Exposure Data Tools - Current Situation in Europe

1. Exposure Data Tools - Current Situation in Europe Gerhard Heinemeyer Federal Institute for Risk Assessment Berlin, Germany 2003 ISEA Annual Meeting, Stresa Italy Federal Institute for Risk Assessment

2. Measurements Substance Source Release Distribution Deposition Disappearance People Behaviour Anthropometrics Steps in Exposure evaluation Model Model variables Scenario Exposure Factors Exposure Descriptions/ Characterizations transformation of Scenario to formula Data to feed the model Federal Institute for Risk Assessment

3. Claims for Exposure Assessments • Scientific state • Evaluation of scenarios, models & exp. factors? • do they and the tools resemble reality? • New developments? • Regulatory requirements • Agreement upon certain approaches(incl. Models and data to be taken) Federal Institute for Risk Assessment

4. I.Scenario descriptions Federal Institute for Risk Assessment

5. Scenario Descriptions (first step of exposure analysis) • Can be characterized from use instructions • Use of categories of use is recommended(e.g. use of textile as carpet, cloth, furniture) • Models can be defined according to scenarios • The exposure factors needed can clearly be described • Harmonization is needed Federal Institute for Risk Assessment

6. Where can scenario descriptions be found? • EU Technical Guidance Document • EPA Exposure factors handbook • Food consumption surveys (image scenarios for food uptake) • ETAD reports (Textile emissions) • RIVM monographs (paints, toys, biocides) • Biocide TGD-draft • Literature • other publications (example Germany) Federal Institute for Risk Assessment

7. II.Model evaluations Federal Institute for Risk Assessment

8. Needs for Consumer Exposure Estimation • Source:Amounts of substances in products, reIeases, uses • Disposition of substance:Identification of release, distribution, ad- and desorption, disappearance • Contact:Behaviour of exposed person,contact times, frequencies, durations Federal Institute for Risk Assessment

9. Models • A number of models have been developed based on published literature • OECD has prepared an inventory of models • A limited number of tools are regularly used for exposure evaluation e.g.: • EU: EUSES, CONSEXPO, EASE • US: SCIES; CEM, MCCEM, THERdBASE • Validation remains a problem Federal Institute for Risk Assessment

10. Comparison of models • Comparative evaluation of models do not exist • Which model for which exposure?Different concepts for the same problem • Computer tools as „black boxes“ • Recalculation of models with other tools is practically not possible, complete algorithms have not been published Federal Institute for Risk Assessment

11. III.Source Data Federal Institute for Risk Assessment

12. Needs for Consumer Exposure Estimation • Source data • Weight fraction (amount) of substance in the product • Releases • Amount of residual monomers • Use data • Frequencies • Durations Federal Institute for Risk Assessment

13. Datapools for sources of exposure Product information • Why is product information important? • The extent of exposure is direct proportional to the amountof substance in the product. • Frequencies and durations of use can modulate the emissions of the substances from the products Federal Institute for Risk Assessment

14. Datapools for sources of exposure Information about preparations • Product registers • Switzerland, the nordic countries, Italy,Germany • Poison Information Centres have product information • Safety Data Sheets, Information brochures from industry • Literature • Rules for gathering data are not harmonised • different regulations • no common formats Federal Institute for Risk Assessment

15. Datapools for sources of exposure Information about articles • Furniture, clothings, carpets, buildings, cars, toys etc. • The extent of exposure is direct proportional to the amount of substance that is released by the product but • Knowledge about substances in articles is limited (downstream users are not aware on the compositions) • Knowledge about release is also very limited • Measurements in air or dust sometimes give hints for releases from articles for certain substances (e.g. Flame retardants, PAH, heavy metals, pesticides) • No common data pool Federal Institute for Risk Assessment

16. Substances in food • We have national surveillance programs for controlling substances (as contaminants) in food by institutions publishing these data • National food consumption studies • Data need to be updated • Studies should be harmonised Federal Institute for Risk Assessment

17. Food Monitoring surveillance programme in Germany • National programme measuring substances in food according to a prefixed schedule • contamination of 282 chemicals • 137 different categories of food, focus on • heavy metals • chlorinated hydrocarbons • pesticides • over a period of 12 years Federal Institute for Risk Assessment

18. IV.Peoples behaviour and Anthromopetrics Federal Institute for Risk Assessment

19. Needs for Consumer Exposure Estimation • Antropometric data • total population • subpopulations Behaviour data (e.g.) • staying inhouse • staying outside • staying at workplace • certain behaviours of subpopulations (focus on children, e.g. playing with toys, sucking) Federal Institute for Risk Assessment

20. Behaviour data • People do influence their own exposure by behaviour • variations in product uses • frequencies, durations • variations in contacts with chemicals • time pattern, staying home etc. • Age dependent behaviours • hand to mouth contacts • Children • eating at the workplace • hygiene during preparation of food Federal Institute for Risk Assessment

21. Anthropometric Data • Lots of compilations about body weights, heights, and surfaces exist • Regional differences to be mentioned • North to South to West to East Europe • Scientific and regulation aspects may deviate considerably Federal Institute for Risk Assessment

22. Compilations that provide anthropometric data • EPA exposure monographs incl. Handbooks • AIHC exposure factors handbook • ECETOC Exposure factors sourcebooks • RIVM monographs (national data) • Standards zur Expositionsabschätzung (national data) • EU Technical Guidance Document • Annals of the ICRP (Intern. Comm. On Radiological Protection) • many data have been written out from other secondary sources ... Federal Institute for Risk Assessment

23. What about secondary literature - body weight • Albania 61,07 • Bosnia-Herzegovina 61,70 • Croatia 61,70 • Macedonia 61,07 • Malta 61,07 • Portugal 61,07 • Slovenia 61,07 • Italy 73,23 • Spain 73,23 • Yugoslavia 75,28 • Greece 76,13 Source: WHO, cited in ECETOC Technical Report Federal Institute for Risk Assessment

24. Children represent a special group of exposed persons • Physiological differences (children are no little adults) • Development (qualitative changes of toxicity during childhood) • Mouthing behaviour • Quantification is difficult Federal Institute for Risk Assessment

25. Information about children • Scientific literature • US-EPA • Danish EPA • some publications from RIVM • workshops • hundreds of publications covering children‘s exposures and dealing with specific questions, but comprehensive collections of high quality information is scarce Federal Institute for Risk Assessment

26. Data sources for exposure assessments in children Cohen Hubal et al, Env. Health Persp. 2003 • insufficient data on children's exposures and activities • multimedia exposures to environmental contaminants cannot be assessed • default assumptions are taken for exposure assessments • reduction of uncertainty in the assumptions and exposure estimates is needed Federal Institute for Risk Assessment

27. V.Quality aspects Federal Institute for Risk Assessment

28. Level of quality Default Worst case Single point estimates Very conservative and hypothetical values High degree of uncertainty 50th percentile 99th percentile Whole distribution Distribution based 50th percentile 99th percentile High quality data are representative, they characterize the range and variability Federal Institute for Risk Assessment

29. Data quality? Transparency Representativeness Validation Federal Institute for Risk Assessment

30. RIVM quality factors 1 2 4 7 2 3 0 0 0 9 Not questionable 8 good value, discussion possible 7 enough space 6 useful, improvement needed 5 doubtful, can be used as a default 4 doubtful, can not be completely used a default 3 bad value, not useful as a default 2 useless, but nearer conceivabilities 1 useless, no conceivabilities Federal Institute for Risk Assessment

31. Data quality of some exposure factors Body weight and height formulations physiologic data use descriptions food consumption time patterns house and room characteristics room ventilation dermal uptake data dust and soil uptake hand to mouth emission rates migration of substances in material etc. Level of quality Federal Institute for Risk Assessment

32. Future aspects (under the aspects of regulation) • Exposure factors and exposure data compilations with the objective for • Standardization • Harmonization • Completeness • Representativeness • Ranges • Uncertainty and Variability • Compile a network for continous update • Data mining (inventory of exposure data) Federal Institute for Risk Assessment

33. The needs we have for exposure assessments only partly meetthe tools Lots of data have been evaluated but they are not available unless they are published in a regular way or otherwise widely available (e.g. per internet) Federal Institute for Risk Assessment

34. Thank you for attention Federal Institute for Risk Assessment

35. Transparent presentation • Criteria for data compilations are transparent and well understood • source, method of analysis • Standardized methodology has been used • Original literature, secondary to be avoided • The procedure can be repeated easily by other people than the authors • e.g a model can by easily be recalculated (many of the computer tools for exposure analysis are „black boxes“) • overinterpretation of data from literature which does not meet the intention of the paper Federal Institute for Risk Assessment

36. Representativeness • Data have been evaluated using standard epidemiologic and statistical methodology • The selection of the study population has been performed by a transparent procedure • Confounders have been considered • Correlation of compared data is checked Federal Institute for Risk Assessment

37. Validation • The result obtained by modelling will be similar to measurements obtained under comparable conditions (same scenario) • Sensitivity analysis The influence of variables that have great or low influence in the model that is used is analysed and well described Federal Institute for Risk Assessment

38. Institutes and Organisations Publishing Data about Exposure in Germany • Superior federal institutions • UBA, BfR, BAM etc. • Institutions of Federal states • Federal state scientific institutions (e.g. universities) • Public foundations • Industry and manufacture • Private associations and foundations • Non governmental organisations • Private laboratories Federal Institute for Risk Assessment