1. And the Accuracy of the HERA Environmental Risk Assessment Kay Fox SEAC Environment, Unilever Chair - HERA Environment Task Force

2. Claudia Poelloth - AISE C. Arregui Petresa C. Stevens Dow Corning G. Boeije P&G R. van Egmond Unilever H. Certa Condea Chemie R. van Wijk Akzo Nobel R. Elsmore McBride T. Wind Henkel K. Fox Unilever A. Aarts Solutia P. Masscheleyn P&G A. Berends Solvay P. Richner CIBA D. Calcinai Condea Augusta W. Schul BASF E. Cerbelaud Rhodia J. Steber Henkel V. Koch Clariant R. Toy Shell Chemicals Environment Task Force

3. Initiatives on High Production Volume (HPV*) Chemicals n Collect and generate hazard data n Produce hazard assessments ICCA Global Initiative, 1998 - 2004 US initiative on HPV (EPA, 1998) * Defined as greater than 1,000 tons/year in Europe and 1 million pounds / year in the U.S.

4. Hazard data only is NOT sufficient to provide reassurance about the SAFETY of chemicals to the Authorities and the public

5. Sensible Risk Management......can only be done within a framework of risk assessment, taking into account both –the hazards of the material AND –the consumer and environmental exposure

6. EU Risk Assessments n Available for only a very small number of substances n lengthy, complex process  increase the pace through focussed risk assessments for certain sectors, e.g. household detergents and cleaning products

7. n Joint European initiative between –suppliers of detergent raw materials (CEFIC) and –the manufacturers of detergents (AISE) n to perform targeted - or focussed - risk assessments on substances of interest to the detergents industry

8. Risk Assessment  focus on chemicals that are used primarily in household detergents and cleaning products  focus on “consumer / private use”  focus on intended use but also consider foreseeable misuse and accidental use  focus on environmental compartments potentially at risk through “household use” of detergent & cleaning products

9. Phase I Develop methodology for HERA risk assessments Objective : rapid & efficient, but still good, sound science Work on example substances Objective : demonstrate feasibility for Regulators Industry All interested parties Phase II - Apply to a wider range of substances

10. Phase 1 Selection for “developing” the methodology: –Alkyl sulphates –Zeolites –Optical brightener FWA-5

11. O S O O O O - Na + Alkyl Sulphate (AS) an example - linear C12 CH=CH OSO 2 Na NaO 2 SO FWA -5

12. Methodology - Environment 1. Collect Hazard, Exposure, and Physical and Chemical data from Producers Formulators 2. Using the Detergent Scenario Spreadsheet, enter the data into EUSES (based on TGD for European Risk Assessment), with modified (AISE) exposure scenario 3. Use a tiered approach to evaluate safety, or identify further data needs

13. Collect Hazard, Exposure, and Physical and Chemical data from Producers and Formulators Chemical characterisation - What is the chemical? - Distribution of components (e. g. chainlengths, isomers?) - Uncertainty? Tonnage of the chemical - How much is released to the environment? - Uncertainty?

14. Chemical characterisation Optical brightener FWA-5 One chemical structure, one CAS number, no problem! Zeolites Several types, but one type has the majority of the detergent market Alkyl sulphates 16 CAS numbers! (Selected from 46!) AS used in detergent products are mixtures of several homologues

15. Tonnage Released Optical brightener FWA-5 One producer, participant, no problem! Recent range 500 - 900 tonnes per year (600 in RA) Zeolites Several producers - main use - detergents Production data from ZEODET Alkyl sulphates European production data from several sources Formulator data Tonnes product sold per year % chemical in product

16. Detergent ingredient usage data - Zeolites 650 000 tonnes taken for HERA RA. Uncertainty - 10%.

17. n Preliminary industry estimates indicate the total Alcohol Sulphate tonnage is around 120,000 tonnes/year in Europe - preliminary validation of these data indicate a probable over estimation of volumes. n It is estimated that 100,000 t/y is used in household detergents and cleaning products, whereas the remaining 20,000 t/y is used in personal care and other applications. Detergent ingredient usage data - AS

18. Detergent ingredient usage data - Uncertainties n +15 000 tonnes per annum? n AS is a significant component in AES –20% to 40% AS in AES, depending on product grade –AES tonnage exceeds AS tonnage AS in AES must be included in the AES risk assessment (definition of a substance). Thus it is not included in the AS risk assessment.

19. Uncertainties Chemical Characterisation and Tonnage Uncertainties must be addressed for each HERA substance in the HERA Risk Assessment Report. Annual tonnage uncertainties can be better than + 15% for high volume chemicals. Lower tonnage chemicals with a very specific use may have larger annual tonnage fluctuations. How good is 1998? Is 1992 similar to 1998?

20. I will NOT discuss: Hazard Data How good are the experimental data? How appropriate are the application factors? EUSES Sensitivity Analysis ( RIVM, esp. Kow ) Agreement of predicted and measured environmental data ( Schwartz, Northrhine-Westphalia)

21. Detergent exposure scenario for EUSES n Wide dispersive use, Detergents (5, 9) n 100% of chemical to sewer (Local Use model) n Tiered Methodology –EUSES Defaults –Replace selected defaults if necessary Removal values in STP Measured Kd values Biodegradation rates in rivers, soil, etc.

22. STD. EU Region Local treatment plants

23. The standard EU region has 10% of the EU detergent consumption - for 5.4% of the EU population.

24. Detergent consumption per person in eighteen European countries in 1998, compared with the average European detergent consumption (Europe 18)

25. STD. EU Region Local treatment plants 4 TGD - Local plant

26. Modified Exposure Scenario - HERA TGD - A reasonable worst case treatment plant will receive 4 times the average load B (representative detergent ingredient) 90th %ile < 1.5 times the average.

27. Modified Exposure Scenario - AISE TGD - Worst case (4) times worst case (~2) gives almost 8 times the average ingredient loading to a local sewage treatment plant. AISE Scenario - Data backed “worst case” (1.5) times “worst case” (~2) shows three times the average ingredient loading to a local sewage treatment plant. Paper on the 1.5 factor submitted for publication in Chemosphere, and for the TGD revision, via ECETOC.

28. Grouping - Alkyl Sulphate Preliminary European Industry Estimates Data to be validated. Much, but not all, experimental data has been obtained from tests on commercial grade materials. Linear 351525 Linear and Mono- branched 15 35 Some 2 branching

29. QSAR and Measured data AS - Phys Chem properties Na salts Illustrative Example

30. Detergent scenario for EUSES n Phys Chem properties - –Is EUSES sensitive to property being represented by QSAR? If not, use QSAR! –If EUSES is sensitive, then how good is the QSAR? logK ow among the better QSARs uncertainty often within factor of 3 different uses of logK ow in EUSES - check out each! QSAR and interpolated (extrapolated?) data

31. Grouping Any grouping used in an individual HERA risk assessment must be fully explained in the risk assessment documentation. Sensitivity to predicted parameters, and the uncertainty in the risk assessment due to their use, must be fully documented.

32. HERA - Methodology Must: n Involve all producers and formulators n Identify all relevant sources of chemical n Consider Uncertainty –Tonnage data –Measured data –QSARs and inter/extrapolations –methodology (EUSES) n Be acceptable to scientists and regulators