Modeling transport and deposition of contaminants to ecosystems of concern: a case study for the Laurentian Great Lakes

Transfer efficiency (TE) is introduced as a model output that can be used to characterize the relative ability of chemicals to be transported in the environment and deposited to specific target ecosystems. We illustrate this concept by applying the Berkeley-Trent North American contaminant fate model (BETR North America) to identify organic chemicals with properties that result in efficient atmospheric transport and deposition to the Laurentian Great Lakes. By systematically applying the model to hypothetical organic chemicals that span a wide range of environmental partitioning properties, we identify combinations of properties that favor efficient transport and deposition to the Lakes. Five classes of chemicals are identified based on dominant transport and deposition pathways, and specific examples of chemicals in each class are identified and discussed. The role of vegetation in scavenging chemicals from the atmosphere is assessed, and found to have a negligible influence on transfer efficiency to the Great Lakes. Results indicate chemicals with octanol-water (K-ow) and air-water (K-aw) partition coefficients in the range of 10(5)-10(7) and 10(-4)-10(-1) combine efficient transport and deposition to the Great Lakes with potential for biaccumulation in the aquatic food web once they are deposited. A method of estimating the time scale for atmospheric transport and deposition process is suggested, and the effects of degrading reactions in the atmosphere and meteorological conditions on transport efficiency of different classes of chemicals are discussed. In total, this approach provides a method of identifying chemicals that are subject to long-range transport and deposition to specific target ecosystems as a result of their partitioning and persistence characteristics. Supported by an appropriate contaminant fate model, the approach can be applied to any target ecosystem of concern. (C) 2003 Elsevier Ltd. All rights reserved.