Reducing Uncertainty in Estimating Toxaphene Loading to the Great LakesEPA Grant Number: R825246
Title: Reducing Uncertainty in Estimating Toxaphene Loading to the Great Lakes
Investigators: Swackhamer, Deborah L. , Hites, Ronald A.
Institution: University of Minnesota - Twin Cities , Indiana University - Bloomington
EPA Project Officer: Hunt, Sherri
Project Period: November 15, 1996 through November 14, 1999
Project Amount: $296,996
RFA: Air Quality (1996) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air
Description:This project will determine the current magnitude of toxaphene inputs from the atmosphere to Lakes Superior and Michigan, and put this in perspective with non-atmospheric sources using a mass balance model. The use of state-of-the-art methods to estimate atmospheric contributions of toxaphene to these Great Waters will greatly reduce the current uncertainty in these loadings, and provide invaluable data on toxaphene levels in the Great Lakes for assessing human and ecological exposures.
There are four major objectives of this research, that address two major hypotheses. The hypotheses are as follows. H #1: The higher-than-expected fish and water concentrations in Lake Superior are a result of physical limnological characteristics of the lake, and not due to non-atmospheric inputs of toxaphene. H #2: Northern Lake Michigan has received significant non-atmospheric inputs of toxaphene since 1980 from Green Bay.
Our objectives are as follows: (1) Determine the current air-water exchange of toxaphene in Lake Superior from detailed seasonal water and air measurements; (2) Use these data to construct and validate a dynamic mass balance model that will reconstruct historic inputs and losses to and from Lake Superior. Using this model we will assess whether time functions acting uniquely in Lake Superior (due to it's unique physical limnology) can explain observed water and sediment concentrations, or whether non-atmospheric inputs are implicated to explain the unusually high values; (3) Determine the relative importance of atmospheric vs. non-atmospheric loading of toxaphene to northern Lake Michigan from sediment core analyses strategically collected from Green Bay and off northern basin tributaries; and (4) Applying this model to both Lake Superior and Lake Michigan, predict future water concentrations with time, for assessing lake recovery and predicting implications for fish contamination.
The model will provide a view of the inputs over time and their impact on current concentrations, and will also provide estimates of future concentrations to Great Lakes resource managers.