Tiered approaches are used to assess chemical exposure. Tier 1 tools like EASE are conservative but have limited validity. Tier 2 tools should provide reliable assessments using measurements and models. The Advanced REACH Tool aims to maximize data use by combining measurements and model estimates, but validation is still needed. Overall, a range of tools are available but more information is needed on their comparability and validity.
2. Summary… Exposure scenarios – what’s their purpose and how should they be specified? Measurements and models The tiered approach and available tools EASE – the rise and fall Sons of EASE – Tier 1 tools ECETOC TRA MEASE Stoffenmanager The next step – a Tier 2 tool ART
5. Measurements and models… REACH allows the use of both measurement sand models Measured data for the actual substance Measured data for analogous/surrogate substances/activities Modelled estimates. Presumption that measurements are “better” Assessment should be conservative
6. Measurement quality High quality median or 90th percentile from 26 personal sampling measurements under conditions representative of the ES Intermediate quality mean from 3 measurements with personal sampling for the ES Lower quality a value given only as a mean – no details of number of measurements etc, especially if it is not fully representative of the activity described in the ES
7. Measurements and models… Where does a model sit in relation to measurement quality? How can we maximise the approach of modelling and measurement?
8. Tiered approach to models… Tier 1 Very conservative With limited work to underpin their validity Tier 1+ Slightly more refined models Better validity Tier 2 Should provide a reliable assessment With good level of validity
9. Available tools… ECETOC TRA (EASE) EMKG Exposure Assessment Tool (COSHH-Essentials) MEASE (EASE) Stoffenmanager (Cherrie et al model) RISKOFDERM calculator
10. EASE… “Estimation and Assessment of Substance Exposure” Rule-based “expert” system Generic tool Developed for the pre-REACH regulatory risk assessment systems in Europe Inhalation and dermal exposure Based on the UK National exposure Database (NEDB) Tickner et al. The development of the EASE model. The Annals of Occupational Hygiene (2005) vol. 49 (2) pp. 103-10
11. Validity? Cherrie and Hughson. The validity of the EASE expert system for inhalation exposures. The Annals of Occupational Hygiene (2005) vol. 49 (2) pp. 125-34
12. Validity of dermal exposure Hughson and Cherrie. Comparison of measured dermal dust exposures with predicted exposures given by the EASE expert system. The Annals of Occupational Hygiene (2005) vol. 49 (2) pp. 111-23
13. ECETOC TRA… Based heavily on… Form of substance – solid, liquid Fugacity Indoor/outdoor Local ventilation PPE % substance in preparatoins
16. The Advanced REACH Tool… Being developed piecemeal by a group of research institutes – TNO, HSL and IOM Many experts originally skeptical Originally supported by governments and only latterly by industry and others Based on the premise of maximising the use of data by combining measurements and model estimates in a Bayesian framework
17. Summary… EASE and its successor tools dominate Tier 1 model options Tool applicability scope is always limited They are likely to typically be highly conservative but not in all situations There are a range of tools available but little information about their comparability and validity BaUA intend to commission a study of Tier 1 tool validity in 2011 For Tier 2 it makes sense to use all available information – measurements and model data
Notes de l'éditeur
A similar substance is defined as possessing similar physico-chemical properties relevant for exposure (e.g. vapour pressure, dustiness). To be on the safe side, a more “critical” similar substance has to be used for analogous/surrogate data. As an example, the use of toluene data for a xylene exposure assessment could be appropriate, since toluene is more volatile than xylene and thus results in a conservative exposure estimate.
Figure 1 compares the proportion of exposure measurements inside the randomly selected range with the corresponding value derived from the expo- sure range allocated by EASE. The data in this graph show the 52 scenarios for 28 different end-points. The bottom right hand area on the graph shows data sets where EASE was more successful than the random allocation of exposure and the top left area where the random allocation was better than EASE. Ideally, we would have liked to have seen most of the points in the former area, although in fact there is no indication that EASE is substantially better than a random allocation of exposure range. In 39% of the end-points the EASE prediction was better than the random allocation, whereas there were 22% of end-points where the random allocation produced a better agreement with the measured exposures. In the remainder of instances the EASE and randomly allocated exposure end- points were equally good (or poor) in the assessment of exposure.