An assessment of risk and safety in civil aviation - Industrial Centre

Journal of Air Transport Management 6 (2000) 43}50
An assessment of risk and safety in civil aviation
Milan Janic
Centre for Transport Studies, Department of Civil and Building Engineering, Loughborough University, Loughborough, Leics LE11 3TU, UK
Abstract
Risk and safety have always been important considerations in civil aviation. This is particularly so under current conditions of
continuous growth in air transport demand, frequent scarcity of airport and infrastructure capacity, and thus permanent and
increased pressure on the system components. There is also the growing public and operators' awareness of these and other system
externalities such as air pollution, noise, land use, water/soil pollution and waste management, and congestion. This paper o!ers an
assessment of risk and safety in civil aviation. It deals with general concept of risk and safety, describes the main causes of aircraft
accidents and proposes a methodology for quantifying risk and safety. 2000 Elsevier Science Ltd. All rights reserved.
Keywords: Risk; Safety; Civil aviation; Externalities
1. Introduction
Society faces important challenges in how best to manage
modern technology. There is a need to e$ciently and
safely use and manage existing technologies; and then
how to make progress by introducing new technologies.
Introducing new technologies is usually expected to provide
social bene"ts through improved e$ciency and
safety. There is, however a need for care and awareness of
the negative impacts of any technology on the environment,
in its broadest sense, that can o!set at least some of
the gains from modernization and the introduction of
new innovations. Optimization involves the assessment
of such risk and ultimately the setting of standards to
maximize society's utility from new technologies.
There are di!erent de"nitions of risk. It may be de"ned
as the probability of occurrence of a hazardous event in
given period. Second, it may be considered as the possibility
that an individual or group be impaired through
the e!ects of speci"c actions in a more or less random
manner. Third, risk can be related to a statistically expected
value of loss (i.e., the statistical likelihood of
a randomly exposed individual being a!ected by some
hazardous event). In this case risk involves a measure of
probability of severity of adverse impacts. In addition,
there are very general classi"cations of risk (Evans, 1996;
Kanafani, 1984; Kuhlmann, 1981; Sage and White, 1980).
E-mail address: m.janic@lboro.ac.uk (M. Janic)
Risk may be voluntary or involuntary. Voluntary risk
is the risk that individuals elect to assume which is not so
with involuntary risk. Travelling by air represents voluntary
exposure to risk of death or injury while living
near a nuclear power plant or airport where some uncontrollable
radiation or aircraft accident may happen,
represents involuntary exposure to risk. Risk may involve
objectively or subjectively known or assumed exposure
probabilities in relation to space, population and
time dependency. Generally, spatial characteristic of exposure
probability range from quite localized to global
hazards. For many types of risks there are groups of the
population that bear speci"c risk. Dependent on whether
a hazard exists over a substantial time horizon and
whether the e!ects or separate exposures to hazard are
cumulative or not, dependent exposure probability to
risk may be continuous, periodic and cumulative.
Four types of societal risk can also be identi"ed (Sage
and White, 1980):
Real risk to an individual, which may be determined
on the basis of future circumstances after their full
development;
Statistical risk, which may be determined by the available
data on the incidents and accidents in question;
Predicted risk, which may be predicted analytically
from the models structured from relevant historical
studies; and
Perceived risk, which may intuitively be felt and thus
perceived by individuals.
0969-6997/00/$- see front matter 2000 Elsevier Science Ltd. All rights reserved.
PII: S 0 9 6 9 - 6 9 9 7 ( 9 9 ) 0 0 0 2 1 - 6

44 M. Janic / Journal of Air Transport Management 6 (2000) 43}50
Civil aviation is an activity where all four types of risk are
present. To companies providing insurance for airlines
#ying constitutes a known statistical risk of the occurrence
of an accident. For passengers who purchase their
insurance while on the ground, #ying represents a perceived
risk that usually exceeds statistical risk. To air
tra$c control authorities, anticipated changes in tra$c
patterns and equipment involve predicted risk. These
changes may be su$ciently good approximations of future
real risk assessments that they are incorporated in
decisions on the introduction of new ATC technology.
Aircraft accidents often have speci"c features that can
distinguish them from accidents associated with other
modes:
Because #ying may take place over long distances,
accidents may occur at any point in time or space.
Hence, there is exposure to individual and global
hazard.
Passengers and aircraft crews are primal target groups
exposed to risk of an accident but there are individuals
on the ground who may be exposed to the same
accidents albeit at a lower probability.
Although being a rare event in an absolute sense,
aircraft accidents can have severe implications.
Conditionally, any aircraft movement is an inherently
risky event, then, according to probability theory, aircraft
accidents may be classi"ed as highly unlikely
(although possible) events.
With respect to time dependency, risk is always present
during given time and space horizons (i.e., whenever
a #ight takes place). The e!ect is non-cumulative
and particularly related to the separate exposures of
the people on board.
A practical problem in air transport is how to manage
risk and safety. Typically, this has been resolved by
investigations of causes of fatal accidents, assessment of
their risk and setting-up a risk standards consistent with
society's preference function (Sage and White, 1980).
Assessment of the risk of aircraft accidents may be carried
out in di!erent ways, from highly intuitive to very
formal and analytical but is usually partitioned into
sub-tasks:
Risk determination relates to the risk identi"cation
involving new risk and changes in the risk parameters.
The latter involves determining the probability of occurrence
of risky events and the likely consequences of
their outcome.
Risk evaluation may be decomposed into risk aversion
and risk acceptance.
Risk measurement involves quanti"cation. One convenient
measure of risk is the number of accidents per
unit of a system's output. Air accidents have normally
be viewed in terms of fatal events with the system's
output de"ned as the number of aircraft kilometers,
passenger kilometers and/or aircraft departures over
a given period. This is useful for comparing risk and
the level of safety of di!erent transport modes, including
civil aviation, as well as for monitoring sustainability
of the sector. There are a number of ways of
modeling and statistically examining these data (Ang
and Tang, 1975; Johnston et al., 1989).
2. The safety record
In the late 1990s the world's airline #eet consists of
more than 15 000 aircraft #ying a network of approximately
15 million kms and serving nearly 10 000 airports.
The sector directly employs more than 3.3 million people,
with over 1.4 million in USA (Air Transport Action
Group, 1996). Some 12 billion people and 23 million
tonnes of freight are being moved per annum. The freight
"gure represents approximately one third of value of the
world's manufactured exports.
Total accidents are closely related to the scale of civil
aviation operations. A variety of international institutions,
organisations and agencies deal with forecasting
future trends, including International Civil Aviation Organization
(ICAO) and International Air Transport Association
(IATA). The airspace manufacturers such as
Airbus Industry, Boeing and Rolls Royce also make
projections. Some idea of projected growth can be seen in
Table 1 (International Civil Aviation Organization,
1994). The broad range of predicted growth rates vary
between 5 and 6.5% across particular forecasters with the
exception of the low "gure from Fokker.
Historically, when there has been relatively rapid
growth in air transport, it has often been followed by
a series of accidents. The occurrence of such events has
stimulated the introduction of technical and operational
measures. As a result, overall safety has improved over
time. ICAO, for example, has shown the fatality rate for
international and domestic schedule aviation operations
has been consistently decreasing over time. Between 1970
and 1993 the fatality rate fell from 0.18 to 0.04 fatalities
per 100 million passenger kilometers with particularly
marked reductions recorded between 1970 and 1977.
During the period 1984}1993, the trend was relatively
stable. The same analysis indicates that the number of
fatal accidents during this 23-yr period varied between 16
and 31/yr. The average number of accident per annum
was 25 and the average annual number of passenger
In this context, &sustainable' development can be de"ned as the
development in which the system's output increases and its negative
impacts on the environment stagnate or decrease. The sustainable
development of aviation sector can be evaluated through externalities
such as safety, air pollution, noise and congestion (Janic, 1999).

M. Janic / Journal of Air Transport Management 6 (2000) 43}50 45
Table 1
Example of air tra$c forecasts
Forecaster Period Average annual growth
Rate (pkm) (%)
Airbus Industry 1992}2001 5.8
2002}2011 5.1
Boeing 1993}2013 5.2
Rolls-Royce 1993}2012 5.2
AcDonnell Douglas 1990}2000 6.5
Fokker 1994}2013 3.5
ICAO 1992}2003 5.0
Source: International Civil Aviation Organisation (1994); Air Transport
Action Group (1996).
fatalities was 741/anuum. At the same time the output of
the sector rose from 1971 to 389 billion passenger-kilometers
which is over a 500% increase (International Civil
Aviation Organization, 1992,1994). Some are arguing
that the scope for further improvements in safety are
becoming exhausted implying that if the accident rate
remains the same, while air travel increases, the number
of accidents will inevitably rise (Cole, 1997).
3. Factors causing fatal air accidents
Investigating causes of fatal aircraft accidents is di$cult
because they generally stem from a complex system
of mutually dependent, sequential factors (Owen, 1998).
These factors can be classi"ed in several ways. First,
according to the current state-of-knowledge they can be
categorized into known and avoidable and unknown and
unavoidable causes. The former should be considered
conditionally in the sense that immediately after an accident
the real causes are seldom fully known but as the
investigation progresses they become known and avoidable.
The causes of some accidents are never uncovered.
Second, with respect to accident type, the main causes of
air accidents can conditionally be classi"ed into human
errors, mechanical failures, hazardous weather, and sabotages
and military operations.
Most accidents can be attributed to human error combined
with other factors. Human errors have been
present in the production, maintenance and operation
of aviation hardware ranging through aircraft, airports
and air tra$c control facilities and equipment. Human
operational errors can come about when workloads
exceed work ability, e.g., in stressful situations. In
The data exclude accidents in the former USSR and the events
involving unlawful interference with aviation.
aviation, working capacity primarily depends on the
ability to receive, select, process and distribute information
on an on-line and o!-line basis in the
control of individual aircraft or air tra$c. Long exposition
to heavy mental workloads causes stress that
can lead to fatigue and deterioration in work performance.
Under stressful conditions, diminished performance
may cause conscious or unconscious risky and
unsafe behavior and generate errors that may result in
fatal accidents. The most common types of such accidents
are mid-air collisions and aircraft #ying into
terrain.
Mid-air collisions have mainly been caused by air
tra$c controller errors usually involving a failure to
maintain prescribed separation minima between aircraft.
For example, the mid-air collision between BEA
and Inex-Adria aircraft on 10 September 1976 over
Zagreb was caused by an error of air tra$c control.
The investigation discovered that the controller had
been working for a long period under stress caused by
tra$c overloading and weaknesses in the monitoring
equipment that left it unable to safely support existing
volumes of tra$c. In the accident 176 people lost their
lives. It initiated improvements to the air tra$c
monitoring procedures at the location and hastened
the development of airborne anti-collision equipment
(Stewart, 1994).
Collisions of aircraft with terrain are mostly associated
with pilot-error, a cause identi"ed with many other
unexplainable air accidents. One example of air accidents
caused by pilot error was the crash of a British
Midland B737 near East Midlands Airport (UK) on
8 January 1989. Forty-one passengers were killed and
79 survived the accident. The inquiry found that the
crew made a series of mistakes caused by confusion in
reading instruments in an emergency approach following
an engine failure (Owen, 1998). Another example of
pilot error involved an American Airlines B727 on
8 November 1965 near Cincinnati (US). In this case,
the crew made mistakes in setting the altimeter and in
determining the vertical position of the aircraft while
approaching the airport in rainy weather (Stewart,
1994; Owen, 1998).
Crew inexperience can also cause air accidents. Inexperience
may lead to pilot-error, that together
with other factors may cause an accident with fatal
outcome. One of the examples is a crash of Air Florida
B737 on 13 January 1982 just after take-o! from
Washington National Airport (US). Seventy "ve
passengers and crew were killed and only "ve survived.
The investigation indicated that the main cause
of the accident was the accumulation of ice on the
aircraft wings and fuselage. The crew, who were inexperienced
in cold weather #ying, had not operated
the anti-icing system prior to before take-o! and
did not apply full engine take-o! power, which

46 M. Janic / Journal of Air Transport Management 6 (2000) 43}50
could save the aircraft despite severe icing (Owen,
1998).
Strictly, mechanical failures result from human errors
made whilst constructing, producing and maintaining
the equipment. Such errors can accelerate metal fatigue
and other failures in aircraft components. The
crashes of Comets are one example (Owen, 1998) and
another was the problem of an Aloha Airlines B737 in
1988 when the aircraft suddenly lost part of its cabin
roof and sides during #ight. In this latter case, investigators
found the main cause of cabin crack was metal
fatigue due to the frequency of take-o!s and landings
of the aircraft and corrosion due to frequent #ying in
salt air. Design problems lead to modi"cations in
equipment. The main cause of a crash of a DC-10 near
Paris in 1974 that killed 346 people was weakness in
the aircraft's doors and di$culties in to checking if
they were closed. The result was stronger and better
designed doors. The crash of a DC-10 at Chicago in
1979 happened due to engine failure. The event resulted
in stricter rules and procedures covering engine
maintenance and a review of take-o! speeds (Stewart,
1974).
The root-cause of many disasters originates in maintenance
workshops and in the factories where vital
components and systems have been produced. An
example "re on a British Airtours B737 at Manchester
Airport in 1985. Thermal fatigue, or weakening of the
metal by constant heating and cooling during an engine's
life produced a crack in the combustion during
the take-o!. The section separated from the engine and
hit the port wing fuel tank spilling of fuel on a hot
engine. Subsequently, cracks were found in other engines
of this type (Owen, 1998).
Hazardous weather such as thunderstorms and frontal
systems can cause troublesome winds, rain, snow,
fog, and low ceilings that may pose safety concerns
at all stages of a #ight. In particular, strong windshear
developing near airports can make #ying
di$cult because of its rapid change in speed and direction
and because of a loss of lift in certain conditions.
The crash of an Eastern Airlines B727 during
approach at New York's Kennedy Airport in June
1975 o!ers a case study of the dangers involved.
During the period 1970}1987 the US National Transportation
Safety Board identi"ed low-altitude wind
shear as the factor causing or contributing to 18 commercial
aircraft accidents; seven were fatal resulting in
the loss of 575 lives. The development of sophisticated
This example illustrates the importance of experience and training
in reducing the probability of an accident (Kuhlmann, 1981). However,
education and training of aviation sta! is expensive which poses problems
at time when airlines are under pressure to control costs (Dose,
1995).
weather reporting, forecasting and detecting systems,
onboard and ground-based, have reduced this type of
threat.
Terrorist actions are highly correlated with political
and economic tensions in the world. A typical example
was the crash of a B747 on 23 June 1985 due to
a suspected bomb explosion. After the crash security
measures at high risk airports were strengthened.
Such acts have also initiated the introduction of new
technologies and security procedures that are intended
to prevent an illegal entry onto the aircraft and to
detect the presence of weapons being taken onboard.
(Rosenberg, 1987).
Military and semi-military operations have also resulted
in accidents. One example was the crash of
a Korean B-747 over Sakhalin Inland killing 269
people. Due to navigational error the aircraft
deviated from its prescribed course and entered
Soviet airspace and #ew over a prohibited area.
After several warnings, the aircraft was shot down by
a Soviet missile. The event stimulated improved coordination
of civil and military aviation (Stewart,
1994).
Human errors can be reduced by training and the
structuring of air tra$c patterns so as to avoid excess
stress. Factors such as hazardous weather, mechanical
faults, sabotages and military operations would seem to
be more random and less easily dealt with. This does not
mean the system is unsafe. Safety should be considered
with respect to the base causes of accidents. If accidents
occur due to known and avoidable factors, the system
should be considered as unsafe. Otherwise, if accidents
occur for unknown and unavoidable reasons, the system
should be considered as safe.
4. A methodology for assessing the risk and safety
In civil aviation, risk has been assessed as the probability
of the occurrence of an air accident in terms of two
aggregate indicators, the accident rate and the fatality
rate. The probability of an air accident is very low making
it a di$cult and complex task to properly explain,
locate, and manage overall aviation safety. There is also
the need to consider the impact of policy on di!erent
impacted groups such as users, service operators (airlines,
airports, air tra$c control), aviation and non-aviation
professional and non-professional organizations and
public (Kanafani, 1984).
Two approaches for assessing risk and safety are considerd.
The causal approach looks at the number of
accidents and number of fatalities, the scale of the system's
output during a given period and other relevant
characteristics that are seen as relevant causal variables.
The number of accidents, deaths and injuries per unit of

M. Janic / Journal of Air Transport Management 6 (2000) 43}50 47
Fig. 1. Scheme of a Poisson-type events (process).
air transport output over time o!ers an indicator of
whether the sector's safety is improving.
The second approach involves the statistical modeling
the occurrence of air accidents over time; a Poisson
sequence or Poisson process is often deployed. Such
a process is based on the following assumptions (Ang and
Tang, 1975):
An event can occur at random and at any time or any
point in space. Past aircraft accidents have possessed
this characteristic. They occurred in a random manner
in di!erent parts of the world.
The occurrence of an event in a given time or space
interval or segment is independent on what happened
in any other non-overlapping intervals or segments.
Air accidents, except very rare mid-air collisions, have
occurred as the series of independent events in time
and space.
The probability of an event occurring in a small interval
῀t is proportional to ῀t and can be estimated by
λ῀t where λ is the mean rate of occurrence of the event.
It is assumed constant and equal to λ"1/¹
, where
¹
is the average time interval between consecutive
events. The probability of two or more occurrences in
῀t is negligible (of higher order of ῀t). From empirical
evidence, as ῀t is assumed to be a su$ciently short
period, the probability of an occurrence of more than
one aircraft accident will normally be negligible.
Fig. 1 illustrates a scheme of a Poisson process
that commences at time t"0 and at random times
t
, t
, t
, 2, t
, 2, t
, the Poisson-type events occur.
In Poisson processes the time intervals between successive
events is exponentially distributed, indicating nomemory
property in the process. This means that future
events do not depend on the number or time of previous
events. This would logically seem to be the case with air
accidents. Mathematically, let ¹ be the random variable
representing the time between any two consecutive
events. This variable is exponentially distributed. The
probability that no accident will occur in time period t is
P(¹'t) K P(X
"0)"e, (1)
Besides national aviation authorities and airlines, ICAO providing
the data on safety.
where, X
is the number of air accidents in time t and λ is
the average accident rate. Similarly, the probability of the
occurrence of at least one event in time t is
P(¹)t)"1!P(¹'t)"P(X
O0)"1!e (2)
5. Application of the methodology
5.1. Causal assessment
Causal assessment considers risk at the global level,
the level of airlines and level of particular aircraft type. At
the global level the number of deaths per passengerkilometer
is taken as the dependent variable GF
. This is
then regressed on the number of fatalities per aircraft
accident and the annual volume of passenger-kilometers
denoted by N
and PKM
, respectively. Data for period
1981}1996 are used for estimation (International Civil
Aviation Organization, 1994) in the following speci"cation
(Janic, 1999):
GF "3.80110#4.19610N
(2.983) (10.674)
!2.09510PKM
(3.446)
R
"0.901; F"69.296; D="1.617; N"16. (3)
The overall regression is signi"cant at the 1% level with
signi"cant coe$cients (t-statistics are in parenthesis). It
also has a relatively high explanatory power without "rst
order auto-correlation problems (Johnston et al., 1989).
The fatality rate increases with the number of people
killed per crash and decreases with the increase in the
level of output. The risk of crashes has signi"cantly fallen
despite more #ying.
The safety of airlines is assessed by regressing the
number of accidents per million #ights by an airline, A
,
on the its number of #ights, F. Fig. 2 illustrates the trend.
The accident rate per airline has decreased more than
proportionally with the cumulative number of #ights.
Since larger airlines have performed a larger number of
these #ights they would seem less risky than smaller ones.
US and European airlines have much lower accident
rates per total number of #ights than other carriers.

48 M. Janic / Journal of Air Transport Management 6 (2000) 43}50
Fig. 2. Dependence of the average fatal accident rate on the number of airline #ights (1970}1997).
Source of data: Internet (1998).
The risks associated with di!erent aircraft types
are found by regressing the number of accidents per
aircraft type AR
, on the number of #ights per aircraft
type F
, and the average age of particular
aircraft type E
. The data cover the period from the
entry into service of a particular aircraft type to 1992.
The aircraft types covered are Fokker F28, Fokker
F70/F100; Airbus A300, A310, A320; Lockheed L1011;
British Aerospace BAe146; Boeing B727, B737-1/200,
B737-3/4/500, B747, B757, B767; McDonnell Douglas
DC9, MD80 (Internet, 1998; Walder, 1991). The equation
used is
AR "1.206 #1.743F #0.900E
(0.692) (6.355) (3.887),
R"0.929; F"84.640; D="1.823; N"16. (4)
The overall equation and individual coe$cients are signi"cant
at the 1% level. The equation may o!er an
explanation of the past but this information was not
available in advance to those involved. The equation
indicates that the cause of air accidents could stem
from the existence of geriatric factors that escalated
faster as aircraft are utilized more and age. Because
the operational hypothesis is that aircraft accidents happen
as random events, the equation does not imply that
more used and older aircraft have been less safe. It
indicates that the risk of traveling in these aircraft is
higher.
5.2. Probabilistic assessment
The probabilistic assessment of accidents uses
a sample of 259 accidents over the period 1965}1998. The
distribution of time intervals between these events is
shown in Fig. 3. A simple calculation provides an estimate
of the average accident rate: λ7.818 accidents per
year or λ0.020 accidents per day. An analysis of the
time intervals between accidents, independent of aircraft
type, indicates they have been independent and exponentially
distributed (a χ test con"rms the hypothesis
matching the empirical and theoretical data, Ang and
Tang, 1975). This o!ers con"rmation that the observed
pattern of accidents can be treated as Poisson process.
Using the exponential distribution seen in Fig. 3, it is
possible to assess the probability of an occurrence of an
air accident. If there is unlikely to be any improvement in
safety features then this distribution can be used for
assessing the probability of future events. Fig. 4 illustrates
the probability of the occurrence of at least one air
accident per period t. This probability rises over time
until the event. For example, the probability of at least
one accident by the following day from now is about 0.02,
by next month 0.45, by six months 0.97, and by next year
0.999.
5.3. Assessment of deaths and injuries
To complete the analysis of past accidents, the distributions
of air accidents, fatalities and survivors per aircraft
category can be separated. Aircraft can be treated as
turbojets, turbo-props and piston-engine; see Table 2.
The largest number of accidents involved turbo-prop
aircraft but the greatest number of people involved in
The accidents involved aircraft types, Boeing B727, B737, B747,
B757, B767, B777 (no event); MD80, DC10, MD11; Lockheed L1011,
Airbus A300, A310, A320, A330 (no events), A340 (no events); Fokker
F28, F100; British Aerospace BAe 146; Embraer EMB-110 Bandeirante,
EMB-120 Brasilia; Dorrnier 228; and Saab 340.

M. Janic / Journal of Air Transport Management 6 (2000) 43}50 49
Fig. 3. Distribution of time intervals between consecutive air accidents (1965}1998).
Source of data: Internet (1998).
accident (although some survivors have been severely
injured).
6. Conclusions
Fig. 4. Dependence of the probability of the occurrence of at least one
air accident within time period t (according to the distribuion shown in
Fig. 3).
accident were on turbojet aircraft because the latter can
carry more passengers.
Regarding the number of deaths per accident
(1965}1998), there were 130 events involving no survivors
implying an overall probability of death during an air
accident of about 50%. In the absolute numbers, the
analysis shows that the average number of deaths per
accident has been N
"76 (σ
"81) and the total number
of people onboard on the aircraft when the accident
happened is N
"103 (σ
"88). By further elaborating
the above "gures, it can be seen that about 73% of
passengers and crews have been killed during the aircraft
This paper has presented a methodology for assessment
risk and safety in civil aviation. The outcomes
con"rm that the accident and fatality rates have decreased
in line with increases in the volume of the sector's
output. The accident rate has been more frequent at more
heavily used and older aircraft which supports ideas of
permanent monitoring, detecting and remedying such
things as metal fatigues.
Air accidents belong to a class of extremely rare events
in the context of the volume and intensity of the operations
and activities involved. Some of the most recent
evidences indicates that despite positive past trends, it
seems that it will be di$cult to continue to reduce risks.
The implications of this is an absolute increase in the
number of fatalities and accidents. ICAO's long-tra$c
forecasts indicate that if the rate of accidents stays stable
until 2003, the number of fatalities will increase by about
75% with the number of fatal accidents rising to 40/yr,
respectively (Corrie, 1994). This poses a range of problems
for policy makers. High numbers of accidents will
inevitably attract considerable media attention but aviation
is the safest mode of transport. Transferring resources
to continually reduce the average risk of an
accident or fatality from other, much more dangerous
modes of transport or from other sectors, such as health

50 M. Janic / Journal of Air Transport Management 6 (2000) 43}50
Table 2
Characteristics of fatal accidents by aircraft category
Aircraft category
Fatal accidents per
type of aircraft (%)
Killed people
per aircraft (%)
Survived people
per aircraft (%)
Number of people
died per aircraft
Number of survived
people per aircraft
Turbojet 34.2 69.6 86.5 56 41
Turbo-prop 48.5 28.1 11.4 16 4
Piston-engine 17.3 3.3 2.1 5 2
Source: International Civil Aviation Organization (1992); Internet (1998).
care or support of the elderly, will inevitably cause even
more deaths in society as a whole.
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