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Keywords:

  • Bioaccumulation;
  • Bioconcentration;
  • Regulatory and resource implications;
  • Screening bioaccumulation potential

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. SUPPLEMENTAL DATA
  8. REFERENCES
  9. Supporting Information

The fish bioconcentration factor (BCF), as calculated from controlled laboratory tests, is commonly used in chemical management programs to screen chemicals for bioaccumulation potential. The bioaccumulation factor (BAF), as calculated from field-caught fish, is more ecologically relevant because it accounts for dietary, respiratory, and dermal exposures. The BCFBAF™ program in the U.S. Environmental Protection Agency's Estimation Programs Interface Suite (EPI Suite™ Ver 4.10) screening-level tool includes the Arnot-Gobas quantitative structure–activity relationship model to estimate BAFs for organic chemicals in fish. Bioaccumulation factors can be greater than BCFs, suggesting that using the BAF rather than the BCF for screening bioaccumulation potential could have regulatory and resource implications for chemical assessment programs. To evaluate these potential implications, BCFBAF was used to calculate BAFs and BCFs for 6,034 U.S. high- and medium-production volume chemicals. The results indicate no change in the bioaccumulation rating for 86% of these chemicals, with 3% receiving lower and 11% receiving higher bioaccumulation ratings when using the BAF rather than the BCF. All chemicals that received higher bioaccumulation ratings had log KOW values greater than 4.02, in which a chemical's BAF was more representative of field-based bioaccumulation than its BCF. Similar results were obtained for 374 new chemicals. Screening based on BAFs provides ecologically relevant results without a substantial increase in resources needed for assessments or the number of chemicals screened as being of concern for bioaccumulation potential. Environ. Toxicol. Chem. 2012; 31: 2261–2268. © 2012 SETAC


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. SUPPLEMENTAL DATA
  8. REFERENCES
  9. Supporting Information

The fish bioconcentration factor (BCF) is commonly used by chemical management programs to screen chemicals for bioaccumulation potential 1. The bioaccumulation factor (BAF) can also be used to screen chemicals; however, there are relatively fewer BAF measurements and BAF quantitative structure–activity relationship (QSAR) models compared with BCF measurements and BCF-QSAR models 2. Bioaccumulation factors may be more appropriate for evaluating the bioaccumulation potential of hydrophobic organics, because the BAF accounts for dietary, dermal, and respiratory exposures, and dietary routes of exposure can be important for hydrophobic chemicals 2. For this reason, empirical BAFs are at least considered, if not preferred, over BCFs when evaluating the bioaccumulation potential of organic chemicals according to regulations in Canada 3 and Europe 4. The merits of using the BAF and BCF for bioaccumulation assessment in general, including regulatory evaluations for bioaccumulation potential, have been reviewed by Gobas et al. 5.

The BCF is measured under controlled laboratory conditions in which fish are exposed to a chemical in the water phase only. The BCF test exposure should be at constant water concentrations, below the chemical's water solubility limit, and for at least 28 d or until steady state is approximated 6. From these laboratory measurements, BCFs have been correlated with the chemical's n-octanol-water partition coefficient (KOW) 7–9. Unlike the laboratory settings recommended to determine a chemical's BCF, the BAF is determined using fish collected from contaminated environments reflecting field conditions, in which an organism is potentially exposed to chemicals from any or all of several sources, including diet, dermal contact, and respiration. The BCFBAF™ program, in the Estimation Programs Interface Suite (EPI Suite™ Ver 4.10) 10, includes models for estimating a chemical's BCF and BAF. The BCFBAF program only requires a chemical's Simplified Molecular Information and Line Entry System (SMILES) notation to calculate its BCF and BAF 11.

The regulatory and resource-use implications of selecting the ecologically relevant BAF over the laboratory-based BCF for bioaccumulation screening assessments have not been evaluated. Changes in estimates of bioaccumulation potential could have widespread impact on chemical management programs, including the U.S. Environmental Protection Agency's (U.S. EPA) new and existing chemical programs; pesticide registration under the U.S. Federal Insecticide, Fungicide, and Rodenticide Act; Canada's New Substances Program; Australia's National Industrial Chemicals Notification and Assessment Scheme; and the European Chemicals Agency Regulation Registration, Evaluation, Authorization, and Restriction of Chemical substances. Measured and evaluated bioaccumulation data were used to assess the performance of the BCF and BAF models for screening chemicals into three bioaccumulation categories: not significantly bioaccumulative (BCF or BAF <1,000), bioaccumulative (BCF or BAF ≥1,000 and <5,000), and highly bioaccumulative (BCF or BAF >5,000). The BCFBAF program was then used to calculate BCFs and BAFs for 6,034 U.S. high- and medium-production volume chemicals, and 374 new chemicals for which ready biodegradation data had been submitted under the Toxic Substances Control Act 12. The results were analyzed to determine the resource and regulatory implications of using BAFs instead of BCFs when screening chemicals for bioaccumulation potential.

METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. SUPPLEMENTAL DATA
  8. REFERENCES
  9. Supporting Information

BCFBAF model

The BCFBAF program provides seven bioaccumulation calculations: four BCFs and three BAFs. One BCF value is calculated using the regression-based method described in Meylan et al. 9. This was formerly known as the BCFWIN™ model in previous versions of the EPI Suite (Ver 3.20) program. To develop the regression-based BCF-QSAR in the current version of EPI Suite (Ver 4.10), the model in Version 3.20 was revised following the same basic methods described in Meylan et al. 9 but using measured BCF data that were reviewed for data quality 2. The other three BCFs and three BAFs in BCFBAF are for upper, middle, and lower trophic levels; these trophic levels are specific for fish and do not reflect the overall food-web trophic levels (Fig. 1). These BAF values can be used to provide a screening-level estimate of whether chemicals are likely to bioaccumulate in lower trophic level fish (e.g., Gulf menhaden or Alewife), middle trophic level fish (e.g., Atlantic croaker), or upper trophic level fish (e.g., Atlantic salmon or Rainbow trout).

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Figure 1. Representative fish-only trophic level (TL) with fish mass and lipid contents used in bioaccumulation factor (BAF) and bioconcentration factor (BCF) values calculated by BCFBAF™ Version 3.01. QSAR = quantitative structure–activity relationship. [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com.].

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The BAF-QSAR model incorporated into BCFBAF 10 is based on the model presented by Arnot and Gobas 13 and represents the steady-state condition where the rate of chemical uptake into the fish is equal to the rate of chemical elimination as

  • equation image

The first term in this equation accounts for chemical partitioning into the organism's nonlipid fraction, where LB is the fish's lipid fraction. The numerator in the second term of the equation includes a rate constant for chemical uptake from water (k1; L/kg/d); a rate constant for chemical uptake from diet (kD; kg/kg/d); the bioavailable (dissolved) solute fraction of the total chemical concentration in the water (ϕ), that is, only the dissolved fraction can permeate membranes of the respiratory surface area; the food web biomagnification factor (β); the food web trophic dilution factor (τ); the volumetric lipid fraction for primary producers (i.e., phytoplankton, algae) at the base of the aquatic food web (LD); and KOW to represent chemical partitioning from water into the primary producers at the base of the food web. The denominator of the second term includes rate constants for chemical elimination at the gill surface (k2; 1/d), fecal egestion (kE; 1/d), growth dilution (kG; 1/d), and whole body, primary metabolic biotransformation (kM; 1/d). Although bioavailability is considered for chemical uptake (i.e., only the truly dissolved chemical is absorbed), the default BCF and BAF calculations in BCFBAF are presented based on the chemical's total water concentration (i.e., BCF or BAF = Cfish/Cwater-total; both the dissolved, bioavailable fraction and the sorbed, nonbioavailable fraction) because most currently published bioaccumulation data in fish are based on total water concentrations.

The original BAF-QSAR model was calibrated using the empirical parameter β to fit measured BAF data for persistent organochlorine compounds from a range of fish species representing various trophic levels 13. This approach captured the overall biomagnification potential of poorly biotransformed chemicals in typical aquatic food webs 13. The measured BAF data were later separated into three different trophic levels of fish (lower, middle, and upper), and the BAF-QSAR model was calibrated to each of these three unique trophic level datasets, thus providing BAF-QSAR estimates for the three general trophic levels of fish 14. The three trophic level approach was adopted in the BCFBAF version of the model with β (calibration) values of 16.1, 30.1, and 62.7 for lower, middle, and upper trophic level fish, respectively (see Supplemental Data). The increasing values for β with an increasing trophic level reflect the higher degree of food web biomagnification observed for persistent chemicals at higher trophic levels relative to the base of the food web. The Arnot and Gobas model also provides screening-level BCF calculations for the three fish trophic levels (i.e., for BCF, β = 0 in the equation).

Metabolic biotransformation can lower BCFs and BAFs, particularly for more hydrophobic chemicals, that is, chemicals with high bioaccumulation potential 15–17. The Arnot and Gobas BCF- and BAF-QSAR models include the input parameter kM to account for chemical-specific metabolic biotransformation rates in the BCF and BAF calculations. The BCFBAF program (Ver 3.01) in EPI Suite (Ver 4.10) also includes a screening-level QSAR model for estimating chemical-specific kM values 18.

The regression-based BCF model in the BCFBAF program (not to be confused with the trophic level Arnot-Gobas BCFs also available in the BCFBAF program) does not explicitly account for chemical-specific metabolic biotransformation 9.

Model applications

Estimates of BCF, BAF, and log KOW (neutral species for ionic chemicals) were obtained by entering each chemical's Chemical Abstracts Service registry number into the BCFBAF Version 3.01 module of the EPI Suite Version 4.10 program, dated January 2011 10. The terms and assumptions used in developing this model are presented in the Supplemental Data. These programs are available at no cost from http://www.epa.gov/oppt/exposure/pubs/episuitedl.htm. The corresponding SMILES required for estimating chemical properties, was automatically retrieved from the SMILECAS database included in the EPI Suite Version 4.10 program. All statistical analyses were performed using Microsoft Office Excel 2003 SP3. All logarithmic values are base 10 (i.e., log10).

Unless otherwise noted, the BAFs reported herein include default biotransformation-rate constants calculated by the kM-QSAR, and the BCFs are from the regression-based QSAR model. The Arnot-Gobas BCF models were not evaluated in the present study; only the BAF and regression-based BCF model outputs are presented here. The BAF and BCF values calculated by BCFBAF Version 3.01 are on a wet-weight basis (L/kg wet wt) and reflect the total chemical concentrations in the water, that is, bioavailable and nonbioavailable fractions for hydrophobic chemicals.

High- and medium-production volume chemicals

The list of the 940 high production volume chemicals was obtained from the High Production Volume Information System database available at http://www.epa.gov/chemrtk/hpvis/. The list of 5,094 medium-production volume chemicals was provided by the Risk Assessment Division of the U.S. EPA Office of Pollution Prevention and Toxics. Of the 940 high-production volume chemicals and 5,094 medium-production volume chemicals, 845 high production volume and 3,726 medium-production volume chemicals were in the SMILECAS database and were subsequently evaluated using the BCFBAF program. The chemical structures in the SMILECAS database were not reviewed, as BCF and BAF values were obtained using the batch input/output mode. Although known errors exist for some chemical structures contained in the SMILECAS database, the error rate was shown to be less than 4% 19.

The BAF and BCF evaluation data

Measured field BAFs that were not used to calibrate the BCFBAF program were obtained from Arnot and Gobas 2. These data (358 BAFs for 49 chemicals) include BAFs from lower, middle, and upper trophic level fish. Additional BAF values not included in the BAF-QSAR calibration dataset are for phthalate esters from Gobas et al. 20, chlorinated hydrocarbons from Burkhard et al. 21, Pereira et al. 22, and Oliver and Niimi 23; chloroparaffins from Houde et al. 24; perfluorooctanesulfonate (PFOS) from Houde et al. 25; and polybrominated diphenyl ethers (PBDEs) from Streets et al. 26. Most (>95%) of the measured BAFs included in the evaluation data set are based on total water concentrations (i.e., BAF = Cfish/Cwater-total); however, some of the measured BAFs are based on estimates of the dissolved chemical concentration in water (i.e., BAF = Cfish/Cwater-dissolved). The few measured BAFs based on dissolved water concentrations are typically for lower KOW chemicals (i.e., log KOW < 6), for which differences between the two types of BAFs are relatively minor.

United States premanufacture notice substances

In the United States, virtually all premanufacture notice data are confidential, and these data are not publicly available. Approximately 16,000 individual notices were received from the fiscal years 1995 through 2002, and review of these submissions yielded a set of 374 substances with at least one test result from a ready biodegradability test. This set of 374 substances was restricted to structures with molecular weight less than 800 and, although collected for a different purpose 12, was considered a suitable set of chemicals for the BCF and BAF comparative analysis. To our knowledge, no measured BCF or BAF data exist for these chemicals.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. SUPPLEMENTAL DATA
  8. REFERENCES
  9. Supporting Information

BCFBAF evaluation with BAF calibration dataset

Figure 2 shows the 358 measured BAFs from lower, middle, and upper trophic level fish species that were used to calibrate the three lower, middle, and upper trophic level BAF-QSAR models. These measured data are for 43 persistent organochlorines (e.g., polychlorinated biphenyls, pesticides, and so forth), and the log BAFs range from 4.49 to 7.51. The BAFs calculated by the BCFBAF program for these chemicals in the three trophic levels ranged from 4.71 to 6.99. This good agreement was expected, because these are the measured BAF values that were used to calibrate the model. Also shown in Figure 2 are the BCFs calculated using the regression-based QSARs, which range from 3.77 to 4.86. Although the BCFs follow a trend similar to that of the calculated BAFs, the BCFs were from 1 to 3.5 log units lower than the measured BAFs, reflecting the fact that BCFs do not include dietary exposures and may not measure the full potential for biomagnification in the environment for these persistent organic pollutants.

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Figure 2. Measured bioaccumulation factors (BAFs) and BCFBAF Version 3.01-calculated lower, middle, and upper trophic level (TL) BAFs and regression-based bioconcentration factors (BCFs). [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com.].

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The rating scheme used by the U.S. EPA for screening the bioaccumulation potential of organic chemicals under the new chemicals (premanufacture notice) program is also shown in Figure 2. The term B1 is for chemicals with log BCF or log BAF less than 3; B2 is for chemicals with log BCF or log BAF between 3 and 3.7; and B3 is for chemicals with log BCF or log BAF greater than 3.7. The interpretation of this scheme is such that a chemical is expected to either be not significantly bioaccumulative (B1), bioaccumulative (B2), or highly bioaccumulative (B3). Compared with the calculated BCFs, the calculated BAFs better represent the measured BAFs; however, no significant differences were found between using the BAF or the BCF model when screening these 43 persistent organochlorine chemicals using the bioaccumulation categorization scheme, that is, all predictions and measurements were B3.

The BCFBAF evaluation with other BAF datasets

The BAF data that were not used to calibrate the BAF-QSAR were used to further evaluate BAFs and BCFs calculated by the BCFBAF Version 3.01 program. Figure 3 shows the 512 measured BAFs for lower, middle, and upper trophic level fish, which range from a log BAF of 1.49 to 7.5 and are for 88 organic chemicals described with log KOW values ranging from 1.60 to 9.52. For chemicals with calculated log BAFs less than 3.5, the calculated BAFs tend to be less than the measured BAFs. For chemicals with calculated log BAFs greater than 3.5, the measured and calculated values tended to be scattered about the y = x line. The calculated BCF values tended to be above the y = x line, indicating that the measured BAFs were generally greater than the calculated BCFs.

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Figure 3. Measured bioaccumulation factors (BAFs) and BCFBAF Version 3.01 calculated lower, middle, and upper trophic level (TL) BAFs and regression-based bioconcentration factors (BCFs) for chlorinated organic compounds and four polybrominated diphenyl ethers. The measured BAFs are based on total water concentrations. [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com.].

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The table inset in Figure 3 summarizes the number of BAFs in this dataset that were assigned to each bioaccumulation rating based on the calculated log BAF (shown in the columns) and measured log BAF (shown in the rows). Of the 512 measured BAFs, 475 had identical B ratings based on measured and calculated BAFs, including 441 agreements for the B3 rating (chemicals with log KOW values greater than 4.78). Only 14 measured BAFs were rated higher (i.e., B3 or B2) than the calculated BAFs (i.e., B2 or B1). Six chemicals received a B1 rating (i.e., not significantly bioaccumulative) based on calculated BCFs when these chemicals should have been rated as B3 (i.e., highly bioaccumulative) based on their 15 measured BAFs. This situation was improved using calculated BAFs in which only one chemical received a B1 when it should have received a B3 rating based on its measured BAF. Overall correspondence between measured and calculated BAFs on the basis of bioaccumulation ratings was 93%, demonstrating good agreement from a chemical screening perspective. In comparison, the overall agreement between bioaccumulation ratings decreased to 85% when calculated regression-based BCFs were used for screening this set of chemicals.

The BCFBAF evaluation with BCF datasets

The BCF data that were not used to calibrate the regression-based BCF were used to further evaluate BAFs and BCFs calculated by the BCFBAF Version 3.01 program. Figure 4 shows the 2,524 measured BCFs for fish, which range from a log BCF of −1.30 to 5.97 and are for 865 chemicals with log KOW values ranging from −6.50 to 10.35. The table inset in Figure 4 indicates that of the 2,524 measured BCFs, 2,140 had identical B ratings based on measured BCFs and calculated BAFs, including 223 agreements for the B3 rating (chemicals with log KOW values greater than 4.51). Only 241 measured BCF values were rated higher (i.e., B3 or B2) by the calculated BAFs (i.e., B2 or B1). Thirteen chemicals received a B1 rating (i.e., not significantly bioaccumulative) based on calculated BCFs when these chemicals should have been rated as B3 (i.e., highly bioaccumulative) based on their 65 measured BCFs. This situation was improved using calculated BAFs in which only one chemical received a B1 when it should have received a B3 rating based on its measured BAF. Overall correspondence between measured BCFs and calculated BAFs on the basis of bioaccumulation ratings was 85%, demonstrating good agreement from a chemical screening perspective. In comparison, the overall agreement between bioaccumulation ratings decreased to 75% when calculated regression-based BCFs were used for screening.

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Figure 4. Measured bioconcentration factors (BCFs) and BCFBAF Version 3.01 calculated upper trophic level (TL) bioaccumulation factors (BAFs) and regression-based BCFs. [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com.].

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The BCFBAF evaluation with perfluorinated compounds

Perfluorooctanesulfonic acid is ionized at environmental pH (i.e., between pH 4 and 8). Despite this, measured log BAFs for PFOS range from 3.3 27 to 5.37 25, whereas the calculated log BAFs range from 3.24 for lower trophic level fish to 3.28 for upper trophic level fish. The calculated (regression based) log BCF for PFOS was 0.5, which is a default value assigned for ionic chemicals with a log KOW of less than 5.0 or greater than 9.0. Thus, PFOS is rated as bioaccumulative (B2) to highly bioaccumulative (B3) based on measured BAFs, bioaccumulative (B2) based on calculated BAFs, and not significantly bioaccumulative based on the calculated BCF. Therefore, bioaccumulation potential for PFOS is estimated more accurately using its BAF from BCFBAF than its BCF from the older, regression-based method.

The improvement in bioaccumulation rating using BAFs rather than BCFs (Figs. 3 and 4) was also noted for perfluoroalkyl carboxlic acids (PFCAs). Figure 5 summarizes measured BCFs obtained from the Japanese National Institute of Technology and Evaluation database 28, and Martin et al. 29 for perfluorotetradecanoic acid, and BAFs determined for European chub, a middle trophic level fish 30. Good agreement was found between the measured and calculated BAFs on the basis of bioaccumulation ratings, with four of the five highly bioaccumulative PFCAs rated as highly bioaccumulative (B3) using the calculated log BAFs for middle trophic level fish (right inset, Fig. 5). Three of the four PFCAs not expected to bioaccumulate (B1) based on measured values were rated as highly bioaccumulative using the calculated log BAFs. However, in contrast to the calculated BCFs, use of the BAFs yielded no false negatives for bioaccumulation potential. All six chemicals were rated B2 or B3 based on measured BAFs and BCFs and were assigned B2 or B3 ratings based on calculated BAFs, whereas with calculated BCFs, all six bioaccumulative PFCAs were assigned a B1 rating (left inset, Fig. 5).

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Figure 5. Measured bioaccumulations factors (BAFs; open symbol) and bioconcentration (BCFs; filled symbol) and BCFBAF Version 3.01 calculated middle trophic level (TL) BAFs and regression-based BCFs for perfluoroalkyl carboxlic acids (PFCAs) and perfluorooctanesulfonate (PFOS). Perfluoroalkylcarboxlic acids abbreviations are according to those given in Buck et al. 37. The measured BAFs and BCFs are based on total water concentrations. PFOS = perflurooctanesulfonate; PFHpA = perfluoroheptanoic acid; PFOA = perfluorooctanoic acid; PFNA = perfluorononanoic acid; PFDA = perfluorodecanoic acid; PFUnDA = perfluoroundecanoic acid; PFDoDA = perfluorododecanoic acid; PFTeDA = perfluorotetradecanoic acid; PFHxDA = perfluorohexadecanoic acid; PFODA = perfluorooctadecanoic acid. [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com.].

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Impact of BAF on bioaccumulation ratings for U.S. high- and medium-production chemicals

To illustrate how using BAFs instead of BCFs might affect the bioaccumulation rating of existing chemicals, Figure 6 shows the log BAFs and log BCFs calculated by the BCFBAF program for a series of alkyl esters of unsaturated alcohols and fatty acids, which is a cluster of medium-production volume chemicals (i.e., greater than 25,000 pounds and less than 1 million pounds per year). Even though the log KOW estimates for these alkyl esters span the range from 2.18 to 13.42, the calculated BAFs (upper trophic level including biotransformation rate estimates) and BCFs (regression-based) are, on average, within 0.26 log units of each other. All of the chemicals presented in Figure 6 have a bioaccumulation rating of B1, with the exception of 9,12-octadecadienoic acid (Z,Z)-, ethyl ester, indicating little impact on the bioaccumulation rating as a consequence of using BAFs.

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Figure 6. BCFBAF Version 3.01 calculated upper trophic level bioaccumulation factors (BAFs) (including biotransformation rate constant estimates and assuming negligible biotransformation, i.e., kM = 0) and regression-based bioconcentration factors (BCFs) for alkyl esters of unsaturated alcohols and fatty acids. [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com.].

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Also shown in Figure 6 is the metabolic biotransformation rate constant (kM) for each chemical as calculated by the kM-QSAR subroutine in BCFBAF 18. These rates range from very fast (see Table 2 in Arnot et al. 18) for 2-buten-1-ol, 3-methyl-, acetate (kM = 8.7/d) to very slow for 9-octadecenoic acid (Z)-, C12-15-alkyl esters (kM = 0.006/d). Even though the biotransformation rate constants decrease to slower values (i.e., 0.006/d), accounting for biotransformation still has a significant effect on the calculated BAF. With the biotransformation rate constant set equal to zero, the log BAFs are orders of magnitude greater. Accounting for the biotransformation rate had less effect on the BAF for chemicals with log KOW values of less than 4.0 and greater than 12.0. With the biotransformation rate constants set to zero, BAFs were greater than BCFs because the BAF model was no longer simulating chemical metabolic biotransformation. BAFs calculated based on total water concentrations (default model output) decrease with increasing log KOW (i.e., >8) partly as a result of the decrease in the bioavailable fraction of the total chemical in the water column (ϕ in Fig. 6).

Although minimal impact occurred on the bioaccumulation rating for the alkyl esters cluster (Fig. 6), this only represents 13 of the 6,034 U.S. high- and medium-production volume chemicals. Figure 7 contains the calculated upper trophic level log BAFs and log BCFs for 4,571 of the 6,034 high- and medium- production volume chemicals; 1,463 chemicals were not contained in the EPI Suite Version 4.10 SMILECAS database and therefore were not included in this analysis. Although there was some degree of agreement between the BAFs and BCFs, as shown by the clustering of data points near the y = x line, no clear correspondence was found between the BAFs and BCFs as indicated by a correlation coefficient of 0.56 (not shown). The regression-based BCF model in BCFBAF assigns default log BCFs for ionized species 9. This is evidenced in Figure 7 (and Fig. 5) by the data points that fall on vertical lines extending from the log BCF axis. When omitting the 1,503 chemicals with default log BCF = 0.5 (which represented most of the 1,696 ionizable chemicals), the correlation coefficient for log BCF and log BAF decreased to 0.51 (not shown).

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Figure 7. BCFBAF Version 3.01 calculated upper trophic level bioaccumulation factors (BAFs) and regression-based bioconcentration factors (BCFs) for 4,571 U.S. high- and medium-production volume chemicals. [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com.].

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The most significant disagreement between bioaccumulation ratings was for 212 chemicals with calculated log BCFs of less than 3.0 (i.e., B1) and calculated log BAFs of greater than 3.7 (i.e., B3). These chemicals had log KOW values between 4.68 and 11.76 and kM values that were classified as moderate to very slow (see Table 2 in Arnot et al. 18). Only one of the 212 chemicals (hexachlorobutadiene) had measured bioaccumulation data. The average (± standard deviation) measured log BCF was 3.92 ± 0.32 (n = 12), whereas the average measured log BAF was 3.58 ± 0.74 (n = 8) 2. The measured BCF and BAF bioaccumulation ratings (B3 and B2, respectively) are more consistent with the upper trophic level BAF model calculations and rating (log BAF = 4.37, B3) than the BCF calculations and rating (log BCF = 2.82, B1).

Impact of BAF on bioaccumulation ratings for U.S. new chemical substances

To determine the overall effect of using BAFs when determining the bioaccumulation potential for new (premanufacture notice) chemicals, the log BAFs and log BCFs were calculated using BCFBAF Version 3.01 for a previously described set of 374 substances with molecular weights less than 800 that had ready biodegradation data 31. Calculated log BAF (upper trophic level fish including biotransformation rate estimate) is plotted against calculated (regression-based) log BCF for these substances in Figure 8. Although some agreement was found between the BAFs and BCFs, as shown by the clustering of data points near the y = x line, no clear correspondence was seen between the BAFs and BCFs as indicated by a correlation coefficient of 0.42 (not shown). As for the medium- and high-production volume chemicals (Fig. 7; previous section), omission of ionizable chemicals with assigned calculated log BCF = 0.5 lowered the correlation coefficient, in this case to 0.23.

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Figure 8. BCFBAF Version 3.01 calculated upper trophic level bioaccumulation factors (BAFs) and regression-based bioconcentration factors (BCFs) for 374 U.S. new (Premanufacture Notice) chemicals. [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com.].

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Twelve of the 374 new chemicals (3.2%) had calculated log BCFs less than 3 (i.e., B1 rating) and calculated log BAFs greater than 3.7 (i.e., B3 rating). These chemicals had estimated log KOW values between 5.97 and 11.35 and estimated biotransformation half-lives (normalized to a 10 g fish at 15°C) of 11.6 to 1,120 d with median and geometric mean half-lives of 41 d and 72 d, respectively. In other words, the kM-QSAR subroutine in BCFBAF suggests that these chemicals show limited biotransformation potential. Five of the 12 chemicals would be ionized at environmental pH.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. SUPPLEMENTAL DATA
  8. REFERENCES
  9. Supporting Information

The BCF, as estimated by regression-based QSARs or measured under controlled laboratory conditions, is well established in regulatory schemes for screening-level bioaccumulation assessments 5. The BAF-QSAR provides ecologically relevant metrics for screening-level bioaccumulation assessments in aquatic food webs. Although speculation has been made that use of a chemical's BAF would lead to more chemicals being categorized as potentially bioaccumulative, which could necessitate regulatory control or additional testing, the results presented here suggest only modest impacts. In terms of impact on the bioaccumulation rating (see the table inset in Fig. 7), 3,924 chemicals had identical bioaccumulation ratings based on BCFs and BAFs. The bioaccumulation ratings were not in agreement for 647 chemicals. Of these, 144 chemicals had lower bioaccumulation ratings, and 503 had higher bioaccumulation ratings based on their calculated BAF. Thus, if BAFs were used instead of BCFs, no change would be seen in the bioaccumulation rating for 86% of the high- and medium-production volume chemicals; 3% of the chemicals would receive a lower bioaccumulation rating; and 11% would receive a higher bioaccumulation rating. Similarly, for the 374 new chemicals, 81% would have an identical bioaccumulation rating if the BAF model were used instead of the BCF model, 9% of the chemicals would receive a lower bioaccumulation rating, and 10% would receive a higher bioaccumulation rating. These results suggest that from a regulatory perspective, using calculated BAFs instead of BCFs would result in few changes for screening-level bioaccumulation assessments. Where there was an increase in bioaccumulation rating, the increase was for chemicals with log KOW values of greater than 4.02, that is, hydrophobic chemicals, for which the BAF better represents bioaccumulation in the environment by including the route of dietary exposure, among other improvements.

Estimating the bioaccumulation potential for ionizable chemicals is important, because approximately 37% of the 4,571 high- and medium-production volume chemicals were classified as ionizable by the BCFBAF program and assigned a log BCF default value of 0.5, 0.75, 1.0, or 1.75. The BCFBAF program calculates a BAF for ionizable chemicals based on the partitioning properties for the neutral form of the chemical only; whereas the BCF regression model assigns default values. The current approach in the Arnot and Gobas model is considered somewhat conservative, but defensible for screening-level assessments given the paucity of bioaccumulation data for ionic organics.

The kM-QSAR may not accurately predict biotransformation rates for some of the ionic chemicals because few chemicals that appreciably ionize at physiological pH were included in the database used to develop this QSAR 18. Of the 421 chemicals in the kM-QSAR training dataset, 66 (15.7%) contained ionizable functional groups, including amines, amides, anilines, phenols, carboxylic acids, and phosphoric acids. Of these 66 chemicals, only 20 chemicals (7 amines, 1 aniline, 2 carboxylic acids, 2 linear alkylbenzene sulfonates, and 8 phenols) are expected to be appreciably charged at environmental pH based on their pKa values (data not shown). Although the bioaccumulation of some chemicals with ionizable functional groups is pH dependent, this may not be the case for all ionizable chemicals. For example, Meylan et al. 9 treated phenols and anilines as neutral organics even though they may be appreciably ionized at environmental pH, because their BCFs were better described using log KOW rather than pKa. More recently, Erickson et al. 32 demonstrated that gill uptake for a series of ionic chlorophenols was more like that of a neutral organic at pH between 6.2 and 8.4, even though only 0.5% of the neutral form was present in this pH range. Thus, BAF estimates for anilines and phenols may be appropriate for screening assessments, even though only 20 amine and 23 phenol-containing chemicals were in the kM-QSAR training dataset.

Although estimating bioaccumulation potential for chemicals with aniline and phenol groups may be appropriate, chemicals with carboxylic acid groups remain problematic because the kM-QSAR training dataset contains only two such compounds. In contrast, the BCF training dataset contains 34 carboxylic acids. This limited representation in the kM-QSAR training dataset makes interpreting the difference between BAF and BCF model results difficult. More than half (55%) of the significant disagreements in bioaccumulation ratings between the two models (i.e., B1 by BCF and B3 by BAF) were for chemicals containing carboxylic acid groups, including fatty acids, tall oils, and resin and rosin acids. For example, the calculated log BCF for octadecanoic (stearic) acid was the default value of 1.0 (B1), whereas the calculated log BAF was 4.9 (B3) because of the slow predicted rate of metabolic biotransformation and the high KOW of the neutral form of the chemical. Given that fatty acids are found in fish and no significant difference was found between octadecanoic acid levels in perch fed with radiolabeled octadecanoic acid and perch that were starved for 5 d after being fed with radiolabeled octadecanoic acid 33, one may conclude that the calculated BAF is more indicative of octadecanoic acid bioaccumulation than the calculated BCF, at least for screening-level evaluations. However, because only two carboxylic acids were included in the kM-QSAR training dataset, the BAF model results should be used with caution when evaluating the bioaccumulation potential of carboxylic acid–containing compounds.

The PFCAs are another important class of carboxylic acid-containing compounds. On average, the calculated regression-based log BCFs were less than 8% of the measured BCFs and BAFs (middle trophic level fish), because the regression-based BCF model assigned default values because of the presence of the ionizable carboxylic acid group. All of the nine PFCAs considered in the present study were assigned default BCFs of 0.5, 1, or 1.75 by the BCFBAF program (Fig. 5). In contrast, the calculated BAFs suggest that all but perfluorohepanoic acid and PFOS are highly bioaccumulative (B3); whereas the measured BCFs and BAFs indicated that only perfluorodecanoic, perfluoroundecanoic, perflurordodecanoic, and perfluorotetradecanoic acids were highly bioaccumulative (B3). Different viewpoints have been expressed on the bioaccumulation potential for PFCAs, with Conder et al. 34 arguing that perfluorooctanoic acid is not significantly bioaccumulative, whereas perfluoroundecanoic and perflurordodecanoic acids are possibly bioaccumulative. Conversely, Kelly et al. 35 suggested that the PFCAs from perfluorooctanoic acid through perflurordodecanoic acids are bioaccumulative in air-breathing animals (e.g., birds and mammals) because of high gastrointestinal uptake and slow respiratory elimination.

For chemical screening assessments, minimizing the potential for false negatives (i.e., type II errors) is generally desirable; in this case, the conclusion that a chemical is categorized to be not significantly bioaccumulative when in fact it is. If regression-based log BCFs had been used for screening assessment when these PFCAs first entered commerce, none of them would have been categorized as potentially bioaccumulative. Because field measurements are now available, showing that some of these substances do bioaccumulate, this scenario equates to a false-negative error in bioaccumulation rating. In contrast, if the BAF-QSAR had been used in rating the bioaccumulation potential for these PFCAs, no false-negative errors would have occurred. Thus, from a regulatory perspective, even though the agreement (as reflected in overall classification accuracy) between measured BCFs and calculated BAFs was poor, the bioaccumulation ratings based on calculated BAFs would have correctly raised concern about the bioaccumulation potential of PFCAs. The importance of evaluating agreement between predicted and measured values not just using standard statistical measures (e.g., correlation coefficient) but also in terms of classification was demonstrated earlier by Tunkel et al. 36, in that case using the ecotoxicity estimation program ECOSAR.

All bioaccumulation models have merits and limitations for bioaccumulation screening assessments, especially considering the paucity of measured values. Bioaccumulation potential has been measured for fewer than 4% of the existing chemicals in commerce, suggesting a need for conservatism in screening-level assessments 2. The present study indicates that BAFs calculated from BCFBAF are generally in better agreement with field-derived BAF values than are BCF-QSAR estimates. Thus, BAFs calculated by BCFBAF can be used in a complementary manner with calculated BCFs, or preferentially, over calculated BCFs to reduce false-negative (type II) errors in bioaccumulation potential ratings, without a substantial strain on limited resources such as a chemical evaluator's time. Moreover, when different BCF and BAF models show consensus with respect to bioaccumulation potential ratings, this increases confidence in the bioaccumulation assessment. Conversely, discrepancies between the models create an impetus to carry out higher-tiered bioaccumulation assessments either through more careful scrutiny of the models and their assumptions and limitations (e.g., ionizing chemicals), or preferably, through appropriate testing. Clearly, strategic bioaccumulation testing for chemicals and chemical classes that are not well represented in existing databases would expand the domain of applicability of existing models and reduce uncertainty in bioaccumulation assessments.

SUPPLEMENTAL DATA

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. SUPPLEMENTAL DATA
  8. REFERENCES
  9. Supporting Information

The file includes default terms and equations in BCFBAF used to estimate BAFs, the aqueous chemical concentration in the BAF equation, and the identity of the 43 persistent organochlorines shown in Figure 2. (49 KB DOC)

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. SUPPLEMENTAL DATA
  8. REFERENCES
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. SUPPLEMENTAL DATA
  8. REFERENCES
  9. Supporting Information

Additional Supporting Information may be found in the online version of this article.

FilenameFormatSizeDescription
etc_1944_sm_SupplData.doc255KSupplementary Data

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