An evaluation of bioaccumulation data for hexachlorobenzene to derive water quality standards according to the EU-WFD methodology

Authors


Abstract

Hexachlorobenzene (HCB) is a priority hazardous substance within the Water Framework Directive (WFD). For aquatic systems, the European Commission has derived quality standards (QS) for HCB in biota. However, in some countries a preference may exist for QS based on water concentrations. The conversion of biota QS into water QS can be done by dividing the quality standard for biota by a reliable bioaccumulation factor (BAF) or by the product of the bioconcentration factor (BCF) and the biomagnification factor (BMF) (BCF × BMF). An extensive literature review of HCB bioaccumulation was performed, and data on bioaccumulation, biomagnification and bioconcentration, both from the field and the laboratory, were assessed for their usefulness to recalculate biota standards into water standards. The evaluation resulted in 10 reliable values for field BAFs, with a geometric mean of 221 000 L/kg (5% lipid-normalized). Bioaccumulation factor measurements show a high variation of more than 1 order of magnitude. At lower trophic levels (algae, small zooplankton), accumulation of HCB already exceeds expected accumulation through equilibrium partitioning by far. This affects BAFs at higher trophic levels as well. Moreover, observed BAF values for HCB in fish cannot be easily explained from the age of the fish, but there is a significant increase with trophic level. Reliable values for laboratory BCFs for fish were retrieved from literature, partly with water-based exposure and partly with dietary exposure. The 5% lipid-normalized BCF of all these data is 12 800 L/kg. Regarding biomagnification, a number of reliable BMF and trophic magnification factor values, mostly determined in the field, were retrieved. From these data, an overall BMF of 3 per trophic level can be deduced. When comparing BCF values for fish multiplied by the BMF (12 800 × 3 = 38 400 L/kg) to the observed BAF values for fish (geometric mean 238 000 L/kg), there appears to be a large gap. Thus, the uncertainties surrounding values for bioaccumulation of HCB are high. Although the confidence in laboratory BCFs is higher, these data seem to be not relevant for small fish in the field. This makes it difficult to obtain a reliable BAF or BCF × BMF value to recalculate biota standards into water standards. On the other hand, biota concentrations in the field show a high variability that also hampers comparison with a fixed limit such as a quality standard. Thus, compliance checking using biota in the field means that a relatively large amount of fish will have to be used to obtain a reliable estimate. The following “tiered approach” is suggested: 1) calculate a water quality standard, using the BAF value that is most relevant for the trophic level to be protected, and 2) if this standard is exceeded in the field, sample representative biota in the field and compare concentrations of HCB in biota and water with their respective standards in a weight of evidence approach for compliance checking. In this way, unnecessary biota sampling can be avoided for reasons of efficiency and animal welfare. Integr Environ Assess Manag 2013; 9: 87–97. © 2012 SETAC

INTRODUCTION

European water quality standards

The European Water Framework Directive (WFD) aims at “maintaining and improving the aquatic environment in the Community.” Member States should achieve the objective of at least a “good ecological status” and a “good chemical status” by defining and implementing the necessary measures within integrated “programs of measures.” For a good chemical status, the WFD requires that environmental quality standards (QS) are met. These QS thus serve as a benchmark to decide whether or not specific measures are required. The methodology for deriving QS within the WFD was developed by Lepper (2005), based on the technical guidance document (TGD) in support of the risk assessment for new and existing substances and biocides (EC 2003). In 2011, a new QS guidance was published (EC 2011). The QS for priority (hazardous) substances are set on European Union (EU) community level. For other compounds that are relevant to individual member states, standards are set on a national level.

Water QS for chronic exposure in the European WFD framework are based on 3 protection goals: direct ecotoxicity to aquatic organisms, exposure of humans through consumption of fish and fishery products (referred to as the “human route”), and exposure of predators through secondary poisoning. The most critical of these routes determines the final standard. For compounds that have a strong potential to bioaccumulate in fish, the human and secondary poisoning routes are often the most critical. Because of the characteristics of these compounds, concentrations increase along the food chain. Consumption of fish, therefore, leads to critical levels in humans or predators whereas at similar concentrations in water, aquatic organisms may not be affected. For these compounds, threshold concentrations in fish can be calculated that will not cause adverse effects in humans or predatory birds and mammals on lifetime consumption.

Environmental QS for hexachlorobenzene

Hexachlorobenzene (HCB) was formerly used as a fungicide, but due to its harmful properties it has been banned globally under the Stockholm Convention. It is also used for the production of fireworks, ammunition, and synthetic rubber, as an intermediate during the production of pesticides, and it is a byproduct of the production of chlorinated solvents. Hexachlorobenzene has been classified as a priority hazardous substance by the EU WFD.

For the aquatic environmental QS for HCB, the human and secondary poisoning routes are the most critical, because of the high level of bioconcentration of these compounds. According to the preamble of Directive 2008/105/EC (EC 2008), within the EU, QS based on surface water concentrations are sufficient for the majority of substances but for HCB, hexachlorobutadiene, and Hg it was considered more appropriate to establish QS for biota, because for these substances it is “not possible to ensure protection against indirect effects and secondary poisoning at Community level by QS for surface water alone.”

Therefore, a maximum concentration in biota for HCB of 10 µg/kgww was set in Art 3(2) of Directive 2008/105/EC, based on a substance data sheet that was compiled in 2005 (EC 2005). The reason for setting standards based on concentrations in biota rather than concentrations in the water column was primarily the uncertainty surrounding bioconcentration and biomagnification factors (BCFs and BMFs, see below).

However, in the Netherlands measuring water samples is preferred above designing and maintaining a biota monitoring program. In this article, data on bioaccumulation have been critically reviewed to determine whether it is feasible to convert biota QS (based on concentrations in biota) into equivalent QS for water using the most recent European methodology. Special consideration is given to the additional uncertainties with this conversion. The data reviewed comprise laboratory bioconcentration studies and dietary bioaccumulation studies, and field-derived bioaccumulation factors (BAFs), BMFs, and trophic magnification factors.

METHODOLOGY

Derivation of QS

The methodology for the derivation of environmental QS (EQS) for water is described in detail in Van Vlaardingen and Verbruggen (2007), which was prepared for a Dutch program on QS, within the context of the methodology of the European WFD. It is partly taken up as an appendix in the recently published EU-EQS guidance (EC 2011). Chronic risk limits for water are represented by annual average-EQS (AA-EQS) values. The overall AA-EQS is the lowest of the EQS for direct ecotoxicity (QSfw,eco), the EQS for secondary poisoning of birds and mammals (QSfw,secpois) and the EQS for human fish consumption (QSfw,hh food). According to the WFD-methodology, the QS for human consumption of fishery products, expressed as a concentration in fish (QSbiota,hh food), is calculated from the human-toxicological threshold (TDI), assuming a body weight of 70 kg, a daily intake of 115 g fish/day, and a maximum contribution to the TDI of 10%. The QS for predatory birds or mammals, also expressed as a concentration in fish (QSbiota,secpois), is derived by applying an assessment factor to the no observed adverse effect level (NOAEL) or no observed effect concentration (NOEC) from toxicity experiments with birds or mammals. This QS for secondary poisoning aims to protect the top predators (Figure 1) by setting a limit for their food, which is 1 trophic level below this top predator. Thus, for freshwater ecosystems, assuming the trophic level for algae, zooplankton, small fish and large fish are 1, 2, 3, and 4, respectively, the QSbiota,secpois is set on the 4th trophic level to protect the birds and mammals in the 5th trophic level.

Figure 1.

Scheme on how to recalculate biota standards into water concentrations. Ovals are protection goals (species to be protected); the rectangle is the trophic level on which the QS are set to protect the upper trophic levels. TL = trophic level; assuming trophic level 1 = algae; 2 = zooplankton; 3 = small fish; 4 = large fish; 5 = predatory birds, mammals, and large fish. QSbiota,secpois is the quality standard protecting predators (through secondary poisoning). QSbiota,hh is the quality standard protecting humans (through the consumption of fish and fishery products). For QSbiota,secpois in freshwater, only the BMF1 is relevant. For QSbiota,secpois in marine waters, the BMF1 and BMF2 are relevant because an additional trophic level should be included to protect marine top predators.

Starting from these QS based on concentrations in fish (Figure 1), corresponding water concentrations can be calculated. For this, information on the accumulation of substances by aquatic organisms from the aqueous phase (bioconcentration) and accumulation in the food chain (biomagnification) has to be taken into account. These processes are represented by a laboratory BCF and BMF or the BAF.

Bioconcentration

Bioconcentration is determined in laboratory studies by exposing aquatic organisms to the substance dissolved in water. The BCF is then calculated as the ratio between the concentration in the organisms and in the water determined at equilibrium, or (preferably) by dividing the uptake rate constant by the depuration rate constant, the kinetic method. The standard guideline to perform bioconcentration tests with fish is the OECD 305 guideline. In principle, the only exposure is through the aqueous phase. Bioconcentration factors can also be determined using laboratory bioaccumulation or food biomagnification studies, using a dietary exposure method. In these studies, fish are exposed to HCB through spiked food during the uptake phase, and then transferred to clean water with uncontaminated food for the depuration phase. It is possible to calculate a BCF from these kinds of experiments using the kinetic method, with an estimated uptake rate and a measured depuration rate constant. The uptake rate constant for aqueous exposure is based on fish weight, according to the REACH guidance (REACH guidance chapter R7C; ECHA 2008). The BCF is preferably normalized to 5% lipids (ECHA 2008).

Biomagnification

The BMF is the ratio of the concentration in the predator organism divided by the concentration in the prey organism (for hydrophobic organic chemicals commonly normalized to lipid content of prey and predator). The BMF in the framework of the WFD describes biomagnification from small fish or aquatic organisms to larger fish that in turn are eaten by predators (including humans). For the marine environment, a second BMF is included in QS derivation to account for accumulation in bird and mammals (e.g., seals, dolphins, seabirds) that serve as food for top predators such as polar bears and killer whales. For substances with low biotransformation potential in upper trophic levels, biomagnification, and thus total bioaccumulation, increases with increasing bioconcentration potential (Gobas et al. 2009).

In general, the most reliable data on biomagnification originate from trophic magnification studies (Gobas et al. 2009). In such studies, the levels of contaminants in several species in an ecosystem are measured and expressed as a function of the trophic level. The trophic level is mostly derived from stable N isotope ratios and a regression is made between contaminant concentration and trophic level. The contaminant values should preferably be normalized to the fraction in the organisms that contains the substance (e.g., lipids in the case for lipophilic organic chemicals). This so-called trophic magnification factor (TMF) is considered to be the most reliable representation of the BMF, because it is normalized to trophic level and levels out fluctuations in biomagnification between individual species by regression over several trophic levels. Thus, where BMFs are measured for predator and prey only (and may be corrected to represent one exact trophic level), TMFs are measured over the whole food web and represent the average biomagnification per trophic level. Thus, TMFs are essentially “average” BMF values that consider all of the trophic interactions and organisms sampled in the food web (Burkhard et al. 2011).

Bioaccumulation

The BAF is the ratio of the concentration in the organisms divided by the concentration in its surroundings (the water column). In contrast to a laboratory BCF, the BAF not only includes exposure through water, but also exposure through food. Thus the BAF represents the quotient of the BCF and the BMF. Furthermore, BAFs are often determined in the field, whereas BCFs are usually determined in the laboratory. For HCB, only field studies with water concentrations expressed as dissolved concentrations are valid within the present context, because equilibrium is assumed between biota and the dissolved concentration and not between biota and the total concentration (including suspended solids). Bioaccumulation factors are often reported based on lipid-weights (e.g., amount of HCB per gram lipid), but for comparison with BCFs the BAF can also be normalized to 5% lipids (ECHA 2008).

Recalculating biota standards into water standards

Using the biota standards, the accompanying concentrations in water (QSfw,hh food and QSfw,secpois) are calculated by dividing the QSbiota,hh food and QSbiota,secpois by the product of BCF and BMF (Figure 1). For example, for the QS for secondary poisoning this would be:

equation image

The equation is based on the assumption that lower trophic levels (including small fish; trophic levels 1–3 in Figure 1) are in thermodynamic equilibrium with the aqueous phase. Larger fish (suitable for consumption; trophic level 4 in Figure 1), have additional exposure through food uptake, and can no longer be assumed to be in equilibrium with the aqueous phase. As discussed in the previous paragraph, the term BCF × BMF may be replaced by the BAF for fish, and thus the QSfw,secpois can also be calculated according to:

equation image

Data collection

Bioaccumulation data were collected by searches for public literature in Scopus (July 2009 and July 2011) and using data from the European substance data sheet (EC 2005). All literature was assessed for validity using the criteria of Klimisch et al. (1997) and assessment methods as described in Van Vlaardingen and Verbruggen (2007). In this article, only valid data will be shown in the results paragraph. For an overview of all valid and nonvalid data, the reader is referred to Moermond and Verbruggen (2011) and the Supplemental Data.

According to the newest methodology (EC 2011), all QS need to be reported as dissolved concentrations. For this reason, only BCFs and BAFs relating to dissolved concentrations can be used to recalculate QS for biota into water QS. For BCFs, this is usually the case. However, many BAF values are only derived using total water concentrations. This might underestimate the BAF greatly (e.g., Burkhard et al. 1997). Therefore, for the purpose of this QS derivation, only valid data based on dissolved concentrations were taken into account.

RESULTS AND DISCUSSION

Bioconcentration factors

A detailed table with BCF values can be found in the Supplemental Data. Table 1 summarizes all valid data for fish, with a column with nonnormalized BCFs and a column with BCFs normalized to 5% lipids for those studies where lipid contents of the fish were reported. A box plot containing all valid data can be seen in Figure 2. For QS derivation purposes, the overall BCF is derived by first calculating the geometric mean for each species, and then taking the geometric mean of all species. Both the nonlipid-normalized and the lipid-normalized geometric mean BCF are 12 800 L/kg. Lipid normalization reduces the variability that is caused by differences in characteristics of the fish used in the experiments. Therefore, the lipid-normalized geometric mean value of 12 800 L/kg is considered most reliable.

Table 1. Summary of fish bioconcentration data for HCB
SpeciesBCF (L/kg)BCF 5% lipidsRemarkReference
  1. BCF = bioconcentration factor; HCB = hexachlorobenzene.

Gambusia affinis37306020 Chaiksuksant et al. 1997
Gambusia affinis37806090 Chaiksuksant et al. 1997
Gambusia affinis37506050Geomean 
Gasterosteus aculeatus22 10040 900 

Egeler et al. 2001

Ictalurus punctatus11 0007450Dietary study

Woodburn et al. 2008

Lepomis macrochirus21 900  

Veith et al. 1979

Oncorhynchus mykiss12 100  

Lu and Wang 2002

Oncorhynchus mykiss16 70029 800Dietary studyExxon Mobil 2005
Oncorhynchus mykiss15 80016 500Dietary studyExxon Mobil 2005
Oncorhynchus mykiss10 80022 500Dietary studyExxon Mobil 2005
Oncorhynchus mykiss10 10015 800Dietary studyExxon Mobil 2005
Oncorhynchus mykiss22 20013 700Dietary studyExxon Mobil 2005
Oncorhynchus mykiss15 00013 400Dietary studyExxon Mobil 2005
Oncorhynchus mykiss5500  

Veith et al. 1979

Oncorhynchus mykiss19 50023 800Dietary study

Fisk et al. 1998

Oncorhynchus mykiss13 20018 600Geomean 
Pimephales promelas26 700  

Carlson and Kosian 1987

Pimephales promelas21 400  

Carlson and Kosian 1987

Pimephales promelas22 500  

Carlson and Kosian 1987

Pimephales promelas17 700  

Carlson and Kosian 1987

Pimephales promelas20 200  

Carlson and Kosian 1987

Pimephales promelas16 600  

Veith et al. 1979

Pimephales promelas18 200  

Veith et al. 1979

Pimephales promelas17 800  

Veith et al. 1979

Pimephales promelas45 700  

Veith et al. 1979

Pimephales promelas16 200  

Veith et al. 1979

Pimephales promelas18 500  

Veith et al. 1979

Pimephales promelas12 2008840 

Nebeker et al. 1989

Pimephales promelas15 30011 100 

Nebeker et al. 1989

Pimephales promelas21 10015 300 

Nebeker et al. 1989

Pimephales promelas12 6009130 

Nebeker et al. 1989

Pimephales promelas13 3009640 

Nebeker et al. 1989

Pimephales promelas11 5008330 

Nebeker et al. 1989

Pimephales promelas20 70015 000 

Nebeker et al. 1989

Pimephales promelas93 800  

Schuytema et al. 1990

Pimephales promelas19 90010 700Geomean 
Poecilia reticulata15 70014 500 

Könemann and van Leeuwen 1980

Poecilia reticulata76609580Dietary study

Clark and Mackay 1991

Poecilia reticulata11 00011 800Geomean 
Overall geometric mean12 80012 800See text 
Figure 2.

Box plots of all valid data for BCF, BAF, and TMF. Box denotes 25th percentile, median, and 75th percentile. Whiskers denote minimum and maximum values. A line is included on the BAF-BCF level to facilitate comparison between BAF-BCF and TMF.

As a comparison, the BCF for fish can be calculated using the linear relationship developed by Veith et al. (1979) as used in the WFD guidance (EC 2011): log BCF = 0.85 × log Kow −0.70. Using the log Kow of 5.73, the resulting BCF is 14 800 L/kg. This is in good agreement with the geometric mean experimental value.

For invertebrates that are not suitable for consumption, at least by humans, BCFs between 13 200 and 75 000 L/kg have been determined, for insects a BCF of 29 000 L/kg is available, and for oligochaetes BCFs range between 25 100 and 106 800 L/kg (see Supplemental Data; Appendix A). For the purpose of QS derivation, these data serve as circumstantial evidence but are deemed to be less relevant when good data for bioconcentration in fish are available. For other frameworks however (e.g., the assessment of persistence, bioaccumulation and toxicity [PBT]), these data are very relevant. For mussels, BCF values tend to be lower than for fish (see Supplemental Data).

Biomagnification factors

In the Supplemental Data, studies on biomagnification are summarized. An overview of all valid BMF values derived from these studies is given in Table 2. Trophic magnification factors are also summarized in the Supplemental Data. An overview of all valid TMF values is given in Table 3, with a box plot in Figure 2. Considering all available data, the use of a BMF value of 3 kg/kg is considered most appropriate for further calculations. This value is around the geometric mean of all BMF and TMF values, and closely resembles the average TMF of 2.9 kg/kg from by the well-performed study of Houde et al. (2008).

Table 2. Overview of valid BMF values for HCB
Predator-preyBMFRemarkReference
  1. BMF = biomagnification factor; HCB = hexachlorobenzene.

Amphipods-prey3.8Corrected for trophic level

Fisk et al. 2001

Fish-invertebrate4 

Borgå et al. 2001

Fish-invertebrate2.4 

Borgå et al. 2001

Fish-oligochaetes0.53 

Egeler et al. 2001

Fish-oligochaetes1.3 

Egeler et al. 2001

Fish-invertebrates1.4–4.8 Hallanger, Ruus, et al. 2011; Hallanger, Warner, et al. 2011
Fish-fish1.7 

Borgå et al. 2001

Fish-fish2.1 

Ruus et al. 1999

Fish-fish0.79 

Russell et al. 1995

Fish-prey6.1Corrected for trophic level

Fisk et al. 2001

Fish-prey6.8Corrected for trophic level

Catalan et al. 2004

Fish-food0.35Laboratory study

Woodburn et al. 2008

Bird-fish63 

Borgå et al. 2001

Bird-fish13 

Borgå et al. 2001

Bird-fish5.2 

Borgå et al. 2001

Bird-fish8.9 

Borgå et al. 2001

Bird-fish15.0–16.9 Hallanger, Ruus, et al. 2011; Hallanger, Warner, et al. 2011
Bird-prey5.0–21.6Corrected for trophic level

Fisk et al. 2001

Seal-fish2.7 

Ruus et al. 1999

Seal-fish0.3 

Ruus et al. 1999

Seals-prey0.2Corrected for trophic level

Fisk et al. 2001

Table 3. Overview of valid TMF values for HCB
TMFRemarkReference
With birds and/or mammalsWithout birdsWithout birds and/or mammals
  • HCB = hexachlorobenzene; n.s. = slope not significant (i.e., TMF not significantly different from 1); TMF = trophic magnification factor.

  • a

    Recalculated by Hoekstra et al. 2003.

  • b

    Calculated from data in figure or table in the original publication.

  0.9–6.9Average is 2.9. Food webs in 17 lakes

Houde et al. 2008

4.71.55a4.7Invertebrates, fish, birds, seals

Hop et al. 2002

2.96 2.85bAlgae, invertebrates, fish, birdsWan et al. 2005
1.36 (n.s.)  Zooplankton, fish, seals, whales

Hoekstra et al. 2003

4.11.75a Zooplankton, invertebrate, fish, birds, seal

Fisk et al. 2001

1.57 (n.s.) b 4.04 (n.s.)bPolychaetes, fish, seal, birdRuus et al. 2002
6.35 2.4MayHallanger, Warner, et al. 2011
12.31 5.9JulyHallanger, Warner, et al. 2011
8.46 3.9OctoberHallanger, Warner, et al. 2011
  2.4Plankton, zooplankton, fishVilla et al. 2011

Bioaccumulation factors

A description of bioaccumulation studies including the rationale on validity is given in the Supplemental Data. Results of valid studies are summarized in Table 4, with a box plot in Figure 2. All reported BAFs are based on lipid-weights. Recalculated BAFs normalized to 5% lipids are also included in the table.

Table 4. Summary of valid BAF data for HCB, with geometric means for all species where applicable
SpeciesTrophic positionBAF (L/kg) (lipid-weight)BAF (L/kg) (normalized to 5% lipids)Reference
FishbaseaReportedb
  • BAF = bioaccumulation factor; HCB = hexachlorobenzene.

  • a

    Source: http://www.fishbase.org; accessed February 10, 2012.

  • b

    Derived from data presented in the studies.

  • c

    Geometric mean of available data per species.

  • d

    BAFs were only calculated for samples which were sampled at the same time and the same location as the water samples.

  • e

    Composite sample, not used for the determination of the final geomean BAF.

Invertebrates
 Arrow worms (Sagitta elegans, Eukrohnia hamata)c,d 2.76.3 × 10531 700Hallanger, Ruus, et al. 2011
 Calanus finnmarchusc,d 21.9 × 1059600Hallanger, Ruus, et al. 2011
 Calanus glacialisd 28.8 × 1044400Hallanger, Ruus, et al. 2011
 Calanus hyperboreusc,d 1.69.8 × 1044900Hallanger, Ruus, et al. 2011
 Krill (mostly Thysanoessa inermis)c,d 2.41.0 × 10651 000Hallanger, Ruus, et al. 2011
 Pontoporeia affinis  4.0 × 106200 000

Oliver and Niimi 1988

 Themisto abyssorumc,d 1.59.4 × 10547 000Hallanger, Ruus, et al. 2011
 Themisto libellulac,d 2.01.4 × 10669 000Hallanger, Ruus, et al. 2011
Fish     
 Alosa pseudoharengus3.51 1.9 × 10695 000

Oliver and Niimi 1988

 Boreogadus saidac,d3.102.91.3 × 10666 000Hallanger, Warner, et al. 2011
 Comephorus dybowskiic3.443.866.7 × 106333 000

Kucklick et al. 1996

 Comephorus baikalensisc3.293.966.1 × 106305 000

Kucklick et al. 1996

 Coregonus autumnalis migratoriusc3.573.401.8 × 107885 600

Kucklick et al. 1996

 Cottus cognatus3.37 3.2 × 106158 000

Oliver and Niimi 1988

 Gadus morhuac,d3.733.33.0 × 106148 000Hallanger, Warner, et al. 2011
 Mallotus villosusd3.152.59.5 × 10548 000Hallanger, Warner, et al. 2011
 Melanogrammus aeglefinusc,d4.092.82.4 × 106120 000Hallanger, Warner, et al. 2011
 Osmerus mordaxc3.00 1.7 × 10686 000

Oliver and Niimi 1988

 Pollachius virensc,d4.383.22.2 × 106111 000Hallanger, Warner, et al. 2011
 Salmo trutta (muscle)3.163.148.7 × 106433 000

Catalan et al. 2004

 Salmonids (Oncorhynchus kisutch, O. mykiss, Salvelinus namaycush, Salmo trutta)e3.16–4.42 2.3 × 106115 000

Oliver and Niimi 1988

Geometric mean of all individual fish data except the composite salmonid sample   238 000 

In the European substance data sheet for HCB (EC 2005), a BAF of 42 000 L/kg is used based on data for bream from the river Elbe. However, this value was deemed to be less reliable because it is based on muscle tissue wet weight instead of 5% lipid-normalized whole fish and was based on total concentrations in water (including suspended solids) instead of dissolved concentrations. Moreover, the trophic position of the species used is low (2.31 according to Van Riel et al. 2006 and 2.94 ± 0.37 according to http://fishbase.org) and the species is mainly benthivorous, which renders the value of the BAF less reliable.

The geometric mean of all individual valid 5% lipid-normalized BAFs is 238 000 L/kg. The worst-case BAF value is 2 116 000 for 3-year-old Coregonus autumnalis. Bioaccumulation factor measurements show a high variation of more than 1 order of magnitude. Bioaccumulation factors are expected to correlate with trophic level of the fish (e.g., Borga et al. 2012). In Figure 3, it is shown that for HCB this is also the case. When all individual BAFs are used, the relationship with trophic level is not significant (p = 0.06). However, if the high value for C. autumnalis is left out of the regression, the slope of the regression line differs significantly from 0 (p = 0.0057). When the residuals of the plot are tested for outliers, the value for C. autumnalis is a significant outlier (p < 0.01). Thus, when the high value of C. autumnalis is not included, the regression between BAF and trophic level becomes highly significant. The value of the slope of this regression line (on a log-basis) is 0.39, which represents a TMF of 2.47.

Figure 3.

Influence of trophic level on BAFs (based on individual data from the references included in Table 4).The regression line with 90% confidence interval shows the dependence of the BAF on trophic level (log BAF = 0.39 TL + 4.00; p = 0.0057).

Although the fish listed in Table 4 do not differ much in trophic level according to http://fishbase.org, there are distinct differences in feeding strategies. For example, the food chain in Lake Ontario, where samples in the study by Oliver and Niimi (1988) originated, includes Cottus cognatus as a benthic predatory fish, Osmerus mordax and Alosa pseudoharengus as pelagic predatory fish, and salmonids as a top predator. From the study by Kucklick et al. (1996), Coregonus is also a salmonid that feeds on smaller fish. Thus, besides trophic level, feeding strategy may influence the BAF for HCB. Other factors, such as age, size, reproductive status, biotransformation efficiency, and omnivorous feeding may be important for the observed contaminant concentrations in an organism (Borga et al. 2012). For fish at higher trophic levels, it is observed that size or age affect bioaccumulation of the contaminant, and larger, slower-growing individuals typically contain higher organic contaminant levels than younger, faster-growing individuals (Borga et al. 2012 and references therein). For HCB however, the expected increase in BAF values with increasing age is not found for 3 fish species in the study by Kucklick et al. (1996). To the contrary, the reverse is more likely, although a high variation is shown (Figure 4). It should be added that the correlation between trophic level and age is also rather weak, although positively correlated. These results are confirmed by measurements of Ferrante et al. (2010) in European eel (Anguilla anguilla) in Italy, where a significant correlation with weight and length was observed for PCBs but not for HCB. Thus, the observed BAF values can be explained primarily by the trophic level of the fish, although the variation remains high.

Figure 4.

Influence of age on BAF values for fish (based on data from Kucklick et al. 1996).

Even at lower trophic levels (algae, small zooplankton), accumulation of HCB already far exceeds what is expected through equilibrium partitioning. For instance the BAF for amphipods and plankton normalized to 5% lipids was 107 000 L/kg in the study by Oliver and Niimi (1988). In the study by Kucklick et al. (1996) data for invertebrates were below the limit of detection. However, for the predatory amphipod Macrohectopus branicii, a BAF could be derived. If the limit of detection for the zooplankton is taken as an upper limit, the BAF values for these invertebrates normalized to 5% lipid weight can be supposed to be below 92,000 L/kg. With the trophic level for zooplankton approximately 2 and the trophic level of the predatory amphipod M. branicii around 2.5, an increase in BAF with a factor of at least 2 per trophic level would be deduced from these data. The same pattern was observed for PCBs in the same study, where in the group of fish no clear trend with trophic level was observed, whereas there was a significant relationship with trophic level if invertebrates were included.

These relatively high HCB concentrations at lower trophic levels cannot be explained easily with the usual theories on bioaccumulation. Possibly, the low water solubility of HCB (that is lower than expected from its Kow) and high crystal energy may cause high sorption to the body surface. Especially at lower trophic levels, with small individuals with a high surface area to body ratio, this may contribute significantly to the observed contaminant levels. This affects BAFs at higher trophic levels as well.

Another source of uncertainty for BAF values is the fairly large uncertainty surrounding the measurements of the aqueous concentrations, which are often very low in the field. Because BAFs for HCB only originate from 4 studies, no definite conclusions can be drawn on the influence of the uncertainty in water concentrations on BAFs. However, it should be stressed that the concentrations of HCB are rather consistent over the 4 studies in the range of 10 to 150 pg/L. This probably reflects the global distribution of this substance.

Comparing BCF, BMF, and BAF

Lower trophic levels (plankton, amphipods) already may have field derived BAF values far above observed laboratory BCFs for fish. Arnot and Gobas (2006) in their review also observed that BAFs from field samples can differ by up to several orders of magnitude from laboratory BCF measurements for some chemicals and explained this through trophic position, sediment–water disequilibria, and unique characteristics for different ecosystems. When comparing BCF values for fish multiplied by the BMF (12 800 × 3 = 38 400 L/kg) to the observed BAF values for fish (48 000–885 600), there appears to be a large difference between these 2 values. This can also be observed with the box plots (Figure 2), where a line on the level of BAF-BCF is included to facilitate the comparison with the TMF. It is shown in this graph that the TMF does not explain the observed difference between the BAF and the BCF. Thus, the assumption that the BAF equals BMF × BCF (or TMF × BCF) does not seem to hold for HCB. This assumption only works if BAF values for small fish and other aquatic species are comparable to the laboratory BCF data, and consequently the BAF for species with a higher trophic level only need to be corrected for one biomagnification step. For HCB, this is apparently not the case. It appears that the BAF values are almost a factor of 20 higher than the BCF values, whereas the increase per trophic level is only a factor of 3. This means that the number of trophic levels that should be taken into account for the biomagnification process is 2 to 3 instead of the single trophic level that is considered in the current methodology for risk assessment and QS derivation (that can also be deduced from the box plots in Figure 2). This is not that far-off because often food chains are longer than 3 trophic levels and fish may also feed on their own brood. Thus, it is not considered appropriate to use BCF × BMF values to recalculate the biota standards into water standards, because this methodology greatly underestimates field BAFs for HCB.

Calculation of QS for HCB in water

In the substance data sheet for HCB (EC 2005), QS for biota based on human consumption of fishery products (QSbiota,hh food) and based on secondary poisoning (QSbiota,secpois) of 9.74 µg/kg and 16.7 µg/kg respectively, are derived. According to the substance data sheet, these can be recalculated into water concentrations using a BAF of 42 000 L/kg, which results in a QSfw,hh food of 0.00023 µg/L (0.23 ng/L) and a QSfw,secpois of 0.00004 µg/L (0.04 ng/L).

The value of 42 000 L/kg for the BAF is, however, not based on an extensive literature search. It is deemed to be less reliable, because it is based on muscle tissue wet weight instead of 5% lipid-normalized whole fish, and refers to total concentrations in water (including suspended solids) instead of dissolved concentrations. Following the most recent guidance for derivation of QS under the Water Framework Directive (EC 2011), QS have to reflect dissolved concentrations.

Using the information acquired above, there are 4 options to implement QS for HCB. These are all discussed below. It should be noted that the option that is preferable from a scientific point of view, may not be the most desirable option from a policy maker's point of view. Besides this, these methods are based on the most recent EU methodology, and the resulting choices below have been made from a European perspective. In other states other methodologies may prevail, like for instance in the United States (USEPA 2000).

  • 1.Use the QSbiota,hh food and QSbiota,secpois from the substance data sheet without any recalculation into water concentrations. This would involve the highest degree of certainty surrounding the value as such. However, monitoring biota for compliance checking with the QSbiota introduces a very high variability, as was demonstrated by the highly variable BAF values in this article, even when these BAF values originated from the same site. This means that for compliance checking of the monitoring data with the QSbiota still a high uncertainty remains. Moreover, monitoring of biota is difficult to harmonize (which age, size, which species, which trophic level), labor-intensive, and consequently costly. Besides that, it should be discouraged from an animal welfare perspective.
  • 2.Use the QSfw,hh food and QSfw,secpois from the substance data sheet (EC 2005), where a BAF of 42 000 L/kg is used (based on total concentrations in water). However, this BAF is deemed to be less reliable and underestimates the observed BAF values and no extensive literature search was performed. Because the BAF is based on total concentrations in water, the resulting QS (QSfw,hh food = 0.23 ng/L and QSfw,secpois = 0.4 ng/L) would also refer to total concentrations. However, according to the most recent guidance on EQS derivation (EC 2011), QS should be based on dissolved concentrations.
  • 3.Use the worst-case BAF of 885 600 L/kg for Coregonus migratorius autumnalis (Kucklick et al. 1996). This value is a geometric mean of BAF values of individual fish of this species with different ages; no age-dependency of the value could be shown, but there was a large variability among the values. Moreover, this value is highly influenced by one single value that can be considered to be an outlier when the regression with trophic level is taken into account (see before). Because the BAF values are based on dissolved concentrations, these QS (QSfw,hh food = 0.011 ng/L and QSfw,secpois = 0.019 ng/L) refer to dissolved concentration.
  • 4.Use the geometric mean of all individual valid BAFs, 238,000 L/kg. Some uncertainties surround this value, because the variation among BAFs is high. The height of the BAF is relatively high (for comparison, the BAF calculated as BCF × BMF would have been 38 400 L/kg (see discussion above), but the BAF is more relevant for the field situation than the BCF × BMF. Also in this case, the BAF values and thus the resulting QS (QSfw,hh food = 0.041 ng/L and QSfw,secpois = 0.070 ng/L) are based on dissolved concentrations.
  • 5.Use the BAF for fish that are most relevant for human consumption and secondary poisoning (trophic level 4 in Figure 1). This can be done by calculating the BAF value at trophic level 4 from the regression of the relationship between BAF and trophic level (Figure 3). This BAF value is 372 000 L/kg. Although individual BAF values vary considerably, this average BAF at trophic level 4 has a confidence interval ranging from 254 000 to 547 000. Because trophic level 4 is at the upper end of the data from which the regression was calculated, the resulting BAF value obtained for trophic level 4 is higher than the geometric mean of all available data (option 4, see above). Also the lower value of the confidence interval is higher than this geometric mean. Because the BAF for trophic level 4 is based on dissolved water concentrations, the QS resulting from this value (QSfw,hh food = 0.026 ng/L and QSfw,secpois = 0.045 ng/L) are also based on dissolved concentrations.

The differences in water-based QS between options 2 and 3 through 5 are not only caused by the height of the BAF used, but are also caused by a difference based on dissolved concentrations versus (higher) total concentrations. This difference is not easy to quantify, because it depends on the amount of suspended solids in the systems. However, in the most recent guidance on QS derivation (EC 2011) it is specifically stated that QS should be based on dissolved concentrations.

Final choice of QS

Regarding the final choice for the above options, option 2 is not preferable because of the less reliable BAF value used. From a scientific point of view, option 3 is also not preferable, because it is highly influenced by 1 single value that can be considered to be an outlier when the regression with trophic level is taken into account. Option 5 might be preferred over option 4, because the QS are based on larger fish (trophic level 4 in Figure 1) that are suitable for consumption and that represent the prey for predators, and for this trophic level the representative BAF values are significantly higher than the geometric mean BAF value over all trophic levels.

Compliance checking involves both uncertainties in the quality standard as well as in the monitoring data. Compliance checking by means of monitoring in water (options 2 through 5) has advantages over biota sampling (option 1) in terms of reproducibility, costs, animal welfare, and uniformity of sampling. However, recalculation of biota standards into water standards (options 2 through 5) introduces considerable uncertainties regarding the height of the BAF used and the resulting quality standard is thus more uncertain than the quality standard for biota. On the other hand, concentrations of HCB in biota that should be monitored to check compliance to these WFD requirements, show high individual variability as reflected by the variability of the BAF values that were considered in this study. Furthermore, the monitored biota should correspond to the same trophic level as the level the EQS refers to. This also introduces a lot of uncertainties, because HCB concentrations in biota are highly variable and will also depend on the species, age, and trophic level of the fish sampled, and there is no guidance on this point yet. These aspects will result in high uncertainty if biota are monitored instead of water.

Thus, the following “tiered approach” is suggested. The geometric mean BAF for the trophic level on which the QS is set (option 5) is used, leading to a critical water quality standard of 0.026 ng/L (based on dissolved concentrations). If this standard is then exceeded in the field, it could be considered to sample biota and make a weight of evidence analysis with both water and biota samples for compliance checking. Such an analysis could for example include an overview of site-specific BAF values for several types of species.

For the marine environment, the QS for human consumption of fishery products equals the freshwater QS for human consumption of fishery products. However, for secondary poisoning the marine top predators (like polar bears) should also be protected. This means that the QS for secondary poisoning in freshwater should be divided by an additional BMF (3) from fish to birds and mammals to account for this extra trophic level in the food chain. The new guideline for deriving EQS (EC 2011) points out that biota QS expressed as concentrations in biota should be divided by this BMF value as well, because monitoring of biota at the level of food for the marine top predators (e.g., seals) is considered inappropriate.

The routine limit of quantification (LOQ) for HCB in water is usually approximately 1 ng/L, with the limit of detection (LOD), depending on the laboratory, approximately a factor of 10 lower. This is significantly higher than the currently derived QS for the water column, even more so because the QS is now based on dissolved concentrations instead of (higher) total concentrations. This means that concentrations of HCB in the water column that are close to the freshwater QS cannot be measured directly (via liquid–liquid extraction) and may have to be measured using passive sampling devices. These are, however, not (yet) used in routine monitoring programs. If conventional methods are used, the QS may already be exceeded when concentrations are still below the detection limit. However, from the studies underlying the BAFs, it can be deduced that analyzing much lower concentrations than the routine LOQ should be possible, e.g., by using large volumes of water. These techniques yield sufficiently low LODs for quantification of the derived QS. However, the practical implication of this is that costs of routine monitoring programs would increase.

CONCLUSIONS

The uncertainties surrounding values for bioaccumulation of HCB are high. Already at low trophic levels, HCB bioaccumulation factors in the field are higher than what is measured in the laboratory with BCF tests. The use of biota standards implies that biota should be monitored regularly in aquatic systems, to check compliance to the European water QS. However, this introduces uncertainties due to the variation in biota concentrations in the field. If for this or other reasons biota standards are not preferred from an ethical or policy makers' point of view, then the following tiered approach is suggested: 1) calculate a water quality standard, using the BAF representative for the trophic level (4) on which the QS is set, and 2) if this standard is exceeded in the field, sample representative biota in the field and compare concentrations of HCB in biota and water with their respective standards in a weight of evidence approach for compliance checking. In this way, unnecessary biota sampling can be avoided for reasons of efficiency and animal welfare.

SUPPLEMENTAL DATA

Appendix A. Bioconcentration data

Appendix B. Biomagnification data

Appendix C. Bioaccumulation data

Appendix D. References

Acknowledgements

We thank Els Smit and Theo Traas for valuable comments during data collection and the preparation of the manuscript.

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