Ann. occup. Hyg., Vol. 47, No. 8, pp. 609-618, 2003
© 2003 British Occupational Hygiene Society
Published by Oxford University Press
Classification of Dermal Exposure Modifiers and Assignment of Values for a Risk Assessment Toolkit
1 Department of Chemical Exposure Assessment, TNO Chemistry, Zeist; 2 ArboUnie Noord Holland West, Alkmaar, The Netherlands; 3 Health and Safety Laboratory, Sheffield, UK; 4 Eurofins Denmark A/S, Galten, Denmark; 5 FoBiG GmbH, Freiburg, Germany
Received 29 January 2003; in final form 12 May 2003
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONOUTLINE OF THE TOOLKITMETHODOLOGYRESULTSCONCLUSIONS AND FUTURE...APPENDIXREFERENCES |
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This paper describes how default dermal exposure values can be adjusted with modifier values for specific work situations. The work presented here is supplementary to a toolkit developed for the EU RISKOFDERM project. This toolkit is intended for the assessment and management of dermal risks in small and medium sized enterprises. Potential dermal exposure (on the outer envelope of the body) is estimated with an algorithm whereby modifier values are applied multiplicatively to dermal default exposure values. These exposure modifiers with their assigned factors are intended to increase or decrease the potential (default) dermal exposure accordingly. Default estimates are modified to obtain two modified defaults: potential exposure rate to the hands and to the body. Quantitative exposure data is at present inadequate and insufficient to derive meaningful information that can be used for the selection of independent modifiers and the assignment of appropriate values. Instead, available information from the literature was considered and, in combination with expert judgement, 15 potential dermal modifiers were selected. Modifiers were classified and grouped into non-overlapping groups in order to avoid double scoring. Values were assigned to modifiers in three different exposure routes, i.e. direct contact, surface contact and deposition. Depending on the significance of a modifier, the values assigned to modifiers were weighted in equal steps on a log-scale. The values assigned to modifiers as presented in this paper are open to validation and revision once new data become available.
Keywords: dermal; determinant; exposure variables; modifier; risk assessment; toolkit
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONOUTLINE OF THE TOOLKITMETHODOLOGYRESULTSCONCLUSIONS AND FUTURE...APPENDIXREFERENCES |
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At present, methodologies for the assessment of dermal exposure remain inadequate. In the absence of a dermal risk assessment and management toolkit, small and medium-sized enterprises (SMEs) are currently unable to assess and manage dermal risks in the work environment. The importance of introducing a practical toolkit for employers has been accentuated in recent years, with statistics showing that work-related skin diseases are responsible for a large number of claims and lost working days. There are very few dermal exposure assessment methods, and those that are available are either very generalized (EASE model: ECB, 1996; Friar, 1998), not thoroughly validated (US EPA, 1987; EUROPOEM, 1996) or specialized for specific work conditions (e.g. the substance-specific OAR model for spray painting: Brouwer and De Pater, 2001). A new development in dermal risk assessment includes a semi-quantitative method called DREAM (Van Wendel de Joode et al., 2003) that can supply estimates of potential dermal exposure, gives insight into the distribution of dermal exposure over the body and could be useful for the ranking of tasks or jobs.
The aim of the EU-funded RISKOFDERM project (Project QLK4-CT-1999-01107) discussed here is to develop a validated predictive model for estimating dermal exposure, and to devise a practical dermal exposure toolkit for SMEs. This publication is the third in a series of four, and focuses on the development of a dermal assessment toolkit. The toolkit framework is described by Oppl et al. (2003) and addresses dermal exposure in three consecutive steps, i.e. (1) the assessment of the potential dermal exposure on the outer envelope of the body, (2) the assessment of the actual dermal exposure on the skin by using a ‘clothing factor’, and (3) the assessment of the systemic dose due to actual skin exposure.
This paper is a contribution to step 1. In the toolkit, potential dermal exposure on the outer envelope of the body is estimated by using a multiplicative method to adjust default dermal exposure values. The derivation of default dermal exposure values is described in Warren et al. (2003).
Our objective was to develop (generic) dermal exposure modifiers to account for differences in, among others, the substances, tasks, process and equipment and control measures. For this purpose, exposure modifiers are defined as those factors that directly or indirectly increase or decrease dermal exposure (Burstyn and Teschke, 1999).
To select modifiers and assign values to each, well-documented information and detailed studies are required that describe the effects of modifiers in a work environment setting. This paper is supported by a comprehensive literature overview of dermal exposure determinants as described in Marquart et al. (2003). However, the availability of conclusive data on dermal exposure modifiers proved to be limited, which meant that in many instances the evidence from the literature, expert judgement and technical knowledge of physical and chemical aspects had to be combined to propose independent modifiers and their modification factors.
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OUTLINE OF THE TOOLKIT |
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The toolkit assumes an evidence-based methodology. For this purpose, dermal exposure operation (DEO) units associated with dermal exposure were adopted from a qualitative survey in the RISKOFDERM project. These DEO units were derived during an in-depth analysis of dermal exposure situations in different industry sectors and include several task-groups or scenarios. The DEO units include handling of contaminated objects, manual dispersion, hand tool dispersion, spray dispersion, immersion and mechanical treatment.
Dermal exposure can be significantly different for solid and liquid applications (Popendorf et al., 1995; SAIC, 1996). The effect of the physical state of a substance is also inherent in other models such as EASE (ECB, 1996). Similarly, this toolkit explicitly considers the physical state of the product by specifying for each DEO unit whether a solid or liquid is used, e.g. manual dispersion of solids.
Methods used for the measurement of skin contamination may include, among others, hand washing methods, patches and whole body sampling (Schneider et al., 1999). During the derivation of default values from quantitative exposure data (Warren et al., 2003), significant variation in exposure levels was detected for body and hand exposure measurements. It was decided to incorporate two dermal exposure estimates into the toolkit, namely potential ‘hand’ and ‘body’ estimates. This implies that adjustments made by modifiers will be applied independently to both hands and body.
Modifiers can affect dermal exposure in different ways, and this is largely dependent on the mechanism or route of dermal exposure. A conceptual model for dermal exposure assessment was developed by Schneider et al. (1999), who describe the mass transport processes. The main exposure routes described in the model of Schneider et al. (1999) have been adopted and simplified, and brought together into three main exposure routes, i.e. direct contact (DC), surface contact (SC) and deposition (DEP). Direct contact refers to the direct transfer of substances from the source to the skin or clothing, e.g. immersion of body parts, exposure through splashes or exposure by large particles (
100 µm) ejected from the source (also referred to as impaction). Surface contact occurs when a substance is transferred from contaminated surfaces onto the skin or clothing, whereas deposition (DEP) involves the transfer of airborne particles (<100 µm) to the skin or clothing. To incorporate these main dermal transport processes, a modifying value was assigned to each of the three routes of exposure.
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METHODOLOGY |
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TOPABSTRACTINTRODUCTIONOUTLINE OF THE TOOLKITMETHODOLOGYRESULTSCONCLUSIONS AND FUTURE...APPENDIXREFERENCES |
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Figure 1 gives an overview of the procedure that is involved in adjusting default values with modifiers. Generic default values have been derived for each DEO unit or task group (Warren et al., 2003), expressed as the potential exposure rate per unit of surface area (mg/cm2/h) as presented in Table A1. Also, based on the outcome of the derived exposure data and by applying expert judgement, dermal exposure is qualitatively ranked into exposure classes, i.e. very low to very high (Table A2). Values assigned to the modifiers are intended to adjust the default value and subsequently to attain the associated qualitative exposure class. Values assigned to modifiers (as presented in this paper) correspond to the modifier values applied in Warren et al. (2003) to derive default values.
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Classification of modifiers
The starting point for the classification of modifiers and the assignment of values was an extensive literature review of dermal exposure modifiers (Marquart et al., 2003). Findings from this literature overview were used to develop a preliminary list of dermal exposure modifiers. However, the modifiers selected for the toolkit do not directly correspond to those used for exposure modelling as suggested by Marquart et al. (2003). The reason for this is that the main framework of the toolkit already incorporates a number of potential dermal modifiers. Potential determinants such as ‘general product features’, ‘duration/frequency’, ‘clothing’ and ‘gloves’ are addressed in the main framework of the toolkit (Oppl et al., 2003). In an attempt to keep the toolkit simple for application in SMEs, potential modifiers of a more subjective and inconsistent nature were excluded, e.g. various modifiers associated with worker characteristics and the work environment, ‘moistness of the skin’ and ‘personal care/hygiene’. One should also note that some modifiers are inherent to the DEO unit selected by the toolkit user, and it is assumed that the effect of these modifiers forms an intricate part of the derived default value (e.g. type of equipment).
An objective for the development of the toolkit was that it should be kept pragmatic and user friendly. Seen from this viewpoint, modifiers had to be selected based on criteria that could narrow down and simplify the complex network of modifiers. Therefore, the preliminary list of modifiers was reviewed and, based on expert judgement, potentially significant modifiers were identified and selected on a consensus basis. The general guideline for selecting modifiers implied that independent modifiers with a significant effect on dermal exposure are given priority. Also, seen in the context of a universal toolkit application, preference was given to modifiers with a generic nature. Determinants that are dependent and related to other independent modifiers (e.g. the area treated versus the amount used) were dropped from the list to avoid double scoring and to prevent subsequent over- or under-rating of exposure estimates by using a multiplicative method.
Modifiers were categorized into three groups that represent different components of an exposure scenario. It allows for a more transparent classification system and helps to organize the modifiers into logical, non-overlapping groups. A brief description of the three groups is given below:
Substance-specific modifiers
Modifiers associated with the substance and product characteristics that determine the release and transfer of a chemical, e.g. volatility.
Workplace-related modifiers
Modifiers related to the process or equipment, task and worker characteristics, work practices and work environment, e.g. amount of product.
Control measure modifiers
These modifiers concern control measures that are expected to reduce dermal exposure significantly, e.g. containment. It should be noted that a separate section of the toolkit addresses a more extensive analysis of control measures (including actual exposure) for the purpose of control actions and risk management (Oppl et al., 2003).
Assignment of values
DEO unit default exposure values applied in this toolkit are normalized for all the modifiers, meaning that modifier values are set at the reference values (Warren et al., 2003). These reference values represent the ‘normal’ conditions that are assumed to occur during a given scenario (operation, task). A variable of a specific modifier that may incur a substantial increase or decrease in dermal exposure is qualitatively described, and these changes in modifiers are translated to step changes in exposure estimates. The qualitative description ensures that the modifier variables are explicit and, for application purposes in SMEs, it will also ascertain that the toolkit user is presented with clear and unambiguous choices. An example of the rationale applied for this purpose is illustrated in the modifier volatility where the reference value (factor 1) of the modifier ‘volatility’ is described as ‘like water’, while two variables are presented, e.g. ‘like solvent’ or ‘like oil’.
Each variable of a modifier was assigned a modifying value. However, information on the relationship between dermal modifiers and their associated dermal exposure variance remains largely insufficient and inconclusive. In the absence of large and representative exposure data sets that can be used for retrospective modelling, information from various studies had to be applied semi-quantitatively and by means of expert judgement for the assignment of generic values.
The assignment of values to modifiers in this study has been based on an incremental log-scale as previously proposed by Cherrie et al. (1996). Depending on the significance of a modifier, the effects of modifiers were weighed in equal steps on a log-scale. The log-scale values correspond to the log-normal distribution that is generally associated with occupational exposure distributions. Modifier values are assigned that will either induce an increase (e.g. 3; 10) or decrease (e.g. 0.3; 0.1) in dermal exposure. A study by Cherrie and Schneider (1999) revealed that statistically significant correlations with exposure measurements were obtained in five validation studies by using a similar log-scale approach.
In the ‘volatility’ example presented earlier, the implementation of this approach can be illustrated by adopting a generic value (for surface contact) of 0.3 for ‘like solvent’ (decrease in exposure) and a factor 3 for ‘like oil’ (increase in exposure). The assumption is therefore that a volatile substance evaporates rapidly from surfaces and results in a decrease in dermal surface contact.
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RESULTS |
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TOPABSTRACTINTRODUCTIONOUTLINE OF THE TOOLKITMETHODOLOGYRESULTSCONCLUSIONS AND FUTURE...APPENDIXREFERENCES |
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Modifiers and their assigned values
A summary of the proposed dermal modifiers and their assigned values for each route of exposure is presented in Table 1. A total of 15 modifiers have been listed. Two modifiers are task-specific and are specifically included for the DEO units ‘handling of objects’ and ‘spray dispersion’.
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Values assigned to the respective modifiers range from 0.001 to 10. This range implies that well-established control measures (e.g. containment, 0.001) can affect dermal exposure significantly, while values inducing an increase in dermal exposure (e.g. dustiness, 3) are generally less pronounced. The relevance of the different exposure routes (DC, SC, DEP) varies from one modifier to another. For example, a number of modifiers are assigned with equal values for all three routes of exposure, notably particle size, restricted workplaces, amount of product and complete containment. The most substantial intervention is incurred by values allocated to the control measures, particularly in the case of complete containment where dermal exposure can be reduced significantly or altogether.
Range of modifier values
Since the values assigned to modifiers are applied multiplicatively, minimum and maximum values are proposed to limit the collective effect of modifiers. Retrospective modelling of inhalation data can give some idea of the typical ranges of principal modifiers. For inhalation exposure, historical exposure data of many years can be applied for retrospective modelling purposes (Armstrong et al., 1996; Glass et al., 2000). These studies elucidate the typical ranges that can be expected for some principal modifying factors such as volatility, equipment, technology, ventilation, work practices and duration of exposure. Modifiers and their assigned values were obtained from benzene (inhalation) exposure data in the petroleum industry and were either data-driven or derived from expert judgement. Values applied for single modifiers varied from 0.1 (modifier: task) to 3.7 (modifier: product concentration), and 0.2–20 (modifiers not specified) for the respective studies. In the study of Armstrong et al. (1996), the substance-specific modifier (volatility) was assigned a value of 0.75–1, while the workplace-related modifiers (temperature, task, loading technology) were assigned values of 0.63–1, 0.1–2, and 1 or 3 respectively.
Retrospective modelling and regression analysis may be hampered by the fact that determinants are interrelated and nested within one another, and because regression models are not easily interpreted in the presence of multi-collinearity (Burstyn and Teschke, 1999). Although dermal modifiers in this toolkit are not directly comparable with those applied for inhalation exposure purposes, the magnitude of quantitative ‘adjustments’ gives a more objective view of the implications of exposure modifiers in general. In Table 2, the postulated minimum and maximum values are given for each modifier group (MG) and the total value of the groups combined (MT). As values assigned for modifiers are intended for generic applications in different types of industries, a provisional overall range of values are proposed (e.g. 0.001–50).
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Implementation
To illustrate the implementation of modifiers in the toolkit, a brief description is included of the calculations required to apply values assigned to modifiers. First, it seems appropriate to define an additional component of the toolkit, i.e. the route weight fraction (RWF). The contribution and relevance of the exposure routes (DC, SC, DEP) are not only relevant for modifiers, but also for different tasks and operations (or DEO unit). For example, for the DEO unit ‘immersion tasks’, the exposure routes DC and SC receive priority, whereas ‘spray dispersion’ tasks may emphasize the importance of all three routes. In order to address this discrepancy, a RWF has been proposed for each DEO unit. These weighting factors therefore account for the percentage contribution of each exposure route of a given DEO unit (Warren et al., 2003).
For the implementation of modifiers the following conditions are suggested:
- 1. Only one modifier of the ‘control measure’ group can be assessed by the toolkit, provided that the modifier is chosen with the highest impact.
- 2. If the modifier ‘complete containment’ is applied, all other modifiers are excluded.
- 2. If the modifier ‘complete containment’ is applied, all other modifiers are excluded.
In Table A3 an example is given to illustrate how modifier values are introduced and the modified default value is estimated using some basic calculations. Below, a summary of the main steps and calculations are presented.
- Selection of the DEO unit and modifiers.
- Per modifier: the contribution of different exposure routes is calculated by multiplying the modifier factor (MFDC,SC,DEP) with the route weight fraction (RWFDC,SC,DEP) of a given DEO unit. Then the modifier value (MV) for hand and whole-body exposure is calculated by summation of the three routes of exposure:
MFhand,whole body = (MVDC · RFDC) + (MVSC · RFSC) + (MVDEP · RFDEP) (1)
- Multiple modifiers: modifier factors (MF) are multiplied with each other to obtain a value per modifier group (MG) and for all groups combined (MT):
MGhand,whole body = MFmodifier 1 · MFmodifier 2 · MFmodifier n (2)
MThand,whole body = MGsubstance · MGworkplace · MGcontrol (3)
Values obtained with formulae (2) and (3) are not allowed to exceed the (provisional) minimum and maximum values as specified in Table 2.
- The total modifier value (MT) calculated above is subsequently multiplied by the default value of the designated DEO unit (DEODV) to obtain the modified default value (DVM). Modified default values (DVM) can be translated to a qualitative exposure estimate by using Table A2.
DVM hand, whole body = MT · DEODV
qualitative exposure class (4)
- Per modifier: the contribution of different exposure routes is calculated by multiplying the modifier factor (MFDC,SC,DEP) with the route weight fraction (RWFDC,SC,DEP) of a given DEO unit. Then the modifier value (MV) for hand and whole-body exposure is calculated by summation of the three routes of exposure:
Effects of values assigned to modifiers
The actual effect of a modifier on default values can be evaluated by observing the shift in the qualitative exposure bands. Table 3 shows the effect of the minimum and maximum total modifier value (MT) on the qualitative exposure bands.
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Three examples are given of default values for the hand and whole body, respectively. The first example shows how the default value of 0.03 mg/cm2/h (low exposure class) for hand exposure is adjusted by the minimum and maximum modifier value to <0.005 mg/cm2/h (very low) and 1.5 mg/cm2/h (high), respectively. These shifts in exposure estimates and qualitative exposure classes give a more concrete illustration of the effect of the selected modifiers on default values. However, from a practical point of view, it would be uncommon for a toolkit user to apply a large number of modifiers that result in values that exceed the minimum and maximum range. In general, default values are adjusted to such an extent that the qualitative exposure class is altered with a shift of one or two exposure bands, e.g. from a medium band exposure class (0.05–0.5 mg/cm2/h) to a very low band (<0.005 mg/cm2/h) or a very high band (
5 mg/cm2/h). Setting of an appropriate range remains dependent on future research and field studies. |
CONCLUSIONS AND FUTURE DEVELOPMENT |
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TOPABSTRACTINTRODUCTIONOUTLINE OF THE TOOLKITMETHODOLOGYRESULTSCONCLUSIONS AND FUTURE...APPENDIXREFERENCES |
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With the support of a comprehensive literature review (Marquart et al., 2003), it was possible to select and group some of the principle modifiers that are responsible for variation in dermal exposure. A number of essential modifiers are not addressed in this paper because some determinants form an intrinsic part of the toolkit itself, e.g. in-use concentration. It is important to note that the toolkit user selects a DEO unit with a fixed derivative default value, and that this value also captures some intrinsic determinants of the task or operation (e.g. the technology/equipment). The principal modifiers related to inconsistent personal and work environment characteristics were excluded in an attempt to simplify the ‘user-level’ application of the toolkit in SMEs. This toolkit should therefore not be mistaken for a comprehensive regulatory risk assessment tool.
The general framework of the toolkit assumes an evidence-based approach that uses quantitative and qualitative exposure data obtained from field studies. At this point in time, however, exposure data of dermal exposure are still insufficient to derive meaningful generic values for modifiers that are solely based on empirical data. Values assigned to modifiers as presented in this paper were derived semi-quantitatively by means of references to the literature and educated assumptions. Hence, a limitation of this proposal is that values assigned to modifiers are not data driven, and this implies that the choice of generic modifiers and their assigned values need to be thoroughly evaluated and validated.
We acknowledge that the presented values do not capture the exact variance of the exposure estimate. However, the advantage of an underlying quantitative model is that its transparent structure allows for revision as new evidence becomes available. For this purpose, field studies are currently being conducted in various industries as part of the RISKOFDERM project.
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APPENDIX |
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TOPABSTRACTINTRODUCTIONOUTLINE OF THE TOOLKITMETHODOLOGYRESULTSCONCLUSIONS AND FUTURE...APPENDIXREFERENCES |
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Tables A1 and A2 give the default exposure values, and Table A3 shows an example of the calculation.
Acknowledgements—The RISKOFDERM project was funded by the European Commission (project QLK4-CT-1999-01107). Additional funding came from The Netherlands Ministry of Social Affairs and Employment.
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FOOTNOTES |
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* Author to whom correspondence should be addressed. Tel: +31-30-694-4903; fax: +31-30-694-4926; e-mail: goede{at}chemie.tno.nl
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REFERENCES |
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TOPABSTRACTINTRODUCTIONOUTLINE OF THE TOOLKITMETHODOLOGYRESULTSCONCLUSIONS AND FUTURE...APPENDIXREFERENCES |
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Armstrong TW, Pearlman ED, Schnatter AR, Bowes SM, Murray N, Nicolich MJ. (1996) Retrospective benzene and total hydrocarbon exposure assessment for a petroleum marketing and distribution worker epidemiology study. Am Ind Hyg Assoc J; 57: 333–43.[Web of Science][Medline]
Brouwer DH, De Pater AJ. (2001) Experimentele studies ter evaluatie van de OAR-benadering bij het binnenshuis met een kwast verwerken van VOS bevattende verfproducten. TNO report V3287-1. Zeist, The Netherlands: TNO Food and Nutrition Research Institute.
Brouwer DH, Brouwer EJ, Van Hemmen JJ. (1992) Assessment of dermal and inhalation exposure to zineb/maneb in the culture of flower bulbs. Ann Occup Hyg; 36: 373–84.
Brouwer DH, de Vreede JAF, de Haan M, et al. (1994) Exposure to pesticides during, and after application in the cultivation of chrysanthemums in greenhouses. Health risk and risk management. Med Fac Landbouw Univ Gent; 59: 1393–1401.
Brouwer DH, Kroese R, Van Hemmen JJ. (1999) Transfer of contaminants from surface to hands: experimental assessment of linearity of the exposure process, adherence to the skin, and area exposed during fixed pressure and repeated contact with surfaces contaminated with powder. Appl Occup Environ Hyg; 14: 231–9.[CrossRef][Medline]
Brouwer DH, de Haan M, van Hemmen JJ. (2000a) Modelling re-entry exposure estimates: techniques and application rates. In Honeycutt RC, editor. Worker exposure to agrochemicals. CRC Press: Baton Rouge, FL, pp. 121–40.
Brouwer DH, de Vreede JAF, Meuling WJA, van Hemmen JJ. (2000b) Determination of the efficiency for pesticide exposure reduction with protective clothing: a field study using biological monitoring. In Honeycutt RC, editor. Worker exposure to agrochemicals. CRC Press: Baton Rouge, FL, pp. 65–86.
Burstyn I, Teschke K. (1999) Studying the determinants of exposure: a review of methods. Am Ind Hyg Assoc J; 60: 57–72.[Web of Science][Medline]
Cherrie JW, Schneider T. (1999) Validation of a method for structured subjective assessment of past concentrations. Ann Occup Hyg; 43: 235–45.
Cherrie JW, Schneider T, Spankie S, Quinn M. (1996) A new method for structured, subjective assessments of past concentrations. Ann Occup Hyg; 3: 75–83.
Cinalli C, Carter C, Clark A, Dixon D. (1992) A laboratory method to determine the retention of liquids on the surface of hands, EPA contract no. 68-02-4254. Washington, DC: Office of Toxic Substances, US Environmental Protection Agency, Chemical Engineering Branch.
De Cock JC, Heederik D, Kromhout H, Boleij J, Hoek F, Tjoe Ny, E. (1998) Determinants of exposure to captan in fruit growing. Am Ind Hyg Assoc J; 59: 166–72.[Web of Science][Medline]
De Pater AJ, Beijer MW, van Drooge HL, Brouwer DH. (2000) Potential dermal exposure during spray painting—a range finding study. TNO report V98.1331. Zeist, The Netherlands: TNO Food and Nutrition Research Institute.
De Vreede JAF, van Amelsfort M. (1997) Exposure to pesticides in a tree nursery using the spray boom and spray lance. TNO Report V97.111. Zeist, The Netherlands: TNO Food and Nutrition Research Institute.
ECB. (1996) Technical guidance documents, in support of the Commission Directive 93/67/EEC on risk assessment for new notified substances and the Commission Regulation (EC) 1488/94 on Risk Assessment for Existing Substances. Ispra, Italy: European Chemical Bureau.
EUROPOEM. (1996) The development maintenance, and dissemination of a European Predictive Operator Exposure Model (EUROPOEM) database. Draft final report. Carshalton, UK: TNO Bibra.
Driver JH, Konz JJ, Whitmyre GK. (1989) Soil adherence to human skin. Bull Environ Contamin Toxicol; 43: 814–20.[CrossRef][Web of Science][Medline]
Fenske RA, Horstman SW. (1987) Assessment of dermal exposure to chlorophenols in timber mills. Appl Ind Hyg; 2: 143–7.
Fogh CL, Byrne MA, Andersson KG et al. (1999) Quantitative meaurement of aerosol deposition on skin, hair and clothing for dosimetric assessment. Roskilde, Denmark: Risø National Laboratory.
Friar JJ. (1998) The assessment of workplace exposure to substances hazardous to health, the EASE model. Bootle: Health & Safety Executive.
Garrod ANI, Rimmer DA, Roberstaw L, Jones T. (1998) Occupational exposure through spraying remedial pesticides. Ann Occup Hyg; 42: 159–65.
Garrod ANI, Martinex M, Pearson J, Proud A, Rimmer DA. (1999) Exposure to preservatives used in the industrial pretreatment of timber. Ann Occup Hyg; 43: 543–55.
Glass DC, Adams GG, Manuell RW, Bisby JA. (2000) Retrospective exposure assessment for benzene in the Australian petroleum industry. Ann Occup Hyg; 44: 301–20.
HSE. (1999) Dermal exposure to non-agricultural pesticides—exposure assessment document EH74/3. Bootle: Health & Safety Executive.
Kissel JC, Richter KY, Fenske RA. (1996) Field measurement of dermal soil loading attributable to various activities: implications for exposure assessment. Risk Anal; 16: 115–25.[CrossRef][Web of Science][Medline]
Lansink CJM, Beelen MSC, Marquart J, van Hemmen JJ. (1996) Skin exposure to calcium carbonate in the paint industry. Preliminary modeling of skin exposure levels to powders based on field data. TNO-report V96.064. Zeist, The Netherlands: TNO Food and Nutrition Research.
Marquart J, Brouwer DH, Gijsbers JHJ et al. (2003) Determinants of dermal exposure relevant for exposure modelling in regulatory risk assessment. Ann Occup Hyg; 47: 599–607.
McArthur BR, Lees PSJ. (1995) Effect of contact time and contact pressure on the transfer of oil to surface sampling media. Appl Occup Environ Hyg; 10: 23–8.
Methmer MM, Fenske RA. (1996) Pesticide exposure during greenhouse applications. Part III: Variable exposure due to ventilation conditions and spray pressure. Appl Occup Environ Hyg J; 11: 174–80.
Oppl R, Kalberlah F, Evans PG, van Hemmen JJ. (2003) A toolkit for dermal risk assessment and management: an overview. Ann Occup Hyg; 47: 629–40.
Popendorf W, Selim M, Lewis MQ. (1995) Exposure while applying industrial antimicrobial pesticides. Am Ind Hyg Assoc J; 56: 993–1001.[Web of Science][Medline]
Preller EA, Schipper HJ. (1999) Respiratory and dermal exposure to disinfectants: a study in slaughterhouses and the meat processing industry. TNO report V98.1306. Zeist, The Netherlands: TNO Food and Nutrition Research Institute.
Roff M. (1997) Dermal exposure of amateur or non-occupational users to wood-preservative fluids applied by brushing outdoors. Ann Occup Hyg; 41: 297–311.
SAIC. (1996) Science Applications International Corporation. Occupational dermal exposure assessment. A review of methodologies and field data. Washington, DC: Office of Toxic Substances, US Environmental Protection Agency.
Schneider T, Vermeulen R, Brouwer DH, Cherrie JW, Kromhout H, Fogh CL. (1999) Conceptual model for assessment of dermal exposure. Occup Environ Med; 56: 765–73.
US EPA. (1987) Methods for assessing exposure to chemical substances. Volume 7. Methods for assessing consumer exposure to chemical substances. EPA/560/5-85-007. Washington, DC: Office of Pesticide and Toxic substances.
Van Drooge HL, de Pater AJ, Brouwer DH, Beijer MW, Bierman EPB, van Hemmen JJ. (2000) Modelling of spray paint deposition with field study data. American Industrial Hygiene Conference & Exhibition 2000, Orlando, FL, USA, May 2000, Book of abstracts. pp. 79–80.
Van Wendel de Joode B, Brouwer DH, Vermeulen R, van Hemmen JJ, Heederik D, Kromhout H. (2003) DREAM; a method for semi-quantitative dermal exposure assessment. Ann Occup Hyg; 47: 71–87.
Warren N, Goede HA, Tijssen SCHA, Oppl R, Schipper HJ, van Hemmen JJ. (2003) Deriving default dermal exposure values for use in a risk assessment toolkit for small and medium-sized enterprises. Ann Occup Hyg; 47: 619–27.
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R. RAJAN-SITHAMPARANADARAJAH, M. ROFF, P. DELGADO, K. ERIKSSON, W. FRANSMAN, J. H. J. GIJSBERS, G. HUGHSON, M. MAKINEN, and J. J. VAN HEMMEN Patterns of Dermal Exposure to Hazardous Substances in European Union Workplaces Ann. Hyg., April 1, 2004; 48(3): 285 - 297. [Abstract] [Full Text] [PDF]
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J. J. VAN HEMMEN Dermal Exposure to Chemicals Ann. Hyg., April 1, 2004; 48(3): 183 - 185. [Full Text] [PDF]
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J. J. VAN HEMMEN, J. AUFFARTH, P. G. EVANS, B. RAJAN-SITHAMPARANADARAJAH, H. MARQUART, and R. OPPL RISKOFDERM: Risk Assessment of Occupational Dermal Exposure to Chemicals. An Introduction to a Series of Papers on the Development of a Toolkit Ann. Hyg., November 1, 2003; 47(8): 595 - 598. [Abstract] [Full Text] [PDF]
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J. MARQUART, D. H. BROUWER, J. H. J. GIJSBERS, I. H. M. LINKS, N. WARREN, and J. J. VAN HEMMEN Determinants of Dermal Exposure Relevant for Exposure Modelling in Regulatory Risk Assessment Ann. Hyg., November 1, 2003; 47(8): 599 - 607. [Abstract] [Full Text] [PDF]
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N. WARREN, H. A. GOEDE, S. C. H. A. TIJSSEN, R. OPPL, H. J. SCHIPPER, and J. J. VAN HEMMEN Deriving Default Dermal Exposure Values for Use in a Risk Assessment Toolkit for Small and Medium-sized Enterprises Ann. Hyg., November 1, 2003; 47(8): 619 - 627. [Abstract] [Full Text] [PDF]
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R. OPPL, F. KALBERLAH, P. G. EVANS, and J. J. VAN HEMMEN A Toolkit for Dermal Risk Assessment and Management: An Overview Ann. Hyg., November 1, 2003; 47(8): 629 - 640. [Abstract] [Full Text] [PDF]
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U. SCHUHMACHER-WOLZ, F. KALBERLAH, R. OPPL, and J. J. VAN HEMMEN A Toolkit for Dermal Risk Assessment: Toxicological Approach for Hazard Characterization Ann. Hyg., November 1, 2003; 47(8): 641 - 652. [Abstract] [Full Text] [PDF]
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