Exposure Research: Health
Methods, Models, Tools and Databases
- Virus Methods
(EPA Manual of Methods for Virology) The manual (EPA 600-4-84-013) describes in detail procedures for detecting viruses in environmental samples. See revised and new chapters here:
- Chapter 12. Identification of Enteroviruses
- Chapter 13. Data Analysis and Experimental Design (not yet available in PDF format)
- Chapter 14. Concentration and Processing of Waterborne Viruses by Positive Charge 1MDS Cartridge Filters and Organic Flocculation
- Chapter 15. Total Culturable Virus Quantal Assay
- Chapter 16. Procedures for Detecting Coliphages
- CMAQ Model
CMAQ is an air quality model and software suite designed to model multiple pollutants at multiple scales. CMAQ allows regulatory agencies and state governments to evaluate the impact of air quality management decisions, and gives scientists the ability to probe, simulate, and understand chemical and physical interactions in the atmosphere.
- Dietary Exposure Potential Model (DEPM)
Dietary models can be used for identifying the importance of diet relative to other exposure pathways and indicating the potential for high exposure of certain populations. Existing consumption and contaminant residue databases, normally developed for purposes such as nutrition and regulatory monitoring, contain information to characterize dietary intake of environmental chemicals. A model and database system, termed the Dietary Exposure Potential Model (DEPM), correlates extant food information in a format for estimating dietary exposure.
- Physiological and Anatomical Visual Analytics (PAVA)
In order to better address issues regarding chemical safety, EPA scientists have developed a new web-based modeling tool, known as PAVA (Physiological and Anatomical Visual Analytics), that lets users import and combine results from multiple computer models and transforms them into animated visualizations. The absorption, distribution, metabolism, and excretion results are automated and then rendered in a way that lets scientists see changes in chemical concentrations in specific tissues over time — from chemical to chemical, scenario to scenario, and model to model.
- SHEDS - Multimedia
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.
- Exposure Related Dose Estimating Model (ERDEM)
ERDEM is a physiologically-based pharmacokinetic (PBPK) model with a graphical user interface (GUI) front end. Such a mathematical model was needed to make reliable estimates of the chemical dose to organs of animals or humans because of uncertainties of making route-to route, low-to-high exposure, and species-to-species extrapolations when there are exposures to one, or to multiple chemicals.
- Fused Air Quality Surfaces using Downscaling
Based on statistical modeling research in the development of fused space-time predictive surfaces for air quality, this web page provides access to the most recent daily O3 and PM2.5 surfaces. As new and improved statistical models become available, we plan to continually update these surfaces.
- Fused Discrete Air Quality Surfaces
This web page provides access to discrete, daily O3 and PM2.5 predictive surfaces. Here, a space-time hierachical Bayesian model (see HBMetadataAir for reference and model description) is used to fuse daily ozone (8-hr maximum) monitoring data from the National Air Monitoring Stations/State and Local Air Monitoring Stations (NAMS/SLAMS) with gridded output from the Models-3/Community Multi-Scale Air Quality Model (CMAQ).
Exposure Analysis Modeling System (EXAMS)
EXAMS is a modeling system that supports development of aquatic ecosystem models for rapid evaluation of the fate, transport, and exposure concentrations of synthetic organic chemicals like pesticides, industrial materials, and leachates from disposal sites. The system is able to generate and summarize data critical for ecological risk assessments. Much of the data required for EXAMS to function has been collected historically. This allows data needs to be met for a certain projects without intensive field sampling.
Framework for Risk Analysis of Multi-Media Environmental Systems (FRAMES)
FRAMES is a software-based modeling system that takes collections of models and modeling tools and applies them to real world problems. FRAMES facilitates communication between models, supporting the passage of data that helps simulate complex environmental processes. The tool has been used in EPA assessments in support of the Hazardous Waste Identification Rule (HWIR), which establishes contaminant concentration levels in industrial waste streams that are considered safe for disposal.
- 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.
- 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.
Virtual Beach (VB)
When recreational waters are contaminated by bacteria and other microorganisms, beach managers need to act quickly to protect public health. EPA scientists developed Virtual Beach, a software suite that uses data on beach location, local hydrology, land use, wave height, and weather to create models that can predict bacteria and other waterborne pathogen outbreaks at saltwater and freshwater beaches before they happen. Using Virtual Beach, beach managers can issue same-day beach closures or health advisories to protect the health of swimmers and the surrounding community.
Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE)
EPA’s Supercomputer for Model Uncertainty and Sensitivity Evaluation, or SuperMUSE, enhances quality assurance in environmental models and applications. Uncertainty analysis (UA) and sensitivity analysis (SA) remain critical, though often overlooked steps in the development and evaluation of computer models. As a result of the SuperMUSE hardware and software technology, EPA can now better investigate new and existing UA and SA methods. EPA can also more easily achieve UA/SA of complex, Windows-based environmental models, allowing scientists to conduct analyses that have, to date, been impractical to consider.
- Environmental Relative Moldiness Index (ERMI) Research Tool
A research tool, called the Environmental Relative Moldiness Index (ERMI), has been developed and is being evaluated in research studies by the U.S. Environmental Protection Agency (EPA) Office of Research and Development (ORD). In the research studies, dust samples are collected in a home and the DNA from some of the many molds contained in the house dust is extracted and analyzed. The DNA results are then used to characterize the concentrations of the molds in the dust sample. The sample results are then compared to the ERMI, an index or scale of moldiness. The analysis can be used by researchers in the U.S. to estimate the amount of mold in a home as well as indicate some of the types of mold that are present. As research continues, the index will be refined.
- Most Probable Number (MPN) Software Program
This program is used for calculating MPN (Most Probable Number) and confidence limits values. The upgraded Windows-based MPN Calculator integrates into a single file and replaces the old DOS-based MPN.exe and MPNV.exe programs. Usage of the latter was required by Section VIII of the ICR Microbial Laboratory Manual.
- 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.
- 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.
- Probabilistic Reverse dOsimetry Estimating Exposure Distribution (PROcEED)
Probabilistic Reverse dOsimetry Estimating Exposure Distribution (PROcEED) is a web-based application used to conduct probabilistic reverse dosimetry calculations. The tool is used for estimating a distribution of exposure concentrations likely to have produced biomarker concentrations measured in a population.
- Expocast Database
EPA's ExpoCast research project advances characterization of the exposure required to translate findings in computational toxicology to support risk assessment.
- 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.
- Human Exposure Database System (HEDS)
An integrated database system that contains chemical measurements, questionnaire responses, documents, and other information related to EPA research studies of the exposure of people to environmental contaminants.
- 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.
- Environmental Geophysics
This website beta version contains information on geophysical methods, references to geophysical citations, and a glossary of geophysical terms related to environmental applications.
- Statistically Fused Air Quality Surfaces using Downscaling
This web page provides access to the most recent O3 and PM2.5 surfaces datasets.
- PPCP (Reference Databases)
Published Literature Relevant to the Issues Surrounding PPCPs as Environmental Contaminants.