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An assessment of risk and safety in civil aviation
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: [email protected] (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): f Real risk to an individual, which may be determined on the basis of future circumstances after their full development; f Statistical risk, which may be determined by the available data on the incidents and accidents in question; f Predicted risk, which may be predicted analytically from the models structured from relevant historical studies; and f Perceived risk, which may intuitively be felt and thus perceived by individuals.
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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: f 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. f 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. f Although being a rare event in an absolute sense, aircraft accidents can have severe implications. f 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. f 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: f 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. f Risk evaluation may be decomposed into risk aversion and risk acceptance. f 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 sustainability1 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
1 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 Table 1 Example of air tra$c forecasts! Forecaster
Period
Average annual growth Rate (pkm)1 (%)
Airbus Industry
1992}2001 2002}2011 1993}2013 1993}2012 1990}2000 1994}2013 1992}2003
5.8 5.1 5.2 5.2 6.5 3.5 5.0
Boeing Rolls-Royce AcDonnell Douglas Fokker ICAO
! Source: International Civil Aviation Organisation (1994); Air Transport Action Group (1996).
fatalities was 741/anuum.2 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$cult because they generally stem from a complex system of mutually dependent, sequential factors (Owen, 1998). These factors can be classi"ed in several ways. First, according to the current state-of-knowledge they can be categorized into known and avoidable and unknown and unavoidable causes. The former should be considered conditionally in the sense that immediately after an accident the real causes are seldom fully known but as the investigation progresses they become known and avoidable. The causes of some accidents are never uncovered. Second, with respect to accident type, the main causes of air accidents can conditionally be classi"ed into human errors, mechanical failures, hazardous weather, and sabotages and military operations. f Most accidents can be attributed to human error combined with other factors. Human errors have been present in the production, maintenance and operation of aviation hardware ranging through aircraft, airports and air tra$c control facilities and equipment. Human operational errors can come about when workloads exceed work ability, e.g., in stressful situations. In
2 The data exclude accidents in the former USSR and the events involving unlawful interference with aviation.
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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$c. Long exposition to heavy mental workloads causes stress that can lead to fatigue and deterioration in work performance. Under stressful conditions, diminished performance may cause conscious or unconscious risky and unsafe behavior and generate errors that may result in fatal accidents. The most common types of such accidents are mid-air collisions and aircraft #ying into terrain. f Mid-air collisions have mainly been caused by air tra$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). f 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). f 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
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M. Janic / Journal of Air Transport Management 6 (2000) 43}50
could save the aircraft despite severe icing (Owen, 1998).3 f 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$culties in to checking if they were closed. The result was stronger and better designed doors. The crash of a DC-10 at Chicago in 1979 happened due to engine failure. The event resulted in stricter rules and procedures covering engine maintenance and a review of take-o! speeds (Stewart, 1974). f The root-cause of many disasters originates in maintenance workshops and in the factories where vital components and systems have been produced. An example "re on a British Airtours B737 at Manchester Airport in 1985. Thermal fatigue, or weakening of the metal by constant heating and cooling during an engine's life produced a crack in the combustion during the take-o!. The section separated from the engine and hit the port wing fuel tank spilling of fuel on a hot engine. Subsequently, cracks were found in other engines of this type (Owen, 1998). f Hazardous weather such as thunderstorms and frontal systems can cause troublesome winds, rain, snow, fog, and low ceilings that may pose safety concerns at all stages of a #ight. In particular, strong windshear developing near airports can make #ying di$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
3 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. f 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). f 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.4 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):
where, X is the number of air accidents in time t and j is t 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~jt t
(2)
5. Application of the methodology f 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. f 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. f The probability of an event occurring in a small interval *t is proportional to *t and can be estimated by j*t where j is the mean rate of occurrence of the event. It is assumed constant and equal to j"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. 1 2 3 i N 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~jt, t
(1)
4 Besides national aviation authorities and airlines, ICAO providing the data on safety.
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 R 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 D A 1981}1996 are used for estimation (International Civil Aviation Organization, 1994) in the following speci"cation (Janic, 1999): GF "3.801]10~10#4.196]10~11N R D (2.983) (10.674) !2.095]10~16PKM A, (3.446) (3) R2 "0.901; F"69.296; D="1.617; N"16. !$+ The overall regression is signi"cant at the 1% level with signi"cant coe$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 , R 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.
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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 airA craft type F , and the average age of particular A aircraft type E . The data cover the period from the A 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 A A A (0.692) (6.355) (3.887), R2"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. 3.5 A simple calculation provides an estimate of the average accident rate: j+7.818 accidents per year or j+0.020 accidents per day. An analysis of the time intervals between accidents, independent of aircraft type, indicates they have been independent and exponentially distributed (a s2 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
5 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 (p "81) and the total num$ $ ber of people onboard on the aircraft when the accident happened is N "103 (p "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
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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 Turbo-prop Piston-engine
34.2 48.5 17.3
69.6 28.1 3.3
86.5 11.4 2.1
56 16 5
41 4 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.
References Ang, H-S.A., Tang, H.W., 1975. In: Probability Concepts in Engineering Planning and Design: Vol. I } Basic Principles. Wiley, New York. Air Transport Action Group, 1996. The Economic Bene"ts of Air Transport. ATAG, Geneva. Cole, J., 1997. Overview of aviation safety issues, Paper presented at The Seventh Annual Aviation Forecast Conference. NATCA-National Air Tra$c Controllers Association, Washington. Corrie, S.J., 1994. Potential growth in air travel demands renewed e!ort to improve safety record. International Civil Aviation Organisation, Montreal, Canada, ICAO Journal 7}9. Dose, A., 1995. Safety is best served by paying close attention to the key elements in its management. ICAO Journal 20}21. Evans, A.W., 1996. Risk assessment by transport organisations. Transport Reviews 17, 145}163. International Civil Aviation Organisation, 1992. Investment requirements for aircraft #eets and for airport and route facility infrastructure to the year 2010. Circular 236, ICAO, Montreal.
International Civil Aviation Organisation, 1994. ICAO projects longterm moderate tra$c growth of 5 per cent per year. ICAO Journal 20}21. Internet, 1998. Safety information for airline passengers. http://airsafe.com/airline.htm. Janic, M., 1999. Aviation and externalities: the accomplishments and problems. Transportation Research D 4, 159}180. Johnston, A.C., Johnston, M.B., Buse, R.C., 1989. Econometrics: Basic and Applied. McMillan, New York. Kanafani, A., 1984. The analysis of hazards and the hazards of analysis: re#ections on air tra$c safety management. Institute of Transportation Studies, University of California, Berkeley, Working paper, UCB-ITS-WP-84-1. Kuhlmann, A., 1981. Introduction to Safety Science. Springer, New York. Owen, D., 1998. Air Accident Investigation: How Science Is Making Flying Safer. Patrick Stephens Limited, Yeovil. Rosenberg, B., 1987. Air safety: the state of art. Aviation Week and Space Technology 51}66. Sage, A.P., White, E.B., 1980. Methodologies for risk and hazard assessment: a survey and status report. IEEE Transaction on System, Man, and Cybernetics SMC-10, 425}441. Stewart, S., 1994. Air disasters: dialogue from the black box. The Promotional Reprint Company Limited, Leicester. Walder, R., 1991. Ageing aircraft programme entails major e!ort and expense. ICAO Journal 6}8.
An assessment of risk and safety in civil aviation Milan Janic Centre for Transport Studies, Department of Civil and Building Engineering, Loughborough University, Loughborough, Leics LE11 3TU, UK
Abstract Risk and safety have always been important considerations in civil aviation. This is particularly so under current conditions of continuous growth in air transport demand, frequent scarcity of airport and infrastructure capacity, and thus permanent and increased pressure on the system components. There is also the growing public and operators' awareness of these and other system externalities such as air pollution, noise, land use, water/soil pollution and waste management, and congestion. This paper o!ers an assessment of risk and safety in civil aviation. It deals with general concept of risk and safety, describes the main causes of aircraft accidents and proposes a methodology for quantifying risk and safety. ( 2000 Elsevier Science Ltd. All rights reserved. Keywords: Risk; Safety; Civil aviation; Externalities
1. Introduction Society faces important challenges in how best to manage modern technology. There is a need to e$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: [email protected] (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): f Real risk to an individual, which may be determined on the basis of future circumstances after their full development; f Statistical risk, which may be determined by the available data on the incidents and accidents in question; f Predicted risk, which may be predicted analytically from the models structured from relevant historical studies; and f 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
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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: f 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. f 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. f Although being a rare event in an absolute sense, aircraft accidents can have severe implications. f 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. f 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: f 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. f Risk evaluation may be decomposed into risk aversion and risk acceptance. f 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 sustainability1 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
1 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 Table 1 Example of air tra$c forecasts! Forecaster
Period
Average annual growth Rate (pkm)1 (%)
Airbus Industry
1992}2001 2002}2011 1993}2013 1993}2012 1990}2000 1994}2013 1992}2003
5.8 5.1 5.2 5.2 6.5 3.5 5.0
Boeing Rolls-Royce AcDonnell Douglas Fokker ICAO
! Source: International Civil Aviation Organisation (1994); Air Transport Action Group (1996).
fatalities was 741/anuum.2 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$cult because they generally stem from a complex system of mutually dependent, sequential factors (Owen, 1998). These factors can be classi"ed in several ways. First, according to the current state-of-knowledge they can be categorized into known and avoidable and unknown and unavoidable causes. The former should be considered conditionally in the sense that immediately after an accident the real causes are seldom fully known but as the investigation progresses they become known and avoidable. The causes of some accidents are never uncovered. Second, with respect to accident type, the main causes of air accidents can conditionally be classi"ed into human errors, mechanical failures, hazardous weather, and sabotages and military operations. f Most accidents can be attributed to human error combined with other factors. Human errors have been present in the production, maintenance and operation of aviation hardware ranging through aircraft, airports and air tra$c control facilities and equipment. Human operational errors can come about when workloads exceed work ability, e.g., in stressful situations. In
2 The data exclude accidents in the former USSR and the events involving unlawful interference with aviation.
45
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$c. Long exposition to heavy mental workloads causes stress that can lead to fatigue and deterioration in work performance. Under stressful conditions, diminished performance may cause conscious or unconscious risky and unsafe behavior and generate errors that may result in fatal accidents. The most common types of such accidents are mid-air collisions and aircraft #ying into terrain. f Mid-air collisions have mainly been caused by air tra$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). f 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). f 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
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could save the aircraft despite severe icing (Owen, 1998).3 f 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$culties in to checking if they were closed. The result was stronger and better designed doors. The crash of a DC-10 at Chicago in 1979 happened due to engine failure. The event resulted in stricter rules and procedures covering engine maintenance and a review of take-o! speeds (Stewart, 1974). f The root-cause of many disasters originates in maintenance workshops and in the factories where vital components and systems have been produced. An example "re on a British Airtours B737 at Manchester Airport in 1985. Thermal fatigue, or weakening of the metal by constant heating and cooling during an engine's life produced a crack in the combustion during the take-o!. The section separated from the engine and hit the port wing fuel tank spilling of fuel on a hot engine. Subsequently, cracks were found in other engines of this type (Owen, 1998). f Hazardous weather such as thunderstorms and frontal systems can cause troublesome winds, rain, snow, fog, and low ceilings that may pose safety concerns at all stages of a #ight. In particular, strong windshear developing near airports can make #ying di$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
3 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. f 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). f 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.4 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):
where, X is the number of air accidents in time t and j is t 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~jt t
(2)
5. Application of the methodology f 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. f 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. f The probability of an event occurring in a small interval *t is proportional to *t and can be estimated by j*t where j is the mean rate of occurrence of the event. It is assumed constant and equal to j"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. 1 2 3 i N 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~jt, t
(1)
4 Besides national aviation authorities and airlines, ICAO providing the data on safety.
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 R 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 D A 1981}1996 are used for estimation (International Civil Aviation Organization, 1994) in the following speci"cation (Janic, 1999): GF "3.801]10~10#4.196]10~11N R D (2.983) (10.674) !2.095]10~16PKM A, (3.446) (3) R2 "0.901; F"69.296; D="1.617; N"16. !$+ The overall regression is signi"cant at the 1% level with signi"cant coe$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 , R 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.
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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 airA craft type F , and the average age of particular A aircraft type E . The data cover the period from the A 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 A A A (0.692) (6.355) (3.887), R2"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. 3.5 A simple calculation provides an estimate of the average accident rate: j+7.818 accidents per year or j+0.020 accidents per day. An analysis of the time intervals between accidents, independent of aircraft type, indicates they have been independent and exponentially distributed (a s2 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
5 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 (p "81) and the total num$ $ ber of people onboard on the aircraft when the accident happened is N "103 (p "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
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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 Turbo-prop Piston-engine
34.2 48.5 17.3
69.6 28.1 3.3
86.5 11.4 2.1
56 16 5
41 4 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.
References Ang, H-S.A., Tang, H.W., 1975. In: Probability Concepts in Engineering Planning and Design: Vol. I } Basic Principles. Wiley, New York. Air Transport Action Group, 1996. The Economic Bene"ts of Air Transport. ATAG, Geneva. Cole, J., 1997. Overview of aviation safety issues, Paper presented at The Seventh Annual Aviation Forecast Conference. NATCA-National Air Tra$c Controllers Association, Washington. Corrie, S.J., 1994. Potential growth in air travel demands renewed e!ort to improve safety record. International Civil Aviation Organisation, Montreal, Canada, ICAO Journal 7}9. Dose, A., 1995. Safety is best served by paying close attention to the key elements in its management. ICAO Journal 20}21. Evans, A.W., 1996. Risk assessment by transport organisations. Transport Reviews 17, 145}163. International Civil Aviation Organisation, 1992. Investment requirements for aircraft #eets and for airport and route facility infrastructure to the year 2010. Circular 236, ICAO, Montreal.
International Civil Aviation Organisation, 1994. ICAO projects longterm moderate tra$c growth of 5 per cent per year. ICAO Journal 20}21. Internet, 1998. Safety information for airline passengers. http://airsafe.com/airline.htm. Janic, M., 1999. Aviation and externalities: the accomplishments and problems. Transportation Research D 4, 159}180. Johnston, A.C., Johnston, M.B., Buse, R.C., 1989. Econometrics: Basic and Applied. McMillan, New York. Kanafani, A., 1984. The analysis of hazards and the hazards of analysis: re#ections on air tra$c safety management. Institute of Transportation Studies, University of California, Berkeley, Working paper, UCB-ITS-WP-84-1. Kuhlmann, A., 1981. Introduction to Safety Science. Springer, New York. Owen, D., 1998. Air Accident Investigation: How Science Is Making Flying Safer. Patrick Stephens Limited, Yeovil. Rosenberg, B., 1987. Air safety: the state of art. Aviation Week and Space Technology 51}66. Sage, A.P., White, E.B., 1980. Methodologies for risk and hazard assessment: a survey and status report. IEEE Transaction on System, Man, and Cybernetics SMC-10, 425}441. Stewart, S., 1994. Air disasters: dialogue from the black box. The Promotional Reprint Company Limited, Leicester. Walder, R., 1991. Ageing aircraft programme entails major e!ort and expense. ICAO Journal 6}8.