Objectives:The goals of the proposed study are 1) to quantify spatial and temporal variations in the content of both strongly and weakly copper binding compounds in a coastal environment (Boston Harbor), 2) to use these observations in conjunction with laboratory experiments to determine the main sources and chemical properties of these copper binding compounds, and 3) to determine whether spatial and temporal variations in copper binding ability can be predicted using easily measurable parameters, such as might be used in Biotic Ligand Model for predicting site specific variations in toxicity in coastal waters.Methodology:In year one we will conduct twice monthly sampling trips to eleven stations in Boston Harbor. We will use competitive ligand exhchange adsorptive cathodic stripping voltammetry (CLE-ACSV), with new calibration and data interpretation techniques to determine the content of both strongly and weakly binding copper binding compounds in these samples. This data will be used to formulate hypotheses regarding sources of copper binding compounds in Boston Harbor. In year two we will concentrate on testing these hypotheses with more targeted observations at a small number of sites in the harbor, and with laboratory experiments. In both years one and two we will test a variety of water parameters for their usefulness in predicting content and binding ability of copper binding compounds in coastal waters, and attempt to formulate a model that can predict spatial and temporal variability in copper binding ability of different coastal water samples.Rationale:Our results will play a crucial role in the development of a model to better predict copper toxicity to aquatic organisms in coastal environments. The EPA has already proposed the use of such a model (the ‘Biotic Ligand Model’) for developing realistic, site specific water quality criteria for metals, especially copper, in freshwaters. The EPA, state regulatory agencies, and industry are all interested in adapting the Biotic Ligand Model for use in coastal environments. Our work will be used for evaluating the feasibility of such an adaptation and determining the parameters required for its implementation.