Modelleren én metenén meten · 4 the ART of exposure assessment NVvA Symposium, 24 maart 2010....

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Modelleren én meten Modelleren én meten Wouter Fransman, Erik Tielemans

Transcript of Modelleren én metenén meten · 4 the ART of exposure assessment NVvA Symposium, 24 maart 2010....

Page 1: Modelleren én metenén meten · 4 the ART of exposure assessment NVvA Symposium, 24 maart 2010. ART approachART approach ... with contextualwith contextual information Model Similarity

Modelleren én metenModelleren én meten

Wouter Fransman, Erik Tielemans

Page 2: Modelleren én metenén meten · 4 the ART of exposure assessment NVvA Symposium, 24 maart 2010. ART approachART approach ... with contextualwith contextual information Model Similarity

Programma workshopProgramma workshop

1) Algemene introductie ) g-Erik-

2) ART voorbeelden -Wouter-

3) Toekomstige ontwikkelingen / rol NVvA (?)3) Toekomstige ontwikkelingen / rol NVvA (?) -Erik-

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Nieuwe ontwikkelingenNieuwe ontwikkelingen

• REACH geeft modelontwikkeling een nieuwe impulsg g pTier 1: Ecetoc TRA, BAuA tool, StoffenmanagerTier 2: Advanced REACH Tool

• Nieuwe meetstrategie in ontwikkelingBOHS – NVvA initiatief

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Making full use of informationMaking full use of information

?ai

nty

+ BDA

Unc

erta + BDA

Model Data Updated estimateModel Data Updated estimate

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ART approachART approach

Exposure database, with contextualwith contextual

information

Model Similarity module to select data for risk

assessment

Bayesian process to combine data

and model outputand model output

Exposure estimatesExposure estimates for risk assessment

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Mechanistic model ART

9 Modifying Factors (MF):

- Intrinsic emission potential (E)- Activity emission potential (H)Equations:- Local controls (LC)- Separation (Sep) - Segregation (Seg)RPECCC ffnft ⋅+= )(

Equations:

g g ( g)- Surface contamination (Su)- Dilution (D)- Personal behavior (P)

nfnfnfnfnfnfnf DSuPLCHEC ⋅+⋅⋅⋅= )(

ffffffffffffffff SepDSuSegLCHEC ⋅⋅+⋅⋅⋅= )( Personal behavior (P)- RPE

ffffffffffffffff

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Hierarchical structuringHierarchical structuring

Modifying Factor 1 Modifying Factor 2 Modifying Factor 3

Underlying determinants

Underlying determinants

Underlying determinants

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Substance Emission Potential (dustiness)Substance Emission Potential (dustiness)

Category Relative g yweight

Firm granule 0.01

Granule 0.03

Coarse dust 0.1

Fine dust 0.3

E t l 1 0Extremely fine dust

1.0

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Activity Emission PotentialActivity Emission Potential

Powders

Liquids

Solid objects

Hot / molten metal

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local controlslocal controls

• No localized controls

• Suppression techniques• Wetting at the point of release• Knockdown suppression (post generation suppression)

• Containment (non-extracted)

• Local ventilation systems Efficacy = 0.5Local ventilation systems• Receiving hoods

• Canopy hoods (hot processes)• Other receiving hoods

• Capturing hoodsEfficacy = 0.0001

• Fixed• Movable• On-tool (integrated) extraction

• Enclosing hoods• Glove boxGlove box• Fume cupboard• LEV systems with partial enclosure (no front cover)

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Page 12: Modelleren én metenén meten · 4 the ART of exposure assessment NVvA Symposium, 24 maart 2010. ART approachART approach ... with contextualwith contextual information Model Similarity

DispersionDispersionQFF Q

NFNF εTIndoor

Outdoor

Spray booth

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Calibration with measurementsCalibration with measurements

• Using multiple sourcesg pAlso including measurements in the low range

• Only good quality data: N~2,500

• Quantification in units (mg/m3)

• Provides model uncertainty

S t di ti f• Separate predictions for:DustVapourMistMistFumes PhD Jody Schinkel

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Bayesian modelBayesian model

• Bayesian techniques allow for different y qtypes of information to be integrated in a theoretically rigorous way via probability theorytheory

• Bayes approach takes account of the relative strength of the different information sources

• Bayesian module is integrated in ART to update model estimate with user’s own data

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Hierarchical exposure modelHierarchical exposure model

• Between company variabilityp y y

• Between worker variabilityComp-1 Comp-2 Comp-n

• Within worker variabilityComp-1 Comp-2 Comp-n

Worker-1 Worker-2 Worker-n

Day-1 Day-2 Day-n

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Weight of EvidenceWeight of Evidence

• Large sample size

• Multiple companies

>> Small sample sizes

>> Single company• Multiple companies

• Uniform measurement series

>> Single company

>> Heterogeneous measurement series

• Analogous data >> Partially analogous data

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ART - outputART output

• Explicit treatment of variability and uncertaintyPercentile of distributionUncertainty of estimateUncertainty of estimate

Variability

Uncertainty90th , 75th , 50th percentile

y

Inter quartile 80 % 90 % 95 % CINVvA Symposium, 24 maart 2010the ART of exposure assessment17

Inter-quartile, 80 %, 90 %, 95 % CI

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Contributions from…Contributions from…

• Health & Safety Executive

• Dutch Ministry

• CEFIC LRI

• Afsset

• Shell

Eurometaux• Eurometaux

• BOHS

• GlaxoSmithKline

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Acknowledgement – external expertsAcknowledgement external experts

• S. Bailey (GSK, UK)• D Brouwer (TNO The Netherlands)D. Brouwer (TNO, The Netherlands)• M. Byrne (University of Galway, Ireland)• D. Dahmann (Bochum University, Germany)• J. Dobbie (BP, UK)• D. Gazzie (Industrial Health Control, UK)• A. Gillies (Gillies Associates Ltd, UK)( , )• E. Joseph (GSK, UK)• I. Kellie (OHS Scotland Ltd, UK)• D. Mark (HSL, UK)• P. McDonnell (University of Galway, Ireland)• M. Newell (Bayer Crop Sciences, UK)• M. Nicas (University of California, USA)• D. O’Malley (Genesis Environmental Ltd, UK)• M. Piney (HSL, UK)• A. Robertson (IOM, UK)• J. Saunders (HSL, UK)

M Smith (Ba er Crop Sciences UK)• M. Smith (Bayer Crop Sciences, UK)• H. Tinnerberg (Lund University, Sweden)• H. Westberg (Örebro University Hospital, Sweden)• A. Wolley (Wolley Associates, UK)• J. Wren (GSK, UK)• D Iddon (Lilly UK)• D. Iddon (Lilly, UK)• D. Noy (Dow chemicals, NL)• J. Urbanus (Shell, NL)• R. Battersby (EBRC consulting, Germany)

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d d h lwww.advancedreachtool.com

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