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Consequences of exposure to toxic gases following industrial disasters
Consequences of exposure to toxic gases following industria.1 disasters Dik de Weger, Chris M. Pietersen and Paul G. J. Reuzel* Department of Industrial Safety, TNO, PO Box 342, 7300 AH Apeldoorn, The Netherlands *CIVO Institute of Toxicology, TNO, PO Box 108, 3700 AC Zeist, The Netherlands
Acute toxicity data are important in risk analysis. In this paper, recent developments in consequence modelling, reported in the so-called Green Book (published by the Dutch Ministry of .Housing, 1990), are presented. The Green Book offers a simplified approach to determine probit functions for man, based on a relatively limited set of toxicity data. The determination process consists of two steps: (1) estimating a human LC 50 from animal data, taking into account interspecies differences and the amount of information available; (2) calculating the probit parameters, based on a value of 1 for the slope of the probit function, which is a conservative assumption with respect to the variation in vulnerability of a human population exposed in emergency circumstances. The probit functions thus derived are a step towards more reliable vulnerability models. The extrapolation of animal data to human data contributes substantially to the uncertainty in risk analysis results. To improve this situation, research into the mechanisms of behaviour of the chemicals in the body is required. (Keywords: toxicity, risk assessment; modellingl
In the last few decades, a number of accidents with industrial chemicals have occurred, some with very large numbers of casualties (e.g. Seveso, Mexico, Bhopal). Public concern has urged the authorities in many countries to impose regulations on industrial activities with hazardous materials, and industry itself is becoming increasingly aware of the necessity for a proper safety policy. The use of safety and risk assessment studies has improved considerably over the last decade. Over the years TN0 has been involved in the development of a risk assessment methodology and of the mathematical models that are required in such a methodology. A risk analysis is one of the tools that can be used to assess the risk of an industrial accident. A risk analysis normally consists of the following steps: 1. identification of potential hazards for releases of hazardous materials; 2. calculation of physical effects of those releases; 3. calculation of consequences due to those effects (e.g. health damage); 4. calculation of the probabilities of steps 1-3; 5. final risk evaluation: combine consequences and probabilities and give risk-reducing recommendations for determination of accident scenarios.
Received
22 November
09504230/91/&40272-05 @ 1991 Butterworth-Heinemann
272
1990 Ltd
J. Loss Prev. Process Ind., 1991, Vol4, July
Physical effect models developed by TN0 have been brought together in the ‘Yellow Book”, enabling calculation of the behaviour of chemicals during phenomena such as explosion, fire, gas dispersion, pool evaporation, etc. Calculation results include explosion overpressure, atmospheric gas concentrations and the amount of heat radiation. Recently, the ‘Green Book’2 has been issued, in which a number of consequence models is presented. These models enable the user to relate the calculated physical effects to the amount of damage to people and constructions. Furthermore, in the ‘Red Book’3 and the supplementary manua14, models and data for the calculation of probabilities are given. With publication of the Green Book, a series of standards has been completed. An important part of the Green Book is the chapter ‘Health damage by acute intoxication’. In the following, the background of the modelling approach is given, together with a brief description of the results.
Modelling of the consequences of a toxic chemical
of the release
In a quantitative risk analysis (QRA) of industrial activities, the consequences and probabilities of releases of hazardous materials are considered. In the case of industrial disasters, acute intoxication of residents in the vicinity of the plant usually occurs by
Exposure exposure to gaseous materials. Therefore in this paper, as well as in the Green Book, toxicity modelling has been limited to inhalation toxicity. It is common practice in QRA to evaluate toxicity risks by calculation of the percentage of the population exposed that shows a certain health effect (usually lethality). The mathematical technique used is the probit analysis, described by Finney’ . Probit equations offer the user the possibility to calculate the response for each combination of exposure time and concentration, or vice versa, to calculate the concentration for a given exposure period and response. In this respect probit analysis is a more powerful technique than risk evaluation with, for instance, just a LCm value, which gives the concentration leading to a fixed response percentage. Probit equations are established using a series of toxicity data for a specific health effect and exposure route and preferably for one species. Toxicity data have to be obtained for a range of exposure times and/or concentrations and response values. As little toxicity data for man are available, especially in the higher response percentages, human probit functions have to be established by extrapolating from animal data. This step introduces a considerable uncertainty into the human data. In the Green Book, a number of probit functions has been derived, making use of a simplified approach which is mainly applicable if only limited toxicity data are available. However, continuous effort is taking place to improve the methodology used in the determination of human toxicity data.
The Green Book probit approach The probit functions in the Green
Book
essentially
have the following features: the probit function is based on a human LCsO, derived from animal LC& data using a safety factor which depends on the amount of information available; the slope of the probit function has a value of 1, which is a conservative assumption; only probit functions for lethal injury are given.
Estimation of human LC,& Since empirical human LC&, values are not available, values have been estimated from animal LC50 values available in the literature. In these calculations, an extrapolation factor is used consisting of two terms: the first takes into account the physical interspecies differences (e.g. body mass, breathing volume, lung siuface, oxygen consumption) for which reasonably well-known empirical relationships exist; the second is a safety factor which takes into account other, less defined differences as well as differences in behaviour during exposure situations. Furthermore, the extrapolation factor is
to toxic gases:
D. de Weger et al.
adjusted, dependent on the amount of information available for a specific chemical. For inhalation toxicity, a distinction can be made between locally acting substances and systemically acting substances. Locally acting substances cause direct damage to the respiratory tract. Therefore, as a measure of the severity of the consequences, the inhaled dose per unit lung surface can be taken as the effective dose, D”:
D” = D/A
(mg m-‘)
(1)
The inhaled dose is determined by the respiration rate, the concentration of the gas and the exposure time: D = (V,/lOOO)Ct
(mg min-‘)
(2)
The lung surface and respiration rate are dependent on the body mass according to the following empirical relationships6: v
a
=
,wO.‘O
A = ,W”.g2
(3) (4)
It follows that D” - (U/U)w-o~22
(5)
This equation accounts for the physical differences between animals and humans, which for locally acting substances comes down to a difference in lung properties. These are eventually expressed in terms of body mass as this is an easily measureable quantity. However, differences between animals and humans are not limited to simple lung properties such as those mentioned above. In general, the retention in the animal nose is higher than the retention in the human respiratory tract. Furthermore, experimental animals are obligatory nose breathers, whereas man is not, which may be an additional cause for larger amounts of material to reach the human lungs. Another factor whichmust be taken into account is the difference in behaviour between animals and humans in exposure situations. It is assumed that at least a part of the exposed human population will try to escape from the accident area. Together with the stress factors accompanying accident situations, this will result in an increase in breathing frequency. Some animal species, however, show the opposite behaviour, in that they dramatically decrease their respiratory frequency in the first few minutes of exposure to irritant chemicals. Therefore, a safety factor of 10 was adopted for locally acting substances, consisting of a factor of 5 accounting for less adsorption in the human respiratory tract and a factor of 2 accounting for behaviour differences between animals and humans. For systemic agents a similar approach is followed. Systemic agents cause damage to the body once they have been absorbed into the blood and distributed through the body. For these chemicals, the differences between animals and humans are largely due to physiological and pharmacokinetic mechanisms. In this case, the measure for the severity of the consequences
J. Loss Prev. Process Ind., 7991, Vol4, July
273
Exposure to toxic gases: D. de Weger et a I. is the dose per unit body mass: D’ = D/W
(mg kg-‘)
(6)
The amount absorbed is assumed to be related to oxygen consumption, which again is linearly related to the respiratory minute volume. Substitution of the empirical relation from Equation (3) into (6) gives: D’ - uw-o.3
(7)
This relation accounts for the differences in absorption of the chemical by animals and humans. However, the toxicity of systemic agents largely depends on pharmacokinetics, metabolism and the actual toxic working mechanism in the target organ. Because very few data are available on these subjects, a conservative safety factor of 10 is taken. Together with the safety factor for behavioural differences (which is the same as that chosen for locally acting substances) the overall safety factor for systemic agents becomes 20. In Table I the extrapolation factors for a number of species are given for both locally acting substances and systemic agents. In this approach, the final extrapolation factors for both substance categories appear to be in the same value range. Therefore, one extrapolation factor per species has been chosen. The estimation of the human LCsO has to be
Extrapolation
Table1 L&(30
factors
Species
Substance category
Rat
Systemic Loca I
Mouse
Toxic load factor
274
of probit constants
J. Loss Prev. Process lnd., 1991, \/o/4, July
of
human
3.3 5.1
20 10
;I;;
0.25
Systemic Local
10.2 5.5
20 10
;;;
0.5
Guinea pig
Systemic Local
2.6 3.8
20 10
;*;;
0.2
Hamster
Systemic Local
3.6 5.8
20 10
;:;;
0.3
carried out according to the scheme given in Figure 1. Before applying the extrapolation factor, the animal values may have to be recalculated for an exposure period of 30 min (the length of time considered to be the maximum exposure in accident situations), using Equation (8): C” t = constant
(8)
If the coefficient RZis not known, an arbitrary value of 2 is chosen. This is in fact a conservative approach. From theoretical considerations, it can be derived that n may
x [t/30)‘”
No
Figure 1 Scheme for determination
estimation
Extrapolation factor
30 min) = LC,(i)
a =5 -
the
Safety factor
Yes LC,(i,
for
min)
I n[ [LCSO(man)~. 30 }
Exposure to toxic gases: D. de Wegeret be dependent on the working mechanism of the chemical. If the active substance is a metabolite, the value of R would be 1; if the chemical itself is the working substance or if it is not known whether metabolism plays any part in the working mechanism, the value of n would be 2 (Ref. 7). However, this hypothesis needs experimental verification. After application of the safety factor, the amount of information available is taken into account. If toxicity data for more than one species are available, the extrapolation factor is increased with a factor of 2, being a correction in a less conservative direction. A probit equation is a Calculation of probit constants. mathematical relationship between the response fraction and the ‘probit’ (or ‘probability unit’), which are related via the normal distribution5. The probit is given by the following equation: Pr=a+blnC”t
(9)
Probit equations are determined for a specific health effect by regression of the response as a function of toxic load (oral dose, or the combination of inhalatory concentration and exposure period). Probit constants are known for only a limited number of substances, and are mainly based on animal toxicity data. In the determination of the human probit equations, the intraspecies differences are accounted for. Animal toxicity data are obtained from relatively homogeneous populations, whereas the variation in the human population exposed during an accident can be very wide. To account for the larger response spread, the slope of the probit equation has been set to 1. This means that the LCg5 relates to the LCos as 27; this value is conservative but still realistic, when compared to the empirical value of 12, determined by Hattis et al.’ from human volunteer data. The results of the calculation of probit constants are given in Table 2.
Summary and conclusions The determination of probit equations applicable for humans is presented here as a two-step process: estimation of a human LCsO followed by calculation of the probit constants. In the first step, an extrapolation factor is used which takes into account the differences between animals and humans. For locally acting substances these are the respiratory volume and the lung surface. These properties can be empirically related to body mass. Furthermore, differences between animals and humans in breathing pathways (nose or nose and mouth), in susceptibility of the lung tissue and in the influence of lung damage to the organism as a whole were brought together in a safety factor, as well as behavioural differences that may influence the respiratory frequency and thus the total respiratory minute volume. For systemic agents, oxygen consumption is taken as the measure for toxic load, which is also assumed to be related to the respiratory volume. In this case, the
Table2 Probit constants for humans, calculated the method described in this paper (see figure tions in mg-3, exposure time in minutes
according to concentra-
I),
Chemical
30 minLC, (ma mm31
n
b
a
Acrolein Acrylonitrile Ammonia Bromine Carbon monoxide Chlorine Ethylene oxide Hydrogen chloride Hydrogen cyanide Hydrogen fluoride Hydrogen sulphide Methyl bromide Methyl isocyanate Nitrogen dioxide Phosgene Sulphur dioxide
304 2533 6164 1076 7949 1017 4443 3940 114 802 987 3135 57 235 14 5784
1.o 1.3 2.0 2.0 1 .o 2.3 1.0 1.0 2.4 1.5 1.9
1
-4.1 -8.6 -15.8 -12.4 -7.4 -14.3 -6.8 -6.7 -9.8 -8.4 -11.5 -7.3 -1.2 -18.6 -0.8 -19.2
A:: 3.7 0.9 2.4
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
al.
safety factor reflects the differences in pharmacokinetits and pharmacodynamics and the lack of knowledge on this subject. Behavioural differences are evaluated in the same way as with locally acting substances. In calculating the human LCso, the safety factors are multiplied by a factor 2 if toxicity data for more than one species are available. This means that a larger amount of information is credited for by a less conservative approach. In the second step, to account for the variability in vulnerability in the human population, which is larger than in experimental animal populations, the slope of the probit .equation is set to 1. This limits the applicability of the probit functions to responses below 50%, which however is not a very serious limitation in accident evaluation. In reality, if concentrations exceed the I$,,, the situation is most severe and rescue activities will be at the highest possible level. It is not very likely that an LC, will be considered less dangerous than an LCa,. The Green Book probit approach is based on LC5,, values, as these data are available in relatively large numbers and have the highest accuracy. The extrapolation factor in the calculation of the human LCsO accounts for the interspecies differences between animals and humans. Application of safety factors is common practice in risk evaluation for foodstuffs when establishing no-effect levels; then, however, safety factors are often of the order of magnitude of 100-1000. The assumed probit slope of 1 accounts for the intraspecies differences within the human population. Because the actual spreading in susceptibility of the population is not known, such a conservative approach is favourable. Furthermore, the uncertainties in the probit functions are greatest in the upper and lower ends of the function. The determination of probit functions presented here is a first step towards reliable vulnerability models. The Green Book methodology is applicable for toxic materials for which only few toxicity data are
J. Loss Prev. Process lnd., 1991, \/o/4, July
275
Exposure to toxic gases: D. de Wegeret
al.
available. The probit functions apply for lethality; with today’s knowledge, establishing well defined probit equations for other health effects is not feasible. In the near future, the research programme should be started, directed towards the development of a more fundamental approach to the modelling of acute toxicity. If the b ‘ lack box’ between administration of a chemical and response of the organism can be filled in with models that adequately describe the fate of a chemical in the body, this will lead to a greater insight into several important aspects of toxicity. Not only will the extrapolation from animal to human toxicity data be improved, but more knowledge will be achieved about non-lethal health effects. The next step to take is the application of the principles of pharmacokinetics to the characteristics of exposure to hazardous chemicals in the case of industrial disasters. Such an approach may lead to the next generation of toxicity vulnerability models.
References 1 TNO, ‘Methods for the Calculation
of Physical Effects of Releases of Hazardous Materials’ (Yellow Book), Dutch Ministry of Social Affairs, The Hague, 1988 (2nd edn only in Dutch) 2 TN0 ‘Methods for the Determination of the Possible Damage to Humans and Goods by the Release of Hazardous Materials’
276
J. Loss Prev. Process Ind., 7997, Vol4, July
3 4 5 6
7
8
(Green Book), Dutch Ministry of Housing, Physical Planning and Entironment, The Hague, 1990 TNO, ‘Methods for Determining and Processing Probabilities’ (Red Book), Dutch Ministry of Social Affairs, The Hague, 1987 Probabilities for Use in Reliability and Risk Analysis Studies, TN0 report 87-298, Apeldootn, The Netherlands, October 1988 Finney, D. J. ‘Probit Analysis’, 3rd Edn, Cambridge University Press, 1980 ten Berge, W. F. and Guldemond, C. P. ‘Required knowledge for the evaluation of health hazards from acute inhalatory exposure of humans’, paper presented at the meeting of the International Process Safety Group, Cannes, 14-15 September 1986 Rutten, A. L. M., Zwart, A. and Reuzel, P. G. J. ‘Concentrationtime relationships in acute toxicity: a theoretical study’, poster presented at the Inhalation Toxicology Symposium, Hatmover, 23-27 March 1987 Hattis, D., Erdreich, L. and Ballew, M. RiskAnal. 1987,7,415
Nomenclature
Tt b C D D'
D"
k u
u
V,
W
Coefficient Lung surface area (m2) Coefficient Concentration of gas (mg rne3) Inhaled dose (mg) Dose per unit body mass Dose per unit lung surface (m Effective dose Coefficient Probit Exposure time (min) Regression coefficient Regression coefficient Minute ventilation (1 mint) Body mass (kg)
Acute toxicity data are important in risk analysis. In this paper, recent developments in consequence modelling, reported in the so-called Green Book (published by the Dutch Ministry of .Housing, 1990), are presented. The Green Book offers a simplified approach to determine probit functions for man, based on a relatively limited set of toxicity data. The determination process consists of two steps: (1) estimating a human LC 50 from animal data, taking into account interspecies differences and the amount of information available; (2) calculating the probit parameters, based on a value of 1 for the slope of the probit function, which is a conservative assumption with respect to the variation in vulnerability of a human population exposed in emergency circumstances. The probit functions thus derived are a step towards more reliable vulnerability models. The extrapolation of animal data to human data contributes substantially to the uncertainty in risk analysis results. To improve this situation, research into the mechanisms of behaviour of the chemicals in the body is required. (Keywords: toxicity, risk assessment; modellingl
In the last few decades, a number of accidents with industrial chemicals have occurred, some with very large numbers of casualties (e.g. Seveso, Mexico, Bhopal). Public concern has urged the authorities in many countries to impose regulations on industrial activities with hazardous materials, and industry itself is becoming increasingly aware of the necessity for a proper safety policy. The use of safety and risk assessment studies has improved considerably over the last decade. Over the years TN0 has been involved in the development of a risk assessment methodology and of the mathematical models that are required in such a methodology. A risk analysis is one of the tools that can be used to assess the risk of an industrial accident. A risk analysis normally consists of the following steps: 1. identification of potential hazards for releases of hazardous materials; 2. calculation of physical effects of those releases; 3. calculation of consequences due to those effects (e.g. health damage); 4. calculation of the probabilities of steps 1-3; 5. final risk evaluation: combine consequences and probabilities and give risk-reducing recommendations for determination of accident scenarios.
Received
22 November
09504230/91/&40272-05 @ 1991 Butterworth-Heinemann
272
1990 Ltd
J. Loss Prev. Process Ind., 1991, Vol4, July
Physical effect models developed by TN0 have been brought together in the ‘Yellow Book”, enabling calculation of the behaviour of chemicals during phenomena such as explosion, fire, gas dispersion, pool evaporation, etc. Calculation results include explosion overpressure, atmospheric gas concentrations and the amount of heat radiation. Recently, the ‘Green Book’2 has been issued, in which a number of consequence models is presented. These models enable the user to relate the calculated physical effects to the amount of damage to people and constructions. Furthermore, in the ‘Red Book’3 and the supplementary manua14, models and data for the calculation of probabilities are given. With publication of the Green Book, a series of standards has been completed. An important part of the Green Book is the chapter ‘Health damage by acute intoxication’. In the following, the background of the modelling approach is given, together with a brief description of the results.
Modelling of the consequences of a toxic chemical
of the release
In a quantitative risk analysis (QRA) of industrial activities, the consequences and probabilities of releases of hazardous materials are considered. In the case of industrial disasters, acute intoxication of residents in the vicinity of the plant usually occurs by
Exposure exposure to gaseous materials. Therefore in this paper, as well as in the Green Book, toxicity modelling has been limited to inhalation toxicity. It is common practice in QRA to evaluate toxicity risks by calculation of the percentage of the population exposed that shows a certain health effect (usually lethality). The mathematical technique used is the probit analysis, described by Finney’ . Probit equations offer the user the possibility to calculate the response for each combination of exposure time and concentration, or vice versa, to calculate the concentration for a given exposure period and response. In this respect probit analysis is a more powerful technique than risk evaluation with, for instance, just a LCm value, which gives the concentration leading to a fixed response percentage. Probit equations are established using a series of toxicity data for a specific health effect and exposure route and preferably for one species. Toxicity data have to be obtained for a range of exposure times and/or concentrations and response values. As little toxicity data for man are available, especially in the higher response percentages, human probit functions have to be established by extrapolating from animal data. This step introduces a considerable uncertainty into the human data. In the Green Book, a number of probit functions has been derived, making use of a simplified approach which is mainly applicable if only limited toxicity data are available. However, continuous effort is taking place to improve the methodology used in the determination of human toxicity data.
The Green Book probit approach The probit functions in the Green
Book
essentially
have the following features: the probit function is based on a human LCsO, derived from animal LC& data using a safety factor which depends on the amount of information available; the slope of the probit function has a value of 1, which is a conservative assumption; only probit functions for lethal injury are given.
Estimation of human LC,& Since empirical human LC&, values are not available, values have been estimated from animal LC50 values available in the literature. In these calculations, an extrapolation factor is used consisting of two terms: the first takes into account the physical interspecies differences (e.g. body mass, breathing volume, lung siuface, oxygen consumption) for which reasonably well-known empirical relationships exist; the second is a safety factor which takes into account other, less defined differences as well as differences in behaviour during exposure situations. Furthermore, the extrapolation factor is
to toxic gases:
D. de Weger et al.
adjusted, dependent on the amount of information available for a specific chemical. For inhalation toxicity, a distinction can be made between locally acting substances and systemically acting substances. Locally acting substances cause direct damage to the respiratory tract. Therefore, as a measure of the severity of the consequences, the inhaled dose per unit lung surface can be taken as the effective dose, D”:
D” = D/A
(mg m-‘)
(1)
The inhaled dose is determined by the respiration rate, the concentration of the gas and the exposure time: D = (V,/lOOO)Ct
(mg min-‘)
(2)
The lung surface and respiration rate are dependent on the body mass according to the following empirical relationships6: v
a
=
,wO.‘O
A = ,W”.g2
(3) (4)
It follows that D” - (U/U)w-o~22
(5)
This equation accounts for the physical differences between animals and humans, which for locally acting substances comes down to a difference in lung properties. These are eventually expressed in terms of body mass as this is an easily measureable quantity. However, differences between animals and humans are not limited to simple lung properties such as those mentioned above. In general, the retention in the animal nose is higher than the retention in the human respiratory tract. Furthermore, experimental animals are obligatory nose breathers, whereas man is not, which may be an additional cause for larger amounts of material to reach the human lungs. Another factor whichmust be taken into account is the difference in behaviour between animals and humans in exposure situations. It is assumed that at least a part of the exposed human population will try to escape from the accident area. Together with the stress factors accompanying accident situations, this will result in an increase in breathing frequency. Some animal species, however, show the opposite behaviour, in that they dramatically decrease their respiratory frequency in the first few minutes of exposure to irritant chemicals. Therefore, a safety factor of 10 was adopted for locally acting substances, consisting of a factor of 5 accounting for less adsorption in the human respiratory tract and a factor of 2 accounting for behaviour differences between animals and humans. For systemic agents a similar approach is followed. Systemic agents cause damage to the body once they have been absorbed into the blood and distributed through the body. For these chemicals, the differences between animals and humans are largely due to physiological and pharmacokinetic mechanisms. In this case, the measure for the severity of the consequences
J. Loss Prev. Process Ind., 7991, Vol4, July
273
Exposure to toxic gases: D. de Weger et a I. is the dose per unit body mass: D’ = D/W
(mg kg-‘)
(6)
The amount absorbed is assumed to be related to oxygen consumption, which again is linearly related to the respiratory minute volume. Substitution of the empirical relation from Equation (3) into (6) gives: D’ - uw-o.3
(7)
This relation accounts for the differences in absorption of the chemical by animals and humans. However, the toxicity of systemic agents largely depends on pharmacokinetics, metabolism and the actual toxic working mechanism in the target organ. Because very few data are available on these subjects, a conservative safety factor of 10 is taken. Together with the safety factor for behavioural differences (which is the same as that chosen for locally acting substances) the overall safety factor for systemic agents becomes 20. In Table I the extrapolation factors for a number of species are given for both locally acting substances and systemic agents. In this approach, the final extrapolation factors for both substance categories appear to be in the same value range. Therefore, one extrapolation factor per species has been chosen. The estimation of the human LCsO has to be
Extrapolation
Table1 L&(30
factors
Species
Substance category
Rat
Systemic Loca I
Mouse
Toxic load factor
274
of probit constants
J. Loss Prev. Process lnd., 1991, \/o/4, July
of
human
3.3 5.1
20 10
;I;;
0.25
Systemic Local
10.2 5.5
20 10
;;;
0.5
Guinea pig
Systemic Local
2.6 3.8
20 10
;*;;
0.2
Hamster
Systemic Local
3.6 5.8
20 10
;:;;
0.3
carried out according to the scheme given in Figure 1. Before applying the extrapolation factor, the animal values may have to be recalculated for an exposure period of 30 min (the length of time considered to be the maximum exposure in accident situations), using Equation (8): C” t = constant
(8)
If the coefficient RZis not known, an arbitrary value of 2 is chosen. This is in fact a conservative approach. From theoretical considerations, it can be derived that n may
x [t/30)‘”
No
Figure 1 Scheme for determination
estimation
Extrapolation factor
30 min) = LC,(i)
a =5 -
the
Safety factor
Yes LC,(i,
for
min)
I n[ [LCSO(man)~. 30 }
Exposure to toxic gases: D. de Wegeret be dependent on the working mechanism of the chemical. If the active substance is a metabolite, the value of R would be 1; if the chemical itself is the working substance or if it is not known whether metabolism plays any part in the working mechanism, the value of n would be 2 (Ref. 7). However, this hypothesis needs experimental verification. After application of the safety factor, the amount of information available is taken into account. If toxicity data for more than one species are available, the extrapolation factor is increased with a factor of 2, being a correction in a less conservative direction. A probit equation is a Calculation of probit constants. mathematical relationship between the response fraction and the ‘probit’ (or ‘probability unit’), which are related via the normal distribution5. The probit is given by the following equation: Pr=a+blnC”t
(9)
Probit equations are determined for a specific health effect by regression of the response as a function of toxic load (oral dose, or the combination of inhalatory concentration and exposure period). Probit constants are known for only a limited number of substances, and are mainly based on animal toxicity data. In the determination of the human probit equations, the intraspecies differences are accounted for. Animal toxicity data are obtained from relatively homogeneous populations, whereas the variation in the human population exposed during an accident can be very wide. To account for the larger response spread, the slope of the probit equation has been set to 1. This means that the LCg5 relates to the LCos as 27; this value is conservative but still realistic, when compared to the empirical value of 12, determined by Hattis et al.’ from human volunteer data. The results of the calculation of probit constants are given in Table 2.
Summary and conclusions The determination of probit equations applicable for humans is presented here as a two-step process: estimation of a human LCsO followed by calculation of the probit constants. In the first step, an extrapolation factor is used which takes into account the differences between animals and humans. For locally acting substances these are the respiratory volume and the lung surface. These properties can be empirically related to body mass. Furthermore, differences between animals and humans in breathing pathways (nose or nose and mouth), in susceptibility of the lung tissue and in the influence of lung damage to the organism as a whole were brought together in a safety factor, as well as behavioural differences that may influence the respiratory frequency and thus the total respiratory minute volume. For systemic agents, oxygen consumption is taken as the measure for toxic load, which is also assumed to be related to the respiratory volume. In this case, the
Table2 Probit constants for humans, calculated the method described in this paper (see figure tions in mg-3, exposure time in minutes
according to concentra-
I),
Chemical
30 minLC, (ma mm31
n
b
a
Acrolein Acrylonitrile Ammonia Bromine Carbon monoxide Chlorine Ethylene oxide Hydrogen chloride Hydrogen cyanide Hydrogen fluoride Hydrogen sulphide Methyl bromide Methyl isocyanate Nitrogen dioxide Phosgene Sulphur dioxide
304 2533 6164 1076 7949 1017 4443 3940 114 802 987 3135 57 235 14 5784
1.o 1.3 2.0 2.0 1 .o 2.3 1.0 1.0 2.4 1.5 1.9
1
-4.1 -8.6 -15.8 -12.4 -7.4 -14.3 -6.8 -6.7 -9.8 -8.4 -11.5 -7.3 -1.2 -18.6 -0.8 -19.2
A:: 3.7 0.9 2.4
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
al.
safety factor reflects the differences in pharmacokinetits and pharmacodynamics and the lack of knowledge on this subject. Behavioural differences are evaluated in the same way as with locally acting substances. In calculating the human LCso, the safety factors are multiplied by a factor 2 if toxicity data for more than one species are available. This means that a larger amount of information is credited for by a less conservative approach. In the second step, to account for the variability in vulnerability in the human population, which is larger than in experimental animal populations, the slope of the probit .equation is set to 1. This limits the applicability of the probit functions to responses below 50%, which however is not a very serious limitation in accident evaluation. In reality, if concentrations exceed the I$,,, the situation is most severe and rescue activities will be at the highest possible level. It is not very likely that an LC, will be considered less dangerous than an LCa,. The Green Book probit approach is based on LC5,, values, as these data are available in relatively large numbers and have the highest accuracy. The extrapolation factor in the calculation of the human LCsO accounts for the interspecies differences between animals and humans. Application of safety factors is common practice in risk evaluation for foodstuffs when establishing no-effect levels; then, however, safety factors are often of the order of magnitude of 100-1000. The assumed probit slope of 1 accounts for the intraspecies differences within the human population. Because the actual spreading in susceptibility of the population is not known, such a conservative approach is favourable. Furthermore, the uncertainties in the probit functions are greatest in the upper and lower ends of the function. The determination of probit functions presented here is a first step towards reliable vulnerability models. The Green Book methodology is applicable for toxic materials for which only few toxicity data are
J. Loss Prev. Process lnd., 1991, \/o/4, July
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available. The probit functions apply for lethality; with today’s knowledge, establishing well defined probit equations for other health effects is not feasible. In the near future, the research programme should be started, directed towards the development of a more fundamental approach to the modelling of acute toxicity. If the b ‘ lack box’ between administration of a chemical and response of the organism can be filled in with models that adequately describe the fate of a chemical in the body, this will lead to a greater insight into several important aspects of toxicity. Not only will the extrapolation from animal to human toxicity data be improved, but more knowledge will be achieved about non-lethal health effects. The next step to take is the application of the principles of pharmacokinetics to the characteristics of exposure to hazardous chemicals in the case of industrial disasters. Such an approach may lead to the next generation of toxicity vulnerability models.
References 1 TNO, ‘Methods for the Calculation
of Physical Effects of Releases of Hazardous Materials’ (Yellow Book), Dutch Ministry of Social Affairs, The Hague, 1988 (2nd edn only in Dutch) 2 TN0 ‘Methods for the Determination of the Possible Damage to Humans and Goods by the Release of Hazardous Materials’
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3 4 5 6
7
8
(Green Book), Dutch Ministry of Housing, Physical Planning and Entironment, The Hague, 1990 TNO, ‘Methods for Determining and Processing Probabilities’ (Red Book), Dutch Ministry of Social Affairs, The Hague, 1987 Probabilities for Use in Reliability and Risk Analysis Studies, TN0 report 87-298, Apeldootn, The Netherlands, October 1988 Finney, D. J. ‘Probit Analysis’, 3rd Edn, Cambridge University Press, 1980 ten Berge, W. F. and Guldemond, C. P. ‘Required knowledge for the evaluation of health hazards from acute inhalatory exposure of humans’, paper presented at the meeting of the International Process Safety Group, Cannes, 14-15 September 1986 Rutten, A. L. M., Zwart, A. and Reuzel, P. G. J. ‘Concentrationtime relationships in acute toxicity: a theoretical study’, poster presented at the Inhalation Toxicology Symposium, Hatmover, 23-27 March 1987 Hattis, D., Erdreich, L. and Ballew, M. RiskAnal. 1987,7,415
Nomenclature
Tt b C D D'
D"
k u
u
V,
W
Coefficient Lung surface area (m2) Coefficient Concentration of gas (mg rne3) Inhaled dose (mg) Dose per unit body mass Dose per unit lung surface (m Effective dose Coefficient Probit Exposure time (min) Regression coefficient Regression coefficient Minute ventilation (1 mint) Body mass (kg)