Diffusive Gradients in Thin Films Sampler Predicts Stress in Brown

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Environ. Sci. Technol. 2005, 39, 1167-1174

Diffusive Gradients in Thin Films Sampler Predicts Stress in Brown Trout (Salmo trutta L.) Exposed to Aluminum in Acid Fresh Waters O D D V A R R Ø Y S E T , * ,† B J Ø R N O L A V R O S S E L A N D , †,‡ TORSTEIN KRISTENSEN,† FRODE KROGLUND,† ØYVIND AABERG GARMO,§ AND EILIV STEINNES§ Norwegian Institute for Water Research (NIVA), P.O. Box 173, Kjelsaas, 0411 Oslo, Norway, Department of Ecology and Natural Resource Management, Agricultural University of Norway, P.O. Box 5003, N-1432 Aas, Norway, and Department of Chemistry, Norwegian University for Science and Technology (NTNU), 7000 Trondheim, Norway

Increased levels of aluminum ions released from nutrient-poor soils affected by acid rain have been the primary cause of fish deaths in the acidified watersheds of southern Norway. The complex aluminum chemistry in water requires speciation methods to measure the gill-reactive species imposing toxic effects toward fish. Previously, aluminum speciation has mainly followed the fractionation principles outlined by Barnes/Driscoll, and several analogues of these fractionation principles have been used both in situ and in the laboratory. Due to rapid transformation processes, aluminum speciation in water samples may change even during short storage times. Thus, results obtained by laboratory fractionation methods might be misleading for the assessment of potentially toxic aluminum species in the water. Until now, all in situ field fractionation methods have been time and labor consuming. The DGT technique (diffusive gradients in thin films) is a new in situ sampler collecting a fraction of dissolved metal weighted according to the rate of diffusion and dissociation kinetics. In a field experiment with acid surface water we studied the DGT sampler as a new prediction tool for the gill accumulation of aluminum in trout (Salmo trutta L.) and the induced physiological stress responses measured as changes in blood glucose and plasma chloride. Aluminum determined with DGT (DGT-Al) was higher than labile monomeric aluminum (Ali) determined with a laboratory aluminum fractionation procedure (PCVsa pyrocatechol violet analogue of Barnes/Driscoll), a difference due to collection of a fraction of organically complexed aluminum by DGT and a reduction of the Ali fraction during sample storage. DGT-Al predicted the gill uptake and the aluminum-induced physiological stress responses (increased blood glucose and decreased plasma chloride, r2 from 0.6 to 0.9). The results indicate that DGT-Al is a better predictor for the stress response than laboratory-determined * Corresponding author phone: +47 22185100; fax: +47 22185200; e-mail: [email protected]. † NIVA. ‡ Agricultural University of Norway. § NTNU. 10.1021/es049538l CCC: $30.25 Published on Web 01/12/2005

 2005 American Chemical Society

Ali, because the DGT sampler collects a more correct fraction of the gill-reactive aluminum species that induces the stress.

Introduction Although acid deposition in Norway has been reduced during the past decade, many of the most vulnerable water catchments are only slowly recovering and are still subject to episodes of high concentrations of toxic aluminum species during snowmelt and storm flows (1). Positively charged aluminum species will bind to negatively charged fish gill epithelia, and become lethal at high concentrations or impose sublethal stress reactions at lower levels. A reduced gill function affects oxygen uptake and osmoregulation (reduction in plasma ions) as well as a series of other stress reactions, e.g., an adrenaline-induced increased plasma glucose (2, 3). Until now, only labor- and time-consuming in situ fractionation techniques (hollow fiber separation and/or Barnes/ Driscoll) have enabled establishment of dose-response relations linking an aqueous fraction of aluminum to accumulation on gills and physiological effects (4). We have faced difficulties in establishing predictors linking traditionally laboratory determined labile Al to fish effects, especially at sublethal exposure. An even more difficult situation exists if the fish are exposed to a situation of increased pH and unstable aluminum chemistry (a mixing zone) where monomeric aluminum forms polymers, and becomes more toxic in the early process of polymerization (5, 6). We have focused on finding tools for identification of suitable habitats for fish during the early phase of recovery from acidification. A necessary criterion for such a tool is the ability to determine bioavailable aluminum. Conventional aluminum fractionation methods based on the principles outlined by Barnes/Driscoll (7-10) separate aluminum in water into three operationally determined fractions, colloids/particles (Alc), organically complexed aluminum (Alo), and labile inorganic monomeric aluminum (Ali), as outlined in Figure 1. The labile inorganic monomeric aluminum fraction (Ali ) Ala - Alo) is the difference between the fractions obtained before and after a cation exchange separation and contains the cationic inorganic species of aluminum (Al3+, Al(OH)n(3-n)+, Al(F)n(3-n)+, and Al(SO4)+ ions/ complexes). This group of inorganic cationic aluminum species has high affinity for fish gills and has been recognized as the most toxic toward fish in acid water. Lack of equilibrium because of slow time-dependent processes and/or the presence of metastable compounds may, however, cause a change in the concentration of these species between the times of sampling and fractionation in the laboratory. The assessment of the toxic potential in the field (4-6) based on laboratory analysis may thus be severely precluded by the time lag between sampling and analysis. This has encouraged investigation of samplers with the potential of in situ collection of the bioavailable form of aluminum during critical time periods (hours, days, weeks, months) of increased sensitivity for fish (spawning, hatching, start feeding, smoltification, etc.). We considered the DGT sampler (DGT ) diffusive gradients in thin films) useful for this purpose because of its in situ speciation capabilities, and because the time-averaged integration of the concentration can be used for assessing the dose (11-14). DGT sampling relies on the establishment of a steady concentration gradient through a defined diffusive layer, one face of which is in contact with the solution containing the VOL. 39, NO. 4, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Overview of the Barnes/Driscoll fractionation procedure for aluminum in water compared to the fractionation procedure of the DGT sampler and the expected toxicity toward fish gills of the different aqueous fractions obtained. metals and the other one in contact with a metal-accumulating gel containing a Chelex-100 resin. For metal ions complexed by natural organic matter (NOM) to be accumulated, they must dissociate during their transport through the diffusive layer, where the concentration of free metal ions is lower than in the bulk solution. Therefore, only complexes that can dissociate on a time scale of minutes are measured, and they will be weighted according to the rate of diffusion through the diffusive layer comprised by the relatively open-sized hydrogel, the membrane filter, and the diffusive boundary layer (15-17). In this paper the aluminum species collected by DGT will be referred to as DGT-Al. They include inorganic monomeric aluminum species and a fraction of the organically bound metal weighted according to the rate of dissociation and diffusion. The accumulated mass of metal, M, is measured after deployment for a known time, t, and eq 1 is used to calculate the concentration, C, in the water (D is the diffusion coefficient, A is the area, and ∆g is the thickness of the diffusion layer):

C ) M∆g/(DtA)

(1)

The potential of the DGT sampler as a predictor for biological uptake or response of metals in water has been recognized by many, but until now only a few applications in soil (18-21) and water (22, 23) have been published. We expected that DGT-Al could predict the concentration of gillreactive aluminum for brown trout similarly to the way that DGT-Cu has been shown to predict gill-reactive copper for rainbow trout (22). The DGT sampler performed well for inorganic aluminum in laboratory tests (14). In 2001 we performed a field study to reexamine chemical threshold parameters for reestablishment of brown trout in acidified water catchments. In the field experiment described in this paper we compared the conventional laboratory fractionation method for Ali and the DGT sampler as predictors of effects on brown trout exposed to acid aluminum-containing waters. Here we report our new findings, which represent the first time the DGT sampler has been used in investigations of the effects on trout caused by bioavailable/toxic species of aluminum in acid water.

Materials and Methods Field Experiment and Water Treatment. The field study was performed during October 2001 in the upper part of River Tovdal at the river inlet in Lake Tveitvatn, southern Norway. This site has been an important area for studies of the effects of acid rain on water quality and fish since 1975 (24, 25). NIVA’s rig for experimental testing of water treatment procedures was applied. In this experiment the rig contained four parallel lines consisting of three consecutive 70 L tanks 1168

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FIGURE 2. Schematic drawing of one tank line for water treatment and exposure of fish. connected with tubes (Figure 2). River water was pumped to a distribution tank and directed by means of gravity to the four tank lines. At the inflow to the first tanks, the water chemistry in three lines was manipulated. Ca(OH)2 solutions were added to two of the four tank lines, which raised the pH from 5.2 ( 0.2 to 5.4 ( 0.3 (low Ca) and 5.9 ( 0.3 (high Ca). A HCl/AlCl3 solution which lowered the pH to 4.8 ( 0.2 and increased the total concentration of aluminum to about 30 µg/L was added to another tank line (Al/H+). The last tank line was left untreated (reference water). On the basis of water flow and water volume in the tanks, the average residence time of the water in each tank was estimated to be 15 min. This experimental setup with three tanks was chosen to detect possible “mixing zone effects”, i.e., changes in speciation and toxicity of aluminum with increasing age of water after treatment (4-6). Sampling and Analysis of Water. Water flow and pH were measured in the field every day. On days 1, 3, 7, and 14 river water from the inlet of the test rig and waters from the outflow of each of the third tanks in the four lines of the test rig were sampled in polyethylene bottles and sent to NIVA’s laboratory in Oslo. The chemical analysis program comprised pH, conductivity, alkalinity, major anions and cations (Na, K Ca, Mg, Cl, and SO4 by ion chromatography), and total organic carbon (TOC by automated persulfate/UV digestion and IR spectrometry). Fractionation of aluminum followed the principles outlined by Barnes/Driscoll (7, 8), but automated for laboratory use by colorimetry using pyrocatechol violet (PCV) and a Skalar air segmented continuous flow analyzer (9). On the basis of three separate measurements comprising total, reactive, and nonlabile aluminum, three fractions were obtained as explained in Figure 1 (note that the fractionation nomenclature used by NIVA in ref 9 is slightly different from that of Driscoll’s original work (8), but the chemical inter-

pretation of the fractions is the same). The precision of the Ali measurements depends on the concentration level, but is usually not worse than 5 µg/L in the concentration range 10-50 µg/L. The quality of the chemical analysis was controlled by a laboratory QA/QC program according to ISO/EN 17025, accredited by the Norwegian Accreditation Authority. The DGT equipment, consisting of 0.8 mm open pore polyacrylamide diffusive gels (cross-linked with an agarose derivative patented by DGT Research Ltd.), 0.4 mm Chelex gels, and solution deployment units of the standard type with a 20 mm window diameter, was purchased from DGT Research, Lancaster, U.K. The DGT samplers were assembled by placing the Chelex gel on the piston base and overlaying it with a diffusive gel followed by a 0.45 µm polysulfone filter and the protective plastic moulding. The DGT samplers were attached to the bottom at the center of each tank, ensuring that the filter side of the sampler faced toward the solution. A total of 3 DGT samplers were deployed in each of the 12 tanks for three different exposure periods: one during the first week (days 0-7), one during the second week (days 7-14), and one during the entire period (days 0-14). After deployment the DGT samplers were rinsed with MilliQ water, placed separately in small plastic containers, and transported to the laboratory where accumulated metals were eluted and determined with inductively coupled plasma mass spectrometry (ICPMS) as previously described (14). To estimate the sampling precision of DGT-Al, we calculated the relative standard deviations for the three DGT samplers that were deployed during the same period in the four tank lines (i.e., 12 sets of 3 each), and found them to be 0-20%, with an average of 12%. Sampling and Analysis of Trout Gills and Blood. Brown trout of the Bygland strain were delivered from the Syrtveit Hatchery, Bygland, Norway. The trout had a length of 19.8 ( 2.8 cm, and at the start of the experiment (day 0, Figure 3), the gill aluminum concentration was low (4.9 ( 2.7 µg of Al/g dw) and concentrations of blood glucose (3.6 ( 0.6 mM) and plasma chloride (138 ( 4 mM) were normal. These levels are taken to represent the starting points (Figure 2). Deviations from these levels are interpreted to indicate an effect of external stressors. At the start of the experiment 25 trout were transferred to each of the 12 tanks. On days 1, 3, 7, and 14 of the experiment a minimum of five trout from each tank were anesthetized with clove oil (immersion in 10 L of water with 0.8 mL of a 10% ethanolic solution of clove oil added). An exception was the fish in the second tanks in each line which were killed on days 7 and 14 with no prior anesthetization. Blood samples from anesthetized and newly killed fish were drawn from the caudal blood vessels into 1 mL heparinized syringes. Whole blood samples were injected into an I-stat cartridge (Abbot, I-stat PCA blood analyzer with a CG8-sensor) for determination of blood glucose and plasma chloride. Gill samples were cut from the second gill arch on the right side, transferred to acid-cleaned preweighed plastic vials, and frozen. At the laboratory the vials were reweighed, the gills were digested in a mixture of nitric acid/ hydrogen peroxide (1.0 plus 0.5 mL) at 100 °C for 30 min, and the resulting solution was diluted to 10 mL with demineralized (MilliQ) water. Aluminum (and other metals) was determined by ICPMS using accredited methods as above. Statistical Analysis of the Data. On days 7 and 14, five fish from the second tank in each line were killed with a blow to the head. When examining the gill data, we found that these fish had systematically higher concentrations of gill aluminum than the fish that were anesthetized. Data from tank 2 were therefore excluded from the gill data analysis. When the data for the physiological response (glucose and chloride concentration) were examined, no such differences within the lines were observed, and we decided to include

the data from all three tanks in each line in the statistical analysis. To reduce the effect of biological variation, data from at least five separate fish were used to calculate averages of gill aluminum concentration and physiological stress response. This is in agreement with earlier practice (4-6), and the data averaged in this way were used in the statistical analysis. The statistical analysis was performed using the linear regression functions of Microsoft Excel. To get an overview of dose-response relationships, we chose to perform linear regression analysis between aluminum determined with, respectively, DGT and Barnes/Driscoll fractionations (Ali) and the fish responses. DGT samplers were deployed for different periods (days 0-7, days 7-14, and days 0-14), and these time-averaged DGT-Al concentrations were compared to concentrations of gill aluminum, plasma chloride, and blood glucose at days 7 and 14. The Ali data from days 7 and 14 were compared to the same fish response data. The results for the linear regression analysis are shown in Table 2. The dose-response relationships are shown in Figures 6-9. For DGT we chose to display the relation for the days 0-14 integration period and present the rest as regression statistics (Table 2). Chemical Equilibrium Calculations of Aluminum. The chemical equilibrium model Visual MINTEQ version 2.30 (available at http://www.lwr.kth.se/English/OurSoftware/ vminteq/) was used to calculate the concentration of inorganic monomeric species of aluminum (Al3+, Al(OH)n(3-n)+, Al(F)n(3-n)+, Al(SO4)+) in equilibrium with a solid Al(OH)3 phase. Visual MINTEQ’s default database of thermodynamic stability constants was used. The most critical parameter to select was the equilibrium constant for the solid Al(OH)3 phase, as reported values in the literature vary over a range of at least 3 orders of magnitude from crystalline gibbsite to amorphous Al(OH)3 (10). We selected the constant recommended for soil gibbsite (log K ) 8.29 at 25 °C (for Al3+ + OH- a Al(OH)3) (27). The composition of major ions in the water from River Tovdal as determined during the test period (Table 1) was selected as the input parameter, and simulations were performed at temperatures of 8 and 15 °C. We lacked data for fluoride, but used a value of 50 µg of F/L, which is a typical value for surface waters in this area of Norway (26). The calculated results were used to draw the solubility curves as the sum of concentrations of the inorganic monomeric aluminum species in equilibrium with the Al(OH)3 phase, as shown in Figure 5. The solubility curve for aluminum depends on the stability constant of the solid phase and on temperature. We consider the curves shown in Figure 5 to be appropriate for examination of the pH-dependent patterns observed in this work.

Results and Discussion Time Development of Water Chemical Parameters, Gill Aluminum Concentrations, and Stress Responses. Averages and standard deviations of important water quality parameters determined in the outlet waters from the third tank in each line are presented in Table 1. The water quality of the inlet water from the River Tovdal was similar to that of the reference water and varied somewhat during the experimental period of 14 days. This introduced some variation in the water chemistry of the tanks containing the fish. DGT-Al was 5-10 µg/L higher during the second week (days 7-14) in most of the tanks as pH in the inlet water decreased to a minimum of 4.9 on day 12 of the experiment. Figure 3 shows the time developments of gill aluminum, blood glucose, and plasma chloride. The concentration of gill aluminum increased during the first 3 days of exposure, but between days 7 and 14 the changes were small (Figure 3) even though the water quality declined somewhat during the second week. The physiological stress responses, blood glucose and plasma chloride, changed strongly especially VOL. 39, NO. 4, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Summary of Important Quality Parameters in the Water from the Test Rig at River Tovdal during the 2 Week Test Perioda water treatment

avg

pH SD

alkalinity, mmol/L avg SD

Ca, mg/L avg SD

total Al, µg/L avg SD

Alc, µg/L avg SD

Alo, µg/L avg SD

Ali, µg/L avg SD

Al/H+ reference low Ca high Ca

4.8 5.2 5.4 5.9

0.2 0.2 0.3 0.3

0.023 0.035 0.037 0.054

0.61 0.61 0.65 1.01

225 193 186 196

75 85 86 111

84 82 82 86

63 29 24 7

0.005 0.002 0.005 0.011

0.11 0.11 0.13 0.20

45 26 33 34

38 14 16 22

20 15 17 18

11 5 10 10

a The average (avg) and the standard deviation (SD) are based on 10 separate daily samples taken from the third tank in each of the four treatment lines (see the Materials and Methods section for details). Additional water chemistry data of the inlet water: conductivity, 1.2(0.1) mS/m; TOC, 3.7(0.6) mg of C/L; temperature, 8(2) °C. These parameters were in the same range in all four water treatment lines.

FIGURE 4. Comparison of in-situ determined DGT-Al and laboratorydetermined Ali. Separate Ali values within each exposure period of the DGT are averaged and compared to the DGT value for the same exposure period. For DGT-Al data for each of the three separate tanks in each line are displayed against one measurement of Ali (tank 3 only).

FIGURE 3. Average concentrations of aluminum accumulated on gills, plasma chloride, and blood glucose. Each data point represents the average for the 15 fish that were sampled from all three tanks on each day (for gill aluminum the fish from the second tank sampled on days 7 and 14 are excluded). The four water treatments (Table 1) are represented by the following symbols: reference water (open circles), high Ca (filled circles), low Ca (filled triangles), and Al/H+ (open triangles). during the first 3 days, but between days 7 and 14 the changes were smaller in the case of chloride and insignificant in the case of glucose (Figure 3). When exposed to the less than optimal water qualities applied in this experiment, the fish experienced an initial shock phase. After 7 days the level of stress had stabilized and the fish appeared to be able to compensate for a certain decline in water quality, but they did not recover completely even in the high Ca water. We consider the fish parameters (gill aluminum, plasma chloride, and blood glucose) determined on days 7 and 14 to be relatively stable and choose to focus on these results for 1170

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comparisons with the aluminum determined as DGT-Al and Ali. DGT-Al Compared to Laboratory-Determined Ali. No systematic change in the concentration of DGT-Al was observed among the three tanks in the same tank lines (i.e., during the time scale of 45 min). Therefore, we considered the DGT measurements in each tank line to be equal and used DGT-Al determined in all three tanks for comparison with Ali (determined in tank 3 only). Figure 4 shows how DGT-Al compares with laboratorydetermined Ali. The linear regression equation of this plot is described by Ali ) -26(4.9) + 1.16(0.10)(DGT-Al) (r2 ) 0.88, n ) 35, P < 0.001, standard errors in parentheses), and shows that at low concentrations (Ali of 10-40 µg/L) the laboratory Ali values are generally 20-30 µg/L lower than those of DGT-Al, whereas the difference is smaller at the highest concentrations (Ali of 60-80 µg/L). This difference may be caused by two mechanisms. The formation of aluminum hydroxides (Al(OH)3 colloids/dissolved polymeric species) during sample storage is important, and is expected to be most predominant in the samples from the water with the highest pH (high Ca). This is supported by the fact that the Alc fraction (particles/colloids) increased from 80 to 90 to about 110 in the high Ca treatment line when the pH shifted from 5.2 to 5.9 (Table 1). No change in concentration of DGT-Al was observed among the three different tanks (with a total retention time of approximately 45 min), implying that the reduction from approximately 50 µg/L DGT-Al in the untreated water to 30 µg/L in the high Ca water must have been rapid. The results for DGT-Al do not exclude that a transformation process, occurring too slow to be detected by the DGT samplers, still could have proceeded after the initial rapid decrease and resulted in low Ali measurements. In a laboratory experiment other

FIGURE 5. DGT-Al (open circles) and Ali (filled circles) plotted against pH. The curves for the sum of dissolved inorganic species of aluminum in equilibrium with Al(OH)3 are shown at two temperatures (upper, 8 °C; lower, 15 °C). The DGT-Al (days 0-7, 7-14, and 0-14) and Ali are all determined in water from the third tank of each line. workers (28) observed an almost instantaneous formation of an amorphous Al(OH)3 phase followed by a much slower (half-times on the order of days) reduction in the concentration of dissolved aluminum species. Precipitation of solid Al(OH)3 is thus a combination of rapid and slow transformations. As the laboratory fractionation (Alr and Alo) must be performed on untreated samples, there is no simple way to avoid such an effect, except analyzing the samples as quickly as possible. Because the samples have to be shipped from field stations to the laboratory, storage times shorter than 2 days are difficult to achieve. A second consideration is the fact that the DGT sampler has been reported to collect a small fraction of metal bound to dissolved NOM (29). While the Ali fraction determined by the PCV method is expected to include mainly inorganic monomeric species of aluminum, the DGT may collect some of the organically complexed aluminum species at a rate determined by the diffusion and dissociation characteristics of the species. This effect depends on the molecular size distributions and aluminum binding properties of the NOM, the magnitude of which is difficult to describe and estimate precisely. Investigations of the speciation of copper, nickel, and zinc in natural waters containing approximately 15 mg/L dissolved organic carbon have indicated that DGT samplers, with the same open pore diffusive gel as applied in this study, collected 15-30% of the organically complexed fraction (30, 31). Downard et al. (32) found that in solutions containing aluminum and fulvic acid the DGT-Al was equal to the sum of the “labile” and “moderately labile” aluminum fractions. To examine this in more detail, we subtracted the Ali from DGT-Al (averages of Ali on days 7-14, compared to DGT-Al on days 7-14) and compared this to the Alo fraction for the same samples. The ratios for this Ali-subtracted DGT-Al value to Alo were from 15% to 25%. This indicates that the proportion of the Alo fraction (80-90 µg/L, Table 1) that can be collected by the DGT is in the range 10-20 µg/L. To examine the effect of precipitation of aluminum hydroxides, the concentrations of Ali and DGT-Al are presented as a function of pH in Figure 5. The solid lines represent the concentration of dissolved aluminum species for the inlet River Tovdal water in equilibrium with a solid Al(OH)3 phase (pK ) 8.3 at 25 °C) at temperatures of 8 (upper) and 15 (lower) °C. At pH above 5.5 the concentration of Ali appears to be controlled by solid Al(OH)3 with solubility as the chosen model Al(OH)3 phase. The concen-

FIGURE 6. Gill aluminum of brown trout after exposure to different water qualities, compared to in-situ determined DGT-Al. Each data point represents DGT-Al (14 days) and the average gill Al determined for five gills collected on day 7 or 14. Key: reference water (open circles), high Ca (filled circles), low Ca (filled triangles), and Al/H+ (open triangles). tration of DGT-Al however is well above the equilibrium concentration of the model Al(OH)3, suggesting that a more soluble phase controls the concentration. This observation can be explained by transition from a more soluble to a less soluble solid Al(OH)3 phase during the storage of the water samples. A relatively small increase of temperature in the water samples can increase the rate of such a transition. At pH below 5.5 the concentrations of Ali and DGT-Al are below saturation and appear to be controlled by other processes. The differences discussed above may thus be caused by two effects: DGT may collect a fraction of the organically complexed aluminum ions in the range 10-30% of the total Alo fraction. Precipitation of aluminum hydroxides may occur during storage especially in the samples where the pH is elevated above 5.5, causing a further decrease in the Ali/DGT-Al ratio. Gill Aluminum Compared to DGT-Al. The results in Figure 6 show the concentration of gill aluminum (days 7 and 14) as a function of DGT-Al (days 0-14). The statistics for this plot and the corresponding regressions for DGT-Al (days 0-7 and 7-14) (Table 2) show that all slopes of the response functions are in the same range (1.4-1.7) for all four ways of expressing the relation between gill Al and DGT-Al. The intercepts (14-55) are highest for gill aluminum (day 7) as a function of DGT-Al (days 0-7), while they are closer to zero (14, 16) for DGT-Al (days 0-14 or 7-14); i.e., the predictions at zero DGT-Al are closer to gill Al of the fish before exposure (4.9 ( 2.7 µg of Al/g dw). The correlation coefficients are in the range 0.57-0.73 and are lower than those obtained for DGT-Al compared to blood glucose/ plasma chloride, but in the same range as observed previously when gill accumulation was compared with classical in situ aluminum fractionation methods (4). The scatter in Figure 6 is relatively large, partly due to the slight difference between the concentration of gill aluminum on days 7 and 14 (Figure 3). The concentration of gill aluminum is a balance between accumulation and depuration and is sensitive to changes in water chemistry (see for instance the time development during the first 3 days in Figure 3). The DGT sampler provides a time-averaged concentration for the whole deployment period (7-14 days in this study) and will not be as sensitive as gill aluminum to changes in the composition of the water during the last days of deployment. Stress Responses Compared to Gill Aluminum. For the same gill data, Figure 7 shows correlations among the concentrations of gill aluminum, blood glucose, and plasma chloride. In this experiment, aluminum is the main toxicant VOL. 39, NO. 4, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 2. Summary of Regression Statistics of the Fish Response Data Compared to DGT-Al and Ali Measurement in Watera

gill Al (days 7 and 14) gill Al (day 14) gill Al (day 7) gill Al (day 14) gill Al (days 7 and 14) plasma chloride (days 7 and 14) blood glucose (days 7 and 14) plasma chloride (days 7 and 14) plasma chloride (day 14) plasma chloride (day 7) plasma chloride (day 14) plasma chloride (days 7 and 14) blood glucose (days 7 and 14) blood glucose (day 14) blood glucose (day 7) blood glucose (day 14) blood glucose (days 7 and 14) a

as a function of

intercept

std err

slope

std err

r2

n

Pb

Figurec

DGT-Al (days 0-14) DGT-Al (days 0-14) DGT-Al (days 0-7) DGT-Al (days 7-14) Ali (days 7 and 14) gill Al (days 7 and 14) gill Al (days 7 and 14) DGT-Al (days 0-14) DGT-Al (days 0-14) DGT-Al (days 0-7) DGT-Al (days 7-14) Ali (days 7 and 14) DGT-Al (days 0-14) DGT-Al (days 0-14) DGT-Al (days 0-7) DGT-Al (days 7-14) Ali (days 7 and 14)

38 16 55 14 63 148 -2.3 142 141 147 138 124 1.7 3.0 -2.9 3.8 11.8

18 23 25 22 15 6 4.1 4 6 5 8 5.1 2.7 4.5 4.1 5.1 1.1

1.6 1.7 1.5 1.4 1.4 -0.36 0.25 -0.74 -0.67 -0.93 -0.47 -0.54 0.53 0.51 0.62 0.39 0.44

0.4 0.5 0.5 0.3 0.4 0.05 0.04 0.08 0.13 0.11 0.13 0.14 0.06 0.09 0.09 0.08 0.03

0.57 0.69 0.61 0.73 0.66 0.79 0.77 0.78 0.74 0.90 0.58 0.71 0.80 0.75 0.85 0.68 0.97

16 8 7 8 8 16 16 24 12 11 12 8 24 12 11 12 8

*** * * * * *** *** *** *** *** ** ** *** *** *** *** ***

5

For DGT-Al all three different averaging periods are used. c Refers to the figure where the relation is shown.

b

and the site of action is located in the gill (3). Thus, high correlations between gill aluminum and physiologic stress factors are expected. The data have been fitted with a linear regression curve, but linearity is not expected to apply at lower concentrations of gill aluminum since a no-effect level somewhere below 50 µg of Al/g dw (high Ca) can be inferred. The intercepts of the regression curves are therefore, respectively, above (148 mM) and below (-2.3) the concentrations of plasma chloride and blood glucose in unexposed trout. Stress Responses Compared to DGT-Al. In Figure 8, the concentrations of plasma chloride and blood glucose are plotted as a function of the concentration of DGT-Al (days 0-14). The regression statistics for this plot and for DGT-Al (days 0-7) and DGT-Al (days 7-14) in Table 2 show that the correlations are highly significant and much of the variation in the stress parameters is explained by the concentration of DGT-Al. A common feature of all the regressions of plasma chloride concentration versus DGT-Al is that the intercepts are equal to or above the concentration in unexposed trout (138 ( 4 mM). In the corresponding regressions for blood glucose the intercepts are equal to or below the concentration in unexposed trout (3.6 ( 0.6 mM). As explained in the previous section this is what one would expect for a linear fit to a portion of a dose-response curve. The slopes of the regression curves vary due to the circumstances described in the first subsection of this section. 9

8 7

8

Probability of regression: *, 0.05 > P > 0.005; **, 0.005 > P > 0.001; ***, P < 0.001.

FIGURE 7. Blood glucose (lower curve) and plasma chloride (upper curve) of brown trout compared to accumulated gill Al. Each data point represents averages for five fish sampled at day 7 or 14. Symbols for water treatments are as in Figure 6.

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FIGURE 8. Blood glucose (lower curve) and plasma chloride (upper curve) of brown trout compared to in-situ determined DGT-Al. Each data point represents DGT-Al (14 days) and the averages determined for five fish sampled on day 7 or 14. Symbols for water treatments are as in Figure 6. Stress Responses Compared to Ali. In Figure 9, the concentrations of plasma chloride and blood glucose are plotted as a function of laboratory-determined Ali on days 7 and 14 of the experiment. The corresponding regression statistics are displayed in Table 2. The physiological stress responses are equally well correlated to the concentration of Ali as they are to gill aluminum and DGT-Al. The response curves achieved for laboratory-determined Ali are, however, different from those achieved with DGT, because the measured concentration of Ali is lower than that of DGT-Al, particularly with respect to the high Ca water. Here the measured concentration of DGT-Al (days 0-14) is 29 µg/L in all three tanks, while the measured concentrations of Ali in the third tank are between 4 and 7 µg/L. The two most probable reasons for this difference are discussed above. The intercepts of the concentration of glucose (12 ( 1 mM) and chloride (124 ( 5 mM) as a function of the concentration of Ali in water are above or below, respectively, the corresponding concentrations in unexposed fish. If we compare the intercept of blood glucose of 12 mM for Ali with the response curve for DGT-Al in Figure 8, a response of 12 mM corresponds to 20-30 µg of DGT-Al/L. In the high Ca water the concentrations of blood glucose (13 ( 2 mM) and chloride (120 ( 3 mM) are significantly different from the corresponding values in unexposed fish (4 and 138 mM, respec-

FIGURE 9. Blood glucose (lower curve) and plasma chloride (upper curve) of brown trout compared to laboratory-determined Ali. Each data point represents the Ali determined in the water sampled on days 7 and 14 and average plasma glucose and chloride for five fish sampled on the same days. Symbols for water treatments are as in Figure 6. tively). The average pH in the high Ca water is 5.9, but the H+ concentration in itself is not large enough to cause this level of stress (33). The elevated concentrations of gill aluminum around 50 µg of Al/g dw (Figure 2) in the high Ca line suggest that aluminum is the main stressor. We do not know the shape of the dose-response curves as the concentration of aluminum approaches the unknown no-effect level, but it seems clear that the laboratory-determined Ali underestimates the concentration of toxic aluminum in the water. Since this is partly a storage effect, we may expect this to be especially predominant in water treated with lime to raise the pH. Some of the transformations are slow, but the concentration of Ali may still decrease during storage, and laboratory fractionation methods will suffer from this problem. General Appraisal. In this field study of toxicity of aluminum toward trout, two methods for determining bioavailable/gill-reactive aluminum in water have been compared: the DGT sampler (DGT-Al, integrated values) and a laboratory version of the Barnes/Driscoll fractionation procedure (Ali, grab samples). Three methods for assessing the fish response, determination of gill aluminum, decreased plasma chloride, and increased blood glucose, have been compared to Ali determined in grab samples and time-averaged values of DGT-Al using deployment times of 7 and 14 days. Both the intercepts and slopes of the response as a function of DGT-Al and Ali in Table 2 have high consistency, especially when the result obtained for the response on day 14 is compared. At day 7 the slopes and intercepts are in the most extreme direction, probably because the initial changes during the first 3 days are large and it takes some time for the trout responses to equilibrate with the water quality. The correlation coefficients are high both at day 7 and at day 14, and the correlations are significant at P < 0.05 for gill aluminum, and even higher (mostly P < 0.001) for the plasma chloride and blood glucose. The time-integrating property of the DGT sampler is useful because the time-averaged concentration can be used for assessing dose despite variable concentrations in the field. Both the primary gill deposition and the induced physiological stress response parameters are slow reactions with lag times from hours to several days to reach a stable level. Although more experimental data are needed to verify the response functions achieved during this work, the reasonably high consistency of the statistical data in Table 2 shows that the time-integrating DGT sampler may be very useful in future research.

The degree of stress that is measured in the trout depends on the water quality during a period of time, preceding sampling. Time-integrated DGT-Al values and grab sampling of Ali and/or gill Al compliment each other in recording the temporal variation in water quality. The accumulated amount of aluminum on gills is a result of aluminum deposition and depuration, and both processes respond to changes in water quality. Thus, at sublethal conditions, fish gill can lose accumulated aluminum if the concentration of gill-reactive aluminum in the surrounding water decreases (4, 34). The accumulation of aluminum on gills is thus a dynamic process, where fluctuations in water concentration and active removal through mucus sloughing may alter the concentrations. As there is a time lag between water/gill interactions both during increased and decreased amounts of gill Al accumulation, grab sampling of gills can underestimate or overestimate the potential toxicity of a site. The time-integrated DGT-Al might therefore predict stress responses better than grab samples of aluminum accumulated on gills and/or in water (Ali), which have been used earlier in assessments of effects. We have observed significant differences between laboratory-determined Ali and DGT-Al that are partly due to storage effects (aluminum hydroxide precipitation) and to the fact that DGT measures a small fraction of organically bound aluminum in water. The storage effect may be minimized by performing Barnes/Driscoll aluminum fractionation directly in the field using short fractionation times of a few minutes. To get data with such representative averages as a DGT integral, however, this strategy requires at least daily sampling and analyses over several days. This is laborious and time-consuming and requires a small field laboratory, which will be more expensive than using DGT. The small fraction of organically bound aluminum collected by the DGT sampler is comprised by the smallest and most rapidly dissociating organic complexes, some of which may also be gill-reactive, and impose stress responses similar to those of inorganic monomeric ions in the Ali fraction. Analysis of waters containing high concentrations of NOM and aluminum are required to investigate if DGT-Al or Ali provides the best estimate of the gill-reactive fraction. The DGT sampler accumulates gill-reactive aluminum species directly. Previously, this fraction could only be estimated by subtraction of Alo from the Ala fraction. As Ali is a difference between measurements, the propagation of error will increase the uncertaintysparticularly if the concentrations of both Ala and Alo are high. The comparisons between DGT-Al and Ali show that the differences are largest when the water has been limed to increase the pH as the inorganic monomeric aluminum ions are transferred to aluminum hydroxides/polymeric species of lower toxicity. Such samples are unstable, with great changes in the distributions of aluminum species during a relatively short period of time (from minutes to hours/days). This is an area where the in-situ-determined DGT-Al probably has the greatest potential compared to Ali. Future Applications of DGT. The time-integrating property of the DGT reduces the number of samples required to get sliding averages. DGT-based water quality parameters may give better predictions not only for the death risk but also in fine-tuning of parameters for growth and vitality of fish and other aquatic organisms affected by aluminum. This is important especially during the most sensitive life history stages, which for salmonids will be fertilization, hatching, start feeding, and smoltification of anadromous species (2, 6). The DGT is a simple tool to assess the survival potential for fish in a water catchment without fish present, and we may omit killing fish to collect gills or determine blood glucose/plasma chloride as effect predictors. For aquaculture, a reliable, low-cost documentation of water quality, and thereby a documentation of animal welfare in the production, VOL. 39, NO. 4, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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is of commercial value. In designing mitigation in acid watersheds or aquaculture facilities (by lime, silicate lye, or seawater additions), DGT can monitor the lime addition necessary to reduce the toxic aluminum species below critical levels, and also to define a secure time to stop the mitigation activity, an option which is of great economic value in connection with liming of acid lakes and rivers (35).

Acknowledgments The Reseach Council of Norway (RCN) supported this work through three projects: O.R., RCN-MU-PROFO 140375/720 “Passive sampling of metals ions in water using DGTs”; B.O.R., RCN-MU-PROFO 140379/720 “ANC-RECOVERYs what is the chemical threshold limit for natural reproduction of trout in areas under decreased acidification”; the work of Ø.A.G. was supported by a Ph.D. fellowship at NTNU, RCN-NT “DGTsa new assessment tool for toxic metals in Norwegian aquaculture”. NIVA supported the DGT and ANC-RECOVERY projects from strategic institutional funding with 25% of the total costs.

Literature Cited (1) Skjelkvale B. L.; Stoddard, J. L.; Andersen T. Trends in surface water acidification in Europe and North America (1989-1998). Water Air Soil Pollut. 2001, 130 (1-4), 787-792. (2) Rosseland B. O.; Staurnes, H.; Kroglund, F.; Hindar K.; Kvellestad, A. Tolerance to acid water among strains and life stages of Atlantic salmon (Salmo salar L). Water Air Soil Pollut. 2001, 130 (1-4), 899-904. (3) Gensemer, R. W.; Playle, R. C. The bioavailability and toxicity of aluminum in aquatic environments. Crit. Rev. Environ. Sci. Technol. 1999, 29 (4), 315-450. (4) Kroglund, F.; Teien, H. C.; Rosseland, B. O.; Salbu, B. Time and pH dependent detoxification of aluminum mixing zones between acid and non-acid rivers. Water Air Soil Pollut. 2001, 130 (1-4), 905-910. (5) Rosseland, B. O.; Blakar, I. A.; Bulger, A.; Kroglund, F.; Kvellestad, A.; Lydersen, E.; Oughton, D. H.; Salbu, B.; Staurnes, M.; Vogt, R. The mixing zone between limed and acidic river waterss complex aluminum chemistry and extreme toxicity for salmons. Environ. Pollut. 1992, 78 (1-3), 3-8. (6) Poleo, A. B. S.; Lydersen, E.; Rosseland B. O.; Kroglund, F.; Salbu, B.; Vogt, R. D.; Kvellestad, A. Increased mortality of fish due to changing Al-chemistry of mixing zones between limed streems and acidic tributaries. Water Air Soil Pollut. 1994, 75 (3-4), 339-351. (7) Barnes, R. A. The determination of specific forms of aluminum in near neutral waters. Chem. Geol. 1975, 15, 177-191. (8) Driscoll, C. T. A procedure for the fractionation of aqueous aluminum in dilute acidic waters. Int. J. Environ. Anal. Chem. 1984, 16 (4), 267-283. (9) Henriksen, A.; Roegeberg, E. J. S. An automated method for the fractionation and determination of aluminum species in water. Vatten 1985, 41, 223-226. (10) Røyset, O. Flow injection analysis for the determination of aluminum in water from forest soils. Ph.D. Thesis, Norwegian Forest Research Institute, Agricultural University of Norway, Aas, Norway, 1992. (11) Davison, W.; Zhang, H. In situ speciation measurements of trace components in natural waters using thin film gels. Nature 1994, 367, 546-548. (12) Zhang, H.; Davison, W. Performance characteristics of the technique diffusive gradients in thin films (DGT) for measurement of trace metals in aqueous solutions. Anal. Chem. 1995, 67, 3391-4000. (13) Davison, W.; Fones, G.; Harper, M.; Teasdale, P.; Zhang, H. Dialysis, DET and DGT: In situ diffusive techniques for studying water, sediments and soils. In In Situ Monitoring of Aquatic Systems: Chemical Analysis and Speciation; Buffle, J., Horvai, G., Eds.; John Wiley & Sons: New York, 2000. (14) Garmo, Ø. A.; Røyset, O.; Steinnes, E.; Flaten, T. P. Performance study of diffusive gradients in thin films (DGT) for 55 elements. Anal. Chem. 2003, 75 (14), 3573-3580. (15) Scally, S.; Davison, W.; Zhang, H. In situ measurements of dissociation kinetics and labilities of metal complexes in solution using DGT. Environ. Sci. Technol. 2003, 37, 1379-1384.

1174

9

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(16) Tusseau-Vuillemin, M. H.; Gilbin, R.; Taillefert, M. A dynamic numerical to characterize labile metal complexes collected with diffusion gradient in thin films devices. Environ. Sci. Technol. 2003, 37, 1645-1652. (17) Zhang, H.; Davison, W. Diffusional characteristics of hydrogels used in DGT and DET techniques. Anal. Chim. Acta 1999, 398, 329-340. (18) Zhang, H.; Fang, J. Z.; Sun, B.; Davison, W.; McGrath, S. P. A new method to measure effective soil solution concentration predicts copper availability to plants. Environ. Sci. Technol. 2002, 35 (12), 2602-2607. (19) Almås, Å. R.; Bakken, L. R.; Mulder J. Changes in tolerance of soil microbial communities in Zn and Cd contaminated soils. Soil Biol. Biochem. 2004, 36 (5), 805-813. (20) Almås, Å. R.; Lombnæs, P.; Sogn, T. A. Prediction of Cd and Zn chemical species in contaminated soils using WHAM Model/VI and DGT and their uptake by Spinach and Ryegrass. Submitted to Chemosphere. (21) Zhang, H.; Lombi, E.; Smolders, E.; Mcgrath, S. Kinetics of Zn release in soils and prediction of Zn concentration in plants using diffusive gradients in thin films. Environ. Sci. Technol. 2004, 38, 3608-3613. (22) Luider, C. D.; Crusius, J.; Playle, R. C.; Curtis, P. J. Influence of natural organic matter source on copper speciation as demonstrated by Cu binding to fish gills, by ion selective electrode and by DGT gel sampler. Environ. Sci. Technol. 2004, 38, 28652872. (23) Tusseau-Vuillemin, M. H.; Gilbin, R.; Bakkaus, E.; Garric, J. Performance of diffusion gradient in thin films to evaluate the toxic fraction of copper to Daphnia magna. Environ. Toxicol. Chem. 2004, 23, 2154-2161. (24) Leivestad, H.; Muniz, I. P. Fish kill at low pH in a Norwegian river. Nature 1976, 259, 391-392. (25) Rosseland, B. O.; Sevaldrud, I.; Svalastog, D.; Muniz, I. P.; Studies on freshwater fish populationsseffects of acidification on reproduction, population structure, growth and food selection. In Ecological Impact of Acid Precipitation; Tollan, A., Drabløs, D., Eds.; SNSF-project report, ISBN-82-90376-07-3, Oslo-Aas, Norway; 1980; pp 336-337. (26) Skjelkvale, B. L. Factors influencing fluoride concentration in Norwegian lakes. Water Air Soil Pollut. 1994, 77, 151-167. (27) Gustafsson, J. P.; Lumsdon, D. G.; Simonsson, M. Aluminium solubility characteristics of spodic B horizons containing imogolite-type materials. Clay Miner. 1998, 33, 77-86. (28) Lydersen, E.; Salbu, B.; Pole`o, A. B. S.; Muniz, I. P. Formation and dissolution kinetics of Al(OH)3 (s) in synthetic freshwater solutions. Water Resour. Res. 1991, 27, 351-357. (29) Zhang, H.; Davison, W. In situ speciation measurements. Using diffusive gradients in thin films (DGT) to determine inorganically and organically complexed metals. Pure Appl. Chem. 2001, 73, 9-15. (30) Zhang, H.; Davison, W. Direct in situ measurements of labile inorganic and organically bound metal species in synthetic solutions and natural waters using diffusive gradients in thin films. Anal. Chem. 2000, 72, 4447-4457. (31) Zhang, H. In-situ speciation of Ni and Zn in freshwaters: comparison between DGT measurements and speciation models. Environ. Sci. Technol. 2004, 38, 1421-1427. (32) Downard, A. J.; Panther, J.; Kim, Y. C.; Powell, K. J. Lability of metal ion-fulvic acid complexes as probed by FIA and DGT: a comparative study. Anal. Chim. Acta 2003, 499, 17-28. (33) Leivestad, H.; Muniz, I. P.; Rosseland, B. O.; Acid stress in trout from a dilute mountain stream. In Ecological Impact of Acid Precipitation; Tollan, A., Drabløs, D., Eds.; SNSF-project report, ISBN-82-90376-07-3, Oslo-Aas, Norway; 1980; pp 318-319. (34) Verbost, P. M.; Berntssen, M. H. G.; Kroglund, F.; Lydersen, E.; Witters, H. E.; Rosseland, B. O.; Salbu, B.; Wendelaar Bonga, S. E. The toxic mixing zone of neutral and acidic river water: acute aluminum toxicity in brown trout (Salmo trutta L.). Water Air Soil Pollut. 1995, 85, 341-346. (35) Henrikson, L.; Hindar, A.; Tho¨rnelo¨f, E. Freshwater liming. Water Air Soil Pollut. 1995, 85, 131-142.

Received for review March 25, 2004. Revised manuscript received October 26, 2004. Accepted November 23, 2004. ES049538L