Title
Stoffenmanager exposure model: Development of a quantitative algorithm
Author
Tielemans, E.
Noy, D.
Schinkel, J.
Heussen, H.
van der Schaaf, D.
West, J.
Fransman, W.
TNO Kwaliteit van Leven
Publication year
2008
Abstract
In The Netherlands, the web-based tool called 'Stoffenmanager' was initially developed to assist small- and medium-sized enterprises to prioritize and control risks of handling chemical products in their workplaces. The aim of the present study was to explore the accuracy of the Stoffenmanager exposure algorithm. This was done by comparing its semi-quantitative exposure rankings for specific substances with exposure measurements collected from several occupational settings to derive a quantitative exposure algorithm. Exposure data were collected using two strategies. First, we conducted seven surveys specifically for validation of the Stoffenmanager. Second, existing occupational exposure data sets were collected from various sources. This resulted in 378 and 320 measurements for solid and liquid scenarios, respectively. The Spearman correlation coefficients between Stoffenmanager scores and exposure measurements appeared to be good for handling solids (rs = 0.80, N = 378, P < 0.0001) and liquid scenarios (rs = 0.83, N = 320, P < 0.0001). However, the correlation for liquid scenarios appeared to be lower when calculated separately for sets of volatile substances with a vapour pressure >10 Pa (rs = 0.56, N = 104, P < 0.0001) and non-volatile substances with a vapour pressure ≤10 Pa (rs = 0.53, N = 216, P < 0.0001). The mixed-effect regression models with natural log-transformed Stoffenmanager scores as independent parameter explained a substantial part of the total exposure variability (52% for solid scenarios and 76% for liquid scenarios). Notwithstanding the good correlation, the data show substantial variability in exposure measurements given a certain Stoffenmanager score. The overall performance increases our confidence in the use of the Stoffenmanager as a generic tool for risk assessment. The mixed-effect regression models presented in this paper may be used for assessment of so-called reasonable worst case exposures. This evaluation is considered as an ongoing process and when more good quality data become available, the analyses described in this paper will be expanded. Based on these analyses, the algorithm will be refined in the near future. © The Author 2008. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.
Subject
Chemistry
Food and Chemical Risk Analysis
Exposure assessment methodology
Risk assessment
Correlation methods
Industrial economics
Chemical products
Exposure assessment methodology
Exposure data
Netherlands
Risk assessment
Semi-quantitative
Small- and medium-sized enterprises
Spearman correlation
Web-based tools
Occupational risks
Computer program
Dust exposure
Health survey
Information processing
Materials handling
Workplace
Algorithms
Environmental Monitoring
Hazardous Substances
Humans
Industry
Inhalation Exposure
Internet
Models, Biological
Occupational Exposure
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http://resolver.tudelft.nl/uuid:7db52305-f397-4648-b04d-69d82d40356d
DOI
https://doi.org/10.1093/annhyg/men033
TNO identifier
240946
ISSN
0003-4878
Source
Annals of Occupational Hygiene, 52 (6), 443-454
Document type
article