Successful Implementation of Gas Driven Electric Power Grid Project for Wells and Facilities Electrification, Yielding GHG Emissions and Cost Benefits

Objectives/Scope: Kuwait Energy is exploring, developing, and operating four concessions located in the Western Desert and the Gulf of Suez in Egypt;the company implemented many projects that had a significant impact on saving operating expenses and reducing greenhouse emissions to preserve the environment. One of these recent executed projects was replacing scattered diesel generators with a Central gas-driven electric power grid in Al- Jahraa field in East Abu-Sennan concession. In this , we present the challenges we faced during the planning phase and execution strategy applied to overcome these challenges. Methods: Al-Jahraa Field includes 13 running wells, a waterflood station, and a main oil and gas production plant. The field electricity is supplied by 15 scattered diesel generators for wells and facilities, consuming 100,000 liters of diesel per month. During the feasibility study phase of the project, many challenges were faced which had a negative impact on the project's economical assessment and that would result in cancelling the project, the challenges were summarized as following;the existence of wells at long distances from the site of the proposed main power station, which would require extending long lengths of electric power cables at a high cost, also the expected delay in the implementation and commissioning of the project resulting from the long delivery time of materials, especially copper cables and main switchgear during the COVID-19 pandemic. Several scenarios were studied for connecting the wells to the power station: The first scenario was to connect all wells and field facilities directly to the main power station. In this case, the estimated power cable lengths required to be extended were 25,000 Mt, in addition to using two 1 MW generators, one in service and the other would be a standby generator to provide backup power during a repair or maintenance service. This option economic model showed negative NPV due to the high cost of cables and extended execution time. Therefore, this option was cancelled. The second alternative was to connect each group of wells to three power stations to be operated using three diesel generators of 500 kVA for each station, with three backup generators. But the implementation of this option would lead to saving the cost of copper cables by 50%, but the cost of purchasing generators would increase due to the increase in the number of stations accordingly, in addition to the increase in operating expenses resulting from the increase in fuel consumption and maintenance cost compared to the first option. The third alternative, in which the economics of the project proved to be the best, is to divide the wells into three groups. Each of the two remote groups of wells are connected to an electric distribution panel, and then the two panels are connected by a main cable to the main power station. Moreover, the project cost was reduced by 50% due to the implementation of the following innovative optimization approach: • Re-using ESP cables instead of copper cables optimized both cost and delivery time as these materials are pulled from ESP wells. • These cables are designed for harsh downhole conditions increases its durability and extends its lifetime. • Using step-up and step-down transformers enabled us to reduce cable sizing, which also reflected on the lower cost of the project and, accordingly, increased its feasibility to be constructed. • An Incremental development approach, was followed in the management and implementation of the project, led to the speed of project delivery, and reduced the project risks and uncertainties. Results: The project was completed and commissioned within the allocated budget and time frame, leading to: ◦ 100% reduction of diesel fuel consumption levels. ◦ +68% reduction in total emissions;emissions are reduced by 2.5tons per year on average. ◦ reduced operational costs for each kilowatt hour generated due to using associated gas as fuel and releasing 13 rental generators. ◦ With the replacement of 1 rental generators with just one, the amount of maintenance waste, such as batteries, used oil, oil filters, fuel filters, and so on, is significantly reduced. ◦ These projects showed positive economic indicators (+NPV), with less than 1 years of payback. Conclusion: From this project's planning, execution, and results, we can claim that if risk assessments, detailed scope of work, good resource and time management, and cost-effective choices were addressed carefully, shall result in outstanding performance. The design of a high-efficiency electrical power supply system and use of associated gas in power generation reduces levels of fuel consumption, GHG emissions, and operational costs. Power generation project is a repeated case performed in one of our own assets in Egypt due to positive results and are easily transferable to sister IOCs & NOCs. Copyright © 2023, Society of Petroleum Engineers.

Effects of Alcohol-Blended Waste Plastic Oil on Engine Performance Characteristics and Emissions of a Diesel Engine

The current study aims to investigate and compare the effects of waste plastic oil blended with n-butanol on the characteristics of diesel engines and exhaust gas emissions. Waste plastic oil produced by the pyrolysis process was blended with n-butanol at 5%, 10%, and 15% by volume. Experiments were conducted on a four-stroke, four-cylinder, water-cooled, direct injection diesel engine with a variation of five engine loads, while the engine's speed was fixed at 2500 rpm. The experimental results showed that the main hydrocarbons present in WPO were within the range of diesel fuel (C13–C18, approximately 74.39%), while its specific gravity and flash point were out of the limit prescribed by the diesel fuel specification. The addition of n-butanol to WPO was found to reduce the engine's thermal efficiency and increase HC and CO emissions, especially when the engine operated at low-load conditions. In order to find the suitable ratio of n-butanol blends when the engine operated at the tested engine load, the optimization process was carried out by considering the engine's load and ratio of the n-butanol blend as input factors and the engine's performance and emissions as output factors. It was found that the multi-objective function produced by the general regression neural network (GRNN) can be modeled as the multi-objective function with high predictive performances. The coefficient of determination (R2), mean absolute percentage error (MAPE), and root mean square error (RSME) of the optimization model proposed in the study were 0.999, 2.606%, and 0.663, respectively, when brake thermal efficiency was considered, while nitrogen oxide values were 0.998, 6.915%, and 0.600, respectively. As for the results of the optimization using NSGA-II, a single optimum value may not be attained as with the other methods, but the optimization's boundary was obtained, which was established by making a trade-off between brake thermal efficiency and nitrogen oxide emissions. According to the Pareto frontier, the engine load and ratio of the n-butanol blend that caused the trade-off between maximum brake thermal efficiency and minimum nitrogen oxides are within the approximate range of 37 N.m to 104 N.m and 9% to 14%, respectively.

Recent Activities in Railway Vehicle Technology Research and Development

Spurred by fall in passenger numbers following the COVID-19 pandemic, railways today have made rapid progress in improving operational efficiency and labor saving measures. DX (digital transformation) technology, which has been applied to automatic train operation, inter alia, is therefore attracting attention. Another focal point for railways is the realization of global decarbonization, illustrated by "2050 Carbon Neutral" goal declared by the Suga Cabinet and "COP26." This paper introduces the outlines of three technologies related to these topics, namely, a "Method for evaluating wheel slide protection (WSP) performance by hybrid simulator," a "Method applying neural networks to detect abnormal noise during train operation," and "High efficiency of diesel electric railcars." © 2022 Ken-yusha Inc.. All rights reserved.

Spatial associations of long-term exposure to diesel particulate matter with seasonal and annual mortality due to COVID-19 in the contiguous United States.

BACKGROUND: People with certain underlying respiratory and cardiovascular conditions might be at an increased risk for severe illness from COVID-19. Diesel Particulate Matter (DPM) exposure may affect the pulmonary and cardiovascular systems. The study aims to assess if DPM was spatially associated with COVID-19 mortality rates across three waves of the disease and throughout 2020. METHODS: We tested an ordinary least squares (OLS) model, then two global models, a spatial lag model (SLM) and a spatial error model (SEM) designed to explore spatial dependence, and a geographically weighted regression (GWR) model designed to explore local associations between COVID-19 mortality rates and DPM exposure, using data from the 2018 AirToxScreen database. RESULTS: The GWR model found that associations between COVID-19 mortality rate and DPM concentrations may increase up to 77 deaths per 100,000 people in some US counties for every interquartile range (0.21 µg/m3) increase in DPM concentration. Significant positive associations between mortality rate and DPM were observed in New York, New Jersey, eastern Pennsylvania, and western Connecticut for the wave from January to May, and in southern Florida and southern Texas for June to September. The period from October to December exhibited a negative association in most parts of the US, which seems to have influenced the year-long relationship due to the large number of deaths during that wave of the disease. CONCLUSIONS: Our models provided a picture in which long-term DPM exposure may have influenced COVID-19 mortality during the early stages of the disease. That influence appears to have waned over time as transmission patterns evolved.

Risk Factors for Respiratory Viral Infections: A Spotlight on Climate Change and Air Pollution.

Climate change has both direct and indirect effects on human health, and some populations are more vulnerable to these effects than others. Viral respiratory infections are most common illnesses in humans, with estimated 17 billion incident infections globally in 2019. Anthropogenic drivers of climate change, chiefly the emission of greenhouse gases and toxic pollutants from burning of fossil fuels, and the consequential changes in temperature, precipitation, and frequency of extreme weather events have been linked with increased susceptibility to viral respiratory infections. Air pollutants like nitrogen dioxide, particulate matter, diesel exhaust particles, and ozone have been shown to impact susceptibility and immune responses to viral infections through various mechanisms, including exaggerated or impaired innate and adaptive immune responses, disruption of the airway epithelial barrier, altered cell surface receptor expression, and impaired cytotoxic function. An estimated 90% of the world's population is exposed to air pollution, making this a topic with high relevance to human health. This review summarizes the available epidemiologic and experimental evidence for an association between climate change, air pollution, and viral respiratory infection.

Integrated transportation and land use regression modelling for nitrogen dioxide mitigation

The transport sector has been identified as one of the main contributors to nitrogen dioxide (NO2) pollution in Ireland. This research develops an enhanced Wind Sector Land Use Regression (WS-LUR) model to estimate NO2 concentrations across Ireland, in areas where air pollution monitoring is not available. The model incorporates details of the vehicle fleet breakdown to weight vehicle type flows based on the emission rates of the vehicle type, differentiating routes with varying proportions of heavier emitting vehicles. In 2008, car taxation underwent a significant change from an engine size based system to a carbon dioxide (CO2) emission rate based system resulting in a significant transition towards diesel fuelled vehicles. A mitigation strategy to remove diesel fuelled vehicles from the public service vehicle fleet was tested achieving predicted NO2 reductions in the range of 0.3 μg/m3 to 1.9 μg/m3. The impact of COVID-19 on NO2 concentration levels was also investigated. © 2022 Elsevier Ltd

Engine emissions with air pollutants and greenhouse gases and their control technologies

Diesel and gasoline are the most used fossil fuels due to their high energy release and low cost for engines. However, the emission of air pollutants and greenhouse gases has caused severe environmental issues, and emission regulations are becoming stricter. Recently, several advances in emission control technologies for fossil fuel engines have been available, which need to be reviewed to manifest future research. Here, we reviewed the primary pollutants emitted from the diesel and gasoline-powered engines, their formation process, and the present technologies to control the emissions of greenhouse gases and air pollutants, especially during the COVID-19 pandemic. In this regard, this review concentrates on a particular matter (PM2.5 and PM10), carbon monoxide (CO), nitrogen oxides (NOx), unburned hydrocarbons (HC), and greenhouse gases (water vapor, CO2, N2O, etc.) as exhaust emissions, the difficulties they cause, and the strategies employed to reduce emissions. This review also provides a framework for understanding how to reduce air pollution and greenhouse gasses generated by diesel and gasoline-powered engines.

Seasonal variation, sources, and risk assessment of PM2.5-bound PAHs in Nantong, China: A pre- and post-COVID-19 case study

Between 2018 and 2022, a total of 231 PM2.5 samples were collected in Nantong, China, and analyzed online for 16 US EPA PAHs utilizing a variety of analytical methodologies, including high-performance liquid chromatography data analysis, principal component analysis, and characteristic ratio analysis. The seasonal variation and pollution characteristics of 16 PAHs in PM2.5 over a long period in Nantong, China, were analyzed, and correlations and traceability changes with a variety of emission sources were established. Additionally, health assessment models for BaP equivalent concentration, daily exposure dose, lifetime excess risk of cancer, and life expectancy loss were constructed for various ages and genders. The results indicated that the total number of days with BaP concentrations less than the national limit standard of 1.0 ng/m(3) was 60.17% (139/231), with rates of 25.40%, 35.71%, and 94.05% from 2019 to 2021, respectively;the total concentration range of 16 PAHs demonstrated a downward trend, but pollution was relatively severe in winter. The seasonal variation showed winter > autumn > spring > summer. The detection rates of 4 and 5 rings were generally high and fluctuated between dropping and increasing. Principal factor analysis and characteristic ratio traceability analysis indicated that PAH pollution is primarily caused by local coal-fired sources and traffic emissions, with a new trend of biomass combustion. Furthermore, BaP remains the primary contributor to carcinogenic factors, and the health risk is higher in females than in males, and in adults than in children. A low level of PAHs in the air may have health benefits. Traffic control and flow restrictions, as well as production restrictions, are all part of Nantong's COVID-19 pandemic prevention and control policies. These policies contributed to PAH risk prevention and control, as well as pollution reduction.

Effect of Al2O3 Nanoparticles on Performance and Emission Characteristics of Diesel Engine Fuelled with Diesel–Neem Biodiesel Blends

Indagation in the sphere of nanoparticle utilisation has provided commendatory upshots in discrete areas of application varying from medicinal use to environmental degradation alleviation. This study incorporates alumina nanoparticles as additives to diesel and biodiesel blends. The prime objective of the present study was the scrutinisation of the denouement of Al2O3 nanoparticle incorporation in diesel–biodiesel blends on a diesel engine’s performance and emission characteristics. Test fuel samples were prepared by blending different proportions of biodiesel and dispersing two concentrations of alumina nanoparticles (25 and 50 ppm) in the diesel. Dispersion was made without the use of a nanoparticle stabiliser to meet real-world feasibility. High-speed shearing was employed to blend the biodiesel and diesel, while nanoparticles were dispersed in the blends by ultrasonication. The blends so devised were tested using a single-cylinder diesel engine at fixed RPM and applied load for three compression ratios. Upshots of brake-specific fuel consumption (BSFC) and brake thermal efficiency (BTE) for fuel samples were measured with LabView-based software, whereas CO emissions and unburnt hydrocarbon (UBHC) emissions were computed using an external gas analyser attached to the exhaust vent of the engine. Investigation revealed that the inclusion of Al2O3 nanoparticles culminates in the amelioration of engine performance along with the alleviation of deleterious exhaust from engine. Furthermore, the incorporation of alumina nanoparticles assisted in the amelioration of dwindled performance attributed to biodiesel blending. More favourable results of nanoparticle inclusion were obtained at higher compression ratios compared to lower ones. Reckoning evinced that the Al2O3 nanoparticle is a lucrative introduction for fuels to boost the performance and dwindle the deleterious exhaust of diesel engines.

Diesel passenger vehicle shares influenced COVID-19 changes in urban nitrogen dioxide pollution

Diesel-powered vehicles emit several times more nitrogen oxides than comparable gasoline-powered vehicles, leading to ambient nitrogen dioxide (NO2) pollution and adverse health impacts. The COVID-19 pandemic and ensuing changes in emissions provide a natural experiment to test whether NO2 reductions have been starker in regions of Europe with larger diesel passenger vehicle shares. Here we use a semi-empirical approach that combines in-situ NO2 observations from urban areas and an atmospheric composition model within a machine learning algorithm to estimate business-as-usual NO2 during the first wave of the COVID-19 pandemic in 2020. These estimates account for the moderating influences of meteorology, chemistry, and traffic. Comparing the observed NO2 concentrations against business-as-usual estimates indicates that diesel passenger vehicle shares played a major role in the magnitude of NO2 reductions. European cities with the five largest shares of diesel passenger vehicles experienced NO2 reductions ∼2.5 times larger than cities with the five smallest diesel shares. Extending our methods to a cohort of non-European cities reveals that NO2 reductions in these cities were generally smaller than reductions in European cities, which was expected given their small diesel shares. We identify potential factors such as the deterioration of engine controls associated with older diesel vehicles to explain spread in the relationship between cities’ shares of diesel vehicles and changes in NO2 during the pandemic. Our results provide a glimpse of potential NO2 reductions that could accompany future deliberate efforts to phase out or remove passenger vehicles from cities.

Effect of Different Combustion Modes on the Performance of Hydrogen Internal Combustion Engines under Low Load

Detailed hydrogen–air chemical reaction mechanisms were coupled with the three-dimensional grids of an experimental hydrogen internal combustion engine (HICE) to establish a computational fluid dynamics (CFD) combustion model based on the CONVN1 -https://media.proquest.com/media/hms/PFT/1/iyX6N?_a=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%3D%3D&_s=XxDsfbWeNCPMojxxWroCr%2FH0Al4%3D ERGE software. The effects of different combustion modes on the combustion and emission characteristics of HICE under low load were studied. The simulation results showed that, with the increase in excess hydrogen, the equivalent combustion and excessive hydrogen combustion modes with medium-cooled exhaust gas recirculation (EGR) dilution could improve the intensity of the in-cylinder combustion of HICE, increase the peak values of pressure and temperature in the cylinder, and then improve the indicated thermal efficiency of HICE under low load. However, larger excessive hydrogen combustion could weaken the improvement in performance;therefore, the performance of HICE could be comprehensively improved by the adoption of excessive hydrogen combustion with a fuel–air ratio below 1.2 under low load. The obtained conclusions indicate the research disadvantages in the power and emission performances of HICE under low load, and they are of great significance for the performance optimization of HICE. Furthermore, a control strategy was proposed to improve the stability of HICE under low load.

Experimental Investigation and neural network modelling of diesel engine using hexanol blended ternary waste cooking oil biodiesel with moderate preheating

The depleting fossil fuel reserves, rising air pollution, technology transformation threat, and most recently, global economic slowdown by the COVID-19 pandemic, led the internal combustion engine-based automotive industries in a critical condition. The development of improved biofuels to meet stringent emission norms is a promising solution. Higher alcohols possess the fuel properties better than lower alcohols to blend with diesel and biodiesel. The miscibility and higher viscosity is the issue. Preheating can help the vaporization and atomization of fuel. The present study investigates the engine characteristics of moderately preheated ternary fuel using 20 to 40% blends of 1-hexanol, waste cooking oil biodiesel, and diesel. The study found that moderately preheated ternary fuel blends showed a drop in brake-specific fuel consumption, HC, CO, and smoke emissions with improvement in peak cylinder pressure, heat release rate, and brake thermal efficiency. A multi-layer neural network model is developed to prognosticate the engine characteristics. Backpropagation algorithm-based neural network with single hidden layers using Levenberg–Marquardt training function gave the best results. The mean square error of the network was 0.00028517 and the correlation coefficient was 0.99944, 0.99945, and 0.99923 for training, validation, and testing respectively. The mean absolute percentage error was found below 4%. © 2022 Elsevier Ltd

Export Growth - Fuel Price Nexus in Developing Countries: Real or False Concern?

This paper investigates the impact of domestic fuel price increases on export growth in a sample of 77 developing countries over the period 2000-2014. Using a fixed-effect estimator and the local projection approach, we find that an increase in domestic gasoline or diesel price adversely affects real non-fuel export growth, with the impact phasing out within two years after the shock. The impact is mainly noticeable in countries with a high-energy dependency ratio and where access to electricity is limited. Further, large fuel price shocks do not seem to lead to disproportionately large changes in exports, suggesting that neither the gradualism nor the shock therapy approach in fuel subsidy reforms dominates. In countries where the export sector is vulnerable to fuel price shocks, appropriate mitigating measures should be designed to smooth the transition to higher fuel prices.

Effect of hybrid nanoparticles MgO and Al2O3 added water-in-diesel emulsion fueled diesel engine using hybrid deep neural network-based spotted hyena optimization

The automotive sector is one of the top energy consumers globally compared with any other sector where oil plays the main role. According to statista. corn (an online platform that displays the stats on oil consumption and reserves), in 2016, the demand for crude oil was about 85.3 million barrels per day worldwide. In 2019, the demand almost reached 100 barrels per day, and then it was reduced to 91 million per day during the 2020 global COVID-19 crisis. However, it was predicted that the global crude oil requirements will exceed 100 million barrels per day by 2023 and will continue to raise. Also, geographically, not all countries worldwide have the oil reservoirs or the technology to extract oil from the reservoirs. Although the oil demand worldwide is increasing every year, researchers have estimated that there are only 47 years of oil left on the planet earth if the current oil consumption will raise this way. Researchers are looking for finding alternative fuels, such as electrochemical energy (electric vehicles), biodiesel, electricity, ethanol, hydrogen, natural gas, propane, emerging fuels, or the use of such fuels in the existing engines to minimize the use of nonrenewable energy resources. However, researchers are also looking more at fuels based on hybrid nanoparticles added to emulsified fuels. Due to the limitations of utilizing electrochemical energy or biofuels include high charging time, limited millage, harmful exhaust emissions, complicated production process, engine efficiency, the cost of fuel, and the advantages over hybrid nanoparticles added emulsified fuels than biofuels. Hence, after going through numerous researches, in this present experimentation, "hybrid nanoparticles (MgO and Al2O3) added water-in-diesel emulsion" are formulated to enhance the quality of emission and improve the performance of the compression ignition engine. The best combination of diesel, MgO, and Al2O3, a water-in-diesel (W/D) emulsion blend, is proposed. The results were further validated using deep neural network-based spotted hyena optimization (DNN-SHO) prediction and compared with traditional machine learning approaches artificial neural network (ANN), convolution neural network (CNN), regression-based network (RBN), recurrent neural network (RNN), and DNN. As a result, the best proportions of the proposed nanoparticles added into the W/D bend are identified to be 10% W/D, 50 ppm of MgO, and 50 ppm of Al2O in terms of engine performance and emission characteristics brake thermal efficiency 30.7%, brake-specific fuel consumption 0.29 kg/kW-h, CO 0.027 vol%, NOx 855 ppm vol, and HC 12 ppm vol. Besides this, the DNN-SHO-based validated outcomes are in good agreement with the experimental values and out-performed other traditional approaches ANN, CNN, RBN, RNN, and DNN used in this study.

Photoelectric and diffusion charging measurements of fine particulate air pollution along the main roads of the city of Madrid from 1999 to 2021

In this work, the evolution of the fine particulate air pollution (of size below one μm) produced by the vehicles when driving along several roads of Madrid is studied. Measurements were taken with portable near real-time sensors of Diffusion Charging (DC) and Photoelectric Charging (PC) while driving along the roads. The obtained measurement profiles basically consist of spikes when measuring in the exhaust plumes of preceding vehicles and a background level of mixed aged exhaust that forms when high traffic intensity exist. The DC sensor measures air concentration of the particles Total Active Surface (TAS) and the PC sensor was calibrated to measure the air concentration of Particle bound Polycyclic Aromatic Hydrocarbons (PPAH). The amount of adsorbed PAH per active surface (the PC/DC ratio) is a measure of particles toxicity. Both sensors are sensible to ultra-fine particles of size below 0.1 μm. The measured median values of DC and PC, for the years 1999, 2001, 2005, 2006, 2016, 2017, 2020 and 2021, are plotted as well as their median PC/DC ratio. Examples of measurement profiles are also shown including measurements during COVID-19 driving restrictions. During these restrictions, we could conclude that our measured particulate air pollution of fine and ultrafine particles is caused by "polluting-vehicles" still coexisting in the vehicle fleet of Madrid, which do not fulfill the latest Euro standard because they are too old or have no/malfunctioning catalytic converter and/or diesel particle filter (DPF). The changes of the measured median of the DC and PC values are discussed based on already known results of implemented vehicle technologies for reducing emissions, the evolution of the vehicle fleet fulfilling the increasingly demanding Euro standards, the traffic count, the PC and DC working principles, the evolution of the exhaust emission when exiting the pipe, and on the sulfur content reductions in diesel. The main factors that allowed the large reduction of the median values of both DC and PC (from 1167 ± 57 mm2/m3 and 990 ± 54 ng/m3 in 1999 to 263 ± 14 mm2/m3 and 124 ± 7 ng/m3 in 2021 respectively) as well as the changes in the PC/DC ratio was, according to our findings, the diesel sulfur content reduction and the implementation of the Diesel Oxidation Catalysis (DOC) and the DPF. • Decrease in the total active surface of fine particles in the air of the city of Madrid since 1999. • Decrease in PAH adsorbed on fine particles in the air along the roads of the city of Madrid since 1999. • Evolution of on-road fine and ultrafine exhaust particle emissions in Madrid since 1999. • Drastic localized increase of air suspended fine particles caused by specific polluting vehicles. • Changes in the on-road fine and ultrafine exhaust particles toxicity in Madrid since 1999. [ FROM AUTHOR] Copyright of Atmospheric Environment is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Household Ability of Expenditures on Electricity and Energy Resources in the Countries That Joined the EU after 2004

The purpose of the following article is to present the situation of the energy market from a household perspective between 2010 and 2020 in selected EU countries (the group of member states which joined EU after 2004). The selected countries when joining the EU had similar economic indicators and to some extent were similar in other macro-economic situations (personal income, unemployment rate, GDP level and annual growth). This article analyzes the past and current situation of the household ability expenditure on electricity and energy resources (petrol—eurosuper 95 and diesel and natural gas), taking into account price, tax conditions and the real possibility to purchase the analyzed energy sources (based on annual net salaries). The paper includes the conclusions and prospects for the future. The main objective of the study is to determine the ability amount of expenditure on electricity, natural gas and liquid fuels by household in the countries that joined the European Union after 2004. The specific objectives of the work include: the evolution of retail prices of energy sources in those countries and prices of electricity, natural gas and liquid fuels—petrol and diesel oil—in the research period from 2010 to 2020. The element that influences the final price, as assessed in this paper, is the share of taxes and compulsory charges imposed by the EU countries covered in this study. The result of the study presented inter alia that energy consumption structure did not change significantly, electricity prices were steadily growing in the countries under assessment, the use of liquid fuels—petrol and diesel oil—in the countries under study, grew over the study period. Furthermore, prices of fuel fluctuated over the period from 2010 to 2020 and during the COVID-19 pandemic, which broke out in March 2020, but did not cause any significant changes in the prices of energy carriers in the analyzed period, apart from the declines in the prices of eurosuper 95 and diesel.

Energy Management in the Multi-Source Systems

[...]it is clear by the policies and scenarios which are already laid out, that we need to investigate in detail and improve the existing technologies in an effective manner. [13] present a frequency splitting based energy management strategy in a microgrid consisting of a diesel generator, supercapacitors, wind turbine, solar photovoltaic generator, and lithium batteries. A dedicated building has been recommended for the electrode station for the sake of limiting energy consumption, preventing electrochemical corrosion, protecting from environmental constraints, and reducing the risk of fire hazards by increasing the fire resistance by installing a firefighting system. [...]a design process for the electrode station building has been proposed in detail.

LNG vs. MDO in Marine Fuel Emissions Tracking

The continuous increase in global maritime freight transport has led to an increase in emissions. The port of Heraklion was selected as a case study to investigate the environmental impact of shipping in wider areas. Two different maritime fuels were examined: the conventional maritime fuel, marine diesel oil (MDO), and an alternative maritime fuel, liquified natural gas (LNG). To carry out this study, real data from the port of Heraklion, the Lloyd’s Register Fairplay (LRF) Sea-Web database, and literature reviews were used. The bottom-up method was adopted for data processing. The results of this study demonstrate that alternative maritime fuels, such as LNG, could drastically reduce SO2, NOx, PM, and CO2 emissions.

CO2 Emission Factors and Carbon Losses for Off-Road Mining Trucks

There are myriad questions that remain to be answered in greenhouse gas (GHG) emissions trading. This article addresses carbon dioxide (CO2) emission factors and carbon losses from heavy equipment that is used to transport ores. Differences occurred between the Intergovernmental Panel for Climate Change (IPCC) emission factor and those that were obtained by considering incomplete combustion and on-site exhaust concentration measurements. Emissions from four off-road vehicles were analyzed. They operated at idle (loading, unloading, and queuing) and in motion (front and rear, loaded and unloaded). The results show that the average CO2 emission factors can be as low as 64.8% of the IPCC standard value for diesel fuel. On the other hand, carbon losses can be up to 33.5% and energy losses up to 25.5%. To the best of the authors’ knowledge, the method that was developed here is innovative, simple, useful, and easily applicable in determining CO2 emission factors and fuel losses for heavy machinery.

Charging Electric Vehicles from Photovoltaic Systems—Statistical Analyses of the Small Photovoltaic Farm Operation

Zero-emission transport is a very important topic that is increasingly taken up by many institutions and research centers around the world. However, the zero-emissivity of the vehicle is quite a complex issue, which should be understood as not only the lack of emissions during the operation of the vehicle, but also the provision of clean energy to the vehicle. In this approach, charging the battery of an electric vehicle from renewable sources—a photovoltaic (PV) farm—and its operation can be considered as a totally zero-emission form of transport. The article presents a PV system containing two micro-installations with a capacity of up to 40 kWp each to supply electricity to two parts of the Lublin Science and Technology Park (LSTP) building. Thanks to the innovative monitoring system, it was possible to analyze the consumption and production as well as the effective use of electricity. Statistical analyses of consumption (charging the electric vehicle battery) and electricity production by the PV installation were carried out. It was found that charging an electric vehicle could be a good way to use the surplus energy production from the farm and thus a faster repayment on investment in the PV farm installation.