Article citation information:
Lasota, M.,
Jacyna, M., Szaciłło, L. Fault tree method as a decision-making tool
for assessing the risks of transportation of dangerous loads. Scientific Journal of Silesian
University of Technology. Series Transport. 2024, 123, 133-154. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2024.123.6.
Michał LASOTA[1], Marianna JACYNA[2], Lucyna SZACIŁŁO[3]
FAULT TREE METHOD AS A DECISION-MAKING TOOL FOR ASSESSING THE RISKS OF
TRANSPORTATION OF DANGEROUS LOADS
Summary. Improving
road traffic safety on the one hand and increasing the transport of dangerous
goods on the other requires searching for methods and tools for risk assessment
at various levels of transport of this type of cargo. This is directly related
to the disruption of the safety and efficiency of road transport systems around
transporting dangerous goods. In this respect, risk assessment and its
estimation method are a significant issue. The article analyzes the risk
resulting from the transport of dangerous goods. Threats occurring during the
organization and execution of the transport of dangerous goods were identified
and risk assessment studies were carried out using the FTA method (fault tree
method). The purpose of using the FTA method was to develop and graphically
illustrate a set of factors that cause adverse events in the transport of
dangerous goods. TopEvent FTA computer software was used to verify the proposed
approach, which is used both to construct error trees and to identify and
correct irregularities in existing trees.
Keywords: dangerous
goods, road transport, risk analysis, fault tree, FTA method
1.
INTRODUCTION
Transport,
due to its functions, is an important determinant of the socio-economic
development of every country. One of the significant areas of transport is the
transport of dangerous goods 19.
According to the literature definition, dangerous goods 33, 21
include objects and materials which, due to their physical, chemical or
biological properties, if improperly handled during transport, may cause loss
of health or bodily injury, contamination of the natural environment, damage or
destruction of other material goods and even death12.
The
total volume of road transport of dangerous goods 48
without division into categories in all EU member states in 2022 was almost
67.4 million tkm (tonne-kilometers). Germany continues to be the leader in
international road transport of this type of cargo. In the last decade, Poland
has also significantly increased its share in international road transport of
dangerous goods, from 6.81 million tkm in 2012 to 7.70 million tkm in 2022
(fig. 1.) 17.
Poland currently ranks fourth in terms of the volume of international transport
of dangerous goods 6,
including explosives and gases, infectious substances and other substances that
have not been assigned to a general category. In the case of domestic
transport, 4.84 million tkm of dangerous goods were transported in 2022, which
places Poland in fifth place in the EU. It is worth adding that, according to
available data, 88-90% of dangerous goods in Poland are transported by road,
and only 8-10% by rail.
Fig.
1. List of dangerous goods transport in individual years without division into
categories
Source:
own elaboration based on 17
Recently,
the rapid economic development of countries has been accompanied by constantly
increasing traffic intensity and the demand for the transport of dangerous
goods. The most common way of transporting this type of cargo in Europe is road
transport. Although the number of accidents involving dangerous goods has never
been very high, the consequences of an incident involving vehicles carrying
this type of cargo can be tragic. Considering the safety and efficiency of road
transport systems, it is important to assess the risks arising from this type
of transport 40.
Due
to the significant dependence of road transport on random events and the
actions of third parties, the identification of threats and risk management is
particularly significant – both on the part of carriers, senders,
recipients and administrative units 18. An extremely
important factor influencing the level of risk in the transport of dangerous
goods by road means of transport is the exemplary organization of the transport
process 55.
This is directly related to the coordinated work of qualified staff and good
and unwavering communication between individual entities responsible for
organizing transport. This, in turn, translates directly into the safety of the
project 38.
The
aim of the article is to perform a multi-aspect analysis of the assessment of
threats affecting the risk of accidents in the road transport of dangerous
goods. The article is divided into three main parts. The first one pointed out
the threats arising from the planning and organization of individual stages of
the transport process and made a critical review of the literature, including
the legal and organizational conditions for the transport of dangerous goods.
The second part of the article is a description of the FTA method as a fault
tree method and its main functionalities. It was emphasized that the FTA method
is a logical diagram consisting of a peak event and a structure specifying the
ways of its occurrence. The last part of the article presents a case study. An
assessment of adverse events was carried out on real data, indicating
environmental contamination combined with a threat to human health or life as
the peak event. The analyses carried out were supported by verification using
TopEvent FTA computer software, which enables the construction, analysis, and
correction of error trees.
2.
ORGANIZATION OF THE PROCESS OF TRANSPORTATION OF DANGEROUS LOADS
2.1.
Legislation governing the transportation of dangerous cargoes
In
any debate on the transport of dangerous goods in which the effectiveness of
existing legal controls is questioned, it is crucial to fully understand the
scale of the risks involved and their main causes, so that well-informed
decisions can be made 39.
Due to the need to ensure the safety of people and the environment, we
transport dangerous goods 1
both in the general context and in the case of road transport has been subject
to numerous regulations and restrictions 35, 46.
Legal provisions introduce special rigor in allowing such cargo to be transported
both domestically and internationally, which is preceded by packaging, marking,
selection of means of transport and performance of loading activities. 44, 45.
The
basic legal act regulating the transport of dangerous goods by road is the
European Agreement concerning the international carriage of dangerous goods by
road ADR (fr. Accord européen relatif au transport international des
marchandises dangereuses par route) 16.
Annex
A of this Agreement covers general and specific footnotes relating to dangerous
goods 56,
including definitions, classification rules, conditions of use of packaging and
tanks, including construction and periodic inspection requirements, as well as
shipping procedures and transport conditions. In accordance with Annex A of the
ADR Agreement, the division of dangerous goods is considered according to the
type of dominant hazard and divides the goods into 9 classes, which in turn
correspond to 13 classes in individual branch regulations (tab. 1).
Tab.
1
Division
of dangerous goods into classes
|
Class |
Name |
|
1. |
Explosive materials and articles |
|
2. |
Gases |
|
3. |
Flammable liquids |
|
4. |
Flammable solids, materials
liable to spontaneous combustion, materials which, in contact with water,
emit flammable gases |
|
5. |
Oxidizing materials and organic
peroxides |
|
6. |
Poisonous and infectious materials |
|
7. |
Radioactive materials |
|
8. |
Corrosive materials |
|
9. |
Various hazardous materials and
items |
Source:
own elaboration based on 16
The division system is important
in determining transport conditions, including marking, selection of packaging,
requirements for means of transport. 13. A
given material or substance is classified into a specific category based on the
hazard it poses, but if it is characterized by several types of hazards, the
hazard with the dominant influence is decisive. Within a class, the type of
hazard is expressed using a classification code. The basic hazard symbols can
be listed: F – flammability, T – toxic effect, C – corrosive
effect. Annex B sets out guidelines relating to means of transport and cargo
operations, including requirements regarding the work of the vehicle crew,
mandatory equipment, documentation, and procedures, as well as the construction
of vehicles and their approval for road traffic 16.
There are also other legal acts
that partially influence the regulation of the movement of dangerous cargo
units, including laws on the control of the transport of dangerous cargo 36,
technical supervision of vehicles carrying this type of load 47
and broadly understood road traffic law 43.
2.2.
Requirements for means of transport for the transport of dangerous goods
Each
vehicle used to transport dangerous goods by road should be appropriately
adapted for this purpose. In addition to the standard equipment specified in
the Road Traffic Act, vehicles should have additional equipment to protect the
driver, other people, and the environment in emergency situations 2. Means of transport used in the
transport of dangerous goods should additionally meet the designed requirements
in the field of electrical installation, quality of cables, fuel tanks, exhaust
system, auxiliary heating, driver's cabin, and speed limiter. An important
element is also the labeling, which should be appropriate to the method of
transport and the type of cargo. These can be, for example:
·
in the case of transporting piece goods (e.g.,
containers, palletized loads), orange plates placed at the front and rear of
the vehicle. In the case of containerized cargo, the container should be marked
with warning stickers (orange stickers with the UN number and stickers
indicating the class of dangerous goods transported) placed on its four walls.
·
in the case of transporting dangerous goods in bulk or
in tanks, the vehicle marking should consist of orange plates containing the
product identification number and the hazard identification number.
Identification numbers should be indelible and remain legible after 15 minutes
in fire. Another type of marking may be orange plates without identifying marks
and warning stickers placed on the front and rear of the vehicle 13.
An information board is placed on road means of
transport specialized for the transport of dangerous goods. In the upper part
of the board, the identification number of the danger, the degree of danger and
additional dangerous features are entered. In turn, the marking at the bottom
of the table indicates the mentioned UN number — designating the
material.
3.
LITERATURE REVIEW
3.1.
Risk and methods of its assessment
Due
to the size of the threats that may be caused by a road accident during the
transport of dangerous goods, the risk aspect is increasingly being analysed by
many authors 5, 42.
Issues related to risk assessment methods are described in both domestic and
international publications 27,
and in general terms, it is most often assigned to one of three groups:
quantitative methods, qualitative methods or quantitative-qualitative methods.
For example, work 14
reviewed the most important sources of knowledge related to this area and
detailed mathematical models for carrying out various types of reliability
analyzes for transport systems. The use of a fault tree and Monte Carlo
simulation in item 41
enabled a qualitative and quantitative assessment of reliability by identifying
weak links in the transport system. In contrast, the paper 53
presents the relationship between reliability costs and potential subsystem
risk by applying a comprehensive allocation method based on fuzzy logic. The
approach related to the use of the HAZOP method (z ang. Hazard and operability
studies) to assess process risk is presented in position 34.
Thanks to the method used, it was possible to identify potential threats and
losses that may occur during the implementation of tasks.
It
should be emphasized that the choice of risk assessment method may be
determined by the specificity of the mode of transport in which cargo or
passengers are transported. As part of planning the demand for rolling stock by
a railway carrier, article 22 uses the
Monte Carlo simulation method. The authors assigned the risk assessment methods
recommended to railway companies to be used in the following approach:
·
checklists – organizations starting the process
on the transport market,
·
analysis of the types and effects of possible errors
(Failure Mode and Effect Analysis, FMEA), analysis of threats and operational
capabilities (Hazard and Operability Study, HAZOP), COSO II – an
organization with extensive experience in the process (e.g., Polish carriers
with at least 2 years of experience)
·
FTA (Fault Tree Analysis) – an organization with
extensive experience in the process, with a large amount of data on events
— the largest freight and passenger carriers, main infrastructure
managers.
The
issues related to ensuring safety in the air traffic management system are
presented in the publication 15. The authors
identified potential threats and assigned them to one of three tolerance areas.
A methodology based on the use of Markov chains for assessing the security risk
of the maritime transport system is included in the article 50.
The authors studied changes in the system state and identified the moment when
a low-probability incident turns into a high-risk event.
In
addition to aspects related to the modal approach to transport, it is also
necessary to indicate international standards that describe and indicate risk
assessment methods. One of the standards used around risk management is the ISO
31000:2018 standard 25. The document
presents guidelines and principles that can be implemented in enterprises, and
assigns methods and techniques recommended for use to individual stages of risk
management. The standard presents dedicated methods for stages such as risk
identification, risk analysis, risk assessment, risk evaluation and recording
and reporting. Proper risk management is a process established to protect also
transport companies against the effects of undesirable phenomena. The purpose
of this process is to take actions to minimize the risk to achieve better
business results, which have a direct impact on ensuring the quality of the
transport services provided. In connection with the above, it should be
emphasized that the selection of the risk assessment method depends primarily
on the object being examined and the purpose of the analyses performed.
3.2. Areas of risk assessment in the transport of dangerous goods
It
is worth specifying what this risk is at the beginning. According to article 3 transport
risk in a general sense can be defined as the probability of an undesirable
event that may result in loss of life or health of persons responsible for the
transport or loss of the subject of shipment. Each type of risk is a source of
undesirable costs, which include: financial resources incurred to reduce the
risk, financial resources intended to finance the risk, expenses resulting from
the cessation of a specific activity due to the associated risk or costs
resulting from the lack of reimbursement of specific losses 23, 20.
Analyzing
the general issue of risk analysis in the road transport of dangerous goods,
the literature on the issues of threats arising from the transport of this type
of cargo is very extensive. Most often, multi-criteria or multi-criteria
methods for determining vehicle routes are used as the main point for risk
assessment. For example, the authors of item 54
developed a risk analysis system for the transport of hazardous materials based
on a geographic information system (GIS). According to them, the risk of an
accident involving dangerous goods can be divided into two elements: the
probability of an accident occurring and the consequences of an accident if it
occurs. In turn, in publication 11
the authors conclude that in previous studies the risk occurring on a given
route was analysed on the basis of research based on operational methods,
without methods taking into account historical data on accidents, which is not
entirely correct. Publication 30
discusses in detail the statistical models that can be used to analyze accident
data. The lessons learned resulted in the improvement of existing methods and
the development of an approach that uses historical accident data to calculate
the risk occurring in the multimodal transport of dangerous goods in Flanders.
In
the case of item 49 a
method was developed for risk analysis and route optimization in road transport
of dangerous goods, based on a path selection model that comprehensively
measures the risk and cost of road transport in time-varying conditions. On
this basis, considering the principle of avoiding high-risk transport routes,
the authors proposed a method for selecting the optimal transport path in
accordance with the assumed preferences. Another important issue is the issue
of determining vehicle routes in the transport of dangerous goods in the
context of minimizing the probability of a road incident with serious damage to
the vehicle performing the transport. The authors of the publication 26
recommended an original model aimed at minimizing the probability of an
accident in the transport of dangerous goods. The research on the selected
region of Poland was based on the use of the heuristic ant algorithm and
Dijkstra's algorithm. The authors finally concluded that the ant algorithm
provides valuable information in solving complex problems related to the
transport of dangerous goods and is much more acceptable compared to Dijkstra's
algorithm.
Article
29
presents Greek experience in the use of quantitative risk assessment (QRA)
methods in the transport of dangerous goods through tunnels located along Greek
transport routes. The publication 8
also discusses the issue of cargo transport through road tunnels. The authors
focused on analyzing the impact of air quality on the transport of dangerous
goods. Scenarios for transport in completely fresh air conditions and in the
event of tunnel ventilation failure were analysed. The article 7
focused in detail on the transport of hydrogen in one-way highway tunnels.
Studies based on event tree and parametric analysis showed an increased level
of risk in the presence of transported hydrogen.
The
safe transportation of dangerous goods depends on many factors. Item 4
addresses the issue of examining the conditions of transport of this type of
cargo and identifying factors that have a significant impact on the transport
of these goods by road. According to the survey conducted in Lithuania, three
groups of such factors were identified. The research results presented in the
article indicate that the greatest influence on the probability of an accident
during the road transport of dangerous goods has the main factors of group I.
The main factors include incorrect loading, vehicle condition, driver fatigue,
weather, and road conditions. Factors from the second group determine, among
others: tightness of the transport vehicle and the technical condition of the
vehicle. Group III are organizational factors and include: the risk associated
with the transport of goods, the selection of an appropriate route and the risk
of communication with emergency services.
The authors of the publication 32
focused on understanding the relationship between the risk of driving a
commercial truck transporting dangerous goods and risk exposure factors. The
aim of the work was to find a way to assess risk in a specific transport
environment, such as a specific route. The research is based on statistical
data from six companies located in China. Using the Weibull distribution, it
was shown that factors such as weather, traffic intensity, travel time and
average speed have the most significant impact on accident-free travel on the
designated route.
The
FTA method is a universal tool whose functionalities can be used both in the
field of transport and in other areas of industry. An example of performing
risk analysis using the fault tree method is position 31.
The authors of the above-mentioned publication focused on the analysis of
infectious medical waste management at the Clinical Centre in Serbia. The
research was based on three aspects of the FTA method — functional,
qualitative, and quantitative. The authors of the publication used the fault
tree method to perform the research due to the possibility of analyzing
individual threats and assessing the relationships and interdependencies
between these threats.
Considering
the above, the authors of the article decided to use the fault tree method to
estimate the risk of road transport of dangerous goods in Poland.
4.
CONSTRUCTION OF A DECISION-MAKING MODEL FOR ASSESSING THE RISK OF
TRANSPORTATION OF DANGEROUS GOODS USING THE FAULT TREE METHOD
The
FTA (Fault Tree Analysis) method is an advanced deductive technique used to
analyze the factors that cause adverse events 10.
Analysis using a fault tree is a cause-and-effect graphical method modelling
how failures of individual parts of the process occur, leading to the failure
of the entire system 51.
The method consists in illustrating individual factors that may lead to an
undesirable event and its potential effects on the so-called error tree. The
error tree indicates the interdependencies between the potential event and the
main event (the so-called peak event) and the causes of this event. Specific
causes marked on the error tree are closely related and may be defined as human
errors, failures, environmental conditions, or other events that may influence
the failure. The risk analysis process using the fault tree method is used for
qualitative analysis, when focusing on the risk and understanding the situation
to which the risk relates. It also enables qualitative analysis, enabling the
determination of the probabilities of sequences of events. The algorithm for
hazard analysis using the failure tree method is shown in fig. 2. The method has several basic steps:
·
identification of the peak event,
·
identification of events threatening/leading to the
occurrence of a peak event — indirect events,
·
creating a hierarchical structure of the error tree
considering all intermediate events and connecting these events with logic
gates,
·
defining the basic events that are the sources of the
peak event,
·
determining the probability of events occurring,
·
determining the elementary events leading to the
occurrence of the peak event,
·
determining the probability of a peak event occurring 57.
The
probability of a peak event is estimated based on individual adverse events.
Each such event should be considered individually 52.
However, if the probabilities of all individual events are not determined, the
final probability of the peak event will be unreliable. In turn, shortcomings,
or faults at the lowest level of the fault tree are the basic and key factors
that have a decisive impact on the occurrence of the peak event. It is on them
that the company should focus the most attention and take actions to limit the
occurrence of the event 37.
Taking
the above into account, the authors of the article decided to assess the risk
of transporting dangerous goods using the unsuitability tree method due to seven
important aspects affecting the attractiveness of this method. It should be
added that none of the risk analysis methods is universal, and the choice
depends on the characteristics of the project, available resources and the
specific nature of the industry. However, FTA is an effective tool, especially
when there is a need for a structural and logical analysis of the causes of
risk. The mentioned features supporting the FTA method are presented in the
table. 2.
Fig.
2. Algorithm for hazard analysis in road transport of dangerous goods using the
fault tree method
Source:
own elaboration
Tab.
2
Special
features of the unfitness tree method
|
1.
No. |
Characteristic feature |
Comment |
|
1. |
Possibility of structural interpretation of
events |
Through the
graphical and structural representation of events, FTA allows you to
understand how factors and the connections between them may contribute to the
occurrence of risk. |
|
2. |
Identification
of critical factors |
The method
allows you to identify elements that have a key impact on the stability and
functionality of the tested system. |
|
3. |
Ease of interpretation of the included data |
Thanks to
the graphical representation of events, both the creators and recipients of
the analyses performed can quickly understand the risk structure and
significant dependencies. |
|
4. |
Assessment of the probability of events |
In further
research, the method can be expanded to include the probabilities assigned to
each element. This will enable risk assessment and assessment of which event
has the greatest impact on transport. |
|
5. |
Integration with other risk analysis methods |
The FTA
method can be used as an element of a more comprehensive risk analysis
method. |
|
6. |
Application
in various industries |
The FTA
method is a flexible tool and, apart from transport, it can be used in other
industries, such as the chemical, aviation, energy, and IT industries. |
|
7. |
Failure
prevention |
FTA analysis
helps to identify critical points characterized by an increased probability
of threat occurrence. This allows project teams to implement appropriate
countermeasures and prevent potential problems more quickly. |
Source:
own elaboration
4.2. Principles of constructing a fault tree
A
classic fault tree consists of three types of nodes: events, logic gates and
transfer symbols. The FTA method distinguishes three types of events, depending
on their location in the tree. These are: base events, intermediate events, and
peak events. At the lowest level of the tree there are basic events that,
according to the assumptions, are not subject to further analysis because they
constitute a direct source of threat. The combination of basic events triggers
the occurrence of intermediate events that describe changes in the structure
and functioning of subsystems. In turn, combinations of intermediate or
intermediate events combined with basic events cause the occurrence of
subsequent intermediate events and ultimately lead to the occurrence of a peak
event.
Logical
relations in the failure tree, as mentioned earlier, are described using logic
gates. These operators, depending on their type, have one or more inputs and
only one output. The input to the gate usually includes primary events,
intermediate events or combinations of internal transfers marked with
triangles. The output of the gate usually contains higher level intermediate
events or peak events. The designations of individual elements used to create
unsuitability trees are presented in tab. 3.
Tab.
3
Symbolism
of the fault tree
|
1.
No. |
Symbol |
Characteristics |
|
1. |
|
Intermediate
event. A fault caused by a logical combination of other events occurring
further down the tree. It
is often a type of logic gate. |
|
2. |
|
Basic event.
Its further analysis is not possible. This is a source of danger. |
|
3. |
|
Undeveloped
event. An event whose contribution is not considered in the analysis because
it is considered unnecessary, or the available information is insufficient. |
|
4. |
|
External
event. It does not represent any error and is part of the nominal behaviour
of the system. An event
occurs or does not occur. |
|
5. |
|
Conditioning
event. Does not necessarily indicate a fault. Serves as a special condition
or restriction for certain types of gates. |
|
6. |
|
OR gate.
Used to show a scenario in which an output event will occur if at least one
of the input events occurs. |
|
7. |
|
AND gate.
Links single faults to a peak event. Occurs only when all events are true. Furthermore, the events must occur
simultaneously. |
|
8. |
|
XOR gate.
Occurs when one and only one of the output events is true. |
|
9. |
|
INHIBIT
gate. It is a special case of an AND gate. Occurs when its only input event
is true in the presence of a conditioning event. |
Source:
own elaboration based on 28
In
the fault tree, logic gates act as event connectors. Each gateway can connect
one input event to one or more output events. Event labeling should be done in
a way that allows easy identification of connections between parts of the fault
trees. The most used logic gates are AND and OR gates. AND gate means that the
output event Ep is
generated when all input events E1,
E2, …, En occurs 9:
Analyzing
two independent events E1
and E2 the probability of
occurrence of the output event P(Ep)
for the AND gate can be presented using the following equation:
For an AND
gate with n independent input events, the probability of an output event
is:
The
OR gate, in turn, is used when adding input events. The output event Ep
is generated when at least one of the input events E1, E2, …, En 9:
For
an OR gate, the probability of the output event P(Ep) for two independent events can be expressed in the
following form:
For
an OR gate with n independent output events, the probability of
generating an output event is:
5.
CASE STUDY
5.1.
Preliminary assumptions for risk assessment of the transportation of dangerous
cargoes
According
to data from 2022, apart from Poland, Germany, Spain, and France are the
largest carriers of dangerous goods and materials in Europe. In Poland,
approximately 150 million tons of dangerous goods are transported by road every
year, 66% of which are flammable liquid materials. The second-largest group,
accounting for 25% of the total transport of dangerous goods, are gases.
Approximately 430,000 tons are transported daily. Based on the available
literature and statistical data, the most common causes of hazards during the
entire transport process of dangerous goods were identified. These can be:
1.
non-compliance of the transport performed with ADR
requirements,
2.
inadequate technical condition of packaging and
loading units,
3.
technical condition of the means of transport
inconsistent with the requirements,
4.
incorrect fastening of the load on the loading surface
of the means of transport,
5.
poor technical condition of transport routes along
which transport is carried out,
6.
inadequate equipment at transshipment points,
7.
poor technical condition of infrastructure and
transshipment equipment,
8.
the lack of adequate theoretical and practical
preparation for the transport of dangerous goods in individual links of the
transport chain,
9.
improper organization and technology of transport of
dangerous goods,
10. failure to properly
protect reloading equipment against the penetration of released hazardous
substances into the natural environment,
11. excessive influence
of other road users on the transport of dangerous goods, resulting in road
collisions as a result of human error.
5.2.
Construction of the fault tree
In
the case under consideration, the unsuitability tree was applied to the problem
of risk analysis in road transport of dangerous goods. In accordance with point
4.2. The peak event of the constructed unsuitability tree is environmental
contamination combined with a threat to human health or life. The peak event
consists of 4 main intermediate events. These are:
1)
occurrence of a road accident (RA),
2)
leakage of substances or gas escape during the
organization and execution of transport,
3)
improper organization and technology of cargo
transport (IOaT),
4)
non-compliance of the transport performed with the
requirements of the ADR Convention (ADR).
For
the sake of uniformity and transparency of the analysis, the unsuitability tree
was divided into five integral parts (figs. 3-7). In each component of the
analysis, the markings in the form of isosceles triangles represent the
above-mentioned transfers to increase the transparency of the model. Markings
in the form of rectangles reflect indirect events, while circles are basic
events that are the direct cause of the threat.
Risk
analysis in the transport of dangerous goods performed using the FTA method
consists of 37 indirect events that have a significant impact on the
organization of transport. In addition, 60 basic events were specified, which
are also sources of danger in this type of transport. 38 logic gates were used
as connecting points, of which only 4 are "AND" logic gates. Figs.
3-5. and 7 contain the logical analysis of the main intermediate events of the
fault tree. In turn, fig. 6 complements the indirect event – the
occurrence of a road accident.
Fig.
3. First part of the fault tree – peak event analysis
Source:
own elaboration
5.2.
Fault tree construction using TopEvent FTA computer software
To
verify and check the correctness of the tests performed using the failure tree
method, a structure analysis was performed using TopEvent FTA computer
software. Thanks to the above-mentioned software, you can create complex error
trees and perform analyzes on ready-made diagrams. The article checked the
correctness of connections between individual events and logical operators. The
verification of the proposed non-compliance tree did not reveal any
irregularities; therefore, it can be concluded that the structure is
constructed correctly and the line of reasoning itself is correct. Top-Top 4
elements represent individual components of the inconsistency tree (according
to figs. 3 - 7). In turn, at the bottom there is an error list bar. When the
probabilities of each intermediate and base event are clearly defined, the
software also allows you to generate the probability of a peak event. This functionality
has been omitted due to the illustrative nature of the article. Fig. 8 shows a
screenshot of the software view with a reflected incompatibility tree.
The
presented analysis is a theoretical structure based on a general approach to
the threats occurring in the road transport of dangerous goods. Future research
may focus on building an unsuitability tree adapted to the individual realities
of transporting dangerous goods, or expanding the current scheme to include
dedicated threats resulting from the specific nature of transporting the
specific types of dangerous goods. It is also possible to expand the analyses
with probabilities for each element of the diagram. This will enable risk
assessment and assessment of which event has the greatest impact on the
occurrence of the investigated peak event.
Fig.
4. Analysis of an intermediate event – non-compliance of the transport
performed with the requirements of the ADR Convention
Source: own elaboration
Fig.
5. Analysis of an intermediate event – occurrence of a road accident
Source: own elaboration
Fig.
6. Analysis of an intermediate event – vehicle breakdown occurs during
transport
Source: own elaboration
Fig.
7. Analysis of an intermediate event - improper organization and technology of cargo
transport
Source:
own elaboration
6.
SUMMARY
The
article focuses on risk analysis during the broadly understood transport of
dangerous goods. The first part included a review of the literature, which
touched upon the specificity of the transport of dangerous goods, the generally
understood risk and legal regulations. The requirements for road means of
transport were also characterized. Moreover, based on statistical data, the
volume of dangerous goods transport in ten European Union countries dominating
in this field of road transport was estimated and compared.
In
the next part of the article, based on the available literature and statistical
data, threats arising from the processes of organizing and carrying out road
transport of dangerous goods are identified. The paper identifies 11 basic
threats that are the most common causes of dangerous situations during
transport. The threats include but are not limited to non-compliance of
transport with applicable regulations, poor technical condition of means of
transport and loading equipment, poor condition of collective packaging,
incorrect fastening of the load on the loading surface of the vehicle or,
mainly speaking, incorrect organization of the transport process.
The
third part of the work presents the analysis of hazards and the resulting risks
in the transport of dangerous goods using the unsuitability tree method, also
known as the error tree in the literature. The peak event in the analyses
carried out was environmental contamination and exposure of people to loss of
life or health. Four main indirect events were analysed: the occurrence of a
road accident, leakage, or escape of a substance/gas during the organization
and performance of road transport, improper organization and technology of cargo
transport, and non-compliance of transport with the provisions of the ADR
Convention. Due to its extensiveness and the inability to read it conveniently,
the analysis was divided into five separate parts, constituting a coherent
whole. In addition to the main indirect events, the analysis using the
unfitness tree includes another 33 indirect events. Ultimately, the list
consists of 60 basic events, which are also sources of the existing threat. To
verify the correctness of the tests performed, a failure tree analysis was
performed using TopEvent FTA computer software. The verification of the
inconsistency tree did not reveal any irregularities; therefore, it can be
concluded that the reasoning and the graphic design of the method were
performed correctly.
Analyzing
the results, the most common indirect events that have a significant impact on
the occurrence of hazards during the transport of dangerous goods are a
deficient level of knowledge, lack of training aimed at appropriate preparation
of employees and damage to cargo equipment/means of transport. However, the
broadly understood human error has the most significant impact on the level of
risk.
Fig.
8. Preview of the TopEvent FTA software
Source:
own elaboration
Acknowledgement
This
article is the result of work carried out under the Dean's grant entitled:
“Analysis of risk in road traffic during the transport of oversized and
dangerous cargo” awarded in 2022. The grant was financed by the Dean of
the Faculty of Transport of the Warsaw University of Technology.
References
1.
Accettura Antonella, Roberto Bubbico, Fabio Garzia, Barbara Mazzarotta. 2014. „Improving
security in road transportation of hazardous materials”. International journal of safety and security
engineering 4(4): 289-305. DOI: 10.2495/SAFE-V4-N4-289-305.
2.
Batarlienė Nijole. 2008. „Dangerous goods transportation: new
technologies and reducing of the accidents”. Journal of Konbin 8(1): 211-222. DOI: 10.2478/v10040-008-0114-7.
3.
Batarliene Nijole. 2008. „Risk analysis and assessment for
transportation of dangerous freight. Transport 23(2): 98-103. DOI: https://doi.org/10.3846/1648-4142.2008.23.98-103.
4.
Batarliene Nijole. 2020. „Essential safety
factors for the transport of dangerous goods by road: A case study of
Lithuania”. Sustainability 12(12): 1-16 4. DOI: https://doi.org/10.3390/su12124954.
5.
Benekos Ioannis, Dimitris Diamantidis. 2017. „On risk assessment
and risk acceptance of dangerous goods transportation through road tunnels in
Greece”. Safety science 91: 1-10. DOI: https://doi.org/10.1016/j.ssci.2016.07.013.
6.
Budny Adrian, Tomasz Rokicki. 2021. „Road transport of dangerous
goods in Poland”. Ekonomika i Organizacja
Logistyki 6(3): 13-21. ISSN: 2450-8055. DOI: https://doi.org/10.22630/EIOL.2021.6.3.18.
7.
Caliendo Ciro, Gianluca Genovese. 2021.
„Quantitative risk assessment on the transport of dangerous goods
vehicles through unidirectional road tunnels: an evaluation of the risk of
transporting hydrogen”. Risk analysis 41(9): 1522-1539.DOI: https://doi.org/10.1111/risa.13653.
8.
Caliendo Ciro, Maria Lusia De Guglielmo. 2017. „Quantitative Risk
Analysis on the Transport of Dangerous Goods Through a Bi‐Directional
Road Tunnel”. Risk Analysis 37(1), 116-129: DOI: https://doi.org/10.1111/risa.12594.
9.
Chybowski Leszek. 2017. Analiza drzewa niezdatności: Podstawy
teoretyczne i zastosowania. Szczecin: Wydawnictwo
Naukowe Akademii Morskiej w Szczecinie. [In English: Unfitness Tree Analysis: Theoretical Foundations and Applications.
Szczecin: Scientific Publishing House of the Maritime University of Szczecin].
10.
Ciszewski Tomasz,
Waldemar Nowakowski, Zbigniew Łukasik. 2020.
„A fault tree analysis-based method of railway traffic control systems
safety assessment”. Prace Naukowe
Politechniki Warszawskiej. Transport (128): 49-57. DOI: 10.5604/01.3001.0014.0902.
11. Clark
M. Rene, Mary E. Besterfield‐Sacre. 2009. „A new approach
to hazardous materials transportation risk analysis: decision modelling to
identify critical variables”. Risk Analysis: An International
Journal 29(3):
344-354. DOI: https://doi.org/10.1111/j.15396924.2008.01163.x.
12.
Conca Andrea, Chiara Ridella, Enrico Sapori. 2016. „A risk assessment for road transportation of dangerous
goods: a routing solution”. Transportation Research
Procedia 14: 2890-2899. DOI: https://doi.org/10.1016/j.trpro.2016.05.407.
13.
Cooper Laura, Dennis Nolan, Richard Bales, Stephen Befort, Lise Gelernter,
Michael Green. 2020. ADR in the
Workplace. Fort Worth. West Academic.
15. Dudek Ewa, Karolina
Krzykowska-Piotrowska, Mirosław Siergiejczyk. 2020. „Risk management in
(air) transport with exemplary risk analysis based on the tolerability
matrix”. Transport Problems 15(2): 143-156. DOI:
https://doi.org/15.10.21307/tp-2020-027.
16. European Agreement Concerning the International Carriage of Dangerous
Goods by Road (ADR). Drawn Up in Geneva on 30
September 1957 (Dz.U. [Journal of Laws] of 1975, No. 35, Item 189).
17. Eurostat-Statistics.
„Road freight transport of dangerous goods by type of dangerous goods and
territorial coverage – annual data”. Available at: https://ec.europa.eu/eurostat/databrowser/view/road_go_ta_dg/default/table?lang=en.
18. Fabiano Bruno, Fabio Currò,
Andrea Pietro Reverberi, Renato Pastorino. 2005.
„Dangerous good transportation by road: from risk analysis to emergency
planning”. Journal of Loss
Prevention in the process industries 18(4-6): 403-413. DOI: https://doi.org/10.1016/j.jlp.2005.06.031.
19.
Fabiano Bruno, Fabio Currò, Emilio Palazzi, Renato Pastorino. 2002. „A framework for risk assessment and decision-making
strategies in dangerous good transportation”. Journal of hazardous materials 93(1): 1-15. DOI: https://doi.org/10.1016/S0304-3894(02)00034-1.
20.
Forigua Julio, Liliana Lyons. 2016. „Safety analysis of
transportation chain for dangerous goods: A case study in Colombia”. Transportation Research Procedia 12: 842-850. DOI: https://doi.org/10.1016/j.trpro.2016.02.037.
21.
Galierikova Andrea, Jarmila Sosedova. 2018. „Intermodal
transportation of dangerous goods”. NAŠE
MORE 65(3): 8-11. DOI: https://doi.org/10.17818/NM/2018/3.8.
22. Gołębiowski Piotr, Ignacy
Góra, Yaroslaw Bolzhelarskyi. 2023.
„Risk assessment in railway rolling stock planning”. Archives of Transport 65(1): 137-154.
23. Guo Jian, Cheng Luo. 2022. „Risk assessment of hazardous materials transportation: A review of
research progress in the last thirty years”. Journal of traffic and
transportation engineering (English edition). DOI: https://doi.org/10.1016/j.jtte.2022.01.004.
24. https://doi.org/10.5604/01.3001.0016.2817.
25.
ISO 31000:2018. Risk Management –
Guidelines. London: BSI Standards Limited 2018.
26.
Izdebski
Mariusz, Ilona Jacyna-Gołda, Paweł Gołda. 2022. „Minimisation of the
probability of serious road accidents in the transport of dangerous
goods”. Reliability Engineering
& System Safety 217: 108093. DOI:
https://doi.org/10.1016/j.ress.2021.108093.
27.
Janno Jelizaveta, Ott Koppel. 2018. „Operational risks in
dangerous goods transportation chain on roads”. LogForum 14(1): 33-41. ISSN: 1895-2038. DOI:
10.17270/J.LOG.2018.261.
28. Kabir Sohag. 2017. „An
overview of fault tree analysis and its application in model based
dependability analysis”. Expert
Systems with Applications (77): 114-135. DOI: https://doi.org/10.1016/j.eswa.2017.01.058.
29. Kalogeraki
Marianna, Fani Antoniou. 2021. „Improving Risk Assessment for
Transporting Dangerous Goods through European Road Tunnels: A Delphi
Study”. Systems 9(4): 80. DOI: https://doi.org/10.3390/systems9040080.
30.
Lord Dominique, Fred Mannering. 2010. „The
statistical analysis of crash-frequency data: A review and assessment of
methodological alternatives”. Transportation
research part A: policy and practice 44(5): 291-305. DOI: https://doi.org/10.1016/j.tra.2010.02.001.
31. Makajic-Nikolic
Dragana, Natasa Petrovic, Ana Belic, Mihailo Rokvic, Jelena Andreja Radakovic,
Vojin Tubic. 2016. „The fault tree analysis of infectious medical waste
management”. Journal of Cleaner
Production 113: 365-373. DOI: https://doi.org/10.1016/j.jclepro.2015.11.022.
32. Niu
Shifeng, Satish V. Ukkusuri. 2020. „Risk Assessment of Commercial
dangerous-goods truck drivers using geo-location data: A case study in
China”. Accident Analysis & Prevention 137: 105427. DOI: https://doi.org/10.1016/j.aap.2019.105427.
33.
Nowacki Gabriel, Krysiuk
Cezary, Rafał Kopczewski. 2016. „Dangerous goods
transport problems in the European Union and Poland”. TransNav: International Journal on Marine
Navigation and Safety of Sea Transportation 10(1): 143-150. DOI:
10.12716/1001.10.01.16.
34. Pruszkowski Leszek. 2015. „HAZOP
jako metoda wspomagająca zarządzanie bezpieczeństwem procesowym
w przedsiębiorstwie”. Acta Universitatis Nicolai
Copernici. Zarządzanie 42(3): 7-20. DOI: https://doi.org/10.12775/AUNC_ZARZ.2015.029. [In English: „HAZOP as a
method to support process safety management in an enterprise”. Acta Universitatis
Nicolai Copernici. Management].
37.
Ruijters Enno, Marïelle Stoelinga. 2015. „Fault tree
analysis: A survey of the state-of-the-art in modelling, analysis and
tools”. Computer science review 15: 29-62. DOI: https://doi.org/10.1016/j.cosrev.2015.03.001.
39.
Slavinskaitė Neringa, Nijole Batarlienė. 2022.
„Investigation of safety conditions in the transport of dangerous goods
by railway”. Transport 37(1): 64-72. DOI:
https://doi.org/10.3846/transport.2022.16985.
40. Staniuk Wiesław, Michał
Staniuk, Norbert Chamier-Gliszczynski, Marianna Jacyna, Michał
Kłodawski. 2022.
„Decision-Making under the Risk, Uncertainty and COVID-19 Pandemic
Conditions Applying the PL9A Method of Logistics Planning-Case Study”. Energies
15(2): 639. DOI: https://doi.org/10.3390/en15020639.
41. Szkoda Maciej, Grzegorz Kaczor. 2016.
„Ocena niezawodności systemu transportowego z wykorzystaniem
metody dynamicznego drzewa niezdatności”. Autobusy 17(6): 1593-1598. ISSN:
1509-5878. [In English: „Reliability assessment of transport system using
dynamic unfitness tree method”. Bus].
42.
Tanackov Ilija, Zdenko
Janković, Siniša Sremac, Milica Miličić, Marko Vasiljević,
Jelena Mihaljev-Martinov, Ivan Škiljaica. 2018. „Risk distribution of dangerous goods in logistics
subsystems”. Journal of Loss
Prevention in the Process Industries 54: 373-383. DOI: https://doi.org/10.1016/j.jlp.2018.03.013.
45.
The Act of 15 November 15, 1984 –
Transport Law (Dz.U. of 1995, No. 119, Item 575).
46.
The Act of 19 August 2011 on the Transport of
Dangerous Goods (Dz.U. 2011, No. 227, Item 1,367).
48.
Torretta Vincenzo, Elena Cristina Rada, Marco Schiavon, Paolo Viotti. 2017. „Decision support systems for assessing risks involved in
transporting hazardous materials: A review”. Safety science 92: 1-9. DOI: https://doi.org/10.1016/j.ssci.2016.09.008.
49.
Van Raemdonck Koen, Cathy Macharis, Olivier
Mairesse. 2013. „Risk analysis system for the transport of hazardous
materials”. Journal of safety
research 45: 55-63. DOI: https://doi.org/10.1016/j.jsr.2013.01.002Get rights and content.
50. Wang
Siqi, Jingbo Yin J, Rafi Ullah Khan. 2020. „The Multi-State Maritime
Transportation System Risk Assessment and Safety Analysis”. Sustainability
12(14): 5728. DOI: https://doi.org/10.3390/su12145728.
51. Yazdi Mohammad, Farzaneh Nikfar, Mahnaz Nasrabadi. 2017. „Failure probability analysis by employing fuzzy fault tree
analysis”. International Journal of System Assurance Engineering and
Management 8: 1177-1193. DOI: 10.1007/s13198-017-0583-y.
52. Yazdi Mohammad, Javad
Mohammadpour, He Li, Hong Zhong Huang, Esmaeil Zarei, Reza Ghasemi
Pirbalouti, Sidum Adumene. 2023. „Fault tree analysis improvements: a
bibliometric analysis and literature review”. Quality and Reliability Engineering International 39(5): 1639-1659.
DOI: https://doi.org/10.1002/qre.3271.
53. Yu Hui, Genbao Zhang, Yan Ran, Mengqi
Li, Yang Wang. 2018. „A
comprehensive and practical reliability allocation method considering failure
effects and reliability costs”. Maintenance and
Reliability 20(2):
244-251. DOI: https://doi.org/10.17531/ein.2018.2.09.
54. Yu Miao,
Ting Deng, Jie Fu. 2012. „Application
of RFID and GPS technology in transportation vehicles monitoring system for
dangerous goods”. In: 2012 2nd
International Conference on Remote Sensing, Environment and Transportation
Engineering, IEEE Xplore: 1-4. DOI: 10.1109/RSETE.2012.6260409.
55. Zabielska Aleksandra, Marianna Jacyna,
Michał Lasota, Karol Nehring. 2023.
„Evaluation of the efficiency of the delivery process in the technical object
of transport infrastructure with the application of a simulation model”. Eksploatacja i Niezawodnosc - Maintenance
& Reliability 25(1): 1-12. DOI: https://doi.org/10.17531/ein.2023.1.1.
56.
Zhang Lukai, Xuesong Feng. 2021. „Planning tank-truck hazardous
materials shipments in intercity road transportation networks”. Applied Mathematical Modelling 89: 1860-1880. DOI:
https://doi.org/10.1016/j.apm.2020.09.009.
57. Zhou Kan, Ge Huang, Shan Wang, Kai
Fang. 2020. „Research on
transportation safety of hazardous chemicals based on fault tree analysis
(FTA). In: 2020 9th International
Conference on Industrial Technology and Management (ICITM): 206-209. DOI: 10.1109/ICITM48982.2020.9080360.
Received 10.12.2023; accepted in
revised form 15.02.2024
Scientific Journal of Silesian University of Technology. Series
Transport is licensed under a Creative Commons Attribution 4.0
International License
[1]
Faculty of Transport, Warsaw University of Technology, Koszykowa 75 Street,
00-662 Warsaw, Poland. Email: michal.lasota@pw.edu.pl. ORCID:
https://orcid.org/0000-0002-3090-4815
[2]
Faculty of Transport, Warsaw University of Technology, Koszykowa 75 Street,
00-662 Warsaw, Poland. Email: marianna.jacyna@pw.edu.pl. ORCID:
https://orcid.org/0000-0002-7582-4536
[3]
Faculty of Transport, Warsaw University of Technology, Koszykowa 75 Street,
00-662 Warsaw, Poland. Email: lucyna.szacillo@pw.edu.pl. ORCID:
https://orcid.org/0000-0002-3074-9931