• Energy Research
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Species persistence in the Anthropocene is dramatically threatened by global climate change. Large emissions of carbon dioxide (CO2) from human activities are driving increases in mean temperature, intensity of heatwaves, and acidification of oceans and freshwater bodies. Ectotherms are particularly sensitive to CO2-induced stressors, because the rate of their metabolic reactions, as well as their immunological performance, are affected by environmental temperatures and water pH. We reviewed and performed a meta-analysis of 56 studies, involving 1259 effect sizes, that compared oxidative status or immune function metrics between 42 species of ectothermic vertebrates exposed to long-term increased temperatures or water acidification (≥48 h), and those exposed to control parameters resembling natural conditions. We found that CO2-induced stressors enhance levels of molecular oxidative damages in ectotherms, while the activity of antioxidant enzymes was upregulated only at higher temperatures, possibly due to an increased rate of biochemical reactions dependent on the higher ambient temperature. Differently, both temperature and water acidification showed weak impacts on immune function, indicating different direction (increase or decrease) of responses among immune traits. Further, we found that the intensity of temperature treatments (Δ°C) and their duration, enhance the physiological response of ectotherms, pointing to stronger effects of prolonged extreme warming events (i.e., heatwaves) on the oxidative status. Finally, adult individuals showed weaker antioxidant enzymatic responses to an increase in water temperature compared to early life stages, suggesting lower acclimation capacity. Antarctic species showed weaker antioxidant response compared to temperate and tropical species, but level of uncertainty in the antioxidant enzymatic response of Antarctic species was high, thus pairwise comparisons were statistically non-significant. Overall, the results of this meta-analysis indicate that the regulation of oxidative status might be one key mechanism underlying thermal plasticity in aquatic ectothermic vertebrates.

Management of natural resources is pivotal for sustained economic growth—the increasing ecological footprints causing biocapacity deficit threaten the resource conversation agenda. The study identified the potential causes and consequences of natural resource depletion in a broad cross-section of 138 countries. Ecological footprints, international migrant stocks, industrial value-added, and population growth influenced natural resource capital across countries. The results show that ecological footprints, industrial value-added, and population growth are the detrimental factors of resource capital. In contrast, continued economic growth is helpful to conserve natural resources for future generations. The rise and fall in the natural resource degradation are evident in the wake of international migrants’ stocks to support an inverted U-shaped relationship between them. The Granger causality inferences confirmed the one-way linkages, running from international migrant stocks, economic growth, and population growth to natural resource degradation. It verifies migrants-led, affluence-led, and population-led resource degradation. Ecological footprints Granger causes industrial value-added across countries. The forecasting estimates suggested that economic growth would likely to influenced greater in magnitude to resource degradation by its innovation shocks of 4.791%, followed by international migrant stocks, population growth, ecological footprints, and industrial value added by their innovation shocks of 4.709%, 1.829%, 1.247%, and 0.700%, respectively. The study concludes that international migrant stocks should manage smartly, causing more resource degradation via a channel of increasing biocapacity deficit across countries.

Abstract The growing concerns of global warming and depleting oil/gas reserves have made it inevitable to seek energy from renewable energy resources. Many nations are embarking on introduction of clean/renewable solar energy for displacement of oil-produced energy. Moreover, solar photovoltaic (PV)–diesel hybrid power generation system technology is an emerging energy option since it promises great deal of challenges and opportunities for developed and developing countries. The Kingdom of Saudi Arabia (K.S.A) being enriched with higher level of solar radiation, is a prospective candidate for deployment of solar PV systems. Literature indicates that commercial/residential buildings in K.S.A. consume about 10–45% of the total electric energy generated. The aim of this study is to analyze long-term solar radiation data of Dhahran (East-Coast, K.S.A.) to assess the techno-economic feasibility of utilizing hybrid PV–diesel–battery power systems to meet the load of a typical residential building (with annual electrical energy demand of 35,120 kWh). The monthly average daily solar global radiation ranges from 3.61 to 7.96 kwh/m 2 . National Renewable Energy Laboratory's (NREL) Hybrid Optimization Model for Electric Renewable (HOMER) software has been employed to carry out the present study. The simulation results indicate that for a hybrid system composed of 4 kWp PV system together with 10 kW diesel system and a battery storage of 3 h of autonomy (equivalent to 3 h of average load), the PV penetration is 22%. The cost of generating energy (COE, US$/kWh) from the above hybrid system has been found to be 0.179 $/kWh (assuming diesel fuel price of 0.1$/l). The study exhibits that for a given hybrid configuration, the operational hours of diesel generators decrease with increase in PV capacity. The investigation also examines the effect of PV/battery penetration on COE, operational hours of diesel gensets for a given hybrid system. Concurrently, attention is focussed on un-met load, excess electricity generation, fuel savings and reduction in carbon emissions (for different scenarios such as PV–diesel without storage, PV–diesel with storage, as compared to diesel-only situation), COE of different hybrid systems, cost of PV–diesel–battery systems, etc.

Agricultural waste-based heterogeneous catalysts are emerging as efficient and green catalysts. The present study explored the agricultural waste-based heterogeneous catalyst utilized in the production of biodiesel. The plant waste is composed of organic compounds and various metals which, on combustion, produces ashes that mainly consist of various metal carbonates and oxides. The most commonly employed approach for the solid catalyst preparation from plant materials is the calcination process, and it is performed at temperatures ranging from 300 to 1200°C. It is known that the temperature employed for calcination plays a vital role in the composition and development of the morphology of the catalyst. The variation in alkalinity, porosity, and, accordingly, the catalytic activity of the catalyst is significantly influenced by the calcination temperature. It was found that the potassium present in the form of oxide and carbonate as the main constituent in such catalysts played a significant role in delivering catalytic efficacy. Therefore, a number of agricultural waste-based catalysts were reported as efficient catalysts. The selection of the catalyst may be one of the important issues for application in large-scale biodiesel production. Thus, the present study was undertaken for the preparation of a rank list among the reported catalysts by following the VIKOR (Višekriterijumsko Kompromisno Rangiranje) multicriterion decision-making approach. In this work, the ranking study was performed considering the reported optimum reaction conditions (ORCs) of biodiesel synthesis reactions. The study was conducted strictly on the basis of the parameters, viz., catalyst concentration ( C 1 ), MTOR ( C 2 ), reaction temperature ( C 3 ), reaction time ( C 4 ), and biodiesel yield ( C 5 ). The parameters are considered good if C 1 , C 2 , C 3 , and C 4 are low or minimum and if C 5 is high or maximum. The catalyst prepared from plantain peel showed the best performance and ranked as the first one followed by Musa paradisiaca peel and cocoa pod husk catalysts which are ranked second. Thus, the VIKOR method can be useful for comparison and ranking purposes if there are a large number of data, and this may be expanded for thorough study by considering more criteria which may give more fruitful results.

Abstract Industrial sustainability has gained huge attention in the scientific community owing to the concern of global warming. Establishing sustainability indicators by the application of exergy analysis can guide and motivate industrial sustainability. In this context, an attempt is made to establish sustainability indicators for the industrial sector. Different measures to improve the sustainability of the industrial sector of Bangladesh are also discussed. Based on the energy consumption data from the year 2000–2015, energy, exergy, and sustainability analyses are performed. It is found that the energy efficiency varies from 55.01% to 59.67% and exergy efficiency varies from 53.11% to 56.97%. Exergy efficiency is found to be at lower side due to the accounting of irreversibility. Various sustainability indicators such as sustainability index, depletion number, exergetic renewable share, cumulative exergy loss, and non-renewable exergetic share have been studied as well. It is observed that depletion numbers vary from 43% to 45% and the sustainability index varies from 2.21 to 2.32. Non-renewable exergetic share is as high as 98% and maximum cumulative exergy loss is found to be 217.3 PJ in 2015. Improvement potential shows a continuous increase from 22.75% in 2000 to 101.89% in 2015. Waste heat recovery, energy audit, waste minimization, and adopting renewable energy sources are recommended to increase the efficiency and sustainability of this sector. The outcome of this study reveals that exergy analysis is an effective technique to develop energy conservation policies for this sector.

Renewable electricity generation not only provides affordable and emission-free electricity but also introduces additional complexity in the day-ahead planning procedure. To address the stochastic nature of renewable generation, system operators must schedule enough controllable generation to have the flexibility required to compensate unavoidable real-time mismatches between the production and consumption of electricity. This flexibility must be scheduled ahead of real-time and comes at a cost, which should be minimized without compromising the operational reliability of the system. Energy storage facilities, such as pumped hydro energy storage (PHES), can respond quickly to mismatches between demand and generation. Hydraulic constraints on the operation of PHES must be taken into account in the day-ahead scheduling problem, which is typically not done in deterministic models. Stochastic optimization enhances the procurement of flexibility, but requires more computational resources than conventional deterministic optimization. This paper proposes a deterministic and an interval unit commitment formulation for the co-optimization of controllable generation and PHES, including a representation of the hydraulic constraints of the PHES. The proposed unit commitment (UC) models are tested against a stochastic UC formulation on a model of the Belgian power system to compare the resulting operational cost, reliability, and computational requirements. The cost-effective regulating capabilities offered by the PHES yield significant operational cost reductions in both models, while the increase in calculation times is limited.

In Saudi Arabia, housing projects account for almost half of the total electricity consumed by the construction industry because of the large number of housing projects compared to other types of buildings. This paper proposes a quantitative approach using a multiple linear regression assessment model to predict the energy cost and environmental cost of housing building in Saudi Arabia. It was developed to assist house owners in Saudi Arabia in estimating the monthly energy cost and associated operational carbon cost according to several predictor parameters. Based on related literature, these parameters were reviewed and discussed by experts from the Ministry of Housing. They included building location, wall type, number of occupants, window type, envelope insulation, building age, building area, number of air-conditioning units and their systems, and lighting system. The model development process included five main stages: collecting the energy and carbon cost data from completed operating housing units, categorizing the collected data based on parameters, diagnosing the quality of gathered data and filtering outlier data if any, building and generating a model, and lastly, testing and validating the model. More than 77 datasets were collected across the country during different times of the year. The findings of this study reveal that the relationship between the number of users and the building area with the energy cost is significant and that the number of users is more correlated to the energy cost than the age of the building or the number of central air conditioners installed. Moreover, the results show that the developed model has the ability to predict energy and carbon costs with high accuracy. The developed model serves as a decision support tool for householders and decision makers in the Ministry of Housing to control the predicted parameters. This would be beneficial for the housing unit owners for allocating constrained budgets.

Supercritical heat transfer has already been applied for decades, as it has several benefits such as improved thermal efficiency of the thermodynamic cycle. Accurate knowledge about supercritical heat transfer and pressure drop of the different working fluids is required to design the heat exchangers and other components used in these systems. In literature, supercritical heat transfer of water and CO2 has already been widely investigated, the research involving refrigerants (for their application in low-temperature heat conversion systems) is however rather scarce. This paper gives an overview of the existing research on supercritical heat transfer. An overview of the applications, general characteristics and the main findings for water and other fluids are summarized. Due to the sharp variations in thermophysical properties, heat transfer and pressure drop cannot be accurately predicted on a single-phase based approach only. An in-detail review of the current research and status of knowledge about supercritical heat transfer of refrigerants is presented. The effect of the different investigated refrigerants and operating parameters on heat transfer and pressure drop, both for heating and cooling applications, is discussed. The remaining gaps in literature are highlighted, which include studies involving larger diameter tubes, horizontal flow, cooling heat transfer and pressure drop estimations and creation of a wider database for a more general correlation development and measurements on newer refrigerants (with low Global Warming Potentials) as these will become increasingly important in the near future. In addition, advances in numerical research should focus on development of suitable turbulence models. Overall, further improving the basic understanding of the fluid structure and occurrence of deteriorated heat transfer, as well as forming reliable models for the thermophysical properties are key in future efforts.