Risk Assessment Data Directory Report No. 434 9 March 2010 Land transport accident statistics I n t e r n a t i o n a l A s s o c i a t i o n o f O i l & G a s P r o d u c e r s
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contents 1.0 Scope and Application... 1 2.0 Summary of Recommended Data... 1 2.1 Road and rail users... 1 2.2 Dangerous Goods Transport... 4 3.0 Guidance on use of data... 5 3.1 General validity... 5 3.2 Uncertainties... 5 3.2.1 Road and Rail User Casualty Frequencies... 5 3.2.2 DG Transport... 5 3.3 Application of frequencies to specific locations... 5 3.3.1 Road and Rail Transport... 6 3.3.2 Dangerous Goods Transport... 6 4.0 Review of data sources... 7 4.1 Basis of data presented... 7 4.1.1 Road Transport... 7 4.1.2 Rail Transport... 8 4.1.3 Dangerous Goods Transport... 10 4.2 Other data sources... 10 4.2.1 Road Transport... 10 4.2.2 Rail Transport... 11 4.2.3 Dangerous Goods Transport... 11 5.0 Recommended data sources for further information... 12 6.0 References... 12 OGP
Abbreviations: ACDS BLEVE DfT DG DNV ECMT E&P ERA EU FEMA FRA GB HGV IRF KSI LGV LPG mm OECD OG&P ORR QRA RSSB UIC UK US(A) (V) km Advisory Committee on Dangerous Substances Boiling Liquid Expanding Vapour Explosion Department for Transport Dangerous Goods Det Norske Veritas European Conference of Ministers of Transport Exploration and Production European Railway Agency European Union Federal Emergency Management Agency Federal Railroad Administration Great Britain Heavy Goods Vehicle International Road Federation Killed or Seriously Injured Light Goods Vehicle Liquefied Petroleum Gas millimetre Organisation for Economic Co-operation and Development Oil and Gas Producers Office of Rail Regulation Quantitative Risk Assessment Rail Safety and Standards Board International Union of Railways United Kingdom United States (of America) (Vehicle) kilometre OGP
1.0 Scope and Application This datasheet provides information on land transport accident statistics for use in Quantitative Risk Assessment (QRA). The datasheet includes guidelines for the use of the recommended data and a review of the sources of the data. Most of the data concern motor vehicles and rail transport, although some data for cyclists are also presented. Data excludes pedestrians; if this is needed local data will need to be examined. The data in this sheet are intended for two main uses: Assessing the risk of transporting personnel; data relating to the frequency of fatalities and serious injuries to road and rail users are presented. Assessing the risks of transporting Dangerous Goods (DG); data on the frequency of releases of hazardous materials from rail and road tankers are presented. In the sections below the following definitions are used: Seriously Injured: Any person not killed, but who sustained an injury as result of an accident, normally needing medical treatment. Killed: Any person killed immediately or dying within 30 days as a result of an accident. Road Injury Accident: Any accident involving at least one road vehicle in motion on a public road or private road to which the public has right of access, resulting in at least one injured or killed person. 2.0 Summary of Recommended Data It is best to try and obtain local data where possible. In the absence of local data the following data can be used. 2.1 Road and rail users The recommended frequencies and associated data are presented as follows: Road user (Table 2.1, Table 2.2, and Table 2.3) Rail user (Table 2.4) OGP 1
Table 2.1 Road Accident Fatality and Injury Rates, Selected Countries, All Vehicles All Rates in deaths or injuries per 10 9 vehicle kilometres Country Year Traffic Volume 10 9 vehicle kilometres Europe Frequency of Accidents Resulting in Injury per 10 9 vehicle kilometres Injury Rate per 10 9 vehicle kilometres Fatality Rate per 10 9 vehicle kilometres Austria 2004 47.8 892.0 1168.0 18.4 Belgium 2004 93.5 520.5 673.7 12.4 Denmark 2005 45.5 118.9 144.7 7.3 Estonia 2005 8.1 288.1 366.6 20.8 Finland 2005 51.6 136.0 174.0 7.3 France 2005 547.6 154.3 197.2 9.7 Latvia 2005 10.2 439.2 550.7 43.5 Lithuania 2005 8.5 796.1 995.4 90.7 Romania 2004 67.9 101.1 82.4 35.6 Slovenia 2005 11.1 928.4 1289.1 23.2 Sweden 2005 73.8 245.3 358.7 6.0 Switzerland 2005 59.9 362.6 446.9 6.8 Turkey 2005 61.1 8732.2 2520.8 74.0 United Kingdom 2005 493.5 402.7 549.2 6.5 Africa Egypt, Arab Rep. 2004 28.7 72.5 264.9 46.0 Ghana 2001 15.3 1022.9 472.5* 81.1 Senegal 2000 4.0 1497.9 1114.6* 161.0 South Africa 2005 123.4 1067.9 1597.5 116.0 America Colombia 2004 15.6 14696.9-351.6 Mexico 2005 91.0 323.9 354.7 51.8 United States 2005 4794.3 386.8 563.0 9.1 Asia/ Middle East Armenia 2005 0.4 2978.4 4027.2 703.7 Bahrain 2002 5.3 308.9 540.0 15.2 China, HK 2005 10.8 1392.8 1763.3 14.0 Israel 2005 41.1 413.5 863.5 10.9 Japan 2004 781.7 1218.1-10.9 Korea, Rep. 2005 314.9 680.1 1086.8 20.2 Kyrgyz Republic 2005 10.2 365.4 449.3 87.8 Mongolia 2002 2.3 2897.3 2148.8* 178.8 Singapore 2005 13.8 486.6 596.8 12.6 Ukraine 2005 14.0 3319.7 3999.1 516.3 Oceania New Zealand 2005 40.6 266.1 355.8 9.9 * These appear to be incorrect values as the injury rate should be higher than the injury accident rate in the previous column. 2 OGP
Road User Table 2.2 Recommended Road Accident Fatality/Injury Rates: Rates by Road Class, Road User Type, Injury Severity All Rates in deaths or injuries per 10 9 vehicle kilometres Urban roads Rural Roads Motorways All Roads Death Seriou s Injury Death Seriou s Injury Death Seriou s Injury Death Seriou s Injury Pedal Cycle 24 490 58 520 - - 32 500 Motor Cycle 65 1220 200 1220 51 300 120 1140 Car 2 28 7 44 2 9 4 31 Bus or Coach 4 110 3 29 4 1 11 4 75 LGV 1 1 6 1 11 1 5 1 8 HGV 1 1 11 2 17 1 7 1 12 All Vehicles 3 51 8 52 2 10 5 44 In some circumstances a QRA may require road user casualty rates in different units which take more account of the specific numbers of passengers being transported. Thus Table 2.3 presents recommended road user casualty rates per billion passenger kilometres. Table 2.3 Recommended Road Accident Fatality/Injury Rates: Rates by Road User Type, Injury Severity All Rates in deaths or injuries per 10 9 passenger kilometres Road User Death KSI* Pedal Cycle 36 684 Motor Cycle 111 1360 Car 2.7 31 Bus or 0.3 11 Coach LGV/ HGV 0.9 11 * KSI = Killed or Seriously Injured The values in Tables 2.2 and 2.3 are based on UK data and considered representative of developed countries with good road safety records. The values from Table 2.1 can be used to generate appropriate modification factors for the rates in Tables 2.2 and 2.3 when applied in different countries. Clearly in any specific situation there will be a number of factors which will influence accident rates such as driver experience, age, etc. No data has been found which could represent these influences explicitly. Table 2.4 Recommended Rail Accident Fatality/Injury Rates All Rates in deaths or injuries per billion passenger kilometres Vehicle Type Death Injury Rail 0.4 15 1 See footnote 3 on page 7 for explanation of data derivation OGP 3
These rail accident data are considered representative of developed countries. In less developed parts of the world the accident rates may be larger, but no data sources have been found to enable them to be quantified. 2.2 Dangerous Goods Transport The data below refers to releases while in transit, not during loading or unloading. Table 2.5 Recommended Rail Tanker Release Frequencies TANKER TYPE TANK SHELL PUNCTURE (per loaded tank wagon km) EQUIPMENT LEAK (per loaded tank wagon hour) Motor spirit 6.3 10-8 - LPG 2.5 10-9 8.3 10-10 Ammonia 2.5 10-9 1.3 10-9 Chlorine 9.0 10-10 3.1 10-9 90% of the punctures are taken to be 50 mm diameter holes, the remaining 10% catastrophic ruptures. The lower chlorine release frequencies are due to higher level of engineering controls, and possibly safer procedural controls related to handling and route management. Data on the causal breakdown of the release frequencies is not available; both internal causes and causes external to the tanker are reflected in the overall frequencies. Table 2.6 Recommended Flammable Liquid Road Tanker Release Frequencies SPILL SIZE 5-15 kg 15-150 kg 150-1500 kg > 1500 kg RELEASE FREQUENCY (per loaded vehicle km) 6.0 10-9 2.6 10-8 7.0 10-9 2.1 10-8 TOTAL 6.0 10-8 Table 2.7 Recommended LPG Road Tanker Release Frequencies (not cylinders) FAILURE CASE BLEVE Cold rupture* Large* liquid space leak Large* vapour space leak RELEASE FREQUENCY (per loaded vehicle km) 2.7 10-12 2.6 10-9 1.8 10-8 2.1 10-9 * Rupture modelled as instantaneous release and large leak modelled as 50 mm diameter hole 4 OGP
3.0 Guidance on use of data 3.1 General validity If transport risk is a relatively small contribution to an overall risk study, the data above may be sufficient. However, if transport risk is the object of the study, local data become very important. As discussed below in Section 3.3, it is strongly recommended that local data sources on accidents and transport risk are obtained. This is because there can be large local variations. In recommending the data in Tables 2.5 to 2.7 on DG transport, there is an implicit assumption that tanker equipment is built to recognised international standards and operated in line with relevant national DG regulations. 3.2 Uncertainties 3.2.1 Road and Rail User Casualty Frequencies Due to the relatively large number of road traffic casualties (see Table 4.1 below), the statistical uncertainties associated with the values in Table 2.2 and Table 2.3 are small compared to the variations between countries. In contrast, national statistics for rail passenger fatalities are generally very low. However, low frequency but high consequence events can have a very large effect on average passenger risk levels. Thus it is important to consider data over a reasonably long time period. The data from Table 2.4 are based on British data 1996-2005 which includes a number of major rail accidents; thus it is considered to be representative with respect to such events. Uncertainties for road and rail user casualty rates will be dominated by local variations. Even within geographically close countries, such as within the EU, variations can be large (see Section 4.0). A further source of transport uncertainty arises from use of frequency units (e.g. per vehicle km or per passenger km). The relative risk of various transport modes can be highly dependent on the frequency units adopted. Thus, it is recommended that any conclusions are tested for their sensitivity to units (see Table 2.2 and Table 2.3). 3.2.2 DG Transport The frequency of releases of hazardous material during transport is much lower than the frequency of road traffic accidents. Hence the statistical uncertainty will be larger, similar to typical major hazard QRA uncertainties. In addition, these frequencies will be influenced by local variations in road and rail accident rates. Thus, local data should be obtained wherever practicable. 3.3 Application of frequencies to specific locations This datasheet contains global data plus more detailed national data. When using these data, it should be realised that they may not be directly applicable to the specific location under study. It is therefore strongly recommended that local data sources on accidents and transport risk from governmental or other national or regional institutions are obtained before using the data given in this sheet. Should these local data not be accessible, or their reliability/applicability be uncertain, then the data in this data sheet could be used after factoring for local circumstances. OGP 5
However, data which have been adjusted to allow for local circumstances should always be used with caution. 3.3.1 Road and Rail Transport In assessing the risks of personnel transport the following steps are recommended: 1. Obtain local data if practicable. 2. If not, use the data in Tables 2.1 to 2.4. For road risks the casualty frequencies can be adjusted for location using the factors suggested in Section 2.0 and presented in more detail in Section 4.0 below. Some location specific data for rail are also presented in Section 4.0, but it is unclear if the variations are real or are a feature of definitions and reporting criteria. 3. Analyse the proposed personnel journey patterns in terms of vehicle types, road types, vehicle kilometres and/ or passenger kilometres (for rail only passenger kilometres are required). 4. Multiply the frequencies from steps 1 or 2 with the journey pattern data in step 3 to obtain overall personnel transport risks. Conduct sensitivity tests using the different units in Table 2.2 and Table 2.3 (if relevant) and alternative data sources discussed in section 4.0 2. Example: estimate the fatality rate per year for an operation involving 30 personnel being transported 4 times a month by bus/ coach along 300km of motorway grade road in North Africa. Assuming local data specific to this type of operation are not available steps 2 to 4 are illustrated below. From Table 2.2 for bus/coach the fatality rate is 4 10-9 per vehicle-km. This is based on UK data. From Table 2.1 the overall fatality rates in Egypt are 7.1 times greater than UK. This is taken as an appropriate multiplication factor. Thus the fatality rate is 28.4 10-9 per vehicle-km. Based on the example information above the number of vehicle-kms per year is 300 4 12 = 14,400. Thus the annual predicted fatality rate would be 28.4 10-9 14,400 = 4.1 10-4. Using the data from Table 2.3 which gives a fatality rate per passenger-km gives a fatality rate per year of 9.2 10-4. 3.3.2 Dangerous Goods Transport In assessing the DG transport release frequencies the following steps are recommended: 1. Obtain local data if practicable. 2. If not, use the data in Tables 2.5 to 2.7 and adjust the release frequencies for location using fault tree analysis, expert judgements (e.g. based on relative transport accident rates), or other appropriate methods. 3. Analyse the proposed DG transport patterns in terms of transport mode (rail/ road), wagon/ vehicle kilometres, loaded tanker hours, etc. 2 While there is uncertainty concerning the location variations in the rail data, as noted above, the location specific data may be used in sensitivity testing. 6 OGP
4. Multiply the frequencies from steps 1 or 2 with the DG transport data in step 3 to obtain overall release frequencies. Example: Estimate the frequency per year of large vapour space leaks in an LPG operation that involves 5 tankers operating each 7 times a week on a 200km route fully loaded. Assuming local data specific to this type of operation are not available steps 2 to 4 are illustrated below. From Table 2.7 the large vapour space leak frequency is 2.1 10-9 per loaded vehicle-km. Assume that expert judgement concludes that this frequency is appropriate. Based on the example information above the number of loaded vehicle-kms per year is 5 7 52 200 = 364,000. Thus the estimated annual leak frequency is 2.1 10-9 364,000 = 7.6 10-4. 4.0 Review of data sources 4.1 Basis of data presented 4.1.1 Road Transport Table 2.1 is based on the International Road Federation s (IRF) 2007 report [10]. For all countries except Turkey, the most recent year s data presented in this report is taken as representative and presented in Table 2.1 (2005 data for Turkey appears to have an error in the injury rate). This report also provides accident rates per 100,000 head of population for a wider range of countries. The data in this table can be compared for trends to the data in the previous Technical Note for E&P Forum which used the IRF s 1994 report [3]. Table 2.2 and Table 2.3 are based on British data from the Department for Transport s 2006 report [1] 3. Table 4.1 shows the number of fatalities per vehicle type for 2006 on which the casualty rates are based. Table 4.1 GB Numbers of Fatalities 2006: Numbers by Road User Type & Severity Road User Death KSI* Pedal Cycle 153 2568 Motor Cycle 634 6992 Car 2580 26713 Bus or Coach 122 1260 LGV 280 2322 HGV 419 2119 All vehicles 3172 31845 * KSI = Killed or Seriously Injured [1] also provides a much greater range of data including trends over time, accident rates as a function of age, gender, alcohol levels etc. One of the E&P Forum (as was) member companies collected statistical data in the 1990s from which accident rates for desert driving conditions can be calculated. This 3 In Table 2.1 in 2006 there were no fatalities on urban roads for LGVs and HGVs and no fatalities on motorways for bus/ coach. For these cells of the table, the recommended fatality rates have been set to the All Roads value. In Table 2.2 the rates are based on 1996-2005 data; as no separate value for HGV is given in Ref. [1] it has been set at the LGV value. OGP 7
data covers a period between 1992 and 1994. The derived desert driving accident and fatality rates are shown in Table 4.2 below and relate to company and contractor work related accidents. Table 4.2 Desert Driving Accident and Fatality Rates Year 1992 Road Traffic (108 V km) 0.79 Road Traffic Accidents 137 Injuries Fatalities Fatality Rate (per 108 V km) 56 4 5.1 1993 0.89 135 42 2 2.3 1994 0.86 111 26 0 0.0 The downward trend in the fatality rate was considered to be the result of improved induction training, the fitting of roll-over bars and speed governors to all LGVs and the near 100% usage of seat-belts. This needs to be taken into account when applying the rates for desert driving at other locations. Deriving an average over the 3 years of 2.4 fatalities per 10 8 vehicle kilometres, this is approximately 5 times higher than the average all-vehicle GB fatality rate. 4.1.2 Rail Transport Table 2.4 is based on British data from 1996 to 2005 [1]. In analysing rail casualty data, care needs to be taken to distinguish casualties caused in train incidents, non-train incidents and vandalism/ suicide. Overall fatality numbers are dominated by the latter category. In addition, statistics may include passengers, staff and others (third parties who were neither passengers nor staff, but who were killed or injured due to rail related activity). Also there is the need to allow for low frequency but high consequence events which are characteristic of rail operations. A national railway may experience several years of very few fatalities and then have one event which kills many tens of people. It is often difficult to determine what has been included in summary statistics. Table 2.4 above is a subset of DfT data comparing various transport modes. It is averaged over 10 years and therefore takes account of low frequency/ high consequence events (e.g. Ladbroke Grove, where there were 31 fatalities). The casualty rates relate just to train passengers, but from all accident causes not only train accidents such as collisions, derailments, fires etc. Further details of UK rail accident rates are provided in the UK Office of Rail Regulation Annual reports [4]. These split out incidents involving passengers, staff and members of the public, and provide train incident rates, as well as other accident categories such as trespass and vandalism. The GB data is considered representative of average EU data. Figure 4.1 below is taken from the RSSB strategic plan [5] and compares UK passenger fatality rates against the 25 EU countries averages. The UK values are shown to be consistent with the EU values except in years when there are major UK disasters. If the major disasters were to be averaged over a few years, there would be an even closer match. In recent years the European Railway Agency has begun to collect statistics from all the European countries. The 2004-2005 Rail Statistics are summarised in Figure 4.2 below [6]. These data would appear to indicate significant differences between EU countries. However, there is a need to be cautious. The variation could be because of inconsistent reporting criteria or it could reflect low frequency/ high consequence events affecting a 8 OGP
few countries in the time period 2004-2005. Given this uncertainty no potential modification factors are suggested in this datasheet. Figure 4.1 Comparison between GB and EU Average Rail Fatality Rate [5] Figure 4.2 EU States Rail Fatality Rate [6] OGP 9
US data from the Federal Railroad Administration [7] for 2006 indicates 2 passenger fatalities in 16,211,393,401 passenger miles = 0.08 fatalities per billion passenger km. This is also consistent with UK data for 2004-2005. 4.1.3 Dangerous Goods Transport Tables 2.5 to 2.7 present a selection of available data suitable for use only where transport risks form a small contribution to a process QRA. They should not be used for transport QRA without detailed consideration of the applicability of the data. In particular local variations in transport accident rates should be analysed. 4.1.3.1 Rail Tankers The Advisory Committee on Dangerous Substances (ACDS) of the UK Health & Safety Commission produced a report in 1991 [8] which provides a detailed QRA of road and rail transport of motor spirit, LPG, ammonia and chlorine in Great Britain, including puncture frequencies based on modified UK experience and equipment leak frequencies based on fault tree analysis. [8] estimated frequencies of tank shell punctures and equipment leaks from tank wagons carrying dangerous goods, based on modified UK data (Table 2.5). The punctures are taken to be 50 mm diameter holes (90%) or catastrophic ruptures (10%). 4.1.3.2 Liquid Tankers The best available estimate of leak frequencies from tankers carrying non-pressurised liquids is also given by [8], based on spills from UK motor spirit tankers (Table 2.6). 4.1.3.3 LPG Road Tanker Leak Frequencies A DNV Technica report [9] compared various sources of leak frequency data for LPG road tankers, and developed a fault tree model to take account of the main influences. Table 2.7 gives the failure case frequencies for a tanker with passive fire protection, based on Hong Kong road traffic accident rates. 4.2 Other data sources 4.2.1 Road Transport The International Road Federation in Geneva collects world road statistics including data on road accidents from a large number of countries [10]. The data include the annual number of accidents, annual number of injured and killed people as well as the number of injury accidents, persons injured or killed per 100 million vehicle kilometres (10 8 V km). The Organisation for Economic Co-operation and Development (OECD) maintains road safety statistics [2]. It presents international fatality information for different road types. The OECD website [2] also presents injury rates and fatalities per 100,000 of the population. The European Conference of Ministers of Transport [11] gives death rates and casualty rates per capita and per vehicle for European countries and Australia, Canada, Japan, Russia and USA. However, it does not have any estimates of vehicle-km. Davies & Lees [12] give a variety of accident statistics for heavy goods vehicles, drawn mainly from national accident statistics. 10 OGP
Koornstra [24] presents a passenger transport model which includes road transport risk. Reference risks are first determined based on data from the original 15 EU countries. Multiplication factors are then developed relating road fatality risks to the Gross National Income per person (GNI/p) and plotted on a graph with a fitted function. Corrections are made for estimated underreporting. The report notes a rather wide scatter of fatality rates for individual countries about the curve. For certain countries there is a difference between the predicted and reliably established risks (where country specific data exists). Thus the report proposes an additional multiplication factor where there are strong indications that a country is relatively less safe or relatively safer than other countries with a comparable GNI/p level. Finally a multiplication factor for road type proportions is proposed based on the variation in risk that is seen on different road types. In principle this method can estimate road transport risks for any country in the world and could be useful when country specific data is not available. The reference risks are consistent with those presented in this report. 4.2.2 Rail Transport A Statistical Analysis of Fatal Collisions and Derailments of Passenger Trains on British Railways [13] provides a detailed analysis of the comparative safety of different designs of passenger carriage on British Railways, including accidents per passenger mile and fatalities per accident. Frequency of Railway Accidents in the German Federal Railways Network: Goods Traffic and Shunting Operations [14] provides a detailed analysis of accident frequencies and involvement probabilities for wagons in goods trains in Germany. Light Rail Accidents in Europe and North America [15] has a detailed comparison of accident frequencies on light rail systems in different countries. The report by Koornstra [24] also includes rail transport risk. Reference risks are determined based on data from the original 15 EU countries. Multiplication factors are again developed relating rail fatality risks to the Gross National Income per person (GNI/p). However there is less country data than for road fatalities on which to base these multiplication factors. Thus, as with road, the report proposes using an additional multiplication factor where there are strong indications that a country is relatively less safe or relatively safer than other countries with a comparable GNI/p level. Further international information on rail transport safety is available from International Union of Railways (UIC) at http://www.uic.asso.fr/. 4.2.3 Dangerous Goods Transport There are a large number of other data sources with information relevant to DG transport, but generally they are older or less generally applicable than the values given in Section 2.0. The Federal Emergency Management Agency (FEMA) [16] provides information for explosive, flammable and otherwise dangerous chemicals. It presents failure rates which originate from several sources. The age of the background data and the individual sources may no longer reflect the reliability of transport vehicles on the roads and railways today because of stricter safety regulations for both vehicles and materials transportation. The individual sources contain information about accident rates for trucks used in the petroleum industry and for transporting bulk hazardous materials ([17] to [23]). OGP 11
5.0 Recommended data sources for further information For further information, the data sources used to develop the release frequencies presented in Section 2.0 and discussed in Sections 3.0 and 4.0 should be consulted. The references used for the recommended data in Section 2.0 are shown in bold in Section 6.0. 6.0 References [1] Department for Transport 2006. Road Casualties Great Britain 2006 http://www.dft.gov.uk/162259/162469/221412/221549/227755/rcgb2006v1.pdf [2] OECD, International Traffic Safety Data and Analysis Group http://cemt.org/irtad/irtadpublic/we2.html [3] International Road Federation (IRF) 1994. World Road Statistics 1980-1993 [4] Office of Rail Regulation (ORR) 2006. Annual Report on Railway Safety 2005. http://www.rail-reg.gov.uk/upload/pdf/296.pdf [5] UK Rail Safety and Standards Board (RSSB) 2007. The Railway Strategic Safety Plan 2008-2010. [6] European Railway Agency (ERA) 2006. A Summary of 2004-2005 EU Statistics on Railway Safety. http://www.era.europa.eu/public/documents/safety/safety_performance/07-05%20era-report2.pdf [7] US Federal Railroad Administration website: http://safetydata.fra.dot.gov/officeofsafety/ [8] ACDS 1991. Major Hazard Aspects of the Transport of Dangerous Substances, Advisory Committee on Dangerous Substances, Health & Safety Commission, HMSO. [9] DNV Technica 1996. Quantitative Risk Assessment of the Transport of LPG and Naphtha in Hong Kong - Methodology Report, Report for Electrical & Mechanical Services Department, Hong Kong Government, Project C6124. [10] International Road Federation 2007. The IRF World Road Statistics 2007, Data 2000-2005. [11] ECMT 1998. Statistical Report on Road Accidents 1993/1994, European Conference of Ministers of Transport, OECD, Paris. [12] Davies, P.A. & Lees, F.P. 1992. The Assessment of Major Hazards: The Road Transport Environment for Conveyance of Hazardous Materials in Great Britain, J. Haz. Mat., 32, 41-79. [13] Evans, A.W. 1997. A Statistical Analysis of Fatal Collisions and Derailments of Passenger Trains on British Railways: 1967-1996, Proc. Inst. Mech. Eng., 211 Part F. [14] Fett, H-J & Lange, F 1992. Frequency of Railway Accidents in the German Federal Railways. [15] Walmsley, D.A. 1992. Light Rail Accidents in Europe and North America, Research Report 335, Transport & Road Research Laboratory, Crowthorne, UK [16] Federal Emergency Management Agency. Handbook of Chemical Hazard Analysis Procedures, available from Federal Emergency Management Agency, Publications Office, 500 C Street, SW, Washington, DC 20472 [17] American Petroleum Institute 1983. Summary of Motor Vehicle Accidents in the Petroleum Industry for 1982. [18] Dennis, A.W. et al. 1978 Severities of Transportation Accidents Involving Large Packages, Sandia Laboratories, NTIS SAND-77-0001. [19] Rhoads, R.E. et al. 1978 An Assessment of the Risk of Transporting Gasoline by Truck, prepared by Pacific Northwest Laboratory for the U.S. Department of Energy, PNL- 2133. 12 OGP
[20] Smith, R.N. and E.L. Wilmot 1982. Truck Accident and Fatality Rates Calculated from California Highway Accident Statistics for 1980 and 1981, prepared by Sandia National Laboratories for the U.S. Department of Energy, SAND-82-7066. [21] National Safety Council. 1988 Accident Facts. [22] Ichniowski T. 1984 New Measures to Bolster Safety in Transportation, Chemical Engineering, pp. 35-39. [23] Urbanek, G.L. and E.J. Barber 1980. Development of Criteria to Designate Routes for Transporting Hazardous Materials, prepared by Peat, Marwick, Mitchell and Co. for the Federal Highway Administration, NTIS PB81-164725. [24] Koornstra, M.J. 2008. A Model for the Determination of the Safest Mode of Passenger Transport between Locations in any Region of the World. Report for Shell International Exploration and Production B.V. OGP 13
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