical names, identification numbers, structures, and pesticide use class — such as insecticide, herbicide, and fungicide. The CPI dataset will serve as a valuable tool for those interested in pesticide mixtures, green or sustainable pesticides, development of methods and models, and other areas of pesticide research.

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