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Modeling the Long-Term Fate and Bioaccumulation of Mercury, PCB s, DDT s and PBDE s in an Enclosed EstuaryEPA Grant Number: FP917287
Title: Modeling the Long-Term Fate and Bioaccumulation of Mercury, PCB s, DDT s and PBDE s in an Enclosed Estuary
Investigators: Greenfield, Ben K
Institution: University of California - Berkeley , Ernest Orlando Lawrence Berkeley National Lab
EPA Project Officer: Jones, Brandon
Project Period: September 1, 2011 through August 31, 2014
Project Amount: $126,000
RFA: STAR Graduate Fellowships (2011) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Fellowship - Ecosystem Services: Aquatic Systems Ecology
This study will use pollutant fate and exposure models to forecast the impacts of alternative management actions across a suite of pollutants in aquatic ecosystems. An additional objective is to determine the role that spatial heterogeneity and variability among individuals will play in influencing the health effects to the human population exposed to these pollutants.
The research plan is to use open-source multimedia contaminant fate, transport, exposure and toxicity models to contrast the time course of pollutant loss from aquatic ecosystems under alternative management scenarios. The toxicity evaluation will focus on forecasting changes in human health effects (i.e., disease burden) resulting from different management actions. This work will focus on potential pollutants of concern, evaluating risks at San Francisco Bay and the Mississippi River Basin. The study plans to compare legacy (e.g., mercury, PCBs) versus emerging (e.g., current use pesticides, PBDEs) pollutants to determine which is most likely to respond to management actions.
This work will build and verify new model extensions to evaluate the fate and exposure pathways of emerging pollutants, including PBDEs, current use pesticides and next generation biofuels compounds. The modeling activities will address three areas. First, by comparing among priority pollutants this study will aid in determining the likely benefit of alternative management approaches. It is predicted that compounds that have been used and released for over a century (e.g., Hg) or were banned decades ago (PCBs) will be far less responsive to management interventions than recently introduced compounds (e.g., PBDEs, current use pesticides). Second, the study will contrast the role of aquatic sediment versus other sources (e.g., terrestrial soils and ambient air) for pollutant exposure to humans. It is hypothesized that surface sediments will be the major source of legacy pollutants to human exposure, via the mechanism of food web trophic transfer, and consumption of local seafood and wildlife. In contrast, the exposure pathways for recently introduced compounds will be more complex, potentially requiring management interventions for multiple pathways. Finally, the study will evaluate the roles of heterogeneity for the extent and time course of human exposure to pollutants. Both spatial heterogeneity in pollutant fate processes and variability in the exposed human population will be examined. For example, it is hypothesized that in San Francisco Bay margin locations, accounting for the spatial and temporal heterogeneity in sediment processes will delay predicted contaminant loss from the system. Human population exposure will be assessed in a spatially explicit fashion, with model runs used to generate statistical distributions of exposure and movement of multiple simulated individuals. This will provide greater realism in depicting population-level variation in contaminant exposure.
Potential to Further Environmental/ Human Health Protection
At regional and local scales, extensive technical and economic resources often are devoted to cleaning up legacy and emerging pollutants. With the continued introduction and use of new chemical compounds, many potential pollutants are emerging in natural waters. In many cases, exposure pathways and risks of greatest concern for future pollutants have not been yet thoroughly evaluated. In addition to informing local management, this study’s technical activities will contribute to science and management applications for polluted waters nationwide. The model simulations of pollutant time trends should broadly interest scientists and managers concerned with forecasting legacy pollutant decline. Additionally, this work should provide useful case studies in the treatment of variability in determining pollutant risks.