Benzenesulfonic acid, 4-C10-13-sec-alkyl derivs., compds. with ethanolamine

Ecotoxicological Summary

Hazard for aquatic organisms

Freshwater

Hazard assessment conclusion:

PNEC aqua (freshwater)

PNEC value:

0.268 mg/L

Assessment factor:

1

Extrapolation method:

assessment factor

PNEC freshwater (intermittent releases):

0.022 mg/L

Marine water

Hazard assessment conclusion:

PNEC aqua (marine water)

PNEC value:

0.027 mg/L

Assessment factor:

10

Extrapolation method:

assessment factor

STP

Hazard assessment conclusion:

PNEC STP

PNEC value:

3.43 mg/L

Assessment factor:

10

Extrapolation method:

assessment factor

Sediment (freshwater)

Hazard assessment conclusion:

PNEC sediment (freshwater)

PNEC value:

8.1 mg/kg sediment dw

Assessment factor:

10

Extrapolation method:

assessment factor

Sediment (marine water)

Hazard assessment conclusion:

PNEC sediment (marine water)

PNEC value:

0.81 mg/kg sediment dw

Assessment factor:

10

Extrapolation method:

assessment factor

Hazard for air

Air

Hazard assessment conclusion:

no hazard identified

Hazard for terrestrial organisms

Soil

Hazard assessment conclusion:

PNEC soil

PNEC value:

35 mg/kg soil dw

Extrapolation method:

sensitivity distribution

Hazard for predators

Secondary poisoning

Hazard assessment conclusion:

no potential for bioaccumulation

Additional information

Data normalization 

For the present registration, the various tested LAS mixtures were first normalized to C11.6 LAS by use of conventional Quantitative Structure-Activity Relationships, as has been previously described in the peer reviewed literature and in OECD and USEPA HPV (High Production Volume) assessments. Similar normalization processes for environmental risk assessment have also been performed for alcohol sulfates, alcohol ethoxysulfates, alcohol ethoxylates and long chain alcohols. The normalization procedures followed the process first described by van de Plaasche et al. (1999) and replicated for HPV (OECD, 2005). 

Strong structure-activity relationships for acute toxicity to fish (and other species) based on studies of pure chain length materials supports read across to all members of the distribution of LAS homologues present in the MEA-LAS substance (Belanger et al., 2016). Four robust and highly localized (Q)SARs have been developed for LAS normalization, including a model for invertebrates (separate models built from Daphnia magna and Ceriodaphnia dubia; Belanger et al., 2016), algae (Desmodesmus subspicatus; Verge and Moreno, 1996) and fish (Pimephales promelas; Belanger et al., 2016). These models have been built from high quality toxicity data using pure LAS chain lengths (C10-C14). Further external validation was performed using LAS mixtures with different average alkyl chain lengths. Detailed QSAR Model Reporting Format (QMRF) documents describing data quality, model development and performance have been developed for each model and are available in the respective Robust Study Summaries (RSS) of the IUCLID dataset. 

Species Sensitivity Distribution (SSD) 

A Species Sensitivity Distribution (SSD) analysis was performed based upon a robust dataset of chronic aquatic toxicity values available from tests with various LAS homolog mixtures. The dataset of 19 chronic ecotoxicity studies included 4 species of algae, 2 aquatic macrophytes, 8 invertebrates and 5 fish. Photosynthetic organisms span blue-green and green algae as well as two floating aquatic macrophytes. Molluscs, water fleas, rotifers and insects are representative invertebrates. Fish include members of the salmonid, centrarchid and cyprinid families and cover warm and cold-water species. Effects of LAS are based on well accepted chronic endpoints such as growth, survival and reproduction. 

All the data in this summary are from studies judged to be “Reliable without restriction” (KL1) or “Reliable with restrictions’ (KL2). Thirteen of the 19 studies have appeared in peer-reviewed literature and the remaining studies are well documented industry and contract laboratory reports.

The quality of the input data used to generate the SSD was evaluated by criteria discussed in the REACH Guidance (R.10.3.1.3: Calculation of PNEC for freshwater using statistical extrapolation techniques). These criteria enable consideration of the potential appropriateness of additional application factors (AF) in extrapolating the HC5 to a PNEC (Predicted No Effect Concentration for the ecosystem). According to these criteria, the data used as input to the SSD satisfied the appropriateness of using the SSD statistical extrapolation technique for PNEC derivation with an AF of 2. 

All chronic toxicity data were normalized to C11.6 LAS using the methods and LAS-specific QSARs outlined above. Normalized chronic toxicity values ranged from 0.23 mg/L for rainbow trout to 16.15 mg/L for the algae Pseudokirchneriella subcapitata (details are presented in Table 1 of the document entitled ‘LAS Species Sensitivity Distribution Technical Summary 02.06.2020’ attached to Section 13 of the IUCLID dataset). 

Development and analysis of the SSD followed ECHA procedures described in the REACH Technical Guidance Document R.10.3.1.3 (Calculation of PNEC for freshwater using statistical extrapolation techniques), supplemented with additional statistical evidence reflecting the state of the science. The SSD was estimated by maximum likelihood assuming a log-logistic distribution of data values, i.e. fitting a logistic distribution to the log-transformed data values. Confidence intervals were computed by the methods of Aldenberg and Slob (1993). The interval on the HC5 is intended to ensure that there is a high probability (95%) that the true HC5 is within the limits of the interval, based upon the model fitted to the data. 

The SSD is plotted in Figure 1 of the document entitled ‘LAS Species Sensitivity Distribution Technical Summary 02.06.2020’ attached to Section 13 of the IUCLID dataset. The 5th percentile value calculated from the SSD, the HC5, was 0.21 mg/L. Hence, the HC5 for LAS was equal to or lower than any of the predicted chronic toxicity values for the 19 taxa tested. 

Statistical evaluations were also conducted to assess the stability and sensitivity of the C11.6 LAS HC5. The analysis consisted of two statistical tests: 

Leave-One-Out Simulation 

An assessment of stability based on a reduced data set where one of the 19 values was theoretically never generated and the HC5 was recalculated. 

A data deletion at the lowest end of the distribution (e.g., Oncorhynchus mykiss) results in a raise in the estimated HC5 concentration to 0.26 mg/L. Data deletion near the centre and upper end of the distribution (> 1 mg/L) resulted in lower HC5 values (~0.20 mg/L), indicating that the variance term had increased as a result of the deletion. Overall the HC5 was stable and would not shift substantially if selected values were deleted.

Add-One-In Simulation 

The influence of adding hypothetical data to the LAS chronic toxicity dataset on the HC₅was evaluated. This technique allows a determination of the influence of adding additional data which could measurably impact the HC₅. The emphasis in this analysis is on adding data on the low end of the toxicity distribution. This can be viewed this as the likelihood of discovering new and previously unknown ultrasensitive taxa.

In order to lower the HC5 by a factor of two (0.11 mg/L), a new chronic toxicity value of 0.0032 mg/L would have to be derived. The probability of finding a new taxon with this hazard concentration is 1 in 14,400.

In order to lower the HC5 by a factor of three (0.07 mg/L), a new chronic toxicity value of 9.1 x 10^-5mg/L would have to be derived. The probably of finding a new taxon with this hazard concentration is 1 in 4,160,000.

These evaluations demonstrated that the chronic toxicity data were highly ordered and strongly adhered to statistical assumptions. The SSD and the resulting HC5 were highly stable to either deletion or addition of new data.

References not cited in Annex 1

Aldenberg, T. and Slob, W. 1993. Confidence limits for hazardous concentrations based on logistically distributed NOEC toxicity data. Ecotoxicology and Environmental Safety25:48–63.

Belanger, S.E. et al. 2006.Aquatic risk assessment of alcohol ethoxylates in North America and Europe. Ecotoxicology and Environmental Safety 64: 85-99. 

Belanger, S. E. et al. 2009.Assessment of the environmental risk of long-chain aliphatic alcohols. Ecotoxicology and Environmental Safety 72:1006-1015.

OECD (Organization for Economic Cooperation and Development). 2005. Linear Alkylbenzene Sulfonate (LAS). OECD SIDS Initial Assessment Report. 357 p. 

van de Plassche, E. J. et al. 1999.Predicted no-effect concentrations for four surfactants: linear alkyl benzene sulfonate (AES), alcohol ethoxylates (AE), alcohol ethoxylated sulfates (AES) and soap. Environmental Toxicology and Chemistry 18(11):2653-2663.

Volz, D.C. et al. 2011.Adverse outcome pathways during early fish development: a conceptual framework for identification of chemical screening and prioritization strategies. Toxicological Sciences 123(2):349-58.

PNECs for the aquatic environment

A model ecosystem study of LAS with a NOEC of 0.268 mg/L was used to derive the aquatic PNEC values for LAS. ECHA describes the interactive roles of statistical extrapolation techniques with the deterministic based PNECs for mesocosms in the REACH Technical Guidance Document Sections R.10.3.1.2 (Calculation of PNEC for freshwater using assessment factors) and R.10.3.1.3 (Calculation of PNEC for freshwater using statistical extrapolation techniques). Stream model ecosystems are considered the most appropriate for assessing this chemical (versus ponds) due to the wide dispersive use and route of discharge to receiving waters via wastewater treatment plants. In the case of the model ecosystem study summarized by Belanger et al. (2002), the following considerations support no additional application factor to be applied to the result when deriving the PNEC water (see ECETOC, 1997; Giddings et al., 2002; OECD, 2006). The most important factors are knowledge of the biological complexity, sensitivity, study duration, exposure determination, and relevance to natural systems for the specific system being assessed. For the model ecosystem study of LAS:

1) The model ecosystem was biologically complex, containing a highly diverse community with 117 invertebrate genera assessed (including ~500 insect species). Approximately 150 algal species were studied, dominated by sensitive diatom flora. Protozoa which were not studied in this particular investigation historically accounted for an additional 300 species.

2) The model ecosystem was sensitive. The system was optimized for statistical and biological sensitivity. Key endpoints evaluated possessed Minimum Detectable Differences using inferential statistics of 5-20% (change needed to be identified as statistically different from the control). Use of PRC, Principal Response Curve Analysis, corroborated use of repeated measure ANOVAs on single population endpoints and coincides with NOECs on the most sensitive taxa and taxonomic groups. The dominant invertebrate taxa were sensitive species of the EPT group (mayflies, stoneflies, and caddisflies; a total of 28 genera were represented). Dominant algae were diatoms, many known as sensitive species. Functional endpoints were also investigated including photosynthesis, organic matter processing, in situ biodegradation, organism drift, insect emergence.

3) The model ecosystem study was longer than most chronic toxicity tests(approximately 4 months duration). Colonization of the streams, leading to stable, consistent and testable communities, was for 10 weeks with exposure of stream communities to LAS was for 8 weeks. Repeated sampling insured ecological and toxicological shifts were tracked.

4) The exposure to LAS was verified weekly and found to be nearly 100% of nominal. For example, the streams exposed to nominal concentrations of 0.300 and 3.000 mg/L were measured at 0.293 mg/L and 2.973 mg/L, respectively. A dynamic sorption model based on detailed weekly investigations of sorption, daily evaluations of suspended solids, and weekly assessments of DOC, TOC were used to express exposure based on the free fraction of dissolved LAS.

5) The study is relevant to natural systems. Studies by the sponsor demonstrated the model ecosystem was nearly indistinguishable from the source system and representative streams that were relatively uninfluenced by man. Dyer and Belanger (1999) showed ESF stream communities were as or more sensitive than >80% of streams in Ohio surveyed at >1200 locations from the period of 1985-1995. The more sensitive systems were Appalachian mountain slope, first or second order systems that never have seen effect or been exposed to human influences to any degree. Peterson et al. (2001) and Morrall et al. (2006) demonstrated community function of the test system was similar to that of low order streams across the globe (including systems outside of the United States) and that predator-prey relationships in the ESF were equivalent to the source river used to deliver water to the streams.

In summary, the NOEC of LAS measured from the ESF model ecosystem study was equal to 293 µg LAS/L which corresponds to 268 µg LAS/L as free (dissolved and not associated with organic or particulate matter). Further, an Application Factor (AF) of 1 is justified, especially when viewed in concert with the chronic toxicity Single Species Sensitivity Distribution (SSD) HC₅of 0.21 mg/L. Based on this data, the PNECfreshwater was calculated as the model ecosystem study NOEC/1 or 0.268 mg LAS/L.

To calculate the PNECmarine the aquatic NOEC of 0.268 mg/L from the model ecosystem study was used as a starting point. The AF for the marine PNEC is generally 10 applied to the PNECaquatic resulting in a PNECmarine of 0.0268 mg/L. This AF is considered appropriate given the detailed literature reviews regarding marine and freshwater organism sensitivity to LAS (Temara et al., 2001). Temara and coworkers provided conclusions that were similar to observations from van de Plaasche et al. (1999), but with additional data to derive a chronic marine SSD to compare with a chronic freshwater SSD. In these investigations, the sensitivity of marine taxa versus freshwater is typically 10-fold, consistent with the AF consistent with principals described in the   REACH Technical Guidance Document Sections R.10.3.2.3 (Calculation of PNEC for marine water).

Finally, the PNEC intermittent releases was calculated as normal by using the lowest acute LC50 value and applying an AF of 100 to get a final PNEC intermittent releases value of 0.0167 mg/L.

References not cited in Annex 1

Belanger, S.E. et al., 2002.Integration of aquatic fate and ecological responses to linear alkyl benzene sulfonate (LAS) in model stream ecosystems. Ecotox. Env. Saf. 52:150-171.

Dyer, S.D. and Belanger, S.E., 1999. Determination of the sensitivity of macroinvertebrates in stream mesocosms through field-derived assessments. Env. Tox. Chem. 18(12):2903-2907.

ECETOC (European Center for Toxicology and Ecotoxicology), 1997. The value of aquatic model ecosystem studies in ecotoxicology. ECETOC Technical Report No. 73.

Giddings, J.M. et al.(Eds.). 2002, Community Level Aquatic Systems Studies Interpretation Criteria. SETAC Press, Pensacola, FL.

Morrall, S.W. et al., 2006. Removal and environmental exposure of alcohol ethoxylates in US sewage treatment. Ecotoxicol. Environ. Saf. 64(1):3-13. 

Peterson, B.J. et al., 2001. Control of nitrogen export from watersheds by headwater streams. Science 292:86–90.

Temara, A. et al., 2001. Marine risk assessment: linear alkylbenzenesulponates (LAS) in the North Sea. Mar. Pollut. Bull. 42(8):635-42.

van de Plassche, E. J. et al., 1999. Predicted no-effect concentrations for four surfactants: linear alkyl benzene sulfonate (AES), alcohol ethoxylates (AE), alcohol ethoxylated sulfates (AES) and soap. Env. Tox. Chem. 18(11):2653-2663.  

PNECs for the terrestrial environment

A review of studies on the toxicity of LAS to soil macro-organisms and terrestrial plants was conducted in order to determine a PNEC in soil. Nine invertebrate and 12 plants studies were used to calculate the PNEC. Full references for all studies used are provided below. In all the plant experiments, LAS was added as an aqueous solution, and the most sensitive endpoint, growth, was used in calculated the PNEC. In cases where a NOEC or an EC10 value was not reported, the original data or graphical estimations were used to calculate the EC10. This was considered more appropriate than using an arbitrary extrapolation factor. Invertebrate data was based on 9 chronic studies. In cases where there was more than one study on a particular species, a geometric mean of the data was used. The data for both sets of studies were merged as the sensitivity of both types of species were similar. This was confirmed by the Kolmogorov-Smirnov test. The species sensitivity distribution was then calculated. From this, the concentration that would exceed the NOEC or EC10 for 5% of species (HC5) was calculated (HC5).

Based on this methodology, the HC5 was determined to be 35.3 mg/kg soil dry weight (dw). The 95% confidence interval was 18.6 -50.0 mg/kg soil dw. The PNEC for soil is therefore 35 mg/kg soil dw. The data used to calculate the PNEC is presented below.

The approach used to derive the soil PNEC value is detailed in a publication by Jensen et al. (2007).

  Data used in the determination of a soil PNEC  

Species	Endpoint	EC10 (mg/kg soil)	EC50 (mg/kg soil)	Reference
Plants
Malva pusilla	Growth	110	204 (14-d)	Marschner, 1992
Solanum nigrum	Growth	120	169 (14-d)	Marschner, 1992
Chenopodium album	Growth	120	164 (14-d)	Marschner, 1992
Amaranthus retroflexus	Growth	110	142 (14-d)	Marschner, 1992
Nigella arvensis	Growth	52	133 (14-d)	Marschner, 1992
Galinsoga parviflora	Growth	55	90 (14-d)	Marschner, 1992
Brassica rapa	Growth	86	164 (14-d)	Gunther and Pestemer, 1992 Marschner, 1992
Avena Sativa	Growth	80	300 (14-d)	Gunther and Pestemer, 1992
Sinapis alba	Growth	200	300 (14-d)	Gunther and Pestemer, 1992
Sorghum bicolour	Growth	68	167 (21-d)	Windeat (1987)
Helianthus annus	Growth	116	289 (21-d)	Windeat (1987)
Phaseolus aureus	Growth	126	316 (21-d)	Windeat (1987)
Invertebrates
Eisenia foetida	Growth (14-d)	277		Swigert, 1989
Aporrectodea caliginosa	Reproduction	46		Krogh et al., 2007
Enchytraeus sp.	Reproduction	27		Holmstop and Krogh, 2001 Krogh et al., 2007
Folsomia fimetaria	Reproduction	107.6		Holmstrup and Krogh, 1996 Holmstrup et al., 2001 Jensen and Sverdrup, 2002
Folsomia candida	Reproduction	205		Krogh et al., 2007
Isotoma viridis	Growth	41		Jensen et al., 2001
Hypogastrura assimilis	Reproduction	100		Holmstrup and Krogh, 2001
Hypoaspis aculeifer	Reproduction	82		Holmstrup and Krogh, 2001
Platynothrus peltifer	Reproduction	320 (NOEC)		Jensen et al., 2001

References not cited in Annex 1

Jensen, J. et al., 2007. European risk assessment of LAS in agricultural soil revisited: Species sensitivity distribution and risk estimates. Chemosphere 69:880-892.

Conclusion on classification

The lowest acute data point for MEA-LAS is a 96 h LC50 value of 2.22 mg/L in Pimephales promelas (Belanger and Brill, 2006). The lowest chronic data point is a 56 d NOEC of 0.268 mg/L from a mesocosm model ecosystem (Belanger, 1997, 2002 and 2004; Lower, 1996). Given that MEA-LAS is readily biodegradable, the substance therefore qualifies for classification as Aquatic Chronic 3 – H412 (Harmful to aquatic life with long-lasting effects) according to EU CLP (1272/2008/EC) criteria.