Paper ESREL Self-Rescue in Quantitative Risk Analysis

7/31/2019 Paper ESREL Self-Rescue in Quantitative Risk Analysis

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1 INTRODUCTIONIf safety measures for self-rescue can not be as-sessed within a quantitative risk analysis (QRA), therisk judgement system does not motivate companiesor local authorities to take measures, because theireffects are not visible in a state-of-the-art risk as-

sessment. In most quantitative risk analysis methods,persons present in the hazardous area are assumed tobe exposed for a fixed amount of time. Assumptionsfor fixed exposure times are 30 minutes for a toxicexposure and 20 seconds for exposure to heat radia-tion. Furthermore, persons are assumed to stay onthe same place. The reality is different: in case of anemergency, every person capable of escape will tryto rescue himself. In case of a toxic release it is pos-sible that a safe place (for example inside a building)is reached within the prescribed 30 minutes. On theother hand, in case of fire in crowded places, it canbe expected that people are unable to escape within20 seconds. Examples of methods are the Dutchprobabilistic QRA methods for transport of danger-ous goods and for stationary installations (Uijt deHaag 2006). In QRA calculations where self-rescueis very important, for instance in tunnel safety stud-ies, extensive calculations with evacuation modelsare performed. Subsequently the output of theevacuation models is used in the QRA, the evacua-tion model is not integrated within the QRA.

The model described in this article provides a so-

lution between evacuation modelling, which mightbe too time-consuming and state-of-the-art QRA-calculations, which have insufficient detail to showthe effect of safety measures. The model can be in-tegrated in a quantitative risk analysis method,

therewith enabling to account for self-rescue and toshow the effect of safety measures by running a sin-gle QRA model. The model is especially suitable forQRAs involving risks to densely populated areas,such as railway stations, stadiums, and offices aswell as for industrial plants and their inhabited sur-roundings.

2 MODEL OUTLINEIn order to judge the effect of self-rescue improvingmeasures, a model has been developed to quantifythe effect of self-rescue, depending on exposure tofire or toxic chemicals. The model distinguishes heatradiation, smoke and several types of toxic chemi-cals and quantifies their effect on the walking veloc-ity and exposure duration (see Figure 1).

Figure 1. Self-rescue in quantitative risk analysis

Self-rescue in quantitative risk analysis

I.J.M. Trijssenaar- Buhre & I.M.E. Raben & T. Wiersma & S.I. WijnantTNO, Apeldoorn, The Netherlands

ABSTRACT: In quantitative risk analysis (QRA) methods, the damage of toxic and fire effects to persons isdetermined using a fixed exposure time. The model described in this paper enables to include self rescue inQRA methods. The model can be used 1) for calculations of a more realistic exposure time, 2) to determinethe number of persons incapable of self-rescue, which is important information for the rescue services 3) to

determine the effect of safety measures improving self-rescue. The model provides a solution betweenevacuation modelling, which might be too time-consuming and state-of-the-art QRA-calculations, which haveinsufficient detail to show the effect of safety measures.


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Other factors that are considered in the model are thedistance to a safe location and the presence of a bot-tleneck in the evacuation route. The model can beused for the following purposes: For fast calculations of the exposure time and the

number of persons incapable of self-rescue; To determine the effect of safety measures im-

proving self-rescue, by calculating the remaining

consequences for a scenario after taking meas-ures. Subsequently these consequences can becompared to those of the original scenario in theQRA.

The following sections show the relations for de-scription of the toxic effects and their influence onthe mobility or walking velocity. Note that in case offire, for instance, there can be interaction betweentoxic exposure and heat exposure: if the mobility de-creases due to toxic exposure (smoke), the exposuretime to heat can increase.

3 TOXIC INJURIESFor toxic injuries a distinction is made between as-phyxiant and irritant gases. For an asphyxiant prod-uct, such as carbon monoxide, the most importantcriterion for its toxic effects is the concentration inthe blood supply to the brains. On the other hand, foran irritant product the most important factor is theconcentration in the lining of the nose, throat, orlung (Purser 2002).

3.1 Asphyxiant fire productsThe Fractional Incapacitation Dose (FID) model ofPurser (Purser 2002) has been selected to describethe effects of asphyxiant fire products for their pres-ence in fire smoke as well as for the pure substance.The FID model relates the toxic dose inhaled by aperson to the dose where incapacitation (i.e. loss ofconsciousness) occurs. The FIN is the sum of theFID values for all asphyxiant fire products, whichalso accounts for hyperventilation resulting from ex-posure to carbon dioxide. Incapacitation occurs by a(cumulated) exposure to carbon monoxide, hydro-cyanic acid and oxygen deficiency (FINtotal =1) or byexposure to high concentrations of carbon dioxide(FIDCO2 =1).

22*)( OHCNCOtotal FIDVCOFIDFIDFIN ++= (1)

where FIDCO, FIDHCN and FIDO2 = Fractional Inca-pacitation Dose for CO, HCN and O2 respectively;

CO = carbon monoxide; HCN = hydrocyanic acid;O2=oxygen; CO2 = carbon dioxide; VCO2 = multi-plication factor hyperventilation [-].

The Fractional Incapacitation Dose is described forCO, HCN, O2, and CO2 by equation 2 to 6 (Purser2002).

PID

tRMVCOFID

CO

036.15 ][10317.3 = (2)

where [CO] = CO concentration in ppm; RMV

=Respiratory Minute Volume in litre/min, which is25 litre/min at light activity; t = exposure time inmin; PID = Personal Incapacitation Dose =30%.

The FIDs for oxygen and hydrocyanic acid are de-scribed by equations 3 and 4. Equation 3 and 4 arevalid for relatively short exposure time (shorter than1 hour) and a constant concentration.

)%9.20(*54.013.8 22 OVO e

tFID

= (3)

where V%O2 = O2 volume percentage;

][*023.0396.5 HCNHCN e

tFID

= (4)

where [HCN] = HCN concentration in ppm.

Carbon dioxide (CO2) increases the RespiratoryMinute Volume, resulting in a larger uptake rate ofother gases. The increase of Respiratory MinuteVolume by hyperventilation is described by a multi-

plication factor VCO2:

1.7

004.22%*1903.0

2

+

=

COVeVCO (5)

where V%CO2 = CO2 volume percentage.

Besides its effect on the Respiratory Minute Vol-ume, CO2 in itself can lead to incapacitation whenpresent in higher concentrations.

22 %*5189.01623.6 COVCO etFID

= (6)

Using equations 1 to 6, the FIN can be determinedfor toxic fire products within fire smoke as well asfor the separate toxic substances.

For asphyxiant fire products the time to incapaci-tation and its severity usually show a short period ofintoxication that is followed by a relatively sharpdecline into incapacitation (Purser 2002). The rela-tion between FIN and mobility is shown in figure 2(University of Greenwich, 2004).


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0,0

0,2

0,4

0,6

0,8

1,0

0 0,2 0,4 0,6 0,8 1

FIN or FIC

Mobilit

yfactor

FIN

FIC

Figure 2. Mobility as a function of FIN and FIC

3.2 Irritant fire productsDose calculations are applied for incapacitation ef-fects of asphyxiant fire products as well as for the le-thal effects of irritant fire products. However, the in-capacitation effect of irritant fire products is relatedto the concentration instead of the dose. The toxiceffects are described by the Fractional Irritant Con-centration (FIC) model.

22

][][][][][ 22

NOSOHFHBrHClF

NO

F

SO

F

HF

F

HBr

F

HClFIC ++++= (7)

where [HCl] = Hydrochloric acid concentration inppm; FHCl = threshold concentration for HCl in ppm;

The threshold values for irritant fire products aregiven in table 1. Incapacitation occurs when the FICequals unity, for which the toxic effect of differentirritant fire products can be added. The relation be-

tween FIC and mobility is shown in figure 2 (Uni-versity of Greenwich, 2004).

Table 1. Threshold values for irritant fire products_____________________________________Toxic gas Severely irritant concentration

(ppm)_____________________________________HBr 200HCl 200HF 120NO2 80SO2 30_____________________________________

3.3 Toxic chemicalsIn order to be able to translate the presence of toxicchemicals into mobility, the methods of FID and FICare also applied for releases of toxic chemicals. Thegeneral equations for the FID and FIC methods are:

== =

==

n

i i

in

i

t

t i

i

Ct

tDt

Ct

CFID

11 0 )(

)(

)(

(8)

=

=

n

i i

i

F

CFIC

1

(9)

where Ci = average concentration in ppm of chemi-cal i over the chosen time increment; t = chosentime increment in min; Di(t) = dose of chemical i attime t; (Ct)i = the threshold dose in ppm*min; Fi =threshold concentration for chemical i in ppm.

Because the FID and FIC threshold values are only

known for fire products, other threshold values arerequired for the toxic chemicals. The Acute Expo-sure Guideline Level 2 (AEGL-2) is very suitablefor the definition of ability of self-rescue. AEGL-2 isthe airborne concentration of a substance abovewhich it is predicted that the general population, in-cluding susceptible individuals, could experience ir-reversible or other serious, long-lasting adversehealth effects or an impaired ability to escape.AEGL-2 values are available for exposure durationsof 10 minutes, 30 minutes and 1 hour, 4 hours and 8

hours. The subdivision of several chemicals in as-phyxiant and irritant as well as their threshold valuesare shown in table 2. The chemicals in table 2 arerepresentative for various hazard categories as usedin QRAs. The AEGL-2 is not (yet) determined foracrylonitrile and ethylchloride, the ImmediatelyDangerous to Life and Health (IDLH) value is usedfor these chemicals. IDLH is defined as a concentra-tion that an exposure up to 30 minutes does notcause death, serious or irreversible health effects, ordoes not impair or impede the ability to escape.

Table 2. Subdivision and AEGL-2 threshold values of toxicchemicals.________________________________________________Chemical Subdivision Concentration (ppm)__________________

10 min 30 minexposure exposure________________________________________________

Acrylonitrile FID - 85*Ethyl chloride FID - 3800*Ammonia FIC 220 220Chlorine FIC 2.8 2.8Methylisocyanate FID 0.40 0.13Nitric acid FIC 43 30_____________________________________________* IDLH threshold value

The FID can now be determined by calculatingthe threshold dose (Ct) from table 2 and insertingthis value into equation 8. For instance, the threshold


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dose (Ct) for acrylonitrile is 255 ppm*min. The FICcan be determined by taking the threshold concentra-tion from table 2, for nitric acid the value dependsslightly on the timescale of the calculations (10 minor 30 min value).

The FID and FIC are translated into a walking ve-locity using the relations shown in figure 2.

4 THERMAL INJURIESExposure to thermal radiation is assumed to have lit-tle or no effect on the mobility of the victims, untilthe injuries become lethal. During the self-rescue pe-riod, the heat radiation to which the person is ex-posed will decrease with the distance. This is ac-counted for by calculating the effective exposureduration (CPR 16E 1992):

++

3

5

0

0 115

3vreff

tx

u

u

xtt (10)

where teff = effective exposure time (s); x0 = the ini-tial distance to the fire source (m); u = the evacua-tion velocity (m/s); tr = reaction time (= 5 s); tv = (xs-x0)/u = evacuation time (s); xs = distance from firesource where heat radiation is below 1 kW/m

2(m).

The evacuation velocity, u, can be influenced byexposure to toxic fire products: if the mobility de-

creases the exposure time to heat is increased:u = mobility factor * u0, where u0 = maximumevacuation velocity. The effective exposure time ob-tained with equation 10 can subsequently be used tocalculate degree of injuries and lethal victims due toheat exposure.

5 EVACUATIONTwo important characteristics of the evacuationroute are included in the model, namely the distance

to a safe location and the presence of bottlenecks onthe evacuation route.

5.1 Distance to safe locationThe distance to a safe location can be defined by athreshold value (concentration, maximum dose orheat radiation level) or it can be the distance to aplace to shelter, such as a building, where windowsand doors can be closed. The mobility of a person isinfluenced by the concentration or toxic dose to

which he is exposed on his way to the safe location.In case of fire, the distance to a heat resistant shelteror the distance to 1 kW/m

2(xs) is inserted in equa-

tion 10.

5.2 Bottlenecks on the evacuation routeThe evacuation calculations within the model are notintended to model the evacuation route in detail.However in cases of important bottlenecks in theroute, such as a door or stairs, it can be very impor-tant to be able to model the effect of the bottleneck.The evacuating persons need to pass the bottleneckbefore reaching a safe location. The actual exposure

time increases due to the time necessary to pass thebottleneck. An average value for the extra exposuretime due to the bottleneck is given by:

tbottleneck= n/ Cbottleneck (11)

where n = number of persons that need to passthrough the bottleneck (-); Cbottleneck= bottleneck ca-pacity in number of persons per minute.

6 IMPLEMENTATION AND APPLICATION6.1 Model implementationThe model can be implemented in several ways, thischapter describes the following examples:1 Straightforward implementation for QRA

method;2 Dynamic implementation for scenario analysis or

more extensive QRA calculations.The difference in implementation is the level of de-tail of modelling the effect of toxic exposure to theevacuation velocity.

6.2 Straightforward implementation methodFor the QRA method a straightforward implementa-tion is often sufficient. In this case the evacuationvelocity is based on the concentration profile on thestarting location of the person. For asphyxiantchemicals, the first step is to estimate the exposuretime with the maximum evacuation velocity, u=u0,

according to:

texp = tr + tbottleneck+(xs-x0)/u; (12)

Subsequently the dose is determined using the con-centration profiles Ci(x0, t) on the starting location ofthe person:

=t

ii dttxCtD0

0 ),()( (13)

FID and corresponding mobility factor are calcu-lated with the equations in sections 3.1 or 3.3 andfigure 2. Subsequently the effective exposure time isdetermined with equation 12, this time with u= mo-bility factor*u0:


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teff= tr + tbottleneck+ (xs-x0) / (mobility factor*u0)

In the final step the effective FID is determined us-ing the effective exposure time. The effective FID isused to determine whether a person with a certainstarting location will become incapable of self-rescue during his attempt to escape (using figure 2).

For irritant chemicals the FIC at the starting posi-tion is determined with the equations in sections 3.2or 3.3 and the mobility factor is read from figure 2.The effective exposure time can then be calculatedwith equation 12, assuming u= mobility factor*u0.The effective exposure time is important input forcalculating lethal damage.

6.3 Dynamic implementation methodFor a scenario analysis the evacuation velocity willbe calculated dynamically: when a person moves to

another (safer) location, he will be exposed to alower concentration. Therefore the toxic dose willincrease less compared to staying on the same loca-tion. For each time increment t, the FID or FIC andmobility factor are calculated and used as input forthe next time increment until a person either reacheda safe location or is incapable of self-rescue. For irri-tant chemicals Ci(x,t) is input for equation 9. For as-phyxiant chemicals the dose is calculated with:

=t

ii dttxCtD0

),()( (13)

For both irritant and asphyxiant chemicals:x = x0 for t trx = x0 + u(t-tr) for t > tru= mobility factor*u0 is determined for each timeincrement with FID (as a function of Di(t)) or withFIC and corresponding mobility factors.

6.4 Model applicationsWhen applying the model, a more realistic expo-

sure time and therewith a more realistic estimationof the (lethal) damage of this exposure can be calcu-lated. Even more important, is the use of the modelto estimate the number of persons in the hazardousarea, who are not capable of self-rescue. The FIDand FIC can be determined for every exposed persondepending on his starting location. If the FID or FICof a person exceeds unity, that person will be inca-pable of self-rescue. Combining this information onself-rescue with population data yields the totalnumber of persons incapable of self-rescue.The number of persons incapable of self-rescue isimportant information for preparation and real-timeactivities of rescue services. In order to determine

the rescue capacity necessary to handle the accident,the number of persons incapable of self-rescue ismore relevant than the number of fatal injuries.

The effects of safety measures improving self-rescue can be determined with the use of the model.An example of a safety measure is increasing the ca-pacity of a bottleneck in the evacuation route orplacing a shelter or safe haven.

7 CONCLUSIONSWith state-of the art QRA methods, safety measuresfor self-rescue cannot yet be assessed. The modeldescribed in this paper enables to include self-rescuein QRA methods. The model distinguishes heat ra-diation, smoke and several types of toxic chemicalsand quantifies their effect on the walking velocityand exposure duration. Evacuation route characteris-tics considered in the model are the distance to a

safe location and the presence of a bottleneck in theevacuation route. The model can be used to deter-mine the number of persons incapable of self-rescue,which is important information for the rescue ser-vices. Furthermore the more realistic exposure timesobtained with the model can be used for improvingthe estimation of lethal damage.The model can be integrated within a quantitativerisk analysis method to directly show the effect ofself-rescue improving measures. The model is espe-cially suitable for QRAs involving risks to densely

populated locations, such as railway stations, stadi-ums, offices as well as industrial plants and their in-habited surroundings.

NOMENCLATURE

[CO] Carbon monoxide concentration (ppm)

AEGL-2 Acute Exposure Guideline Level 2: airborne

concentration of a substance above which it

is predicted that the general population, in-

cluding susceptible individuals, could ex-

perience irreversible or other serious, long-

lasting adverse health effects or an impaired

ability to escape

Cbottleneck Bottleneck capacity (persons / min)

Ci(x,t) Concentration profile of chemical i (ppm)

FHCl Threshold concentration for HCl (ppm)

FIC Fractional Irritant Concentration (-)

FID Fractional Incapacitation Dose (-)

FIN Sum of the FID values for asphyxiant fire

products (-)

IDLH Immediately Dangerous to Life and Health

(IDLH) value: concentration that an expo-sure up to 30 minutes does not cause death,

serious or irreversible health effects, or does

not impair or impede the ability to escape


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n Number of persons that need to pass through

the bottleneck (-)

PID Personal Incapacitation Dose (%)

QRA Quantitative Risk Analysis

RMV Respiratory Minute Volume (litre/min)

t Exposure time (min)

teff Effective exposure time (s)

tr Reaction time (= 5 s)

tv Evacuation time (s)u Evacuation velocity (m/s)

u0 Maximum evacuation velocity (m/s)V%O2 Oxygen volume percentage (%)

VCO2 Multiplication factor hyperventilation (-)

x0 Initial distance to the fire source (m)

xs Distance from fire source where heat radia-

tion is below 1 kW/m2(m)

REFERENCES

CPR 16E. 1992. Methods for the determination of possibledamage to people and objects resulting from releases ofhazardous materials. First edition. Committee for the Pre-vention of Disasters caused by dangerous substances. TheHague: directorate-General of Labour of the Ministry ofSocial Affairs and Employment. ISBN 90-5307-052-4.

Purser, P.A. 2002. Toxicity assessment of combustion prod-ucts, In: The SFPE handbook of fire protection engineering.3rd edition. Quincy, Massachusetts: NFPA. ISBN 087765-451-4.

Uijt de Haag, P.A.M. 2006. Handleiding RisicoberekeningenBEVI (Guidelines for quantitative risk analysis, in Dutch).

University of Greenwich. 2004. Building Exodus Manual.

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Paper ESREL Self-Rescue in Quantitative Risk Analysis