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Keywords:

  • QSAR;
  • Soil ecotoxicity;
  • Bioavailability;
  • Solid-phase microextraction;
  • Folsomia candida

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

To meet the goals of Registration, Evaluation, Authorisation, and Restriction of Chemicals (REACH) as formulated by the European Commission, fast and resource-effective tools are needed to predict the toxicity of compounds in the environment. We developed quantitative structure-activity relationships (QSARs) for the toxicity of nine chlorinated benzenes to the soil-dwelling collembolan Folsomia candida in natural LUFA2.2 (Landwirtschaftliche Untersuchungs und Forschungsanstalt [LUFA]) standard soil and in Organisation for Economic Co-operation and Development artificial soil. Toxicity endpoints used were the effect concentrations causing 10% (EC10) and 50% (EC50) reduction in the reproduction of the test organism over 28 d, while lethal effects on survival (LC50) were used for comparisons with earlier studies. Chlorobenzene toxicity was based on concentrations in interstitial water as estimated using nominal concentrations in soil and literature soil–water partition coefficients. Additionally, for LUFA2.2 soil the estimated concentrations in interstitial water were experimentally determined by solid-phase microextraction measurements. Measured and estimated concentrations showed the same general trend, but significant differences were observed. With the exception of hexachlorobenzene, estimated EC10 and EC50 values were all negatively correlated with their logKow and QSARs were developed. However, no correlation for the LC50 could be derived and 1,2,4,5-tetrachlorobenzene and hexachlorobenzene had no effect on adult survival at all. The derived QSARs may contribute to the development of better ecotoxicity-based models serving the REACH program. Environ. Toxicol. Chem. 2012; 31: 1136–1142. © 2012 SETAC


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Persistent organic pollutants are a threat to ecosystem functioning, species diversity, and environmental health, although the impact and effects have been described for decades 1. With the implementation of the Registration, Evaluation, Authorisation, and Restriction of Chemicals (REACH) legislation by the European Union authorities 2, risk evaluations for 30,000 3 up to 68,000 or even 101,000 4 compounds produced in or imported into member states with production volumes exceeding 1 ton per year must be accomplished before 2018. To achieve this goal for representative organisms and test endpoints, statistical models offer a strong alternative to the vast number of required toxicity tests 5.

Quantitative structure-activity relationships (QSARs) are models that relate toxicity to physicochemical properties of organic compounds and their interaction with environmental matrices. Quantitative structure-activity relationships were originally developed for sediment and freshwater ecosystems about 30 years ago 6, but meanwhile have been applied in soil ecotoxicology to link sorption, exposure, and toxic impacts on biota 7–9. Exposure and consequent effects of organic compounds in soil are strongly related to the chemicals' hydrophobicity and to the characteristics of the soil matrix, for example, organic carbon content (foc) 10–13. The general assumption is that effects in soil can be explained by the freely dissolved (bioavailable) concentration in interstitial water 14, 15. The focus in QSAR development should therefore be on this concentration only, rather than on total soil-associated concentrations. Solid-phase microextraction (SPME) has been shown to be an efficient and simple technique to determine the freely dissolved concentrations of pollutants in various matrices 16–18. Organic pollutants partition to the polymer-coated SPME fibers in a similar fashion as they accumulate in soil biota 19–22. Additionally, SPME allows comparing actual with estimated concentrations in interstitial water.

Most organic compounds exert toxicity primarily via disrupting the cell membrane, a mode of action referred to as narcosis. Their toxicity can therefore be related and attributed directly to their hydrophobicity (logKow). Increased hydrophobicity induces stronger associations with the lipid bilayer of cells and increases toxicity 23, at least for compounds having a logKow ≤ 5.5. Chlorinated benzenes represent a group of semivolatile, nonpolar monoaromatic contaminants, which are present in a wide range of soils, even in remote areas, such as Greenland 24. Their distribution over different soil compartments (total soil, interstitial water, and organisms) has been described for tests with earthworms 22. So far, ecotoxicological studies with chlorinated benzenes in soil have been performed only with different earthworm species 7, 18, 22, 25. Previous studies have, however, indicated that Collembola are more sensitive to organic compounds than earthworms and thus may represent a more appropriate test organism 9, 26. Folsomia candida is a well-described standard test Collembola species used in toxicity tests. Its pathenogenetic life history makes it a suitable organism for sublethal toxicity tests 27.

The main objective of the present study was to develop QSARs for the toxicity of a series of chlorobenzenes to the soil-dwelling springtail F. candida in two different soils, that is, LUFA2.2 (Landwirtschaftliche Untersuchungs und Forschungsanstalt [LUFA]) natural standard soil and the Organisation for Economic Co-operation and Development (OECD) artificial soil. Effect concentrations causing 10% (EC10) and 50% (EC50) reduction in reproduction, respectively, were first derived for both soils based on concentration-response measurements, and QSARs were constructed. Subsequently, the natural standard LUFA2.2 soil was spiked with the calculated EC10 and EC50 concentrations and concentrations in the interstitial water were experimentally determined with polyacrylate-coated SPME fibers. Estimated and measured concentrations were then compared. Finally, a new QSAR for the natural soil was developed using measured concentrations.

MATERIAL AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Maintenance and culturing of the test organism

Continuous F. candida (strain “Berlin”) cultures were maintained in climate chambers (20°C, 12:12 h light:dark, 75% humidity) in pots with a moist plaster of Paris base. Animals were fed with dry baker's yeast (Dr. Oetker).

Test compounds

The selected chlorobenzene series included 1,4-dichlorobenzene, all three trichlorobenzene isomers (1,2,3-, 1,2,4-, and 1,3,5-trichlorobenzene) all three tetrachlorobenzene isomers (1,2,3,4-, 1,2,3,5-, and 1,2,4,5-tetrachlorobenzene), pentachlorobenzene, and hexachlorobenzene. The most important properties of the compounds are given in Table 1. All compounds were purchased from Sigma-Aldrich, except for 1,2,4-trichlorobenzene, which was obtained from Acros Organics. The minimum purity was 98%.

Table 1. Selected test compounds and relevant properties: Chemical Abstract Service (CAS)-number; molecular weight (MW). water solubility (log Sw; mol/m−3), organic carbon-water partition coefficient (log Koc), octanol-water partition coefficient (log Kow), and melting point (mp; °C)
ChemicalCAS no.MWLogSw a,elogKocblogKowcmp d
  • a

    Gobas et al. 35.

  • b

    Sabljic et al. 12.

  • c

    Ren 36.

  • d

    Cole and Mackay 37.

  • e

    Chiou 38.

1,4-dichlorobenzene106-46-7147−0.672.633.4451
1,2,3-trichlorobenzene87-61-6181.45−1.173.294.1353
1,2,4-trichlorobenzene120-82-1181.45−0.593.154.0517
1,3,5-trichlorobenzene108-70-3181.45−1.642.854.1864
1,2,3,4-tetrachlorobenzene634-66-2215.89−1.413.204.6447
1,2,3,5-tetrachlorobenzene634-90-2215.89−1.873.594.6554
1,2,4,5-tetrachlorobenzene95-94-3215.89−1.963.644.60140
Pentachlorobenzene608-93-5250.34−2.473.505.1886
Hexachlorobenzene118-74-1284.78−4.783.995.73230

Test soils

Standardized natural LUFA2.2 soil was slowly dried and defaunated in a stove at 60°C for 24 h. LUFA2.2 is classified as a sandy loam (particle size distribution: 50–2,000 µm, 75.3%; 2–50 µm, 16.6%; and <2 µm, 8.1%) with 2.2 ± 0.2% organic carbon and a pH (KCl) of 5.5 ± 0.4. Maximum water holding capacity was determined to be around 40% (w/w) of dry weight. Artificial soil was prepared according to OECD guideline 207 28 with 70% silver sand (Praxis), 20% kaolin clay (China clay, CH112, Keramikos), and 10% dried and ground Sphagnum peat (Jongkind B.V). The pH was adjusted with calcium carbonate to 6.5 ± 0.2. Water holding capacity was determined to be 81% of dry weight. Both soils were 2 mm sieved prior to use.

Soil treatment

Both soils were spiked with a nominal concentration range of 10, 20, 40, 80, and 160 mg kg−1 dry soil for all chemicals, except for hexachlorobenzene, which was tested with a range of 31.3, 62.5, 125, 250, 500, and 1,000 mg kg−1 dry soil. Controls included a water and solvent control. Five replicates were used for each concentration and control treatment. Acetone (HPLC-grade; Sigma-Aldrich) was used as a carrier solvent. For each concentration series, acetone dilutions were made from a stock solution. Stock solutions were not older than two days prior to use. Equal volumes of acetone (10 ml for 20 g of soil) were added for each treatment. To limit the effect of the acetone on the soil, a prespiking step was introduced. A total of 10% of the total soil mass for each test concentration was prespiked. Acetone solutions containing the test compound were introduced into a glass container, resulting in a thin layer of acetone covering the soil. The containers were closed with Teflon lids and mildly shaken (150 round min−1) for 1 h on a shaker and then stored in the dark. After 24 h of equilibration, the lids of the containers were removed for about 10% of the lid area in a fume hood to allow acetone evaporation. When the acetone was no longer olfactory detectable, the remaining 90% of dry soil was added to the container and the soils were mixed thoroughly. Mixed soils were brought up to 50% of the water holding capacity with demineralized water. Then, 30 g of spiked soil were transferred into 100-ml acetone-cleaned glass test jars and organisms were added within 16 h. In case jars were stored prior to testing (16 h max), they were tightly closed with methanol-cleaned screw caps.

Experimental setup

Toxicity tests were performed with synchronized 10- to 12-d-old animals, according to the International Organization for Standardization guideline 11267 29. Tests started with transferring 10 F. candida individuals into each test jar. A few grains of dried baker's yeast were added for food into each jar. If grains were no longer visible on the soil, additional food was added, but not before the second week of the test. The jars were closed with methanol-cleaned plastic screw caps, and water loss through evaporation was compensated by adding demineralized water once a week, if necessary. Jars were kept in fume cabinets with a 12:12 h light:dark period at 20°C and 75% humidity. Tests were terminated after 28 d. Animals and soils were then gently flushed into 400-ml glass beakers using 100 ml of water. Surviving adults and young juveniles floated on the slurry surface and photographs were taken from the surface with a digital camera (C-5060, Olympus) in triplicate to compensate for animal movement. Pictures were analyzed with the digital counter software Cell⁁D (Olympus), and the mean adult and juvenile numbers counted on three pictures were used for further calculations.

Solid-phase microextraction

The LUFA2.2 soil was spiked with the calculated EC10 and EC50 concentrations of all chlorobenzenes, except for 1,4-dichlorobenzene, based on the initial nominal concentrations applying the same procedure as described above. Within 12 h after spiking, soil slurries were prepared in quadruplicate in 7-ml amber-colored vials with 2 g of soil and 6.5 ml of Millipore water containing 0.01 M calcium chloride and 25 mg/L sodium azide. Finally, 2-cm long, 30-µm polyacrylate-coated SPME fibers (Poly Micro Industries) were added and the vials were placed on a “Rock-and-Roller” apparatus (Snijders Scientific) for four weeks. The fibers were then removed, quickly cleaned with a wet (Millipore water) tissue, and transferred to brown vials containing cyclohexane (pestiscan grade; LabScan) (volume tuned to expected concentrations). Internal standard solution was then added (10 mg/L PCB-31 in cyclohexane) and concentrations in the fiber extracts were determined by gas chromatography-electron capture detector (GC 8000 gas chromatograph; Fisons Instruments), equipped with a CombiPAL autosampler system (CTC Analytics), a Rtx-5 amine column (30 m length, coating thickness 25 µm, internal diameter 0.25 µm), a deactivated fused silica precolumn (length 2 m), and a 63Ni electron capture detector. Chromatographic data were analyzed with Chromcard 1.21 (CE Instruments).

Concentrations in the fibers (Cf) were used to calculate freely dissolved chlorobenzene concentrations in the soil interstitial water (Cmath image) using polyacrylate fiber-water partition coefficients [Kfiber], which had been determined according to the method reported by Muijs & Jonker 30). In short, seven 100-ml full glass, brown bottles were filled each with Millipore water containing 0.01 M calcium chloride and 25 mg/L sodium azide, 21 cm of fiber was added to each bottle, and the systems were spiked with a cocktail solution of the chlorobenzenes in acetone. After six weeks of equilibration on a shaker at 20°C, the fibers were removed and placed in autosampler vials with 200 µl of cyclohexane in an insert. A total of 50 ml of the water phase was than extracted three times with 10 ml of n-hexane, after which the solvent phases were pooled, concentrated, and exchanged to 0.5 ml of cyclohexane. All extracts finally received internal standard and were analyzed as described above. Resulting data were corrected for blank and recovery determinations (both in fivefold).

Statistical analyses

Concentration–response relationships for the effects on reproduction (EC10 and EC50) and survival (median lethal concentration [LC50]) were estimated by applying a log-logistic model in SPSS Statistics Software (Ver 15.00; IBM). Curves were fit following the equation by van Brummelen et al. 31 based on the initial nominal concentrations

  • equation image(1)

with y being the number of juveniles or survivors, x the test concentration, and k the number of juveniles or survivors in the control group. In case of survival data, the EC50 notations in Equation 1 were replaced with LC50 and EC10 with LC10. Corresponding concentrations in the interstitial water (Cmath image) were estimated using the organic carbon content (foc) of the two soils and the organic carbon-water partition coefficients (Koc) reported by Sablic 12 (Table 1). Obtained concentrations were used for linear structure-activity relationship regression analysis. Derived QSARs for both soils and effect concentrations, and for estimated and measured concentrations in interstitial water, respectively, were tested for significance with F-distribution analysis and compared with a generalized likelihood ratio test in SPSS.

RESULTS AND DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Chlorobenzene toxicity

Seven out of the nine tested chlorobenzenes had an effect on F. candida adult survival in both soils within the applied concentration range of 0 to160 (−1000) mg kg−1 dry soil. In OECD soil, eight out of nine compounds had an effect on reproduction, while for LUFA2.2 soil all nine compounds yielded an EC10 and EC50. The estimated threshold values (EC10, EC50, and LC50) expressed on a molar basis per kilogram of dry soil are given in Table 2. The EC10 and EC50 values for both soils increased with increasing logKow, going from 1,4-dichlorobenzene to pentachlorobenzene. For the LC50, this trend was not that prominent. In case of LUFA2.2 soil, the lethal effects occurred between 323 µmol kg−1 dry soil for 1,2,3,4-tetrachlorobenzene and 436 µmol kg−1 dry soil for 1,2,4-trichlorobenzene, but most compounds had a LC50 around 350 µmol kg−1 (Table 2). Comparing chemicals with the lowest and highest logKow, the LC50 differed only by 5 µmol kg−1 dry weight in LUFA2.2 soil and 34 µmol kg−1 dry weight in OECD soil. This finding confirms the older studies by van Gestel and Ma 14 with the earthworms Eisenia fetida and Lumbricus rubellus, in which the LC50 differences, especially between tetra- and pentachlorobenzene, were marginal. As shown in Figure 1, regressions of LC50 values against logKow for both soils are comparable when LC50 values are plotted as mmol L−1 interstitial water (estimated concentrations). In case of 1,4-dichlorobenzene, 1,2,3,4-tetrachlorobenzene, and pentachlorobenzene, LC50 values were actually overlapping or the same. Furthermore, a comparison with LC50 values derived from polycyclic aromatic hydrocarbons (PAHs) taken from Droge et al. 9 indicates that molecular size of organic pollutants might have different effects on the survival of F. candida (Fig. 1).

Table 2. Chlorobenzene concentrations causing 10% and 50% reduction of reproduction (EC10, EC50) and 50% mortality (LC50) of Folsomia candida exposed for 28 d to LUFA2.2 and OECD soil
 LUFAOECD
EC10EC50LC50EC10EC50LC50
Mmol kg−1aMmol kg−1aMmol kg−1aMmol kg−1aMmol kg−1aMmol kg−1a
  • a

    Concentrations are given as µmol kg−1 dry soil with 95% confidence intervals. ND = Not detected; NO = not observed.

Compounds
 1,4-dichlorobenzene498 (456–539)575 (514–635)349 (320–377)571 (524–617)651 (598–703)932 (856–1007)
 1,2,3-trichlorobenzene233 (210–255)378 (348–407)341 (277–404)211 (193–228)432 (397–466)701 (644–757)
 1,2,4-trichlorobenzene209 (192–225)443 (407–478)436 (405–466)254 (233–274)487 (447–526)451 (414–487)
 1,3,5-trichlorobenzene225 (201–248)261 (251–270)346 (314–377)230 (211–248)309 (283–334)679 (624–733)
 1,2,3,4-tetrachlorobenzene123 (104–141)183 (166–199)323 (252–393)98 (90–105)281 (258–303)828 (760–895)
 1,2,3,5-tetrachlorobenzene60 (49–70)289 (249–328)394 (358–429)88 (80–95)269 (247–290)625 (574–675)
 1,2,4,5-tetrachlorobenzene170 (148–191)183 (158–207)NO117 (107–126)319 (293–344)NO
 Pentachlorobenzene143 (130–155)155 (146–163)354 (313–394)135 (124–145)216 (198–233)898 (825–970)
 HexachlorobenzeneND1320 (945–1694)NONONONO
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Figure 1. Relationships between median lethal concentration (LC50) values for the effect on survival of Folsomia candida after 28 d of exposure to chlorobenzenes and logKow. Hexachlorobenzene and 1,2,4,5-tetrachlorobenzene are not included, as no lethal effect was observed up to a concentration of 1,000 mg kg−1 dry soil. White squares = Organisation for Economic Co-operation and Development soil; black squares = LUFA2.2 soil; grey triangles = polycyclic aromatic hydrocarbons (PAH; naphthalene, phenanthrene, and pyrene) data as reported by Droge et al. 9.

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Two compounds showed toxicity that was dissimilar from the other chlorobenzenes. Hexachlorobenzene was not toxic to adult animals over the complete concentration range and only affected reproduction in LUFA2.2 soil. This is in agreement with earlier findings in soil toxicity tests with F. candida and other soil-dwelling organisms that indicated reduced or no toxic effects on exposure to compounds with a logKow > 5.5. Droge et al. 9, for instance, found no lethal or reproductive effects for PAHs with a logKow higher than 5.54 at a maximum concentration of 990 mg kg−1 dry soil. In toxicity tests with a related species, Folsomia fimeteria, Sverdrup et al. 8 found no toxic effect of benz[a]anthracene (logKow 5.9) and chrysene (logKow 5.8) at nominal concentrations of 980 mg kg−1 dry soil in a soil with 1.6% organic carbon. With a logKow of 5.73, hexachlorobenzene is positioned in the same hydrophobicity range and displays a comparable mode of action. The fact that effect concentration values could be calculated for LUFA2.2 soil might derive from indirect effects on F. candida or its eggs, or a slow physiological response. Both aforementioned studies with PAHs also indicated a logKow threshold of 5.2 with a toxicity of pyrene similar to pentachlorobenzene in our compound series (logKow 5.18). This “super-lipophilic” range beyond logKow > 5.2 needs careful attention in future studies. The occurrence of exceptional effects like the toxicity of hexachlorobenzene in LUFA2.2 or additive effects in mixtures cannot be excluded.

More exceptional is the effect of 1,2,4,5-tetrachlorobenzene, with a clear impact on reproduction, but not on the survival of F. candida. Possible explanations for this remarkable response that was not observed for the other two tetrachlorobenzenes might be (1) an efficient metabolism in the adult individuals, as also shown for polycyclic compounds 32, effectively detoxifying the compound, but affecting the reproduction; or (2) an alternative compound property such as the melting point, as presented by Mayer and Holmstrup 33. In their experiment, mortality of 41- to 44-day-old adult F. candida only occurred when exposed to compounds with a melting point below 110°C. Chemicals with higher melting points did not have an effect within 7 d of exposure. The results for 1,2,4,5-tetrachlorobenzene are consistent with this finding because its melting point is 140°C, whereas for the other isomers, it is 47 and 54°C, respectively. Additionally, Hurdzan et al. 22 compared the toxicity of tetrachlorobenzenes to the terrestrial oligochaete Eisenia andrei and the aquatic oligochaete Tubifex tubifex and found no effects on adult survival. However, in none of these studies were effects on reproduction determined, which makes it impossible to generalize the observed pattern for 1,2,4,5-tetrachlorobenzene: the induction of effects only on reproduction. Based on traditional approaches of logKoc and logKow, a narcotic effect would have been expected. Alternative compound properties, such as melting point, cannot solely explain the effect on the reproduction. In this respect, QSAR development requires taking into account not only the mode of action of a compound but also a time of action of the test system and the test organism's possible life stage of action. An underestimated issue in soil ecotoxicological tests is the differentiation in terms of developmental stages in the life cycle of the test organisms. It is possible that several compounds cause their toxic effect only on eggs and not on adults. Toxicity therefore might result from effects on adult, hatchling, or dormant stages, or be multilevel. Taking into consideration that eggs are not only morphologically and physiologically different and have a higher metabolic rate, but are also immobile, toxic compounds can influence them differently compared to mobile adults. It is therefore recommended to include egg tests in the future to discriminate sensitive life stages.

Quantitative structure-activity relationships

In Figure 2, EC10 and EC50 values for the eight chlorobenzenes are plotted against logKow. The effect concentrations are expressed on the basis of estimated molar concentrations in the soil interstitial water. The figures show negative correlations for both soils, with slopes not being significantly different in all four cases (F-distribution test; p > 0.05). This is according to expectations, as for neutral compounds, the uptake into organisms and the association with complex substrates, like soil and sediment, are both based on hydrophobic interactions. As in previous studies with PAHs and F. candida9 and the related species F. fimetaria8, chlorobenzenes exhibit their toxic effect on reproduction following baseline toxicity. The correlation with logKow is strongest for OECD artificial soil in case of the EC50, but all four linear regression equations have r2 values above 0.9 (Eqns. 2–5)

  • equation image(2)
  • equation image(3)
  • equation image(4)
  • equation image(5)
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Figure 2. Relationships between the effective concentration for 10% (EC10) (a) and 50% (EC50) (b) values for the effect of chlorobenzenes on reproduction of Folsomia candida and the logKow in Organisation for Economic Co-operation and Development soil (white squares) and LUFA2.2 soil (black squares).

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Tri- and tetrachlorobenzene isomers with respective similar logKow and logKoc values form distinct clusters that are more compact in OECD soil and for the EC10 (Fig. 2a) than in LUFA2.2 soil and for the EC50 (Fig. 2b). For the EC10 this strong grouping is interrupted just by 1,2,3,5-tetrachlorobenzene for LUFA2.2 soil, which has lower estimated EC10 values in interstitial water as compared with its isomers. The same compound, however, has a higher EC50. A steep concentration-response curve for 1,2,3,5-tetrachlorobenzene probably caused the small differences between EC10 and EC50 values in the LUFA2.2 soil. Chemical properties offer no further generalizable explanation here because similar results were not observed for OECD artificial soil. Likewise, 1,3,5-trichlorobenzene had lower effect concentrations than its isomers in both soils, but only at the EC50 level. Having a lower logKoc than its isomers, a higher interstitial water-based EC50 would be expected instead. Possibly, biodegradation with soil and species-specific thresholds for microbial activity occurred over the 28-d test period, influencing the concentration in soil. Unfortunately, data on biodegradation of 1,3,5-trichlorobenzene in soil or any natural environment are scarce. Volatilization cannot be excluded, but should have a similar effect on the EC10, which is not the case.

Another observation that can be made from Figure 2 is that the distance between the regression lines for the two test soils is different. The OECD has effect concentrations in interstitial water that are lower than those in LUFA2.2 for both effect concentration values. Estimated EC50 and EC10 values should, however, be more or less equal, because physiological responses to toxic compounds can be expected to be related to the concentration in interstitial water only. Therefore, the differences are most probably due to variations in the logKoc values, which were used to calculate the aqueous concentrations. Ter Laak et al. 34, for instance, reported logKoc to vary by a factor of 1.6 to 3.5 for soot- and coal-free low organic content soils. In the present study, the following soils with different origin of their organic matter were used: sphagnum peat used in OECD soil is derived from slowly decomposed freshwater biomass, whereas the LUFA2.2 soil contains natural organic matter derived from grassland soils. From sorption QSARs it can be derived that aquatic organic matter generally sorbs organic chemicals stronger than terrestrial organic material 12, an observation that might explain the above discrepancy between the two soils.

Solid-phase microextraction and model validation

Polyacrylate fiber-water partition coefficients (logKfiber) determined for the eight chlorobenzenes are shown in Table 3. Dichlorobenzene was excluded from the SPME analyses because its estimated half-life in the thin fiber coating was too short in comparison to the time needed for processing and extracting the fibers. Hexachlorobenzene is not included as it was already discarded from the QSAR due to its deviating behavior. The Kfiber values appear to be somewhat lower, yet proportional to octanol-water partition coefficients (logKow) (see Fig. 3). The values were used for the measurement of chlorobenzene concentrations in interstitial water of LUFA2.2 soil. The resulting EC10 and EC50 values are given in Table 3. In Figure 4, the tri-, tetra-, and pentachlorobenzene data are compared to the logKow of the compounds. Although correlations similar to those in Figure 2 are observed, predicted (Eqns. 2–5) and SPME measurements-derived models are significantly different for the EC10 (p = 0.03) and the EC50 (p = 0.002) in a pair-wise t test. Equations based on measured concentrations in interstitial water are

  • equation image(6)
  • equation image(7)
Table 3. Polyacrylate fiber-water partition coefficients (logKfiber) for selected chlorobenzenes and measured concentrations in interstitial water of LUFA2.2 soil at effective concentration for 10% (EC10) and 50% (EC50) levels for the effect on the reproduction of Folsomia candidaa
ChemicallogKfiberSPME LUFA2.2
EC10EC50
µmol L−1µmol L−1
  • a

    Concentrations are given as µmol L−1. Values in brackets represent standard deviations (n = 7) SPME = solid-phase microextraction.

1,2,3-trichlorobenzene3.91 (0.03)14.2 (1.12)28.54 (0.94)
1,2,4-trichlorobenzene3.82 (0.03)7.89 (0.49)14.48 (0.68)
1,3,5-trichlorobenzene3.83 (0.04)13.5 (2.02)15.84 (1.06)
1,2,3,4-tetrachlorobenzene4.51 (0.02)3.20 (0.21)4.75 (0.17)
1,2,3,5-tetrachlorobenzene4.39 (0.04)1.99 (0.03)11.69 (0.24)
1,2,4,5-tetrachlorobenzene4.35 (0.03)5.80 (0.15)7.17 (0.37)
Pentachlorobenzene4.96 (0.01)1.44 (0.04)1.67 (0.06)
thumbnail image

Figure 3. Relationship between polyacrylate fiber-water partition coefficients (logKfiber) and octanol-water partition coefficients (logKow) for chlorobenzenes.

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thumbnail image

Figure 4. Comparison of the relationships between estimated (Koc-derived) effective concentration for 10% (EC10) (a; grey circles) and 50% (EC50) (b; grey circles) values and measured Solid-phase microextraction (SPME)-derived EC10 (a; black circles) and EC50 (b; black circles) values for the toxicity of chlorobenzenes to Folsomia candida in LUFA2.2 natural soil.

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Interestingly, the obtained correlations based on measured concentrations are less significant than the QSARs based on estimated concentrations, even though one would expect accurate measurements to improve the significance. Measured compound-specific concentrations were all lower than corresponding estimated concentrations, with the exceptions of the EC50 values for 1,2,3- and 1,3,5-trichlorobenzene and 1,2,3,5- and 1,2,4,5-tetrachlorobenzene, which were similar. Lower measured concentrations may be due to loss through volatilization or biodegradation, or stronger sorption. However, the latter is most likely because the SPME measurements started already 12 h after soil preparation and were performed in closed systems to which a biocide was added. Assuming that the SPME-derived concentrations reflect actual exposure concentrations, the literature Koc values may provide poor reflections of actual sorption, as also observed for other chemicals 17. This hypothesis is supported by the observation that generally the distance between the estimated and measured EC10 and EC50 values increased with increasing logKow (Figs. 4a and 4b).

Perspectives for REACH

Folsomia candida is generally more sensitive to chlorobenzenes than other soil invertebrates, such as the earthworms E. andrei and L. rubellus7. Thus, tests performed with this standard test organism should be preferred over earthworm tests under the perspective of REACH.

The observed toxicity of chlorobenzenes correlated with their logKow, which agrees with prior findings, with two major exceptions. Hexachlorobenzene, being the most hydrophobic chemical tested, demonstrated only reduced toxicity, but should be considered in future tests for superlipophilic compounds. However, mixture effects in the presence of other compounds are possible and should be the focus of future studies. Furthermore, the prominent pattern of 1,2,4,5-tetrachlorobenzene, having effects on reproduction only and not on survival, agrees with findings by Hurdzan et al. 7. This indicates that the prediction of potential toxicity of compounds, with a classification based only on hydrophobicity, is not sufficient. However, replacing classical approaches by alternative descriptors is risky. This is illustrated by the fact that QSARs based on melting points cannot predict the present soil toxicity data. The melting point may explain outlier behavior of certain compounds, even groups of isomers, but is so far more an asset than an alternative. More data, also for heterocyclic and polar compounds are therefore required.

The QSARs based on EC10 and EC50 values developed in the present study follow baseline toxicity, as they are proportional to logKow. The differences observed between the natural LUFA2.2 soil and the OECD artificial soil, however, reveal a major problem in soil toxicity modeling. The estimated effect concentration values depend on the applied logKoc to such an extent that the same physiological response appears to occur at different concentrations in the interstitial water. This makes QSARs less accurate for predicting toxicity over a wide range of soils differing especially in the nature and properties of the organic matter fraction. Nevertheless, QSARs remain a very efficient tool for assessing potential risks of individual compounds and compound series. Solid-phase microextraction offers a simple and fast technique to measure concentrations in interstitial water and can help optimizing QSARs for soil ecotoxicity, as presented in the present study.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

This work was supported by the European Union 6th Framework Integrated Project OSIRIS (contract no. GOCE-ET-2007-037017; http://www.osiris-reach.eu).

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES
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