A kinetic model of copper cycling in San Francisco Bay
Brad Bessinger, Exponent, Inc.
Terry Cooke, URS Corporation
Barton Forman, URS Corporation
Vivian Lee, URS Corporation
Philip Mineart, URS Corporation
Louis Armstrong, URS Corporation

Download the Paper (PDF format) - February 2006 Related Files: Final_Bessinger_AppA.pdf (126 kB) Appendix A: Hydrodynamic and sediment-transport model calibration results Final_Bessinger_AppB.pdf (34 kB) Appendix B: Copper model sensitivity runs Tell a colleague about it. Download Adobe Reader: Access to internal hyperlinks requires the full version of Adobe® Acrobat® 7.0. If you do not have this version, some internal hyperlinks may not work. This work has been peer reviewed.

ABSTRACT:
A two-dimensional, depth-averaged kinetic model of copper cycling was developed for the San Francisco Bay estuary. Adsorption and desorption reaction rate constants were determined from experimental sorption experiments. To calibrate the model, processes related to aqueous speciation were included. The model was used to predict spatial and seasonal trends in the adsorption and desorption of copper. Model predictions show that copper is continually being re-partitioned between sediment and water. Re-partitioning is prevalent near tributary and anthropogenic sources. It also occurs between segments of the bay, in response to differences in salinity and the availability of organic ligands dissolved in the water. In areas of restricted circulation such as the South Bay, copper adsorbed onto settling particles during wet season storm events acts as a source to the water column during the dry season. The relative contribution of resuspended benthic sediment to dissolved copper concentrations is highly variable in the bay. In the North Bay, dissolved copper is principally introduced from the San Joaquin-Sacramento Delta. In the South and lower South bays, desorption from sediment during the dry season may contribute as much as 20% of the total mass input of dissolved copper. Improvement of water quality can be achieved by reducing loads; however, changes are predicted to take years.