Waterborne toxicity of several DDT congeners to Hyalella azteca, and its implications for contaminated sediment assessment

doi:10.21203/rs.3.rs-3547624/v1

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Waterborne toxicity of several DDT congeners to Hyalella azteca, and its implications for contaminated sediment assessment

https://doi.org/10.21203/rs.3.rs-3547624/v1

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Although banned long ago in many countries and jurisdictions, the organochlorine pesticide dichlorodiphenyltrichloroethane (DDT) and compounds related to it remain in the aquatic environment, particularly in sediments, and can pose risks to aquatic life. To inform ecological risk assessment of these compounds, we tested the toxicity of six DDT congeners, specifically the p,p’ (4,4’) forms of DDT, dichlorodiphenyldichloroethylene (DDE), dichlorodiphenyldichloroethane (DDD), and dichlorodiphenylchloroethylene (DDMU), as well as the o,p’ (2,4’) isomers of DDT and DDD. The epibenthic amphipod, Hyalella azteca, was exposed for 7 days to waterborne chemical and assessed for changes in survival and growth. Median effect concentrations for biomass gain (aggregating effects on growth and survival) ranged from 0.14 µg/L (p,p’DDT) to 5.8 µg/L (o,p’DDD). Among p,p’ congeners, relative toxicity was DDT > > DDD > DDE ≈ DDMU. Ortho-para’ isomers averaged 6.6-fold less toxic than their p,p’ analogs. Application of these waterborne exposure endpoints in ecological risk assessment of contaminated sediments is discussed.

DDT

DDE

DDD

DDMU

aquatic toxicity

Hyalella azteca

Dichlorodiphenyltrichloroethane, generally known as DDT, was an early synthetic pesticide brought into widespread use across the globe in the 1940s. Because of its toxicity to wildlife, and particularly piscivorous birds, its use in the U.S. was banned in 1972, and banned or heavily restricted in many countries and jurisdictions throughout the latter part of the 20th century (ATSDR 2022). Despite the reductions in production and use, DDT remains in the aquatic environment, particularly in aquatic sediments near sites of historical production or disposal.

The term DDT is used to refer either to the specific compound dichlorodiphenyltrichloroethane, or to the commercial pesticide of which the compound DDT was a primary component. The technical grade pesticide DDT was not a single compound but a mixture of several closely related compounds, primarily p,p’-DDT (~ 77%) and o,p’-DDT (~ 15%; USEPA 1980). The remainder included additional congeners, including p,p’ and o,p’ isomers of dichlorodiphenyldichloroethylene (DDE) and dichlorodiphenyldichloroethane (DDD). In addition to being minor components of the technical pesticide, DDE and DDD can form from DDT in the environment through aerobic and anaerobic degradative processes, to the extent that they may occur in higher concentrations than DDT. There are additional congeners along the degradation pathway, such as dichlorodiphenylchloroethylene (DDMU) and others that arise through dechlorination and subsequent oxidation of the trichloroethane structure in the middle of the DDT molecule (USEPA 1980); this family of congeneric compounds is sometimes referred to collectively as DDX. Because of this chemical diversity, assessment of toxicity or risk from DDX mixtures requires information on the relative toxicity of the different congeners.

In addition to being persistent in the environment, DDX compounds are also quite hydrophobic, with octanol-water partition coefficients (K_OW) in the range of log 5.5-7 (USEPA 2023) and low water solubility. This hydrophobicity leads to accumulation in sediment and a resulting exposure of benthic organisms; this exposure can in turn result in both direct toxicity to exposed organisms and bioaccumulation of DDX into their tissues and transfer up the food chain. The focus of the experiments in this paper is to aid in the assessment of direct toxicity to benthic organisms.

Over the last 30 years, assessing or predicting the direct toxicity of non-ionic organic compounds in sediments to benthic organisms has often relied on the concept of equilibrium partitioning (EqP). EqP theory asserts that chemical activity in the solid phase and interstitial water of sediments approximates thermodynamic equilibrium, and that toxicity of sediments is expected when freely dissolved concentrations of chemical in the interstitial water equal those shown to be toxic in water-only toxicity tests (Di Toro et al. 1991). Initially, EqP was used to derive effect concentrations in bulk sediments by converting water-only effect concentrations to bulk sediment concentrations based on estimates of the organic carbon:water partition coefficient (K_OC). This conversion was used in part because accurately measuring freely dissolved concentrations (C_free) of contaminants in interstitial water was considered too technically difficult. In the interim, there has been extensive development of passive sampling techniques to directly assess C_free in sediment interstitial water, with this approach emerging as a preferred approach in many instances (Mayer et al. 2014; Lydy et al. 2014; Greenberg et al. 2014). In 2017, the U.S. Environmental Protection Agency published guidance for developing interstitial water-based remedial goals for assessment of historically-contaminated sediments under the remedial program known as “Superfund” (USEPA 2017).

Because of their environmental persistence, DDX mixtures remain a common presence at contaminated sediment sites. To apply equilibrium partitioning and/or passive sampling approaches in assessing potential toxicity of this contamination, water-only toxicity data are needed to establish hazard concentrations for benthic species. Three literature studies have evaluated the lethality of the p,p’ isomers of DDT, DDE, and DDD to the amphipod Hyalella azteca, arguably the most commonly used organism for testing freshwater sediments in North America (Phipps et al. 1995; Lotufo et al. 2000; Ding et al. 2012). The purpose of the present study is to enhance our understanding of the toxicity of DDX mixtures by providing data on a wider range of DDT congeners, evaluating the relative toxicity of p,p’ and o,p’ isomers, and assessing sublethal effects on organism growth in addition to lethality.

Separate toxicity tests were conducted with each of the six DDX chemicals in 7-d exposures of the amphipod, Hyalella azteca, using methods adapted from those described by Kadlec et al. (2023). The primary difference from those previous methods is in our use of silicone O-rings as passive dosing devices (Mayer et al. 1999; Smith et al 2010) to compensate for losses of DDX chemicals, as preliminary work showed that stable water concentrations could not be maintained using daily renewal of test solutions alone.

Test chemicals and test solution preparation

Test water was prepared from sand-filtered and UV-treated Lake Superior water, pumped from a gravel/sand covered intake offshore of our laboratory at approximately 46.840°N, 92.004°W. This water was then supplemented with major ion salts to make the composition more similar to average surface waters of the U.S. (see Mount et al. 2016), and modified further to meet minimum requirements of the “US laboratory strain” of H. azteca for chloride (Soucek et al. 2015) and bromide (Borgmann 1996; Ivey et al. 2016). This results in a water with a composition of 11.3 mg Na/L, 1.5 mg K/L, 14.6 mg Ca/L, 4.1 mg Mg/L, 15.0 mg Cl/L, 14.9 mg SO₄/L, 52.4 mg HCO₃/L, and 0.055 mg Br/L (hardness ~ 53 and alkalinity ~ 43, both in mg/L as CaCO₃). Typical dissolved organic carbon (DOC) is 1.6 mg/L.

Test chemicals were p,p’ isomers of DDT, DDE, DDD, and DDMU, and o,p’ isomers of DDT and DDD, obtained from commercial suppliers with reported purity of ≥ 98% (Supplemental Information S1). Silicone O-rings (USA Sealing #216; 3.53 mm cross section, 35.23 mm overall diameter) were washed with methanol, then loaded with test chemical by soaking them for several days in methanol containing concentrations of test chemical based on partition coefficients empirically derived from previous experiments. For each experimental treatment, twelve to sixteen O-rings were soaked in 200 ml methanol/DDX solution for at least 3 days, after which they were removed and quickly rinsed with a small volume of de-ionized water to remove excess methanol. Rings were then transferred to ashed 3.8 L jars with foil-lined lids containing 3 L of control water, and placed on a roller mill at 10 rpm for 4–6 days to equilibrate. Separate sets of rings were prepared for each of 5 or 6 test concentrations, which were spaced by 0.5-fold intervals. Test treatments also included a procedural blank of sham-loaded (methanol only) O-rings, and a negative control with no O-rings.

Toxicity test procedures

Primary toxicity test methods are described by Kadlec et al. (2023). Test organisms were obtained from in-house cultures of adult animals isolated to obtain cohorts of animals within 24-hours of age, which were then reared for 7-d before use in toxicity tests. Tests were conducted in 100-mL tall-form glass beakers with two 12 mm holes drilled in opposing sides of the beaker, positioned to provide 60 mL of water volume before overflow; stainless steel screens were placed over the holes using silicone glue on the outside of the beaker. Beakers were held inside glass aquaria that were placed in temperature-controlled water baths equipped with electronic monitoring and alarms; water levels in the surrounding aquaria were maintained just below the screen ports so there could be no mixing of solution among beakers. A thin layer of clean quartz sand (2.5 mL) was added to each beaker to serve as substrate for the test organisms. Test solutions were renewed by slowly introducing 60 mL of fresh test solution from above using a reservoir with a small-bore outlet; excess solution flowed out through the screened ports. Replacement of solution was not complete, as new and old solutions mixed during the renewal process.

In addition to daily solution renewal, maintenance of chemical exposure was further aided by suspending one (p,p’-DDT, p,p’-DDD) or two (all other chemicals) silicone O-rings. To allow time for exposure concentrations to stabilize in test beakers, four replicate test beakers per treatment were set up one (p,p’-DDT) or five days (remaining chemicals) prior to the introduction of organisms. O-rings were removed from the equilibrated test solution and suspended in the test beakers horizontally at about the 40-mL level using stainless steel wire. Sixty mL of test solution was added to each beaker along with a glass tube introducing a slow stream of air (1–2 bubbles/sec) to encourage exchange between the ring and test water. The remaining 8 O-rings were left in the stock solution on the roller mill, which was used for solution renewals for the remainder of the test. Daily renewals of test solution began on day 0 (p,p’ isomers of DDT, DDE, DDD) or day − 2 (remaining chemicals) and continued for the duration of the experiment. Increasing pre-exposure equilibration times, earlier renewals, and increasing from 1 to 2 O-rings were all steps taken in attempts to further reduce fluctuations in exposure concentrations between renewals, but these modifications did not appear to have substantial effect.

On test day 0, 10 organisms were distributed to each test beaker, with replicates stocked in random order. Within 30 minutes of receiving organisms, each beaker was supplied with 1 mL of a mixture of yeast, cereal leaves, and trout chow (YCT at 1.7–1.9 mg solids/mL; see USEPA 2002) and 0.25 mg of flake tropical fish food (TetraMin® Tropical Flakes) that was crumbled dry until it passed a 50 µm stainless steel screen; these rations were added daily, after solution renewal, for the duration of the test. Target test temperature was 23 ± 1° C, with ambient laboratory lighting on a 16h light:8h dark photoperiod. Temperature was measured daily in each treatment prior to renewal; dissolved oxygen and pH were measured on three different days in both stock solutions and test beakers (prior to renewal).

After 7 d of exposure, the tests were ended by pouring the contents of each beaker into a shallow plastic tray on a light box; surviving organisms were counted and placed in tared, pre-ashed aluminum weigh pans, dried at 90° C for ≥ 24 h, weighed (to 0.01 mg), ashed at 450° C for 2 h, and weighed again to determine ash-free dry weight (AFDW) by difference. AFDW was used rather than dry weight because the organism mass is so small that even one grain of substrate sand inadvertently transferred to the weigh pan can influence dry weight substantially -- AFDW eliminates this concern because any sand would be subtracted off as ash. Four samples of 10 organisms each were also collected at the start of each exposure and processed similarly to determine initial AFDW.

Analysis of Exposure Concentrations

The analytical method was adapted from EPA Method 1699 (USEPA 2007). Analytical standards 4,4’-DDT, 2,4’-DDT, 4,4’-DDD, 2,4’-DDD, 4,4’-DDE and 2,4’-DDE were purchased from Absolute Standards (Hamden, CT, USA), and 4,4’-DDMU from AccuStandard (New Haven, CT, USA). Mass Labeled Surrogate and Internal Standards 4,4’-DDT-(Ring-13C12), 2,4’-DDT-(Ring-13C12), 4,4’-DDE-(Ring-13C12) and PCB-52-(Ring-13C12) were obtained from Cambridge Isotopes (Tewksbury, MA, USA) and DDT Decomposition Test Solution (M-1656-DS) from AccuStandard.

Water samples (2–10 mL) were collected and centrifuged at 5° C and ~ 2000x g for 15 min, then an aliquot of supernatant was transferred to a tared volatile organic analysis vial that was previously spiked with a surrogate mixture, and weighed to determine sample mass. Each vial received sodium sulfate (~ 50 mg), followed by 1–3 mL (depending on water sample volume) hexane, then was manually shaken for one minute; after shaking, isopropanol was added dropwise to break any emulsion, and the organic layer was transferred to a 15-ml centrifuge tube. The remaining aqueous phase was extracted twice more, and the combined extracts evaporated to 1 mL. Clean-up columns were prepared in solid phase extraction cartridges loaded with ~ 0.5 cm layers (from bottom up) of sodium sulfate, basic silica gel, acid silica gel, and more sodium sulfate, separated with glass frits or wool. After rinsing the column with three bed volumes of hexane, sample extracts were loaded onto the column along with three hexane washes of the vial. The column was then eluted with three more bed volumes of hexane. The aggregated column eluate was evaporated to 1 ml, solvent exchanged to toluene, moved to a GC vial, and evaporated to 20 µL, to which 5 µL of internal standard was added. Analysis was conducted by gas chromatography/high resolution mass spectroscopy (GC/HRMS; Thermo GC-QExactive-Orbitrap) using isotopic dilution analysis as described in EPA Method 1699; see Supplemental Information S1 for instrumental parameters and further details.

Data analysis

Average exposure concentration in a treatment was calculated as the mean of the six “pre-renewal” measurements (from two replicate test chambers sampled on days 0, 2, and 6) and three measurements of the fresh solutions used for renewal on the same days. Because daily water renewals involved mixing of new and old solution rather than complete replacement, the resulting average being weighted toward the old solutions was considered appropriate.

Exposure-response analyses were conducted on two biological endpoints: survival and biomass gain. Biomass gain was calculated as the AFDW of organisms pooled from a single replicate, minus the estimated initial aggregate mass of the surviving organisms (calculated as average initial AFDW × number of surviving organisms). Biomass gain was used rather than total AFDW per replicate because the initial AFDW of the organisms was a meaningful percentage of the final AFDW (circa 25%). Regressions used a logarithmic concentration scale; controls were arbitrarily assigned a value of 1/10 of the lowest treatment. Point estimates of the median lethal concentrations (LC50) and 20% and 50% effect concentrations for biomass gain (EC20, EC50), including 95% confidence intervals, were calculated using the regression methods described by Kadlec et al. (2023). Final model outputs are provided in the Supplemental Information (S3). The procedural blank and negative control treatments were compared by t-test at p = 0.05 (Microsoft Excel).

Summary of Exposure Conditions and Control Performance

A detailed presentation of experimental data for each of the exposures is provided in the Supplemental Information (S3). Control survival averaged 96.3% (range 90–100%; procedural blank and negative controls combined) and ending AFDW for controls averaged 3.79 times starting weight (range 2.93–4.46). Control performance criteria for a 7-d exposures with H. azteca have not been established, but control survival and growth in all tests exceeded performance criteria established for 10-d exposures (≥ 80% survival and final weight ≥ 2.5x initial; ASTM 2020). T-tests did not show significant differences between negative controls and procedural blanks except for the p,p’-DDMU test, in which biomass gain in the procedural blank was significantly higher than in the negative control (Table S3.6). However, biomass gain in the three lowest exposure concentrations had essentially the same average as the negative control, suggesting that the negative control might be more representative of a no-response value. Accordingly, all regression analyses included both negative and procedural blank controls. Temperature averaged 22.9 across all experiments, with all individual measurements between 22.0 and 24.0°C except for the first day of the p,p’-DDMU exposure wherein three treatments were below 22.0°C by up to 0.5°C, which was corrected and did not recur. Dissolved oxygen was consistently near 100% (chambers were aerated), and pH averaged 7.9 (range 7.4–8.3).

Measured DDX concentrations in the equilibrated test solutions used for renewals showed very small increases over the course of the exposure; measurements taken on days 0, 2, and 6 averaged 96.2, 100.7, and 103.0% (respectively) of the overall treatment average. DDX concentrations in test beakers measured immediately prior to renewal showed more increase over time, averaging 73.7, 84.8, and 103.6% of the average concentration in the renewal solutions on days 0, 2, and 6. This increase may have arisen from ongoing saturation of binding sites in the test vessels; another possibility is that DOC may have increased over the course of the test. An increase in DOC could result in greater DDX association with DOC, which could increase the overall water column concentration even if freely dissolved concentrations were maintained at a constant value by the O-rings (chemical analyses quantified total concentration, not C_free). Measured concentrations in individual treatments of all exposures are provided in the Supplemental Information (S3).

Toxicity of DDT Congeners and Comparison with Literature Data

Seven-day LC50, EC20, and EC50 values are shown in Table 1, and exposure-response curves in Fig. 1. Toxicity among the tested congeners varied substantially, with a range in biomass EC50 values of about 40-fold, from 0.14 µg/L for p,p’-DDT to 5.85 µg/L for o,p’-DDD. Among p,p’ congeners, relative toxicity was DDT > > DDD > DDE ≈ DDMU for all three endpoints. For the two congeners tested in both p,p’ and o,p’ isomers, the o,p’ isomers were notably less toxic, with EC50 (biomass) values 7.4-fold lower for p,p’-DDT compared to o,p’-DDT, and 5.9-fold lower for p,p’-DDD compared to o,p’-DDD. Response curves for all chemicals were uniformly quite steep, meaning the magnitude of effect declined quickly with declining exposure concentration (Fig. 1); EC20 (biomass) values averaged 80% of the corresponding EC50 (range 71–85%). Much of the toxic response was expressed as lethality; there was never more than one exposure concentration in which AFDW was reduced but survival was not (Supplemental Information S3). As a result, biomass EC50 and LC50 concentrations did not differ greatly, with the biomass EC50 averaging 75% of the LC50 (range 69–82%).

Table 1. Seven-d Hyalella azteca LC50 (lethality), EC50 (biomass gain), and EC20 (biomass gain) values (95% confidence limits) for the six DDT congeners tested in the current study, shown alongside 10-d LC50s from literature sources.

Chemical	CAS	Current Study: 7-d Effect Concentration (µg/L)			Literature 10-d LC50 (µg/L)
Chemical	CAS	LC50 (lethality)	EC50 (biomass)	EC20 (biomass)	Phipps et al 1995	Lotufo et al. 2000	Ding et al. 2012
p,p’-DDT	50-29-3	0.19(0.17 – 0.21)	0.14 (0.12 - 0.16)	0.10 (0.08 – 0.12)	0.07	0.10	0.094
o,p’-DDT	789-02-6	1.41 (1.24 – 1.59)	1.06 (0.77 – 1.15)	0.90 (0.37 – 1.25)	--	--	--
p,p’-DDE	72-55-9	4.04 (3.65 – 4.47)	3.32 (2.63 – 4.19)	2.82 (2.22 – 3.57)	1.66	3.88	3.21
p,p’-DDD	72-54-8	1.46 (1.25 – 1.69)	1.11 (0.98 – 1.33)	0.92 (0.81 – 1.15)	0.19	0.77	0.30
o,p’-DDD	53-19-0	8.55 (7.60 – 9.62)	5.88 (5.04 – 6.87)	4.21 (3.17 – 5.61)	--	--	--
p,p’-DDMU	1022-22-6	5.44 (4.74 – 6.23)	4.07 (3.43 – 4.96)	3.26 (2.67 – 4.23)	--	--	--

Also shown in Table 1 are 10-d LC50 values for H. azteca reported in the literature for the p,p’ isomers of DDT, DDE, and DDD (Phipps et al. 1995; Lotufo et al. 2000; Ding et al. 2012). Across studies, LC50 values were not greatly different for p,p’-DDT and DDE, varying by less than 3-fold, with a larger range (7.7-fold) for p,p’-DDD. Our finding of lower toxicity of p,p’-DDD study is reinforced by a prior study we conducted, in which treatments from 0.05 to 0.63 µg/L had no effect on survival or AFDW (data not shown). Rank order of sensitivity among the four studies was consistent across the three chemicals, with Phipps having the lowest LC50s, followed by Ding, Lotufo, and the current study. Methodological differences among the four studies may affect these comparisons. The three literature studies were 10-d in duration rather than 7-d in the present study, and both Lotufo et al. (2000) and Ding et al. (2012) reported 4-d LC50s that were in the range of 50–300% higher than 10-d LC50s. The Phipps study was conducted in unamended Lake Superior water, which has a low chloride concentration (1.5 mg/L); later work showed this low chloride concentration was associated with reduced performance and greater toxicological sensitivity of H azteca (Soucek et al. 2015), which might explain the lower effect concentrations reported by Phipps et al. (1995). Chloride concentrations in tests by Ding et al. (2012) were about 33 mg/L (MJ Lydy, personal communication), while those for Lotufo et al. (2000) were not available.

Loss of chemical over time was reported in both the Lotufo and Ding studies. Lotufo et al. (2000) reported daily declines in exposure concentrations of 25 to 62% between daily 75% renewals. Ding et al. (2012) used static exposures (no renewals) and reported declines of 41 to 74% in exposure concentration over the course of the exposure. Depending on the toxicokinetics of the chemicals, fluctuating exposure might bias LC50 values calculated based on mean concentration, but the direction and magnitude of any such potential bias is not clear. All four studies used 1 ml YCT as food, but the current and Phipps study fed daily, while the Lotufo study was fed every other day, and the Ding study only twice over 10 d (the current study also included a flaked fish food addition). Whether reduced ration would increase sensitivity to DDX congeners is uncertain. McNulty et al. (1999) found that starvation prior to testing increased the acute sensitivity of H. azteca to pentachlorophenol and carbaryl while sensitivity to KCl and CdCl₂ was not changed, but in the Lotufo and Ding studies food was not withheld, only reduced relative to standard rates.

We limited our testing of o,p’ isomers to DDT and DDD, electing not to test o,p’-DDE and o,p’-DDMU. Because of the very high silicone:water partition coefficients and low silicone:methanol partition coefficients, loading of silicone O-rings required relatively large amounts of test chemical (circa 0.2 to 1 g). Lack of commercial availability and/or very high cost of these quantities of o,p’-DDE and o,p’-DDMU were important factors in the decision not to pursue testing, as were concerns about solubility of the compounds in methanol. In our test with p,p’-DDE, achieving the highest treatment required loading the O-rings in solutions at the limit of chemical solubility in the methanol loading solution, and only that solubility-constrained concentration was sufficient to cause toxicity to H. azteca. Assuming that the o,p’ isomers of DDE and DDMU would be substantially less toxic than the p,p’ congeners (as was true for DDT and DDD), it might not be possible to achieve toxic concentrations in water using our dosing approach.

As noted, however, the relative toxicity of o,p’ and p,p’ isomers was similar for DDT and DDD in our experiments. The ratio of o,p’ to p,p’ effect concentrations across both of those chemicals and all three endpoints in Table 1 averages 6.6. In the absence of measured values, one might assume a similar isomer separation for o,p’-DDE and o,p’-DDMU, yielding estimated LC50, EC50, and EC20 values of 27, 21, and 19 µg/L for o,p’-DDE, and 36, 27, and 22 µg/L for o,p’-DDMU.

Implications for Ecological Risk Assessment

The variation in toxicity of different congeners has important implications for risk assessment of environmental mixtures stemming from DDT contamination. Because p,p’-DDT is about 77% of the commercial pesticide formulation and is also the most toxic congener, we calculate that about 97% of the toxicity of the pesticide formulation in water would be attributable to p,p’-DDT (if the components acted additively based their fractional potencies, which seems a reasonable assumption in the absence of contrary evidence). Although already a minority component of the commercial pesticide (~ 15%), the influence of o,p’-DDT on overall toxicity is further minimized by its considerably lower toxicity. Based on these calculations, the expected toxicity of the unweathered DDT pesticide mixture would be only about 20% lower (by mass) than if it were pure p,p’-DDT, and an assessment based on total measured DDX compounds (sometimes termed DDTR) would be fairly accurate if all DDTR was assumed to be the most toxic congener, p,p’-DDT. Nebeker et al. (1989) reported 10-d LC50s of ~ 0.5 µg/L for H. azteca exposed to pesticide DDT in water which is not far above values for p,p’-DDT; those tests were conducted with much older organisms (~ 28 d) than those used for tests listed in Table 1, which might influence the comparison.

However, with environmental weathering and other processes acting on DDT contamination, composition of environmental mixtures can vary widely, not only through dechlorination and oxidation of the central trichloroethane moiety, but also as a result of environmental processes that can change the ratio of p,p’ and o,p’ isomers dramatically (Ricking and Schwarzbauer, 2012). DDX contamination in Palos Verdes shelf sediments showed little DDT or DDD, and was instead dominated by DDE and more degraded structures (Eganhouse et al. 2018). Similarly, using passive sampling, Fernandez et al. (2014) found DDX in Palos Verdes Shelf sediment interstitial water and surface water at the sediment-water interface was predominately DDE. These highly modified mixtures can be expected to have considerably different toxicity compared to unweathered pesticide, emphasizing the need to understand the relative toxicity of different DDT congeners.

We did not test the toxicity of DDT metabolites beyond DDMU in the degradation series, but it is possible their toxicity may not decline a great deal more than that of DDMU. This hypothesis stems from the expected toxicity of chemicals acting through baseline (aka “narcotic”) toxicity. Based on the modeling of Di Toro et al. (2000), an aromatic and halogenated narcotic compound with log Kow of 5.5 can be expected to cause acute lethality to sensitive taxa at about 0.07 µmol/L. At a molecular weight of 250 (in the range of more degraded DDT congeners), this equates to about 17 µg/L, not much higher than the effect concentrations of some of the less toxic congeners tested here.

Equilibrium partitioning (Di Toro et al. 1991) has been used as a means of predicting toxicity of non-ionic organic chemicals in sediment, by predicting the chemical activity of contaminants via the appropriate K_OC. Making this prediction for DDT congeners is complicated by variability in K_OC values across sediments. ATSDR (2022) provides log K_OC values for isomers of DDT, DDE, and DDD ranging from 4.70 to 5.18, and estimates from poly-parameter linear free energy relationship (PPLFER) models range from 4.84 to 5.60 (Ulrich et al. 2017). In contrast, measurements from Palos Verdes shelf sediments indicate log K_OC values of 6.3 to 7.5 for various DDT congeners, about 0.5 log units higher than the estimated K_OW (Eganhouse et al. 2018), which the authors attribute to the effects of other hydrocarbons present in the sediments. The potential for more than 100-fold variability in K_OC is problematic for deriving broadly applicable effect concentrations for bulk sediment.

Another consequence of the high hydrophobicity of DDT congeners is their propensity to associate with dissolved or colloidal organic carbon (DOC), thereby reducing the proportion of waterborne DDX that is freely dissolved and thought to be bioavailable (Di Toro et al. 1991). This effect can be particularly important in sediment interstitial waters, which can contain relatively high DOC concentrations. Eganhouse et al. (2018) found that the DOC-bound fractions of DDE and DDMU were very high (> 80%) in shallow portions of sediments from the Palos Verdes shelf. Hoke et al. (1994) reported DDX concentrations in interstitial water isolated by centrifugation, and found that they exceeded the predicted C_free, a difference they attributed to DOC binding. These examples make clear that when assessing potential toxicity of DDX mixtures in sediments (or waters with high DOC), use of passive sampling or other methods able to parse C_free is important (USEPA 2017b).

The toxicity to H. azteca of the six DDT congeners tested varied by about 40-fold. Among p,p’-isomers, DDT was the most toxic (7-d biomass EC20 = 0.10 µg/L), followed by DDD then DDE; this ranking matched that found in previous studies. Toxicity of the previously untested p,p’-DDMU was comparable to that of p,p’-DDE. Both of the o,p’ isomers tested (DDT, DDD) were notably less toxic than their p,p’ forms. Inclusion of growth (biomass) as an endpoint did not greatly decrease effect concentrations over lethality alone. Variations in the toxicity of DDT congeners combined with the variation in the composition of environmental DDX mixtures emphasize the need to consider both as part of assessing potential toxicity of DDT contamination in water or sediment.

Funding

The information in this document has been funded wholly by the U.S. Environmental Protection Agency. It has been subjected to review by the Center for Computational Toxicology and Exposure (CCTE) and approved for publication. Approval does not signify that the contents reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

Conceptualization: David R. Mount, Lawrence P. Burkhard; Methodology: Tylor J. Lahren, J. Russell Hockett, David R. Mount, Lawrence P. Burkhard; Investigation: J. Russell Hockett, Chloe J. Holloway, Sarah E. Howe, James J. Jenson, Sarah M. Kadlec, Alex J. Kasparek, Tylor J. Lahren, Kevin G. Lott, Edward Piasecki, John J. Swanson, Lauren K. Votava; Data curation: Sarah M. Kadlec, Tylor J. Lahren, David R. Mount; Formal analysis: Sarah M. Kadlec, Tylor J. Lahren, David R. Mount; Writing – original draft: David R. Mount; Writing – review & editing: all authors.

Data Availability

Data in Supplementary Information

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Waterborne toxicity of several DDT congeners to Hyalella azteca, and its implications for contaminated sediment assessment

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Abstract

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Introduction

Methods

Test chemicals and test solution preparation

Toxicity test procedures

Analysis of Exposure Concentrations

Data analysis

Results and Discussion

Summary of Exposure Conditions and Control Performance

Toxicity of DDT Congeners and Comparison with Literature Data

Implications for Ecological Risk Assessment

Summary

Declarations

References

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