EPA exposure scientists have developed methods, predictive modeling systems and metabolomics-based tools for characterizing and assessing human and ecosystem exposure to chemicals — data that is necessary to inform risk assessments. These tools are helping scientists define possible adverse outcomes and provide data to inform the development of strategies for reducing exposures and protecting human and ecosystem health.
The Environmental Fate Simulator, or EFS, is a computational tool being designed to screen organic chemicals for possible routes of human and ecological exposure. The EFS compiles all available data on chemicals and chemical processes, integrating this information with state-of-the-art computer tools that store information about chemical structure and reactions. The tool is being designed to systematically capture and use this science to assist the agency's pesticide and pollution programs in conducting high-volume, high-speed assessments for registration of new chemicals and re-registration of existing chemicals.
EPA scientists are developing metabolomics-based tools for characterizing changes in metabolic substances produced by animal systems in the presence of different stressor chemicals and scenarios. These tools are helping scientists define possible adverse outcomes in fish and wildlife as a result of exposure to specific stressors. The researchers have advanced this program by using modeling systems to study known estrogenic chemicals and exposures to modeled species. They are now working to apply the technology to “real world” exposures and are developing biomarkers of exposure for humans and important ecological species.
EPA scientists are developing new methods for detecting nanomaterials in the environment and conducting research to quantify and understand how nanomaterials move in both terrestrial and aquatic environments throughout their lifecycle. These data will assist health and ecological researchers in determining the potential of nanomaterials to cause adverse health or environmental effects.
EPA ecosystems researchers have developed a predictive modeling system known as SPARC (SPARC Performs Automated Reasoning in Chemistry) for estimating chemical reactivity parameters and physical properties for a wide range of organic molecules. This information is needed to be able to predict the fate and transport of pollutants in the environment. SPARC is being designed to incorporate multiple mathematical approaches to estimate important chemical reactions and behavior. It will then interface directly with air, water, and land models to provide scientists with data that can inform risk assessments and help prioritize toxicity-testing requirements for regulated chemicals.
EPA scientists have developed a computerized system called MetaPath to support the rapid evaluation of pesticide applications submitted to EPA for registration and re-registration. When a pesticide application is submitted, the system allows EPA risk assessors to efficiently evaluate the chemical against similarly registered compounds to determine the potential for the new chemical, its metabolites or degradation products, to result in harm to humans or the environment. Data analysis tools built into MetaPath permit comparisons across species, sample matrices, and chemical structures that weren’t previously possible, as well as data needed for metabolism simulators.
EPA scientists have developed a prototype cloud computing-base knowledge management system to support ecological risk decisions mandated under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) and the Endangered Species Act. The “ubertool” dashboard infrastructure integrates the processing of model results for over a dozen commonly-used EPA aquatic and terrestrial regulatory models and supporting datasets.
EPA scientists are analyzing potential pollutant exposures from industrial waste by assessing human and ecosystem exposure during their treatment, storage and disposal, and also when these materials are reused in products. Using complex mathematical modeling systems, the scientists are studying the transport of potentially hazardous pollutants during their lifecycle to soil, water and air to assess how industrial byproduct reuse affects human and ecological exposure.
Data for environmental modeling, or D4EM, is a comprehensive set of tools that obtains and processes environmental data for mathematical models. D4EM is a programming library with a component-based architecture that can be integrated with other modeling applications. Programmers can use D4EM to perform data management and processing tasks inside a specialized application. The user interacts with data through a customized MapWindow GIS user interface for obtaining and manipulating data, validating data for completeness, and generating model-specific data files.
- Fact Sheet: Chemical Safety for Sustainability research
- Chemical safety exposure research tools
- Fact Sheet: EPA Green Chemistry research
- EPA nanotechnology research
- Listening to Loons: Mercury and Merganser
- PCBs in caulk
- About the Office of Chemical Safety and Pollution Prevention (OCSPP)
- Pesticides: Regulating pesticides