Energy nexus最新文献

{"title":"Dynamics of urban consumption and resulting impacts on ecological footprint: A longitudinal study of Khulna, Bangladesh","authors":"Syed Riad Morshed ,&nbsp;Reshma Afroz Rimi","doi":"10.1016/j.nexus.2025.100427","DOIUrl":"10.1016/j.nexus.2025.100427","url":null,"abstract":"<div><div>This study investigated the ecological impact of citizen consumption in Khulna, the third-largest city in Bangladesh, focusing on five primary sources of carbon emissions: food consumption, shelter-related activities, mobility, goods consumption, and services. Utilizing Landsat 5 and 8 imageries, the research tracked land use changes over two decades. To estimate the carbon footprint, about 651 sample data were collected through a questionnaire survey. Biocapacity data was obtained using supervised image classification techniques in ArcGIS, with calculations conducted for 2002, 2007, 2012, 2017, and 2022 to identify trends. Results revealed that Khulna City Corporation emits approximately 0.76 million tons of carbon annually, translating to 0.209 global hectares per person. The largest emission contributors were shelter-related activities and food consumption, accounting for 41.35 % and 39.41 % of total emissions, respectively. The city's ecological footprint was 0.209 global hectares per capita, with a biocapacity of 0.076, resulting in an ecological deficit of 0.134 global hectares per person, indicating that the ecological demand exceeds the biocapacity by 2.7 times. Over the past two decades, Khulna's biocapacity declined by 0.026 global hectares per capita, from 0.1028 in 2002 to 0.076 in 2022. Overall study provides a framework for assessing consumer level carbon footprint focusing on SDGs 11 and 13 which will help policymakers, urban planners and environmentalists in strategic planning to reduce carbon footprint and increasing environmental sustainability.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100427"},"PeriodicalIF":8.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Sustainable Campus Energy Management: A Comprehensive Review of Energy Management, Predictive Algorithms, and Recommendations","authors":"Noor Islam Jasim ,&nbsp;Saraswathy Shamini Gunasekaran ,&nbsp;Nouar AlDahoul ,&nbsp;Ali Najah Ahmed ,&nbsp;Ahmed El-Shafie ,&nbsp;Mohsen Sherif ,&nbsp;Moamin A Mahmoud","doi":"10.1016/j.nexus.2025.100435","DOIUrl":"10.1016/j.nexus.2025.100435","url":null,"abstract":"<div><div>Rapid growth and challenges are likely to be experienced by energy generation, delivery, and consumption in the upcoming years, which in turn affect the economic and environmental perspectives. University buildings account for a significant portion of global energy consumption and associated CO₂ emissions, and this is expected to rise substantially in the near future. Unawareness of energy efficiency in academic buildings results in weak sustainability financially and environmentally. This paper aims to review the existing studies related to energy management, efficiency, prediction, and recommendations in university buildings. Various works and algorithms were discussed addressing the challenges and limitations in the existing systems, and proposing insights as an attempt to fill the gap in this significant research domain. Additionally, the limitations of current systems, which offer only short-term solutions, become evident over time. These systems are ineffective in the long run as they lack predictive capabilities that could guide users toward predefined savings goals, actions, recommendations, or established energy standards. The paper states that to facilitate energy efficiency and manage consumption, it is important to extract patterns of energy consumption by data modelling and predictive algorithms to achieve the ultimate goal of consumption recommending and advising. This data driven decisions can support the reduction of energy load which helps in having more sustainable infrastructure and ensures less economic and financial expansion. Practically, the main objective is to support universities to save energy, reduce electricity bills, and maintain people comfort. This paper is beneficial to researchers that have interests to conduct future studies related to energy efficiency, management, prediction, and recommendations. This review study proposes a significant solution for smart buildings that fulfils energy efficiency with minimal cost and efforts.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100435"},"PeriodicalIF":8.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143946501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced modeling of thermal screens: Maximizing energy and water savings in greenhouses","authors":"Ali Ghamari,&nbsp;Mehdi Baneshi,&nbsp;Amirhossein Fathi","doi":"10.1016/j.nexus.2025.100426","DOIUrl":"10.1016/j.nexus.2025.100426","url":null,"abstract":"<div><div>Maintaining an appropriate greenhouse microclimate for optimal plant growth often incurs significant energy costs due to heating and cooling demands. This study investigates the potential of thermal screens to minimize energy and water consumption in greenhouses. A detailed hourly thermal model was developed to simulate the thermal behavior of greenhouse components, incorporating all relevant heat transfer mechanisms. The model uniquely considers the presence of plants and their evapotranspiration processes, a crucial factor impacting energy and water usage within greenhouses. The model assessed the impact of six thermal screen materials on both heating and cooling loads, water consumption, and solar radiation transmission. Results revealed that implementing thermal screens leads to a substantial 41 % reduction in annual heating demand compared to greenhouses without screens. The impact on cooling loads varies significantly by screen type, ranging from an unfavorable 73 % increase to a beneficial 24.5 % reduction compared to conditions without screens. The white polyester screen achieved the best overall energy performance, reducing annual energy demand by 33.4 %. Additionally, the PH-66 (al) screen showed the highest water-saving potential, decreasing annual water consumption by 47 %. Moreover, the PH-super thermal screen enabled the highest solar radiation transmission to the plants<em>.</em> These findings suggest thermal screens as a promising strategy to enhance greenhouses' sustainability and economic viability, particularly in regions experiencing distinct winter and summer seasons.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100426"},"PeriodicalIF":8.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143887252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling and optimization of a hybrid photovoltaic-parabolic trough concentrated solar power plant: Technical, economic, and environmental","authors":"Montaser Mahmoud ,&nbsp;Salah Haridy ,&nbsp;Ayman Mdallal ,&nbsp;Abdul Hai Alami ,&nbsp;Mohammad Ali Abdelkareem ,&nbsp;Abdul Ghani Olabi","doi":"10.1016/j.nexus.2025.100436","DOIUrl":"10.1016/j.nexus.2025.100436","url":null,"abstract":"<div><div>This research presents detailed guidelines for modeling and optimizing an integrated photovoltaic-concentrated solar power (PV-CSP) plant using response surface methodology (RSM), tailored to the climate of Sharjah, UAE. Five factors are considered in the optimization, which are the percentage share of PV/CSP (A), PV tilt angle (B), PV spacing (C), CSP solar multiple (D), and thermal storage size (E), with corresponding ranges of 10–90% (equivalent to 10 to 90 MW), 20–40°, 1–7 m, 2.5–7.5, and 5–20 h, respectively. The research utilizes three software tools: System Advisor Model (SAM) for CSP, PV_syst for PV, and Design-Expert for RSM. Based on the analysis of variance (ANOVA), seven factors (A, C, E, D², AC, AE, and DE) are significant for energy output, while eight (A, C, D, E, AC, AD, AE, and DE) are significant for LCOE. Through multi-objective optimization aimed at maximizing energy production while minimizing LCOE and land area, the results indicate that the optimal configuration comprises 38.6% CSP and 61.4% PV. This configuration achieves an energy output of 3.64 × 10⁸ kWh/year, a LCOE of $0.033/kWh, and a land area of 743.46 acres. These results were achieved with B, C, D, and E of 27.18°, 5.45 m, 4.41, and 15.49 h, respectively.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100436"},"PeriodicalIF":8.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Valorization of grape seed residues post-oil extraction as an adsorbent for hexavalent chromium in water. Kinetics, isotherms, thermodynamics, and techno-economic analysis","authors":"Elvis G. Gonzales-Condori ,&nbsp;Dalescka G. Bejar-Aramburu ,&nbsp;Joan A. Gutierrez-Delgado ,&nbsp;José A. Villanueva-Salas ,&nbsp;Jonathan Gonzales-Condori ,&nbsp;Betty M. Salazar-Pinto","doi":"10.1016/j.nexus.2025.100437","DOIUrl":"10.1016/j.nexus.2025.100437","url":null,"abstract":"<div><div>The objective of the present research was to valorize grape seed residues post-oil extraction (GSR-POE) obtained by pressing as a potential adsorbent of Cr (VI) from simulated aqueous solutions. For this, we first compared the removal of Cr (VI) by grape seeds (GS) and GSR-POE, obtaining that GSR-POE achieves higher removal efficiency than GS. Subsequently, it was determined that, with a particle size of 75 μm of GSR-POE and pH=2, the adsorption efficiency of Cr (VI) was favored, achieving the removal of 68.76 % of a simulated aqueous solution of Cr (VI) of 100 mg/L with a GSR-POE dosage of 0.8 g/L. The kinetic study showed that the GSR-POE adsorption process best fitted the pseudo-second order model, likewise, the Langmuir isotherm best described the process resulting in a maximum adsorption capacity of 169.48 mg/g. The thermodynamic study showed that the process is endothermic and spontaneous. The mechanisms involved in the adsorption process would be chemisorption and electrostatic attraction as there is a higher adsorption at pH=2 which is lower than the point of zero charge of GSR-POE (pH_PZC= 4.95). Finally, a techno-economic analysis confirmed the economic viability and profitability of implementing a plant for GSR-POE production. In conclusion, under the conditions of this study, GSR-POE is a cost-effective and efficient adsorbent for Cr (VI) adsorption.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100437"},"PeriodicalIF":8.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing bio-hydrogen and biogas yields through optimized ultrasonic pretreatment of algal biomass for sustainable energy production","authors":"Asad A. Zaidi ,&nbsp;Sohaib Z. Khan ,&nbsp;Hamad Almohamadi ,&nbsp;Enio Pedone Bandarra Filho ,&nbsp;Noreen Sher Akbar ,&nbsp;M. Imran Khan ,&nbsp;Fahid Riaz ,&nbsp;Muhammad Farooq","doi":"10.1016/j.nexus.2025.100430","DOIUrl":"10.1016/j.nexus.2025.100430","url":null,"abstract":"<div><div>Algae are a promising resource for sustainable energy production, including biogas and bio-hydrogen. This study investigates the effect of ultrasonic (US) pretreatment on <em>Enteromorpha</em> algae to enhance biogas yields. Using response surface methodology (RSM), three key parameters—sonication time, amplitude, and liquid-to-solid ratio—were optimized, with cumulative biogas production as the response. The optimal conditions (5 min sonication, 30 % amplitude, 20:1 liquid-to-solid ratio) resulted in a maximum cumulative biogas production of 373 ml and a bio-hydrogen yield of 32.7 % (v/v). Scanning electron microscopy (SEM) revealed significant cell wall disruption, enhancing substrate availability for microbial digestion. However, prolonged sonication reduced yields due to inhibitory effects. Kinetic modeling with Modified Gompertz and Logistic Function models demonstrated faster reaction rates and higher production potentials for pretreated samples. This study highlights the potential of US pretreatment for improving the biodegradability of algae, offering an efficient and sustainable method for bioenergy production<del>.</del></div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100430"},"PeriodicalIF":8.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143887251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrathin Zinc cobalt oxide nanowalls for supercapacitive energy storage applications","authors":"Bashar Aljawrneh ,&nbsp;Borhan Aldeen Albiss ,&nbsp;Amani Al-Othman ,&nbsp;Muhammad Tawalbeh ,&nbsp;Abdelelah Alshanableh ,&nbsp;Saja Alrousan ,&nbsp;Rawan Hayajneh","doi":"10.1016/j.nexus.2025.100439","DOIUrl":"10.1016/j.nexus.2025.100439","url":null,"abstract":"<div><div>The development of efficient energy storage devices with enhanced performance and stability is crucial to advance the next generation energy applications. Supercapacitors are of particular interest due to their fast charge-discharge cycles and durability that make them ideal for portable electronic devices and renewable energy systems. While functional, supercapacitors are often fabricated from high-cost materials. This work aims at synthesizing a lower cost, supercapacitor based on ultrathin zinc-cobalt (ZC) oxide nanowalls supported on a copper tape (Cu) via a hydrothermal method. The structural and electrochemical characteristics were evaluated for energy storage applications. The scanning electron microscope (SEM) and atomic force microscope (AFM) confirmed the formation of ultrathin ZC/Cu nanowalls with a surface roughness of 233 nm, while elemental analysis (XRF) revealed the presence of 32.3 % zinc and 67.7 % cobalt. The crystallinity degree of the prepared samples was examined via X-ray diffraction (XRD) and showed enhanced properties. The electrochemical analysis demonstrated an optimum specific capacitance of 205 F/g at a scanning rate of 10 mV/s within a potential window ranging from 0.0 (V) to 0.7 (V). The galvanostatic charge-discharge (GCD) curves exhibited an asymmetric triangular-like shape. The electrochemical impedance spectroscopy (EIS) data showed a low transfer resistance of 13Ω, demonstrating efficient transport of ions at the electrolyte/electrode interface. The results reported in this work suggest that the prepared ZC/Cu materials are promising for supercapacitive energy storage applications.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100439"},"PeriodicalIF":8.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the effects of electric field treatments on crop cultivation: a game-changing sustainable energy strategy for plant pathogen eradication and boosting yield growth in agriculture, validated with an artificial intelligence approach","authors":"S.S. Jayakrishna ,&nbsp;S. Sankar Ganesh","doi":"10.1016/j.nexus.2025.100438","DOIUrl":"10.1016/j.nexus.2025.100438","url":null,"abstract":"<div><div>Discovered novel energy contact patterns in agriculture for banana crop cultivation, the power of electro-culture-based electrified farming witnessed the incredible results of plant pathogen control, which boosts banana yield growth and enhances food safety. Project E-Grow involves real-time agricultural practices, providing electrical conductivity to crops for 9 h/Day for 275 days up to the final harvest. The electrified Triangular Farming (ETF) approach delivers the effects of electrical phenomena on the termination of pathogenic nematodes. The results are validated through a computer vision-based model that improved YOLO-v8 by redesigning the c2f function and employing deep learning techniques with a self-developed Banana Pathogenic Nematode (BPN) dataset. This model achieved a precision of 85 %, a recall of 87.3 %, and an mAP50 of 81 %, scoring highly in comparison to other versions of YOLO-v8n, m, and l size. The experiment included two different (T) treatments based on power energization contact with crops. T1 used Static Electricity Treatment (SET) and T2 employed Rhizosphere Electrode Treatment (RET) with anode and cathode terminals inserted into the soil. The direct power discharging throughout the plant and soil protects the crop from parasite invasion. Significant protein increases were observed in Dissolved Organic Matter (DOM) analysis on electrified banana plants. Further, the electrified plants produced early flowering fruit bunches faster and healthier than those in non-treated (control) zones. Live controlled by the Internet of Things (IoT) using microscopy image analysis and Programmable DC Power Supply (PDPS) digital data. Comprehensively, this study discloses various electric patterns and aids farmers in employing electrified cultivation cost-effectively, offering a promising future for agriculture.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100438"},"PeriodicalIF":8.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143876954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term trends of chemical fertilizer consumption and productivity in cultivating five major crops in Iran","authors":"Saeed Sharafi ,&nbsp;Kamran Kheiralipour","doi":"10.1016/j.nexus.2025.100444","DOIUrl":"10.1016/j.nexus.2025.100444","url":null,"abstract":"<div><div>Material indicators are important in sustainable production to decrease resource use and environmental impacts and increase economic productivity. The present research aims to calculate material indicators of chemical fertilizers in crop production systems in Iran. Material intensity and productivity for nitrogen, phosphor, and potassium were calculated from 1980 to 2016. Cereal, pulse, oilseed, tuber, and fiber were the studied crops. The mean production value in all systems was 4.40 ton.ha⁻¹, which had an increasing trend from 1980 to 2016. The mean of material intensity for the fertilizers in all production systems were 2.19, 1.04, and 0.16 kg.ton⁻¹, respectively while the mean values of the material productivity were 0.52, 1.16, 13.39 ton.kg⁻¹, respectively. The productivity of all studied fertilizers had an increasing trend while it had a decreasing trend for phosphor and potassium in recent years. The results of the present research can be used to optimize fertilizer consumption and consequently decrease production costs and environmental impacts.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100444"},"PeriodicalIF":8.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wind farm capacity factor forecasting: An Australian case study","authors":"Aiman Albatayneh ,&nbsp;Ragheb AbuAlRous ,&nbsp;Merlinde Kay ,&nbsp;Ramez Abdallah ,&nbsp;Adel Juaidi ,&nbsp;Amos García-Cruz ,&nbsp;Francisco Manzano-Agugliaro","doi":"10.1016/j.nexus.2025.100422","DOIUrl":"10.1016/j.nexus.2025.100422","url":null,"abstract":"<div><div>Wind energy ranks second among all renewable energy sources in generating power. The F(v) is a common probability distribution for determining the frequency of wind speeds. When evaluating wind data, the scale and shape characteristics of the Weibull distribution should be considered. The average wind speed corresponds to the scale factor, whilst the shape parameter represents the standard deviation of the data. Several attempts have been made, using models or formula, to establish a direct link between the Weibull parameters and the capacity factor of the wind farm. Nevertheless, closer inspection of these methods reveals their error rate is much higher than real wind farm capacity factor estimates. This work aims to provide a more workable and practical approach that provides more realistic numbers by connecting the Weibull shape and scale parameters to the capacity factor. Predicting the capacity factor values for wind farms using these parameters is possible. This research examined data from a wind farm on the northwest coast of Tasmania, Australia, from July 1, 2007, to August 31, 2008. Throughout this time, the farm produced power and recorded wind speeds every ten minutes. These observations were used to compute the wind farm's actual capacity factor and average wind speed. The Weibull shape and scale parameters were then determined. Additional computations were performed to determine Weibull parameters and the capacity factor for various periods after dividing the data into half-yearly, quarterly, monthly, 10-day, 5-day, and daily intervals. These interval results show that every combination of shape and scale parameter values is associated with a certain value of the capacity factor, irrespective of the period over which the computations are performed—monthly, yearly, weekly, etc. Consequently, wind speed data available for brief periods may predict the capacity factor value for wind farms over longer time intervals.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100422"},"PeriodicalIF":8.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}