Energy nexus最新文献

Development of macro and micro-nutrient rich integrated Jeevamrutha bio-fertilizer systems using rural and commercial precursors

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-03-01 DOI: 10.1016/j.nexus.2025.100402

Udaratta Bhattacharjee , Ramagopal V.S. Uppaluri

Cow dung-based bio-fertilizers often requires additional organic amendments to demonstrate the nutritional necessities for field applications. Thereby, the present study validated the need for an integrated farming technique with the readily available rural and commercial precursors (such as vermicompost, neem cake, tea waste and water hyacinth) into the cow-excreta-based Jeevamrutha organic bio-fertilizer. Hence, physio-chemical, nutritional content and microbial characteristics were targeted. The ratios of Jeevamrutha and the above-mentioned precursors were varied as 1:4 for vermicompost, 1:3 for neem cake, 1:2 for tea waste and 1:3–1:4 for water hyacinth at an ambient temperature between 12 and 38ºC during winter and summer seasons respectively. The wide range of temperature was considered to accomodate the average temperatures of summer and winter seasons of Guwahati, India. Nutritional factors such as total Kjeldahl nitrogen (TKN), ammonium nitrogen (AN) and phosphate (P) was maximum for tea waste-integrated Jeevamrutha bio-fertilizer. These respectively varied as 1.94–3.22 %, 726.8–1076.4 mg/L and 0.57–0.65 % during the winter and summer seasons. Similar nutrient trend was followed by neem cake-integrated Jeevamrutha bio-fertilizer (TKN:1.78–2.24 %; AN:623.4–873.56 mg/L and P:0.64–0.71 %) during winter and summer seasons. Phytotoxicity assay shows that desired concentration of the optimal compositional set was 50 % (v/v) and 20 % (v/v) for the seasons. Cost analysis for the bio-fertilizer systems revealed a minimal expenditure associated for tea waste (Rs. 10.56/kg) followed by water hyacinth-integrated Jeevamrutha bio-fertilizer (Rs. 12.68/kg) in comparison with the conventionally used jaggery-based Jeevamrutha bio-fertilizer (Rs. 17.3/kg). Here, jaggery refers to the product obtained as a product in rural India.

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引用次数: 0

Maintenance techniques to increase solar energy production: A review

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-17 DOI: 10.1016/j.nexus.2025.100384

Fernando Martinez-Gil , Christopher Sansom , Aránzazu Fernández-García , Alfredo Alcayde-García , Francisco Manzano-Agugliaro

This review explores advanced maintenance techniques aimed at improving solar energy production efficiency. The study analyzes the rapid growth of solar energy and the challenges posed by environmental factors such as soiling, harsh climate conditions and hotspots, which reduce photovoltaic (PV) and concentrated solar power (CSP) system performance. Predictive models for solar energy generation and soiling detection, including artificial intelligence (AI) and machine learning (ML) algorithms and Internet of Things (IoT), are discussed as means for optimizing energy production and reducing maintenance costs. It is also emphasized the role of Unmanned Aerial Vehicles (UAVs) to capture images for fault detection and failure prediction, enhancing maintenance accuracy and minimizing downtime. The study concludes by analyzing the role of these techniques to reduce water consumption in cleaning tasks, as well as solutions to increase the operational lifespan and performance of solar plants such as anti-soiling coatings, robotic cleaning systems and accurate predictive models.

{"title":"Maintenance techniques to increase solar energy production: A review","authors":"Fernando Martinez-Gil , Christopher Sansom , Aránzazu Fernández-García , Alfredo Alcayde-García , Francisco Manzano-Agugliaro","doi":"10.1016/j.nexus.2025.100384","DOIUrl":"10.1016/j.nexus.2025.100384","url":null,"abstract":"<div><div>This review explores advanced maintenance techniques aimed at improving solar energy production efficiency. The study analyzes the rapid growth of solar energy and the challenges posed by environmental factors such as soiling, harsh climate conditions and hotspots, which reduce photovoltaic (PV) and concentrated solar power (CSP) system performance. Predictive models for solar energy generation and soiling detection, including artificial intelligence (AI) and machine learning (ML) algorithms and Internet of Things (IoT), are discussed as means for optimizing energy production and reducing maintenance costs. It is also emphasized the role of Unmanned Aerial Vehicles (UAVs) to capture images for fault detection and failure prediction, enhancing maintenance accuracy and minimizing downtime. The study concludes by analyzing the role of these techniques to reduce water consumption in cleaning tasks, as well as solutions to increase the operational lifespan and performance of solar plants such as anti-soiling coatings, robotic cleaning systems and accurate predictive models.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100384"},"PeriodicalIF":8.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative analysis of environmental impact and energy consumption in sesame and mung bean production using life cycle assessment and data envelopment analysis

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-17 DOI: 10.1016/j.nexus.2025.100397

Homa Rostami , Amir Azizpanah , Rostam Fathi , Morteza Taki

The study aimed to evaluate energy consumption patterns, environmental impacts, and optimization of energy use in sesame and mung bean productions in Abdanan, Iran. Data were gathered and evaluated using surveys from 41 farmers through questionnaire and face to face interview. The results revealed that for sesame production, the energy ratio was 1.68, energy productivity was 0.067 kg MJ^-1 and specific energy was 14.48 MJ kg^-1, while for mung bean production, these values were significantly lower at 0.72, 0.049 kg MJ^-1 and 2.32 MJ kg^-1. In terms of environmental impact, sesame production exhibited fewer emissions across most of the 15 mid-point environmental indicators assessed, with mung bean production resulting in higher emissions related to ecosystem quality, human health, climate change and resource depletion; specifically, the global warming potential for producing one ton of sesame was calculated as 1459.17 kg CO_2eq compared to 2237.11 kg CO_2eq for mung bean. The primary contributor to climate change was identified as direct emissions from input usage, with reduced diesel fuel consumption in sesame farming significantly mitigating environmental impacts. Efficiency analysis using Data Envelopment Analysis (DEA) indicated that 65.85 % of mung bean production units were efficient in the Variable Returns to Scale (VRS) model and 34.15 % in the Constant Returns to Scale (CRS) model. For sesame production, these rates were 56.09 % in the VRS and 36.58 % in the CRS model. Average technical efficiency was estimated at 87.89 % for mung bean and 85.83 % for sesame. The study concludes that sesame production is more energy-efficient and environmentally friendly compared to mung bean production, suggesting that farmers should adopt practices that reduce diesel fuel consumption and optimize input usage to enhance sustainability and minimize environmental impacts. Future research could explore alternative farming practices that further improve energy efficiency and reduce greenhouse gas emissions in both crops.

{"title":"Comparative analysis of environmental impact and energy consumption in sesame and mung bean production using life cycle assessment and data envelopment analysis","authors":"Homa Rostami , Amir Azizpanah , Rostam Fathi , Morteza Taki","doi":"10.1016/j.nexus.2025.100397","DOIUrl":"10.1016/j.nexus.2025.100397","url":null,"abstract":"<div><div>The study aimed to evaluate energy consumption patterns, environmental impacts, and optimization of energy use in sesame and mung bean productions in Abdanan, Iran. Data were gathered and evaluated using surveys from 41 farmers through questionnaire and face to face interview. The results revealed that for sesame production, the energy ratio was 1.68, energy productivity was 0.067 kg MJ<sup>-1</sup> and specific energy was 14.48 MJ kg<sup>-1</sup>, while for mung bean production, these values were significantly lower at 0.72, 0.049 kg MJ<sup>-1</sup> and 2.32 MJ kg<sup>-1</sup>. In terms of environmental impact, sesame production exhibited fewer emissions across most of the 15 mid-point environmental indicators assessed, with mung bean production resulting in higher emissions related to ecosystem quality, human health, climate change and resource depletion; specifically, the global warming potential for producing one ton of sesame was calculated as 1459.17 kg CO<sub>2eq</sub> compared to 2237.11 kg CO<sub>2eq</sub> for mung bean. The primary contributor to climate change was identified as direct emissions from input usage, with reduced diesel fuel consumption in sesame farming significantly mitigating environmental impacts. Efficiency analysis using Data Envelopment Analysis (DEA) indicated that 65.85 % of mung bean production units were efficient in the Variable Returns to Scale (VRS) model and 34.15 % in the Constant Returns to Scale (CRS) model. For sesame production, these rates were 56.09 % in the VRS and 36.58 % in the CRS model. Average technical efficiency was estimated at 87.89 % for mung bean and 85.83 % for sesame. The study concludes that sesame production is more energy-efficient and environmentally friendly compared to mung bean production, suggesting that farmers should adopt practices that reduce diesel fuel consumption and optimize input usage to enhance sustainability and minimize environmental impacts. Future research could explore alternative farming practices that further improve energy efficiency and reduce greenhouse gas emissions in both crops.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100397"},"PeriodicalIF":8.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing sustainability through optimized adsorption using a novel Klason-lignin-based biosorbent derived from sugar-palm fruit shells for efficient removal of Pb(II) and Cd(II)

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-13 DOI: 10.1016/j.nexus.2025.100398

Ruka Yulia , Husni Husin , Muhammad Zaki , Nasrullah Razali , Hisbullah , Fahrizal Nasution , Ahmadi , Nurhazanah , Muhammad Lathiful Yazil , Yuliana Sy , S. Syafiie

This study investigates the isolation and application of a Klason-lignin-based biosorbent derived from sugar palm fruit shell (SPFS) waste for the adsorption of Pb(II) and Cd(II) from toxic wastewater. The SPFS waste, rich in lignocellulose, underwent pretreatment to extract lignin-containing functional groups suitable for metal ion adsorption. The biosorbent's morphology before and after adsorption was analyzed. Adsorption effectiveness was evaluated through isotherm and kinetic models, with optimal conditions determined using Box-Behnken Design and Response Surface Methodology. Maximum adsorption capacities of 31.35 mg/g for Pb(II) and 12.5 mg/g for Cd(II) were achieved. Optimal conditions, based on Box-Behnken design, were 116.535 mins, 60 mg/L concentration, and 0.5 g adsorbent mass, resulting in adsorption efficiencies of 94.48 % and 60.98 % for Pb(II) and Cd(II), respectively. This research demonstrates the potential of Klason lignin from sugar palm fruit shell (KLSPFS) as an effective biosorbent for Pb(II) and Cd(II) removal, contributing to sustainable development goals 3, 6, and 12 by promoting efficient recycling technologies for improved health, water quality, and waste reduction.

{"title":"Enhancing sustainability through optimized adsorption using a novel Klason-lignin-based biosorbent derived from sugar-palm fruit shells for efficient removal of Pb(II) and Cd(II)","authors":"Ruka Yulia , Husni Husin , Muhammad Zaki , Nasrullah Razali , Hisbullah , Fahrizal Nasution , Ahmadi , Nurhazanah , Muhammad Lathiful Yazil , Yuliana Sy , S. Syafiie","doi":"10.1016/j.nexus.2025.100398","DOIUrl":"10.1016/j.nexus.2025.100398","url":null,"abstract":"<div><div>This study investigates the isolation and application of a Klason-lignin-based biosorbent derived from sugar palm fruit shell (SPFS) waste for the adsorption of Pb(II) and Cd(II) from toxic wastewater. The SPFS waste, rich in lignocellulose, underwent pretreatment to extract lignin-containing functional groups suitable for metal ion adsorption. The biosorbent's morphology before and after adsorption was analyzed. Adsorption effectiveness was evaluated through isotherm and kinetic models, with optimal conditions determined using Box-Behnken Design and Response Surface Methodology. Maximum adsorption capacities of 31.35 mg/g for Pb(II) and 12.5 mg/g for Cd(II) were achieved. Optimal conditions, based on Box-Behnken design, were 116.535 mins, 60 mg/L concentration, and 0.5 g adsorbent mass, resulting in adsorption efficiencies of 94.48 % and 60.98 % for Pb(II) and Cd(II), respectively. This research demonstrates the potential of Klason lignin from sugar palm fruit shell (KLSPFS) as an effective biosorbent for Pb(II) and Cd(II) removal, contributing to sustainable development goals 3, 6, and 12 by promoting efficient recycling technologies for improved health, water quality, and waste reduction.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100398"},"PeriodicalIF":8.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental and computational analyses of a photovoltaic module cooled with an optimized converging channel absorber

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-12 DOI: 10.1016/j.nexus.2025.100401

Ali Radwan , Salah Haridy , Aimane Kemel , Ibrahim I. El-Sharkawy , Essam M. Abo-Zahhad

The electrical performance of photovoltaic (PV) modules under concentrated illumination significantly declines due to the substantial increase in the module's average temperature, especially in areas with elevated ambient temperatures and high levels of solar radiation, such as the Gulf region. Therefore, implementing efficient thermal management to these modules is required for achieving a lower operating temperature, longer lifespan, higher electrical energy output, and harnessing low-grade thermal energy. Converging absorbers are commonly used in PV module's cooling. However, the optimized design for these absorbers is rarely explored. This study proposes an integrated framework combining outdoor experimental testing, computational modeling, and desirability optimization through response surface methodology (RSM) to fill this gap. This integrated framework is employed to statistically evaluate the impact of the converging channel outlet height (H_out, ranging from 3 mm to 17 mm), cooling fluid velocity (from 0.007 to 0.01 m/s), adhesive material thermal conductivity (from 0.14 to 3.7 W/m·K), and cooling water inlet temperature (25 to 35 °C) at a solar concentration ratio of 3 Suns on various PV module responses. Five responses including module temperature, module temperature non-uniformity, thermal power, net electrical power, and entropy generation rate are evaluated at these ranges of the design factors. Predictive models for these five responses are developed with high coefficients of determination (R²). An analysis of variance is performed to identify the most significant factors and interactions influencing each response. Various optimization scenarios for the responses are explored. Among these, maximizing the thermal and electrical generated power can be attained by using a converging channel with H_out of 3 mm, inlet velocity of 0.0084 m/s, inlet temperature of 20 °C, and adhesive thermal conductivity of 2.94 W/m·K.

{"title":"Experimental and computational analyses of a photovoltaic module cooled with an optimized converging channel absorber","authors":"Ali Radwan , Salah Haridy , Aimane Kemel , Ibrahim I. El-Sharkawy , Essam M. Abo-Zahhad","doi":"10.1016/j.nexus.2025.100401","DOIUrl":"10.1016/j.nexus.2025.100401","url":null,"abstract":"<div><div>The electrical performance of photovoltaic (PV) modules under concentrated illumination significantly declines due to the substantial increase in the module's average temperature, especially in areas with elevated ambient temperatures and high levels of solar radiation, such as the Gulf region. Therefore, implementing efficient thermal management to these modules is required for achieving a lower operating temperature, longer lifespan, higher electrical energy output, and harnessing low-grade thermal energy. Converging absorbers are commonly used in PV module's cooling. However, the optimized design for these absorbers is rarely explored. This study proposes an integrated framework combining outdoor experimental testing, computational modeling, and desirability optimization through response surface methodology (RSM) to fill this gap. This integrated framework is employed to statistically evaluate the impact of the converging channel outlet height (H<sub>out</sub>, ranging from 3 mm to 17 mm), cooling fluid velocity (from 0.007 to 0.01 m/s), adhesive material thermal conductivity (from 0.14 to 3.7 W/m·K), and cooling water inlet temperature (25 to 35 °C) at a solar concentration ratio of 3 Suns on various PV module responses. Five responses including module temperature, module temperature non-uniformity, thermal power, net electrical power, and entropy generation rate are evaluated at these ranges of the design factors. Predictive models for these five responses are developed with high coefficients of determination (R²). An analysis of variance is performed to identify the most significant factors and interactions influencing each response. Various optimization scenarios for the responses are explored. Among these, maximizing the thermal and electrical generated power can be attained by using a converging channel with H<sub>out</sub> of 3 mm, inlet velocity of 0.0084 m/s, inlet temperature of 20 °C, and adhesive thermal conductivity of 2.94 W/m·K.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100401"},"PeriodicalIF":8.0,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance evaluation, prediction analysis and optimization of experimental ORC using artificial neural networks (ANN)

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-12 DOI: 10.1016/j.nexus.2025.100383

Diki Ismail Permana , Federico Fagioli , Maurizio De Lucia , Dani Rusirawan , Istvan Farkas

The Organic Rankine Cycle (ORC) system stands out as the most efficient solution for converting low-grade thermal energy, making it highly effective for dispersed power generation and adaptable to various heat sources, such as solar energy, geothermal, biomass, and waste-heat recovery at different temperatures. Unlike traditional Rankine cycles, ORC systems use refrigerants or mixed fluids as working fluids, which have lower boiling points than water and are environmentally friendly, allowing efficient power generation on a smaller scale and at lower temperatures (above 200°C). While many experimental studies on ORC have been conducted, significant gaps remain in accurately predicting unknown or unmeasured data and identifying optimal operating conditions. This research addresses these challenges using machine learning, specifically an artificial neural network (ANN), a self-learning and nonlinear method capable of approximating complex functions, making it ideal for ORC prediction models. The novelty of this study lies in developing a 2 kW ORC prototype and applying ANN to predict and optimize performance using 102 experimental data sets—reducing experimental resource requirements and enhancing model accuracy. Additionally, a multi-objective optimization approach is used to simultaneously maximize net output work and thermal efficiency, setting a benchmark for efficient, low-cost, and sustainable ORC system designs. The benefits of this research include advancing predictive modeling for ORC systems, improving resource efficiency, and providing insights into optimized ORC operations for real-world applications.

{"title":"Performance evaluation, prediction analysis and optimization of experimental ORC using artificial neural networks (ANN)","authors":"Diki Ismail Permana , Federico Fagioli , Maurizio De Lucia , Dani Rusirawan , Istvan Farkas","doi":"10.1016/j.nexus.2025.100383","DOIUrl":"10.1016/j.nexus.2025.100383","url":null,"abstract":"<div><div>The Organic Rankine Cycle (ORC) system stands out as the most efficient solution for converting low-grade thermal energy, making it highly effective for dispersed power generation and adaptable to various heat sources, such as solar energy, geothermal, biomass, and waste-heat recovery at different temperatures. Unlike traditional Rankine cycles, ORC systems use refrigerants or mixed fluids as working fluids, which have lower boiling points than water and are environmentally friendly, allowing efficient power generation on a smaller scale and at lower temperatures (above 200°C). While many experimental studies on ORC have been conducted, significant gaps remain in accurately predicting unknown or unmeasured data and identifying optimal operating conditions. This research addresses these challenges using machine learning, specifically an artificial neural network (ANN), a self-learning and nonlinear method capable of approximating complex functions, making it ideal for ORC prediction models. The novelty of this study lies in developing a 2 kW ORC prototype and applying ANN to predict and optimize performance using 102 experimental data sets—reducing experimental resource requirements and enhancing model accuracy. Additionally, a multi-objective optimization approach is used to simultaneously maximize net output work and thermal efficiency, setting a benchmark for efficient, low-cost, and sustainable ORC system designs. The benefits of this research include advancing predictive modeling for ORC systems, improving resource efficiency, and providing insights into optimized ORC operations for real-world applications.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100383"},"PeriodicalIF":8.0,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment of Community Gardens’ role in mitigating air pollution and expanding social opportunities: Lessons from a neighborhood with limited green infrastructure in Tehran city 评估社区花园在缓解空气污染和扩大社会机会方面的作用：德黑兰市一个绿色基础设施有限的社区的经验教训

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-11 DOI: 10.1016/j.nexus.2025.100363

Mahsa Khanpoor-Siahdarka , Mohammad Reza Masnavi

This study investigates the potential of community gardens as sustainable interventions to address environmental and social challenges in Tehran's District 10, a densely urbanized area with limited green spaces and acute socio-environmental disparities. Employing a mixed-method approach, this research integrates community surveys, chi-square analyses, and Envi-Met® simulations to assess the dual benefits of community gardens. Findings reveal significant environmental gains, including CO₂ reduction, urban heat island (UHI) mitigation, and enhanced humidity regulation, facilitated by strategically placed vegetation such as broadleaf trees and phytoremediation plants. Concurrently, social analyses highlight nuanced community preferences, with gendered trends influencing garden design and family dynamics shaping plot arrangements. These insights emphasize the role of culturally sensitive and inclusive green spaces in fostering social cohesion and well-being.

By bridging environmental metrics with socio-cultural dimensions, the study advances theoretical frameworks like Nature-Based Solutions (NbS) and urban sustainability. It offers a replicable model for integrating ecological and social benefits in socio-economically divided cities, particularly in Middle Eastern contexts. The research underscores the transformative potential of community gardens in enhancing urban resilience, informing policymakers and urban planners on evidence-based strategies for sustainable development.

{"title":"Assessment of Community Gardens’ role in mitigating air pollution and expanding social opportunities: Lessons from a neighborhood with limited green infrastructure in Tehran city","authors":"Mahsa Khanpoor-Siahdarka , Mohammad Reza Masnavi","doi":"10.1016/j.nexus.2025.100363","DOIUrl":"10.1016/j.nexus.2025.100363","url":null,"abstract":"<div><div>This study investigates the potential of community gardens as sustainable interventions to address environmental and social challenges in Tehran's District 10, a densely urbanized area with limited green spaces and acute socio-environmental disparities. Employing a mixed-method approach, this research integrates community surveys, chi-square analyses, and Envi-Met® simulations to assess the dual benefits of community gardens. Findings reveal significant environmental gains, including CO₂ reduction, urban heat island (UHI) mitigation, and enhanced humidity regulation, facilitated by strategically placed vegetation such as broadleaf trees and phytoremediation plants. Concurrently, social analyses highlight nuanced community preferences, with gendered trends influencing garden design and family dynamics shaping plot arrangements. These insights emphasize the role of culturally sensitive and inclusive green spaces in fostering social cohesion and well-being.</div><div>By bridging environmental metrics with socio-cultural dimensions, the study advances theoretical frameworks like Nature-Based Solutions (NbS) and urban sustainability. It offers a replicable model for integrating ecological and social benefits in socio-economically divided cities, particularly in Middle Eastern contexts. The research underscores the transformative potential of community gardens in enhancing urban resilience, informing policymakers and urban planners on evidence-based strategies for sustainable development.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100363"},"PeriodicalIF":8.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental investigation and economic evaluation of wind impacts on the solar panel array of a floating photovoltaic (FPV) system across different turbulence intensities

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-11 DOI: 10.1016/j.nexus.2025.100380

Krishna Debnath , Chien-Chun Hsieh , Chao-Yang Huang , Jagadish Barman , Chung-Feng Jeffrey Kuo

The increasing global demand for renewable energy and the scarcity of suitable land for large-scale photovoltaic (PV) installations have driven interest in floating photovoltaic (FPV) systems. FPV systems are being widely adopted globally as solar energy proves to be a highly efficient renewable energy source. However, these systems face challenges such as sinking or overturning in severe environmental conditions. This study investigates the aerodynamic performance and economic viability of FPV systems under different wind speeds and turbulence intensities. Using 1:50 scale models, wind tunnel experiments were conducted to represent both single-island and multi-array FPV setups. The research assessed aerodynamic properties, including drag, lift, and net pressure coefficients, to evaluate structural stability in offshore environments, particularly under extreme turbulence. The results highlight turbulence as a critical factor influencing aerodynamic force distribution, with upstream panels affecting the stability of those downstream. Structural issues like material fatigue and potential failures during extreme weather conditions were analyzed to inform design improvements. Additionally, the study identifies cost-saving opportunities through material optimization, enhancing the economic feasibility of FPV systems without sacrificing performance. Many floating bodies might be replaced with less expensive materials, which would be more cost-effective, if the floating PV system's size continues to grow.

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引用次数: 0

A critical review on combining adsorption and photocatalysis in composite materials for pharmaceutical removal: Pros and cons, scalability, TRL, and sustainability

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-11 DOI: 10.1016/j.nexus.2025.100396

Sajad Ahmadi , Jennyffer Martinez Quimbayo , Velma Beri Kimbi Yaah , Sergio Botelho de Oliveira , Satu Ojala

Pharmaceuticals have been detected in water matrices with different concentrations raising the concerns about their effects on the environment and human health. Despite these concerns there are no clear regulations established by governments about the maximum accepted values of these pollutants in potable water. It is important that stake holders establish regulatory limits to the permitted concentration of pharmaceuticals in water bodies. Adsorption and photocatalysis are common techniques that have been studied to treat these pollutants. However, they each have challenges and limitations. As a result, combining both processes seem to be the way forward. Composite materials combining adsorption and photocatalysis tend to in most cases have an improved specific surface area, electron hole separation efficiency and electrical properties that are beneficial for their application in water treatment. In this work the advantages, disadvantages, sustainability, and cost implications of the methods used to synthesize these composites materials were discussed. To better outline their impact in combining adsorption and photocatalysis, the challenges and limitations of using a single technique were listed. The technology readiness level (TRL) of the techniques was also presented. Different types of composite materials have been studied, and their stability, regeneration and recyclability are still under development. It is evident how focus on pollutants has been expanded during the last decade, and year by year more research results on how to remove pharmaceuticals from water are reported. The synthesis, design and efficiency of the materials have improved through the years, however though still at the laboratory scale.

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引用次数: 0

Does oil dependence cause energy risk?

IF 8 Q1 ENERGY & FUELS

Energy nexus

Pub Date : 2025-02-10 DOI: 10.1016/j.nexus.2025.100393

Bekhzod Kuziboev , Elbek Khodjaniyazov , Ilhan Ozturk , Khamid Sabirov , Samariddin Makhmudov , Sarbinaz Utegenova

These days, the issue of energy risk is becoming more prevalent worldwide. Particularly, the issue of oil dependence raises awareness. The previous studies provide very limited background to this issue because of the absence of an energy risk variable. In this context, this study is a pioneer as it empirically assesses the effect of oil dependence on energy risk, a novel variable that has never been applied before, in 84 countries using annual data from 2000 to 2021. The estimations are conducted in the sample of the world and development stage, employing the Method of Moments Quantile Regression (MMQR), which allows us to estimate the impact of oil dependence on energy risk at various quantiles of energy risk. The findings reveal that dependence on oil resources leads to energy risk in the world and developing countries, whereas in developed countries oil dependence does not cause energy risk. We assume that developed countries, with their advanced technological capabilities and strong international collaboration, have adopted various alternative energy sources. Therefore, as policy implications, enhancing energy source diversification is suggested since dependence of energy consumption on various sources mitigates oil dependence, thus energy risk. Furthermore, we emphasize the significance of technological progress, as it determines the efficient and minimal use of energy resources and oil, both of which depend on the level of technological advancement. Furthermore, enhancing the involvement of international organizations in energy cooperation is crucial for managing effective energy distribution.

{"title":"Does oil dependence cause energy risk?","authors":"Bekhzod Kuziboev , Elbek Khodjaniyazov , Ilhan Ozturk , Khamid Sabirov , Samariddin Makhmudov , Sarbinaz Utegenova","doi":"10.1016/j.nexus.2025.100393","DOIUrl":"10.1016/j.nexus.2025.100393","url":null,"abstract":"<div><div>These days, the issue of energy risk is becoming more prevalent worldwide. Particularly, the issue of oil dependence raises awareness. The previous studies provide very limited background to this issue because of the absence of an energy risk variable. In this context, this study is a pioneer as it empirically assesses the effect of oil dependence on energy risk, a novel variable that has never been applied before, in 84 countries using annual data from 2000 to 2021. The estimations are conducted in the sample of the world and development stage, employing the Method of Moments Quantile Regression (MMQR), which allows us to estimate the impact of oil dependence on energy risk at various quantiles of energy risk. The findings reveal that dependence on oil resources leads to energy risk in the world and developing countries, whereas in developed countries oil dependence does not cause energy risk. We assume that developed countries, with their advanced technological capabilities and strong international collaboration, have adopted various alternative energy sources. Therefore, as policy implications, enhancing energy source diversification is suggested since dependence of energy consumption on various sources mitigates oil dependence, thus energy risk. Furthermore, we emphasize the significance of technological progress, as it determines the efficient and minimal use of energy resources and oil, both of which depend on the level of technological advancement. Furthermore, enhancing the involvement of international organizations in energy cooperation is crucial for managing effective energy distribution.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100393"},"PeriodicalIF":8.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0