Energy nexus最新文献

{"title":"Agricultural energy transition pathways: Differential impacts of fine and coarse cereals on GHG emissions in India","authors":"Smily Thakur ,&nbsp;Baljinder Kaur Sidana ,&nbsp;Sunny Kumar ,&nbsp;Ramandeep Kumar Sharma ,&nbsp;Meetpal Singh Kukal ,&nbsp;Samanpreet Kaur ,&nbsp;Asim Biswas","doi":"10.1016/j.nexus.2025.100484","DOIUrl":"10.1016/j.nexus.2025.100484","url":null,"abstract":"<div><div>Understanding how agricultural energy use and cereal production choices—particularly between fine and coarse cereals—shape greenhouse gas (GHG) emissions is crucial for designing effective mitigation strategies in light of agriculture’s major contribution to national emissions and growing climate-induced productivity concerns. This study investigates the dynamic relationships between these factors in India using an Autoregressive Distributed Lag (ARDL) model on data spanning 1975–2019. Pre-analysis (Unit root, an ideal lag length, and co-integration testing) and post-analysis (serial correlation, heteroscedasticity, and recursive residuals) assumptions for ARDL model estimation were tested which came aligned with the research questions. The model robustness statistical diagnostic tests CUSUM (cumulative sum), CUSUMSQ (cumulative sum of squares), and variance decomposition testing were carried out and found to be satisfactory. The study aimed to provide comprehensive analysis of how different cereal types i.e. fine versus coarse cereals influence agricultural energy-emissions relationship and their long run effects on agricultural production-emission scenario of India. Our analysis reveals significant differences in the emissions impacts of different cereal types: while rice and wheat production contribute positively to emissions in the short run (0.06 % and 0.01 % respectively), coarse cereals demonstrate a substantial negative impact (−2.08 %) in the long run. The energy-emissions relationship shows increasing coupling over time, with elasticity rising from 0.02 % in the short run to 1.06 % in the long run. Variance decomposition analysis identifies rice production as the dominant contributor to emissions variability, accounting for 34.43 % of future fluctuations. These findings suggest that strategic crop diversification, particularly increased cultivation of coarse cereals, could significantly reduce agricultural emissions while maintaining food security. The study recommends a three-pronged approach i.e., investing in energy-efficient agricultural technologies, developing policy frameworks to incentivize coarse cereal adoption, and strengthening institutional mechanisms for technology transfer. These insights contribute to the development of targeted policies for sustainable agricultural energy transition in India.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100484"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657012","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":"Global energy conservation research: A systematic analysis of thematic areas, methodologies and geographic distribution","authors":"Bushra Jan ,&nbsp;Muhammad Asif ,&nbsp;Mansour Alhazmi","doi":"10.1016/j.nexus.2025.100477","DOIUrl":"10.1016/j.nexus.2025.100477","url":null,"abstract":"<div><div>Energy conservation is pivotal in addressing global sustainability and climate change challenges. Despite substantial research in this field, gaps remain in understanding regional priorities and methodological patterns. This systematic review aims to bridge that gap by synthesizing findings from 144 peer-reviewed studies, selected using PRISMA guidelines and validated through independent screening and thematic analysis. The study first explores thematic and geographical distributions, categorizing research into four primary areas: Behavioral Interventions, Policy and Governance, Educational and Awareness Campaigns, and Technological and Data-Driven Solutions. The analysis reveals that 87 % of studies focus on specific regions, with developed countries accounting for 65.6 %—highlighting strong institutional and infrastructural support—while developing countries represent 34.4 %, focusing more on culturally adapted behavioral and policy approaches. Both groups show a strong preference for mixed methods (48.8 %), though quantitative approaches are more common in developing regions (46.5 %) compared to developed ones (39 %). Qualitative methods remain underutilized, particularly in developing countries (4.7 %). The findings emphasize the urgent need for greater international collaboration and tailored policy frameworks. By promoting knowledge transfer and context-sensitive strategies, this review offers actionable insights to enhance global energy conservation efforts and advance progress toward sustainable development goals.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100477"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666057","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":"Assessing Energy Efficiency of Indian Chemical Industry: Examine the Role of Innovation and Regional Heterogeneity","authors":"Shan Mohammad ,&nbsp;Govindapuram Suresh ,&nbsp;Salman Haider","doi":"10.1016/j.nexus.2025.100476","DOIUrl":"10.1016/j.nexus.2025.100476","url":null,"abstract":"<div><div>This study aims to measure energy efficiency levels and the impact of technological innovation and regional heterogeneity on energy efficiency. Hence, we use Indian chemical industry data covering 85 firms from 2003–04 to 2018–19. First, we employ the stochastic frontier analysis (SFA) to measure total factor energy efficiency (TFEE). Second, we use truncated regression to assess the effect of innovation and other factors. Our time-varying TFEE has a mean level of 0.84. Most firms can improve their energy efficiency by 15 %. Hence, a substantial energy-saving opportunity exists in the case of the chemical industry in India. Our second-stage results suggest that firms' innovative capability accumulates over time, enabling them to achieve higher energy efficiency. Additionally, older firms perform better than younger ones in terms of TFEE. However, having facilities at different locations reduces energy efficiency, while the number of products produced does not significantly impact energy efficiency. Our study emphasises the need to consider regional heterogeneity and technological gaps when developing strategies to enhance energy efficiency at the firm level. The findings have significant implications for regulating the manufacturing sector, providing insights for policymakers and industry practitioners to design effective strategies to promote energy efficiency.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100476"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662949","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":"BIPV-driven smart vertical greenhouses: a water energy food environment nexus framework for sustainable urban agriculture","authors":"Yazdan Alvari,&nbsp;Majid Zandi,&nbsp;Ali Jahangiri,&nbsp;Mohammad Ameri,&nbsp;Aslan Gholami,&nbsp;Poroushat Shahidi,&nbsp;Seyed Ali Mousavi","doi":"10.1016/j.nexus.2025.100473","DOIUrl":"10.1016/j.nexus.2025.100473","url":null,"abstract":"<div><div>This study addresses the inefficiencies and environmental burdens of conventional urban greenhouses by experimentally evaluating a building integrated solar-powered vertical greenhouse system designed for sustainable food production. A stepwise methodology is employed, in which energy audits defined system demands, followed by real-time measurements and performance simulations of photovoltaic energy integration. Three configurations were assessed including a conventional greenhouse, a smart greenhouse powered entirely by the grid electricity, and a smart greenhouse supplied by an integrated solar energy system with grid backup. The solar-powered system achieved 86 percent annual energy self-sufficiency, supplying 20,591 kWh of electricity and requiring minimal grid support. Additionally, real-world data were used to validate a modified simulation model accounting for environmental factors such as dust accumulation and aging, achieving a performance ratio of 82.6 percent. Economically, the system demonstrated a payback period of three years and a 17 percent internal rate of return, while environmentally it reduced annual carbon dioxide emissions by 4843 kg. Additionally, the closed-loop system achieved up to 90 percent water savings. This research contributes an experimentally validated, resource-efficient model for integrating solar energy with vertical food production systems tailored to urban sustainability goals.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100473"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634023","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":"Energy efficiency assessment of drinking water treatment plants incorporating technological differences and exogenous variables","authors":"Maria Molinos-Senante ,&nbsp;Alexandros Maziotis","doi":"10.1016/j.nexus.2025.100470","DOIUrl":"10.1016/j.nexus.2025.100470","url":null,"abstract":"<div><div>Assessing the energy efficiency (EE) of drinking water treatment processes through the integration of multiple indicators is essential for a comprehensive evaluation. This study proposes two composite indicators, namely group energy efficiency (GEE) index and metafrontier energy efficiency (MEE) index to assess the energetic performance of drinking water treatment plants (DWTPs). Its quantification was conducted using Stochastic Frontier Analysis (SFA) and the metafrontier framework. The analysis includes 96 DWTPs operating in Chile, categorized into two technological groups: pressure filtration (PF) and coagulation-flocculation with rapid gravity filtration (CF-RGF). The results indicate that CF-RGF facilities exhibit higher EE, with a mean MEE index of 0.506, compared to 0.423 for PF plants. The GEE index was also higher for DWTPs employing CF-RGF compared to those using PF, with average scores of 0.606 and 0.510, respectively. Additionally, factors such as plant age, raw water source, and ownership structure significantly influence energy consumption in DWTPs. This study provides empirical evidence to support targeted energy optimization strategies, helping to reduce energy consumption and enhance energy performance in the water treatment sector.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100470"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657093","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":"Breakfast commodities and global warming effects","authors":"Miguel A. Martin-Valmayor ,&nbsp;Luis A. Gil-Alana ,&nbsp;Manuel Monge","doi":"10.1016/j.nexus.2025.100471","DOIUrl":"10.1016/j.nexus.2025.100471","url":null,"abstract":"<div><div>This paper investigates global warming in the breakfast index commodities by comparing the statistical properties of the prices of the commodities and their relationship with temperature from a regional perspective. Empirical results indicate that temperature deviations are individually mean reverting and display long memory behavior; however, in breakfast commodity prices mean reversion is only observed in the case of orange and wheat with the log prices. This evidence suggests that food commodities ares more vulnerable to shocks, with a higher exposure to the poorer population segments due to their high demand elasticity. Furthermore, the results of the cointegration analysis confirm the evidence of impact in prices of temperature deviations, especially for wheat and cocoa. For the rest of the cases, shock duration is expected to be short-lived with a smaller risk for the global economy.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100471"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657004","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":"Robust modelling of wettability for hydrogen geo-storage in sandstone formations incorporating the role of cushion gas: Application of data-driven strategies in gas-sandstone-water systems","authors":"Abolfazl Dehghan Monfared,&nbsp;Mohammad Behnamnia,&nbsp;Negin Mozafari","doi":"10.1016/j.nexus.2025.100467","DOIUrl":"10.1016/j.nexus.2025.100467","url":null,"abstract":"<div><div>As global energy demand rises, the environmental impacts of fossil fuels prompt the search for cleaner energy sources. Hydrogen has emerged as a promising alternative, with efficient underground storage being essential for its large-scale deployment. The sandstone formations are suitable, particularly with cushion gas (i.e. inert gas to maintain pressure and increase pore volume while minimizing water intrusion). In this regard, the gas-rock-brine interactions—governed by wettability and quantified via the contact angle—play a pivotal role in hydrogen trapping and mobility in porous media. This study hypothesizes that machine learning (ML) models can reliably predict contact angles under diverse subsurface conditions, thereby improving the understanding and design of hydrogen storage systems. To test this, a dataset comprising 2391 experimental data points, collected from a comprehensive review of published literature, was used to train and validate various ML models, including Extreme Learning Machine, Multilayer Perceptron optimized by different algorithm, General Regression Neural Network optimized using the Imperialist Competitive Algorithm (ICA), Least Squares Boosting (LSBoost), Least Squares Support Vector Machine, and K-Nearest Neighbors. Among these, the ICA-LSBoost model outperformed others, achieving a root mean square error of 0.5434 in training and 1.5413 in testing, along with a mean absolute error of 0.3267 and 0.9872 for training and testing, respectively. These results contribute to a better understanding of the simulation and prediction phases of the hydrogen storage process by accurately simulating contact angles and optimizing storage strategies, ultimately facilitating the efficient use of hydrogen as a clean energy source.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100467"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634025","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":"Sustainable groundnut production in arid region with drip irrigation and sulphur fertilization","authors":"Priyanka Gautam ,&nbsp;S.R. Bhunia ,&nbsp;B. Lal ,&nbsp;A. Sahoo ,&nbsp;R.K. Sawal ,&nbsp;Shantanu Rakshit ,&nbsp;V.K. Yadav ,&nbsp;S.K. Meena ,&nbsp;Ramniwas ,&nbsp;Gograj Ola ,&nbsp;Ashish Kumar Sharma ,&nbsp;V.S. Rathore","doi":"10.1016/j.nexus.2025.100491","DOIUrl":"10.1016/j.nexus.2025.100491","url":null,"abstract":"<div><div>In India, groundnut is the third most important oilseed crop after soybean and mustard; however, its productivity remains suboptimal due to inefficient irrigation scheduling and inadequate sulphur (S) nutrition. To address these constraints, a study was planned to evaluate the impact of different drip irrigation (DI) regimes based on pan evaporation (PE) levels (0.6, 0.8, 1.0 PE, and their stage-specific combinations) and graded S fertilization (0, 20, 40, and 60 kg S ha⁻¹) on growth, yield, quality, and resource use efficiency of groundnut. The results demonstrated that higher DI levels, particularly 1.0 PE and 0.8+1.0 PE (moderate irrigation during vegetative and higher during reproductive stage), significantly enhanced pod and kernel yield (up to 7-fold) and haulm yield (up to 10-fold) compared to the lowest irrigation regime (0.6 PE). Although 1.0 PE yielded the highest, the 0.8+1.0 PE treatment reduced evapotranspiration by 10.7% and saved approximately 60–70 mm of water without compromising yield, thereby improving water productivity and energy efficiency. This regime also recorded the lowest carbon footprint per unit yield (CFy), indicating better environmental performance. Sulphur fertilization had a significant influence on yield and quality parameters. While groundnut responded positively up to 60 kg S ha⁻¹, the response was most economically and environmentally efficient up to 40 kg S ha⁻¹. The 40 kg S ha⁻¹ level reduced carbon footprint by 2–3% and energy consumption by 3–4%, while providing comparable yields and higher benefit-cost ratios than 60 kg S ha⁻¹. The combination of 0.8+1.0 PE irrigation with 40 kg S ha⁻¹ emerged as the most efficient and sustainable strategy, offering a favourable balance between productivity, input use, economic returns, and environmental impact. These findings underscore the importance of optimizing irrigation and nutrient management practices for enhancing groundnut productivity, resource use efficiency, and environmental sustainability.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100491"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666060","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":"Multi-factor optimization for electric bus charging stations: Integrating electrical, social, and environmental perspectives","authors":"Mustafa Nurmuhammed ,&nbsp;Ozan Akdağ ,&nbsp;Teoman Karadağ ,&nbsp;Maged Kafafy˘","doi":"10.1016/j.nexus.2025.100500","DOIUrl":"10.1016/j.nexus.2025.100500","url":null,"abstract":"<div><div>In this study, a method that provides the optimal placement of Charging Stations (CSs) for Electric Buses (EBs) on the distribution network considering electrical, social, and environmental aspects is proposed. The parameters used in the study are power loss, voltage deviation, voltage stability index, population density, traffic density, proximity to points of interest and location cost. The energy consumption of the EBs is calculated by linear modeling method using ten parameters. To test the applicability and effectiveness of the proposed method, IEEE-33 and IEEE-69 bus systems are modified in accordance with EBs, and the distances between the stops are set as routes. Afterwards, CS placement is performed for different scenarios and power effects are shown. The power loss is decreased by 17.34 % in the 33-bus and 8.75 % in the 69-bus test systems. Accordingly, 106 and 25 kgs of CO₂ per hour can be prevented, respectively. In summary, this study provides a method that comprehensively evaluates both electrical and social-environmental factors for the optimal placement of CSs for EBs. Additionally, the practical applications of the proposed method offer valuable data for reducing power loss and CO₂ emissons, thus providing important insights for sustainable urban transportation solutions. The findings of the study can form the basis for future research on optimizing EV charging infrastructure (based on both social/environmental and electrical data) and guide policymakers and urban planners in developing more efficient and sustainable transportation networks.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100500"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666058","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":"Optimizing electrical production from renewable energy with electrochemical hybrid-energy storage system at EGAT, Mae-Moh Site","authors":"Artit Teeprueksa ,&nbsp;Atipoang Nuntaphan ,&nbsp;Yuttana Mona ,&nbsp;Xiong Shu ,&nbsp;Feng Gong ,&nbsp;Tanakorn Wongwuttanasatian ,&nbsp;Amnart Suksri ,&nbsp;Konlayutt Punyawudho","doi":"10.1016/j.nexus.2025.100468","DOIUrl":"10.1016/j.nexus.2025.100468","url":null,"abstract":"<div><div>The optimization of the renewable energy system was examined through mathematical simulations utilizing the HOMER program. The simulations were performed in alignment with the real implementations called “demonstration site”, where was effectively developed with power output of 10 kW at the Mae Moh power plant by EGAT. The energy generation from both optimized model and practical setup successfully fulfilled the energy demand throughout the year. Cost-benefit analysis showed that the optimized model had 57% lower LCOE and NPC than a demonstration site. Furthermore, the optimization was conducted to achieve higher power output within the range of 350–460 kW under dynamic load conditions, as well as within the 5 MW range for power plant. The average energy generated by the simulation over a year was sufficient for both scenarios (i.e., 254% for 460 kW and 303% for 5 MW), even under the lowest solar irradiation conditions observed from June to August. The hybrid energy storage system, which uses batteries and hydrogen, was the most cost-effective in both situations, according to LCOE and NPC. Under consistent modeling parameters (i.e., no power outages throughout a year), the LCOE for 5 MW ($0.127/kWh) is 25.73% lower than for 460 kW ($0.171/kWh). Consequently, increased power production rates lead to reduced investment and operating costs compared to lower power generation rates.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"19 ","pages":"Article 100468"},"PeriodicalIF":8.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657006","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}