Pub Date : 2025-12-09DOI: 10.1016/j.nexus.2025.100618
Mary Taiwo Akano, Bhekumuzi Prince Gumbi, Olatunde Stephen Olatunji
Advanced oxidation procedures using heterogeneous semiconductor photocatalysts have been regarded as one of the most promising approaches for the remediation of environmental pollution. In this study, hexagonal boron nitride (BN) was synthesized using the chemical vapor deposition method, and to further improve its photocatalytic properties, nitrogen-doped reduced graphene oxide (NRGO) was composited. This was achieved by varying the ratios via hydrothermal synthesis at 180 °C for 12 h to form BNNRGO nanocomposites, which were used for the photocatalytic degradation of perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA). These composites were characterized using FTIR, SEM-EDX, UV–VIS, and Raman spectroscopy to investigate their physicochemical and optical properties. The as-synthesized BNNRGO (1–3) photocatalyst ratio achieved 56% removal efficiency of PFOA and 82% of PFOS after 150 min of irradiation. The efficiency of the photocatalyst was determined by optimizing catalyst dosage and pH. Optimal degradation of 72% PFOA and 99% PFOS was achieved at a pH of 2 and a catalyst dosage of 100 mg. A decrease was observed with an increase in pH from 8 to 10, where PFOA decreased from 72% to 18% and PFOS decreased from 99% to 51%. The phytotoxicity of the degradation products shows no phytotoxic effects on Lactuca sativa. Thus, the degradation pathway for PFOA and PFOS by BNNRGO nanocomposites was attributed to the hole-initiated reaction.
{"title":"Synergistic enhancement of the photocatalytic properties of boron nitride using nitrogen-doped reduced graphene oxide for the degradation of perfluoroalkyl substances","authors":"Mary Taiwo Akano, Bhekumuzi Prince Gumbi, Olatunde Stephen Olatunji","doi":"10.1016/j.nexus.2025.100618","DOIUrl":"10.1016/j.nexus.2025.100618","url":null,"abstract":"<div><div>Advanced oxidation procedures using heterogeneous semiconductor photocatalysts have been regarded as one of the most promising approaches for the remediation of environmental pollution. In this study, hexagonal boron nitride (BN) was synthesized using the chemical vapor deposition method, and to further improve its photocatalytic properties, nitrogen-doped reduced graphene oxide (NRGO) was composited. This was achieved by varying the ratios via hydrothermal synthesis at 180 °C for 12 h to form BN<img>NRGO nanocomposites, which were used for the photocatalytic degradation of perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA). These composites were characterized using FTIR, SEM-EDX, UV–VIS, and Raman spectroscopy to investigate their physicochemical and optical properties. The as-synthesized BN<img>NRGO (1–3) photocatalyst ratio achieved 56% removal efficiency of PFOA and 82% of PFOS after 150 min of irradiation. The efficiency of the photocatalyst was determined by optimizing catalyst dosage and pH. Optimal degradation of 72% PFOA and 99% PFOS was achieved at a pH of 2 and a catalyst dosage of 100 mg. A decrease was observed with an increase in pH from 8 to 10, where PFOA decreased from 72% to 18% and PFOS decreased from 99% to 51%. The phytotoxicity of the degradation products shows no phytotoxic effects on <em>Lactuca sativa</em>. Thus, the degradation pathway for PFOA and PFOS by BN<img>NRGO nanocomposites was attributed to the hole-initiated reaction.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"21 ","pages":"Article 100618"},"PeriodicalIF":9.5,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799035","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}
Pub Date : 2025-12-09DOI: 10.1016/j.nexus.2025.100615
Athanasia Orfanou , Eleftheria Klontza , Stergios Vakalis , Irene Voukkali , Antonis A. Zorpas , Demetris F. Lekkas
Hospitality sector is a crucial industry for Greek and global economy which applies environmental pressure through services such as accommodation, food and waste management. This study proposes a methodology for the calculation of the carbon footprint during hotel operation by considering four main domains: energy consumption, propane gas consumption (used for meal preparation), hotel waste and food waste. A 5-star resort hotel in Northern Greece was used as a pilot study. Reports on energy consumption were provided through electricity meters installed in the hotel, while data on the quantities of waste and the existing management practices were collected through staff interviews and questionnaires. Emissions (CO₂eq) were calculated using RETScreen, the average-data method and emission factors. The results demonstrate that energy consumption is responsible for the 81 % of CO2eq emissions/ guest night, followed by emissions from food waste (11 %), waste (5 %), and propane gas used in the kitchen which contributes the least (3 %) in total emissions. Different scenarios were analysed to evaluate sustainable practices such as Renewable Energy Sources penetration, food waste composting and increasing recycling and their contribution to the reduction of total emissions. Scenario analysis showed that solar energy use could reduce total emissions by 36 %, while it is underlined that the application of sustainable waste management practices, which are often easier and less costly than energy efficiency improvements, could lead up to 15 % reduction of overall emissions, reducing them to 25.79 kgCO2eq/guest-night. The combination of all the proposed scenarios could lead to a total reduction of 47.45 % of hotel emissions.
{"title":"Introducing waste generation as a factor affecting carbon footprint in hotel operation and assessment of reduction practices","authors":"Athanasia Orfanou , Eleftheria Klontza , Stergios Vakalis , Irene Voukkali , Antonis A. Zorpas , Demetris F. Lekkas","doi":"10.1016/j.nexus.2025.100615","DOIUrl":"10.1016/j.nexus.2025.100615","url":null,"abstract":"<div><div>Hospitality sector is a crucial industry for Greek and global economy which applies environmental pressure through services such as accommodation, food and waste management. This study proposes a methodology for the calculation of the carbon footprint during hotel operation by considering four main domains: energy consumption, propane gas consumption (used for meal preparation), hotel waste and food waste. A 5-star resort hotel in Northern Greece was used as a pilot study. Reports on energy consumption were provided through electricity meters installed in the hotel, while data on the quantities of waste and the existing management practices were collected through staff interviews and questionnaires. Emissions (CO₂eq) were calculated using RETScreen, the average-data method and emission factors. The results demonstrate that energy consumption is responsible for the 81 % of CO<sub>2</sub>eq emissions/ guest night, followed by emissions from food waste (11 %), waste (5 %), and propane gas used in the kitchen which contributes the least (3 %) in total emissions. Different scenarios were analysed to evaluate sustainable practices such as Renewable Energy Sources penetration, food waste composting and increasing recycling and their contribution to the reduction of total emissions. Scenario analysis showed that solar energy use could reduce total emissions by 36 %, while it is underlined that the application of sustainable waste management practices, which are often easier and less costly than energy efficiency improvements, could lead up to 15 % reduction of overall emissions, reducing them to 25.79 kgCO<sub>2</sub>eq/guest-night. The combination of all the proposed scenarios could lead to a total reduction of 47.45 % of hotel emissions.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"21 ","pages":"Article 100615"},"PeriodicalIF":9.5,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145927134","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}
Pub Date : 2025-12-07DOI: 10.1016/j.nexus.2025.100610
Mohammed E.B. Abdalla , Osama Ayadi , Aseel Al Omari , Bilal Rinchi , Jawad T. Al-Bakri
Agrivoltaics (AV), the co-location of solar photovoltaic energy generation and agricultural farming, directly addresses the water-energy-food nexus and associated security challenges. Maximizing land efficiency is a long-standing practice, and AV presents an untapped opportunity to optimize land use in countries struggling with water, energy, or food security. Despite its promise, AV potential remains unexplored in countries that could benefit the most, particularly those in the Middle East & North Africa (MENA) region. While AV suitability has been studied in many countries, no region-wide, quantitative assessment exists for the MENA region, despite its acute resource constraints. This study is the first to quantify AV suitability across the MENA region, expressed as a proportion of national agricultural land, using a Geographic Information System (GIS)-based weighted overlay analysis. The method integrated openly available datasets on solar irradiance, land cover, slope, and agricultural land distribution, providing a consistent-resolution assessment at regional and national scales. Results show that in the absence of solar radiation limitations, AV-suitable areas almost perfectly overlap with agriculturally suitable areas, yielding ranges of 74–100% under a conservative scenario and 94–100% under an optimistic scenario. Results from a control set of countries (UK, JPN, ECU, SWZ) exhibited substantially lower overlap supporting these findings. These findings highlight the immense AV potential in the MENA region and demonstrate the scalability of this open-dataset approach, providing a foundation that encourages detailed crop-specific studies and pilot projects at localized scales.
{"title":"A pathway to food and energy security: Agrivoltaic potential in the MENA region","authors":"Mohammed E.B. Abdalla , Osama Ayadi , Aseel Al Omari , Bilal Rinchi , Jawad T. Al-Bakri","doi":"10.1016/j.nexus.2025.100610","DOIUrl":"10.1016/j.nexus.2025.100610","url":null,"abstract":"<div><div>Agrivoltaics (AV), the co-location of solar photovoltaic energy generation and agricultural farming, directly addresses the water-energy-food nexus and associated security challenges. Maximizing land efficiency is a long-standing practice, and AV presents an untapped opportunity to optimize land use in countries struggling with water, energy, or food security. Despite its promise, AV potential remains unexplored in countries that could benefit the most, particularly those in the Middle East & North Africa (MENA) region. While AV suitability has been studied in many countries, no region-wide, quantitative assessment exists for the MENA region, despite its acute resource constraints. This study is the first to quantify AV suitability across the MENA region, expressed as a proportion of national agricultural land, using a Geographic Information System (GIS)-based weighted overlay analysis. The method integrated openly available datasets on solar irradiance, land cover, slope, and agricultural land distribution, providing a consistent-resolution assessment at regional and national scales. Results show that in the absence of solar radiation limitations, AV-suitable areas almost perfectly overlap with agriculturally suitable areas, yielding ranges of 74–100% under a conservative scenario and 94–100% under an optimistic scenario. Results from a control set of countries (UK, JPN, ECU, SWZ) exhibited substantially lower overlap supporting these findings. These findings highlight the immense AV potential in the MENA region and demonstrate the scalability of this open-dataset approach, providing a foundation that encourages detailed crop-specific studies and pilot projects at localized scales.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"21 ","pages":"Article 100610"},"PeriodicalIF":9.5,"publicationDate":"2025-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798688","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}
Pub Date : 2025-12-07DOI: 10.1016/j.nexus.2025.100611
Ridvan Aydin , Abdul Ghani Olabi , Sameh Tawfiq AlShihabi , Lina Abu Lail
Ensuring an optimal electricity mix is essential for policymakers seeking to meet rising electricity demand, foster economic development and job creation, mitigate the impact of global warming, and promote renewable energy adoption. However, the economic and environmental impacts of energy resources have not been well addressed in developing existing optimal electricity mix models. This study introduces a multi-objective optimization model to establish an optimal sustainable electricity mix in the United Arab Emirates (UAE) through 2050 while simultaneously minimizing the total cost and CO2 emissions released in electricity generation from different energy sources. The proposed model incorporates the retirement of old natural gas power plants, promoting a shift towards renewable energy. The non-dominated sorting genetic algorithm II (NSGA-II) is adopted to obtain Pareto optimal solutions for the UAE’s electricity mix until 2050. The findings indicate that solar photovoltaic energy will dominate future capacity, followed by natural gas and nuclear energy, potentially reducing CO2 emissions to below 200 gCO2/kWh by 2050. This represents a substantial reduction from the UAE’s present gas-dominated system and brings it below the current levels of some major European economies, such as Germany (344 gCO2/kWh in 2024). The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to select the most sustainable electricity mix from the Pareto set. Unlike previous models, this study uniquely integrates power plant retirement schedules, ensuring peak demand reliability, and a combined NSGA-II–TOPSIS framework to offer a novel and policy-relevant approach to sustainable electricity mix planning.
{"title":"Sustainable electricity mix planning for the United Arab Emirates using a multi-objective optimization modeling","authors":"Ridvan Aydin , Abdul Ghani Olabi , Sameh Tawfiq AlShihabi , Lina Abu Lail","doi":"10.1016/j.nexus.2025.100611","DOIUrl":"10.1016/j.nexus.2025.100611","url":null,"abstract":"<div><div>Ensuring an optimal electricity mix is essential for policymakers seeking to meet rising electricity demand, foster economic development and job creation, mitigate the impact of global warming, and promote renewable energy adoption. However, the economic and environmental impacts of energy resources have not been well addressed in developing existing optimal electricity mix models. This study introduces a multi-objective optimization model to establish an optimal sustainable electricity mix in the United Arab Emirates (UAE) through 2050 while simultaneously minimizing the total cost and CO<sub>2</sub> emissions released in electricity generation from different energy sources. The proposed model incorporates the retirement of old natural gas power plants, promoting a shift towards renewable energy. The non-dominated sorting genetic algorithm II (NSGA-II) is adopted to obtain Pareto optimal solutions for the UAE’s electricity mix until 2050. The findings indicate that solar photovoltaic energy will dominate future capacity, followed by natural gas and nuclear energy, potentially reducing CO<sub>2</sub> emissions to below 200 gCO<sub>2</sub>/kWh by 2050. This represents a substantial reduction from the UAE’s present gas-dominated system and brings it below the current levels of some major European economies, such as Germany (344 gCO<sub>2</sub>/kWh in 2024). The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to select the most sustainable electricity mix from the Pareto set. Unlike previous models, this study uniquely integrates power plant retirement schedules, ensuring peak demand reliability, and a combined NSGA-II–TOPSIS framework to offer a novel and policy-relevant approach to sustainable electricity mix planning.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"21 ","pages":"Article 100611"},"PeriodicalIF":9.5,"publicationDate":"2025-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712479","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}
Pub Date : 2025-12-01DOI: 10.1016/j.nexus.2025.100603
Hari Kumar suberi
Innovation in the Agri-economy face challenges due to insufficient policy instruments that support closed-loop energy and material metabolism for rural development. Implementing the Research-through-Design (RtD) approach within the Analysis–Projection–Synthesis framework, and supported by the Vester Sensitivity software tool, the innovative Agri-economy is analysed in detail by calculating non-linear normative values based on eighteen identified global variables: Energy sources, Agriculture farming, Transport Service, Technology Innovation, Local Climate, Incubation Centre, Recycling Service, Market Growth, Financial Services, Built Environment, Political Influence, Community Participation, Environment Protection, Forest Management, Infrastructure Availability, Enabling Conditions, Soil Quality, and Water Availability.
The normative assessment and scenario projection indicate that the integration of three key technologies—pyrolysis of dry biomass, anaerobic digestion of wet biomass, and Agri-PV systems—can enable closed-loop material and energy flow management, with the potential to add value to the Agri-economy. The observation of the system’s self-regulating behaviour, achieved by modifying the negative feedback cycle using ‘Technology Innovation’ as the starting variable, shows that all system variables reach saturation after 32 simulation rounds. Assuming each simulation round represents one year, this indicates that the impact of the intervention becomes fully evident only after 32 years. However, the study presents multiple alternative interventions corresponding to different policy choices, which may serve as additional research directions in the future
{"title":"Innovation ecosystem in agriculture economy","authors":"Hari Kumar suberi","doi":"10.1016/j.nexus.2025.100603","DOIUrl":"10.1016/j.nexus.2025.100603","url":null,"abstract":"<div><div>Innovation in the Agri-economy face challenges due to insufficient policy instruments that support closed-loop energy and material metabolism for rural development. Implementing the Research-through-Design (RtD) approach within the Analysis–Projection–Synthesis framework, and supported by the Vester Sensitivity software tool, the innovative Agri-economy is analysed in detail by calculating non-linear normative values based on eighteen identified global variables: Energy sources, Agriculture farming, Transport Service, Technology Innovation, Local Climate, Incubation Centre, Recycling Service, Market Growth, Financial Services, Built Environment, Political Influence, Community Participation, Environment Protection, Forest Management, Infrastructure Availability, Enabling Conditions, Soil Quality, and Water Availability.</div><div>The normative assessment and scenario projection indicate that the integration of three key technologies—pyrolysis of dry biomass, anaerobic digestion of wet biomass, and Agri-PV systems—can enable closed-loop material and energy flow management, with the potential to add value to the Agri-economy. The observation of the system’s self-regulating behaviour, achieved by modifying the negative feedback cycle using ‘Technology Innovation’ as the starting variable, shows that all system variables reach saturation after 32 simulation rounds. Assuming each simulation round represents one year, this indicates that the impact of the intervention becomes fully evident only after 32 years. However, the study presents multiple alternative interventions corresponding to different policy choices, which may serve as additional research directions in the future</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"20 ","pages":"Article 100603"},"PeriodicalIF":9.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618183","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}
Pub Date : 2025-12-01DOI: 10.1016/j.nexus.2025.100590
Hasan Masrur , Ali T. Al-Awami , Yasser Almoghathawi
The increasing global water scarcity and energy supply disruptions pose substantial challenges to water-energy infrastructure resilience. While most previous studies addressed either the economic operation or resilience of water-energy systems separately, this work uniquely integrates reverse osmosis (RO) desalination, renewable-rich microgrid optimization, and quantitative resilience assessment within a unified Mixed-Integer Linear Programming (MILP) and Kaplan–Meier (KM) survival analysis framework. This integration fills a critical research gap in modeling how High-Impact Low- Probability (HILP) events jointly affect both water and power subsystems. The proposed model minimizes lifecycle costs while evaluating system survivability under extreme disruptions, incorporating photovoltaic (PV) generation, combined heat and power (CHP) units, battery storage, and grid interactions. Simulation results for a hospital-scale case study show an approximately 13 % reduction in total operating cost and a 22 % improvement in the resilience index relative to a baseline without desalination integration. The findings demonstrate that coupling desalination with renewable-rich microgrids significantly enhances both economic efficiency and system resilience under HILP scenarios, offering a robust framework for sustainable, resilient water-energy systems.
{"title":"Modeling and operation of water-energy microgrids considering resilience assessment","authors":"Hasan Masrur , Ali T. Al-Awami , Yasser Almoghathawi","doi":"10.1016/j.nexus.2025.100590","DOIUrl":"10.1016/j.nexus.2025.100590","url":null,"abstract":"<div><div>The increasing global water scarcity and energy supply disruptions pose substantial challenges to water-energy infrastructure resilience. While most previous studies addressed either the economic operation or resilience of water-energy systems separately, this work uniquely integrates reverse osmosis (RO) desalination, renewable-rich microgrid optimization, and quantitative resilience assessment within a unified Mixed-Integer Linear Programming (MILP) and Kaplan–Meier (KM) survival analysis framework. This integration fills a critical research gap in modeling how High-Impact Low- Probability (HILP) events jointly affect both water and power subsystems. The proposed model minimizes lifecycle costs while evaluating system survivability under extreme disruptions, incorporating photovoltaic (PV) generation, combined heat and power (CHP) units, battery storage, and grid interactions. Simulation results for a hospital-scale case study show an approximately 13 % reduction in total operating cost and a 22 % improvement in the resilience index relative to a baseline without desalination integration. The findings demonstrate that coupling desalination with renewable-rich microgrids significantly enhances both economic efficiency and system resilience under HILP scenarios, offering a robust framework for sustainable, resilient water-energy systems.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"20 ","pages":"Article 100590"},"PeriodicalIF":9.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618265","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}
Pub Date : 2025-12-01DOI: 10.1016/j.nexus.2025.100587
Soliman Gad , Mahmoud A. El-Shazly , Ayman H.A. Eissa , Kamal I. Wasfy , Mohammad M.H. Khan , Mohammed Al-Shehri , Mahmoud Moustafa , Mohamed E. Abd El-Hack , Alaa Awny
This study employed an integrated methodology to evaluate the sustainability performance of a biogas-based heating system within a commercial-scale broiler house under real winter conditions in Egypt. A naturally ventilated 24 m² broiler house was equipped with a completely integrated environmental control system (ventilation, lighting, evaporative cooling, and dual heating modes). Poultry litter and farm residues were co-digested in optimized proportions with different concentrations of rumen starters to achieve maximum biogas production. The optimal combination (75% poultry litter + 25% residues + 50% starter) was then employed to substitute electric heating in the poultry house with two ventilation time intervals (3 and 5 min). The combined system resolved waste management, renewable energy production, and environmental regulation in parallel. Maximum daily biogas yield was 25.6 L/day with up to 85.6% methane content providing thermal efficiencies of 850 MJ/day. Biogas heating provided thermal stability and reduced temperature–humidity index scores compared to electric heating, especially with 5-min ventilation, enhancing bird welfare. Broilers reached 10% higher final body weight (2.4 kg) and 25% improved feed conversion ratio (1.2) compared to electric heating. Total and specific energy utilization decreased to 1.4 kWh and 0.6 kWh/kg, respectively, while production cost decreased by up to 30% and the net profit increased to 0.80 USD/kg. By on-site valorization of waste, renewable energy supply, and climate optimization, this study demonstrates a novel, field-scale strategy to sustainable poultry production. The findings affirm that biogas technology could consistently counteract dependence on fossil fuels, lower the expense, and increase productivity, presenting an expandable pathway toward circular and climate-resilient livestock farming.
{"title":"Evaluation of biogas as sustainable heating alternative for poultry houses: Effects on production performance and energy efficiency","authors":"Soliman Gad , Mahmoud A. El-Shazly , Ayman H.A. Eissa , Kamal I. Wasfy , Mohammad M.H. Khan , Mohammed Al-Shehri , Mahmoud Moustafa , Mohamed E. Abd El-Hack , Alaa Awny","doi":"10.1016/j.nexus.2025.100587","DOIUrl":"10.1016/j.nexus.2025.100587","url":null,"abstract":"<div><div>This study employed an integrated methodology to evaluate the sustainability performance of a biogas-based heating system within a commercial-scale broiler house under real winter conditions in Egypt. A naturally ventilated 24 m² broiler house was equipped with a completely integrated environmental control system (ventilation, lighting, evaporative cooling, and dual heating modes). Poultry litter and farm residues were co-digested in optimized proportions with different concentrations of rumen starters to achieve maximum biogas production. The optimal combination (75% poultry litter + 25% residues + 50% starter) was then employed to substitute electric heating in the poultry house with two ventilation time intervals (3 and 5 min). The combined system resolved waste management, renewable energy production, and environmental regulation in parallel. Maximum daily biogas yield was 25.6 L/day with up to 85.6% methane content providing thermal efficiencies of 850 MJ/day. Biogas heating provided thermal stability and reduced temperature–humidity index scores compared to electric heating, especially with 5-min ventilation, enhancing bird welfare. Broilers reached 10% higher final body weight (2.4 kg) and 25% improved feed conversion ratio (1.2) compared to electric heating. Total and specific energy utilization decreased to 1.4 kWh and 0.6 kWh/kg, respectively, while production cost decreased by up to 30% and the net profit increased to 0.80 USD/kg. By on-site valorization of waste, renewable energy supply, and climate optimization, this study demonstrates a novel, field-scale strategy to sustainable poultry production. The findings affirm that biogas technology could consistently counteract dependence on fossil fuels, lower the expense, and increase productivity, presenting an expandable pathway toward circular and climate-resilient livestock farming.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"20 ","pages":"Article 100587"},"PeriodicalIF":9.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618267","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}
Pub Date : 2025-12-01DOI: 10.1016/j.nexus.2025.100591
Jingyu Lyu , Shuhong Mo , Won-Ho Nam , Lan Zhang , Hui Sun , Siyu Yan
Water, food, and energy are essential resources for human survival and socio-economic development. The complex interconnections have positioned the Water-Food-Energy Nexus (WFEN) as a critical framework for achieving integrated and effective resource allocation, while maintaining the stable operation of coupled systems. This study, for the first time, proposes a novel WFEN-based multi-objective optimization framework that integrating system dynamics (SD) modeling, the non-dominated sorting genetic algorithm III (NSGA-III), and the weighted technique for order preference by similarity to ideal solution (TOPSIS) approach. This integrated framework enables dynamic, year-by-year optimization and comprehensive performance assessment across multiple scenarios, thereby facilitating rational resource allocation and enhancing overall system sustainability. The framework quantifies the impacts of key decision variables such as crop planting areas, irrigation quotas, and energy quotas on the system mechanisms, thereby revealing the complex coupling between feedback loops and policy regulation. A regional case study in Ningxia, northwest China, was conducted to implement and validate the proposed method. The SD model demonstrated high reliability, with simulation relative errors consistently below 10 % during the study period, indicating its suitability for representing the real-world conditions in the study area. The solution sets obtained from the multi-objective optimization exhibited substantial diversity and convergence, underscoring the effectiveness of the proposed integrated method. Under the top1 ranked solution selected by the weighted TOPSIS method, from 2011 to 2022, regional security indicators improved significantly: the Water Security Indicator (WSI) increased from 1.31 to 1.76, the Food Security Indicator (FSI) increased from 0.31 to 0.80, the Energy Security Indicator (ESI) increased from 0.51 to 1.05, and the Water-Food-Energy Security Indicator (WFESI) increased from 0.59 to 1.14. Incorporating integrated management principles into policymaking enables this study to break away from conventional single-sector policy frameworks. Moreover, by adjusting key variables that link across sectors, the proposed framework offers a promising pathway toward win-win synergies and sustainable prosperity in the regional water, agriculture, and energy systems.
{"title":"Enhancing the sustainability of the Water-Food-Energy Nexus within an optimization framework: A case study of Ningxia, Northwest China","authors":"Jingyu Lyu , Shuhong Mo , Won-Ho Nam , Lan Zhang , Hui Sun , Siyu Yan","doi":"10.1016/j.nexus.2025.100591","DOIUrl":"10.1016/j.nexus.2025.100591","url":null,"abstract":"<div><div>Water, food, and energy are essential resources for human survival and socio-economic development. The complex interconnections have positioned the Water-Food-Energy Nexus (WFEN) as a critical framework for achieving integrated and effective resource allocation, while maintaining the stable operation of coupled systems. This study, for the first time, proposes a novel WFEN-based multi-objective optimization framework that integrating system dynamics (SD) modeling, the non-dominated sorting genetic algorithm III (NSGA-III), and the weighted technique for order preference by similarity to ideal solution (TOPSIS) approach. This integrated framework enables dynamic, year-by-year optimization and comprehensive performance assessment across multiple scenarios, thereby facilitating rational resource allocation and enhancing overall system sustainability. The framework quantifies the impacts of key decision variables such as crop planting areas, irrigation quotas, and energy quotas on the system mechanisms, thereby revealing the complex coupling between feedback loops and policy regulation. A regional case study in Ningxia, northwest China, was conducted to implement and validate the proposed method. The SD model demonstrated high reliability, with simulation relative errors consistently below 10 % during the study period, indicating its suitability for representing the real-world conditions in the study area. The solution sets obtained from the multi-objective optimization exhibited substantial diversity and convergence, underscoring the effectiveness of the proposed integrated method. Under the top1 ranked solution selected by the weighted TOPSIS method, from 2011 to 2022, regional security indicators improved significantly: the Water Security Indicator (WSI) increased from 1.31 to 1.76, the Food Security Indicator (FSI) increased from 0.31 to 0.80, the Energy Security Indicator (ESI) increased from 0.51 to 1.05, and the Water-Food-Energy Security Indicator (WFESI) increased from 0.59 to 1.14. Incorporating integrated management principles into policymaking enables this study to break away from conventional single-sector policy frameworks. Moreover, by adjusting key variables that link across sectors, the proposed framework offers a promising pathway toward win-win synergies and sustainable prosperity in the regional water, agriculture, and energy systems.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"20 ","pages":"Article 100591"},"PeriodicalIF":9.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618270","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}
Pub Date : 2025-12-01DOI: 10.1016/j.nexus.2025.100606
Mohammadali Allahrabbi Shirazi, Rahim Zahedi, Hossein Yousefi, Alireza Aslani
This study assesses the environmental impacts of the energy consumption of electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) using a life cycle assessment (LCA) approach considering four temperature scenarios. The aim is to compare the environmental performance of the energy consumption of both vehicle types under different climatic conditions and to identify the most sustainable option. The functional unit for this study was set at 100 km of distance. The results show that temperature significantly affects the environmental impacts of EVs and ICEVs. EVs operating at warmer temperatures (30 °C) showed lower environmental impacts compared to those operating at colder temperatures (-7 °C). The third EV scenario with renewable wind energy at 30 °C produced 90 % less CO2 emissions than the third ICEV scenario at the same temperature (0.3318 kg CO2eq per 100 km, compared to 3.3372 kg CO2eq). In addition, EVs showed lower impacts in key categories such as human health, particulate matter formation and resource depletion. ICEV scenarios, especially at lower temperatures, showed higher greenhouse gas emissions and environmental loads. The findings suggest that electric vehicles, especially when powered by renewable energy sources and operated under optimal temperature conditions, offer significant environmental benefits over ICEVs. This study highlights the importance of considering temperature and energy sources when assessing the environmental performance of vehicles and provides valuable insights for future vehicle design and policymaking aimed at reducing the environmental impacts associated with transportation. Policy recommendations include optimizing charging infrastructure in cold regions and promoting EVs in warmer climates.
{"title":"Environmental and damage assessment of electric vehicles compared to internal combustion engine vehicles under various ambient temperature scenarios using the LCA approach","authors":"Mohammadali Allahrabbi Shirazi, Rahim Zahedi, Hossein Yousefi, Alireza Aslani","doi":"10.1016/j.nexus.2025.100606","DOIUrl":"10.1016/j.nexus.2025.100606","url":null,"abstract":"<div><div>This study assesses the environmental impacts of the energy consumption of electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) using a life cycle assessment (LCA) approach considering four temperature scenarios. The aim is to compare the environmental performance of the energy consumption of both vehicle types under different climatic conditions and to identify the most sustainable option. The functional unit for this study was set at 100 km of distance. The results show that temperature significantly affects the environmental impacts of EVs and ICEVs. EVs operating at warmer temperatures (30 °C) showed lower environmental impacts compared to those operating at colder temperatures (-7 °C). The third EV scenario with renewable wind energy at 30 °C produced 90 % less CO<sub>2</sub> emissions than the third ICEV scenario at the same temperature (0.3318 kg CO<sub>2eq</sub> per 100 km, compared to 3.3372 kg CO<sub>2eq</sub>). In addition, EVs showed lower impacts in key categories such as human health, particulate matter formation and resource depletion. ICEV scenarios, especially at lower temperatures, showed higher greenhouse gas emissions and environmental loads. The findings suggest that electric vehicles, especially when powered by renewable energy sources and operated under optimal temperature conditions, offer significant environmental benefits over ICEVs. This study highlights the importance of considering temperature and energy sources when assessing the environmental performance of vehicles and provides valuable insights for future vehicle design and policymaking aimed at reducing the environmental impacts associated with transportation. Policy recommendations include optimizing charging infrastructure in cold regions and promoting EVs in warmer climates.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"20 ","pages":"Article 100606"},"PeriodicalIF":9.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618272","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}
Pub Date : 2025-12-01DOI: 10.1016/j.nexus.2025.100598
Swapnanil SenGupta , Anshita Sachan
We revisit whether the income-renewable energy nexus is nonlinear and regime-dependent, and complement the established U-shaped income-renewable energy relationship by determining threshold income values. Using a panel of up to 189 countries over 1990–2021, we estimate a dynamic panel threshold regression that accommodates endogeneity and lagged dependence. We identify statistically significant income thresholds of $13,726 (global), $43,000 (advanced economies, AEs), and $6588 (emerging markets and developing economies, EMDEs). Below the threshold, a 1% rise in income reduces renewable energy consumption by about 0.03% globally and 0.13% in EMDEs; above the threshold, the effect turns positive (about 0.16% globally and 0.01% in EMDEs). Thus, the Renewable Energy Kuznets Curve (RKC) is confirmed. For AEs, the association is positive on both sides and markedly stronger above the threshold. Thresholds and signs remain stable across five stress tests. The cut-offs stay within narrow bands (global $15,693-$17,189; AEs $38,522-$43,521; EMDEs $4989-$6412).
{"title":"Rich enough to go green? A threshold regression analysis on the nonlinear effects of income on renewable energy demand","authors":"Swapnanil SenGupta , Anshita Sachan","doi":"10.1016/j.nexus.2025.100598","DOIUrl":"10.1016/j.nexus.2025.100598","url":null,"abstract":"<div><div>We revisit whether the income-renewable energy nexus is nonlinear and regime-dependent, and complement the established U-shaped income-renewable energy relationship by determining threshold income values. Using a panel of up to 189 countries over 1990–2021, we estimate a dynamic panel threshold regression that accommodates endogeneity and lagged dependence. We identify statistically significant income thresholds of $13,726 (global), $43,000 (advanced economies, AEs), and $6588 (emerging markets and developing economies, EMDEs). Below the threshold, a 1% rise in income reduces renewable energy consumption by about 0.03% globally and 0.13% in EMDEs; above the threshold, the effect turns positive (about 0.16% globally and 0.01% in EMDEs). Thus, the Renewable Energy Kuznets Curve (RKC) is confirmed. For AEs, the association is positive on both sides and markedly stronger above the threshold. Thresholds and signs remain stable across five stress tests. The cut-offs stay within narrow bands (global $15,693-$17,189; AEs $38,522-$43,521; EMDEs $4989-$6412).</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"20 ","pages":"Article 100598"},"PeriodicalIF":9.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618136","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号