Ann. Occup. Hyg., Vol. 55, No. 9, pp. 980–988, 2011
Ó The Author 2011. Published by Oxford University Press
on behalf of the British Occupational Hygiene Society
doi:10.1093/annhyg/mer093
Advanced REACH Tool: Development and
Application of the Substance Emission Potential
Modifying Factor
MARTIE VAN TONGEREN1*, WOUTER FRANSMAN2, SALLY SPANKIE1,
MARTIN TISCHER3, DERK BROUWER2, JODY SCHINKEL2,
JOHN W. CHERRIE1 and ERIK TIELEMANS2
1
Institute of Occupational Medicine, Research Avenue North, Riccarton, Edinburgh EH14 4AP, UK;
Business Unit Quality and Safety, TNO Quality of Life, PO Box 360, 3700 AJ Zeist, The Netherlands;
3
Federal Institute for Occupational Safety and Health, Unit 4.1: Exposure Scenarios, 44149
Dortmund, Germany
2
Received 12 April 2011; in final form 22 August 2011
The Advanced REACH Tool (ART) is an exposure assessment tool that combines mechanistically modelled inhalation exposure estimates with available exposure data using a Bayesian
approach. The mechanistic model is based on nine independent principal modifying factors
(MF). One of these MF is the substance emission potential, which addresses the intrinsic substance properties as determinants of the emission from a source. This paper describes the current knowledge and evidence on intrinsic characteristics of solids and liquids that determine
the potential for their release into workplace air. The principal factor determining the release
of aerosols from handling or processing powdered, granular, or pelletized materials is the dustiness of the material, as well as the weight fraction of the substance of interest in the powder
and the moisture content. The partial vapour pressure is the main intrinsic factor determining
the substance emission potential for emission of vapours. For generation of mist, the substance
emission potential is determined by the viscosity of the liquid as well as the weight fraction of
the substance of interest in the liquid. Within ART release of vapours is considered for substances with a partial vapour pressure at the process temperature of 10 Pa or more, while mist formation is considered for substances with a vapour pressure £10 Pa. Relative multipliers are
assigned for most of the intrinsic factors, with the exception of the weight fraction and the
vapour pressure, which is applied as a continuous variable in the estimation of the substance
emission potential. Currently, estimation of substance emission potential is not available for
fumes, fibres, and gases. The substance emission potential takes account of the latest thinking
on emissions of dusts, mists, and vapours and in our view provides a good balance between
theory and pragmatism. Expanding the knowledge base on substance emission potential will
improve the predictive power of occupational exposure models and thereby the accuracy
and precision of the exposure estimates.
Keywords: dust, dustiness; emission potential; exposure modelling; mist; vapour; volatility
elled inhalation exposure with available exposure data
using a Bayesian approach (Tielemans et al., 2011).
The mechanistic model is based on nine independent
principal modifying factors (MF) (Fransman et al.,
2011). These include two source-related MF: (i)
substance emission potential, which addresses how
the intrinsic properties of the substance affect emission, and (ii) activity emission potential, which
INTRODUCTION
The Advanced REACH Tool (ART) is an exposure
assessment tool that combines mechanistically mod*Author to whom correspondence should be addressed.
Tel: þ44-131-449-8097; fax: +44-131-449-8084;
e-mail: martie.van.tongeren@[email protected]
980
Substance Emission Potential
addresses how the process or activity affects the emission of the substance. The latter is described by Marquart et al. (2011), while this paper describes the main
intrinsic properties of substances in relation to emission.
Depending on the type of product and the way it
is handled, emission of a contaminant can result in
several exposure forms. For instance, a solid object
may result in inhalable dust exposure due to abrasion
or fumes due to hot work. Table 1 provides a description of the various exposure forms. ART (version
1.0) estimates exposure for three of these exposure
forms: vapour, mist, and dust; exposure to fumes,
fibres, gases, and bioaerosols are presently excluded.
Table 2 shows the different broad categories for
modelling of ‘substance emission potential’ that
are currently included in ART. For each category,
a distinct set of underlying determinants is used for
modelling the substance emission potential as the
nature of the determinants across categories is very
different.
This paper describes the derivation of the factors that
are used to model release of dust (from handling powders or abrasion of solid objects), along with mists and
vapours (from handling liquids). These categories (Table 2) were also treated separately in the calibration of
the mechanistic model as discussed by Schinkel et al.
(2011). Further information on the mechanistic model
is described by Fransman et al. (2011).
981
HANDLING POWDERS, GRANULES, AND
PELLETS RESULTING IN DUST EXPOSURE
The principal factor determining the release of aerosols from handling or processing powdered, granular, or
pelletized materials is the dustiness of the material.
Dustiness is characterized as the propensity of materials
to produce airborne dust during handling (Mark, 2005).
Dustiness can be tested by applying a standard type and
amount of mechanical energy to a specified amount of
test material for a specified time in order to overcome
adhesive binding forces within the test material (Plinke
et al., 1991) and thus disperse/release existing particles
from the test material into the air (Lidén, 2006).
For powders, dustiness can be estimated using
several methods, but the two main methods are the
rotating drum test and the continuous single-drop test
(CEN, 2006). The rotating drum dustiness test involves the continuous multiple dropping of a sample
of the material in a slow moving horizontal stream of
air, while in the continuous single-drop method material falls through the air into an enclosed chamber.
Both methods aim to reliably reproduce the generation of dust under standard conditions, mimicking
different workplace powder handling scenarios
(CEN, 2006). Unfortunately, the results of dustiness
tests depend on various factors, including the apparatus used, the testing time, the mass of the chemical
tested, the environmental conditions, and the dust
fractions measured (Chung and Burdett, 1994;
Table 1. Definitions of exposure forms
Gas
Vapour
Dust
Fume
Mist
Fibre
Bioaerosol
This is the airborne state of a chemical whose liquid is so volatile that its vapours cannot reach an equilibrium with
its liquid. If such a chemical were present in an open container in a closed room, all the liquid would evaporate.
This is the airborne state of a chemical, which, if a sufficiently large amount of liquid were released into a closed
room at normal temperature, would not completely evaporate but rather would reach equilibrium with its liquid.
Solid particles that are formed by aerosolization of already existing powders or by abrasion of solid objects. A
broad range of diameters is possible but those larger than 100 lm in diameter will not stay airborne long.
Solid particles that are formed by condensation from high temperature vapour, such as from molten metal or
smoke. Fumes form at an initially very small diameter (ca. 0.01 lm), and although they will aggregate into larger
particles, they still rarely get larger than 0.5 lm.
Any airborne liquid particles. A water mist in the form of steam, fog, or a fine spray is a common example, but
mists of an organic solvent or even mercury can be formed. Mists smaller than 1 lm are hard to generate, and
mists larger than 100 lm will not stay airborne long.
Elongated particles whose length-to-diameter ratio is at least 3:1.
Particles of biologic origin (plants, food, etc.).
Based on Popendorf (2006).
Table 2. Overview of categories for modelling of ‘substance emission potential’
Categories for modelling substance emission
potential
Type of product
Type of exposure
Handling solid objects resulting in dust exposure
Solid objects
Dust
Handling powders resulting in dust exposure
Powders, granules, or pelletized material
Dust
Handling liquids resulting in vapour exposure
Volatile liquids (vapour pressure .10 Pa)
Vapour
Handling liquid resulting in mist exposure
Low-volatile liquids (vapour pressure 10 Pa)
Mist
982
M. van Tongeren et al.
Breum, 1999, Mark, 2005; CEN, 2006; Back and
Schmidt, 2008; Pensis et al., 2010). Furthermore,
the two test methods do not always rank materials
in the same order (CEN, 2006, Pensis et al., 2010).
Hence, dustiness is not a well-defined physical or
chemical property of a product (Lidén, 2006).
Using both the rotating drum and single-drop
method, Heitbrink et al. (1990) found varying
correlations between dustiness test results and
exposure measurements at four workplaces with
bag filling and dumping operations. On the other
hand, simulations involving handling small volumes of powder showed that the dustiness index,
measured using a single-drop method (Cowherd
et al., 1989a), was one of five parameters significantly related to exposure (Cowherd et al.,
1989b). Brouwer et al. (2006) showed that dustiness test results, obtained using a rotating drum
method, explained 70% of the variance in personal dust exposure levels under controlled circumstances. However, they investigated only a limited
number of substances.
Intrinsic features of a product that are likely to be
associated with the dustiness include the particle size
distribution (of the product), the shape of particles,
the bulk density, the moisture level, and the friability
of the product. These factors give rise to considerable differences between materials. Hjemsted and
Schneider (1996) measured the dustiness of 31 different products using the rotating drum method and
observed a very wide range of results between the
substances, with a factor 2000 difference between
the highest and lowest dustiness level. In a project
funded by the European Commission under the 6th
Framework Programme, 12 different materials were
tested using the rotating drum, which showed a 50fold difference in the inhalable dustiness mass
fraction between the highest and the lowest results
(Burdett et al., 2000).
Quantitative dustiness information is generally not
available and therefore existing exposure models
that include a dustiness parameter tend to use dustiness categories (HSE, 1999; Marquart et al., 2008).
COSHH Essentials uses three dustiness categories
to estimate exposure (granules, coarse dust, and fine
dust) (HSE, 1999), while CEN EN 15051 identifies
four and Stoffenmanager uses five distinct dustiness
categories (firm granules or flakes, granules or flakes,
coarse dust, fine dust, and extremely dusty products)
(Marquart et al., 2008). These qualitative categories
may introduce operational difficulties for the user
due to their fuzzy boundaries and broad dustiness
categories. The categorization process may therefore
raise difficulties and introduce ‘linguistic uncertainty’ (Morgan and Henrion, 1990), in particular
if borderline cases have to be evaluated (Tischer
et al., 2003).
The ART mechanistic model adopted the classification scheme for the dustiness of materials from
Stoffenmanager. The categories within this scheme
are based on a qualitative description similar to that
used in Stoffenmanager. In addition, measured
Table 3. The classification scheme for dustiness categories and assigned values for powdered, granular, and pelletized material
Category
Description
Relative
multiplier
Firm granules,
flakes, or pellets
Product does not result in dust emission without intentional
breakage of products: e.g. firm polymer granules, granules covered
with a layer of wax)
0.01
100
Granules,
flakes, or pellets
Granules or flakes may fall apart and crumble, resulting in only
a very limited amount of fine particles. Handling the product does
not result in a visible dust cloud; e.g. fertilizer, garden peat, animal
pellets.
0.03
101–500
Coarse dust
A powdered product containing coarse particles. Handling the
product in its dry form results in a dust cloud that settles quickly due
to gravity: e.g. sand.
0.1
501–2000
Fine dust
A powdered product containing fine particles. This category may
also contain products with a mixture of fine particles and large
particles or granules. Handling the product in its dry form results in
a dust cloud that is clearly visible for some time: e.g. talcum
powder, carbon black.
0.3
2001–5000
Extremely fine
and light powder
A powdered product containing very fine, free flowing, light
particles. This category may also contain products with a mixture of
very fine particles and large particles or granules. Handling the
product in its dry form results in a dust cloud that remains airborne
for a long time. The product may be wind swept: e.g. magnesium
stearate.
1.0
5000
As measured with rotating drum dustiness tester according to CEN (2006).
Dustiness test
level (mg kg1)
Substance Emission Potential
dustiness (inhalable fraction) in milligrams per kilogram are also provided, which can be used as indicative cut-off points (Table 3). A range of two orders
of magnitude between lowest and highest dustiness
class appears to be plausible given the total range
in individual dustiness test results and the fact that
only a limited number of classes are used in this
scheme. Therefore, a relative multiplier was assigned
to each category ranging from 0.01 for ‘firm granules,
flakes, or pellets’ to 1 for ‘extremely fine and light
powder’.
We compared the assignment of dustiness category
for 27 substances based on measured dustiness with
the assignment by an expert panel of six occupational
hygienists. The dustiness was measured using a rotating
drum tester (EDT 38 L; JS Holdings, UK). Each member of the expert panel independently assigned a dustiness category to each substance, and subsequently one
category was assigned to each substance based upon
a consensus procedure. The median and range of the
measured dustiness values for the dustiness categories
are shown in Table 4. Unfortunately, there were no
‘firm granules or flakes’ materials included in this
study. Comparing the assignment of dustiness category
based on the measured dustiness with the expert panel
assessment showed that there was agreement for
33% of the substances (Table 4). For nearly half
the substances, the expert panel assigned a higher dustiness category, while for 20% of the substances the
expert panel assigned a lower dustiness category. These
results suggest that the qualitative assignment of dustiness category of a product appears to be broadly appropriate, albeit somewhat conservative.
Increasing the moisture content or incorporating
additives will generally reduce emission of dusts
from powders, although the effect of moisture content on dustiness is complicated and varies for different types of products. Water can be added to the
product before or during the activity. The latter case
is treated as a control measure (‘wet suppression
983
techniques’) in the ART model and is therefore taken
into account in the MF ‘localized control’ (Fransman
et al., 2011), whereas the former is considered an intrinsic property of the material. Plinke et al. (1991)
showed that for powders, increasing the moisture
tended to reduce the dustiness by one order of magnitude or more. Three categories of moisture content
of powders were adopted in the ART (Table 5),
with multipliers used for powders ranging from
1 for dry powders (,5% moisture) to 0.01 for powders with .10% moisture content.
Within ART, it is assumed that the emission of dust
from handling powders or abrasion of solid materials is
proportional to the weight fraction of the substance of
interest. For example, if the weight fraction of the
chemical in a powder is reduced from 10 to 1%, then
the emission of the substance is reduced by a factor
of 10 (all other factors being equal).
The relative multiplier for the substance emission
potential for powders is calculated as follows:
ð1Þ
E 5 DMW;
where D is the relative dustiness multiplier, M is the
relative multiplier for moisture content, and W is the
weight fraction.
HANDLING SOLID OBJECTS RESULTING
IN DUST EXPOSURE
Intrinsic characteristics of the solid materials,
such as structure, friability, and hardness of the materials, are all important factors in the mass of aerosols emitted during abrasive activities and their
particle size distribution. For example, grinding of
wood clearly produced aerosols of a larger size distribution as compared to the other investigated (and
harder) substrates (e.g. aluminium, steel, ceramic,
granite) (Zimmer and Maynard, 2002). However, in
particular within similar materials, the evidence for
an association between the intrinsic characteristics
Table 4. Comparison of the dustiness classification of 27 products based on qualitative and quantitative assessments
Qualitative dustiness
categories
Nexpert panel Median (range) of Dustiness category based on measurements (mg kg1)
measured dustiness
100
101–500
501–2000
2001–5000
.5000
(mg kg1)
Firm granules, flakes, or pellets
0
Granules, flakes, or pellets
5
99 (25–1055)
Coarse dust
9
588 (195–4762)
10
2933 (691–6526)
3
8176 (2703–9795)
Fine dust
Extremely fine dust
—
Nmeasured
0
3
1
1
4
2
4
3
5
7
3
4
2
1
2
8
4
Nexpert panel, Number of products assigned to each dustiness category by the expert panel; Nmeasured, Number of products assigned
to each dustiness category based on the dustiness measurements.
984
M. van Tongeren et al.
Table 5. The effect of moisture content on dustiness of
powdered, granular, or pelletized products and solid objects
Category
Powders,
granules,
or pellets
Solid
objects
Dry product (,5% moisture content)
1.0
1.0
5–10% moisture content
.10% moisture content
0.1
0.01
0.3
0.03
and the emission rate is inconsistent. Alwis et al.
(1999) found that hard wood produces more
and finer dust than soft wood, although Thorpe and
Brown (1995) showed that hardness of the wood
was inversely associated with the dust production
rate and aerodynamic diameter of dust emitted
during sanding operations. Chung et al. (2000) did
not find any significant differences in the quantity of
dust generated from sawing hardwood, softwood, or
medium-density fibre boards. According to Kalliny
et al. (2008), processing of hardwood and mixed
woods generally were associated with higher exposure than were softwood and plywood, although results may have been confounded by other
unaccounted exposure determinants. Petavratzi et al.
(2007) indicate that hardness of material could be
an important factor in dust liberation mechanisms in
quarry operations. Roberts (1997) evaluated the dustiness of sandstone and observed that hard sandstone
resulted in higher exposures compared with stone
with lower crushing strength.
Due to the inconsistent results of studies investigating the impact of the intrinsic characteristic of
solid substances on exposure levels during abrasive
activities, it is currently difficult to develop a coherent, generic classification system across different
materials. Instead, the effect of the intrinsic properties of solid materials is (at least partly) covered by
the activity emission potential component of the
model (Marquart et al., 2011).
Similar to powders, the emission potential for solid
objects is modified by the moisture content and the
weight fraction of the chemical substance within
the solid object and pre-existing moisture content
of solid material is considered as part of the intrinsic
emission potential. The relative multiplier for moisture content of the solid material is based on evidence
of the effect of wet suppression techniques (used as
localized control measure to reduce emission levels).
Relatively low moisture content (5–10%) is assumed
to reduce emission by about a factor 3 compared to
dry material, based on median efficacy values obtained for ‘wet suppression’ (Fransman et al.,
2008) and exposure reduction figures described for
spraying of bricks with a fine water mist (Buringh
et al., 1990). For solid materials with high moisture
content, a reduction factor of 0.03 is applied.
The relative multiplier for the substance emission
potential for solid objects is calculated as follows:
E 5 MW;
ð2Þ
where M is the relative multiplier for moisture
content and W is the weight fraction.
HANDLING (VOLATILITY) LIQUIDS RESULTING
IN EXPOSURE TO VAPOURS
Evaporation is the main process for emission for
volatile liquids, with the rate of evaporation depending on the volatility of the liquid (vapour pressure or
boiling point), the dimensions of the source (surface
area), and the environmental conditions, such as air
temperature, air velocity, direction, and turbulence.
In 1916, Lewis demonstrated that the specific evaporation rate of a pure liquid is directly proportional
to the vapour pressure (Nielsen et al., 1995). The
vapour pressure of a pure substance at room temperature is readily available and the vapour pressure at
higher liquid temperatures can either be assessed
empirically, using so called Cox charts (after the
engineer who developed it in the early 1920s), or
estimated using, for example Trouton’s rule:
TBP
ln p 10:6 1 ;
ð3Þ
T
where
p is the vapour pressure (in atm),
TBP is the boiling point temperature of the liquid (K),
and
T is the temperature of the liquid (K).
Trouton’s rule, which is used in some regulatory
exposure assessment models, assumes that the ratio
between the enthalpy of vaporization and the normal
boiling temperature (at a pressure of 1 atm) is close
to 88 J K1 mol1 and that the change in the enthalpy is linearly related to temperature (between
298 K and the boiling point temperature).
When estimating the vapour pressure for substances in a mixture, one needs to account for the fact
that more than one substance will contribute to the
overall vapour pressure. This is based on a fundamental thermodynamic relationship called Raoult’s
law, which shows that the contribution of the partial
vapour pressure of liquid component ‘i’ to the total
vapour pressure of the mixture is reduced as the molar fraction of component i (xi) decreases.
Substance Emission Potential
pT 5
X
xi pi ;
ð4Þ
i
where
pT is the vapour pressure of the mixture,
xi is the molar fraction of component i in the liquid,
and
pi is the vapour pressure of the ith component.
Raoult’s law relates the vapour pressure of the components to their composition in an ideal mixture. However in non-ideal mixtures, vapour pressures can be
greater (positive deviations) or smaller (negative deviations) than is expected under conditions of an ideal
mixture. When the attractive forces between the molecules in the solution are weaker than the attractive
forces between the molecules of the individual components on their own, e.g. ethanol and benzene, there is
a positive deviation from Raoult’s law. Negative deviations are found in solutions where the attractive forces
between the molecules in solution are stronger than
the forces between the molecules of the individual
components on their own.
For non-ideal mixtures, a correction factor (or activity coefficient, c) is introduced into Raoult’s law.
X
pT 5
ci xi pi ;
ð5Þ
i
where ci is the activity coefficient of the ith component at a given molar fraction.
The activity coefficients depend on both the concentration and the composition of the mixture
(Maken et al., 2004). Generally, the activity coefficients are close to 1 where the interactions between
the molecules in solution (solute and solvent) are almost the same as those for the molecules of the pure
liquid. This is typical of non-polar hydrocarbon solutes mixed with a non-polar hydrocarbon solvent
and polar solutes dissolving in polar solvents. The
activity coefficient will increase with increasing difference in the polarity between the substance and the
solvent (Popendorf, 2006). The activity coefficient
of most hydrocarbons and other hydrophobic solutes
in water will be greater than unity, while the activity
coefficient for hydrophilic solutes in water (such as
ammonia and formaldehyde) will be less than unity
(Popendorf, 2006). If liquid components are only
sparingly soluble in each other, then the activity coefficient ci is inversely related to the corresponding
solubility of one solute in the solvent.
The activity coefficient can be empirically derived. Alternatively, tools such as the UNIversal
Functional Activity Coefficient (UNIFAC) method
can be used. The UNIFAC method, which was orig-
985
inally developed by Fredenslund et al. (1975), considers molecules as assemblies of fractions of
molecules (functional groups). The UNIFAC method
for estimating the activity coefficients has several
limitations. For example, the temperature of the mixture should be ,150°C and should not contain .10
functional groups. Furthermore, it relies on availability of information on exact molar fraction, which
is generally not available for most liquid products.
Within the ART, the user is requested to provide
the vapour pressure at the process temperature. If this
is unknown, then Trouton’s rule is applied to estimate the vapour pressure at the process temperature.
Subsequently, the molar fraction or, if this is unknown, the weight fraction of the substance in the
liquid mixture is requested and used to obtain the
partial vapour pressure (pi,mix). The default value
of the activity coefficient for a liquid mixture is set
at 1. However, the user is encouraged to use the UNIFAC or other method to obtain the actual activity coefficient for the substance within the liquid mixture.
The relative multiplier for the substance emission
potential for a volatile substance (in a mixture) is
then calculated as follows:
pi;mix
E5
:
ð6Þ
30 000
Substances with a vapour pressure of equal or
.30 000 Pa will evaporate almost immediately.
The relative multiplier for the substance emission
potential is therefore restricted to a maximum of
E 5 1 when pi,mix 30 000 Pa. Substances with very
high vapour pressures .100 000 Pa are formally
considered gases and are outside the applicability domain of ART. The relative multiplier has been set at
a minimum of E 5 3.33 104 when pi,mix ,10 Pa.
HANDLING (LOW VOLATILITY) LIQUIDS
RESULTING IN EXPOSURE TO MISTS
Mists can be generated by a number of processes,
such as by impaction of a liquid on a surface, by bubbling of gases through a liquid or by evaporation followed by condensation of the vapour. Within ART,
we consider the potential for mist formation when
handling of low-volatile liquids (i.e. with a vapour
pressure 10 Pa). This category also includes powders suspended in a liquid (e.g. copper in antifouling paint) or substances dissolved in a liquid
(biocides dissolved in water). The level of aerosol
formation is mainly determined by the activity (activity emission potential) (Marquart et al., 2011).
However, the viscosity of a liquid may also affect
the potential for aerosol formation. Handling of
986
M. van Tongeren et al.
liquids with low viscosity (like water) will result
in more mist formation compared to handling of
liquids with medium viscosity (like oil), with all
other factors the same. Therefore, we have arbitrarily
assigned relative weighting factors of 1 for lowviscosity liquids and 0.3 for medium-viscosity
liquids in the ART. Highly viscous products like
resin or paste have stronger binding forces and are
therefore unlikely to form aerosols during handling.
Similar to dust and solid object, the weight fraction of the chemical substance in the product will
(proportionally) modify the emission of the chemical. The relative multiplier for the emission potential
for low-volatile liquids resulting in mist formation is
estimated as follows:
E5
10
WV;
30 000
ð7Þ
where W is the weight fraction and V is the relative
modifier for viscosity.
DISCUSSION
This paper described the current knowledge and
evidence on intrinsic characteristics of solids and
liquids that determine the potential for their release
into workplace air. The substance emission potential
takes account of the latest thinking on emissions of
dusts, mists, and vapours and in our view provides
a good balance between theory and pragmatism.
This approach has been applied in the ART mechanistic model development (Fransman et al., 2011).
Obtaining reliable estimates for the emission potential for a substance and activity is critical in any mechanistic exposure model. The vapour pressure for
liquids and dustiness for powders, pellets, and granules are believed to be good proxies for the intrinsic
emission potential of a substance. However, use of
the mechanistic model in ART requires knowledge
of and experience in exposure assessment, in particular when deciding on the correct category for exposure
determinants, such as the dustiness class. Consequently, we advise that the ART should only be used
by exposure assessment experts. For powdered, granulated, and pelletized materials, the dustiness category
will often need to be selected in the absence of actual
dustiness information and is therefore subjective.
More empirical data are required on the dustiness of
materials. Manufacturers of these materials should
be strongly encouraged to include such information
in the safety data sheets, although this would require
standardization of the methods for assessing the dustiness and the reporting of this information. Also, the
impact of moisture content and environmental condi-
tions such as humidity on the dustiness should be investigated further. It would also be worthwhile to
investigate the dustiness of solid objects; standard protocols will need to be developed for this. This information could be used to estimate the release of dust
during general handling of solid materials. For activities other than general handling, it is likely that the
activity or process is much more important for estimating the release of dust than the intrinsic characteristics of the material. However, further experimental
work is required to confirm this.
For evaporation of volatile liquids, the prediction of
the emission potential is relatively straightforward
when dealing with a single, pure substance; mixtures
are more complicated, especially if the exact composition of the mixture is unknown or is variable. The molar fraction of the constituents of the mixture should be
known to estimate accurately the partial vapour pressure of the constituents and hence the emission potential. However, as this information is rarely accurately
available, it was decided to use the weight fraction in
the ART as a proxy for the molar fraction. If there
are no large differences between the molecular weights
of components within the mixture, then the weight
fraction is a reasonably good proxy for the molar fraction. However, if there are large differences, for instance mixtures that contain polymers, the molar
fraction and weight fraction can deviate substantially,
and hence, the emission potential may be estimated
with substantial error. Manufacturers should be encouraged to include information on the molar fraction of
substances on the safety data sheets of liquid products. Clearly, accurate predictions of the partial
vapour pressures for substances in mixtures of varying
composition (i.e. products of which the exact composition will vary between different batches) are difficult. More detailed information on the composition
is required, such as information on the distribution
of the molar fraction of individual components, rather
than just the range.
For complex (liquid) mixtures with variable composition (e.g. oil distillate products), the exposure of
interest may be the mixture itself rather than or in addition to the individual components. Generally, the
vapour pressure and boiling point are provided as
a range for such complex mixtures. Currently, we
recommend that the maximum vapour pressure of
the mixture is applied when using ART to estimate
exposure, although this would probably lead to an
overestimate of the actual exposure. If such liquid
products are used above room temperature, then
the vapour pressure range should be determined experimentally. Studies investigating the effect of temperature on the exposure to complex mixtures as
Substance Emission Potential
well as exposure studies in real exposure scenarios
are needed to refine ART in this area.
Currently, ART does not take into account the effect that other materials in the mixture may have on
the emission (e.g. insoluble solids), as for example is
the case in paints. The emission rate for volatile
agents from a painted surface will be reduced by
the formation of a drying layer on the surface of
the paint. van Veen et al. (1999) developed a twocompartment model for emission of volatile agents
from a painted surface to address the rate-limiting
evaporation process during the drying of a painted
surface. The current version of ART will overestimate emission for such mixtures and further refinement would be needed to provide a more realistic
emission factor.
The ART model is relatively unsophisticated for
mists. We have assumed that the viscosity of the material may determine the mist generation. However,
other issues that affect mist generation, such as surface tension, evaporation, and condensation, are not
taken into account. A full review of the factors affecting mist generation during different tasks (e.g.
cutting and grinding, electroplating, spraying, and
carpet cleaning) will be necessary to ascertain what
further refinements of the ART model would help
to improve its accuracy and widen its applicability
for assessing workplace exposures to mists.
ART applies a strict dichotomy for generation of vapours, if the vapour pressure at the process temperature
is .10 Pa, and generation of mist, if the vapour pressure is 10 Pa. This dichotomy might not be the most
optimal solution for semi-volatile compounds. During
activities with limited or no aerosol formation, evaporation may still be the dominant exposure generating
process for semi-volatile compounds, even if vapour
pressure is ,10 Pa. In order to avoid underestimation,
it is therefore advised to use a vapour pressure of 11 Pa
in ART for the following specific situations:
The substance is a semi-volatile compound with
a vapour pressure between 0.01 (which is arbitrarily chosen) and 10 Pa at the respective process temperature
987
aerosols, and gases. For fibres, there is evidence suggesting that the addition of oil to the fibres will
reduce the emission (Cherrie et al., 1987; Class
et al., 2001). In the case of metal fumes, we are
aware that there are a vast amount of data and knowledge on welding fumes available in the literature,
and therefore, we believe it is not necessary for a generic tool such as ART to include exposure to welding fumes. There is little evidence linking any of the
intrinsic properties of the materials with the emission of fumes during other hot processes, although
it is possible that the ratio of the process temperature
of the metal or alloy and the boiling point temperature of the metal of interest may be related to the
emission rate (Popendorf, 2006).
For gases, it is unclear to what extent the intrinsic
characteristics of the gas are important when estimating the release from a source. Clearly, gases need
to be contained in closed vessels or tanks, although
there may be release from small leaks and when connecting or disconnecting. However, the magnitude of
these emissions will probably depend more on the
integrity of the container seals and the pressure difference between the inside and outside of the container than the intrinsic substance characteristics of
the gas.
The model has been calibrated separately for
the various exposure forms using actual exposure
data (Schinkel et al., 2011). These results show
that the model predicted 60% of the variance
in results from dust and vapour measurements, although for mist exposure the explained variance
was lower (30%). Occupational inhalation modelling could make significant further progress by
improving our understanding of exposure determinants and by extending the conceptual basis
to other emission forms, such as fumes, fibres,
and gases. Expanding the knowledge base on
characteristics that are closely linked to intrinsic
emission potential and bridging some of the
knowledge gaps described above will improve
the predictive power of occupational exposure
models and thereby the accuracy and precision
of the exposure estimates.
and
The activity belongs to one of the following activity classes: (i) activities with open (undisturbed) liquid surfaces or open reservoirs, (ii)
handling of contaminated objects, (iii) spreading
of liquid products, and (iv) bottom loading.
The ART version 1.0 does not estimate exposures
for fibres, fumes (i.e. from hot metal processes), bio-
FUNDING
Dutch Ministry of Social Affairs and Employment; United Kingdom Health and Safety Executive;
French Agency for Environmental and Occupational
Health Safety (Afsset); CEFIC LRI; Shell; GlaxoSmithKline; Eurometaux; British Occupational Hygiene Society.
988
M. van Tongeren et al.
Acknowledgements—The ART consortium is indebted to the
Steering Committee of the ART project for providing expert
advice on the scientific part of the project and on practical implementation aspects. The ART consortium is grateful to the
external experts who reviewed the scientific information of
the mechanistic model.
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