Article citation information:
Szczucka-Lasota, B. Ongoing monitoring of liquid fuel quality at storage facilities. Scientific Journal of Silesian University of Technology. Series Transport. 2024, 125, 259-282. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2024.125.17.
Bożena
SZCZUCKA-LASOTA[1]
ONGOING
MONITORING OF LIQUID FUEL QUALITY AT STORAGE FACILITIES
Summary. The newly developed
method employs spectral analysis to evaluate fuel quality continuously. Unlike
traditional approaches, it eliminates the need for sampling and laboratory
analysis, provides real-time results, facilitates rapid decision-making
regarding fuel quality, and enhances operational efficiency. A comparative
analysis of the new method with laboratory tests carried out following ISO
standards demonstrated its effectiveness in the assessment of liquid fuels
containing biocomponents. The determined age in sample ageing index is highly
correlated with the oxidative stability of the Diesel oil and resin content for
Pb95 and Pb98. Statistically, significant transformation functions were
developed. The results confirm the ability of the method to rapidly identify
substandard fuels, thereby accelerating their withdrawal from the market. The
implementation of this spectral analysis-based method represents a significant
advance in fuel quality assessment. Its continuous monitoring capability and
real-time reporting distinguish it from conventional approaches, thereby
offering practical benefits for fuel management. Ensuring timely interventions
to maintain quality standards are supported by enabling the prompt detection of
degraded fuels. The applicability of this method to state fuel reserves and
petrol stations underlines its usefulness in improving fuel quality control
measures. Overall, its introduction offers both economic and environmental
benefits to the transportation sector.
Keywords: fuel ageing, biofuels, exhaust gasses, resins
content, oxidative stability
1. LITERATURE REVIEW
Quality of stored fuel
Chemical reactions in long-term stored fuel are responsible for sediment accumulation, causing changes in fuel density and performance properties. These changes adversely affect motor vehicles, causing mechanical problems in the powertrain, premature wear of structural components, and changes in the thermodynamics of fuel combustion and the amount of environmentally damaging emissions (Owczuk and Kołodziejczyk 2015). The research carried out as part of the study indicates that fuel stored for a long time adversely changes its properties due to spontaneous ageing processes. In addition, it has been shown that the same fuel, obtained from one manufacturer and stored in one tank, can have different properties within the liquid, depending on whether it comes from the upper or lower fraction of the tank (Hirota and Kashima 2020; Matijošius and Sokolovskij 2009; He et al. 2021; Silva et al. 2021; Vasileiadou, Zoras, and Iordanidis 2021; Correia et al. 2018; Debe 2012; Blaabjerg et al. 2006).
Research conducted worldwide shows
that fuel stored for a long time adversely changes its properties as a result
of spontaneous ageing processes (Jerzy Kawlas 2019). Moreover, it has been shown that
the same fuel, from one manufacturer and stored in one tank, may have different
properties within the liquid, depending on whether it originates from the upper
or lower part of the tank (Fig. 1).
Fig. 1. Sediments
emitted on the walls of the vessel during long-term storage
– in the near-surface fraction (own source)
A detailed analysis of research
results published worldwide allows us to conclude that (Lalramnghaka,
Thanga, and Biaktluanga 2023; Aarhaug et al. 2020; Jerzy Kawlas 2019; Hirota
and Kashima 2020; He et al. 2021; Silva et al. 2021; Vasileiadou, Zoras, and
Iordanidis 2021; Correia et al. 2018):
1. The observed changes in the morphology of liquid fuels correspond to
the ageing changes occurring in these fuels (both in the case of gasoline and diesel
oils analyzed in the literature). It was confirmed that owing to the long-term
storage of fuels, their functional properties deteriorated significantly.
2. Some tested fuels should be withdrawn from the market because of
their insufficient quality for use due to ongoing ageing processes. An example
is the formation of deposits, which, according to the literature, may cause a
decrease in the efficiency of vehicles powered by these fuels, resulting in the
formation of carbon deposits. This phenomenon translates into reduced engine
performance and increased emissions of harmful substances into the atmosphere.
Fuel quality control has become increasingly important owing to the direct
relationship between fuel quality and vehicle emissions (Lalramnghaka, Thanga, and
Biaktluanga 2023). The presented results by Aarhaug,
T. A., Kjos, O. S (2020) show that 29% of the fuel samples
did not meet the quality requirements.
3. Different fuel fractions from the same tank may exhibit different
characteristics, resulting in different operational properties. For example,
diesel oil fractions collected from the bottom of the tank showed significant
progress in the degradation processes compared with the near-surface fractions.
Therefore, it can be concluded that fuel samples taken for laboratory testing
without first mixing the fuel can result in measurement errors and incorrect
decisions. Inadequate quality fuel may be released for use. Similar
observations have been reported by Aarhaug and Kjos. The authors compared the
analysis results between two different laboratories and observed differences in
the analysis results of these fuels, which proves that the method of collecting
samples of new fuels for testing may affect the final results.
4. When testing fuels, such as gasoline, estimating the amount of
deposits formed in the liquid is not sufficient to determine the quality of the
fuel and its service life. Deposits usually form above the liquid surface; in
gasoline, they are unobservable under a light microscope. Additionally,
improper collection of samples for testing may result in incorrect
interpretation of the results obtained.
5. Comparing the test results for gasoline and oil, it can be concluded
that the amount of deposits precipitated in diesel oil is many times higher
than that in gasoline.
The degradation processes of
biofuels often follow a logarithmic law from a certain point in storage, which
indicates a sudden and rapid change in the performance of fuels. Thus, the
tested fuel sample from a given tank may differ significantly from the fuel
used for testing a month later. Given the time involved in the logistics chain,
including taking a sample for testing, sending it for laboratory testing,
laboratory testing time, and making decisions about fuel, it seems appropriate
to look for new methods to assess fuel quality. The technique must be
relatively simple, it should provide a quick qualitative (rather than
quantitative) assessment of the tested fuel, and its results should allow for
immediate decision-making. The authors' research: Lalramnghaka, J., Thanga, et
al. (2023) showed that out of 179 tested
samples of gasoline fuel at gas stations, inappropriate chemical composition
was identified in 103 samples, thus confirming that the results of the majority
of research on gasoline fuel in the study area are adulterated or improperly
conducted.
All scientific studies published
around the world confirm that despite the different mechanisms of deposit
formation in the case of gasoline and diesel oil, the quality of liquid fuels
results from their ageing processes occurring in them.
1.1.
Impact of the fuel used on the
environmental aspects and travel dynamics of the vehicle
The impact of the quality of the
fuel used on the environmental aspects and travel dynamics of the vehicle has
been investigated and proven by many authors, for example, (Heywood 2018; Lack and Corbett
2012; Lewis et al. 2004; Zhang et al. 2007). This issue is also discussed in
the context of a system for controlling and monitoring the quality of motor
fuels and liquid biofuels, along with storage conditions. Al-Arkawazi (2019) indicated a direct impact of
gasoline fuel quality on fuel consumption, air-fuel ratio (AFR), lambda (λ), and some vehicle exhaust gas
emissions, including carbon dioxide (CO2), oxygen (O2),
and nitrogen oxides (NOx). The results also indicated the indirect
impact of gasoline fuel quality on hydrocarbon (CxHy)
vehicle exhaust emissions. In the literature (Sibilieva, Dokshyna, and
Topilnytskyi 2024), it was demonstrated that a fuel
with inadequate thermal oxidative stability, without a suitable content of
compounding agents, causes the formation of coke and exhaust carbon on injector
components. This, in turn, deteriorates the combustible mixture spraying
conditions, which leads to a loss of power and may cause corrosion, seizure of
the injector needle, and even engine failure (von
Wielligh, Burger, and Wilcocks 2003; Dziubak 2016, Jiang, K., et al. 2024;
Jeon, C. H., Park, C. K., Na, B. K., & Kim, J. K. 2017; Stępień, Z. 2015;
Ukhanov, D. A., et al. 2022; Sacha, D. 2020).
At the same time, fuel with a
high canola oil content of 30–70% and FAME (B30, B40, B50, and B70) leads to
coke build-up in sprayers, loss of throughput of sprayer openings, and sprayer
infiltration, which results in higher exhaust emissions. The presence of resins
and the excess of aromatic hydrocarbons and heavier hydrocarbon fractions
results in the excessive formation of sediments and higher temperatures at the
end of distillation, which could cause difficulties in the precise dosage of
fuels in compression-ignition engines, leading to engine operation disruptions
and even damage. Another important issue is the negative impact of biofuels, in
which microbes have developed, on the formation of particulate sediments and
fuel emulsification, which leads to the clogging of fuel filters and lines,
blockage of injectors, lower efficiency, and quicker wear and tear of engines (Dziubak 2016). Nelson et al. (2008) and Ferrão et al. (2011) demonstrated that using inadequate
quality fuels resulted in the quicker wear and tear of vehicle components and
decreased their efficiency, which translated to the increased emission of
harmful substances into the environment during operation and increased the rate
of repairs, failures, and replacements of the components. Wardoyo et al. (2023) examined the fuel stored for
0, 2, and 4 weeks. They showed that, as the storage time increased, the density
and viscosity increased, and the power generated by the engine powered by the
tested gasoline decreased.
The quality of fuel depends not only on the production process and the original chemical composition but also on how and when it is stored. (Tab. 1).
Tab. 1
Impact of the storage process on fuel quality
|
Source |
Test scope |
Conclusions |
Solution |
|
(Jeon et
al. 2017; Kude and Patil 2017; Lack and Corbett 2012; Abramovič and Abram
2005) |
It was demonstrated that the
quality of the fuel in storage is influenced by: ·
the tank material, ·
fuel storage condition (light, temperature, oxygen access). |
Fuel stored in unfavorable
conditions or PET or PE containers may be subject to accelerated
deterioration compared to fuel stored in a steel tank. |
An advantageous solution would be
to use continuous fuel quality monitoring. |
|
(Gaylarde, Bento, and Kelley 1999) |
The increased
microbial growth is due to the use of additives for liquid fuels,
particularly plant oil additives. |
Biofuels may deteriorate more
quickly and require more frequent storage control. |
An advantageous solution is to use
a continuous fuel quality monitoring method. |
|
(Yue et al. 2015; Knothe 1999) |
The
addition of bio-components contributed to accelerated ageing reactions in
stored fuels. |
||
|
(Danek and Pałuchowska 2010) |
The results of the US Army
Research and Development Center confirmed that the induction period standards
for fuel in storage were not sufficient to assess the fuel's tendency to
ageing. This
demonstrates the difference in fuel quality assessment depending on the normalized
assessment method used. |
There is no correlation between
different fuel quality assessment methods; low correlation between the
induction period and the resin content in the fuel. |
An advantageous solution would be
to use a continuous fuel quality monitoring method. |
|
(Jeon et al. 2017) |
These studies involved testing
oils and petrol with varying ester contents. It was demonstrated, among other
things, that the resin content in B7 Diesel oils (methyl ester content up to
7% V/V) and B20 ( Different amounts of insoluble
sediments and variable oxidative stabilities were identified in storage
fuels. Fuels with actinide content were quicker to undergo ageing processes. |
The fuels stored under the same
conditions, which differ in chemical composition (e.g., ester content),
undergo ageing processes over different periods. Fuel
quality may change dramatically after six months of storage. |
An advantageous solution would be
to use a continuous fuel quality monitoring method. |
The performance characteristics of
fuels in long-term storage change owing to reactions occurring within them. The
fuel quality is influenced by the storage tank type (the tank material and the
potential for interaction between the material and fuel; its technical
condition and cleanliness) and the temperature conditions of fuel storage.
However, in the recent decade, due to the intense development of biofuels, the
impact of additives in bio-components on the acceleration of fuel ageing
reactions and microbial growth has been noted. The same fuel, even when
supplied by one manufacturer, may change its properties in a different period,
depending on the transport and storage conditions. As shown by Amaral et al. (2020), a reduction in fuel quality occurs
in the short term, even for fuels with antioxidant additives, especially
biodiesel content, when storage temperature and humidity are high. The authors
demonstrated that biofuels should be used judiciously, particularly in
high-humidity storage conditions, and alternative viable solutions should be envisaged
for such regions. Many other studies (Abramovič and Abram 2005; Danek and
Pałuchowska 2010; Gaylarde, Bento, and Kelley 1999) have unambiguously confirmed that
the performance characteristics of fuels in long-term storage depend on their
stability:
a)
Diesel
oils, depended above all on the oxidative stability or the resistance of the
fuel to oxidation, causing the formation of sediments, cokes, and exhaust
carbon deposition in injector components, which could result in:
·
improper
spraying of the combustible mixture,
·
uneven
engine operation, engine damage,
·
seizure
of injectors, clogging of micro-openings,
·
increasing
air emissions of harmful substances.
In addition, the decomposition of
the fuel with low thermal-oxidative resistance results in the formation of
highly corrosive acids.
b)
For
petrol, they depended mainly on the amount of resins produced, which formed
sediments on engine components and deposits in the combustion chamber, impeding
piston operation and causing uneven engine operation.
Fuel properties also change
depending on the fuel composition and amount of microbes.
In addition, it should be noted that
fuel quality may also change due to fungal or bacterial contamination of
transport grids, production line components, and storage tanks (Premier et al. 2011), and the use of the same transport
tankers for different fuel grades without thorough cleaning. Both the
measurements they performed and presented, and the test results presented in (Danek and Pałuchowska 2010) confirmed that the fuel testing
methods used worldwide may not provide objective and comparable results (e.g.,
no relationship was found between the indications obtained using PN ISO
12205:2011 methods and PN EN 15751:2014-05 methods), as well as complete
information on fuel quality. The above reviews of the literature prove both the
lack of non-ambiguity of the control methods in use and the need to develop a
method to ensure the continuous monitoring of fuels during storage.
In summary, it should be stated
that:
Therefore, a legitimate objective is
to search for a new test method that would enable continuous monitoring of the
ageing processes of stored fuels, allowing us to obtain results in real time
and in a form that will enable their relatively quick analysis to make
decisions regarding the possible withdrawal of fuel from the market or its
reclassification for other uses.
The purpose of this study is to
present the original method of continuous monitoring of fuel ageing processes
using the fuel transmission spectrum and to propose an index for the evaluation
of the fuel ageing degree.
1.2. Other liquid fuel quality
measurement methods
As demonstrated in section 1.1., the
measurement methods do not always reflect the valuable quality of fuels.
Therefore, alternative liquid fuel quality control methods were sought (Tab.
2).
Tab. 2
Alternative liquid fuel quality
control methods
|
Source |
Control method |
Method limitations |
|
(Zhang et al. 2007) |
Test liquid quality assessment for
ongoing ageing processes. |
The method requires laboratory
sampling of fuels, and for safety reasons (danger of ignition), it cannot be
approved for continuous monitoring of fuels in long-term storage. |
|
(Lima et al. 2004) |
Fuel quality assessment was
performed using a pyroelectric detector placed in the test chamber in the
presence of the tested fuel vapors. |
The measurement method cannot be
used to test fuels in long-term storage because the detector interacts with
the fuel, which decreases its performance. |
|
(Mendonça et al. 2007) |
The liquid biofuel assessment
method uses capacitive micro-sensors to measure the electrical capacity of
bioethanol. |
The measurement method requires
sample preparation before filling the tank because the sensor causes
interaction with the fuel: · accelerate fuel ageing processes, · initiates chemical reactions, ·
nickel is a radical source. |
|
(Borecki et al. 2013) |
The method uses an optical fiber
optrode to measure the time of formation and disappearance of the bubbles of
gas heated to high temperatures and the relation between the measured time
and the determined fuel properties. |
The method proposed by the
authors, due to the equipment and the heating of fuel, is not suitable for
use in fuel storage systems. |
|
(Kude
and Patil 2017) |
Fuel ageing measurement method
using the optical fiber probe. |
|
|
(Ferrão
et al. 2011; Knothe 1999) |
Spectrometric methods and optical
fiber techniques, including near- or medium-infrared (MID IR) spectrometers,
are used to determine the fuel quality parameters, such as the ignition
point, density, and sulfur content. |
The apparatus is extensive and
requires laboratory working conditions; therefore, it is impossible or very
difficult to use for fuel quality assessments at storage depots. The proposed
solutions only point in the direction of further research and exploration. |
|
(Khodabakhshikoulaei et al. 2022) |
This study first aims to determine
the physical characteristics of bioethanol from its dielectric properties
during the production process. The findings from this paper suggest that
dielectric spectroscopy is a valuable approach for estimating the physical
features of bioethanol. |
For fuel production only; not
suitable for long-term property monitoring. |
|
(Bojkovic
et al. 2022; J. Xu et al. 2021; Johnson 2017; Qi and Kim 2022) |
Spectrometric methods, such as
UV-visible, FTIR, Raman, NMR, or optical mass and emission spectrometry,
enable quick, accurate, and non-invasive analyses of the chemical composition
of fuels. |
Only for the production process of
fuel, not for monitoring the properties after long storage time. |
|
(Lalramnghaka, Thanga, and Biaktluanga 2023) |
Determination of kerosene and
Methyl tert-butyl Ether (MTBE) concentration in gasoline fuel is done using
partial least squares (PLS) regression multivariate technique as applied to
FTIR-ATR spectral data of the test samples. |
The method required sample
preparation and laboratory. The method does not monitor fuel quality, i.e.,
changes resulting from the fuel ageing process. The method enables measurement of
HC chain length, oxygenate, toluene and aromatic content are the major
variables that cause sample variation and grouping to detect adulterated
fuel. |
|
(Felizardo et al. 2007) |
This work reports that the use of
near infrared (NIR) spectroscopy to determine the content of water and
methanol in industrial and laboratory-scale biodiesel samples in combination
with multivariate calibration, is a promising technique to assess the
biodiesel quality in both laboratory-scale and industrial-scale samples. |
The method required sample
preparation and laboratory tests. |
|
(Squissato et al. 2018) |
Fast and on-site monitoring of the
quality parameters of fuels can be achieved by electrochemical techniques
using disposable sensors, such as screen-printed electrodes (SPEs). The
method gives information about organic and inorganic analyses using
voltammetric or amperometric detection. The SPE technology for quality
control of fuels, based on the reported electrochemical methods may be
considered by regulatory agencies. |
The method is not a continuous
measurement; therefore it does not enable the owners of stored fuel stations
to make appropriate decisions, the decision is made by the controlling body
and involves additional financial burdens for the entrepreneur. |
The publications presented in Tab. 2.
point to the essence of the problem, which is the attempt to assess fuel
quality in long-term storage. They indicate the direction of searching for a
new research method that would enable the assessment of the quality level of
selected fuel performance parameters in a relatively short time. The techniques
developed so far, due to numerous limitations, cannot be used to assess and
continuously monitor the quality of liquid fuels stored on a long-term basis.
Most of the new solutions presented in the world enable a relatively fast
analysis of the composition of fuels, often using advanced technology and
devices to determine this composition at the molecular level. However, such
specialized tests are not needed to assess the quality of liquid fuels as an
element of the decision-making chain for the transport industry. A brief
feedback is expected from the new method – whether the quality of the fuel is
sufficient to introduce it or withdraw it from the market. We are therefore
interested in evaluation in a qualitative rather than a quantitative sense.
They point in directions for
searching for a new test method to enable assessing the quality level of
selected fuel performance parameters in a relatively short time. The priorly
developed methods, due to their numerous limitations, cannot be used for the
assessment and continuous monitoring of the quality of liquid fuels in
long-term storage.
Some fuel problems that can be
addressed through mass spectrometry are associated with the changes in
composition and degradation of fuels as they age. The article includes the
analysis of both significant hydrocarbon components non‐polar components and minor polar components will be described. The
properties and composition of natural and significant classes of synthetic
lubricants, the presence of additives, and the problems that develop as the
lubricant is used such as additive depletion, thermal and oxidative
degradation, and lubricant contamination have been examined using mass
spectrometric techniques. The application of mass spectrometric techniques for
the analysis of the complex mixtures inherent in fuel and lubricant samples
gives good results, but the presented technique requires the preparation of
samples. The article shows that either very high-resolution mass spectrometry
or one of the hyphenated techniques gas chromatography-mass spectrometry
(GC-MS) or liquid chromatography-mass spectrometry (LC-MS) are essential
directions in the research of liquid fuels. Still, in the presented form they
are not suitable for use in the form of continuous monitoring. (Johnson 2017)
In addition, the presented solutions
provide very detailed information on the fuel composition, which is not always
necessary for entrepreneurs at the decision-making stage. Too much information can
only slow down the decision-making process, especially in the case of people
who do not deal with science on a daily, and only the method is supposed to be
an element supporting the fuel management process.
Studies conducted by various authors
indicate a broad application of spectrometry in determining the quality of
liquid fuel. Spectrometric methods, such as UV-visible, FTIR, Raman, NMR, or
optical mass and emission spectrometry, enable quick, accurate, and
non-invasive analyses of the chemical composition of fuels and the detection of
pollutants and undesirable substances (Bojkovic
et al. 2022; Rüger et al. 2021). These studies confirm that
spectrometry is an irreplaceable tool in fuel quality control, which is
essential in the production, distribution, and use of liquid fuels. However, it
should be emphasized that these methods are often used to determine the quality
of fuels during production or the so-called fresh fuels, produced and just
introduced to the market, not distributed fuels and long-term stored in tanks:
gas stations, government reserves, and others. For example, recent research,
including (J. Xu et al. 2021) confirms a systematic review of the
applications of Raman spectroscopy to study the thermochemical processing of
coal, biomass, and waste, and its application to characterize raw materials
such as raw coal, biomass, and waste. Raman spectroscopy is used for ex-situ
characterization of char and ash products after reaction discussion to study
thermochemical processes. The quality of fuels is determined at the production
stage, not the use stage, after long-term storage. Also, in this case, the
quality of fuels is determined at the stage of their production, not use, after
long-term storage (L. Xu et al. 2020;
Khodabakhshikoulaei et al. 2022).
Moreover, the accuracy of the information obtained is too detailed for
fuel management, and the equipment in most cases is not suitable for use in the
form of long-term monitoring (safety reasons, extensive specialized equipment,
etc.). Most commercial gaseous and liquid fuels are mixtures of multiple
chemical compounds, e.g., the variability of gasoline fuel from one refilling
station to another is analyzed using Fourier Transform Infrared spectroscopy
(FTIR) and Principal Component Analysis (PCA). The study Lalramnghaka, et al. (2023) provides an inexpensive and
effective method to investigate gasoline quality, detection of adulterants, and
oxygenators in areas where contaminants of fuel are quite widespread. The
technique is relatively cheap and allows you to detect compounds that should
not be added to the fuel. The method does not monitor fuel quality, i.e.,
changes resulting from the fuel ageing process.
In recent years, these mixtures
became even more complicated when the suppliers started to admix biofuels into
the petrochemical primary fuels. As the properties of such mixtures can vary
with composition, there is a need for reliable analytical technologies to
ensure the stable operation of devices such as internal combustion engines and
gas turbines. Vibrational spectroscopic methods have proved their suitability
for fuel characterization. Moreover, they have the potential to overcome
existing limitations of established technologies because they are fast and
accurate, and they do not require sampling; hence they can be deployed as
inline sensors (Kiefer
2015).
The authors of the study suggest the
use of solutions in gas turbines. They do not present results confirming the
possibility of using the method in containers for long-term storage of liquid
fuels, especially regarding the safety of using the technology.
The rest of the presented test
methods are developed for new fuels. In this respect, they are concerned with
the generation of technology and the possibility of obtaining energy from
so-called renewable sources. The development of renewable fuels from biomass or
waste is an essential subject of research due to the increase in energy
consumption and the need to reduce the environmental problems of the modern
world. At the same time, work is being carried out to improve the efficiency of
crude oil processing to obtain products. A particularly crucial issue is the
conversion or removal of compounds containing a nitrogen or sulfur atom and
materials with highly condensed aromatic structures. Therefore, advanced mass
spectrometry has been employed extensively in the field of energy and fuels to
characterize the chemistry of solid, liquid, or gaseous fuels and products.
Especially an advanced mass spectrometry technique, such as
ultrahigh-resolution mass spectrometry (UHR-MS), has significantly been used to
obtain molecular level details (Qi and Kim 2022).
Advanced mass spectrometry provides
information about the individual chemicals found in fuels.
However, relatively few researchers
and authors of publications consider another emerging problem related to the
storage of new types of fuels and the ageing changes that occur in them. Fuels
with the addition of biocomponents are subject to faster destruction, and the
latest compounds and deposits formed in them have a negative impact on the
elements of machines and devices. The composition of the fuel changes its
properties and its shelf life. Therefore, as shown in the introduction, stored
fuels require constant quality monitoring. A significant, unsolved problem so
far, is the development of a method for continuous monitoring of liquid fuels,
to avoid a complicated research and logistic procedure related to collecting
samples and sending the fuel to a specialized research laboratory.
To sum up, it should be stated
unequivocally that the main limitations of the presented methods are:
However, relatively few researchers
and authors of publications take into account another emerging problem related
to the storage of new types of fuels and the ageing changes taking place in
them. Fuels with the addition of biocomponents are destroyed faster, and the
new compounds and deposits formed in them adversely affect the components of
machinery and equipment. The composition of the fuel changes its properties and
durability. Therefore, as shown in the introduction, stored fuels require
constant quality monitoring. A significant problem that has not yet been solved
is the development of a method for continuous monitoring of liquid fuels to
avoid the complicated research and logistical procedure associated with
sampling and sending the fuel to a specialized research laboratory.
Current methods for fuel quality
testing require sampling and analysis in a properly equipped laboratory. Due to
the long-term costs of storage logistics, it is necessary to implement a new
method that would enable quick information about the current level of stored
fuel. A new method for assessing the quality of liquid fuels should make it possible
to indicate whether the performance of the fuel will be maintained at a level
that ensures continued safe operation, or whether it should be withdrawn from
the market.
Following the identified research
gap, the authors have developed a novel method for continuously monitoring fuel
ageing processes using the fuel transmission spectrum and proposing an
indicator to assess the degree of fuel ageing.
2. DESCRIPTION OF THE NEW METHOD OF CONTINUOUS
MONITORING OF FUEL AGEING PROCESSES
The proposed new method consists of
cyclical observation of changes in the transmission spectrum of the fuel in
storage. The new measurement method uses a special optical fiber probe,
permanently immersed in the fuel tank, to measure the spectrum of the light
passing through the tested fuel at regular time intervals. The spectral
analysis is performed in a device that receives the spectral signals fed by the
optical fiber. Then, the processed signal can be transmitted to any location
through the GSM network, to the central computer collecting signals from
multiple probes. The measurements are performed regularly, unattended. The
automatic analysis of spectrum changes in each tank enables determining if the
ageing processes have already started, which allows a timely response to
optimize the logistics related to long-term fuel storage. The results obtained,
and their analysis constitute the basis for the assessment of the fuel quality
level, in particular in terms of oxidative stability. They indicate if the
subject parameters are approaching or have exceeded the limit value, which
constitutes the basis for deciding on the introduction to the market, use, or
disposal of the fuel. This type of solution has not been used to date.
2.1. Material and test
methods
During long-term storage, the
quickest parameters to exceed the values permitted by standards in specific
fuel groups are the oxidation resistance (Diesel oils) and resin content
(petrol). The current most popular liquid fuels for transport are selected for
testing (Tab. 3).
Specification
of fuels subject to measurements
|
No. |
Description |
Designation of samples |
|
1 |
95-octane
petrol compliant with the requirements of EN 228: 2009: Automotive fuels - Unleaded petrol -
Requirements and test methods, with approx. 4.6% ethyl alcohol and
approx. 4.7% ETBE |
Bl Pb 95 |
|
2 |
98-octane petrol compliant with the requirements of EN 228: 2009: Automotive fuels - Unleaded petrol - Requirements and test methods, with approx. 4.5% ethyl alcohol and approx. 4.9% ETBE |
Bl Pb 98 |
|
3 |
Diesel oil
as per EN 590: 2011: Automotive
fuels - Diesel - Requirements and test methods, with less than 0.50%
fatty acid methyl esters (FAME) content |
ST ON |
|
4 |
Diesel
oil as per EN 590: 2011: Automotive
fuels - Diesel - Requirements and test methods, with approx. 6.6% fatty
acid methyl esters (FAME) content |
ST ON 7 |
Fuel samples were subject to ageing
processes. The ageing process was simulated by the following applicable
standards:
· for petrol, it was following EN ISO 7536: Methods of test for petroleum and its products - Petroleum products - Determination of oxidation stability of gasoline - Induction period method. The induction period test apparatus was used;
·
for
Diesel oils, it was following EN ISO 12205: Petroleum
products. Determination of the oxidation stability of middle-distillate fuels.
The oxidative stability determination apparatus was used.
Tab. 4
Ageing
simulation parameters of selected fuels
|
Fuel ageing simulation/standard |
Parameter |
Value |
|
Petrol EN ISO 7536 |
temperature |
100 ±2°C |
|
oxidizing agent pressure |
690-705 kPa |
|
|
ageing time |
3 h, 6 h, 12 h, 18 h and 24 h |
|
|
sample volume |
100 cm3 |
|
|
Diesel oil EN ISO 12205:2011 |
temperature |
95ºC |
|
oxygen flow |
3
dm3h-1 |
|
|
ageing time |
3 h, 6 h, 18 h, 24 h, 38 h, 48 h, 66 h |
|
|
sample volume |
400 cm3 |
For fuels ageing in presented
conditions and times (Tab. 4), the content of resins in petrol and oxidative
stability in Diesel oils were measured by standards and, at the same time,
transmission spectrum measurements were performed using the newly developed
test method.
The test
station (Fig. 2) consisted of:
1-
The
measurement probe for the VIS-1 range.
2-
The
measurement probe for the UV range.
3-
The
glass test sample container for testing Diesel oils.
4-
The
glass test sample container for testing petrol.
5-
USB
illuminators: UV and VIS.
6-
The
measurement data processing module.
7-
The
computer for storing and analyzing data.
Fig. 2. Laboratory measurement station for petrol and Diesel oil
samples
For Diesel oil transmission spectrum
measurements, the VIS-visible light illuminator was used, and for petrol, the
UV illuminator was used. Since the light is fed to the probes using the optical
fiber, connected using the SMA quick-connector, for protection against
uncontrolled signal changes due to optical fiber switching, two probes were
tested, each with one illuminator installed, not changed during the
measurements. Based on the recorded measurements, the sample ageing index was
determined
as the ratio of the beam intensity at the
moment of
It was concluded that presenting the
plots in the form of a transmission spectrum is advantageous for assessing the
proper operation of the measurement system, however, the conversions into
tagging fuel index are directly connected with quantitative determination of
the physical and chemical phenomena.
3. RESULTS
AND DISCUSSION
3.1. Wavelength selection
The recorded spectral changes were analyzed in selected UV-A spectrum ranges for tested petrol (Fig. 3) and in the VIS range for Diesel oils (Fig. 4). To facilitate the interpretation and comparison of measurement results for different fuels, the normalized intensity was determined as the ratio of the beam intensity value for the given wavelength to the maximum intensity recorded for the given fuel type. For each fuel type, the wavelength was selected, for which the normalized intensity peak was achieved. The wavelength was assumed at 377 nm for petrol and 460 nm for Diesel oils. Significantly different from the other fuels is Diesel oil ON (without biocomponent), for which the normalized intensity does not change with increasing ageing time, and the fuel ageing index is quasi-constant. This means the proposed method cannot be applied to Diesel oils without biocomponents. A similar analysis of the spectrum for 90- and 92-octane gasoline was performed by Wardoyo et al. (2023). They obtained significant differences in transmittance values depending on the storage time (0, 2, 4 weeks) in the range of wave numbers 1200-500 [cm-1].
|
Pb 95: |
Pb 98: |
|
|
|
|
a) |
b) |
|
|
|
|
c) |
d) |
Fig. 3. Test results of aged PB 95 (left column) and Pb 98 (right column) fuel a-b) Change of normalized intensity of aged petrol; c-d) Ageing index (age in) of aged petrol with 377nm wavelength marked by a grey vertical line
3.2. Comparison of results with
the standardized method
The analysis of the test results obtained enables asserting that the age in for the individual types of petrol change with the resin content (values determined under standards, using the classical laboratory measurement method) for the same samples (Tab. 5). The Regulation of the Minister of Economy (Regulation the Minister of Economy of 9 October 2015 on Quality Requirements for Liquid Fuels 2015) allows the resin content < 5 mg/100 ml. It means that the recorded index changes enable an unambiguous determination if the given fuel was subject to ageing processes and even prediction of the ageing time.
The summary of ageing time, resin content in petrol fuel and their corresponding age in results are presented in Table 5.
|
STON7 |
ST ON |
|
|
|
|
a) |
b) |
|
|
|
|
c) |
d) |
Fig. 4. Test results of aged ST ON7 (left column) and ST ON (right column) fuel a-b) Change of normalized intensity of aged Diesel oil; c-d) Ageing index (age in) of aged Diesel Oil with 460nm wavelength marked by grey vertical line
Tab. 5
Summary of resins content and age in
results in petrol
|
|
|
Ageing time [h]: |
|||||
|
Petrol |
Characteristic |
0 |
3 |
6 |
12 |
18 |
24 |
|
Pb 95 |
Resins content [mg/100 ml] |
<1 |
<1 |
<1 |
7.8 |
17.4 |
185 |
|
Age in value |
1 |
1.000015 |
0.9835 |
0.9304 |
0.7603 |
0.7434 |
|
|
Pb 98 |
Resins content [mg/100 ml] |
<1 |
<1 |
<1 |
16.8 |
69.8 |
250 |
|
Age in value |
1 |
0.9645 |
0.9505 |
no data |
0.9185 |
0.9161 |
|
Following table data (Tab. 6, Figs. 5-6), it can be noted that for the wavelength of 377 nm, the age in value drops to below 0.75 for Pb 95 and 0.91 for Pb98. They are the limit values for these fuels. After exceeding the determined limits, abrupt ageing changes begin in the fuel. Longer storage increases the resin content beyond 185 mg/100 ml (for Pb 95) and 250 ml/100 ml (for Pb 98). Using this type of fuel may result in the formation of sediments on the surface of the engine piston, corrosion, and catalyst damage. Using petrol with the age in below 0.8 (for Pb95) and below 0.91 (for Pb 98) will harm the environment. With the age in value of 0.5 or lower, immediately take action to transfer the stored liquid for treatment.
At this stage of research, it can be noted that the method is very sensitive and the maintained measurement continuity indicates that this method is more precise than laboratory testing. An essential advantage of this method is no need for tested fuel processing. Normalized methods for determining the resin content require many hours of sample baking.
A similar analysis was performed on the obtained age in values and their corresponding laboratory-determined, as per ISO12205:2011, oxidative stability for Diesel oil samples.
The transmission spectrum was tested and the
age in was determined for Diesel oil ST ON7 and ST ON (Fig. 3). In the wavelength
range of 450-480 nm, the greatest peak intensity differences between the
individual sample ageing periods can be seen. The test results indicate that
for the wavelength of 460 nm, the spectrum is the most characteristic.
The age in plot analysis for the wavelength of 460 nm shows a decreasing tendency in the recorded peak values that correspond to the fuel ageing times. The obtained oxidative stability values for aged fuel (determined using the laboratory method following the standard) and their corresponding age in values for Diesel oil ST ON7 are shown in Table 6. In the analyzed ageing period, the oil did not exceed the oxidative value parameters. However, the clear peak pitch observed (marked in red on the plot) indicates that the fuel quality starts to drop abruptly. It means that in the test sample of the Diesel oil, chemical structure changes occurred in some components. The change in the physical and chemical fuel properties contributes to the deterioration of its performance characteristics. Such fuel (by traditional, laboratory measurement results) may be introduced to the market because the qualitative parameters determined by the standard have not been exceeded. Nonetheless, the age in value enables estimating that further storage will cause the excess of the oxidative stability value specified in the Regulation of the Minister of Economy (Regulation the Minister of Economy of 9 October 2015 on Quality Requirements for Liquid Fuels 2015) within 5-6 months. This regulation permits the minimum oxidative stability value of 20 h. Following the literature data, using Diesel oil with such a deterioration degree generally leads to gradual damage to the technical condition of the engine.
Therefore, it may be concluded that the assessed fuel should not be in long-term storage because the occurring and recorded ageing changes indicate unambiguously the loss of the capability of fuel to serve its purposes in the estimated time of 5-6 months, based on the results obtained.
Tab. 6
Summary of oxidation stability
results as per EN 15751:2014-05
and age in for ST ON and ST ON7
|
Fuel: |
Ageing time [h] |
||||||||
|
0 |
3 |
6 |
18 |
24 |
38 |
48 |
66 |
||
|
ST ON 7 |
Oxidative stability [h] |
43.3 |
42.4 |
40.1 |
36.3 |
37.2 |
33.1 |
31.3 |
26.2 |
|
Age in value for 460 nm |
1 |
1.001 |
1.010 |
1.012 |
1.031 |
1.069 |
1.049 |
1.133 |
|
|
ST ON |
Oxidative stability [gmm] |
5 |
10 |
8 |
15 |
14 |
29 |
60 |
150 |
|
Age in value for 460 nm |
1 |
0.999 |
1.004 |
1.002 |
1.000 |
1.000 |
0.989 |
0.993 |
|
The results of the comparative measurements performed for ST ON indicate that this fuel shows higher oxidative stability (Fig. 3d) than ST ON 7, caused by the low content of unstable bio-components (content smaller than 0.5%). The approved ageing level assessment method is not suitable for ST ON. Based on the analysis of the test results for all fuel grades (petrol and oils), the method is susceptible and precise for fuels with bio-component content. For these fuels, mathematical relationships were checked between the age in indications and the results of the normalized laboratory tests of aged fuels.
3.3. Unifying transformations
To assess the relationship between the assessment of aged fuel quality measured using the two described methods (the newly developed non-laboratory measurement method and the standardized method), non-linear regression analysis was used. The relationship was noticed between the oxidative stability of Diesel oil and age in, however not a linear relationship – Fig. 4.
The response of age in indications to fuel quality deterioration is stronger than that of oxidative stability testing. Therefore, it may be concluded that the newly developed measurement method is more precise for the aged fuels, of which the stability is determined as low. Analogical strong relationships were found between the laboratory test results and the indications of the new method for aged Pb98 and Pb95 petrol (Fig. 4).
To explain the relationships between
the deterioration of liquid fuel (oil or petrol) in long-term storage and
changes in the observed spectroscope spectrum, a quantitative assessment of the
correctness of using the newly developed measurement method was completed.
Determined using the least-square method, the relationship between the
oxidative stability values for Diesel oil ST ON7 and resins content for PB95
and PB98 petrol and the age in. Due to the small number of measurements, and
statistically significant differences between the measured values and the age
in model-derived values, the Wilcoxon non-parameter pair test was used. This is
the test used to compare the measurement of the same objects in various
conditions or with different methods. The compared variable values must be at
least in the order area. The data analyzed meets these assumptions. For testing
purposes, the null hypothesis
|
(a) |
|
|
(b) |
(c) |
Fig.
4. Relationship
between the age in value and: the oxidative stability of the Diesel oil (a),
resins content in aged Pb95 (b) and Pb98 (c) with regression line presented in
Tab.8 and 95% confidence interval (grey stripe).
The Wilcoxon pair sequence test
results to assess the conformity between the quality assessment results of fuel
subject to deterioration caused by long-term storage, measured using the
oxidation (
|
|
Function equation |
Z |
p-value |
|
PB98 |
|
0,52 |
0,60 |
|
PB95 |
|
0,40 |
0,69 |
|
ON7 |
|
0,14 |
0,89 |
4. CONCLUSIONS
The newly
developed liquid fuel quality measurement method enables the continuous
monitoring of the fuel in storage. It does not require collecting samples for
testing and sending them to specialized test laboratories, which significantly
accelerates the decision-making process related to the approval of the fuel for
marketing. Based on the presented statistical analysis, it may be asserted that
the proposed wave method of monitoring the quality measurement of the fuel
deteriorating due to the occurring ageing processes is identical to the
traditional normalized oxidative method. The index changes measured using the
wave method (using optical spectroscopy) indicate, in a significant and
measurable manner, qualitative changes in the fuel. Therefore, it may be
concluded that the newly developed wave method efficiently indicates the fuel
quality status.
The fuel
tests show that each of them is characterized by different changes in the age
in value over time. Therefore, determining the appropriate index levels for the
given fuel, beyond which the fuel has undergone ageing processes, is important
to the discussed method. In the article, ageing fuel index levels were
determined for the selected petrol and Diesel oils:
·
the
age in value for the sample of Pb95 and Pb98 petrol can be the basis for
conclusions on the marketing of the fuel in long-term storage or taking action
to transfer the liquid in storage to the refinery.
·
the
age in value for the Diesel oil sample with up to 7% bio-components content, ST
ON7, enables determining the estimated fuel ageing time, which is the basis for
conclusions on its suitability for vehicle use.
During the
tests, it was concluded that there is a correlation between the obtained age in
values and the liquid fuel ageing time. For the given fuel type, an age in
value corresponding to the abrupt increase in the resin content in petrol or
excess oxidative stability in Diesel oil can be determined. Knowing the index
value corresponding to the aged fuel that is non-compliant with the
requirements, one may unambiguously assess the suitability of the fuel for
further operation. When the index value is higher, the fuel is suitable for
operation, when it is lower, it may fail to meet the qualitative requirements.
For
the Diesel oil ST ON with less than 0.5% bio-components content, the
spectrometric method was found to be ineffective. Therefore, the newly
developed method is applicable wherever bio-components are used. It may be
assumed that the method will enable the assessment of other liquid fuels with
bio-component content, as well as the newly marketed biofuels. The method also enables quick decision-making
on the recall of inadequate quality fuels from the market. The developed method
has significant application potential, currently, the method has been
successfully implemented at the position of the Industrial Automotive Institute
at a small volume storage station in Poland.
Acknowledgement
The
paper is a part of the UIDB/00151/2020, The AeroMaS - Aerospace Materials and
Structures Group of the CMAST - Centre for Mechanical and Aerospace Science and
Technologies
References
1.
Aarhaug Thor A., Ole S. Kjos, Alain Ferber, Jong Pyong
Hsu, Thomas Bacquart. 2020. “Mapping of Hydrogen Fuel Quality in Europe.” Frontiers
in Energy Research 8 (November). DOI:
https://doi.org/10.3389/fenrg.2020.585334.
2.
Abramovič
Helena, Veronika Abram. 2005. “Physico-Chemical Properties, Composition and
Oxidative Stability of Camelina Sativa Oil.” Food Technology and
Biotechnology 43(1): 63-70.
3.
Amaral Bruna Elói do, Daniel Bastos de Rezende, Vânya
Márcia Duarte Pasa. 2020. “Aging
and Stability Evaluation of Diesel/ Biodiesel Blends Stored in Amber
Polyethylene Bottles under Different Humidity Conditions.” Fuel 279
(November): 118289. DOI: https://doi.org/10.1016/j.fuel.2020.118289.
4.
Blaabjerg
F., R. Teodorescu, M. Liserre, A.V. Timbus. 2006. “Overview of Control and Grid
Synchronization for Distributed Power Generation Systems.” IEEE Transactions
on Industrial Electronics 53(5): 1398-1409. DOI: https://doi.org/10.1109/TIE.2006.881997.
5.
Bojkovic,
Aleksandar, Florence H. Vermeire, Maja Kuzmanović, Hang Dao Thi, and Kevin M.
Van Geem. 2022. “Analytics Driving Kinetics: Advanced Mass Spectrometric
Characterization of Petroleum Products.” Energy & Fuels 36 (1): 6-59. DOI: https://doi.org/10.1021/acs.energyfuels.1c02355.
6.
Borecki
Michał, Piotr Doroz, Jan Szmidt, Michael L. Korwin-Pawłowski, Andrzej Kociubiński, and Mariusz Duk. 2013. “Sensing Method and
Fiber Optic Capillary Sensor for Testing the Quality of Biodiesel Fuel.” The
Fourth International Conference on Sensor Device Technologies and Applications: 19-24.
Barcelona.
7.
Correia
Radigya M., Eloilson Domingos, Vagne M. Cáo, Brenda R.F. Araujo, Sthefany Sena, Layla U. Pinheiro, André M. Fontes, et al. 2018.
“Portable near Infrared Spectroscopy Applied to Fuel Quality Control.” Talanta
176 (January): 26-33. DOI: https://doi.org/10.1016/j.talanta.2017.07.094.
8.
Danek B., M.
Pałuchowska. 2010. “Zmiany stabilności chemicznej benzyny silnikowej
zawierającej do 10% (V/V) bioetanolu, podczas jej przechowywania w warunkach
laboratoryjnych.” Nafta-Gaz 66(4): 297-301. [In Polish: “Changes in the chemical
stability of motor gasoline containing up to 10% (V/V) of bioethanol during its
storage under laboratory conditions. ”]. Available at: https://pbn.nauka.gov.pl/core/#/publication/view/60e730582467f01e9315448e/b79e0350-69fb-4b34-9ede-5b09f6aae2ac.
9.
Debe Mark
K. 2012. “Electrocatalyst Approaches and Challenges for Automotive Fuel Cells.”
Nature 486(7401): 43-51. DOI: https://doi.org/10.1038/nature11115.
10.
Dziubak
Tadeusz. 2016. “Operating Fluids Contaminantions and Their Effect on the Wear
of Elements of Motor Vehicle`s Combustion Engine.” The Archives of
Automotive Engineering – Archiwum Motoryzacji 72(2). DOI: https://doi.org/10.14669/AM.VOL72.ART3.
11.
Felizardo Pedro, Patrícia Baptista, Margarida Sousa Uva,
José C. Menezes, M. Joana Neiva Correia. 2007.
“Monitoring Biodiesel Fuel Quality by near Infrared Spectroscopy.” Journal
of Near Infrared Spectroscopy 15(2): 97-105. DOI: https://doi.org/10.1255/jnirs.714.
12.
Ferrão Marco Flôres, Mariela de Souza Viera, Rubén
Edgardo Panta Pazos, Daniela Fachini, Annelise Engel Gerbase, and Luciano
Marder. 2011. “Simultaneous Determination of Quality
Parameters of Biodiesel/Diesel Blends Using HATR-FTIR Spectra and PLS, IPLS or
SiPLS Regressions.” Fuel 90(2): 701-6. DOI:
https://doi.org/10.1016/j.fuel.2010.09.016.
13.
Flamarz Al-Arkawazi, Shamil Ahmed. 2019. “The Gasoline Fuel Quality Impact on Fuel
Consumption, Air-Fuel Ratio (AFR), Lambda (λ) and Exhaust Emissions of
Gasoline-Fueled Vehicles.” Edited by Claudio Cameselle. Cogent Engineering
6(1). DOI: https://doi.org/10.1080/23311916.2019.1616866.
14.
Gaylarde
Christine C., Fátima M. Bento, and Joan Kelley. 1999. “Microbial Contamination
of Stored Hydrocarbon Fuels and Its Control.” Revista de Microbiologia
30(1): 01-10. DOI: https://doi.org/10.1590/S0001-37141999000100001.
15.
He Jian,
Qian Qiang, Shima Liu, Ke Song, Xianwu Zhou, Jie Guo, Bo Zhang, Changzhi Li.
2021. “Upgrading of Biomass-Derived Furanic Compounds into High-Quality Fuels
Involving Aldol Condensation Strategy.” Fuel 306 (December): 121765. DOI:
https://doi.org/10.1016/j.fuel.2021.121765.
16.
Heywood
John B. 2018. Internal Combustion Engine Fundamentals. 2nd ed. Available at: https://www.accessengineeringlibrary.com/content/book/9781260116106.
17.
Hirota
Keiko, and Shigeru Kashima. 2020. “How Are Automobile Fuel Quality Standards
Guaranteed? Evidence from Indonesia, Malaysia and Vietnam.” Transportation
Research Interdisciplinary Perspectives 4 (March): 100089. DOI:
https://doi.org/10.1016/j.trip.2019.100089.
18.
Jeon
Cheol Hwan, Cheon Kyu Park, Byung Ki Na, and Jae Kon Kim. 2017. “Properties of
Gasoline Stored in Various Containers.” Energies 10(9). DOI:
https://doi.org/10.3390/en10091307.
19.
Jerzy
Kawlas. 2019. “Evaluation of Ageing of Motor Fuel on Their Useful Properties.” Katowice. Available
at: https://delibra.bg.polsl.pl/dlibra/show-content/publication/edition/58892?ID=58892.
20.
Johnson
David W. 2017. “Applications of Mass Spectrometric Techniques to the Analysis
of Fuels and Lubricants.” In Mass Spectrometry. InTech. DOI:
https://doi.org/10.5772/intechopen.68592.
21.
Khodabakhshikoulaei
Azar, Hassan Sadrnia, Mohammad Tabasizadeh, Barat Ghobadian, and Vijaya
Raghavan. 2022. “Bioethanol Fuel Quality Assessment Using Dielectric
Spectroscopy.” Biofuels 13(6): 693-701. DOI: https://doi.org/10.1080/17597269.2021.1894002.
22.
Kiefer
Johannes. 2015. “Recent Advances in the Characterization of Gaseous and Liquid
Fuels by Vibrational Spectroscopy.” Energies 8(4): 3165-97. DOI: https://doi.org/10.3390/en8043165.
23.
Knothe
Gerhard. 1999. “Rapid Monitoring of Transesterification and Assessing Biodiesel
Fuel Quality by Near‐infrared
Spectroscopy Using a Fiber‐optic
Probe.” Journal of the American Oil Chemists’ Society 76(7): 795-800. DOI: https://doi.org/10.1007/s11746-999-0068-5.
24.
Kude
Vivek, Anita Patil. 2017. “Detection of Fuel Adulteration in Real Time Using
Optical Fiber Sensor and Peripheral Interface Controller.” International
Journal of Optics and Photonics 11(2): 95-102. DOI: https://doi.org/10.18869/acadpub.ijop.11.2.95.
25.
Lack
D.A., J.J. Corbett. 2012. “Black Carbon from Ships: A Review of the Effects of
Ship Speed, Fuel Quality and Exhaust Gas Scrubbing.” Atmospheric Chemistry
and Physics 12(9): 3985-4000. DOI: https://doi.org/10.5194/acp-12-3985-2012.
26.
Lalramnghaka
J., H.H. Thanga, and Lal Biaktluanga. 2023. “Evaluation of Gasoline Fuel
Quality Using FTIR Spectroscopy and Multivariate Technique: A Case Study in
Aizawl City.” Petroleum Science and Technology 41(6): 677-99. DOI: https://doi.org/10.1080/10916466.2022.2091596.
27.
Lewis
B.J., W.T. Thompson, F. Akbari, D.M. Thompson, C. Thurgood, J. Higgs. 2004.
“Thermodynamic and Kinetic Modelling of Fuel Oxidation Behaviour in Operating
Defective Fuel.” Journal of Nuclear Materials 328(2-3): 180-96. DOI:
https://doi.org/10.1016/j.jnucmat.2004.04.336.
28.
Lima
J.A.P., M.S.O. Massunaga, H. Vargas, L.C.M. Miranda. 2004. “Photothermal
Detection of Adulterants in Automotive Fuels.” Analytical Chemistry 76(1):
114-19. DOI: https://doi.org/10.1021/ac034306a.
29.
Matijošius
Jonas, Edgar Sokolovskij. 2009. “Research into the quality of fuels and their
biocomponents.” Transport 24 (3): 212-17. DOI:
https://doi.org/10.3846/1648-4142.2009.24.212-217.
30.
Mendonça
Lucas Gonçalves Dias, Delson Torikai, Ricardo Cury Ibrahim, Eliphas Wagner
Simões, Nilton Itiro Morimoto. 2007. “Interdigitated Capacitive Sensor
to Verify the Quality of Ethanol Automotive Fuel.” In International Congress
of Mechanical Engineering.
31.
Nelson
Peter F., Anne R. Tibbett, Stuart J. Day. 2008. “Effects of Vehicle Type and
Fuel Quality on Real World Toxic Emissions from Diesel Vehicles.” Atmospheric
Environment 42(21): 5291-5303. DOI: https://doi.org/10.1016/j.atmosenv.2008.02.049.
32.
Owczuk Marlena, and
Krzysztof Kołodziejczyk. 2015.
“Liquid Fuel Ageing Processes in Long-Term Storage Conditions.” In Storage
Stability of Fuels. InTech. DOI: https://doi.org/10.5772/59799.
33.
Premier
Giuliano C., Jung Rae Kim, Iain Michie, Richard M. Dinsdale, Alan J. Guwy.
2011. “Automatic Control of Load Increases Power and Efficiency in a Microbial
Fuel Cell.” Journal of Power Sources 196(4): 2013-19. DOI: https://doi.org/10.1016/j.jpowsour.2010.09.071.
34.
Qi Fei,
and Sunghwan Kim. 2022. “Virtual Special Issue of Recent Advances in Analysis
of Fuels and Products by Advanced Mass Spectrometry.” Energy & Fuels
36(3): 1151-54. DOI: https://doi.org/10.1021/acs.energyfuels.2c00147.
35.
Regulation
the Minister of Economy of 9 October 2015 on Quality Requirements for Liquid
Fuels. 2015. Poland.
36.
Rüger Christopher P., Ole Tiemann, Anika Neumann, Thorsten
Streibel, Ralf Zimmermann. 2021.
“Review on Evolved Gas Analysis Mass Spectrometry with Soft Photoionization for
the Chemical Description of Petroleum, Petroleum-Derived Materials, and
Alternative Feedstocks.” Energy & Fuels 35(22): 18308-32. DOI: https://doi.org/10.1021/acs.energyfuels.1c02720.
37.
Sibilieva Olena, Sofiia Dokshyna, and Petro Topilnytskyi.
2024. “International Requirements and Modern
State in Sphere of Motor Fuels Quality Control: Basic Principles of Monitoring
and Control.” In Boichenko S., A. Zaporozhets, A. Yakovlieva, I. Shkilniuk
(eds). Modern Technologies in Energy and
Transport. Studies in Systems, Decision and Control 510: 249-72.
Springer, Cham. DOI: https://doi.org/10.1007/978-3-031-44351-0_13.
38.
Silva Jilliano B., Josue S. Almeida, Rodrigo V. Barbosa,
Glauber J. T. Fernandes, Ana C. F. Coriolano, Valter J. Fernandes, Antonio S.
Araujo. 2021. “Thermal Oxidative Stability of
Biodiesel/Petrodiesel Blends by Pressurized Differential Scanning Calorimetry
and Its Calculated Cetane Index.” Processes 9(1): 174. DOI:
https://doi.org/10.3390/pr9010174.
39.
Squissato André L., Eduardo S. Almeida, Sidnei G. Silva,
Eduardo M. Richter, Alex D. Batista, Rodrigo A.A. Munoz. 2018. “Screen-Printed Electrodes for Quality Control of
Liquid (Bio)Fuels.” TrAC Trends in Analytical Chemistry 108 (November):
210-20. DOI: https://doi.org/10.1016/j.trac.2018.08.024.
40.
Vasileiadou
Agapi, Stamatis Zoras, and Andreas Iordanidis. 2021. “Fuel Quality Index and
Fuel Quality Label: Two Versatile Tools for the Objective Evaluation of
Biomass/Wastes with Application in Sustainable Energy Practices.” Environmental
Technology & Innovation 23 (August): 101739. DOI: https://doi.org/10.1016/j.eti.2021.101739.
41.
Wardoyo D.,
A. Wulandari, Rahmat Firdaus, Eko Arif Syaefudin. 2023. “Effect of Storage Time
of Boosted Pertalite Fuel on Its Physical Properties to Improve Performance on
a Single Cylinder 108.2 Cc Petrol Engine.” Evergreen 10(3): 1991-96. DOI: https://doi.org/10.5109/7151763.
42.
Wielligh
A.J., N.D.L. Burger, T.L. Wilcocks. 2003. “Diesel Engine Failures Due to
Combustion Disturbances, Caused by Fuel with Insufficient Lubricity.” Industrial
Lubrication and Tribology 55(2): 65-75. DOI:
https://doi.org/10.1108/00368790310470895.
43.
Xu Jun,
Qichen He, Zhe Xiong, Yun Yu, Shu Zhang, Xun Hu, Long Jiang, et al. 2021.
“Raman Spectroscopy as a Versatile Tool for Investigating Thermochemical
Processing of Coal, Biomass, and Wastes: Recent Advances and Future
Perspectives.” Energy & Fuels 35(4): 2870-2913. DOI: https://doi.org/10.1021/acs.energyfuels.0c03298.
44.
Xu
Lujiang, Shijia Chen, He Song, Yang Liu, Chenchen Shi, and Qiang Lu. 2020.
“Comprehensively Utilization of Spent Bleaching Clay for Producing High Quality
Bio-Fuel via Fast Pyrolysis Process.” Energy 190 (January): 116371. DOI:
https://doi.org/10.1016/j.energy.2019.116371.
45.
Yue Xin,
Ye Wu, Jiming Hao, Yuan Pang, Yao Ma, Yi Li, Boshi Li, Xiaofeng Bao. 2015.
“Fuel Quality Management versus Vehicle Emission Control in China, Status Quo
and Future Perspectives.” Energy Policy 79 (April): 87-98. DOI: https://doi.org/10.1016/j.enpol.2015.01.009.
46.
Zhang
Xinge, Mark Robertson, Cyrille Deĉes-Petit, Wei Qu, Olivera Kesler,
Radenka Maric, and Dave Ghosh. 2007. “Internal Shorting and Fuel Loss of a Low
Temperature Solid Oxide Fuel Cell with SDC Electrolyte.” Journal of Power
Sources 164(2): 668-77. DOI: https://doi.org/10.1016/j.jpowsour.2006.10.087.
Received 02.06.2024; accepted in revised form 09.10.2024
Scientific
Journal of Silesian University of Technology. Series Transport is licensed
under a Creative Commons Attribution 4.0 International License
[1] Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland. Email: bozena.szczucka-lasota@polsl.pl. ORCID: 0000-0003-3312-1864