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Ecosystems Research


Everyday humans and animals come into contact with environmental stressors that pose potentially dangerous health risks. EPA scientists have developed various methods, measurements and models to assess and predict exposures of humans and ecosystems to these contaminants. Thorough studies using state-of-science metabolomics and genomic methods, EPA exposure science provides information to assist in the development of approaches to reduce exposures and safeguard human health and the environment.


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.

Quantitative Microbial Risk Assessment

Quantitative Microbial Risk Assessment, or QMRA, is an approach that brings together information from epidemiology studies, dose/response models, and exposure data to determine the probability of human infection due to exposure to waterborne pathogens. EPA scientists are using a QMRA approach in sampling urban and agricultural runoff discharges in streams and other water bodies. Information from this research is expected to improve scientific understanding of relationships between sources of specific disease producing pathogens and fecal contamination at watershed scales.

Data for Environmental Modeling (D4EM)

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.

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