Chemical log Kow Number Mean Mean BAFs log BAF R f d BAF R f d PCBs 32 5.44 4 5.84 6.84e+ 05 33 5.60 8 6.18 1.50e+ 06 40 5.66 8 5.94 8.72e+ 05 42 5.76 4 6.61 4.06e+ 06 44 5.75 8 6.54 3.46e+ 06 45 5.53 4 6.04 1.09e+ 06 46 5.53 8 5.71 5.08e+ 05 49 5.85 4 6.82 6.61e+ 06 52 5.84 8 6.69 4.90e+ 06 53 5.62 4 7.02 1.04e+ 07 63 6.17 4 7.25 1.77e+ 07 64 5.95 4 6.94 8.80e+ 06 66 6.20 4 7.26 1.83e+ 07 74 6.20 8 7.51 3.23e+ 07 77 6.36 4 6.99 9.68e+ 06 81 6.36 4 7.35 2.24e+ 07 82 6.20 8 7.17 1.48e+ 07 83 6.26 4 7.55 3.53e+ 07 84 6.04 4 7.65 4.50e+ 07 85 6.30 8 7.58 3.83e+ 07 87 6.29 4 7.59 3.89e+ 07 91 6.13 8 7.23 1.69e+ 07 92 6.35 4 7.64 4.32e+ 07 95 6.13 4 7.41 2.55e+ 07 97 6.29 4 6.90 7.95e+ 06 99 6.39 8 7.54 3.49e+ 07 100 6.23 4 7.64 4.40e+ 07 101 6.38 8 7.73 5.43e+ 07 105 6.65 8 8.34 2.18e+ 08 110 6.48 8 7.68 4.74e+ 07 118 6.74 8 8.31 2.04e+ 08 119 6.58 4 8.33 2.12e+ 08 126 6.89 4 8.56 3.63e+ 08 128 6.74 8 8.39 2.44e+ 08 129 6.73 8 8.03 1.06e+ 07 130 6.80 4 8.30 1.98e+ 08 132 6.58 4 7.65 4.47e+ 07 208 Table 2.4.2: Mean BAF R d s from Lake Ontario BSAFs for Salmonids ( continued)

Chemical log Kow Number Mean Mean BAFs log BAF R d BAF R d PCBs 136 6.22 4 8.39 2.44e+ 08 138 6.83 4 8.59 3.88e+ 08 141 6.82 8 8.31 2.03e+ 08 146 6.89 8 8.34 2.18e+ 08 149 6.67 8 7.98 9.66e+ 07 151 6.64 8 8.16 1.45e+ 08 153 6.92 8 8.52 3.31e+ 08 156 7.18 4 8.91 8.12e+ 08 158 7.02 4 8.37 2.32e+ 08 167 7.27 4 8.27 1.87e+ 08 171 7.11 4 8.67 4.72e+ 08 172 7.33 4 8.63 4.24e+ 08 174 7.11 8 8.40 2.51e+ 08 177 7.08 8 8.64 4.38e+ 08 178 7.14 8 8.83 6.80e+ 08 180 7.36 8 9.05 1.13e+ 09 183 7.20 8 8.94 8.63e+ 08 185 7.11 8 8.53 3.36e+ 08 189 7.71 4 8.72 5.30e+ 08 194 7.80 8 9.23 1.72e+ 09 195 7.56 4 8.97 9.32e+ 08 197 7.30 4 8.50 3.20e+ 08 198 7.62 4 9.60 3.98e+ 09 201 7.62 8 8.89 7.70e+ 08 205 8.00 8 8.75 5.64e+ 08 206 8.09 8 8.84 6.90e+ 08 207 7.74 8 8.77 5.92e+ 08 209 8.18 8 8.13 1.35e+ 08 24+ 27 5.40 8 5.78 5.98e+ 07 28+ 31 5.67 8 6.31 2.06e+ 06 37+ 42 5.80 4 6.76 5.70e+ 06 47+ 48 5.82 8 6.91 8.18e+ 06 41+ 64+ 71 5.87 4 6.70 4.97e+ 06 56+ 60 6.11 4 6.76 5.82e+ 06 70+ 76 6.17 8 7.29 1.96e+ 07 66+ 95 6.17 4 7.06 1.14e+ 07 56+ 60+ 81 6.19 4 7.06 1.16e+ 07 84+ 92 6.20 4 7.45 2.82e+ 07 209 Table 2.4.2: Mean BAF R d s from Lake Ontario BSAFs for Salmonids ( continued)

Chemical log Kow Number Mean Mean BAFs log BAF R d BAF R d PCBs 87+ 97 6.29 4 7.81 6.46e+ 07 137+ 176 6.80 4 8.03 1.07e+ 08 138+ 163 6.91 4 8.42 2.64e+ 08 156+ 171+ 202 7.18 4 8.44 2.76e+ 08 182+ 187 7.19 4 8.89 7.85e+ 08 157+ 200 7.23 4 8.59 3.86e+ 08 170+ 190 7.37 8 8.98 9.53e+ 08 195+ 208 7.64 4 8.66 4.58e+ 08 196+ 203 7.65 8 8.92 8.27e+ 08 PCDDs 2378 TCDD 7.02 4 6.95 9.00e+ 06 12378 PeCDD 7.50 4 7.40 2.49e+ 07 123478 HxCDD 7.80 4 7.22 1.65e+ 07 123678 HxCDD 7.80 4 6.83 6.71e+ 06 123789 HxCDD 7.80 4 6.87 7.44e+ 06 1234678 HpCDD 8.20 4 6.85 7.16e+ 06 OCDD 8.60 4 6.63 4.29e+ 06 PCDFs 2378 TCDF 6.50 4 6.34 2.16e+ 06 12378 PeCDF 7.00 4 6.28 1.89e+ 06 23478 PeCDF 7.00 4 7.14 1.38e+ 07 123478 HxCDF 7.50 4 6.32 2.07e+ 06 123678 HxCDF 7.50 4 6.70 5.07e+ 06 123789 HxCDF 7.50 4 7.23 1.70e+ 07 234678 HxCDF 7.50 4 7.27 1.84e+ 07 1234678 HpCDF 8.00 4 5.98 9.47e+ 05 1234789 HpCDF 8.00 4 7.53 3.35e+ 07 OCDF 8.80 4 6.96 9.10e+ 06 0 5 10 15 20 25 30 1 > 1 2 > 2 4 > 4 6 > 6 8 > 8 10 > 10 12 > 12 14 > 14 16 > 16 18 > 18 20 Range of Ratios Number of Occurrences Exhibit 2.4.2: Ratios between Oliver and Niimi ( 1988) measured BAFs and BAFs predicted from Oliver and Niimi ( 1988) 0 5 10 15 20 25 1 > 1 2 > 2 4 > 4 6 > 6 8 > 8 10 Range of Ratios Number of Occurrences Exhibit 2.4.4: Ratios between BAFs predicted from EPA BSAFs and BAFs predicted from Oliver and Niimi ( 1988) BSAFs Exhibit 2.4.7: Ratios between Oliver and Niimi ( 1988) measured BAFs and BAFs predicted from Green Bay BSAFs 0 5 10 15 20 25 1 > 1 2 > 2 4 > 4 6 > 6 8 > 8 10 Range of Ratios Number of Occurrences Exhibit 2.4.9: Ratios BAFs predicted from EPA BSAFs and BAFs predicted from Green Bay BSAFs 0 5 10 15 20 25 30 1 > 1 2 > 2 4 > 4 6 > 6 8 > 8 10 > 80 90 Range of Ratios Number of Occurrences 24Note: Equilibrium partitioning theory would predict BCF R f d approximately equal to K ow, thus the BCF R f d would not be trophic level dependent.

219 <IP_ADDRESS> Baseline BAF Derived from a Laboratory Measured BCF and Food Chain Multiplier For the third tier in the data preference hierarchy for nonpolar organic chemicals, EPA recommends the use of a predicted BAF derived from a technically defensible, laboratory measurement of the BCF and an appropriate food chain multiplier ( FCM). A FCM is determined as the ratio of the baseline BAF ( BAF R f d) of an organism at a particular trophic level to the baseline BCF ( usually determined for trophic level one). 24 FCMs with values greater than 1.0 indicate biomagnification and typically apply to organic chemicals with K ow values between 4.0 and 9.0. Laboratory measured BCFs are preferred over predicted BCFs because laboratory measured BCFs inherently account for effects of chemical metabolism on the BCF during its measurement.

The equation for calculating a baseline BAF from a laboratory measured BCF is:

Baseline BAF fd R ' ( FCM) Measured BCF t T f fd & 1 1 f R ( Equation 2.4.17)

where:

Baseline BAF R f d = BAF expressed on a freely dissolved and lipid normalized basis BCFtT = BCF based on total concentration in tissue and water f R = Fraction of the tissue that is lipid f fd = Fraction of the total chemical in the test water that is freely dissolved FCM = Food chain multiplier obtained from Tables 2.4.4, 2.4.5, or 2.4.6 by linear interpolation for the appropriate trophic level as necessary ( or from appropriate field data)

For each trophic level, the species mean baseline BAF is calculated as the geometric mean if more than one acceptable baseline BAF is predicted from laboratory measured BCFs for a given species. For each trophic level, the trophic level specific BAF is calculated as the geometric mean of the species mean baseline BAFs based on laboratory measured BCFs. 220 Procedural and Quality Assurance Requirements for Measured BCFs A measured BCF derived from results of a laboratory exposure study is acceptable if the study has met certain specific technical criteria. These criteria include, but are not limited to:

1. The test organism should not be diseased, unhealthy, or adversely affected by the concentration of the chemical because these attributes may alter accumulation of chemicals by otherwise healthy organisms.

2. The total concentration of the chemical in the water should be measured and should be relatively constant during the steady state time period.

3. The organisms should be exposed to the chemical using a flow through or renewal procedure.

4. For organic chemicals, the percent lipid should be either measured or reliably estimated for the tissue used in the determination of the BCF.

5. For organic chemicals with log K ow greater than four, the concentrations of POC and DOC in the test solution should be either measured or reliably estimated. For organic chemicals with log K ow less than four, virtually all of the chemical is predicted to be freely dissolved, except in water with extremely high DOC and POC concentrations, which is not characteristic of laboratory dilution water used in BCF determinations.

6. Laboratory measured BCFs should be determined using fish species, but BCFs determined with molluscs and other invertebrates may be used with caution. For example, because invertebrates metabolize some chemicals less efficiently than vertebrates, a baseline BCF determined using invertebrates is expected to be higher than a comparable baseline BCF determined using fish.

7. If laboratory measured BCFs increase or decrease as the concentration of the chemical increases in the test solutions in a bioconcentration test, the BCF measured at the lowest test concentration above control concentrations should be used ( i. e., a BCF should not be calculated from a control treatment). The concentrations of an inorganic chemical in a bioconcentration test should be greater than normal background levels and greater than levels required for normal nutrition of the test species if the chemical is a micronutrient, but below levels that adversely affect the species. Bioaccumulation of an inorganic chemical might be overestimated if concentrations are at or below normal background levels due to, for example, nutritional requirements of the test organisms.

8. For inorganic chemicals, BCFs should be used only if they are expressed on a wet weight basis. BCFs reported on a dry weight basis cannot be converted to wet weight 221 unless a conversion factor is measured or reliably estimated for the tissue used in the determination of the BAF.

9. BCFs for organic chemicals may be based on measurement of radioactivity only when the BCF is intended to include metabolites, when there is confidence that there is no interference due to metabolites, or when studies are conducted to determine the extent of metabolism, thus allowing for a proper correction.

10. The calculation of the BCF must appropriately address growth dilution.

11. Other aspects of the methodology used should be similar to those described by ASTM ( 1990).

In addition, the magnitude of the octanol water partition coefficient ( K ow) and the availability of corroborating BCF data should be considered. For example, some chemicals with high log K ow s may require longer than 28 days to reach steady state conditions between the organism and the water column. As with BAFs, the BCFs should be divided by the mean lipid fraction to express the value on a lipid normalized basis.

Food Chain Multipliers The food chain multiplier represents a measure of a chemical's tendency to biomagnify in aquatic food webs. For non polar organic chemicals, FCMs can be determined from bioaccumulation models or directly from field data ( tissue residues).

For model derived FCMs, EPA recommends using the food web model by Gobas ( 1993) to determine FCMs for nonpolar organic chemicals. There are several advantages to using the Gobas ( 1993) model. First, uptake into both benthic and pelagic food chains is measured, incorporating exposure of organisms to chemicals from both the sediments and the water column. Second, the input data needed to run the model can be readily defined. Third, the model predicted BAFs ( which are used to derive the FCMs) are in agreement with field measured BAFs for chemicals, even those with very high log K ow s. Finally, the model predicts chemical residues in benthic organisms using equilibrium partitioning theory, which is consistent with EPA's sediment quality criteria effort.

The Gobas ( 1993) model predicts the chemical residues in the organisms, which are then used to estimate BAFs for each species in the food chain: 222 BAF fd R ' C R C fd w ( Equation 2.4.18)

FCM ' BAF fd R K ow ( Equation 2.4.19) where:

= Lipid normalized BAF using the freely dissolved concentration in the water BAF fd R = Freely dissolved concentration of the chemical in the water column C fd w = Lipid normalized concentration in appropriate tissue C R Food chain multipliers are then calculated from the predicted BAF R f ds using the following equation:

where:

K ow = n octanol/ water partition coefficient Data Requirements to Predict the Food Chain Multiplier. The food chain model by Gobas ( 1993) requires specific data on the structure of the food chain and the water quality characteristics of the water body of interest including:

C Feeding preferences, weights, and lipid contents for each species in the food chain.

C Water temperature.

C Organic carbon content of the sediment and the water column.

C Concentrations of the chemical in the sediment and freely dissolved concentration of the chemical in the water column.

C Densities of lipid and organic carbon.

C Metabolic transformation rate constant. 223 C K ow values, estimated using the methods described in Section <IP_ADDRESS> ( subsection entitled: Guidance on Selecting Appropriate K ow Values).

It should be noted that the model of Gobas ( 1993) does not include solubility controls or limitations; thus, the concentration of the chemical in the water used with the model is arbitrary for determining the BAFs, i. e., the ratio of the concentration of the chemical in the tissue to the concentration of the chemical in the water column ( BAF) obtained using a 1 ng/ L concentration of the chemical in the water will be equal to that obtained using a 150 F g/ L concentration of the chemical for a specified K ow.

It should be noted that the model of Gobas ( 1993) takes the total concentration of the chemical in the water and, before doing any predictions, calculates the freely dissolved concentration of the chemical in the water. The freely dissolved concentration of the chemical in the water is then used in all subsequent calculations by the model. By setting the concentration of the DOC and POC to 0 mg/ L, the total concentration of the chemical input to the model becomes equal to the freely dissolved concentration of the chemical in the water. This allows the fixing of the chemical concentration relationship between sediment and water phases in the model. BAFs were determined by dividing the chemical residues predicted by the model of Gobas ( 1993) by the freely dissolved concentration of the chemical in the water; therefore, they are not influenced by the concentration of DOC input to the model.

Measured chemical residues in fishes assigned to trophic level 3 can be higher than those in piscivorous fishes ( trophic level 4) from the same food chain. Potential causes of the higher concentrations ( on a lipid basis) in the trophic level 3 fish include 1) growth rates which are much slower than rates for predator fishes; 2) slower rates of metabolism than the predator fishes for the chemicals of interest; and 3) feeding preferences for trophic level 3 fish, including predation on other fish. In the development of FCMs, the feeding preferences for smelt ( see Gobas 1993) consisted of a mixture of trophic level 2 and 3 organisms, i. e., mysids, Diporeia sp., and sculpin. This mixture of different trophic levels combined with bioenergetic factors for the smelt caused the predicted concentrations of the chemicals and subsequently, the derived FCMs, to be slightly larger than those for the piscivorous fishes ( trophic level 4). 224 Table 2.4.3: Environmental Parameters and Species Characteristics Used With the Model of Gobas ( 1993) for Deriving Chain Multipliers Environmental parameters:

Mean water temperature: 8 E C Organic carbon content of the sediment: 2.7% Organic carbon content of the water column: 0.0 kg/ L Density of lipids: 0.9 kg/ L Density of organic carbon: 0.9 kg/ L Metabolic transformation rate constant: 0.0 day 1 A socw = 25 * log Kow. Species characteristics: Phytoplankton Lipid content: 0.5% Zooplankton: Mysids ( Mysis relicta) Lipid content: 5.0% Diporeia sp. Lipid content: 3.0% Sculpin ( Cottus cognatus) Lipid content: 8.0% Weight: 5.4 g Diet: 18% zooplankton, 82% Diporeia sp. ( pelagic/ benthic food web) 100% Diporeia sp. ( all benthic food web) 100% zooplankton ( all pelagic food web) Alewives ( Alosa pseudoharengus) Lipid content: 7.0% Weight: 32 g Diet: 60% zooplankton, 40% Diporeia sp. ( pelagic/ benthic food web) 100% Diporeia sp. ( all benthic food web) 100% zooplankton ( all pelagic food web) Smelt ( Osmerus mordax) Lipid content: 4.0% Weight: 16 g Diet: 54% zooplankton, 21% Diporeia sp., 25% sculpin 54% Diporeia sp., 46% sculpin ( all benthic food web) 68% zooplankton, 32% sculpin ( all pelagic food web) Salmonids ( Salvelinus namaycush, Oncorhynchus mykiss, Oncorhynchus velinus namaycush) Lipid content: 11.0% Weight: 2410 g Diet: 10% sculpin, 50% alewives, 40% smelt 225 Table 2.4.4: Food Chain Multipliers for Trophic Levels 2, 3, & 4 ( Pelagic and Benthic Structure)

Log Kow Trophic Level 2 Trophica Level 3 Trophic Level 4 < 2.0 1.000 1.000 1.000 2.0 1.000 1.005 1.000 2.5 1.000 1.010 1.002 3.0 1.000 1.028 1.007 3.1 1.000 1.034 1.007 3.2 1.000 1.042 1.009 3.3 1.000 1.053 1.012 3.4 1.000 1.067 1.014 3.5 1.000 1.083 1.019 3.6 1.000 1.103 1.023 3.7 1.000 1.128 1.033 3.8 1.000 1.161 1.042 3.9 1.000 1.202 1.054 4.0 1.000 1.253 1.072 4.1 1.000 1.315 1.096 4.2 1.000 1.380 1.130 4.3 1.000 1.491 1.178 4.4 1.000 1.614 1.242 4.5 1.000 1.766 1.334 4.6 1.000 1.950 1.459 4.7 1.000 2.175 1.633 4.8 1.000 2.452 1.871 4.9 1.000 2.780 2.193 5.0 1.000 3.181 2.612 5.1 1.000 3.643 3.162 5.2 1.000 4.188 3.873 5.3 1.000 4.803 4.742 5.4 1.000 5.502 5.821 5.5 1.000 6.266 7.079 5.6 1.000 7.096 8.551 5.7 1.000 7.962 10.209 5.8 1.000 8.841 12.050 5.9 1.000 9.716 13.964 6.0 1.000 10.556 15.996 6.1 1.000 11.337 17.783 6.2 1.000 12.064 19.907 6.3 1.000 12.691 21.677 6.4 1.000 13.228 23.281 6.5 1.000 13.662 24.604 6.6 1.000 13.980 25.645 6.7 1.000 14.223 26.363 Table 2.4.4: Food Chain Multipliers for Trophic Levels 2, 3, & 4 ( Pelagic and Benthic Structure)

Log Kow Trophic Level 2 Trophica Level 3 Trophic Level 4 226 6.8 1.000 14.355 26.669 6.9 1.000 14.388 26.669 7.0 1.000 14.305 26.242 7.1 1.000 14.142 25.468 7.2 1.000 13.852 24.322 7.3 1.000 13.474 22.856 7.4 1.000 12.987 21.038 7.5 1.000 12.517 18.967 7.6 1.000 11.708 16.749 7.7 1.000 10.914 14.388 7.8 1.000 10.069 12.050 7.9 1.000 9.162 9.840 8.0 1.000 8.222 7.798 8.1 1.000 7.278 6.012 8.2 1.000 6.361 4.519 8.3 1.000 5.489 3.311 8.4 1.000 4.683 2.371 8.5 1.000 3.949 1.663 8.6 1.000 3.296 1.146 8.7 1.000 2.732 0.778 8.8 1.000 2.246 0.521 8.9 1.000 1.837 0.345 9.0 1.000 1.493 0.226 a The FCMs for trophic level 3 are the geometric mean of the FCMs for sculpin and alewife. 227 Table 2.4.5: Food Chain Multipliers for Trophic Levels 2, 3, & 4 ( All Pelagic Structure)

Log Kow Trophic Level 2 Trophica Level 3 Trophic Level 4 < 2.0 1.000 1.000 1.000 2.0 1.000 1.000 1.001 2.1 1.000 1.000 1.001 2.2 1.000 1.000 1.001 2.3 1.000 1.000 1.002 2.4 1.000 1.000 1.002 2.5 1.000 1.001 1.002 2.6 1.000 1.001 1.003 2.7 1.000 1.001 1.003 2.8 1.000 1.001 1.004 2.9 1.000 1.001 1.005 3.0 1.000 1.002 1.006 3.1 1.000 1.002 1.007 3.2 1.000 1.002 1.009 3.3 1.000 1.003 1.011 3.4 1.000 1.004 1.013 3.5 1.000 1.005 1.016 3.6 1.000 1.006 1.021 3.7 1.000 1.007 1.026 3.8 1.000 1.009 1.032 3.9 1.000 1.011 1.040 4.0 1.000 1.014 1.050 4.1 1.000 1.018 1.063 4.2 1.000 1.022 1.078 4.3 1.000 1.028 1.097 4.4 1.000 1.034 1.121 4.5 1.000 1.043 1.150 4.6 1.000 1.053 1.185 4.7 1.000 1.066 1.228 4.8 1.000 1.081 1.280 4.9 1.000 1.099 1.342 5.0 1.000 1.121 1.415 5.1 1.000 1.147 1.502 5.2 1.000 1.176 1.603 5.3 1.000 1.210 1.719 5.4 1.000 1.248 1.851 5.5 1.000 1.289 1.999 5.6 1.000 1.333 2.162 5.7 1.000 1.379 2.337 5.8 1.000 1.425 2.521 5.9 1.000 1.471 2.711 Table 2.4.5: Food Chain Multipliers for Trophic Levels 2, 3, & 4 ( All Pelagic Structure)

Log Kow Trophic Level 2 Trophica Level 3 Trophic Level 4 228 6.0 1.000 1.514 2.900 6.1 1.000 1.554 3.083 6.2 1.000 1.589 3.254 6.3 1.000 1.619 3.407 6.4 1.000 1.643 3.536 6.5 1.000 1.660 3.637 6.6 1.000 1.671 3.705 6.7 1.000 1.674 3.738 6.8 1.000 1.669 3.733 6.9 1.000 1.657 3.688 7.0 1.000 1.636 3.602 7.1 1.000 1.606 3.474 7.2 1.000 1.567 3.305 7.3 1.000 1.518 3.094 7.4 1.000 1.458 2.848 7.5 1.000 1.389 2.570 7.6 1.000 1.308 2.270 7.7 1.000 1.219 1.958 7.8 1.000 1.122 1.647 7.9 1.000 1.020 1.349 8.0 1.000 0.915 1.076 8.1 1.000 0.810 0.835 8.2 1.000 0.707 0.631 8.3 1.000 0.610 0.466 8.4 1.000 0.520 0.336 8.5 1.000 0.438 0.237 8.6 1.000 0.366 0.164 8.7 1.000 0.303 0.112 8.8 1.000 0.249 0.075 8.9 1.000 0.204 0.050 9.0 1.000 0.166 0.033 a The FCMs for trophic level 3 are the geometric mean of the FCMs for sculpin and alewife. 229 Table 2.4.6: Food Chain Multipliers for Trophic Levels 2, 3, & 4 ( All Benthic Structure)

Log Kow Trophic Level 2 Trophica Level 3 Trophic Level 4 < 2.0 1.000 1.000 1.000 2.0 1.000 1.009 1.001 2.1 1.000 1.010 1.001 2.2 1.000 1.011 1.001 2.3 1.000 1.013 1.002 2.4 1.000 1.015 1.002 2.5 1.000 1.018 1.002 2.6 1.000 1.022 1.003 2.7 1.000 1.026 1.003 2.8 1.000 1.032 1.004 2.9 1.000 1.039 1.005 3.0 1.000 1.048 1.006 3.1 1.000 1.060 1.008 3.2 1.000 1.074 1.010 3.3 1.000 1.092 1.013 3.4 1.000 1.114 1.017 3.5 1.000 1.142 1.022 3.6 1.000 1.177 1.029 3.7 1.000 1.222 1.039 3.8 1.000 1.277 1.053 3.9 1.000 1.347 1.072 4.0 1.000 1.433 1.099 4.1 1.000 1.541 1.138 4.2 1.000 1.676 1.195 4.3 1.000 1.843 1.276 4.4 1.000 2.050 1.392 4.5 1.000 2.306 1.559 4.6 1.000 2.620 1.796 4.7 1.000 3.004 2.131 4.8 1.000 3.470 2.595 4.9 1.000 4.032 3.232 5.0 1.000 4.702 4.087 5.1 1.000 5.492 5.215 5.2 1.000 6.411 6.668 5.3 1.000 7.462 8.501 5.4 1.000 8.643 10.754 5.5 1.000 9.942 13.457 5.6 1.000 11.337 16.617 5.7 1.000 12.800 20.213 5.8 1.000 14.293 24.192 5.9 1.000 15.774 28.468 Table 2.4.6: Food Chain Multipliers for Trophic Levels 2, 3, & 4 ( All Benthic Structure)

Log Kow Trophic Level 2 Trophica Level 3 Trophic Level 4 230 6.0 1.000 17.202 32.920 6.1 1.000 18.539 37.405 6.2 1.000 19.753 41.764 6.3 1.000 20.822 45.836 6.4 1.000 21.730 49.472 6.5 1.000 22.469 52.544 6.6 1.000 23.037 54.949 6.7 1.000 23.433 56.610 6.8 1.000 23.659 57.472 6.9 1.000 23.717 57.501 7.0 1.000 23.606 56.679 7.1 1.000 23.326 55.007 7.2 1.000 22.873 52.507 7.3 1.000 22.246 49.227 7.4 1.000 21.443 45.254 7.5 1.000 20.467 40.714 7.6 1.000 19.327 35.780 7.7 1.000 18.040 30.657 7.8 1.000 16.629 25.572 7.9 1.000 15.129 20.744 8.0 1.000 13.580 16.359 8.1 1.000 12.026 12.547 8.2 1.000 10.510 9.368 8.3 1.000 9.068 6.822 8.4 1.000 7.732 4.856 8.5 1.000 6.522 3.387 8.6 1.000 5.448 2.321 8.7 1.000 4.513 1.567 8.8 1.000 3.711 1.045 8.9 1.000 3.032 0.689 9.0 1.000 2.465 0.451 a The FCMs for trophic level 3 are the geometric mean of the FCMs for sculpin and alewife. 25These equations were used to derive the equation for ffd presented in Section <IP_ADDRESS>, and are discussed in Appendix D.

231 f fd ' 1 1 % DOC @ K doc % POC @ K poc ( Equation 2.4.21)

C fd w ' C t w @ f fd ( Equation 2.4.22) The freely dissolved concentrations of the chemicals in the water column were calculated from the data of Oliver and Niimi ( 1988) using the equations of Gschwend and Wu ( 1985) and Cook et al. ( 1993) 25 for freely dissolved fraction:

and freely dissolved concentration:

where:

f fd = Fraction of the chemical which is freely dissolved in the water DOC = Concentration of dissolved organic carbon POC = Concentration of particulate organic carbon K doc = Partition coefficient for the chemical between the DOC and the freely dissolved phase in the water K poc = Partition coefficient for the chemical between the POC phase and the freely dissolved phase in the water C w t = Total concentration of the chemical in the water C w f d = Freely dissolved concentration of the chemical in the water The concentrations in the water reported by Oliver and Niimi ( 1988) were obtained by liquidliquid extraction of aliquots of Lake Ontario water which had passed through a continuous flow centrifuge to remove POC. Therefore, the concentrations in the water reported by Oliver and Niimi ( 1988) include both the freely dissolved chemical and the chemical associated with the DOC in the water sample. The above equations were used to derive the freely dissolved concentrations of the 232 chemicals in the water by setting the POC = 0 mg/ L and DOC = 2 mg/ L. K ow s used to derive the freely dissolved concentrations have been reported elsewhere ( USEPA, 1995c).

In Exhibit 2.4.10, A socw is plotted against K ow for each chemical reported by Oliver and Niimi ( 1988). Because the chemical residues by Oliver and Niimi ( 1988) for the foraging and piscivorous fishes were almost entirely for the PCBs and pesticides, a regression equation of the form log II = A x log K ow + B was determined using this set of chemicals. Using the geometric mean regression technique, the slope ( standard deviation) of this equation was 1.07 ( 0.078). This slope was not significantly different from 1.0, and thus, the relationship between the A socw/ K ow of the individual PCB and pesticide compounds. The average ( standard deviation) ratio was 24.7 ( 25.7). The following relationship was therefore selected to define A socw in this investigation: A socw = 25 * log K ow.

In addition to determining FCMs for organic substances using the Gobas ( 1993) model, EPA also recommends the use of FCMs derived from field data where data are sufficient to enable scientifically valid and reliable determinations to be made. Currently, field measured FCMs are the only method recommended for estimating FCMs for inorganic substances because appropriate modelderived estimates are not yet available. Similarly, field measured FCMs can also be determined for organic substances. Compared to the model based FCMs described previously, properly derived field based FCMs may offer some advantages in some situations. For example, field measured FCMs rely on measured contaminant concentrations in tissues of biota and therefore inherently account for any contaminant metabolism which may occur. Field measured FCMs may also be useful for estimating BAFs for some highly hydrophobic contaminants whose water column concentrations are very difficult to determine with accuracy and precision. Furthermore, field measured FCMs may better reflect local conditions that can influence bioaccumulation, such as differences in food web structure, exposure pathways, water body type, and target species. Finally, use of field measured FCMs in estimating BAFs may enable existing data on contaminant concentrations in aquatic organisms to be used in situations where companion water column data are unavailable or are judged to be unreliable for calculating a BAF. 234 As discussed below and in Appendix C, FCMs are related to and can be determined from biomagnification factors ( BMF). For example:

1. FCM TL 2 = BMF TL 2 2. FCM TL 3 = ( BMF TL 3) ( FCM TL 2) = ( BMF TL 3) ( BMF TL 2)

3. FCM TL 4 = ( BMF TL 4) ( FCM TL 3) = ( BMF TL 4) ( BMF TL 3) ( BMF TL 2)

where:

FCM = Food chain multiplier for designated trophic level ( TL2, TL3, or TL4) BMF = Biomagnification factor for designated trophic level ( TL2, TL3, or TL4)

The basic difference between FCMs and BMFs is that FCMs relate back to trophic level one ( or trophic level two as assumed by the Gobas ( 1993) model), whereas BMFs always relate back to the next lowest trophic level. For nonpolar organic chemicals, biomagnification factors can be calculated from lipid normalized tissue residue concentrations determined in biota at a site according to the following equation.

BMF TL2 = ( C R  TL2) / ( C R  TL1) BMF TL3 = ( C R  TL3) / ( C R  TL2) BMF TL4 = ( C R  TL4) / ( C R  TL3)

where:

C R = Lipid normalized concentration of chemical in tissue of appropriate biota that occupy the specified trophic level ( TL2, TL3, or TL4).

For inorganic chemicals, BMFs are determined as shown above, except that tissue concentrations expressed on a wet weight basis and are not lipid normalized. In calculating fieldderived BMFs for determining FCMs, care must be taken to ensure that the biota upon which they are based actually represent functional predator prey relationships at the study site, and therefore, would accurately reflect any biomagnification that may occur at the site.

As with field measured BAFs, the potential advantages of using field data for estimating bioaccumulation can be offset by improper collection and use of information. In calculating fieldbased FCMs, steps similar to those recommended for determining field measured BAFs need to be taken to ensure that the resulting FCMs accurately represent potential exposures to the target population at the site( s) of interest. Some of the general procedural and quality assurance requirements that are important for determining field measured FCMs include: 235 1. A food web analysis should be conducted for the site from which the tissue concentration data are to be determined ( or have been already been determined) to identify the appropriate trophic levels for the aquatic organisms and appropriate predator prey relationships. To assist in trophic level determinations, EPA is in the process of finalizing its draft trophic level and exposure analysis documents ( USEPA 1995d; 1995e; 1995f) which include trophic level analyses of numerous species in the aquatic based food web.

2. The aquatic organisms sampled from each trophic level should reflect the most important exposure pathways leading to human exposure via consumption of aquatic organisms. For higher trophic levels ( e. g., 3 and 4), aquatic species should also reflect those that are commonly consumed by humans.

3. Collection of tissue concentration field data for a specific site for which criteria are to be derived and with the specific species of concern are preferred.

4. If data cannot be collected from every site for which criteria are to be derived, the site of the field study should not be so unique that the FCM values cannot be extrapolated to other locations where the criteria and values will apply.

5. Samples of the appropriate resident species and the water in which they reside should be collected and analyzed using appropriate, sensitive, accurate, and precise methods to determine the concentrations of bioaccumulative chemicals present in the tissues.

6. For organic chemicals, the percent lipid should be either measured or reliably estimated for the tissue used in the determination of the lipid normalized concentration in the organism's edible tissues.

7. The tissue concentrations should reflect average exposure conditions over the time period required to achieve steady state conditions for the contaminant in the target species ( usually trophic level three or four organisms).

<IP_ADDRESS> Baseline BAF from Predicted BCF and Food Chain Multiplier As the fourth tier in the data preference hierarchy for nonpolar organics ( e. g., when acceptable field measured BAFs, BSAFs, or laboratory measured BCFs are unavailable), EPA recommends multiplying the FCM by the K ow for the chemical for estimating the baseline BAF. This is equivalent to the direct use of the food chain bioaccumulation model for estimating the BAF when modelderived FCMs are used. For each trophic level, the equation for calculating this baseline BAF is:

Baseline BAF ' ( FCM) ( predicted baseline BCF) ' ( FCM) ( K ow)

( Equation 2.4.23) 236 log BCF ' 1.00 log K ow & 0.08 ( Equation 2.4.24) where:

Baseline BAF = BAF expressed on a lipid normalized basis using the freely dissolved concentration of the chemical in water FCM = Food chain multiplier obtained from Table 2.4.3, 2.4.4, or 2.4.5 by linear interpolation ( or from appropriate field data)

K ow = Octanol water partition coefficient Use of the K ow in place of the baseline BCF is supported by equilibrium partitioning theory. The linear relationship between the BCF and K ow is also based on the underlying assumption that the bioconcentration process can be viewed as a partitioning of a chemical between the lipids of the aquatic organisms and water and that the K ow is a useful surrogate for this partitioning process ( Mackay, 1982). These authors presented a thermodynamic basis for the partitioning process for bioconcentration and, in essence, the BCF on a lipid normalized basis ( and freely dissolved concentration of the chemical in the water) should be similar if not equal to the K ow for organic chemicals.

In addition, empirical data support the use of the K ow in place of the BCF. As indicated by Isnard and Lambert ( 1988), numerous studies have demonstrated a linear relationship between the logarithm of the BCF and the logarithm of the octanol water partition coefficient ( K ow) for organic chemicals for fish and other aquatic organisms. In addition, when the regression equations are constructed using BCFs reported on a lipid normalized basis, the slopes and intercepts are not significantly different from one and zero, respectively. For example, de Wolf et al. ( 1992) adjusted a relationship reported by Mackay ( 1982) to a 100 percent lipid basis ( lipid normalized basis) and obtained the following relationship:

For chemicals with large log K ow s ( i. e., greater than 6.0), reported BCFs are often not equal to the K ow for non metabolizable chemicals. BCFs for non metabolizable chemicals are equal to the K ow when the BCFs are reported on lipid normalized basis, determined using the freely dissolved concentration of the chemical in the exposure water, corrected for growth dilution, determined from steady state conditions or determined from accurate measurements of the chemical's uptake ( k 1) and elimination ( k 2) rate constants from and to the water, respectively, and determined using no solvent carriers in the exposure. Therefore, EPA recommends that the K ow can be used as an approximation of the BCF.

It is important to recognize the BAF estimated using this method is based on nonmetabolizable chemicals. Thus, predicted BAFs will be larger than laboratory measured BCFs for 237 chemicals that undergo some metabolism. For some chemicals, such as PAHs, the predicted BAF can be higher than the measured BAF.

<IP_ADDRESS> Metabolism One factor affecting bioaccumulation is metabolism of the chemical by aquatic organisms. Many organic chemicals that are taken up by aquatic organisms are transformed to some extent by the organism's metabolic processes, but the rate of metabolism varies widely across chemicals and species. For most organic chemicals, metabolism increases the depuration rate and reduces the BAF of the parent compound.

The procedures to measure or predict BAFs differ in the extent to which they account for metabolism. Field measured BAFs and BSAFs inherently account for any metabolism of the chemical. Predicted BAFs that are obtained by multiplying a laboratory measured BCF by a modelderived FCM take into account the effect of metabolism on the BCF, but not on the FCM. Use of field derived FCMs takes into account metabolism. A food chain model prediction of the BAF ( the fourth data preference for nonpolar organics) makes no allowance for chemical metabolism. Despite the differential effects of metabolism on predicted BAFs, information is not available for predicting the effect of metabolism on predicted BAFs that rely on the food chain multiplier or predicted BCFs.

<IP_ADDRESS> Mixtures For chemical classes where sufficient data on the relative toxicities of individual members of the class is available, toxicity equivalency factors ( TEF) can be used to assess the total toxicity risk of the mixture ( for further discussion of TEFs, see Appendix I, Section A. 3. f and Appendix III, Section F. 4 of the Federal Register notice). To date, adequate data to support use of TEFs has been found in only one class of compounds ( dioxins) ( USEPA, 1989). Because individual chemicals of a class ( e. g., PCDDs and PCDFs) not only differ in their relative toxicities, but also their relative bioaccumulation potentials, bioaccumulation equivalency factors ( BEF) can also be used to account such differences. Bioaccumulation equivalency factors have been developed for PCDDs and PCDFs based on bioaccumulation data for the Great Lakes ( 60 FR 15366). As adequate data become available to establish TEFs for other chemical classes, the BEF methodology described in 60 FR 15366 and U. S. EPA 1995c should be considered for assessing combined risk from chemical mixtures.

2.4.5 BAFs Used in Deriving AWQC As discussed above for nonpolar organic chemicals, after the baseline BAF has been derived for a chemical using one of the four methods, the next step is to calculate a BAF that will be used in the derivation of AWQC. This requires information on: ( 1) the baseline BAF for the chemical of interest using one of the four methods described above; ( 2) the percent lipid of the aquatic organisms consumed by humans at the site of interest; and ( 3) the freely dissolved fraction of the chemical in the ambient water of interest. 238 BAF for AWQC( TL n) ' [ ( Baseline BAF fd R ) TL n @ ( f R ) TL n % 1] @ ( f fd)

( Equation 2.4.25) <IP_ADDRESS> General Equation for an AWQC BAF For each trophic level, the equation for deriving a BAF to be used in deriving AWQC is applicable to all four methods and is:

where:

BAF for AWQC ( TL n) = BAF at trophic level " n" used to derive AWQC based on site conditions for lipid content of consumed aquatic organisms for trophic level " n" and the freely dissolved fraction in the site water Baseline BAF R f d ( TL n) = BAF expressed on a freely dissolved and lipid normalized basis for trophic level " n"

f R ( TL n) = Fraction lipid of aquatic species consumed at trophic level " n"

f fd = Fraction of the total chemical in water that is freely dissolved <IP_ADDRESS> Baseline BAF The baseline BAFs used in this equation are those derived from the equations presented in Section 2.4.3 above.

<IP_ADDRESS> Lipid Content of Aquatic Species Eaten by Humans The lipid content of the aquatic species consumed by humans is required when deriving BAFs for a nonpolar organic chemical that will be used for deriving ambient water quality criteria ( AWQC). Information on lipid content is needed because it affects the extent of bioaccumulation of nonpolar organic chemicals in aquatic organisms ( Mackay, 1982; Connolly and Pederson, 1988; Thomann, 1989) and therefore, is important in characterizing the potential contaminant exposure to the target population ( e. g., general population, sport anglers, subsistence anglers).

The lipid content of aquatic organisms can vary considerably across different species, across different locations for a given species across seasons, and across different age classes ( life stages) of a species at a given location. In addition to lipid content, the types and quantity of aquatic species 239 eaten by individuals differ substantially throughout the United States. In order to account for some of this variability in determining a representative lipid content of consumed aquatic species, EPA recommends that the lipid fraction of aquatic organism be weighted by the consumption rate of those aquatic species consumed by the target population based on information from the local or regional survey. Information on consumption rates and lipid content is most accurately determined on a local or regional basis and is recommended as the first choice for estimating lipid content of consumed species. Since baseline BAFs are determined for each trophic level and must be adjusted to reflect the lipid content of consumed aquatic species, EPA recommends that the consumption weighted lipid content of consumed aquatic organisms also be determined for each trophic level. If sufficient information is not available to derive trophic level specific lipid contents, then States and Tribes may choose to calculate an overall consumption weighted lipid content that combines data from the relevant trophic levels.

EPA recognizes that local or regional fish consumption data are not always available. Therefore, EPA has derived default, national estimates of consumption weighted lipid content for use in deriving national AWQC, when local or regional information is unavailable. If local data on both aquatic species consumption rates and lipid contents are not available, States may wish to use national default lipid values calculated by EPA. Using the general relationship in Equation 2.4.26 and information on national finfish and shellfish consumption rates at various trophic levels, EPA has developed a national default consumption weighted mean lipid values of 2.3% at trophic level 2, 1.5% at trophic level 3, and 3.1% at trophic level 4 ( expressed to two significant digits for convenience). The data sources, calculations and assumptions supporting of these national default lipid values are described below.

Data Sources To estimate a national default consumption weighted percent lipid value for humans, information is needed at a national level on: ( 1) the type and quantity of aquatic biota consumed by humans; ( 2) the percent lipid of the aquatic biota consumed by humans; and ( 3) the trophic level of the consumed species. These data are described below.

Fish Consumption Data. Information on the types and quantity of aquatic organisms consumed in the U. S. were obtained from USDA's Continuing Survey of Food Intake by Individuals ( CSFII) ( USEPA, 1998b). This survey provided daily average per capita estimates of fish consumption for the U. S. population for categories of estuarine, freshwater, and marine fish and shellfish. Although other regional or local surveys were available, the CSFII was selected because it provided consumption information on a national basis and was the most recent data available. In this survey, consumption rates were divided into 16 categories representing mostly estuarine species and 5 categories representing mostly freshwater species. Mean per capita consumption rates were characterized for individuals 18 years and older. For a detailed discussion of the use of the CSFII data see the chapter on exposure in this TSD. Table 2.4.7 displays the habitat classification, CSFII consumption categories, mean per capita consumption rates, and the fraction of total estuarine and freshwater consumption represented by each category in the survey. 240 Lipid Content of Consumed Species. The second type of information required in deriving national default values for lipid content includes data on the lipid content of consumed aquatic species. Six primary data sources were used to estimate lipid content. These include: EPA's STORET data base, EPA's National Study of Chemical Residues in Fish ( USEPA, 1992), two reviews from National Marine Fisheries Service of the National Oceanic and Atmospheric Administration ( Sidwell, 1981; Kryznowek and Murphy, 1987), data from the California Toxic Substances Monitoring Program ( TSMP), Green Bay Mass Balance Study ( USEPA, 1992b, 1995g), and a study of the Hudson River conducted by the New York Department of Environmental Conservation ( HydroQual, Inc., portions published in Armstrong and Sloan, 1988). Each of these data sources are discussed in more detail below.

STORET. Data from EPA's STORET ( STOrage and RETrieval of U. S. Waterways Parametric data) data base, a waterway related monitoring data base, were retrieved by downloading tissue and sediment chemistry data from ambient non land based monitoring stations, including lipid content, from 1980 through October, 1993. Data are stored in STORET by many government agencies, both federal and state. Most of the data used in this analysis were collected in the Midwest, in particular in Illinois, Minnesota, Michigan, Iowa, Kansas, Missouri, and Nebraska. The number of individual organisms per sample is not known. Information on the common and Latin name for the species sampled, the tissue sampled, the percent lipid content, the collection date and location, and the agency responsible for the data were retrieved from STORET. Data from the other data bases used in this analysis were confirmed as not being present in STORET, which could have caused double counting of some samples. 241 Table 2.4.7: Aquatic Organism Categories and Average Consumption Rates from CSFII Habitat USDA CSFII Category Estimated Mean Consumption Rate ( g/ person/ day) Percentage of Total Consumption Rate Estuarine shrimp 1.72959 30.08%

perch 0.60368 10.50%

estuarine flatfish 0.52735 9.17%

crab 0.37126 6.46%

flounder 0.29941 5.21%

oyster 0.22555 3.92%

mullet 0.08756 1.52%

croaker 0.06749 1.17%

herring 0.03925 0.68%

smelt 0.03753 0.65%

clam 0.03146 0.55%

scallop 0.00322 0.06%

anchovy 0.00292 0.05%

scup 0.00068 0.01%

sturgeon 0.00054 0.01%

Freshwater catfish 1.18227 20.56%

trout 0.44946 7.82%

carp 0.05727 1.00%

pike 0.02337 0.41%

freshwater salmon 0.01096 0.19%

Source: USDA combined 1989, 1990, and 1991 Continuing Survey of Food Intakes by Individuals ( CSFII). Notes: Estimates are projected from a sample of 8,478 individuals 18 years of age and older in the U. S. population of 177,807,000 individuals 18 years of age or older using 3 year combined survey weights. The population for this survey consisted of individuals in the 48 conterminous states. The fish component of foods containing fish was calculated using data from the recipe file for release 7 of the USDA's Nutrient Database for individual food intake surveys. The number of digits does not imply their significance. 242 National Study of Chemical Residues in Fish. This EPA study was a one time screening investigation to determine the prevalence of selected bioaccumulative pollutants in fish ( USEPA, 1992a). Three to five fish collected from one location were used for each composite sample. For each composite sample, two measurements of the percent lipid content were obtained, one from the test for dioxins/ furans and one from the test for other xenobiotics. The average of the two lipid values was used to represent each sample data point. Location and sampling date information were available as was the common name of the species collected and the tissue type sampled ( whole body, fillet).

NOAA Data. Data on the lipid content of estuarine species from the National Marine Fisheries Service of the National Oceanic and Atmospheric Administration were available from two reviews ( Sidwell, 1981; Kryznowek and Murphy, 1987). These reviews consist of compilations of data from primary literature sources. Information on the specific location and number of individuals per value were not available in these reviews. Data not collected in North America were excluded, where information was available to make this distinction. Information was available on common and Latin name, tissue type, and method of preparation ( e. g., raw, cooked). Only samples that were indicated as being fresh or raw, or for which no preparation information was available, were used in the analysis. Other information such as the number of individuals in a sample, age, weight, and sex were not available. This data source was used to augment the data from the other data sources which were very limited in quantity. For those categories ( catfish, trout, carp, pike, and perch) for which we had extensive data from the other sources, data from NOAA were not used.

California Toxic Substances Monitoring Program ( TSMP). This program is run by the California Environmental Protection Agency, California State Water Resources Control Board, Division of Water Quality, Monitoring and Assessment Unit. The TSMP was organized to provide a uniform statewide approach to the detection and evaluation of the occurrence of toxic substances in fresh water, and to a limited extent, in estuarine and marine waters, through the analysis of fish and other aquatic life. Samples are collected annually and composite samples of six fish are collected when possible. The data base provides information on age, sample collection date, location, number of organisms per sample, weight, and length. Most samples for the species of interest are fillet samples, although some whole organism samples are also present. Data were obtained via the Internet at World Wide Web site: http:// www. swrcb. ca. gov.

Green Bay Mass Balance Study. This study includes lipid content from aquatic species from Green Bay, Lake Michigan. All data are whole body samples. Included in the data base are information on collection date, zone of bay in which the sample was collected, age, and number of fish in average or composite. Data were obtained from HydroQual, Inc. ( U. S. EPA 1992b; U. S. EPA 1995g). These data are also available on the World Wide Web at www. epa. gov/ glnpo/ monitor. html.

Hudson River Data. The New York Department of Environmental Conservation conducted sampling from which percent lipid content for fish species from the Hudson River were available. All data are for muscle fillet samples, and there is one individual per sample. In this data base, collection 243 date, length, weight, and sex are available, as well as location in the form of river mile. Data were obtained from HydroQual, Inc. ( U. S. EPA 1995h; 1995i and Armstrong and Sloan, 1988).

Data Analysis Data Screening/ Treatment. Several steps were required to prepare the data for the calculation of average, consumption weighted lipid content. As described further in the following section, each record was assigned to a CSFII species category based information on the common and Latin names given in the various data bases and information on whether they could reasonably be expected to be consumed. Data for those species that could not be assigned to a CSFII species category were omitted. For the STORET data, only those data that contained the common name, Latin name, and species code were used so as to maintain consistency of species names within and across data bases. In addition, several steps were taken to correct species codes where known mistakes occurred. An upper bound lipid content was also set at 35 percent to exclude extreme values that were considered outliers. Very few values occurred above 35 percent.

Data were screened by tissue types that corresponded to those considered most commonly consumed by humans. For all finfish species, with the exception of herring, anchovy, and smelt species, data were considered only for selected tissues that include: fillet, fillet/ skin, muscle, meat, and flesh samples. The great majority of samples used for the finfish species were fillet or fillet/ skin samples. For crab species, data considered in the analysis included tissues designated as edible flesh, edible portion, or edible skinned, in addition to those described for finfish. For the remaining shellfish species ( clam, oyster, scallop, and shrimp) and for herring, anchovy and smelt, whole body samples were considered in addition to the tissue types used for fish and crab species. These criteria were established based on the portions of a species are believed to be consumed and constraints on the availability of data.

Selection of Species for Inclusion in Lipid Analysis. Given information from the CSFII survey on the types of aquatic organisms consumed in the U. S., the next step in calculating the consumption weighted average lipid content involved assigning species to the general CSFII categories. In most cases, information was not available from the CSFII survey to identify which species were included for determining the consumption rates listed in Table 2.4.7. Therefore, inclusion of species and accompanying lipid data into a CSFII category was based on: ( 1) their taxonomic and publicly perceived linkage to a CSFII category, ( 2) consideration of their likelihood for being caught ( either recreationally or commercially) and consumed in the U. S., and ( 3) their occurrence in either fresh or estuarine waters for at least some portion of their life cycle. The species included in the lipid analysis and their relationship to the CSFII consumption categories is provided in Table 2.4.8. Information from numerous published sources were used to help determine whether a species met these criteria. Because several of the CSFII species categories were broad in terms of the types of species that could be included, some species were assigned to multiple CSFII survey categories. For example, flounder species fit into both estuarine flatfish and flounder categories. In such cases, appropriate records were included in both CSFII categories. Notably, some species that 244 are commonly caught and consumed but did not fit into a CSFII category, such as bass and walleye, were not included in this analysis.

Lipid Content of Species in CSFII Categories. Based on lipid data from the aforementioned sources, an average lipid content was determined for each of the species in the CSFII consumption categories ( Table 2.4.8). Next, the overall average lipid content of each CSFII category was determined as the average of the corresponding individual species mean lipid values. Ideally, if sufficient national consumption data were available at the species level, the overall average lipid value for each CSFII category would be determined on a consumption weighted basis. However, sufficient national information was not available below the CSFII category level and thus, equal weights were assigned to each species mean lipid value. For example, lipid contents were available for several species of trout ( e. g., rainbow trout, brown trout, and others), whereas consumption rates were available from the CSFII only for trout as a group. Thus, mean lipid values for all trout species were averaged and combined with the consumption rate for trout from the CSFII.

Trophic Level Assignments to CSFII Categories. National fish and shellfish consumption data from the CSFII ( see Table 2.4.7) indicate that on average, individuals consume aquatic organisms from a variety of trophic levels ( e. g., oysters and clams in trophic level two, flounder and shrimp in trophic level three, perch and certain catfish species in trophic level four). Therefore, for the purposes of calculating national AWQC using the CSFII consumption data, BAFs need to be derived that are applicable to each of these trophic levels and should be adjusted to reflect the average lipid content of organisms consumed in each of the trophic levels. To estimate the consumption weighted average lipid content in each of the three trophic levels ( and to estimate consumption rates of aquatic organisms within each of the trophic levels see Section 2.4.8), a trophic level designation must be assigned to each of the consumption rate categories of the CSFII shown in Table 2.4.7.

In order to estimate the trophic level status of consumed aquatic species, one should ideally rely on information concerning the identity, size, age, and diets of individual aquatic species consumed. This information is useful because not only can individual species differ in their trophic status, but trophic level status can also differ for different sizes ( ages) of individuals within a species because diets often change with age/ size of the organism. Information on the identity, and size ( age) of consumed aquatic species should be obtained from the fish consumption survey, if available. Information on the diet of consumed aquatic species might be available on a local or regional basis, but more often is scattered about in the scientific literature based on studies of various sites around the United States. If local or regional information is not available, then EPA recommends the use of the most recent version of the document: Trophic Level and Exposure Analysis for Selected Piscivorous Birds and Mammals ( USEPA, 1995d, 1995e, 1995f), which contains information on the dietary composition of numerous aquatic species. This draft document is currently being revised based on peer review comments and is expected to be made final in 1998. 245 Table 2.4.8: Lipid Data for Aquatic Species Included in the Derivation of a National Default Consumption Weighted Lipid Value CSFII Consumption Category Common Name Scientific Name Species Mean Lipid (%) Sample Size CSFII Mean Lipid (%)

Anchovy Northern anchovy Engraulis mordax 11.70 2 7.25 Striped anchovy Anchoa hepsetus 2.80 1 Carp Carp Cyprinus carpio 4.45 1433 4.45 Catfish Black bullhead Ameiurus melas 1.12 11 2.36 Brown bullhead Ameiurus nebulosus 2.79 704 Channel catfish Ictalurus punctatus 5.00 1108 White catfish Ameiurus catus 2.15 46 Yellow bullhead Ameiurus natalis 0.75 29 Clam Butter clam Saxidomus nuttalli 1.22 2 1.68 Geoduck clam Panope generosa 3.20 1 Hard clam Mercenaria mercenaria 1.04 2 Littleneck clam Protothaca staminea 0.75 2 Soft shell clam Mya arenaria 1.29 5 Venus clam Tapes philippinarum 2.60 1 Crab Blue crab Callinectes sapidus 2.33 7 1.40 Dungeness crab Cancer magister 1.15 2 King crab Paralithodes camtschatica 0.80 1 Snow crab Chionoectes bairdi 1.30 1 Croaker Atlantic croaker Micropogonias undulatus 3.30 3 4.77 Spot Leiostomus xanthurus 10.35 2 White croaker Genyonemus lineatus 2.33 7 Yellowfin croaker Umbrina roncador 3.11 1 Estuarine Flatfish Gulf flounder Paralichthys albigutta 0.80 1 1.48 Rainbow smelt( 1) Osmerus mordax 4.50 88 Southern flounder Paralichthys lethostigma 1.20 1 Starry flounder Platichthys stellatus 0.97 3 Summer flounder Paralichthys dentatus 0.40 1 Winter flounder Pseudopleuronectes americanus 1.00 2 Estuarine Salmon( 2) Atlantic salmon Salmo salar 5.65 2 4.55 Chinook salmon Oncorhynchus tshawytscha 2.09 271 Chum salmon Oncorhynchus keta 4.25 2 Coho salmon Oncorhynchus kistuch 2.17 308 Pink salmon Oncorhynchus gorbuscha 5.00 2 Sockeye salmon Oncorhynchus nerka 8.12 4 Flounder Gulf flounder Paralichthys albigutta 0.80 1 0.87 Southern flounder Paralichthys lethostigma 1.20 1 Starry flounder Platichthys stellatus 0.97 3 Table 2.4.8: Lipid Data for Aquatic Species Included in the Derivation of a National Default Consumption Weighted Lipid Value CSFII Consumption Category Common Name Scientific Name Species Mean Lipid (%) Sample Size CSFII Mean Lipid (%)

246 Summer flounder Paralichthys dentatus 0.40 1 Winter flounder Pseudopleurnectes americanus 1.00 2 Freshwater Salmon Atlantic salmon Salmo salar 5.65 2 4.22 Kokanee salmon( 3) Oncorhynchus nerka 2.28 3 Chinook salmon Oncorhynchus tshawytscha 2.09 271 Chum salmon Oncorhynchus keta 4.25 2 Coho salmon Oncorhynchus kistuch 2.17 308 Pink salmon Oncorhynchus gorbuscha 5.00 2 Sockeye salmon Oncorhynchus nerka 8.12 4 Herring Atlantic herring Clupea harengus 13.04 5 10.34 Blueback herring Alosa aestivalis 8.63 3 Pacific herring Clupea pallasi 9.34 8 Mullet Striped mullet Mugil cephalus 4.49 9 4.49 Oyster Eastern oyster Crassostrea virginica 1.94 8 1.62 European oyster Ostrea edulis 1.65 2 Olympia oyster Ostrea lurida 0.50 1 Pacific oyster Crassostrea gigas 2.40 8 Perch White perch Morone americana 5.34 296 3.00 Yellow perch Perca flavescens 0.66 220 Pike Chain pickerel Esox niger 1.21 5 0.84 Northern pike Esox lucius 0.47 356 Scallop Atlantic bay scallop Aequipecten irradians 0.60 1 0.70 Sea scallop Placopectens magellanicus 0.80 2 Scup Scup Stenotomus chrysops 3.70 1 3.70 Shrimp Brown shrimp Penaeus aztecus 0.93 3 0.75 Northern pink shrimp Pandalus borealis 0.78 2 Pink shrimp Penaeus duorarum 0.78 2 White shrimp Penaeus setiferus 0.52 2 Smelt Rainbow smelt Osmerus mordax 4.50 88 4.50 Sturgeon White sturgeon Acipenser transmontanus 1.09 6 1.09 Trout Brook trout Salvelinus fontinalis 1.51 7 4.29 Brown trout Salmo trutta 3.81 142 Cutthroat trout Salmo clarki 1.23 16 Lake trout Salvelinus namaycush 10.90 380 Rainbow trout Oncorhynchus mykiss 4.00 123 ( 1) Information from the CSFII survey indicated that rainbow smelt were included in the calculation of fish consumption rates for estuarine flatfish. ( 2) Because these species are anadromous, data on lipid content were also included for freshwater salmon category. ( 3) Information from the American Fisheries Society publication: Common and Scientific Names of Fishes from the United States and Canada ( AFS, 1991) indicates that freshwater stocks of sockeye salmon are commonly referred to as Kokanee. 247 For the national CSFII survey, very limited data were available to further delineate the identity and size of species consumed within each of the CSFII categories in Table 2.4.7. For most of the CSFII categories, this lack of information was not viewed as problematic, because rather unambiguous assignments of trophic status could be made to these categories ( e. g., all oysters are considered to be trophic level two). However, for other CSFII categories, assignment of trophic status required some reasonable assumptions to be made and therefore reflect greater uncertainty. The following procedures were used in assigning trophic status to the CSFII consumption categories.

1. Data from EPA's draft trophic level document ( USEPA, 1995d, 1995e, 1995f) and other sources were used to estimate the trophic level of species that could reasonably be classified in each of the CSFII consumption categories. Species level trophic assignments were performed as follows.

a. For game fish that correspond to the CSFII categories, data were used for edible size ranges ( about 20 cm [ 8 inches] or larger). b. For species where multiple size ranges were available, preferences was given to the larger specimens in determining the species trophic level. c. Trophic level 2 was assigned to a species if appropriate trophic level data ranged between 1.6 and 2.4; trophic level 3 if trophic level data ranged from 2.5 to 3.4; trophic level 4 if trophic level data were 3.5 or higher. This is consistent with the approach taken in the Great Lakes Water Quality Initiative guidance ( USEPA, 1995c).

2. Once the species level trophic assignments were completed, this information was used to assign a trophic level to each CSFII consumption rate category as follows.

a. In situations where a CSFII category was represented by the vast majority of species within a single trophic level, that trophic level was assigned to the CSFII category ( e. g., trout, estuarine flatfish, smelt). b. In one situation ( catfish), the CSFII consumption rate was equally divided between trophic level 3 and 4 because about half the species were determined to be trophic level 3 and about half trophic level 4. c. For shrimp, trophic level 3 was assigned based on data for the " general shrimp category" in USEPA ( 1995f) because other data ( grass shrimp, mysids) were for species that are not consumed by humans.

3. The results of the trophic level assignments are shown in Table 2.4.9. Table 2.4.9: Trophic Level Assignment of Aquatic Species Corresponding to CSFII Consumption Categories CSFII Consumption Category Common Name Scientific Name Size Trophic Level ( a)

( Mean) Trophic Level ( a)

( Range) Notes ( a) Species Assigned Trophic Level ( b) CSFII Assigned Trophic Level ( c)

Anchovy Northern anchovy Engraulis mordax  3  Feeds on zooplankton 3 3 Adult 3.2  Feeds on large zooplankton Juvenile 3  Feeds on zooplankton Carp Common carp Cyprinus carpio   2.2 3.1 Young feed on zoopl., adults on plants, molluscs, crustacea and become more herbivorous 3 3 10 23 cm 3 2.8 3.1 Up to 23 cm, feed primarily on benthic inverts. > 23 cm 2.4 2.2 2.6 Larger carp (> 23 cm approx) feed primarily on plants and detritus ( 60 70%), benthic inverts. ( 15 35%) and some zoopl (< 15%). Catfish Black bullhead Ameiurus melas  3 2.9 3.2 Seem to consume zooplankton and benthic inverts. throughout life. Indiv. > 15 cm may consume some small fish, but also plant materials. 3 3 ( 50%) 4 ( 50%)

Blue catfish Ictalurus furcatus  3  Assumption. 3 Brown bullhead Ameiurus nebulosus   2.7 3.3 Diet changes with size. 3 > 10cm 3.0 2.7 3.2 > 10cm feeds on 20 30% plants & 70 100% benthic inverts ( burrowing mayfly, scud, chironomid types). some consume small fish as well. Channel catfish Ictalurus punctatus 36 54cm  2.8 4 Changes with age; can grow up to 50 cm or larger. Two studies indicated they consume plants, one other did not 4 5 30cm 3.1  5 30 cm; consumes largely benthic inverts. ( 60 80%), detritus ( 10 15%) and zooplankton ( 10 25%) Catfish ( cont'd) 30 35cm 3.3 3 3.5 30 35cm; consumes fish ( 32%), benthic inverts. ( 40%), zoopl. ( 12%), and detritus ( 15%). Some populations consume up to 25% algae. Table 2.4.9: Trophic Level Assignment of Aquatic Species Corresponding to CSFII Consumption Categories CSFII Consumption Category Common Name Scientific Name Size Trophic Level ( a)

( Mean) Trophic Level ( a)

( Range) Notes ( a) Species Assigned Trophic Level ( b) CSFII Assigned Trophic Level ( c)

Channel catfish Ictalurus punctatus 35 45cm 3.8 3.5 3.9 35 45cm; consumes fish ( 67%), benthic inverts. ( 25%), and detritus ( 8%). Some populations consume up to 25% algae > 45cm 4 4.0 4.2 > 45cm; consumes fish ( 100%) Flat bullhead Ictalurus platycephalus   3.2 3 4 Can grow to large sizes; feeds on molluscs ( primarily clams), bryozoans, & worms 4 Flathead catfish Pylodictis olivaris  3.8  Diet consists primarily of fish with some crayfish, & molluscs. 4 Yellow bullhead Ictalurus natalis 30 46 cm 2.6  Scavengers, often consumes minnows, crayfish, insect larvae, worms and algae 3 Clam Clams ( general)   2.2 2.1 2.4 Filter feeders on plankton, detritus. Includes zooplankton. 2 2 Amethyst gemclam     2.2 2.1 2.4 Filter feeder. 2 Atlantic rangia Rangia cuneata  2.2 2.1 2.4 Filter feeder. 2 Baltic macoma Macoma balthica   2.2 2.1 2.4 Filter feeder. 2 Dwarf surf clam Mulina lateralis  2.2 2.1 2.4 Filter feeder. 2 Crab Blue crab Callinectes sapidus  3.2 2.8 3.4 Feed primarily on molluscs ( 39%), organic debris ( 20%), fish ( 20%), crustaceans ( 15%), plants ( 4%) worms ( 2%) 3 3 Croaker Atlantic croaker Micropogonias undulatus  3  Opportunistic bottom feeders; mostly on polychaetes, copepods, mysids, small clams ( From: Mercer, 1989) 3 3 Estuarine Flatfish Flounder ( general)   3.2 3.0 3.4 Feeds on benthic organisms ( e. g., sea urchins, sand dollars, brittle stars, shrimp, molluscs, & worms) most of which are detritivores.   3 Lefteye flounders ( Bothidae)   3.2 3.0 3.4 Assumed equal to general flounder diet. 3 European flounder Platichthys flesus  3.2 3.0 3.4 Assumed same as general flounder diet. 3 Table 2.4.9: Trophic Level Assignment of Aquatic Species Corresponding to CSFII Consumption Categories CSFII Consumption Category Common Name Scientific Name Size Trophic Level ( a)

( Mean) Trophic Level ( a)

( Range) Notes ( a) Species Assigned Trophic Level ( b) CSFII Assigned Trophic Level ( c)

Righteye flounders   3.2 3.0 3.4 Assumed equal to general flounder diet. 3 Starry flounder Platichthys stellatus  3.2 3.0 3.4 Assumed same as general flounder diet. 3 Winter flounder Pseudopleuronectes americanus  3.2 3.0 3.4 Assumed same as general flounder diet. 3 Smelt ( general)   3  Assumed same TL as other smelt, except for adult smelt in Great Lakes 3 American ( Rainbow) smelt Osmerus mordax  3.1  Feeds on zoopl.; some surface insects 4  3.5  In Great Lakes, > 1yr old feed on smaller fish and on Mysis ( TL3); and other inverts & zooplankton ( TL2)  3.1  During first year, feed on zoopl. 3 Juvenile night smelt Spirinchus starksi  3  Assumed same as other smelt 3 Juvenile top smelt ( Osmeridae)   3  Assumption 3 surf smelt Hypomesus pretiosus  3  Assumed same TL as other smelt. 3 Table 2.4.9: Trophic Level Assignment of Aquatic Species Corresponding to CSFII Consumption Categories CSFII Consumption Category Common Name Scientific Name Size Trophic Level ( a)

( Mean) Trophic Level ( a)

( Range) Notes ( a) Species Assigned Trophic Level ( b) CSFII Assigned Trophic Level ( c)

Flounder Flounder ( general)   3.2 3.0 3.4 Feeds on benthic organisms ( e. g., sea urchins, sand dollars, brittle stars, shrimp, molluscs, & worms) most of which are detritivores.  3 Lefteye flounders ( Bothidae)   3.2 3.0 3.4 Assumed equal to general flounder diet. 3 European flounder Platichthys flesus  3.2 3.0 3.4 Assumed same as general flounder diet. 3 Righteye flounders   3.2 3.0 3.4 Assumed equal to general flounder diet. 3 Starry flounder Platichthys stellatus  3.2 3.0 3.4 Assumed same as general flounder diet. 3 Winter flounder Pseudopleuronectes americanus  3.2 3.0 3.4 Assumed same as general flounder diet. 3 Freshwater Salmon Kokanee salmon Oncorhynchus nerka 4  Larger specimens. 4 4 Herring Herring ( general)   3.2 3.1 3.4 Feeds primarily on copepods and krill.  3 Atlantic herring Clupea harengus  3.2 3.1 3.4 Feeds primarily on copepods and krill. 3 Pacific herring Clupea pallasi   3.2 3.1 3.4 Feeds primarily on copepods and krill. 3 Mullet Striped mullet Mugil cephalus  2.2  Feeds on plant material, detritus, & plankton. 2 2 Oyster Molluscs ( general)   2.1 2.0 2.2 Bivalves feed on plankton  2 Mussels ( general)   2.2 2.1 2.4 Filter feeders on plankton, detritus, zooplankton.

Perch Yellow perch Perca flavescens 20 30cm 3.4 3.1 3.8 20 30cm; consumes 10% zoopl., 50% benthic inverts, 34% fish ( some pops.); nearly 100% fish in other populations. 4 4 Table 2.4.9: Trophic Level Assignment of Aquatic Species Corresponding to CSFII Consumption Categories CSFII Consumption Category Common Name Scientific Name Size Trophic Level ( a)

( Mean) Trophic Level ( a)

( Range) Notes ( a) Species Assigned Trophic Level ( b) CSFII Assigned Trophic Level ( c)

Pike Northern pike Esox lucius > 10cm 4  > 10cm; diet primarily all fish. 4 4 Pickerel ( redfin & grass) Esox americanus larger specimens 4  Larger specimens consume small fish 4 Scallop Molluscs ( general)   2.1 2.0 2.2 Bivalves feed on plankton 2 2 Scup Scup Stenotomus chrysops  3  Bottom feeder, primarily on molluscs, worms, and small crustaceans ( Jordan and Evermann, 1969) 3 Shrimp Shrimp ( general) ( Palaemonidae)  3.0  Filter feeding on zoopl. 3 3 Grass shrimp Palaemonetes sp.  2.1  Detritivore, primarily on plant material 2 Mysis Mysis relicta  3.5 3 4 Cold water forms; during warm months, restricted to hypolimnion 4 Smelt Smelt ( general)   3  Assumed same TL as other smelt, except for adult smelt in Great Lakes  3 American ( Rainbow) smelt Osmerus mordax  3.1  Feeds on zoopl.; some surface insects 4  3.5  In Great Lakes, > 1yr old feed on smaller fish and on Mysis ( TL3); and other inverts & zooplankton ( TL2) American ( Rainbow) smelt Osmerus mordax  3.1  During first year, feed on zoopl.

Juvenile night smelt Spirinchus starksi  3  Assumed same as other smelt 3 Juvenile top smelt ( Osmeridae)   3  Assumption 3 surf smelt Hypomesus pretiosus  3  Assumed same TL as other smelt. 3 Table 2.4.9: Trophic Level Assignment of Aquatic Species Corresponding to CSFII Consumption Categories CSFII Consumption Category Common Name Scientific Name Size Trophic Level ( a)

( Mean) Trophic Level ( a)

( Range) Notes ( a) Species Assigned Trophic Level ( b) CSFII Assigned Trophic Level ( c)

Sturgeon White sturgeon Acipenser transmontanus   3 4 Estimated range based on following account by Jordan & Evermann ( 1969): Can grow to several hundred pounds, diet reportedly consists of small plants & small animals, including small fish. One young specimen ( 25 in.) had 11 minnows in its stomach, larger specimens had several suckers about 12 in. long. ( Jordan & Evermann, 1969). 4 4 Lake sturgeon Acipenser rubicundus    3 4 Estimated range based on following account by Jordan & Evermann ( 1969): Can grow up to 100 pounds, averages about 40 50 pounds for adults; primarily a bottom feeder, reportedly feeding on small gastropods, crustaceans, insect larvae and small fishes 4 Trout Brook trout Salvelinus fontinalis 10 40cm 3.2  10 40cm; at most, 7 8% fish in diet; remainder primarily benthic inverts. but also some zoopl. in some populations 3 4 Cutthroat trout Salmo clarki < 40cm 3  < 40cm; consumes invertebrates 4 > 40cm 3.2  > 40cm; becomes piscivorous Table 2.4.9: Trophic Level Assignment of Aquatic Species Corresponding to CSFII Consumption Categories CSFII Consumption Category Common Name Scientific Name Size Trophic Level ( a)

( Mean) Trophic Level ( a)

( Range) Notes ( a) Species Assigned Trophic Level ( b) CSFII Assigned Trophic Level ( c)

Trout ( cont'd) old adults 4  Assumption for oldest specimens Dolly Varden trout Salvelinus malma     3 4 TL changes with age 4 10 30cm 3  10 30cm; diet 100% benthic inverts. Dolly Varden trout Salvelinus malma 30 40cm 3.75  30 40cm; diet 75% fish, 17% benthic inverts. > 40cm 4  > 40cm; diet consists of 100% fish Lake trout Salvelinus namaycush 20 30cm 3.7 3.5 4.0 20 30cm; feeds primarily on small fish ( 70%) and benthic inverts. ( 30%) 4 30 40cm 3.9 3.7 4.1 30 40cm; feeds primarily on fish ( 90%) and some benthic inverts. ( 10%) > 40cm 4.2 4.0 4.5 > 40cm; feeds entirely on fish; in L. Michigan, feed on alewives, which feed on Mysis, which feed on zoopl. Rainbow trout Oncorhynchus mykiss < 30cm 3  < 30cm; diet completely of benthic inverts. or both inverts. & zoopl. 4 30 50cm 3.6  30 50cm; diet 35 90% fish, 25 75% benthic inverts, zoopl., terrestrial insects > 50cm 4  > 50cm; diet of 100% fish Footnotes: ( a) Unless otherwise specified, information on trophic status was obtained from U. S. EPA, ( 1995d, 1995e, 1995f). Game fish data were limited to specimens considered to be representative of the edible size range ( i. e., sizes ranges of 20cm or larger). ( b) In determining species trophic level assignments, preference was given to data on larger specimens. Trophic level 4 was assigned to a species with data indicating TL 3.5 or higher; trophic level 3 was assigned to a species with data indicating TL 2.5 to 3.4; trophic level 2 assigned for TL 1.5 2.4. ( c) In determining CSFII category trophic level assignments, best professional judgement was used. For example, the CSFII category for catfish includes 4 species that are assigned TL3 and 3 species assigned as TL4. Thus, it is assumed that half ( 50%) of consumption in the catfish CSFII category is from TL3 and half from TL4. Except for shrimp, all other CSFII categories included species that either were exclusively or predominately one trophic level ( e. g., trout, estuarine flatfish, smelt). 255 f R ' j CR i CR tot C f R , i ( Equation 2.4.26) Calculation of Consumption Weighted Lipid Content, by Trophic Level. Using consumption rate data from CSFII ( daily average per capita estimates of individuals 18 years and older   Table 2.4.7), the mean lipid content estimated for organisms assigned to each CSFII category ( Table 2.4.8), and the trophic level assignments of each CSFII consumption category ( Table 2.4.9), consumption weighted mean lipid content determined within each trophic level according to the following equation.

where:

f R = Lipid fraction representative of aquatic species eaten by the target population that correspond to a given trophic level CR i = Consumption rate of species " i" of a given trophic level eaten by the target population CR tot = Consumption rate of all species at that same trophic level eaten by the target population f R , i = Lipid fraction of species " i" eaten by the target population Calculation of the consumption weighted lipid content values is shown in Table 2.4.10. The mean, consumption weighted percent lipid values were calculated as ( expressed here to 2 significant figures for convenience):

Trophic Level Two: 2.3% Trophic Level Three: 1.5% Trophic Level Four: 3.1%

Because of limitations in the availability and precision of the used to estimate consumption rates, lipid content, and trophic level status, uncertainty exists in the estimation of national default, consumption weighted lipid content. To illustrate some of this uncertainty, " high" and " low" estimates of the consumption weighted lipid content values were determined using the species with the highest and lowest species mean lipid value, respectively, within each CSFII category. " High" and " low" estimates of percent lipid content values within each trophic level are:

" High" Estimate for Trophic Level Two: 3.0% " High" Estimate for Trophic Level Three: 2.2% " High" Estimate for Trophic Level Four: 6.2%

" Low" Estimate for Trophic Level Two: 1.5% " Low" Estimate for Trophic Level Three: 0.77% " Low" Estimate for Trophic Level Four: 0.91% 256 The reason that there is not a greater difference between the mean lipid content values ( where each species within a CSFII category was given equal weighting) and the " high" and " low" estimates is likely because the mean consumption rates in the CSFII survey are weighted heavily by relatively lean aquatic organisms such as shrimp, crab, perch, and flounder. Therefore, because the consumption of aquatic organisms may differ on a local or regional basis from that reflected in the CSFII survey, EPA recommends that States and Tribes give preference to using local and regional data on consumption patterns over national default estimates, when available.

<IP_ADDRESS> Freely Dissolved Fraction The next step in calculating a BAF used in deriving an AWQC involves adjusting the baseline BAF to account for the freely fraction of the chemical at the site( s) to which the AWQC will apply. The same equation used to estimate the freely dissolved fraction for determining a baseline BAF ( Equation 2.4.11) is used to estimate the freely dissolved fraction for determining the AWQC BAF. However, in this case, however, the POC and DOC values should be based on the site( s) where the BAF and the criterion will be applied and not where the samples were collected for determining the BAF. If POC and DOC data are not available for the site( s) to which the AWQC will apply, then data from sites closely related to those to which the AWQC sites can be used. Care should be taken to ensure that conditions affecting the POC and DOC concentrations at the surrogate sites are representative of conditions at the AWQC sites. States and tribes are encouraged to use local or regional data when appropriate and scientifically defensible. If such data are unavailable, then the default values for POC and DOC can be used. EPA has developed national default values of 0.48 mg/ L ( 4.8 x 10 7 kg/ L) for POC and 2.9 mg/ L ( 2.9x 10 6 kg/ L) for DOC. Both of these values are 50th percentile values ( medians) based on an analysis of over 132,000 DOC values and 81,000 POC values contained in EPA's STORET data base. These default values reflect the combination of values for streams, lakes and estuaries across the United States. Further delineation of the POC and DOC concentrations in different water body types is provided in Table 2.4.11. These default values, which are derived at a more disaggregated level may provide more appropriate estimates of POC and DOC concentrations associated with the field BAF study compared to the national default medians listed above. The K ow value for the chemical is the same as used for deriving the baseline BAF for the chemical. 257 Table 2.4.10: Calculation of National Default Consumption Weighted Mean Lipid Content of Consumed Aquatic Organisms Habitat CSFII Category ( 1) Assigned Trophic Level( 2) Trophic Level Weighting Factor( 3) Average Percent Lipids ( 4) Mean Consumption Rate ( g/ person/ day) Trophic Level Weighted Mean Consumption rate ( g/ person/ day) CSFII Category Weights Consumption Weighted Percent Lipid Values Estuarine clam 2 1.0 1.68 0.03146 0.03146 0.09046 0.15219 Estuarine mullet 2 1.0 4.49 0.08756 0.08756 0.25176 1.13069 Estuarine oyster 2 1.0 1.62 0.22555 0.22555 0.64852 1.05162 Estuarine scallop 2 1.0 0.70 0.00322 0.00322 0.00926 0.00648 Estuarine anchovy 3 1.0 7.25 0.00292 0.00292 0.00078 0.00568 Freshwater carp 3 1.0 4.45 0.05727 0.05727 0.01538 0.06842 Freshwater catfish 3 0.5 2.36 1.18227 0.59114 0.15874 0.37486 Estuarine crab 3 1.0 1.40 0.37126 0.37126 0.09970 0.13918 Estuarine croaker 3 1.0 4.77 0.06749 0.06749 0.01812 0.08648 Estuarine estuarine flatfish 3 1.0 1.48 0.52735 0.52735 0.14161 0.20927 Estuarine flounder 3 1.0 0.87 0.29941 0.29941 0.08040 0.07022 Estuarine herring 3 1.0 10.34 0.03925 0.03925 0.01054 0.10897 Estuarine scup 3 1.0 3.70 0.00068 0.00068 0.00018 0.00068 Estuarine shrimp 3 1.0 0.75 1.72959 1.72959 0.46446 0.34821 Estuarine smelt 3 1.0 4.50 0.03753 0.03753 0.01008 0.04535 Freshwater catfish 4 0.5 2.36 1.18227 0.59114 0.35205 0.83133 Freshwater freshwater salmon 4 1.0 2.28 0.01096 0.01096 0.00653 0.01486 Estuarine perch 4 1.0 3.00 0.60368 0.60368 0.35952 1.07956 Freshwater pike 4 1.0 0.84 0.02337 0.02337 0.01392 0.01168 Estuarine sturgeon 4 1.0 1.09 0.00054 0.00054 0.00032 0.00035 Freshwater trout 4 1.0 4.29 0.44946 0.44946 0.26767 1.14837 Trophic Level Sum of Consumption Rates ( g/ pers./ day) Sum of Weights Consumption Weighted Mean Percent Lipid Trophic Level 2 0.34779 1.00 2.34%

Trophic Level 3 3.72389 1.00 1.46%

Trophic Level 4 1.67915 1.00 3.09%

Total: 5.75082 ( 1) Source of consumption data: USDA's Continuing Survey of Food Intakes by Individuals ( CSFII) combined from 1989, 1990 & 1991 for individuals 18 years and older ( USEPA, 1998b and Table 2.4.7). ( 2) Trophic level designation of organisms corresponding to CSFII consumption categories, as described in the text and Table 2.4.9. ( 3) Trophic level weighing factor used to apportion consumption rates to multiple trophic levels for catfish only ( see text). ( 4) Mean lipid content for species assigned to each CSFII category as described in the text and Table 2.4.8. 258 Table 2.4.11: National Default Values for POC and DOC in U. S. Water Bodies WATER BODY TYPE DOC ( mg/ L) POC ( mg/ L)

50th% ( Median) Mean 50th% ( Median) Mean Stream/ River 4.0 6.2 0.70 1.3 Lake 2.1 3.0 0.31 0.43 Estuary 2.7 3.4 0.90 1.1 All Types 2.9 4.9 0.48 0.83 Source: USEPA STORET data base, data retrieval February, 1996. Sample sizes for DOC are: 77,637 ( stream/ river); 40,472 ( lake); 14,376 ( estuary); 132,485 ( all water bodies) Sample sizes for POC are: 30,236 ( stream/ river); 39,931 ( lake); 10,920 ( estuary); 81,087 ( all water bodies)

2.4.6 Determining BAFs for Inorganic Substances Unlike organic chemicals, the lipid BAF relationship does not generally apply to the determination of BAFs for inorganic chemicals. Thus, BAFs and BCFs for inorganics should not be expressed on a lipid normalized basis, and are not as transferable from one species to another, or one tissue to another, as with organic chemicals. Bioaccumulation of some trace metals is substantially greater in internal organs than muscle tissue. For example, BCFs for various tissues of the rainbow trout after exposure to cadmium for 178 days are as follows ( Giles, 1988):

liver 325 kidney 75 gut and skin 7 muscle 1 Merlini and Pozzi ( 1977) reported that lead bioconcentrated 30 times more in bluegill liver than in bluegill muscle tissue after eight days. Because of the differential uptake to different tissues and species, the BAFs should be measured in edible tissues.

BAFs or BCFs measured in plants or invertebrate animals may be available. However, these factors might be one or more orders of magnitude greater than BAFs or BCFs for the edible tissue of fish as noted in Table 5 in each of the EPA criteria documents for cadmium, copper, lead and nickel ( USEPA, 1985a; USEPA, 1985b; USEPA, 1985c; and USEPA, 1986). For this reason, invertebrate BAFs and BCFs should only be used in the derivation of human health criteria when they are considered to be a significant component of the diet of the target consumers. 259 Although bioaccumulation of many inorganic chemicals is similar to their bioconcentration, mercury and certain other metals are subject to methylation through microbial action in nature, and may biomagnify through the food chain. For example, research demonstrates that methyl mercury is bioaccumulative in fish and biomagnifies in aquatic food webs ( Grieb et al. 1990; Gardner, 1978).

The following two procedures, in order of priority, should be used to estimate BAFs for inorganic chemicals. EPA is not aware of any other generic procedures for predicting the BAF for these substances.

Field measured BAFs are the most preferred BAFs for inorganic chemicals. Section <IP_ADDRESS> ( Field Measured BAFs) describes data requirements for measuring BAF values using field data for nonpolar organic chemicals. These requirements are applicable to field measured BAFs for inorganic chemicals as well, except that inorganic BAFs should not be lipid normalized because bioaccumulation of inorganics is not proportional to lipid content. However, as noted above, inorganic bioaccumulation can differ dramatically between tissues. Thus, BAFs based on uptake into edible tissue should be used to calculate human health criteria.

If field measured BAFs are not available for inorganic chemicals, a laboratory BCF may be used to estimate bioaccumulation of inorganic substances from water. The BCF may be used because for most inorganic substances, bioaccumulation and bioconcentration are similar. Section <IP_ADDRESS> ( Predicted BAF Based on Laboratory Measured BCF and a Food Chain Multiplier) describes acceptable data for measuring BCFs for organic chemicals in the laboratory, which are applicable to BCFs measured for inorganic chemicals. For inorganic chemicals where dietary exposure forms a significant portion of the exposure to target organisms, ( e. g. mercury, selenium) BCFs should be used in conjunction with field derived food chain multipliers.

2.4.7 Example Calculations The two examples below illustrate how BAFs are developed using two of the four methods recommended for deriving BAFs for nonpolar organic chemicals for use in establishing AWQC for human health. The first example illustrates the development of a BAF when field measured BAFs are available. The second example illustrates the development of BAFs using a laboratory measured BCF and a food chain multiplier.

<IP_ADDRESS> Example 1: Field Measured BAF for Chemical M The calculation of a BAF used in the derivation of a human health criteria is a two step process. The first step is to derive baseline BAFs for appropriate trophic levels. The second step is to derive BAFs that can be used in deriving human health AWQC. Each of these steps are illustrated below. 260 Baseline BAF fd R ' Measured BAF t T f fd & 1 1 f R ( Equation 2.4.27) Baseline BAF for Chemical M This example illustrates the development of a baseline BAF appropriate for trophic level four for a lipophilic chemical M. Data are available from Lake Washington ( a hypothetical lake) on the total concentration of chemical M in fish tissue in lake trout and the water column. A review of the dietary preferences of lake trout indicates that this organism is at trophic level four for larger size ranges commonly consumed by the target population ( USEPA, 1995d, 1995e, 1995f). The development of a baseline BAF for a given trophic level requires information on a field measured BAF ( Measured BAFtT ), the fraction of the chemical that is freely dissolved in the ambient water ( f fd), and the fraction lipid content of the species sampled ( f R ) . The equation for calculating a baseline BAF using a field measured BAF is:

To determine a field measured BAF, information is needed on the total concentration of chemical M in fish tissue and in ambient water at the site of sampling. For this example, the mean total concentration for chemical M in fish tissue is 100 ng/ g and the mean total water column concentration 160 pg/ L. Data from the field studies indicates that the mean water column concentration reflects adequate temporal and spatial averaging based on the K ow of this chemical and is representative of the average exposure of fish to chemical M. The field measured BAF tT for chemical M is 625,000 L/ kg, as demonstrated below.

Field measured BAFtT = Total concentration of chemical M in fish tissue Total concentration of chemical M in the water column ( Equation 2.4.28)

Field measured BAFtT = ( 100 ng/ g)( 1,000 pg/ ng)( 1,000 g/ kg) = 625,000 L/ kg tissue 160 pg/ L ( Equation 2.4.29)

To determine the fraction of chemical M that is freely dissolved in the ambient water requires information on the particulate organic carbon ( POC) and dissolved organic carbon ( DOC) in the ambient water where the samples were collected and the K ow of chemical M. For this example, the median POC concentration from Lake Washington, where the samples were collected, is 0.6 mg/ L 261 f fd ' 1 [ 1 % ( POC @ K ow) % ( DOC @ K ow 10 )]

( Equation 2.4.30)

f fd ' 1 [ 1 % ( 6.0 x 10 & 7kg/ L @ 100,000 L/ kg) % ( 8.0 x 10 & 6 kg/ L @ 100,000 10 L/ kg)] ' 0.8772 ( Equation 2.4.31)

Baseline BAF fd R ' 625,000 0.8772 & 1 1 0.08 ' 8,906,166 L/ kg & lipid ( Equation 2.4.32) ( 6.0 x 10 7 kg/ L) and the median DOC concentration is 8.0 mg/ L ( 8.0 x 10 6 kg/ L). Importantly, the POC and DOC concentrations used in calculating the freely dissolved fraction for baseline BAFs is from the waterbody used in the BAF study. Use of default POC and DOC concentrations in the derivation of baseline BAFs is not appropriate. The K ow for chemical M is 100,000 or a log K ow of 5.0. The fraction freely dissolved for chemical M is 0.8722, as shown below.

The freely dissolved fraction has been expressed to four significant digits for convenience. The scientific basis supporting this equation for estimating the freely dissolved fraction is described in Section <IP_ADDRESS> and Appendix D.

Finally, the mean fraction lipid content of the fish species sampled in Lake Washington was 8 percent. Using the baseline BAF equation and information on the field measured BAF, the fraction freely dissolved, and the fraction lipid content provides a baseline BAF for lake trout of 8,906,166, which is illustrated below.

For the purposes of this example, it has been assumed that only one acceptable BAF value is available for trophic level four organisms. Thus, the baseline BAF for trophic level four is equal to this baseline BAF. Had other acceptable field measured BAFs been available for trophic level four 262 BAF for AWQC( TL n) ' [ ( Baseline BAF fd R ) TL n @ ( f R ) TL n % 1] @ ( f fd)

( Equation 2.4.33) organisms, then the baseline BAF for trophic level four would have been calculated as the geometric mean of the acceptable baseline BAFs at trophic level four.

BAF for Chemical M to Be Used in Deriving AWQC After the derivation of trophic level specific baseline BAFs for chemical M ( described in the previous section), the next step is to calculate BAFs that will be used in the derivation of AWQC. This step is necessary to adjust the baseline BAFs to conditions that are expected to affect the bioavailability of chemical M at the sites applicable to the AWQC. Derivation of AWQC BAFs requires information on: ( 1) the baseline BAF at appropriate trophic levels, ( 2) the percent lipid of the aquatic organisms consumed by humans at the site( s) of interest ( trophic level specific), and ( 3) the freely dissolved fraction of the chemical in ambient water at the site( s) of interest. For each trophic level, the equation for deriving a BAF to used in deriving AWQC is:

where: BAF for AWQC ( TL n) = BAF at trophic level " n" used to derive AWQC based on site conditions for lipid content of consumed aquatic organisms for trophic level " n" and the freely dissolved fraction in the site water Baseline BAF R f d ( TL n) = BAF expressed on a freely dissolved and lipid normalized basis for trophic level " n" f R ( TL n) = Fraction lipid of aquatic species consumed at trophic level " n" f fd = Fraction of the total chemical in water that is freely dissolved For the purposes of this example, an AWQC BAF is being calculated only for aquatic organisms at one trophic level ( trophic level four). If fish consumption data indicates the target population consumes significant quantities from multiple trophic levels, then AWQC BAFs should be derived for each of the appropriate trophic levels.

For chemical M, the baseline BAF at trophic level four is calculated to be 8,906,166 L/ kg lipid as described above. The fraction lipid content of aquatic species consumed by the target population at trophic level four is assumed to be 3.1% based on the national default lipid content for trophic level four derived in Section <IP_ADDRESS>. The freely dissolved fraction of chemical M that is expected in the sites applicable to the AWQC was determined to be 0.9615. This value is calculated as shown below using hypothetical expected POC and DOC concentrations at the sites applicable to the AWQC of 263 f fd ' 1 [ 1 % ( POC @ K ow) % ( DOC @ K ow 10 )]

( Equation 2.4.34)

f fd ' 1 [ 1 % ( 3.0 x 10 ! 7 kg/ L @ 100,000 L/ kg) % ( 1.0 x 10 ! 6 kg/ L @ 100,000 10 L/ kg)]

( Equation 2.4.35) 0.3 mg/ L ( 3.0 x 10 7 kg/ L) and 1.0 mg/ L ( 1.0 x 10 6 kg/ L), respectively, and the same K ow of 100,000 for chemical M.

f fd = 0.9615 Using the AWQC BAF equation described previously, the AWQC BAF for trophic level four organisms is calculated to be 265,463 L/ kg as shown below.

AWQC BAF for Trophic Level Four = [( 8,906,166 L/ kg lipid)°( 0.031) + 1] ° ( 0.9615) = 265,463 L/ kg tissue This AWQC BAF relates the total concentration in water to the total concentration in tissue of trophic level four organisms, based on the expected conditions that would affect the bioavailability of chemical M ( i. e., freely dissolved fraction at AWQC sites and lipid content of consumed aquatic organisms).

<IP_ADDRESS> Example 2: Laboratory Measured BCF for Chemical R When a field measured BAFtT or field measured BSAF are not available, a laboratorymeasured BAFtT along with a food chain multiplier should be used to derive a baseline BAF and then an AWQC BAF for use in deriving human health criteria.

Baseline BAF for Chemical R The development of a baseline BAF R f d for chemical R specific to a given trophic level requires information on a laboratory measured BCF ( measured BCF tT ), the fraction of the chemical that is freely dissolved in the test water ( f fd), the fraction lipid content of the species sampled ( f R ) , and the food chain multiplier for the chemical ( FCM). For a given trophic level, the equation for calculating a baseline BAF R f d using a laboratory BCF tT and food chain multiplier is: 264 f fd ' 1 [ 1 % ( POC @ K ow) % ( DOC @ K ow 10 )]

( Equation 2.4.39) Baseline BAF fd R ' ( FCM) Measured BCF t T f fd & 1 1 f R ( Equation 2.4.36)

The basis of this equation is described in Section <IP_ADDRESS>.

The laboratory measured BCF requires information on the total concentration of chemical R in fish tissue and the total concentration of chemical R in the test water. For this example, the mean total fish tissue concentration for chemical R is 10 ng/ g and the mean total test water concentration is 3 ng/ L. The laboratory measured BCF is 3333 L/ kg.

Laboratory measured BCF tT = Total concentration of chemical R in fish tissue Total concentration of chemical R in test water ( Equation 2.4.37)

Laboratory measured BCF tT = ( 10 ng/ g)( 1,000 g/ Kg) = 3333 L/ kg  tissue 3 ng/ L ( Equation 2.4.38)

To determine the fraction of chemical R that is freely dissolved in the test water requires information on the particulate organic carbon ( POC) and dissolved organic carbon ( DOC) in the test water and the K ow of chemical R. For this example, the median POC concentration in the test water is 0.6 mg/ L ( 6.0 x 10 7 kg/ L) and the median DOC concentration is 8.0 mg/ L ( 8.0 x 10 6 kg/ L). The K ow for chemical R is 10,000 or a log K ow of 4.0. The fraction freely dissolved for chemical R is 0.9860, as shown below. 265 f fd ' 1 [ 1 % ( 6.0 x 10 & 7 kg/ L @ 10,000 L/ kg) % ( 8.0 x 10 & 6 kg/ L @ 10,000 10 L/ kg)] ' 0.9862 ( Equation 2.4.40)

BAF for AWQC( TL n) ' [ ( Baseline BAF fd R ) TL n @ ( f R ) TL n % 1] @ ( f fd) ( Equation 2.4.42) The freely dissolved fraction has been expressed to four significant digits for convenience. The scientific basis supporting this equation is explained in Section <IP_ADDRESS> and Appendix D.

The fraction lipid content of the fish species sampled in the laboratory is 8 percent. The foodchain multiplier based on a log K ow of 4 is 1.072, as indicated in Table 2.4.4 ( assuming mixed benthic and pelagic food web structure and trophic level four for the tested species). Using the baseline BAF R f d equation and the information on the laboratory measured BCF tT , the fraction freely dissolved, the fraction lipid content, and the FCM provides a baseline BAF R f d of 45,274 L/ kg  lipid, which is used in the derivation of the BAF as described in the next section.

Baseline BAF fd R ' ( 1.072) 3333 0.9862 & 1 1 0.08 ' 45,274 L/ kg & lipid ( Equation 2.4.41)

For the purposes of this example, it has been assumed that only one acceptable baseline BAF value could be derived for trophic level four organisms. Thus, the baseline BAF for trophic level four is equal to this baseline BAF. Had other acceptable BCFs been available for trophic level four organisms, then the trophic level four baseline BAF would have been calculated as the geometric mean of the acceptable BCF predicted baseline BAFs for trophic level four.

AWQC BAF for Chemical R After the derivation of trophic level specific baseline BAFs for chemical R ( described in the previous section), the next step is to calculate BAFs that will be used in the derivation of AWQC. This step is necessary to adjust the baseline BAFs to conditions that are expected to affect the bioavailability of chemical R at the sites applicable to the AWQC. Derivation of AWQC BAFs requires information on: ( 1) the baseline BAF at appropriate trophic levels, ( 2) the percent lipid of the aquatic organisms consumed by humans at the site( s) of interest ( trophic level specific), and ( 3) the freely dissolved fraction of the chemical in ambient water at the site( s) of interest. For each trophic level, the equation for deriving a BAF to used in deriving AWQC is: 266 f fd ' 1 [ 1 % ( POC @ K ow) % ( DOC @ K ow 10 )]

( Equation 2.4.43)

f fd ' 1 [ 1 % ( 4.8 x 10 ! 7 kg/ L @ 10,000 L/ kg) % ( 2.9 x 10 ! 6 kg/ L @ 10,000 10 L/ kg)

( Equation 2.4.44)

f fd ' 0.9924 where:

BAF for AWQC ( TL n) = BAF at trophic level " n" used to derive AWQC based on site conditions for lipid content of consumed aquatic organisms for trophic level " n" and the freely dissolved fraction in the site water Baseline BAF R f d ( TL n) = BAF expressed on a freely dissolved and lipid normalized basis for trophic level " n"

f R ( TL n) = Fraction lipid of aquatic species consumed at trophic level " n"

f fd = Fraction of the total chemical in water that is freely dissolved For the purposes of this example, an AWQC BAF for chemical R is being calculated only for aquatic organisms at one trophic level ( trophic level four). If fish consumption data indicates the target population consumes significant quantities from multiple trophic levels, then AWQC BAFs should be derived for each of the appropriate trophic levels.

For chemical R, the baseline BAF at trophic level four is calculated to be 45,274 L/ kg lipid as described above. The fraction lipid content of aquatic species consumed at trophic level four is assumed to be 3.1% based on the national default lipid content for trophic level four derived in Section <IP_ADDRESS>. The freely dissolved fraction of chemical R that is expected in the sites applicable to the AWQC was determined to be 0.9924. This value is calculated as shown below using hypothetical expected POC and DOC concentrations at the sites applicable to the AWQC of 0.48 mg/ L ( 4.8 x 10 7 kg/ L) and 2.9 mg/ L ( 2.9 x 10 6 kg/ L), respectively, and the same K ow of 10,000 for chemical R.

Using the AWQC BAF equation described previously, the AWQC BAF for trophic level four organisms is calculated to be 1,394 L/ kg as shown below. 267 AWQC BAF for Trophic Level Four = [ 45,274 L/ kg lipid)°( 0.031) + 1] ° ( 0.9924) = 1,394 L/ kg tissue This AWQC BAF relates the total concentration in water to the total concentration in tissue of trophic level four organisms, based on the expected conditions that would affect the bioavailability of chemical R ( i. e., freely dissolved fraction at AWQC sites and lipid content of consumed aquatic organisms).

2.4.8 Trophic Level Specific Fish Consumption Rates When local or regional data are unavailable for calculating fish and shellfish consumption rates, EPA has derived national default consumption rates of 17.8 g/ person/ d, 39 g/ person/ d, and 86.3 g/ person/ d based on the 90th, 95th and 99th percentile of average per capita fish consumption from the adult U. S. population ( see Section 2.3 on exposure). These default consumption figures reflect total consumption of aquatic organisms across all trophic levels. However, as described in above, EPA recommends that BAFs be determined separately for specific trophic levels because accumulation of chemicals is often related to the trophic position of the aquatic organism, particularly for highly persistent, lipophilic organic chemicals. The question then becomes how to best relate available fish consumption rates to the trophic level specific BAFs in the calculation of AWQC.

When calculating AWQC, EPA recommends that if possible, fish consumption rates be determined for individual trophic levels for which BAFs have been derived. For example, if available fish and shellfish consumption survey data indicate that the target population is consuming significant portions of aquatic organisms at trophic levels two, three, and four, then both BAFs and fish consumption rates should be determined for each of these trophic levels to provide the most accurate representation of contaminant exposure via the consumption of aquatic organisms. In this example, applying the total consumption rate from all three trophic levels to a BAF that is derived for a single trophic level may not accurately reflect likely exposure to the target population, if BAFs differ greatly by trophic level.

Calculating fish consumption rates for individual trophic levels requires information on the trophic status of consumed species from the consumption survey. Determination of trophic status of aquatic organisms is best determined on a local or regional basis and should involve consideration of the size ( age) of aquatic organisms in addition to their dietary preferences. If local or regional information is not available, then EPA recommends the use of the most recent version of the document: Trophic Level and Exposure Analysis for Selected Piscivorous Birds and Mammals ( USEPA 1995d, 1995e, 1995f), which contains information on the dietary composition of numerous aquatic species. This draft document is currently being revised based on peer review comments and is expected to be made final in 1998. Described below is the derivation of trophic level specific fish consumption rates for EPA's CSFII based, national default fish consumption rates listed above. 268 f( FI, TL n) ' FI( TL n)

FI( all TL) In estimating trophic level specific consumption rates appropriate to the national default consumption rates from the CSFII consumption survey ( USEPA, 1998b), EPA first estimated the trophic level of aquatic organisms corresponding to each of the CSFII consumption categories for mean per capita consumption of adults ( see Table 2.4.9 and associated text for trophic level determinations of the various CSFII consumption categories; see Table 2.4.7 for mean per capita consumption rates from the CSFII survey). Since the national default consumption rates of 17.8, 39.0, and 86.3 g/ person/ day reflect consumption at the 90th, 95th and 99th percentiles, respectively, trophic level assignments would have ideally been made according to consumption patterns corresponding to these higher percentiles because consumption patterns might differ at higher percentiles. However, inherent limitations in the data from the CSFII survey prevented a meaningful assessment of consumption patterns at these upper percentiles. Therefore, the consumption pattern reflective of mean per capita consumption rates was assumed to adequately reflect consumption at the higher consumption rate percentiles.

The second step involved calculating the fraction of total fish and shellfish consumption at trophic level two, three and four using the mean per capita consumption rates of adults from CSFII survey ( Table 2.4.7). The fractions of total fish consumption at specific trophic levels is shown below:

where:

f ( FI, TL n) = Fraction of total mean per capita fish consumption at trophic level " n" FI ( TL n) = Mean per capita fish consumption rate at trophic level " n" ( g/ person/ day) FI ( TL all) = Total mean per capita fish consumption rate for all trophic levels ( g/ person/ day)

Fraction total fish consumption at:

Trophic Level Two: 0.06048 = 0.34779 ( g/ pers./ day) / 5.75082 ( g/ pers./ day) Trophic Level Three: 0.64754 = 3.72389 ( g/ pers./ day) / 5.75082 ( g/ pers./ day) Trophic Level Four: 0.29198 = 1.67915 ( g/ pers./ day) / 5.75082 ( g/ pers./ day)

These fractions indicate that on a national, per capita average basis, the majority of fish and shellfish consumption is occurring at trophic level three, followed by trophic level trophic level four. This is corroborated by the comparatively greater consumption of shrimp, catfish, perch, estuarine flatfish, trout, crab, and flounder ( Table 2.4.7). Finally, the trophic level specific consumption rates 269 FI i th percentile ( TL n) ' FI i th percentile ( all TL) @ f ( FI, TL n) applicable to 90th, 95th, and 99th percentile national default consumption values were calculated using the following equation:

where:

FI ith percentile ( TL n) = Estimated fish consumption rate at trophic level " n" for the ith percentile FI ith percentile ( TL all) = Total fish consumption rate for all trophic levels for the ith percentile f ( FI, TL n) = Fraction of total mean per capita fish consumption at trophic level " n" ( determined above)

Trophic level specific consumption rates ( in g/ person/ day) corresponding to the national default consumption rates of 17.8g/ d, 39.0g/ d, and 86.3g/ d ( i. e., the 90th, 95th and 99th percentile of mean per capita consumption of adults from the CSFII survey) are shown below.

90th 95th 99th TL2 1.1 2.4 5.2 TL3 11.5 25.2 55.9 TL4 5.2 11.4 25.2 All TL 17.8 39.0 86.3 EPA recognizes that in some situations, States and Tribes may lack sufficient data to determine trophic level specific fish consumption rates that are applicable to their target populations and site( s) of concern. In these situations, EPA recommends that States and Tribes assign the total fish consumption rates to the highest BAF determined across the relevant trophic levels. In most cases, this will be the BAF corresponding to trophic level four, but in some cases, it may be trophic level three. This approach reflects a assumption that may be conservative, the degree to which will depend on the actual consumption pattern of the target population.

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3. MINIMUM DATA CONSIDERATIONS 3.1 Background The 1980 AWQC National Guidelines did not present specific minimum data requirements. However, the following minimum data requirements were implied from the text:

3.1.1 Threshold Effects Guidelines Animal dose response toxicity data were used in developing guidelines for deriving criteria based on noncarcinogenic responses. The following guidelines for deriving criteria were adopted: 277 ° A free standing Frank Effect Level ( FEL) is unsuitable for the derivation of criteria.

° A free standing No Observed Effect Level ( NOEL) is unsuitable for the derivation of criteria. If multiple NOELs are available, with or without additional data on Lowest Observed Effect Levels ( LOELs), No Observed Adverse Effect Levels data ( NOAELs), or Lowest Observed Adverse Effect Levels ( LOAELs). The highest NOEL should be used to derive a criterion.

° A NOAEL, LOEL, or LOAEL can be suitable for criteria derivation. A well defined NOAEL from a chronic study ( 90 day study was considered minimum) may be used directly, applying the appropriate uncertainty factor. For a LOEL, a judgment needs to be made as to whether it actually corresponds to a NOAEL or a LOAEL. In the case of a LOAEL, an additional uncertainty factor is applied; the magnitude of the additional uncertainty factor is judgmental and should lie in the range of 1 to 10. Caution must be exercised not to substitute FELs for LOAELs.

3.1.2 Non Threshold Effects This section discusses lifetime animal studies or human studies where excess cancer risk has been associated with exposure to the agent.

<IP_ADDRESS> Animal Studies ° For some chemicals, several studies conducted at several doses and different routes of exposure are available for different animal species, strains, and sexes. A choice must be made as to which of the data sets from several studies are to be used in the model. The procedures listed below, used in evaluating these data, are consistent with the estimate of a maximum likely risk.

° The data ( i. e., dose and tumor incidence) used in the model are data sets where the incidence is statistically significantly higher than the control for at least one test dose level and/ or where the tumor incidence rate shows a statistically significantly trend with respect to dose level. The data set which gives the highest estimate of lifetime carcinogenic risk, q1*, estimated from each of these data sets, is used for risk assessment.

° If sufficient data exist for two or more significant tumor sites in the same study, the number of animals with at least one of the specific tumor sites under consideration was used as incidence data in the model.

° Since to a close approximation, the surface area is proportional to the 2/ 3 power of the weight as would be the case for a perfect sphere, the exposure in mg/( body weight) 2/ 3/ day is similarly considered to be an equivalent exposure. 278 ° Use data from organ sites which are statistically higher than the control data.

3.1.3 Exposure Assumptions The three exposure related parameters listed below were provided in the 1980 AWQC National Guidelines. Although the concept of accounting for dietary and inhalation exposures was included, no parameters were provided.

° 2 L/ day drinking water consumption;

° 6.5 g/ day consumption of fish; and ° Lipid normalized bioconcentration factor ( BCF).

3.2 Minimum Data Considerations in the Federal Register Notice Many sections of the Federal Register notice which accompanies this Technical Support Document ( TSD) include discussions of data quality. While many of these discussions are qualitative in nature, they may help direct the reader to the kinds of data which meet a minimally successful risk assessment. For example, in the exposure section, there is a discussion of what constitutes acceptable data for conducting a relative source contribution assessment; in addition, there is a discussion regarding minimally acceptable fish consumption surveys and data collection. In developing bioaccumulation factors, there is a discussion in the Federal Register of what is regarded as a minimally acceptable BCF and K ow. That section also cites a field guidance document which will contain minimum data requirements for assessing field measured BAFs and field measured lipid levels and POC/ DOC. Once this document is finalized in 1998, the results will be cited and incorporated into the final TSD.

On the toxicological side of the human health methodology, the following minimum data is suggested for RfD development:

3.2.1 Noncancer  Data Suggestions <IP_ADDRESS> RfD Development ( Minimal Data)

° One well conducted subchronic ( 90 days) mammalian bioassay by the oral route of exposure in which a NOAEL or LOAEL can be derived.

° If the most critical endpoint is an acute effect, which occurs short term, it should be used as the basis of the RfD.

° One short term developmental study, if it can be shown that the developmental toxicity endpoint is the critical effect given other subchronic or chronic studies. 279 ° One developmental study cannot be used as the basis of an RfD on its own unless other studies exist to support its use.

Of course, a more ideal data set is preferred but not always available. The following data set is considered complete and likely to have much less uncertainty associated with the resulting RfD:

<IP_ADDRESS> RfD Development ( Ideal Situation)

° One well conducted epidemiological study; or ° Two or more adequate chronic studies in two animal species, one of which must be with rodents, by the oral route of exposure in which one can identify a NOAEL and LOAEL; and ° One adequate mammalian multi generation reproductive toxicity study by the oral route of exposure; and ° Two adequate mammalian developmental toxicity studies by the oral route of exposure in different species; and ° Mechanistic, pharmacokinetic and target organ toxicity data; and ° If the most critical endpoint is an acute effect, which occurs short term, it should be used as the basis of the RfD.