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The San Francisco Bay (California, USA) is a water body listed as impaired because of Hg contamination in sport fish for human consumption, as well as possible effects on resident wildlife. A legacy of Hg mining in local watersheds and Hg used in Au mining in the Sierra Nevada (USA) has contributed to contamination seen in the bay, with additional more recent and ongoing inputs from various sources. Methylmercury is the species of Hg most directly responsible for contamination in biota, so better understanding of its sources, loads, and processes was sought to identify the best means to reduce impacts. A regional scale model of San Francisco Bay was developed to characterize major methylmercury inputs and processes. The model was used to evaluate the potential impact of uncertainties in estimates for methylmercury loading pathways and environmental processes, identify major data gaps, and explore management prospects for reducing methylmercury contamination. External loading pathways considered in the mass balance include methylmercury loads entering via atmospheric deposition to the bay surface, and discharges from the Sacramento/San Joaquin Delta, local watersheds, municipal wastewater, and fringing wetlands. Internal processes considered include exchange between bed and suspended sediments and the water column, in situ production and demethylation, biological uptake, and losses via hydrologic transport to the ocean through the Golden Gate. In situ sediment methylation and demethylation were dominant sources and losses determining ambient steady-state concentrations in the model, with changes in external loads and export causing smaller changes. Better information on methylation and demethylation is thus most critical to improving understanding of methylmercury balances and management. Environ. Toxicol. Chem. 2011;30:88-96. © 2010 SETAC [ABSTRACT FROM AUTHOR]

Abstract: A mass budget of polybrominated diphenyl ethers (PBDEs) in San Francisco Bay is developed as a first step towards understanding the local sources and transport processes controlling PBDE fate in a highly urbanized estuary. Extensive monitoring of PBDEs in estuarine water and sediment, freshwater tributaries, air, and wastewater effluents and sludges were integrated with a mass budget model to provide a synthetic view of these emerging contaminants. The Bay inventories of BDE 47 and BDE 209 in 2006 were estimated to be 33±3 kg and 153±45 kg, respectively. Empirically derived estimates of annual inputs of BDE 47 and BDE 209 from all quantifiable external sources ranged from 11 to 28 kg/y and 22 to 24 kg/y, respectively. BDE 47 loads were dominated by wastewater while runoff from local tributaries represented the largest contributor to BDE 209 loads. Model results suggest the Bay PBDE inventory is highly sensitive to changes in external loads, with degradation and outflow being the major processes governing PBDE fate. The mass budget presented provides a framework for integrating future monitoring and modeling efforts. [Copyright &y& Elsevier]

Abstract: An edge detection algorithm was developed that is capable of objectively detecting significant edges in remotely sensed images of the surface ocean. The algorithm utilizes a gradient-based edge detector that is less sensitive to noise in the input image than previously used detectors and has the ability to detect edges at different length scales. The algorithm was used to provide a statistical view of surface front occurrences in the Southern California Bight using six years of satellite observations of sea-surface temperature (AVHRR) and chlorophyll (SeaWiFS). Regions of high front occurrence probability were identified near capes, headlands, and islands. In onshore direction, chlorophyll concentration increased and temperature decreased, indicative of coastal upwelling. The algorithm was further applied to coincident time series of temperature and chlorophyll to investigate the event-scale dynamics of mesoscale features and the spatial relationships between physical and biological processes. A simple scheme for identifying and classifying eddies delineated by the edge detection algorithm was developed to yield a census of eddy occurrence in the Southern California Bight. [Copyright &y& Elsevier]