Kristiansen Svein. Maritime Transportation: Safety Management and Risk Analysis
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From the observations and comments made in this section of the chapter, it should
now be clear that it is necessary to evaluate and study the underlying data basis of
any statistic before one draws any conclusions both on its results and on accident type
distribution.
2.5.2 Tre nd i n Loss Frequ ency
Over the last decades considerable resources have been spent on reducing the risks
involved in shipping. However, the effects of this work are difficult to assess, mainly
because isolating the effects of each risk-reducing measur e implemented is almost hopeless,
given the co mplexity of cause and effect relations in shippin g.
Lancaster (1996) studied the long-term trend of the total loss frequency, and
concluded that the annual loss rate had been reduced by a factor of 10 in the twentieth
century, from more than 3% in 1900 down to 0.3% in 1990. However, as illustrated
by Figure 2.6, the rate of improvement was greatest in the first half of the century,
after which the improvement rate levelled out as the potential for further improve-
ments became less and the relative improvements achieved by each safety measure
became smaller.
Figure 2.7 gives a more detailed account of how the loss ratio has been reduced for
different accident types. The upper line indicates the total loss rate, including all the
different accident types. As can be seen, the total loss ratio had setbacks around 1968 and
1980. A further analysis of Figure 2.7 shows that the main contribution to the long-term
reduction in loss rate comes from the grounding/stranding category where the loss ratio
has shown dramatic improvement.
Figure 2.5. Distribution (in per cent) of losses and serious accidents for the Norwegian merchant fleet,
19 9 8 ^9 9. (S o urce: Official Statistics of Norway: Maritime Statistics 1 998 ^99.)
26 CH A PTER 2 MARITIME RIS K PICTU R E
Figure 2.8 gives a serious accident rate dist ribution for different ship types. From this
distribution the following observations can be made:
. Ro-Ro (Roll-on Roll-off) cargo vessels are the most accident-prone of all vessel types.
This has been explained by operation in congested coastal waters, relatively high-speed
operation and weak hull subdivision against flooding.
. Tankers and liquefied gas ships are less vulnerable than general cargo.
. Non Ro-Ro passenger vessels have the best accident rate performance among trading
vessels.
Figure 2.6. Annual percentage of ships lost worldwide.
Figure 2.7. World loss ratio time series for ships above 100 GT. The loss ratio is given by annual losses
per ships at risk.
2.5 QUANTITATIVE RISK PICTURE 27
Even in Figure 2.8 there are possible sources for misinterpretation. The low accident
rate of fishing vessels should be questioned on the basis of our knowledge about this vessel
category, i.e. operation in coastal waters, critical hatches, often subjected to harsh weather
conditions, etc. However, an important characteristic of fishing vessels is that the majority
of these vessels have considerable inactive periods, whereas trading vessels normally only
have a few days off-hire per year. The ratio of accidents to the number of vessels at risk is
therefore somewhat misleading. A better measure of exposure might have been the number
of accidents per hour of operation (fishing or sailing).
2.6 FATALITY RISK
Only about 5% of all fatalities happen because of accidents. The relatively large public
focus on accidents reflects soc iety’s considerable awareness of these fatalities (Ka
˚
rstad
and Wulff, 1983). However, in order to better understand how people relate to the risk of
fatality, this observation must be studied in more detail.
Accidents may be analysed on the basis of personal characteristics. There is,
for instance, a significant correlation between age and the risk of fatality through
accidents. For people aged between 5 and 40, accidents constitute the single most
important death threat, while they constitute only 5% of the fatalities of people 60 years
and above.
There are several alternative ways of measuring accident frequency. One approach is to
include all accidents, irrespecti ve of the types of consequences involved. Another approach
is to consider only a specific consequence such as fatalities or material and economic
losses. Accident frequency varies between different activities, and as shown in Table 2.5,
shipping appears to be relatively risky compared to other industrial activities and sectors.
Also other maritime activities, such as offshore work (i.e. continental shelf in Table 2.5)
and fishing have high fatality rates.
Figur e 2.8. Loss and serious accident rate for the world fleet by ship type, 1980 ^ 89. (Source: Lloyd’s
Register of Shipping (1962^93), (1994 ^98).)
28 CHA PTER 2 MA R ITIME RIS K PICTURE
A comparison of different modes of transport is given in Table 2.6 above, and from
these statistics it is clear that there are much more dangerous forms of transport than
waterborne. There is, for example, less focus on the use of motorcycles than the statistica l
values should indicate. This can be explained by the fact that the use of a motorcycle is
a kind of personal choice, and that the consequence normally is limited to one or two
fatalities.
The risk level in the maritime sector is a result of a number of factors relating to
the environmental conditions maritime activities are subjected to and the way the work
processes are organised. The main factors or hazards were summaris ed in Table 2.1 earlier
in the chapter.
Fatality risks in shipping vary considerably between the different accident types.
Figure 2.9 shows the relative distribution of fatality risks on the basis of the number of
fatalities, the number of accident cases resulting in fatalities, and the total tonnage
involved. As can be seen in this diagra m, the accident types leading to the highest number
of fatalities are collisions and foundering. This is in accordance with similar observations
made earlier in this chapter. Although there are many groundings, these accidents tend to
give relatively few fatalities.
Ta b l e 2 . 5 . Fatality frequency in various activities
Industrial activity Fatalities per 1000
worker-years
Mining 0.9–1.4
Construction 0.3
Industry 0.15
Shipping 1.9–2.1
Continental shelf 2.3
Fishing 1.5
Table 2.6. Transportation risk
Mode of travel Fatalities per 10
8
passenger-km
Fatalities per 10
8
passenger hours (FAR)
Motorcycle 9.7 300
Pedal cycle 4.3 60
Foot 5.3 20
Car 0.4 15
Van 0.2 6.6
Bus/coach 0.04 0.1
Rail 0.1 4.8
Water 0.6 12
Air 0.03 15
2.6 FATALIT Y RISK 29
2.6.1 Work Accidents
Fatalities and injuries in shipping are not just related to vessel accidents such as
groundings and collisions, they are also related to the work process es on board the vessels.
The deck, cargo area, engine roo m and galley are all seen as dangerous workplaces on a
ship. Figure 2.10 gives a breakdown of work-related accident categories/types, and their
corresponding number of occurrences, in the Norwegian fleet. It appears that the accident
categories of ‘stepping on, knocking into, crushed by’ and ‘injuries by/from tools’ are the
dominating work-related accidents.
2.7 POLLUTION
In recen t times there has been an increasing focus on the environmental aspects of
maritime activities. Ships are pollut ing both the marine environment and the atmosphere,
and although there is general agreement about these negative effects of maritime
transport, there is considerable uncertainty about the magnitude of the problem. One
of the first estimates on this was done in 1985 (see Table 2.7), and this study indicated
Figur e 2.9. Risk parameters for vessel accident types.
Figure 2.10. Work-related accidents in the Norwegian fleet by category,1994.
30 CHA PTER 2 MA R ITIME RIS K PICTURE
that the share of hydrocarbon ocean pollution that could be related to maritime
transportation was approximately 45%. The main problem was the spill of oil related to
cargo operations and tank cleaning. Massive efforts during the last decade have, however,
reduced these sources of oil pollution, as is illustrated above by Table 2.8. It is presently
assumed that accidental spills are the major problem. It should, however, be kept in mind
that statistics on accidental spills can be somewhat misleading due to the fact that the
annual volume of spills varies considerably.
2.8 THE RISKCONCEPT
Risk in the conte xt of engineering is normally presented as the product of the
consequences and the probability of occurrence. Quite often, however, the consequences
are hard to quantify and may involve some degree of subjectivity. For this reason it is
Ta b l e 2 . 7. Total input of hydrocarbons into the marine environment in1985
Source of pollution Best estimate
(million tons annually)
Natural sources 0.25
Offshore production 0.05
Maritime transportation: 1.50
Tanker operation 0.70
Tanker accidents 0.40
Other 0.40
Atmospheric pollution carried to the sea 0.30
Municipal and industrial wastes and runoff 1.18
Total 3.28
Source: National Research Council, US.
Ta b l e 2 . 8 . Est i mated world marit im e sour ces of oil ent eri ng the marine en vi ron ment
Source 1990
(1)
1981–85
(2)
1973–75
(2)
Bilge and fuel oil 0.25 0.31
Tanker operational losses 0.16 0.71 1.08
Accidental spillage:
Tanker accidents 0.11 0.41 0.20
Non-tanker accidents 0.01 – 0.10
Marine terminal operations 0.03 0.04 0.50
Dry-docking 0.03 0.25
Scrapping of ships 0.01
Total 0.57 1.50 2.13
Sources: (1) US Coast Guard; (2) National Research Council, US.
2.8 THE RISKCONCEPT 31
quite common to present the risk as a probability measure for the various categories of
consequences. The categories for personnel risk may be grouped a ccording to Figure 2.11.
The abbreviations in Figure 2.11 will be explained in detail below.
Similar approaches may be used for environmental risk and risk associated with
damage to assets. There are numerous alternative measures for each consequence, and
some examples are presented in Table 2.9.
One should be aware of the fact that the various actors involved in the safety work may
apply statistical measures differently. For example, safety managers normal ly consider the
experienced level of safety, while risk analysts are mainl y concerned with the estimated/
predicted level of risks/safety.
As the total risk picture for a given activity or system can be very complex and involve
many different aspects, it is often necessary to break it down into risk scenarios.
Equation (2.1) below computes the total risk for a given activity/system as the sum of the
risks for each accident type and each phase of the accidental process:
R ¼
X
i
X
j
p
ij
c
ij
ð2:1Þ
where:
R ¼ Total risk
i ¼ The number of scenarios that may lead to a particular consequence (e.g.
Table 2.2)
j ¼ Number of phases within each accidental outcome (e.g. initiating event,
mitigation, escape, evacuation and rescue)
c
ij
¼ Conseq uence measure for the relevant scenario and phase of the accidental
process, e.g. n fatalities, m tons of spill, etc.
p
ij
¼ Probability (or frequency) of the relevant consequence c
ij
for a given scenario
and accidental phase
Figure 2.11. Personnel risk.
32 CH A PTER 2 MARITIME RIS K PICTU R E
Ta b l e 2 . 9 . Risk criteria
Type Definition
Occupational
accidents
LTI-rate Lost-Time Injury frequency rate Number of lost-time injuries per 10
6
employee hours
AIR Average Individual Risk Number of fatalities per exposed individual
IIR Injury Incident Rate (Number of reportable injuries in a financial year)/(Average number
employed during the year) 10
5
IFR Injury Frequency Rate (Number of injuries in the period)/(Total hours worked during the
period) 10
5
S-rate Severity rate Number of working days lost due to lost-time injuries per 10
6
employee-hours. Fatalities and 100% permanent disability account
for 7500 days working days lost
TRI-rate Total Recorded Injury rate Total number of recordable injuries (including lost-time injuries,
medical treatment injuries and injuries resulting in transfer to
another job or restricted work) per 10
6
employee-hours
Average number of days lost S-rate/LTI-rate
FAR Fatal Accident rate Number of fatalities per 10
8
working hours
Fatality rate Fatalities per 1000 worker-years
PLL Potential Loss of Life Number of fatalities experienced (or predicted) within a given period
of time, e.g. the number of lives lost per year in shipping
Work-related WRD-rate Work-Related Diseases rate Number of new cases of possible work-related diseases resulting in
absence from work per 10
6
employee hours
Sick leave percentage Number of sick-leave days as percent of total number of possible
workdays
Pollution Rate of emissions Emissions due to accident in kg/m
3
per ton production, e.g. the
emissions of fluor in kg per ton produced primary aluminium
Material losses Loss rate Number of accidents or losses per produced unit, e.g. collisions per
10
5
nautical miles sailed
Loss ratio Number of ships (or tonnage) totally lost per number of ships (or
tonnage) at risk, e.g. merchant vessel lost world-wide per total
number of merchant vessel
Relative loss ratio The loss ratio for an activity divided by the world-wide loss ratio. A
loss ratio of one (1) corresponds to the world average, and a higher
loss ratio indicates higher losses than the world average
2.8 THE RISKCONCEPT 33
2.8.1 Fatality Risk
Table 2.9 defined a number of fatality risk measures that may be used. The Potential
Loss of Life (PLL) measure is a basic measure that may be calculated according to
Eq. (2.1). However, this risk criterion has the shortcoming of not incorporating any
exposure measure. As outlined in Figure 2.11, it is also necessary to make a clear
distinction between individual risk and group risk.
The most commonly used risk measures for individual fatality risk are the Average
Individual Risk (AIR) and Fatal Accid ent Rate (FAR). The AIR measure is calculated by
dividing the PLL by the number of people exposed, e.g. the crew size on a merchant ship.
In some accident cases only the number of crew on duty are considered. The FAR value
is calculated by dividing the PLL by the total man-hours of exposure, and multiplying
this measure by a compulsory 10
8
scaling value. The FAR is therefore the expecte d
(or experienced) number of fatalities per 10
8
working hours.
Exam p le
Problem
Accidents involving passenger ferries may result in a large number of fatalities, and
hence attract considerable media attention. On the other hand, experts often consider
the objective risk of such large-scale accidents as relatively low. From an analysis of the
safety level of ferries in the UK since 1950 (Spo uge, 1989), it was found that 3 large-
scale ferry accidents resulted in an average of 107 fatalities per accident (i.e. 41% of
the passengers aboard). Over the period of time studied in the analysis, this gives an
average number of about 9 fatalities per year. This average number is, however, not
representative for the real distribution of a high number of fatalities on a few number
of cases.
In the period of time studied, the UK ferry traffic involved an average of
approximately 28 million journeys per year (domestic and international), one return
journey per passenger per year, and a typical journey duration was estimated to be 3 .5
hours. Given this information, find the Average Individual Risk (AIR) and the Fatal
Accident Rate (FAR) for UK ferries.
Solution
Assumptions:
The relatively low number of accidents is representative of the risk picture of UK ferries.
Analysis:
The Average Individual Risk (AIR) rate can be calculated as follows:
AIR ¼
9 fatalities=year½2 journeys=person½
28 10
6
journeys=year½
6:4 10
7
fatalities=person½
34 CH A PTER 2 MARITIME RIS K PICTU R E
The AIR rate for UK ferries may be put into perspective when compared to other UK
activities:
. Smoking 5.0 10
3
. All natural causes 1.2 10
3
. Work 2.3 10
5
. Driving 1.0 10
4
. Railway 2.0 10
6
. All accidents 3.0 10
4
. Lightning strike 1.0 10
7
This confirms that the average individual risk for UK ferries is not alarming, compared
to other types of transport. However, the AIR value does not include the time of exposure,
and in this context the Fatal Accident Rate (FAR) is valuable. The FAR, which is the
number of fata lities per 10
8
exposed hours, can be calculated as follows:
Exposure time ¼ 28 10
6
journeys
year
3:5 hours½¼9:8 10
6
hours
year
FAR ¼
9 fatalities=year½9:8 10
6
hours=year½
10
8
hours½
8:8 fatalities½
The FAR value of 8.8, i.e. 8.8 fatalities per 10
8
exposed hours, can also be compared to
other UK FAR values for alternative means of transportation:
. Motorcycle 660
. Aeroplan e 240
. Bicycle 96
. Personal car 57
. Railway 5
. Bus 3
The FAR value for UK ferries indicates that ferries are among the safest means of
transportation. However, aeroplanes obtain an unfairly high FAR because of the high
velocity at which they travel. Therefore, when comparing two alternative ways to travel,
the risk per trip is a more reasonable measure than the risk per hour.
In addition to estimating the risk to individuals, attention should also be paid to group
risk. Group risk criteria will be explained below.
Group risk criteria can often describe the inherent risk level for an activity or system in
a more comprehensive, differentiated and understandable way than most individual
risk criteria. The most commonly used technique for presentation of group risk is the
2.8 THE RISKCONCEPT 35