You are here:
VALIDATION OF AMBIENT WATER QUALITY CRITERIA (AWQC) BIOACCUMULATION METHODOLOGY USING FIELD DATA FROM GREEN BAY AND THE HUDSON RIVER
Citation:
Endicott, D D., K. Sappington, AND E. L. Winchester. VALIDATION OF AMBIENT WATER QUALITY CRITERIA (AWQC) BIOACCUMULATION METHODOLOGY USING FIELD DATA FROM GREEN BAY AND THE HUDSON RIVER. Presented at 21st SETAC Annual Meeting, Nashville, TN, November 12-16, 2000.
Description:
In 1998, EPA published its draft revision to the methodology for deriving ambient water quality criteria to protect human health. Four methods were proposed to determine lipid-normalized bioaccumulation factors based on freely-dissolved water concentrations (BAFs) for nonpolar organic chemicals. These included: (1) use of directly measured BAFs, (2) use of biota sediment accumulation factors (BSAFs), (3) use of bioconcentration factors (BCFs) with food chain multipliers, and (4) use of octanol water partition coefficients (Kows) with food chain multipliers. The Green Bay Mass Balance (GBMB) study and Hudson River PCB data sets were used to validate methods 2 and 4. These data sets are particularly comprehensive and high-quality, making them logical candidates for BAF validation. Maximum likelihood estimate (MLE) unbiased mean PCB congener concentrations were calculated for each data set, which were censored at multiple detection limits. The agreement between BSAF-based (method 2) predictions and field-measured BAF values was very good. 95% exceedance (confidence) levels for the ratio of predicted to measured congener-specific BAF fell within the range 0.2 (1/5 of the predicted BAF) to 4.0 (4 x of the predicted BAF). The agreement between Kow-based (method 4) predictions and field-measured BAF values was also generally good for Green Bay. Kow-based predictions depend upon less reliable dissolved water concentration measurements for each congener, while BSAF-based predictions do not. The validation also considered the role of site-specific factors including the gradient of chemical fugacity between sediment and water and food chain multipliers, as well as the selection of reference chemicals for the BSAF-based BAF predictions.