Federal Institute for Risk Assessment1 Exposure Data Tools - Current Situation in Europe Gerhard Heinemeyer Federal Institute for Risk Assessment Berlin,

Federal Institute for Risk Assessment 1

Exposure Data Tools - Current Situation in Europe

Gerhard Heinemeyer

Federal Institute for Risk Assessment

Berlin, Germany2003 ISEA Annual Meeting, Stresa Italy


Exp

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Exposure Factors

Source

Distribution

Release

Deposition

Disappearance

Behaviour

Anthropometrics

Substance

People

Steps in Exposure evaluationScenario

Model Model variables

Descriptions/Characterizations

transformation ofScenario to formula

Data to feed the model

Measurements


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)


I.Scenario descriptions


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


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)


II.Model evaluations


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


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


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


III.Source Data



Source data Weight fraction (amount) of substance in the

product Releases Amount of residual monomers Use data

Frequencies Durations


Datapools for sources of exposure

Product information Why is product information important? The extent of exposure is direct proportional to the amount

of substance in the product.

Frequencies and durations of use can modulate the emissions of the substances from the products

kAE mountxp *


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


Datapools for sources of exposureInformation 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


Substances in food

We have national surveillance programs for controlling substances (as contaminants) in food by institutions publishing these data

National food consumption studiesData need to be updatedStudies should be harmonised


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


IV.Peoples behaviour

and

Anthromopetrics



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)


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


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


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 ...


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


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


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


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


V.Quality aspects


Very conservative and hypothetical valuesHigh degree of uncertainty

Default

Worst case

50th percentile

Whole distribution

Leve

l of

qual

ity

Sin

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poin

t es

timat

esD

ist r

ibu t

i on

bas

ed

99th percentile

50th percentile 99th percentile

High quality data are representative, they characterize the range and variability


Data quality?

ValidationRepresentativeness

Transparency


RIVM quality factors9 Not questionable8 good value, discussion possible7 enough space6 useful, improvement needed5 doubtful, can be used as a default4 doubtful, can not be completely

used a default3 bad value, not useful as a default2 useless, but nearer conceivabilities1 useless, no conceivabilities

1

2

4

7

2

3

0

0

0


Data quality of some exposure factors

Body weight and heightformulations

physiologic datause descriptionsfood consumption

time patternshouse and room characteristics

room ventilationdermal uptake datadust and soil uptake

hand to mouth emission rates

migration of substances in materialetc.

Level

of

quality


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)


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 wayor otherwise widely available (e.g. per internet)


Thank you

for attention


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


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


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


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

Documents

Federal Institute for Risk Assessment1 Exposure Data Tools - Current Situation in Europe Gerhard Heinemeyer Federal Institute for Risk Assessment Berlin,