Uncertainty Analyses of Models in Integrated Environmental Assessments

The summary for the Uncertainty Analyses of Models in Integrated Environmental Assessments grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the Environmental Protection Agency, which is the U.S. government agency offering this grant.

Uncertainty Analyses of Models in Integrated Environmental Assessments: Grants awarded under this announcement may involve Geospatial Information. The U.S. Environmental Protection Agency (EPA), as part of its Science to Achieve Results (STAR) program, is seeking applications proposing interdisciplinary research in the formal treatment of uncertainty when models are used to conduct integrated environmental assessments. Integrated assessments use findings, data, and methods across different disciplines to generate information about a particular issue. For example, to assess the impact of mercury on public health and the environment, EPA integrated results from air dispersion models, exposure models, health effects models, and economic models (EPA 2005). To facilitate integrated assessments, models are used either (1) as a single, overarching model that integrates all pertinent information; or, as in EPAs impact assessment for mercury, (2) as a suite of multiple models, with each model focusing on a specific aspect of the integrated assessment. In either case, NCER is interested in research that explores two types of uncertainties: (1) uncertainties within the models themselves, i.e. within their underlying data and hypotheses; and (2) uncertainties that arise during decision-making, as stakeholders discuss the weight of scientific evidence embodied within these models.