Search Results (47)

In recent years, carbon dioxide (CO₂) emissions have increased at the fastest rates ever recorded. This is a trend that contradicts global efforts to stabilise greenhouse gas (GHG) concentrations and prevent long-term climate change. Over 90% of global transport relies on oil-based fuels. The continued use of diesel and petrol raises concerns related to oil costs, supply security, GHG emissions, and the release of air pollutants and volatile organic compounds. This study explored electric vehicle (EV) charging networks by assessing environmental impacts through GHG and petroleum savings, developing dynamic pricing strategies, and forecasting infrastructure needs. A substantial dataset of over 259,000 EV charging records from Palo Alto, California, was statistically analysed. Machine learning models were applied to generate insights that support sustainable and economically viable electric transport planning for policymakers, urban planners, and other stakeholders. Findings indicate that GHG and gasoline savings are directly proportional to energy consumed, with conversion rates of 0.42 kg CO₂ and 0.125 gallons per kilowatt-hour (kWh), respectively. Additionally, dynamic pricing strategies such as a 20% discount on underutilised days and a 15% surcharge during peak hours are proposed to optimise charging behaviour and improve station efficiency. Full article

Biofuels, such as ethanol (CH₃CH₂OH), remain significantly underutilized globally despite their potential to mitigate environmental effects associated with fossil fuel combustion. Ethanol (ETH) can seamlessly blend with petroleum-derived gasoline, boosting its octane rating as a virtuous side effect. However, in several countries, octane number (ON) boosters such as methyl-tert-butyl-ether (MTBE) are still blended into the gasoline (also known as gas or petrol) sold in fuel stations, despite this being restricted or banned due to deleterious effects on the environment and health. Additionally, in nations overproducing naphtha from refining petroleum condensates, such as in the Middle East, investments in extra carbon chain rearrangement units can be an outlet to enhance gasoline production, since they produce high-ON streams; however, aromatic concentration becomes a limiting constraint. A discrete-event simulation algorithm combines sixteen main (primary) manufacturing variations into two secondary manufacturing and three supply chain variations, building gasoline yield and property plots over 512 gasoline production scenarios. Full article

Saudi Arabia’s rapid urbanization and economic growth have increased the number of petrol stations crucial to national infrastructure. Despite oversight from seven local authorities, many stations fail to meet Ministry of Municipal and Rural Affairs (MMRA) standards due to decentralized management. This study develops a Condition Rating Index (CRI) for petrol stations, designed to serve as the backbone of a comprehensive decision support system for the operation and rehabilitation processes of petrol stations in Saudi Arabia. It is based on dividing petrol stations into four key areas: refueling tanks, pump stations, car service buildings, and commercial spaces. Performance factors for each area are identified and categorized hierarchically into main and sub-factors. The Analytical Hierarchy Process (AHP) is used to determine relative importance weights for these factors, while Multi-Attribute Utility Theory (MAUT) is used to assign utility scores (1–10 scale) reflecting performance levels, where 1 is poor, and 10 is optimal. The overall CRI for each petrol station is calculated by aggregating the scores of all four spaces, combining their relative importance weights with the specific CRI scores aligned with each factor’s utility level. These space-specific CRI scores reveal particular performance levels and rehabilitation needs for each area. The developed CRI functions as a transparent, integrated tool for effectively communicating performance levels and rehabilitation needs among all stakeholders. It serves as an effective decision support tool for prioritizing rehabilitation interventions based on performance levels and budget constraints, offering a comprehensive approach for enhancing petrol station management across Saudi Arabia. This paper develops a transparent and adaptable Condition Rating Index (CRI) that bridges gaps in petrol station management and aligns with sustainability goals. Full article

Lead isotope ratios vary depending on the origin of the lead, meaning that characteristic isotopic signatures can be used for source identification in environmental samples. Lead in ambient particulate matter was collected and analysed at 23 monitoring stations as part of the UK heavy metals air quality monitoring network to assess compliance with legislative limit values for allowable concentrations of lead in air. For the first time on a nationwide UK basis, isotopic analysis of lead was carried out on these samples to gain further information about the origin of the lead and the sources influencing measured concentrations at each of the monitoring stations. These measurements were undertaken with the novel application of ICP–MS/MS for high throughput analysis of over 200 samples from 23 sites across the UK. Values for 207Pb/206Pb ranged from 0.864 to 0.910 with an average standard error of 0.68%, while 208Pb/206Pb values ranged from 2.08 to 2.187 with an average standard error of 0.84%. The dataset was used to draw conclusions as to the main sources of pollution contributing to each site and has demonstrated the utility of ICP–MS/MS as a fit-for-purpose analytical method for the high throughput of a large number of samples in complex matrices. It was possible to identify different source types at the monitoring stations based on the lead isotope signature observed. Comparison with literature values showed clear links with traffic emissions at roadside sites and leaded petrol at a site near an airfield where small aircraft still use this type of fuel. Full article

Transitioning from petrol or gas vehicles to electric vehicles (EVs) poses significant challenges in reducing emissions, lowering operational costs, and improving energy storage. Wireless charging EVs offer promising solutions to wired charging limitations such as restricted travel range and lengthy charging times. This paper presents a comprehensive approach to address the challenges of wireless power transfer (WPT) for EVs by optimizing coupling frequency and coil design to enhance efficiency while minimizing electromagnetic interference (EMI) and heat generation. A novel coil design and adaptive hardware are proposed to improve power transfer efficiency (PTE) by defining the optimal magnetic resonant coupling WPT and mitigating coil misalignment, which is considered a significant barrier to the widespread adoption of WPT for EVs. A new methodology for designing and arranging roadside lanes and facilities for dynamic wireless charging (DWC) of EVs is introduced. This includes the optimization of transmitter coils (TCs), receiving coils (RCs), compensation circuits, and high-frequency inverters/converters using the partial differential equation toolbox (pdetool). The integration of wireless charging systems with smart grid technology is explored to enhance energy distribution and reduce peak load issues. The paper proposes a DWC system with multiple segmented transmitters integrated with adaptive renewable photovoltaic (PV) units and a battery system using the utility main grid as a backup. The design process includes the determination of the required PV array capacity, station battery sizing, and inverters/converters to ensure maximum power point tracking (MPPT). To validate the proposed system, it was tested in two scenarios: charging a single EV at different speeds and simultaneously charging two EVs over a 1 km stretch with a 50 kW system, achieving a total range of 500 km. Experimental validation was performed through real-time simulation and hardware tests using an OPAL-RT platform, demonstrating a power transfer efficiency of 90.7%, thus confirming the scalability and feasibility of the system for future EV infrastructure. Full article

The expansion of impervious areas in the context of climate change leads to an increase in stormwater runoff. Runoff from roads, petrol stations, and service stations is the most common form of unintentional release of petroleum hydrocarbons (PHs). Rain gardens are an important practice for removing PHs from stormwater runoff, but little data exist on the removal efficiency and behaviour of these substances within the system. The main objective of the study is to investigate the effectiveness of rain gardens in removing pollutants such as diesel fuel (DF) and used engine oil (UEO) in a laboratory setting, as well as to study the behaviours of these pollutants within the system. Eight experimental columns (7.164 dm³) were packed with soil (bulk density 1.48 kg/dm³), river sand (1.6 kg/dm³), and gravel. Plants of the Physocarpus opulifolia Diabolo species were planted in the topsoil to study their resistance to PHs. For 6 months, the columns were watered with model PHs followed by simulated rain events. The concentrations of PHs in the leachate and soil media of the columns were determined by reverse-phase high-performance liquid chromatography (RP-HPLC). The results of HPLC indicated the absence of UEO and DF components in the leachates of all experimental columns, which suggested 100% removal of these substances from stormwater. The chromatography results showed that 95% of the modelled PHs were retained in the surface layer of the soil medium due to the sorption process, which led to a change in hydraulic conductivity over time. Recommendations are proposed to increase the service life of rain gardens designed to filter PHs from stormwater. Full article

The application of sustainability practices has become one of the key drivers to gaining a favorable stand in the market. However, petroleum companies are hesitant with its implementation due to the perceived negative financial impact. This study was conducted to determine the purchase intentions of consumers from petroleum stations implementing sustainability practices by utilizing the pro-environmental planned behavior (PEPB) framework. The research utilized an online questionnaire with 400 respondents who have been a petrol station customer. The data were examined with a higher-order construct using partial least squares structural equation modelling (PLS-SEM). The findings showed a positive relationship between variables and revealed that economic concern, subjective norms, perceived behavioral control, economic factors, and sustainable knowledge significantly influenced customers’ intention to purchase goods and services from a petrol station adopting sustainability practices, while attitude was found to have no direct significant impact on customers’ intention. The results of this study adds value to the potential increase in PEPB understanding and consumer behavior and may be beneficial for petroleum companies as the basis for managerial decisions regarding the implementation of sustainability practices or initiatives towards adopting the concept of “green stations” and consumer preferences to attract purchase intentions. Full article

Planning petrol station replenishment is an important logistics activity for all the major oil companies. The studied Multi-Depot Periodic Petrol Station Replenishment problem derives from a real case in which the company must replenish a set of petrol stations from a set of depots, during a weekly planning horizon. The company must ensure refuelling according to available visiting patterns, which can be different from customer to customer. A visiting pattern predefines how many times (days) the replenishment occurs during a week and in which visiting days a certain amount of fuel must be delivered. To fulfill the weekly demand of each petrol station, one of the available replenishment plans must be selected among a given set of visiting patterns. The aim is to minimize the total distance travelled by the fleet of tank trucks during the entire planning horizon. A matheuristic approach is proposed, based on the cluster-first route-second paradigm, to solve it. The proposed approach is thoroughly tested on a set of realistic random instances. Finally, a weekly large real instance is considered with 194 petrol stations and two depots. Full article

Recently, the main aim of the road freight transportation sector has been the establishment of a cost-effective and sustainable operation because it is one of the most environmentally damaging and most expensive elements of the supply chains’ activities. The efficiency improvement and optimization of these transport activities can result in significant cost savings, which lead to increased competitiveness of the transport companies. Two new methods were elaborated for the optimization of road freight transport activities; therefore, this research is very innovative and up to date. The elaborated methods are as follows: (1) A new calculation method for the precise prime cost pre-calculation of transport tasks in order to determine an accurate transport fee, thus ensuring the company’s profit; furthermore, the losses can be eliminated in order to provide competitiveness to the transport company. (2) A new optimization method for the refueling procedure of international transport trips in order to minimize the total fuel cost of the transport trips taking into consideration the different unit fuel prices at the different stations. Therefore, the elaborated optimization method on the one hand helps in selecting the optimal petrol station and, on the other hand, defines the optimal amount of fuel to be refueled. Based on the newly developed methods, two decision-supporting software applications were developed to establish more profitable and sustainable transportation. The added value of the developed calculation methods and software applications is that, recently, both the prime cost calculation and the fuel supply optimization have not been supported by software. This is the reason the two developed methods and two software applications are innovative and unique. The newly developed software applications were successfully implemented at transport companies. The correctness of both elaborated mathematical methods was validated using the developed software in real case studies. Full article

Due to global environmental impacts, the electric vehicle (EV) adoption rate is increasing. However, unlike conventional petrol vehicles, EVs take a considerable time to charge. EVs on the road with different battery charging statuses and driving demographics may cause uncertain peak time arrivals at charging stations. Battery-swappable charging stations are a quick and easier way to replace uncharged batteries with charged ones. However, charging due to uncertain EV arrival causes higher charging profiles posing load to the grid, management of charged and discharged batteries, and peak time charging tariffs. These challenges hinder the wide operation of battery-swappable charging stations. Nevertheless, a pre-assessment of peak hours using EV demographics can reduce congestion. In recent literature surveys for battery-swappable charging stations, spot congestion has not been given much attention, which has a direct influence on the sizing and operation of battery-swappable charging stations. This research study is focused on estimating peak time events using a novel integrated techno-economic assessment framework. A fuzzy-based parametric assessment tool is developed that identifies the factors that influence higher congestion events. Based on the peak event assessment, grid, and solar PV-based generation is optimized using mixed integer linear programming. In the final step, an environment analysis of a swappable charging station is performed. Furthermore, the results achieved using the proposed framework for battery-swappable charging stations (BSCSs) were compared with fast-charging (FC) stations. FC can economically perform well if integrated with solar PV systems; however, the capital cost is 80% greater than the BSCSs designed under the proposed framework. The operational cost of BSCSs is 39% higher than FC stations as they use 29% higher grid units than FC stations due to night operations under congestion. Full article

The adoption of fully battery-powered electric vehicles (EVs) in Kuwait is currently at less than one percent of the population, and hence Kuwait has the lowest index rank among countries around the globe. Effectively, only Kuwaiti nationals have the opportunity to own EVs, as there are no fast direct-current charging stations in Kuwait, and Kuwaiti landlords (expats cannot own real estate) do not allow the installation of EV-charging home wall boxes at their rented properties. Given these facts, this paper only focuses on the preferences of Kuwaiti nationals, even though they only constitute 25 percent of the population of Kuwait. To accomplish the present objectives, a quantitative descriptive method (closed-ended questions) was used to collect data from a sample of 227 Kuwaiti nationals who were representative of the owners of half a million internal combustion engine (ICE) cars and that were categorized as early majority consumers. The findings of the present study indicate that over 50 percent of the respondents would prefer to buy an EV in the following three years when certain criteria were satisfied, including government-controlled pricing policies and recharging point availability, high-speed roads, and free EV-dedicated parking spaces. Furthermore, over 40 percent of respondents stated that they would contemplate purchasing an electric vehicle if the price of gasoline or diesel increased by 19 to 50 percent. The findings also indicated that more than 40 percent of respondents believed that EVs are fire- and crash-safe, and roughly 50 percent of the respondents would be willing to pay between 6 and 20% more for an EV because they believe that EVs are ecofriendlier vehicles and are significantly faster than conventional petrol vehicles. Additionally, respondents rewarded those vehicles with an excellent mark because of their ecological, economical, and technological attributes and benefits. Full article

The development and functional perfection of urban areas have led to increasingly severe fire risks in recent decades. Previous urban fire risk assessment methods relied on subjective judgment, rough data collection, simple linear statistical methods, etc. These drawbacks can lead to low robustness of evaluation and inadequate generalization ability. To resolve these problems, this paper selects the indicator and regression models based on the high-resolution data of the spatial distribution characteristics of Longquanyi distinct in Chengdu, China. and proposes an integrated machine learning algorithm for fire risk assessment. Firstly, the kernel density analysis is used to map the fourteen urban characteristics related to fire risks. The contributions of these indicators (characteristics) to fire risk and its corresponding index are determined by Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGBoost). Then, the spatial correlation of fire risks is determined through Moran’s I, and the spatial distribution pattern of indicator weights is clarified through the raster coefficient space analysis. Finally, with these selected indicators, we test the regression performance with a backpropagation neural network (BPNN) algorithm and a geographically weighted regression (GWR) model. The results indicate that numerical variables are more suitable than dummy variables for estimating micro-scale fire risks. The main factors with a high contribution are all numerical variables, including roads, gas pipelines, GDP, hazardous chemical enterprises, petrol and charging stations, cultural heritage protection units, assembly occupancies, and high-rise buildings. The machine learning algorithm integrating RF and BPNN shows the best performance (R² = 0.97), followed by the RF-GWR integrated algorithm (R² = 0.87). Compared with previous methods, this algorithm reduces the subjectivity of the traditional assessment models and shows the ability to automatically obtain the key indicators of urban fire risks. Hence, this new approach provides us with a more robust tool for assessing the future fire safety level in urban areas. Full article

The increasing environmental awareness paired with the rise of global warming effects has led, in the past few years, to an increase in the sales of electric vehicles (EVs), partly but not only, caused by governmental incentives. A significant roadblock in the mass transition to EVs can be found in the so-called range anxiety: not only do EVs have, generally, considerably shorter ranges than their internal combustion engine vehicle (ICEV) equivalents, but recharge takes significantly longer than does filling up a gas tank, and charging stations are less widespread than are petrol stations. To counteract this, EV manufacturers are developing route planners which select the best route to go from A to B according to the range of the vehicle and the availability of charging stations. These tools are indeed powerful but do not account for the state of health (SoH) of the battery or for temperature conditions, two factors which may severely degrade the range of an EV. This article presents an innovative route planning method which takes into account SoH, temperature and driving style and selects, along the planned route, the charging stations among those which can be reached with the energy of the battery. To verify its proper operativity, simulations were conducted, highlighting the risk of running out of battery before destination, considering if the route is planned based on the declared range, and taking into account battery SoH, external temperature and driving style. Full article

Polycyclic aromatic hydrocarbons (PAHs) are chemical compounds that are widespread in the environment, arising from the incomplete combustion of organic material, as well as from human activities involving petrol exploitation, petrochemical industrial waste, gas stations, and environmental disasters. PAHs of high molecular weight, such as pyrene, have carcinogenic and mutagenic effects and are considered pollutants. The microbial degradation of PAHs occurs through the action of multiple dioxygenase genes (nid), which are localized in genomic island denominate region A, and cytochrome P450 monooxygenases genes (cyp) dispersed in the bacterial genome. This study evaluated pyrene degradation by five isolates of Mycolicibacterium austroafricanum using 2,6-dichlorophenol indophenol (DCPIP assay), gas chromatography/mass spectrometry (CG/MS), and genomic analyses. Two isolates (MYC038 and MYC040) exhibited pyrene degradation indexes of 96% and 88%, respectively, over a seven-day incubation period. Interestingly, the genomic analyses showed that the isolates do not have nid genes, which are involved in PAH biodegradation, despite their ability to degrade pyrene, suggesting that degradation may occur due to the presence of cyp150 genes, or even genes that have not yet been described. To the best of our knowledge, this is the first report of isolates without nid genes demonstrating the ability to degrade pyrene. Full article

Electric transportation will assist in lowering emissions of greenhouse gases and mitigating the impact of rising petrol prices. To promote the widespread adoption of electric transportation, a diverse range of charging stations must be established in an atmosphere that is friendly to users. Wireless electric vehicle charging systems are a viable alternative technology that can charge electric vehicles (EVs) without any plug-in issues. Wireless power transfer (WPT), which involves the transmission of electricity via an electromagnetic field despite the presence of an intervening area, holds out the possibility of new prospects for EVs to increase environmentally responsible mobility. This review article examines the WPT technology and how it might be applied to electric vehicles from both a technical and safety standpoint. The prime aim of this review is (1) to illustrate the current state of the art in terms of technological advances as well as research limitations in the field of WPT development and use within the field of transportation; (2) to organise the experimental the deployment of WPT EV systems in the actual world; and (3) to analyse the results over a sustainable period and to identify limitations as well as chances for growth. From a technical point of view, the progress that has been made on the selection of material for designing coils, different types of coils with a specific focus on the overall performance of the system. As a result, this study aims to provide an extensive overview focusing on the magnetic materials and the architectures of the transmitter and receiver pads. Full article