Environ. Sci. Techno/. 1995, 29, 726-734
S m g a t e Parameter for the
Baseline Toxicity Content of com Water: Simdatinm the Biocoacemtration of Mixtures of Pdlwfmts and Co~tiny Molectiles -
HENK J. M. VERHAAR,' F R A N S J . M . B U S S E R , AND J O O P L . M . HERMENS Research Institute of Toxicology, Environmental Toxicology Section, Utrecht University, P.O. Box 80.1 76, NL-3508 TD Utrecht, The Netherlands
A large part of all environmental pollutants can be classified as narcosis-type chemicals with regard to acute aquatic toxicity. This baseline, or narcosistype, toxicity is generally assumed to be brought about through one and the same mechanism. The effects of these chemicals are directly related to their (equilibrium) body burden. This implies that the 'total baseline toxicity content' of an aquatic sample is dependent only on the cumulative body burden of these compounds and that this could be made into an important parameter in risk assessment for the aquatic ecosystem. A simple procedure to simulate the biotic body burden of a mixture of pollutants, by using Cia-Empore disks and to subsequently quantify this cumulative body burden on the basis of molar concentrations by means of vapor pressure osmometry is described. This procedure fulfils the requirements of a true surrogate parameter for the estimation of the total baseline toxicity content of environmental water samples by obviating the need of identifying and quantifying individual compounds and by enabling an estimation of the contribution of baseline toxicity to the overall toxicity of surface waters and effluents.
Introduction Approaches in Risk Assessment of Complex Mixtures of Pollutants. The pollution of surface water, wastewater effluents, and groundwater is one of the major problems of our time. In most cases, water pollution encompasses complex mixtures of organic and inorganic contaminants, which normally have to be (qualitatively) identified and (semi)quantitatively analyzed in order to be able to accurately assess the associated risk. Moreover, the risk assessment of contamination with mixtures is confounded by the fact that the combined effect of mixtures may be either antagonistic, additive, synergistic, or anythmg in between. Our insight into these processes of joint toxicity in the environment has been furthered by the distinction into differenttypes ofmixtures as pointed out by Konemann ( 1 ) or Broderius and Kahl (Z), who showed that for mixtures of compounds with the same (or a similar) mode of action effects are completely concentration additive. The (semi)quantitativeanalyses needed for risk assessment can be performed using a number of basically different approaches: (1) Identification and quantification of all individual pollutant components from an environmental sample and subsequent assessment of the toxic potency of the sample using known or estimated aqueous toxicities for each component (2) Quantitative determination of a so-called 'surrogate' parameter for groups of (known, organic) pollutants. Examples of surrogate parameters are total organic chlorine (TOCl) or extractable organic chlorine (EOC1) as an indication of the amount of organochlorine contaminants or an in-vitro acetylcholinesterase (AChE)inhibition assay as an indication of the amount of organophosphorus andlor carbamate pesticides. (3) Direct determination of the toxicity of an environmental water sample or a concentrate of the sample, in any of a number of types of (simple) toxicity tests such as the Microtox assay (Photobacteriumphosphoreum) or a D a p h nia test. All mentioned approaches have inherent drawbacks that will, sometimes severely, limit their usefulness in actual risk assessment procedures. Analysis of individual components presupposes the availability of methods of complete and nonselective extraction of all xenobiotics from water-something which is not normally achieved-and the possibility of positive identification of all extracted compounds. Noordsij et al. (3) concluded that, in 1983, not even 5% of all extracted organic compounds could be identified by GUMS techniques. By 1994, this situation had not improved considerably (4). Moreover, for only a small percentage of actual identified pollutants, pertinent toxicity data are available, and even less is known on how to arrive at a measure of the toxicity of a complex mixture from individual toxicity data and concentration data. Another problem with this approach is that no information is available on what fraction of extracted compounds is actuallybioavailablefor aquatic lifeformsand what fraction ~~
* Corresponding author; Fax: 31 30 535077; e-mail address:
[email protected].
726
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 29, NO. 3,1995
0013-936X/95/0929-0726$09,00/0
0 1995 American Chemical Society
is (irreversibly)bound to organic carbon (both dissolved and particulate) or sediment. Most surrogate parameters suffer from a very limited capability to actually predict quantitative effects, since no information is gained on either the (intrinsic) toxicity of the compounds involved or even the levels attainable in organisms. Direct toxicity assessments on the other hand do give information on the expected effects in the environment but fail to yield information on what compounds or groups of compounds are involved-to that end, additional analyses need to be performed. All methods mentioned fail to directly yield information on the potential of mixtures of contaminants to bioconcentrate from the aqueous phase into biota. Clearly then, there is a need for an (additional) surrogate parameter that is based on chemical analysis and is toxicologicallyrelevant. It is, of course, impossible to devise one procedure that provides toxicological relevant information for all possible chemicals in a complex mixture. There is however one very broad ‘class’of compounds in the sense that it includes many organic chemicals. It covers all those compounds that act (under certain circumstances) by a ‘nonspecific’ mode of action, also referred to as narcosis or baseline toxicity. The objective of this study was to develop a chemical procedure for the estimation of the total amount of ‘nonspecific activity’ in an aquatic sample. Such a procedure is at the same time capable of providing information on the bioconcentration potential of complex mixtures. Before giving an outline of the approach followed, it is necessary to explain briefly the theoretical background of baseline toxicity and mixture partitioning.
Theory Baseline Toxicity and Bioconcentration: Critical Body Residues. Uptake of (most) organic micropollutants from water by aquatic organisms can be regarded as a passive, diffusion-driven process that ultimately depends on the concentration gradient of a compound between water and organism and on the affinity of the compound for these ‘two’ phases (5, 6). The distribution behavior of a compound between water and (specific)biota can be expressed as a so-called bioconcentration factor (BCF). This BCF is usually computed as
BCF = C,/C, with Cfdesignating the whole-body (or lipid-normalized whole-body) concentration in biota and Ca denoting aqueous concentration, both at equilibrium. It has been shown that for a large set of environmentally relevant compounds and within certain limits there exists an adequate (unity) linear relationship between log BCF, expressed on a lipid weight basis, and the octanol-water partition coefficient log KO, (7-9). Van Hoogen and Opperhuizen (10) and McCarty and co-workers (11,12),among others, showed that for sets of compounds exhibiting baseline toxicity there appears to be a fKed lipid-normalized whole-body concentration at which aquatic animals die, the so-called lethal body burden (LBB) or critical body residue (CBR). For this baseline LBB values of ca. 2-8 mmol kg-l wet body weight were reported (IO), whereas for chlorophenols, generally classifled as polar narcotics (13-13, LBBvaluesof0.5-1 mmolkg-’wetbody weight were reported (16). McCarty et al. ( I 7) reported a
lipid-normalized CBR for baseline toxicity chemicals of ca. 50 mmol L-’; van Leeuwen et al. (18)and Verhaar et al. (19) used this CBR approach to arrive at a safe body residue, based on aquatic HC5values (hazardous concentration to 5% of all species), of ca. 0.25 mmol L-l. These findings are of course in agreement with the well-known relationships between log KO, and log LCso (median lethal aquatic concentration), which show a linear relationship with a regression coefficient of approximately negative unity for both classes of compounds (20-24). Konemann (I), Broderius and Kahl (2),and Deneer et al. ( 2 3 , among many others, showed that, at least for chemicals that act by either narcosis or polar narcosis, the joint toxic action of mixtures of two or more chemicals from one class can be regarded as being simply concentration additive. This of course means that the LBB (as described above) will hold for total (molar) whole-body concentrations of mixtures of compounds as well. Moreover, it has been argued by Hermens and Leeuwangh (26)that compounds that act by more specific modes of toxic action, such as reactive electrophiles or specifically acting organophosphates, can be regarded as baseline toxicity compounds when they are present below their (additive)threshold concentrations and thus will contribute to the joint additive baseline toxicity effect level. All these considerations taken together lead us to the conclusion that a simple way of measuring total molar concentrations of xenobiotics-without necessarily having to know what compounds are present-in biota or in surrogate lipoid phases that can accurately mimic biotawater partition behavior for large groups of xenobiotics would be an ideal tool for quickly screening environmental water samples for their toxic potential. An outline of the approach is depicted in Figure 1. Figure l a shows the partition behavior from water to lipoid phases (e.g.,fish) for three chemicals with partition coefficients of 10, 1000, and 100 000, respectively. Note that in our approach not the individual concentrations but the cumulative molar concentration of all compounds in the lipoid phase are of interest. In Figure lb, CBRs are shown for three different effects, viz., lethality (median lethal body burden (17)), no-observed-effect concentration in a ‘fish early life stage test’ (241, and the HC5, which represents a safe level for effects on ecosystem level (18, 19). As already mentioned, the approach should fulfil the following requirements: (1) the concentration technique employed must reflect differences in hydrophobicity; (2) the quantitative analysis must supply information on total molar concentrations. Simulating Bioconcentration: BiomimeticExtraction. Surrogate Lipoid Phases. As has been argued, there exist adequate linear relationships between log BCF and log Kow Furthermore, many authors have pointed out that a relationship exists between Cls reversed-phase HPLC capacity factors IC and KO,, and have actually used this relationship to estimate log KO, values for a large number of very diverse compounds, usually with very good results (27-29). We therefore hypothesize that a chemically bonded Cle-coated silica material (essentially a reversedphase HPLC column packing material), brought into direct contact with water, would create a good surrogate partitioning system for either an octanol-water system or a biota-water system. Since a system consisting of ‘raw’reversed-phase HPLC column packing material in (a large amount of) water is an VOL. 29, NO. 3,1995 /ENVIRONMENTAL SCIENCE &TECHNOLOGY
727
b
-
bn
-
NOEC 5 m M c
.-0
c
Y
e
c E,
aJ U
5
U
Aqueous phase
-m
Fish
Y
FIGURE 1. Schematic outline of the baseline toxicity surrogate parameter. (a) Pattitioning behavior of three different chemicals between water and lipoid phase. The relevant parameter in baseline toxicity is the cumulative concentration of all compounds, on a molar basis, in the target organism, as denoted by ZG. (b) Overview of critical body residue levels for three different effects: 50% lethality, noobserved-effect, and (tentative) safe level for ecosystam effects; these levels are valid for either single compounds or mixtures of minimum toxicity compounds.
experimentally difficult system,we decided to employBaker Empore disk material, cut into pieces of appropriate size, instead of raw packing material. Empore disks consist of a Teflon fiber matrix in which a reversed-phase,chemicallybonded C18 silica material is trapped. The use of a chemically bonded CIS silica liquid chromatography-type material has certain practical advantages over other surrogate biophases, such as the hexane-filled dialysis bags described by Sodergren and co-workers (30, 31) or the semipermeable membrane devices proposed by Huckins etal. (32). Some of these advantages are shorter equilibration periods and simpler extraction procedures. In order to adequately simulate the bioconcentration process that occurs in either BCF determination experiments or in actual environmental bioconcentration, care has to be taken in order to ensure that the actual aqueous concentration of contaminant(s) during experiments does not decrease. For most environmental contamination situations, it can easily be shown that the bulk of contaminated water is large enough to ensure that uptake of contaminants by aquatic organisms will not affect the aqueous concentration of the contaminants. The requirement that the aqueous concentration of contaminants does not decrease due to the extraction (or concentration) procedure is in contrast with most extraction techniques, which intend to extract 100% of all contaminants from an aqueous sample under study (so-called ‘analytical extraction’). Several practical extraction techniques are in common use today, such as XAD extraction, Soxhlet extraction, SPE microcolumn extraction, etc. (33). To make clear the distinction between this analytical extraction and our intended extraction, we will call our procedure ‘biomimeticextraction’. Theoretically, in this biomimetic extraction procedure aqueous concentrations will also decrease during partitioning process. This means that, in practice, arbitrary limits will have to be set as to what decreasein concentration we find acceptable,without makingthe analytical procedure unduly difficult or impossible. We have arbitrarily set an aqueous concentration decrease of 25% of the most hydrophobic compound as the acceptable limit. It can easily be shown that for any concentration decrease limit a corresponding Wl Vratio can be calculated according to 728
ENVIRONMENTAL SCIENCE &TECHNOLOGY / VOL. 29, NO. 3,1995
w-100 - x V
X
where Wis the volume of the aqueous phase, Vis the volume of the hydrophobic phase, x is the acceptable limit of aqueous concentration decrease in percent, and K is the partition coefficient for the most hydrophobic, relevant compound. Partly because of practical considerations, we chose an experimental WIV ratio of 0.68 x lo6, which ensures that we will stay within our chosen limits for compounds up to a partition coefficient Kof 5 2 . 3 x lo5. Mixture Partitioning. The intention of the surrogate parameter described in this paper is to simulate the bioconcentrationof a mixture of micropollutantsfrom water into an organism,without the need to actually identify and quantify all compounds present in both aqueous and biomimetic samples. The aim is to provide one concentration-type number that can easily be related to the expected total body burden in aquatic animals. This number should be obtainable by measuring the total amount ofxenobiotics in only the biomimetic sample. It should however be realized that for mixtures of compounds of different partitioning behavior (read: different log there is no simple distribution coefficient linking aqueous concentration to the concentration in a hydrophobic phase. This can easily be shown for a simple, two-constituent mixture. The partitioning behavior of a mixture can be described with the following equation: Qi
w&K,v+
1 (3)
where Kmk is the partition coefficient of the mixture, W is the volume of the aqueous phase, V is the volume of the lipoid phase, n is the number of compounds in the mixture, Qi is the total amount of compound i in the system, and K, is the partition coefficient of compound i. Ifwe apply this formula to a 1:1mixture of two compound with partition coefficientsKjof, 100and 10 000, respectively, we see that for a Wl V ratio of lo5, Kmh is approximately
4820, whereas for a Wl V ratio of 1, Kmk is approximately 199. It can equally be derived that, for an equimolar mixture, in order to arrive at a Kmk that is effectively independent of the Wl V ratio, Wl V must at least be five time higher than & of the most lipophilic compound of the mixture. This of course also means that for mixtures of unknown composition, the Wl Vratio must be chosen such that it reflects the Ki of the most lipophilic compound expected or the most lipophilic compound that is to be considered important. This Wl V ratio restriction also ensures that there will be no significant decrease in aqueous concentration, as required for biomimetic extraction. Measuring Total Molar Concentration: Counting Molecules. The CBR approach hinges on the assumption (whichis supported by a number of observations)that only the total molar concentration of all compounds that act through narcosis is the important parameter. To peruse this notion in analytical environmental toxicology, there is a need for an analytical method that is capable of measuring the total molar concentration of a mixture of solutes, regardless of the nature of these solutes. There are not many analytical techniques that are capable of doing just this, and all techniques that do, employ the concept of osmosis (34). The analytical methods that can measure the osmolality of a solution (i.e., the total molar concentration of solutes present) are as follows: (1)osmotic pressure determination; (2) freezing point depression determination; (3)boiling point elevation determination; (4)vapor pressure depression determination. Of these four techniques, the vapor pressure depression determination method has the advantage of needing the smallest amount of solute sample and of generally being the most sensitive, while still needing only relatively inexpensive equipment. For these reasons we chose to develop a total molar concentration surrogate parameter based on vapor pressure osmometry as an analytical technique. In this method, a small sample of a solution is applied onto a thermistor, which is situated in a thermostated chamber that is saturated with solvent. A drop of pure solvent is applied onto a second thermistor inthis chamber, and the temperature difference between these two thermistors, resulting from the condensation of solvent vapor onto the solute sample, is measured. Typically, a single measurement takes about 4-5 min at the highest sensitivity setting; this time is mainly needed for the instrument’s signal to stabilize. Overview of Experiments. In order to assess both the applicability of vapor pressure osmometry to the analysis of so-called biomimetic extracts and the use of the Empore disk material as simulated biophase, a number of experiments have been performed. Detection limit and linear response range of the vapor pressure osmometer was tested using a concentration series of solutions of 1,2,3,4-tetrachlorobenzene in cyclohexane. Independence of molar responses from a compound’s nature and additivity of osmometer responses for mixtures of diverse compounds was tested using two mixtures (see Table 2) as well as the individual constituents of these mixtures. Applicability of Empore disks to simulate bioconcentration was tested in three experiments, in which aqueous solutions of 1,2,3,4-tetrachlorobenzene, mixture A, and mixture B, respectively, were allowed to equilibrate with small slivers of Empore disk material. These experiments were performed at three concentrations and in triplicate.
Levels of individual compounds in the highest concentration experiments were usually chosen such that they were a factor of 30 less than reported aqueous solubilities. All experiments were accompanied by controls, which consisted of spiked water at the highest employed aqueous concentration but to which no Empore material was added.
Methods Biomimetic Extraction Partitioning to Simulated ‘Biophase’. All partitioning experimentswere carried out using 2-L glass bottles with Teflon-lined screw caps (Schott). Bottles were filled with 2 L of deionized water, obtained by treatment with a Milli-Q (Waters) apparatus fitted with an Organic-Free kit. This water was spiked with test compounds or test compound mixtures dissolved in 100 pL of acetone (J.T. Baker, resi-analyzed). The spiked water that was thus obtained was stirred vigorously with magnetic spin bars and magnetic stirrers Uanke & Kunkel) for at least 48 h, or until compounds were fully dissolved. Only then was the hydrophobic phase material added. As hydrophobic phase material (simulated ‘biophase’), slivers of approximately 13mg of Empore disk (Baker)were used. According to documentation obtained from the supplier, these disks consist of 10%wlw Teflon matrix, in which 90%wlw silica particles with chemicallybonded CIS material (‘octadecyl’) are contained. This chemically bonded octadecyllsilica material is claimed to have an organic carbon content of 17% wlw; implying that 1 g of the coated silica material contains 0.197 g of CIS. If it is assumed that the density of CISis equal to the density of octadecane, which is 0.78 g mL-’, 1 g of Empore disk contains 0.227 mL octadecyl hydrophobic phase. Consequently, 13mg of Empore disk contains 2.95pL of octadecyl hydrophobic phase material, yielding a Vl W ratio (see above) of 0.68 x lo6. Substituting this VI W ratio, plus our chosen maximum allowable concentration decrease of 25%, into eq 2 shows that this setup should be sufficient for compounds with a partition coefficient of 2.3 x lo5. All Emporelwater partitioning experiments were performed at ambient temperature in a temperature-stabilized room (thermostated at ca. 22 “C). Water samples (2.5 or 5 mL) were taken regularly, both before and after the addition of the hydrophobic phase material, to assess the actual aqueous concentration of test compound(s) at the start of the experiment as well as to monitor the decrease of the aqueous concentration during the partitioning process. This allowed us to get a reasonable impression of the time to reach equilibrium concentrations. Water samples were then extracted with equal amounts of n-hexane (J. T. Baker, resi-analyzed), and a known amount of internal standard (either lindane (PolyScience Corp.) or PCB153 (Dr. Ehrenstorfer)) was added. Aliquots of the hexane layer were then quantitatively analyzed by gas chromatography (Carlo Erba 5360 GC), equipped with a J&WScientific DB-5 fused silica capillary column and an electron capture detector, coupled to a Baseline (Waters) data acquisition and processing system. Empore disk slivers were collected at the end of the experiment-depending on the actual experiment after 10 or 14 days-flushed with deionized water, and extracted with 1mL of cyclohexane (1.T. Baker, resi-analyzed) under sonication (Elma Transsonic T460) for ca. 30 minutes. Cyclohexane extracts were analyzed both by GC/ECD as described above and by osmometric analysis as will be described in the next section. VOL. 29. NO. 3, 1995 /ENVIRONMENTAL SCIENCE &TECHNOLOGY
729
Statistical analyses were performed using the comprehensive statistical package SYSTAT, version 5.2 (39, and the symbolic algebra package Theorist, version 1.51 (36). Nonlinear regression fits of aqueous concentration vs time were performed using a quasi-Newton algorithm, with standard deviations in Y values (concentrations) used as weighting factors. All calculations were performed on a Macintosh LC desktop computer, equipped with a floating point unit. Osmometric Analyses: Counting Molecules. Osmometric analyses were performed with a Gonotec Osmomat 070 vapor pressure osmometer with a Control Unit B. Output from this instrument is recorded with a Servogor strip chart recorder. The instrument was calibrated using cyclohexane solutions of 1,2,3,4-tetrachlorobenzene (Riedel de Haen, p.a.1. These solutions were also used for determining the practical concentration detection limit of the instrument. In order to assess the (theoretically expected) additivity of responses for different chemicals, molar response factors for individual compounds as well as for a number of different mixtures from the abovementioned set of test compounds were determined. Total molar concentrations of test compounds on Empore disk material were measured as follows. Empore disk slivers were collected and extracted with 1 mL of cyclohexane under sonication. From this 1 mL of test solution, 0.5 mL was used for control measurements with GC/ECD, while the other 0.5 mL was used for osmometric analyses. External concentration reference standard is provided by measuring responses for a series of 1,2,3,4tetrachlorobenzene solutions of known concentration and calculating a calibration curve from these data. All measurements were performed in accordance with the manufacturer-supplied operating manual. Measuring time was 5 min, and the sample cell temperature was 49 "C.
Performance of Vapor Pressure Osmometer. For the determination of detection limit and linear response, the osmometric responses for a series of 1,2,3,4-tetrachlorobenzene solutions in cyclohexane, plus a control solvent sample,were measured as described. The calibration curve for the response of the vapor pressure osmometer vs concentration of 1,2,3,4-tetrachlorobenzene (0.39-50 mM) is presented in Figure 2, which shows the responses corrected for control solvent response. Figure 3 shows an example of osmometer output (highest sensitivity setting) for a 0.5 mM 1,2,3,4-tetrachlorobenzene solution sample. These results indicate that the absolute detection limit for this vapor pressure osmometer is about 0.1 mosM or 0.1 mM for nondissociating compounds. Molar response factors for most of the 18 compounds that were used in this study were reasonably constant, varying between 42 and 45 VIM W. M. G. M. van Loon and J. L. M. Hermens, manuscript in preparation), as was expected. A few compounds, viz., 1,4-dichlorobenzene, pentachloroethane, and hexachloroethane, have substantially lower molar responses (33.5, 27.2, and 39.1 V/M, respectively); this is due to the substantial vapor pressure that these compounds have with regard to the vapor pressure of the solvent used (cyclohexane). Mixture studies with these 18 compounds additionallyshowed the expected additivity of the osmometric response. Responses of two equimolar mixtures consisting of (a) 8 chlorohydrocarbons 730 ENVIRONMENTAL SCIENCE &TECHNOLOGY / VOL. 29, NO. 3, 1995
J
0.1
1 10 100 Concentration (mM)
FIGURE 2. Calibration curve for vapor pressure osmometer output (V) vs concentration of a series of standard solutions of 12,3,4tetrachlorobenzene in cyclohexane (mM).
]benzene
FIGURE 3. Example of a typical vapor pressure osmometer output trace (0.5 mM 1,2,3,4-tetrachlorobenzene) at the highest sensitivity setting of the instrument's amplifier.
and (b) several aromatic chloro and nitro compounds, anilines, and pesticides were measured. The first mixture (mixture A) had an expected response of 0.405 V vs a measured response of 0.404 V, and the second mixture (mixture B) had an expected response of 0.441 V vs a measured response of 0.445 V. These results clearly show that osmolarity measurements of mixture solutions are a viable option for assessing total molar concentrations of contaminants in samples that have a high enough total concentration of xenobiotics. Biomimetic Extraction of Spiked Water Samples. Detailed results of the biomimetic extraction experiment for 1,2,3,4-tetrachlorobenzene are summarized in Table 1; results include concentration in the aqueous phase over time, final concentration on Empore disk slivers, mass balance, and the experimental partition coefficientKD.This experiment was performed &fold and included two controls, for a total of 10 sample bottles. All mass balances were between 97% and 106%. The resulting KD value is 221 000 f25 000 (mean f SD; log KD= 5.34). A plot of the concentration of 1,2,3,4-tetrachlorobenzene in the aqueous phase vs time is given in Figure 4. The results of the two mixture experiments are presented in Table 2 ; information on the final aqueous concentrations, mass balances, andKDvalues is given. Detailed information
TABLE 1
Results from Partition Experiment of 1,2,3,4=Tetraehlorobenzene between Water and Empore Disk Material control 1
control 2
3
362.1
362.5
378.0 356.6 370.1 364.1 101
370.6 373.1 369.8 360.8 100
356.3 329.1 337.5 292.6 282.6 279.2 276.1 75 534.2 217.3 106 5.400
Cas.t=o (pg/L)" Caq,e3 ( d L ) " caq, e6 caq.e 2 4
(pg/L)'
Cas,t=a(pg/L)a Cas.e97 ( , d J a caq, f=144
Caq,e14dCaq.t=o ( % ) b amount i n water (pg)" amount on disk (pgId mass balance
log KD'
4
355.1
5
350.3 326.3 334.5 294.6 280.1 260.5 284.6 272.3 265.3 261.1 266.7 74 76 533.4 522.2 200.9 197.9 102 105 5.353 5.373
6
351.2
7
360.5
8
358.4 337.3 346.9 316.3 272.9 297.6 294.0 278.7 266.8 278.9 270.8 270.1 257.5 274.3 265.9 78 74 72 548.6 531.8 515.0 179.7 156.3 222.5 97 100 105 5.251 5.396 5.317
9
10
356.6
354.5
312.8 289.0 282.8 264.3 74 528.6 183.2 100 5.318
318.9 298.6 280.1 265.0 75 530.0 178.3 100 5.320
a C ., = aqueous concentration at time t. Percentage of TeCB remaining in the aqueous phase at time t= 144. Amount of TeCB in the aqueous phase at time t = 144. dAmount of TeCB in the lipoid phase at time t = 144. e Overall mass balance for the complete experiment. Empore-water partition coefficient.
400
r
250 0
I
I
I
50
100
150
Time (h) FIGURE 4. Decrease of the aqueous Concentration of 1,2,3,4tetrachlorobenzene during 6 days of partitioning between water and Empore disk material. Data are means and standard deviations from eight individual bottles, as given in Table 1.
is only presented for experiments performed at the highest aqueous concentrations, but the results for the two lower levels are very similar. KDvalues as reported in these two tables are mean values for all three concentration levels (three triplicates each for a total n = 9). Figure 5 shows a comparison of the experimental KD values with experimental Kow values obtained from the MedChem Starlist (37). The corresponding correlation between log GW and log KDhas the following regression fitted form:
log KD = 0.995 log KO, + 0.70
? = 0.93
SE = 0.24
(4)
Figure 6 shows the results of the comparison of the summed GC-derived amounts of contaminant on the Empore disk slivers vs the amount measured with vapor pressure osmometry, employing a standard series of 1,2,3,4-tetrachlorobenzene to create a calibration curve. These results are also presented in Table 3.
Discussion Performance of Vapor Pressure Osmometer. The results shown in Figures 2 and 3 show that the vapor pressure osmometer has an adequate linear response domain (at least from 0.5 to 50 mM) and an absolute detection limit of ca. 0.1mosM (0.1mM for neutral organic compounds) or less. Preliminaryresults on molar responses and mixture
responses for 18 environmentally relevant compounds indicate that molar responses are indeed constant and independent of the type of compounds used or the makeup of the mixture. Only those compounds that have a nonnegligible vapor pressure as compared to the solvent showed a somewhat lower response. More information on these aspects of vapor pressure osmometry as an analy&ical tool will be published in a forthcoming paper by van Loon and Hermens (manuscript in preparation). Biomimetic Extraction of Spiked Water Samples. The results of the experiment with 1,2,3,4-tetrachlorobenzene, summarized in Table 1, can be used to draw a number of important conclusionsregardingthe biomimetic extraction procedure. From the data on the aqueous concentration of 1,2,3,4-tetrachlorobenzene vs time (see Figure 4),it can be inferred that for this compound an equilibrium in aqueous and Empore concentration is essentially reached after 96 h. The results of the two mixture experiments show that, for those chemicals with a lower hydrophobicity than 1,2,3,4-tetrachlorobenzene, equilibriumwas reached within the duration of the experiment. For some of the compounds with a higher hydrophobicity,notablypentachlorobenzene and dieldrin, equilibrium was not entirely reached within 10 or 14 days. From numerical fits to exponential decay functions, it can be calculated that pentachlorobenzene had reached &79%of equilibrium in 251 h, fenchlorphos had reached &85%of equilibrium in 359 h, and pentachlorobenzene would have reached &89% of equilibrium in 359 h. The mass balances for the 1,2,3,4-tetrachlorobenzene extraction experimentwere essentially loo%,indicating that possible losses of material are neghgible. For the experiments with mixtures A and B, mass balances were acceptable (generally95%or higher) except for 2,4-dichloroaniline, methylparathion, and fenchlorphos (ronnel),which were between 80% and 90%. The overall decrease in aqueous concentration of tetrachlorobenzene over the course of the experiment was larger than expected. As indicated in the Introduction, the W / V ratio employed in these experiments should be sufficient for compounds with a partition coefficient of up to 105.36. The experimental Empore-water partition coefficient log KDfor 1,2,3,4-tetrachlorobenzene is determined to be 5.35, substantially higher than its 1ogGw,and is clearly at the limit of applicability of the chosen ratio. For VOL. 29, NO. 3 , 1 9 9 5 / ENVIRONMENTAL SCIENCE &TECHNOLOGY
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TABLE 2
Results from Partition Experiments of Mixtures A and B between Water and Empore Disk Material compd
highest nominal concnd(pg/L)
pentachloroethane 1,4-dichlorobenzene hexachloroethane 1,3,5-trichIorobenzene 3,4-dichlorotoluene 1,2,4,5-tetrachlorobenzene 1,2,3,4-tetrachlorobenzene pentachlorobenzene
2000 1000 100 200 400 100 500 30.0
1,2,3-trichlorobenzene 1-chloro-3-nitrobenzene 2,4-dichloroaniline 1,2,3,4-tetrachlorobenzene 1,2-dichloro-4-nitrobenzene 2,4,6-trichloroaniline y-hexachlorocyclohexane methylparathion fenchlorphos dieldrin
396 1574 451 1 220 1512 1599 323 2005 40 1 105
mass balanceC (% (SO)) n = 9
Caq,*JGq,WJb
(Yo(SO)) n = 9
log Kod (SO) n=9
log &we
Mixture A 90 (4) 93 (3) 91 (3) 87 (4) 92 (4) 71 (2) 74 (3) 43 (4)
90 (4) 95 (3) 99 (3) 95 (3) 100 (3) 94 (4) 96 (4) 96 (5)
3.78 4.01 4.72 4.78 4.74 5.29 5.27 5.89
(0.03) (0.04) (0.02) (0.05) (0.05) (0.05) (0.04) (0.05)
3.22' 3.44 4.14' 4.19 3.95s 4.60 4.64 5.18
92 (3) 96 (4) 85 (8) 92 (3) 95 (4) 93 (4) 96 (3) 84 (3) 82 (3) 101 (4)
4.60 (0.02) 3.25 (0.06) 3.37 (0.12) 5.22 (0.02) 3.80 (0.04) 4.00 (0.1 1) 4.58 (0.10) 4.35 (0.10) 6.08 (0.08) 6.11 (0.13)
4.14 2.46' 2.91 4.64 3.12' 3.69 3.68 3.04 5.07 5.40
Mixture B 87 (3) 96 (4) 85 (8) 73 (2) 94 (4) 91 (4) 91 (2) 81 (3) 28 (4) 29 (2)
a Middle and lower concentrations were one-third and one-tenth of highest concentration, respectively. * Percentage of compound remaining in the aqueous phase at time t= -=. Overall mass balancefor the complete experiment. Empore-water partition coefficient. a Data from de Bruijn et a/. (39)except those denoted by for g. 'Experimental values from the MedChem Starlist (373.9 Calculatedvalue according to CLOGP algorithm
(37).
~4000
2e 3000
20
5 2000
i h 0)
u
0
"
2
2
3
4 109
5
6
7
1000 2000 3000
41
GC response - summed (nmol)
Kow
FIGURE 5. Plot of the relationship between the Empore-water partition coefficients (log KO) and the octanol-water partition coefficients ('slow-stirring' method) for the 17 compounds from Mixtures A and 6.
compounds with a higher distribution coefficient, viz., pentachlorobenzene, fenchlorphos, and dieldrin, correspondinglylower final aqueous concentrations or higher decreases, up to a decrease of 72%, were found. Clearly, in order to be able to analyze mixtures containing or expected to contain compounds of similar or even higher distribution coefficients, higher V1W ratios are called for. In order for the 'biomimetic' Empore extraction to be useful in light of the prediction of baseline toxicity CBRs, there should be a good, preferably unity, correspondence between log KO, and log KDof these and other compounds. To show that there is indeed a very good correspondence between these two parameters, they have been plotted against each other in Figure 5. As can be concluded from eq 4, for the chemicals tested, the correlation between these two partition coefficients is 732 1 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 29, NO.
0
Mixture B
3,1995
FIGURE 6. Plot of the correspondence between total molar concentrations as calculated from GCKCD analysis results and measured directly by vapor pressure osmometry.
indeed approximatelyunity, and almost all of the difference between them is in the intercept. If we for the moment assume that, for most compounds that exhibit baseline toxicity, there exists a simple relation linking lipid-based bioconcentration and hydrophobicity (38),being of the form: log BCF = log KO,
(5)
then there would be a relation between lipid-based bioconcentration and Empore-water partition of the form:
log BCF = 1.005 log KD - 0.704
(6)
This relation approximates to a unity-slope equation between log BCF and log &, and can therefore be transformed to this relationship between total Empore concentrations and body residues:
TABLE 3
Results from Osmometric Analysis of Total Molar Concentrations on Empore Disk Lipoid Phase for Mixtures A and B, Including Total Amounts As Calculated from GC/ECD Analyses and Total Amounts As Measured Directly by Vapor Pressure Osmometrp total amount on disk by GC analysis (nmol) highest concn middle concn lowest concn
highest concn middle concn lowest concn
a
total amount on disk by osmometer analysis (nmol)
Mixture A 2530 2376 2159 691 718 732 221 223 226 Mixture B 2928 2928 3010 1050 1020 1028 390 388 404
2320 2100 1980 600 650 620 210 200 210 3350 3390 3470 1160 1190 1250 510 520 NAb
Correlation between total molar concentrations as derived from
GC analyses and measured by vapor pressure osmometry is depicted in Figure 6. Not available.
C, = 0.198CE,,,,,
(7)
Extrapolation of Total Concentrations to Critical Body Residues: Overall Performance of the Procedure. Total concentrations in Empore disk hydrophobic phase as measured with both quantitative GClECD analysis and vapor pressure osmometric analysis (see Table 3 as well as Figure 6 ) agree very well. For mixture B, the osmometric responses are slightly higher than for mixture A. This stems from the fact that mixture A contained two compounds with nonnegligible vapor pressures (viz., penta- and hexachloroethane). The lowest total molar levels measured for mixture A (Samples 8-10 from Table 3) represent direct extraction measurements of k200 nmol of organic contaminant on an amount of Empore CISmaterial of approximately 3 pL. According to eq 7, this corresponds to a lipid-based body residue of approximately 13 mM. This is slightlylower than the acute toxicity CBR of 50 mM reported by McCarty et al. (17).
The detection limit of the current procedure can tentatively be calculated as follows: the detection limit of the vapor pressure osmometer is ca. 0.1 mM. Taking into account a dilution factor of 33 going from Empore disk sliver to cyclohexane solution (as a result of the minimum amount of 100 ,uLsolution needed for the osmometric analysis),this corresponds to an Empore hydrophobic phase concentration of ca. 3.3 mM. This corresponds (eq 7) to a lipid-based body residue of approximately 0.65 mM or 1.3%of the acute toxicity CBR of McCarty et al. ( 1 7). Lower detection limits for simulated body residues can of course be achieved by using larger water samples and, thus, larger Empore hydrophobic phases.
From these approximate calculations it should be clear that surrogate body residues of substantially less than the acute toxicity CBR could, in principle, routinely be detected by this approach. On the other hand, the corresponding level of 0.25 mM, being the baseline toxicity lipid-based HC5 body residue (18, 191, cannot be achieved by the procedure in its current setup. This means that the described surrogate parameter can be employed to signal relevant, subacute levels of total baseline toxicity for contaminant mixtures, but that it cannot (yet) be expected to decide whether total contaminant levels are in a safe zone, i.e., below the acute toxicity HCs level. Sincewe think that there is room for improvement of the overall detection limit, it is foreseen that HC5 levels, or simulated body residues of 0.25 mM or lower, should in principle be detectable with this technique. The procedure as described does have some limitations. One of these is the fact that, due to the lipophilic nature of the compounds of interest, some time is needed to actually reach an equilibrium between the aqueous and lipoid phases-this limitation is of course not unique to this procedure, but is inherent to all procedures that presuppose equilibrium partitioning. Another limitation is that, due to the demand for biomimetic extraction and the ensuing Empore-water volume ratio V/W, the detection limit of the described procedure is not yet satisfactory. There are (at least) two possible ways of alleviatingthis problem, the first being the use of larger water samples. This will allow the use of larger Empore phases and thus higher concentrations of compounds in the final cyclohexane solution to be measured. The second possibility is the application of the described extraction procedure in situ; as long as there is a reasonable stability in the level of pollutants present in a lake or river, a biomimetic equilibrium between water and Empore will be reached eventually. One of the major questions with this approach is whether there will be confounding influences from other constituents of natural waters, such as the dissolved organic carbon (mainly humic and fulvic substances) or particulate organic carbon fractions. Research is currently being performed to illuminate these and other aspects of in situ application of this surrogate parameter procedure. Preliminary results from in situ experiments seem to indicate that no confounding influences from natural DOC fractions are to be expected; these preliminary results have been presented at the ‘Livingwith Water’ conference, August 1994, Amsterdam, and will be published in the proceedings (W. M. G. M. van Loon and J. L. M. Hermens, manuscript in preparation).
Acknowledgments The work described here was financially supported by the Dutch Ministry of Housing, Physical Planning and Environment, Directorate-General for Environmental Protection, under Contract 361344.
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(7) Veith, G. D.; Defoe, D. L.; Bergstedt, B. V. J. Fish. Res. Board Can. 1979, 36, 1040-1048. (8) Mackay, D. Environ. Sci. Technol. 1982, 16, 274-278. (9) Gobas, F. A. P. C.; Shiu, W. Y.; Mackay, D. In QSAR in Environmental Toxicology-II; Kaiser, K. L. E., Ed.; D. Reidel Publishing Company: Dordrecht, The Netherlands, 1987; p p 107-123. (10) van Hoogen, G.; Opperhuizen, A. Environ. Toxicol. Chem. 1988, 7, 213-219. (11) McCarty, L. S. In QSAR in Environmental Toxicology-II; Kaiser, K. L. E., Ed.; D. Reidel Publishing Company: Dordrecht, The Netherlands, 1987; p p 207-220. (12) McCarty, L. S.; Mackay, D.; Smith, A. D.; Ozburn, G. W.; Dixon, D. G. Ecotoxicol. Environ. Sat 1993, 25, 253-270. (13) Veith, G. D.; Broderius, S. J. In QSAR in Environmental ToxicolowIt Kaiser, K. L. E., Ed.; D. Reidel Publishing Company: Dordrecht, The Netherlands, 1987; pp 385-391. (14) Veith, G. D.; Broderius, S. J. Environ. Health Perspect. 1990, 87, 207-21 1. (15) Verhaar, H. J. M.; van Leeuwen, C. J.; Hermens, J. L. M. Chemosphere 1992, 25, 471-491. (16) Kobayashi, K.; Akitake, H.; Manabe, K. Bull. / p n . SOC.Sci. Fish. 1979, 45, 173-175. (17) McCarty, L. S.; Mackay, D.; Smith,A. D.; Ozburn, G. W.; Dixon, D. G. Sci. Total Environ. 1993, 109ll10, 515-525. (18) van Leeuwen, C. J.; van der Zandt, P. T. J.; Aldenberg, T.; Verhaar, H. J. M.; Hermens, J. L. M. Environ. Toxicol. Chem. 1992, 11, 267-282. (19) Verhaar, H. J. M.; van Leeuwen, C. J.; Bol, J,; Hermens, J. L. M. SAR QSAR Environ. Res. 1994, 2, 39-58. (20) Konemann, W. H. Toxicology 1981, 19, 209-221. (21) Veith, G. D.; Call, D. J.; Brooke, L. T. Can./. Fish.Aquat. Sci. 1983, 40, 743-748. (22) Hermens, J. L. M.; Broekhuyzen, E.; Canton, H.; Wegman, R. Aquat. Toxicol. 1985, 6, 209-217. (23) Hermens, J. L. M. In Handbook of environmental chemistry; Hutzinger, O., Ed.; Springer Verlag: Berlin, 1989; Vol. 2E, p p 111- 162. (24) van Leeuwen, C. J.; Adema, D. M. M.; Hermens, J. L. M. Aquat. Toxicol. 1990, 16, 321-334.
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Received for review July 6, 1994. Revised manuscript received November 2, 1994. Accepted November 30, 1994.@
ES9404 151 ~
@Abstractpublished in Advance ACS Abstracts, January 1, 1995.
