The Advanced REACH Tool (ART) is a generic higher tier tool developed to estimate occupational exposure that incorporates both measurement data and modeling. It uses a mechanistic model based on earlier work by Cherrie and Schneider that considers nine modifying factors that influence exposure. ART integrates this model with a user's own exposure data using Bayesian statistics to provide probabilistic exposure estimates along with uncertainties. Key developers of ART include scientists from TNO, IOM, HSL, BAuA, and other organizations.

1. The Advanced REACH ToolJohn Cherrie

2. Summary…BackgroundThe concept of ARTThe mechanistic model toolDispersion, an example of the work to underpin the modelBayesian updatingModel output

3. Background…ART is a generic higher tier toolIncluded in the REACH GuidanceApplicable for exposure to dust, vapour, mist, and fumesCo-development project funded by:Shell, GSK, Eurometaux, CeficHSE, Dutch government, AfssetBOHSDelivered by:TNO, IOM, HSL, BAuA, UU and NRCWE

4. The conceptual basis…Based on the premise that both models and measurement data can be informative about exposureSet within a Bayesian framework

5. Combining data reduces uncertainty+BDAUncertaintyModel Data Updated estimate

6. The ART approach…Exposure database, with contextual informationModel Similarity module to select data for risk assessmentBayesian process to combine data and model outputExposure estimates for risk assessment

7. Modelling the exposure distributionScenarioMedian exposureMechanistic modelInformation from meta-analysisExposure variability

8. Model specification…Between-companyvariability- Between-workervariability- Within-workervariability

9. Underpinning the mechanistic model…The early work by Cherrie, Schneider et alDeveloped a model for use in epidemiological studiesMultiplicative deterministic modelNear-field/Far-fieldRelied on the assessor to choose the parametersValidated in a number of different situationsDispersion parameters derived from a 2-box modelCherrie and Schneider. (1999) Validation of a new method for structured subjective assessment of past concentrations. The Annals of Occupational Hygiene;43 (4):235-245.Cherrie. (1999) The effect of room size and general ventilation on the relationship between near and far-field concentrations. Applied occupational and environmental hygiene; 14 (8): 539-46.

10. An example of the use of this model…1000.0100.010.0Estimated exposures (ppm)1.00.0010.00.11.010.0100.010.10.010.001Measured exposures (ppm)

11. Validation of the model…

12. The ART mechanistic model…

13. The mechanistic model…Far-fieldSource barrierPersonal barrierSurfacesLCIRSource2ndPersonal behaviourNear-fieldRPEInhalation boundry

14. Nine modifying factors…Intrinsic emission potential (E)Activity emission potential (H)Local controls (LC)Separation (Sep) Segregation (Seg)Surface contamination (Su)Dilution (D)Personal behavior (P)RPE

15. Three basic equations…

16. Substance emission potential…

17. Substance emission potential…Partial vapour pressure of substance i in mixtureMole fractionVapour pressure of substance iActivity coefficientUNIFAC

18. Activity emission potential…PowdersLiquidsSolid objectsHot / molten metal

20. Local controls…No localized controlsSuppression techniquesWetting at the point of releaseKnockdown suppressionContainment (non-extracted)Local ventilation systemsReceiving hoodsCapturing hoodsEnclosing hoodsEfficacy = 0.5Efficacy = 0.0001

21. Dispersion…QFFQNFeTIndoorOutdoorSpray booth

22. Calibration with measurements…Using multiple sourcesAlso including measurements in the low rangeOnly good quality data: N~2,500Quantification in units (mg/m3)Provides model uncertaintySeparate predictions for:DustVapourMistFumes

24. Bayesian updating…Bayesian techniques allow for different types of information to be integrated in a theoretically rigorous way via probability theoryBayes approach takes account of the relative strength of the different information sourcesBayesian module is integrated in ART to update model estimate with user’s own data

26. ART output…Explicit treatment of variability and uncertainty

27. Percentile of distribution

28. Uncertainty of estimateVariabilityBayesian update90th , 75th , 50th percentileUncertaintyInter-quartile, 80 %, 90 %, 95 % CI