Usage Of Fossil Fuels Research Articles

Evolution of Photobioreactors: A Review based on Microalgal Perspective

Energy is indispensable for bringing competence, resilience, and comfort for the ever-advancing human lifestyle. Therefore, to satisfy the growing energy requirement researchers are trying to delve in exploring sustainable and renewable energy sources that will contribute to the reduction of carbon footprint and ultimately help to check the issue of global warming caused by the increased emission of CO2, due to the excessive usage of non-renewable and exhaustive fossil fuels. Microalgae are having the potential which can be exploited to produce biofuels (substitute for fossil fuels) and other value-added compounds. Microalgae is a form of unicellular photoautotrophic microorganism which can attain higher rate of proliferation. Microalgae is having merits over other terrestrial crops and fossil fuels as they have higher productivity of oil per hectare of land. Various other advantages of microalgae include their tolerance in different types of environment because of their ubiquitous nature (in terms of pH, salinity, and temperature). Furthermore, they can be cultivated in nonarable land and wastewater which will resolve the food-fuel duel and problem of freshwater usage, therefore leading towards environmental sustainability. The main factors governing the growth and cultivation of microalgae are light, CO2/air, nutrients, process parameters (pH, temperature, growth medium etc) and most importantly the type of system used for cultivation. The systems usually employed for the cultivation of microalgae are open system (open ponds, raceway ponds, scrubbers), closed system also commonly known as photobioreactors (flat plate and tubular photobioreactors) and hybrid system in which separation of biomass growth and lipid accumulation is achieved in two stages. All the systems have some merits and demerits but photobioreactors are widely accepted and used because they are having an upper hand over open system because of the optimised control of the growth conditions, contamination evasion and efficient productivity of microalgal biomass. This review will provide an insight to different parameters which govern the growth of microalgae and various types of photobioreactors with their advantages and disadvantages. This study will help in the optimized selection of the photobioreactors for a particular species of microalgae because despite the continuous and intensive research going on the cultivation systems it is a challenge for the researchers to achieve a suitable and economically viable system.

The state of art review on thermal management techniques for the thermoelectric cooler

The usage of renewable energy sources and reducing the usage of fossil fuels are important to improve the quality of life and environment. Thermoelectric devices are direct energy conversion devices, which can be used for power generation, heat and cooling applications. Thermoelectric devices can be integrated with solar thermal systems, solar photovoltaic systems and waste heat recovery systems etc. to produce electrical energy and cooling effect. This article presents the state of art review on the thermal management techniques for thermoelectric cooler. The thermal management on TEC will improve the thermal performance of cooling power and Coefficient of performance.

Low-Dimensional Nanostructured Photocatalysts for Efficient CO2 Conversion into Solar Fuels

The ongoing energy crisis and global warming caused by the massive usage of fossil fuels and emission of CO2 into atmosphere continue to motivate researchers to investigate possible solutions. The conversion of CO2 into value-added solar fuels by photocatalysts has been suggested as an intriguing solution to simultaneously mitigate global warming and provide a source of energy in an environmentally friendly manner. There has been considerable effort for nearly four decades investigating the performance of CO2 conversion by photocatalysts, much of which has focused on structure or materials modification. In particular, the application of low-dimensional structures for photocatalysts is a promising pathway. Depending on the materials and fabrication methods, low-dimensional nanomaterials can be formed in zero dimensional structures such as quantum dots, one-dimensional structures such as nanowires, nanotubes, nanobelts, and nanorods, and two-dimensional structures such as nanosheets and thin films. These nanostructures increase the effective surface area and possess unique electrical and optical properties, including the quantum confinement effect in semiconductors or the localized surface plasmon resonance effect in noble metals at the nanoscale. These unique properties can play a vital role in enhancing the performance of photocatalytic CO2 conversion into solar fuels by engineering the nanostructures. In this review, we provide an overview of photocatalytic CO2 conversion and especially focus on nanostructured photocatalysts. The fundamental mechanism of photocatalytic CO2 conversion is discussed and recent progresses of low-dimensional photocatalysts for efficient conversion of CO2 into solar fuels are presented.

State of the art methods for combined water and energy systems optimisation in Kraft pulp mills

This paper presents a state-of-the-art overview of water and energy optimisation methods with applications to Kraft pulp mills. The main conclusions are highlighted, and several research gaps are identified and proposed for future research. Kraft processes have the potential to be adapted to biorefineries for producing biofuels and other high-value products from wood biomass. Biorefineries enable opportunities to increase the revenue of the process, reduce fossil fuels usage and greenhouse gas emissions. However, to ensure an effective Kraft process transformation, the existing mill infrastructure needs to be consolidated. In this sense, the water system, the heat exchanger network and the utility system should all be optimised together. A series of systematic methods (process integration-conceptual and mathematical programming) have been identified in the literature, along with the results of several case studies that reduce water and energy consumption in Kraft processes. Initial studies in this field considered and solved separate water and energy integration problems, but recent works have been focused on the development of methods for combined water and energy integration and their application to various processes. Typical savings lead to freshwater consumption decreases between 20 and 80% and energy consumption reductions between 15 and 40%.

Research progress of the decarboxylation mechanisms of fatty acids to generate aliphatic hydrocarbons catalyzed by iron-containing enzymes

With the progress of human society, the consumption of energy materials is increasing in particularly the fossil fuels, which accounts for 84.7% of the total global consumption in 2018. Thus, excessive exploitation of fossil fuels not only brings about an increasingly serious energy crisis, but also leads to a series of environmental problems, such as the air quality deterioration and soil acidification, which are not conducive to the sustainable development of society. Since the 21st Annual Conference of the China Association for Science and Technology in 2019, “renewable synthetic fuels” has become one of the focuses of attention, and it also puts forward higher requirements for the research and development of renewable energy. About 60 years ago, many plants, insects, microorganisms and microalgae were found to metabolize hydrocarbons. In 2010, Schirmer’s groups recognized the alkane biosynthesis pathways of marine chlorobacteria, which aroused great interest in hydrocarbon biosynthesis. Recently, more proteases to catalyze the synthesis of hydrocarbons have been successively discovered, such as aldehyde deformylase (ADO, CYP4G and CER), fatty acid decarboxylase (UndA, UndB and OleT), polyketone synthase (Ols) and thiolytic enzyme complex system (OleABCD). In the past decades, many studies have been conducted to explore the biosynthesis of hydrocarbon, and useful information regarding the reaction mechanism has been obtained, including the kinetic rate constants and the crystal structures of the enzymes. In addition, on the basis of crystal structure, quantum chemistry method (QM) and molecular dynamics simulations (MD) were also used to explore the reaction mechanism of fatty acid decarboxylation. Since most enzymes involved in the hydrocarbon biosynthesis are iron-containing enzymes, which employ the Fe-coordinate dioxygen to trigger the reaction. In general, the whole reaction cycle contains the binding of substrates and dioxygen, and decarboxylation usually involves the hydrogen atom abstraction and breaking of C−C bond. During the reaction, complex electron transfer takes place among the Fe center, O2 and substrate, and many factors were found to affect the catalytic activity. According to the previous experimental and theoretical studies, different enzymes show different activity and substrate scope. In general, the catalytic efficiency is still very low for most enzymes, and thus, understanding the mechanism of these catalytic reactions is undoubtedly an important basis for engineering optimization and all applications, and can also provide ideas for the design and synthesis of biomimetic catalysts. In this paper, we review the research progress of five representative iron enzymes that catalyze the biosynthesis of aliphatic hydrocarbon, including OleT, UndA, UndB, ADO and CYP4G, and discuss the future development and application of enzyme catalysis in renewable synthetic fuels. This paper may offer some ideas and guidelines for sustainable energy supply in the future.

Impacts of Changes in Atmospheric O2 on Human Physiology. Is There a Basis for Concern?

Concern is often voiced over the ongoing loss of atmospheric O2. This loss, which is caused by fossil-fuel burning but also influenced by other processes, is likely to continue at least for the next few centuries. We argue that this loss is quite well understood, and the eventual decrease is bounded by the fossil-fuel resource base. Because the atmospheric O2 reservoir is so large, the predicted relative drop in O2 is very small even for extreme scenarios of future fossil-fuel usage which produce increases in atmospheric CO2 sufficient to cause catastrophic climate changes. At sea level, the ultimate drop in oxygen partial pressure will be less than 2.5 mm Hg out of a baseline of 159 mmHg. The drop by year 2300 is likely to be between 0.5 and 1.3 mmHg. The implications for normal human health is negligible because respiratory O2 consumption in healthy individuals is only weakly dependent on ambient partial pressure, especially at sea level. The impacts on top athlete performance, on disease, on reproduction, and on cognition, will also be very small. For people living at higher elevations, the implications of this loss will be even smaller, because of a counteracting increase in barometric pressure at higher elevations due to global warming.

A review on the prospect of wind power as an alternative source of energy in Malaysia

Fossil fuels has dictated the energy sector for several decades, rising as the primary and prominent source of energy production for various sector of industries namely electricity (power), transportation, manufacturing and others. However, extensive usage of fossil fuels majorly contributed to pollution issues and degradation of the environment. Hence, governments and research agencies are providing supports and resources to facilitate the growth of renewable energy sector (RES). This manuscript provides a brief view of the challenges of wind renewable energy sector in Malaysia relative to geographical wind condition, government policies and challenges in initiation of wind technologies and global perspective of green energy in terms of RER. It is found that data presented by previous researchers on wind speed data are considered unreliable to be utilized for WT power density assessment and design. Notably, wind speed in Malaysia is seasonal based and highly inconsistent. The wind flow pattern and intensity experience by Malaysia are merely an aftereffect of weather change in neighbouring regions. Nevertheless, it is found that selected regions of east-coast peninsular Malaysia and selected region of Sabah and Sarawak is potential for harvesting wind power due to substantial and adequate wind pattern behavior during monsoon season. Therefore, it is evident that geographical wind condition of Malaysia is appropriate for wind power devices as a form of RER in green energy sector of Malaysia. However, it is also found that fundamental design modification is required on conventional design of WT in terms of blade morphology and configuration in order to adapt to unsteady monsoon wind speed pattern.

Low-Viscosity Ether-Functionalized Ionic Liquids as Solvents for the Enhancement of Lignocellulosic Biomass Dissolution

Due to the substantial usage of fossil fuels, the utilization of lignocellulosic biomass as renewable sources for fuels and chemical production has been widely explored. The dissolution of lignocellulosic biomass in proper solvents is vital prior to the extraction of its important constituents, and ionic liquids (ILs) have been found to be efficient solvents for biomass dissolution. However, the high viscosity of ILs limits the dissolution process. Therefore, with the aim to enhance the dissolution of lignocellulosic biomass, a series of new ether-functionalized ILs with low viscosity values were synthesized and characterized. Their properties, such as density, viscosity and thermal stability, were analyzed and discussed in comparison with a common commercial IL, namely 1-butyl-3-methylimidazolium chloride (BMIMCl). The presence of the ether group in the new ILs reduces the viscosity of the ILs to some appreciable extent in comparison to BMIMCl. 1-2(methoxyethyl)-3-methylimidazolium chloride (MOE-MImCl), which possesses the lowest viscosity value among the other ether-functionalized ILs, demonstrates an ability to be a powerful solvent in the application of biomass dissolution via the sonication method. In addition, an optimization study employing response surface methodology (RSM) was carried out in order to obtain the optimum conditions for maximum dissolution of biomass in the solvents. Results suggested that the maximum biomass dissolution can be achieved by using 3 weight% of initial biomass loading with 40% amplitude of sonication at 32.23 min of sonication period.

Firm-specific responses to energy policies in Dutch horticulture

AbstractReducing the usage of fossil fuels is a central issue in ongoing policy debates. This in particular holds for Dutch horticulture, given its energy-intensive production. We analyse differences in energy usage and price responsiveness of horticultural firms by estimating energy demand functions using a Bayesian random coefficient model. Beyond, the effects of a proposed energy tax are assessed. Allowing for firm-specific energy price coefficients gives a better model fit compared to conventional models with fixed slope parameters. This confirms that firms respond differently to energy prices, which is taken into account in simulating the effects of more restrictive energy policies. The results show that larger-sized firms use less gas per square meter yet also point at a considerable spread in additional energy expenses between firms.

Effect of Hydrogen Addition on the Energetic and Ecologic Parameters of an SI Engine Fueled by Biogas

The global policy solution seeks to reduce the usage of fossil fuels and greenhouse gas (GHG) emissions, and biogas (BG) represents a solutions to these problems. The use of biogas could help cope with increased amounts of waste and reduce usage of fossil fuels. Biogas could be used in compressed natural gas (CNG) engines, but the engine electronic control unit (ECU) needs to be modified. In this research, a spark ignition (SI) engine was tested for mixtures of biogas and hydrogen (volumetric hydrogen concentration of 0, 14, 24, 33, and 43%). In all experiments, two cases of spark timing (ST) were used: the first for an optimal mixture and the second for CNG. The results show that hydrogen increases combustion quality and reduces incomplete combustion products. Because of BG’s lower burning speed, the advanced ST increased brake thermal efficiency (BTE) by 4.3% when the engine was running on biogas. Adding 14 vol% of hydrogen (H2) increases the burning speed of the mixture and enhances BTE by 2.6% at spark timing optimal for CNG (CNG ST) and 0.6% at the optimal mixture ST (mixture ST). Analyses of the rate of heat release (ROHR), temperature, and pressure increase in the cylinder were carried out using utility BURN in AVL BOOST software.

Combustion characteristics of briquette fuels from sorghum panicle-pearl millets using cassava starch binder.

The utilization of agricultural wastes is an attractive and viable option to reduce the environmental pollution and reverse the over-exploitation of fossil fuels. Now-a-days, the usage of fossil fuels has increased manifold causing twin serious problems such as depletion of limited source of fossil fuels and increase in environmental pollution with major consequences. In this study, briquettes were produced using sorghum panicles (SP) and pearl millet (PM) with different ratios (100:0, 10:90, 20:80, 30:70, 40:60, 50:50, 60:40, 70:30, 80:20, 90:10 and 0:100) using cassava starch as a binder with a planned compacting pressure level (200kN) by exploring hydraulic compression method. The proximate parameters such as water content, level of fixed carbon, ash and volatile matter were determined using American Society for Testing and Materials (ASTM) standard procedures. The elemental analyses (SEM/EDAX) which include carbon (C), oxygen (O), potassium (K), calcium (Ca), chlorine (Cl), sulphur (S), phosphorus (P), aluminium (Al), silicon (Si), magnesium (Mg), cobalt (Co), iron (Fe), zinc (Zn) and sodium (K) were determined in all the briquette samples. Weight loss and optimum heating values of the samples were measured by adopting differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) respectively. In addition to that, the density and compressive strength of all the produced briquettes were determined. In comparison with pongamia-tamarind shell, sorghum panicle-pearl millet briquettes have better fuel properties. The pongamia-tamarind shell fuel has nitrogen and hydrogen whereas sorghum panicle-pearl millet has no identities on both nitrogen and hydrogen content. The occurrence of nitrogen absence is due to non-availability of NOx emissions during combustion. By the cause of more fixed carbon composition, there exists lack in hydrogen content. The sorghum panicle-pearl millet briquettes have better calorific value than pongamia-tamarind shells, and they produce better heating values. Hence, the prepared biomass briquettes are potentially good fuels that derived from agro wastes. Likewise, the determined parameters are compared with the other biomass briquettes.

IoT enabled advanced forest fire detecting and monitoring on Ubidots platform

The amount of land that we have lost during the 2019 forest fires is nearly 11.9 million hectares. The area of forest that is prone to forest fires is increasing day by day. The number of wild animals died during the forest fires is uncountable but in the recent Australian forest fires we have found that nearly a billion animals have died this includes 25,000 koalas. So, the main issue we have is can we prevent forest fires YES prevention is better than cure, but we humans are so deep in the usage of fossil fuels we need an estimated 30 years to go carbon negative. So, the immediate work we must do is to stop the spreading of forest fires the main part of stopping forest fires is the detection of forest fires. We are using ESP32 board and rain sensors, sound sensor, DHT11 sensor, PIR sensor are being used.

Global Horizontal and Direct Normal Solar Irradiance Modeling by the Machine Learning Methods Xgboost and Deep Neural Networks with CNN-LSTM Layers: A Case Study Using the GOES-16 Satellite Imagery

Restrictive legislations over the usage of fossil fuels are encouraging the research on clean and renewable energies. As a drawback, renewable energies are characterized by having random behavior, which hampers its integration on the current energy base system. Thus, solar irradiation estimation is important to a better assimilation of the renewable energies into the energy matrix. In this paper, two machine learning (ML) estimation models for global (GHI) and direct normal solar irradiance (DNI) are proposed: the first using XGBoost and the second using a hybrid convolutional neural network (CNN) with a long short-term memory (LSTM), CNN-LSTM. Both models use images from the GOES-16 satellite, taken from the city of Petrolina, Brazil. The results of the proposed models are analyzed against the reference models Copernicus Atmosphere Monitoring Service (CAMS), Solcast and the Physical Solar Model (PSM) provided by the National Solar Radiation Database (NSRDB). For GHI estimation, the PSM model reached the smallest RMSE, equal to 147.23 W/m^2, while the model CNN-LSTM was the best one to estimate DNI with a RMSE equal to 238.22 W/m^2. The proposed model managed to improve RMSE when compared against the benchmarking models by 2.89 % and 1.70 % for CNN-LSTM and XGBoost, respectively.

Optimal design and energy management of a renewable energy plant with seasonal energy storage

The exploitation of fossil fuels is undoubtedly responsible of environmental problems such as global warming and sea level rise. Unlike energy plants based on fossil fuels, energy plants based on renewable energy sources may be sustainable and reduce greenhouse gas emissions. However, they are unpredictable because of the intermittent nature of environmental conditions. For this reason, energy storage technologies are needed to meet peak energy demands thanks to the stored energy. Moreover, the renewable energy systems composing the plant must be optimally designed and operated. Therefore, this paper investigates the challenge of the optimal design and energy management of a grid connected renewable energy plant composed of a solar thermal collector, photovoltaic system, ground source heat pump, battery, one short-term thermal energy storage and one seasonal thermal energy storage. To this aim, this paper develops a methodology based on a genetic algorithm that optimally designs a 100% renewable energy plant with the aim of minimizing the electrical energy taken from the grid. The load profiles of thermal, cooling and electrical energy during a whole year are taken into account for the case study of the Campus of the University of Parma (Italy).

Systematic review and perspective on the progress of algal biofuels

In recognition of the increasing demand of energy and the worsening environmental problems linked with fossil fuels usage, algal biofuel has been proposed as one of the alternative energy sources. It has become one of the hottest topics in renewable energy field in the new century, especially over the past decade. In this review, we summarized the characteristics of different types of algae biofuels. Besides, an in-depth evaluation of the systematic cultivation and practical application of algae have been conducted. Although algal biofuel has a great potential, its unacceptably high cost limits the large-scale industrialization. In order to resolve such restrictions, feasible methods of improving the large scale production and practical application of algal biofuels are proposed. Future efforts should be focused not only on the cost reduction and innovation techniques, but also towards high value by-products to maximize economic benefits. Our results are dedicated to provide valuable references for subsequent research and guidelines on algae biofuels field.

Experimental study on catalytic pyrolysis of plastic waste using low cost catalyst

Energy generation and utilization become an index of country development. The currently using conventional energy sources are depleting at faster rate, thereby researchers are searching for a viable alternative to generate the energy. The source should be compatible with the existing engines to run and sustain eco-balance. The two severe problems facing across the world are continuous raise of plastic usage and depletion of fossil fuels. The major hurdles with the plastic waste are disposal and recycling. The disposal for land filling may cause soil contamination, environmental disturbance due to incineration both are leads to social resistance. Pyrolysis is the one effective solution to resolve the plastic waste disposal is converting the energy a Though, pyrolysis is an effective approach to extract fuel oil from waste plastic, it suffers from expensive of catalysts. In the present work, an attempt has made to address it by utilizing low cost catalyst like fly ash for pyrolysis of HDPE and LDPE plastic. Experiments were conducted on pyrolysis unit by varying the mass fraction of catalyst at 5%, 10% and 15%. It is observed that yield of maximum at 5% and it is decline with the further addition of catalyst. In contra, increase in mass fraction of catalyst reduces the reaction temperatures as well as retention times. The physiochemical properties of collected oil were measured and compared against the diesel and gasoline fuels bides in polymerized links into usable form. It offers dual solution in environmental aspects and addressing the verge fossil fuels.

Development and characterization of aluminum matrix composite reinforced with continuous stainless-steel fibers

Driven by energy conservation and environmental protection, present-day engineering applications focus on the effective usage of fossil fuels. Hence, industrial sectors perform extensive research on light-weighting of structures to improve efficiency. In this study, the aluminum matrix composite (AMC) is fabricated by reinforcing continuous stainless-steel (SS 304) fibers. The fabricated AMC is examined for its mechanical, metallurgical, and tribological properties. The results indicate a 6% enhancement in ultimate tensile strength, a 73% enhancement in hardness, and a 33% enhancement of wear resistance in developed AMC.

WITHDRAWN: A CENTRALIZED EMBEDDED CONTROLLER FOR MAXIMUM POWER POINT TRACKING IN SOLAR PHOTO VOLTAIC SYSTEM UNDER FLUCTUATING IRRADIANCE CONDITION

Abstract The best way to avoid Global warming is to minimize or nullify the usage of Fossil Fuels. Renewable Energy sources are best alternative to Fossil fuels. The solar Energy is best among other Green Energy sources since, it is available everywhere and all the day. The Maximum Power Point Tracking technique is a boom to extract Maximum possible Power from the sun's radiation. Irradiance is the situational task to be handled effectively to achieve the maximum power generation from Photo Voltaic Array modules. This paper proposes a centralized embedded controller to handle the said situation in effective way, and it proposes a Modified Centralized Decision Algorithm for Photo Voltaic System (MCDA-PVS). The two level proposed system starts with a comparative analysis ADBFOA, M-WOA based XSG model and M-EHO technique, following with the implementation of Modified Markovian Sequential Decision Making (MMSM) Algorithm. The MMSM is opting better protocol under irradiance scenario of the Sun. The complete system is coded using Math Lab Simulink and a proto type is developed using 50 Watts 12 Volts Photo Voltaic Array systems. The proto type results are matched with simulation values as well it has been compared with existing methodologies. The results produced displays better performance with superiority.

Upgrading fuel potentials of waste biomass via hydrothermal carbonization

In recent decades, massive exploitation of fossil fuels caused a growing demand for the production of energies from renewable sources. Hydrochar obtained from waste biomass via hydrothermal carbonization (HTC) possesses good potentials as a biofuel. Therefore, we performed HTC of corn cob, paulownia leaves, and olive pomace at different temperatures (180, 220, and 260oC). The main goal of this study was to comparatively evaluate the influence of HTC conditions on the structure and fuel characteristics of the obtained solids. The results showed that the yields of hydrochar decrease significantly with increasing temperature in all samples. The carbon content and higher heating value increased and reached the highest values in hydrochars obtained at 260?C, while the content of volatile matter decreased. Furthermore, the Van Krevelen diagram reveals that the transformation of feedstock to lignite-like products upon HTC was achieved. In this study, the results showed that processes of dehydration and decarboxylation during HTC provoke intensive biomass transformation and that hydrochars obtained at higher temperatures have significantly enhanced fuel properties and fewer volatiles compared to the feedstock.

Energy Production Forecasting From Solar Photovoltaic Plants Based on Meteorological Parameters for Qassim Region, Saudi Arabia

Due to the increasing cost of crude oil because of pandemic COVID-19 and global environmental threats, the exploitation of fossil fuels for power generation is discouraged. Further, the demand for electrical power is increasing drastically, and therefore, the exploitation of renewable energy resources, particularly solar photovoltaic-based technology for power generation is invigorated. However, the large-scale penetration of solar photovoltaic is becoming a major challenge in terms of stability, reliability of power when integrated with the grid. Thus, it becomes important to develop a novel approach or strategy which is useful to improve power quality, reliability, and grid stability. Solar photovoltaic power forecasting is a key tool for this new era and becoming the main component for a smart grid environment. Here, in this paper, the ensemble trees approach-based machine learning approach is utilized to forecast the solar photovoltaic power with the help of various meteorological parameters. The high-quality measured data for meteorological parameters for Qassim, Saudi Arabia is used in this research. The performance of the proposed model is evaluated with the help of statistical indices such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Square Error (MSE), Mean Absolute Percentage Error (MAPE), Training Time (TT) and found within the desired limits. To validate the obtained results a comparative analysis with other machine learning models is carried out. Moreover, the proposed research may provide the roadmap in achieving the vision 2030 of the government of Saudi Arabia.