Abstract

As electric vehicle adoption accelerates, the development of sustainable and efficient charging infrastructure is essential. This study presents a novel electric vehicle charging system that integrates solar photovoltaic energy with an energy storage system using a bidirectional buck-boost converter. The converter enables energy flow in both directions between the energy storage system and the electric vehicle, allowing flexible operation under varying energy availability. A control framework combining maximum power point tracking and proportional-integral control is implemented to regulate power flow and enhance system stability. MATLAB-based analysis evaluates system performance under different operational scenarios. Results show that the integration of an energy storage system reduces dependence on grid electricity while maintaining charging efficiency. The bidirectional buck-boost converter achieves high efficiency in both charging and discharging modes, enabling optimal energy utilization across solar, storage, and electric vehicle components. This work contributes to the advancement of smart and renewable-based electric vehicle charging infrastructure by improving energy flexibility, reliability, and sustainability.

Abstract

The global transition towards sustainable development necessitates the integration of renewable energy systems with circular resource management to mitigate environmental impacts and enhance efficiency. This review emphasises the urgent need to assess how circular economy strategies interact with the deployment of renewable energy in practical settings. It is posited that a synergistic integration of these two approaches can significantly improve sustainability outcomes. The study utilises a systems-level analysis that encompasses thermodynamic evaluations, spatial planning, and optimisation of energy flows through advanced process integration methodologies. Several groups of challenges have been identified – thermodynamic, spatial, and multiplicity challenges. The multiplicity challenge class is the most complex, encompassing topology, variability, and organisational subclasses. The review points to several possible tools to be applied – including Energy Quality Pinch for the thermodynamic challenges, P-graph framework and digital orchestration to address the multiplicity and organisational challenges. The review concludes that the strategic application of intelligent coordination mechanisms, transparent accounting frameworks, and emerging technologies has the potential to realise the benefits of sustainable circular energy systems fully.

Abstract

Plastic pollution in the ocean is a widespread issue in the marine biosphere that requires large-scale monitoring systems. However, extending the use of deep-learning-based detection methodologies to real-world marine settings is difficult. Reflections from surfaces, small target objects, and partially blocked debris often hinder the effective functioning of such systems. To mitigate these challenges, this paper presents a detection system built on the You Only Look Once architecture that explicitly considers the aforementioned constraints. The architecture combines two mutually supportive modules: a directional coordinate attention module, which decodes spatial dependencies along horizontal and vertical axes, and a Sinkhorn distance-based regularization term, which stabilizes feature focus across spatial dimensions. Experimental testing of image collections by aerial and underwater cameras shows significant performance improvements compared to the latest state-of-the-art assessments. The proposed system achieves a precision of 92% and a recall of 94% in aerial scenes and a precision of 90% and a recall of 92% in sub-aqueous scenes. An ablation study validates the hypothesis that the two modules work together to improve performance. Furthermore, visual inspection yields more reliable results for detecting typical marine debris, including reflective artifacts, small objects, and visually contaminated scenes.

Abstract

Water is an indispensable resource for all forms of life, with a particularly critical role in supporting human health, agriculture, and industrial development. With the predicted water scarcity worldwide, it is critical to have a tool to analyse and predict water potability accurately and in real-time. This study used machine learning models to predict water potability based on quality features such as potential of Hydrogen (pH) value, hardness, solids content, chloramines, sulfate, and conductivity. Potability is determined based on the concentration of these features in the water. Four Machine Learning algorithms, namely, Random Forest (RF), Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), and Deep Learning Neural Networks, are used to analyse water potability after training using a water quality dataset. Initial experiments showed moderate performance, with Random Forest (F1-score = 0.47 and area under the receiver operating characteristic curve of 0.68) and XGBoost (F1-score = 0.49 and area under the receiver operating characteristic curve of 0.66), outperforming the other two models. After addressing class imbalance and introducing more features using feature engineering, the performance of the four models was significantly improved, with Random Forest achieving an F1-score of 0.85 and an area under the curve of 0.90 and XGBoost achieving an F1-score of 0.86 and an area under the curve of 0.91. The results clearly indicate that Random Forest and XGBoost consistently outperformed the Linear Regression model and the Deep Learning model in terms of predictive accuracy and robustness. These results demonstrate the critical importance of feature engineering and hyperparameter optimization in enhancing model effectiveness. A real-time water potability prediction application was developed to classify water as either “safe to drink” or “unsafe to drink”, and its functionality was successfully validated, and its output was displayed on a user-friendly graphical user interface (GUI).

Abstract

The accelerating expansion of global digital infrastructure has raised urgent concerns about the energy efficiency and environmental impact of data centers. This study quantitatively evaluates the sustainability of 135 facilities across 137 countries using data from 2021–2022. Two derived indicators, Power per Centre (MW) and White Space per Centre (m²), were developed to normalise architectural and operational performance. Results show substantial regional disparities: Europe achieves the highest average efficiency (0.13 MW and 0.19 m² per centre), while the Americas record lower power density (0.03 MW per centre) due to legacy infrastructures. The strong correlation between gross power and white space (r > 0.99) indicates coupled global growth of spatial and energy provisioning. In contrast, emerging regions such as Africa and the Pacific remain under-represented. The findings highlight that normalised metrics provide clearer insight into design efficiency and energy equity than aggregate totals. The study concludes that sustainable digital infrastructure requires region-specific efficiency benchmarks, transparent reporting standards, modular renewable-ready designs, and developing a Global Digital Infrastructure Sustainability Index (GDISI) to guide policy action.

Abstract

The viability of implementing Blockchain technology in sustainable development platform is thoroughly explored in this study. A healthy ecosystem for all inhabitants can be built by introducing a new behavioural shift through combating harmful environmental activities. The paper outlines the benefits that the users might get from integrating tokenization technology into their regular routines. To determine whether the blockchain will be accepted by its potential users, this article employed the technology acceptance model (TAM). This research reveals that TAM’s constructs have a big impact on the way people think about using blockchain-enabled solutions in a platform for sustainable development. The strategy suggests that government agencies and financial players concentrate on factors affecting residential and industrial consumers’ attitudes toward adopting blockchain to provide a platform for sustainable development. 

Abstract

Household biogas technology can potentially contribute to the clean cooking transition. However, when improperly used and not well customised to the user’s cooking needs and practices, the technology can lead to counterintuitive and detrimental phenomena, e.g. venting. It not only affects the technology’s effective use but also its climate benefits. This work aims to estimate greenhouse gas emissions associated with biogas venting from household biogas technology use and establish its causes. Household biogas utilisation data were collected remotely by using smart biogas meters and validated with conventional analogue pressure gauges. The remotely acquired data were analysed to understand the household biogas utilisation and venting levels from Rwandan households as a case for the study. Results showed that the ratio of biogas utilisation to venting was 16:1. Biogas lost through venting resulted in average monthly emissions of 33–56 kgCO2,e per household. Interactive interviews and field observations indicated that the current household biogas systems are not customised to the local cooking practices and the required heating for cooking specific Rwandan staple meals. This situation results in underutilisation of the produced biogas, leading to venting, hence greenhouse gas emissions. Customising the household biogas systems to local cooking practices and/or adjusting cooking practices to the technology designs can increase biogas utilisation, minimise venting and enhance envisaged technology benefits.

Abstract

This study proposes a financial evaluation methodology based on real options to assess photovoltaic energy projects in health-care institutions under uncertainty. Applied to a hospital in Barranquilla, Colombia, a solar system generating 16,761 kilowatt-hours (kWh) per year—covering 50% of electricity demand in critical areas—reduced operating costs and improved energy security. The traditional valuation yielded a net present value of US$10,316, while real options analysis produced a value of US$5,334. Scenario analysis showed outcomes ranging from US$5,168 to US$15,467. The expansion strategy could increase the project value to US$72,901, and a put option of US$2,559 offers a safeguard under adverse conditions. The probability of achieving positive returns was 50.1%, with electricity price and solar irradiation as the most influential variables. Beyond its practical findings, the study introduces a novel application of real options tailored to the health-care sector, offering a robust framework for sustainable energy investment planning.

Abstract

The use of biogas in Eswatini is encouraged by favorable climate and availability of organic waste, with opportunity for renewable energy generation on site with associated health and environmental benefits.  This study provides a review of the development of biogas installations with the objective of identifying the relevant factors that determine the success of biogas schemes. The study is based on local experience through a survey of about twenty biogas pilot installations in Eswatni.  Data were collected using desk studies, field observations, interviews and focus group discussions. The study revealed that despite the existence of good potential, most of the biogas projects in the past experienced poor performance and were abandoned due to a multitude of factors related to policy, technical, institutional, socio-cultural, climatic and economic factors. Future implementation of biogas projects need to carefully address these relevant factors at both the planning and implementation stages and shall be accompanied by proper feasibility studies with program and project support in order to realize the full benefit and reduce failure rates. 

Abstract

Appropriate tilt angle optimization for bifacial solar panels is essential for optimal energy yield since solar incidence angles in tropical low-latitude regions play a significant role in overall performance. The effects of variations in tilt angles 0°, 5°, 10°, and 15° on the components of solar irradiance and energy production are presented here through a combination of simulations and field studies. The study was carried out at Jomo Kenyatta University of Agriculture and Technology, Kenya, at latitude 1.03°S and longitude 36.98°E to assess the effect of tilt angles on the front side beam irradiance and the rear side ground reflected irradiance. Results indicate that while increasing the tilt angle enhances ground reflected irradiance, it leads to beam irradiance losses due to the cosine effect, with reductions of approximately 5%, 7%, and 10% for tilt angles of 5°, 10°, and 15°, respectively. The optimal tilt angle in this study was found to be 5°. The ideal Height was found to be 2 m, where the bifacial panel experienced around 16.8% energy gain. These findings highlight the trade-off between optimizing ground reflection and minimizing angular losses, providing critical insights for the strategic deployment of bifacial PV systems in tropical regions.

Abstract

This paper aims to assess the impact of certain economic factors on pollution for selected 112 countries worldwide. Due to data availability, carbon dioxide emissions in tonnes per capita were chosen as the dependent variable measuring pollution. Based on panel data and generalized moments method, the relationship between economic activity and environmental pollution was estimated. The results show that in the whole sample, as well as for two subsamples of developed and undeveloped countries, carbon dioxide emissions are statistically significantly affected by gross domestic product per capita, energy intensity and renewable energy consumption. The linear effect of economic activity positively effects the pollution, while the quadratic relationship is negative. Thus, the validity of inverted-U curve of the environmental Kuznets curve has been demonstrated. The estimated effect of economic activity measured by gross domestic product per capita on pollution does not differ in developed and undeveloped countries.

Abstract

We are pleased to present the inaugural issue of the Journal of Sustainable Development of Smart Energy Networks, a platform dedicated to advancing research in energy systems powered by variable renewable energy sources. This highly interdisciplinary field is pivotal to the global transition toward a fully decarbonized energy paradigm. The development of smart energy networks requires the integration of diverse research disciplines, including energy engineering, control engineering, electrical engineering, environmental science, and social science. In this context, the Journal welcomes contributions that explore emerging technologies and their integration into innovative energy systems. A key challenge for future smart networks is the effective management of excess renewable energy production, which is essential for ensuring safe and robust system operation. Technologies such as Power-to-X (PtX), district heating and cooling systems, renewable energy communities, sector coupling, demand response strategies, the water-energy-food nexus, and advanced energy storage will play a central role in shaping these networks. Moreover, further efforts are needed to promote building energy efficiency, HVAC systems, renewable electrical and thermal technologies, hydrogen, fuel cells, and sustainable transportation systems. These technologies are critical to achieving decarbonization targets. The Journal also encourages contributions that examine circular economy principles and the social acceptability of smart energy networks, recognizing their importance in fostering sustainable and inclusive energy transitions. Through this Journal, we aim to cultivate a collaborative and forward-thinking research community dedicated to the sustainable development of next-generation energy networks.

Abstract

The granular activated carbon (GAC) filter was found to be very effective as a treatment for the removal of herbicides. The Sips isotherms showed the best fit with 6.6 % error. Fixed-bed column experiments packed with GAC were conducted with different GAC bed heights (5, 10, and 15 cm) and different effluent velocities. The GAC fixed bed column shows the model simulation fits reasonably well during the initial period, and also with a shallow bed depth (5 cm) with a flow rate of 4 m/h. Another set of experiments is GAC and GAC doping Zn with various concentrations to remove herbicides from water. The doped Zn–TiO₂ GAC batch experiments can remove MM in terms of DOC from 60 to 77 % by using different w/v of doped Zn onto TiO₂–GAC. The highest removal of MM 77 % by using a batch experiment was 0.125 % w/v Zn -TiO₂.

Abstract

Climate change stands as one of the most significant global threats of the 21st century, directly impacting water resources and challenging their resilience against water-related crises. This review paper analyses global trends in the resilience of water resources to climate change, with the primary aim of examining key challenges and opportunities, evaluating diverse policies and strategies across various countries, and presenting best management practices to enhance water resilience. The study begins by introducing the concept of water resources resilience in the face of climate change, followed by an in-depth examination of critical challenges such as shifts in precipitation patterns, rising temperatures, declining water availability, and the intensification of water crises. Emphasis is placed on the necessity for robust infrastructure development, the integration of advanced technologies, and the implementation of sustainable policies at global, national, and local levels. Furthermore, the paper highlights the importance of incorporating social, economic, and cultural dimensions into policy-making and implementation processes. Findings indicate that despite technological advancements and various initiatives, many countries, particularly those in less developed regions, face persistent obstacles such as limited access to financial resources, insufficient technical capacity, and a lack of international coordination. Consequently, the study recommends strengthening international cooperation, improving water resource management policies, and raising public awareness of climate change as essential strategies to bolster the resilience of water systems against future crises. Ultimately, the paper underscores the critical need for global collaboration and knowledge exchange in water resource management and climate adaptation efforts.

Abstract

Rainwater can be a safe and sustainable source of drinking water. Progressive freeze concentration has been identified to be a suitable freeze treatment process to treat rainwater into drinking water. In this work, the harvested rainwater quality was evaluated based on atmospheric conditions and the subsequent purification process was carried out and reported on the respective supercooling phenomena and effect of operating parameters.  Statistical analysis found the total dissolved solids of rainwater to negatively correlate with rainfall amount (r = −0.32) and the range was found to be workable for our progressive freeze concentration system. The supercooling effect in the falling film freeze treatment system was found to be non-existent, showing rainwater can be purified to a relatively high purity without excessive precaution to prevent contamination caused by supercooling. Experimental results and statistical analysis showed higher circulation time (26 min) and lower rainwater total dissolved solids (6 ppm) improved the purification efficiency of rainwater by giving higher concentration factor (3.4). A simple energy consumption analysis also signifies this system to consume a significantly lower energy compared to distillation. This work can serve as a preliminary study for future research to explore freeze treatment as a viable process to produce drinking water from rainwater.

Abstract

The solar photovoltaic energy sources are becoming popular due to being cleaner, sustainable and cost-effective sources of electrical energy. Photovoltaic sources are being deployed widely worldwide for residential and commercial use. In this research, a unique methodology is explored by modelling a 3-phase induction motor drive system fed from a photovoltaic source via pulse width modulation based inverter. The pulse width modulation pulse width modulation inverter technology provides a convenient way to control the motor speed by varying either the modulation index or the frequency of the reference signal for. The modulation index control method achieves faster dynamic response by enabling direct voltage amplitude adjustment, allowing for rapid torque control without inducing flux variations, which results in settling times of 0.2 s for speed and 0.12 s for torque compared to the frequency-based method with settling times of slightly greater than 0.5 s. The drive is integrated with heating and lighting load through a boost converter to absorb the surplus power from photovoltaic so that the overall system runs at maximum power point condition. Furthermore, partial shading condition is applied to assess the speed response of the motor, being the primary motive of this paper which is observed to stay at a reference of 1700 rpm. The prioritization of the motor load is ensured by the system’s design, where the motor is directly fed by the inverter with control algorithms tailored to run at a desired speed, while the boost converter connected to auxiliary loads (heating and lighting) operates on the surplus power, as regulated by the maximum power point tracking algorithm.

Abstract

Integrating renewable energy sources and improving energy efficiency in public buildings is one of the key targets of energy transition and decarbonisation. PV systems can significantly contribute to achieving these goals. In this context, this paper presents an easy-to-replicate method for spatial, energy, and economic analysis of solarization of public buildings. The method is tested in a case study area of the City of Osijek. The method combines different software, tools, and data to calculate the feasibility of a solarization project. The results showed that the project of solarization is feasible for current market conditions, resulting in an IRR of 4.1% and an NPV 1,470,244.77 €. The production cost from PV systems installed at public buildings is 49.74 €/MWh, while purchasing electric energy from the network is 149 €/MWh.

Abstract

This study proposes an Artificial Intelligence-Supported Hyperfuzzy framework to evaluate hydrogen fuel cell technologies in Morocco's smart urban and supply chain ecosystems. Integrating compromise-ranking with efficiency benchmarking, the model addresses challenges in performance optimization, decision uncertainty, and supply integration. Key metrics—like power density, fuel efficiency, and system adaptability—are assessed through fuzzy logic and Artificial Intelligence-enhanced sensitivity analysis. Findings confirm that hydrogen-powered public transport offers superior efficiency and robustness, emerging as the top-ranked alternative. Artificial Intelligence strengthens traceability, weight calibration, and adaptability under expert preference variation. The study underscores the importance of supportive infrastructure, including refueling stations and grid-integrated systems, for scalable deployment. Results offer data-driven insights for policymakers and planners, guiding sustainable hydrogen strategies tailored to urban mobility and energy supply networks. By advancing decision accuracy under real-world uncertainty, this framework provides a replicable model for optimizing hydrogen-based solutions in smart cities.

Abstract

Critical materials are essential to the global economy but face supply risks from geopolitical, environmental, and market pressures. The European Union identifies 34 critical materials, ranging from lithium, cobalt, and nickel for batteries to rare earth elements for magnets, and high‑strength alloy metals such as chromium and tungsten. Even abundant metals like copper and aluminium can become critical when demand outpaces sustainable supply.

Eco‑design offers strategies to mitigate this dependency by extending product lifespan, enabling component disassembly for recycling, and seeking viable material substitutions. In modular construction — especially container‑based self‑sufficient modules — such measures can improve both resource efficiency and sustainability.

Although these modules are increasingly used in remote and off‑grid contexts, little scientific work has quantified the criticality of their materials. This study addresses that gap by applying thermodynamic rarity indicators to a case study: the ZEROENERGYMOD project module, built to PassivHaus standards and integrating renewable generation with dual energy storage (lithium batteries and green hydrogen).

The research focuses on identifying subsystems with the highest critical material contribution, assessing trade‑offs between energy storage options, and proposing design measures to reduce criticality without compromising function. The structural frame and internal partitions contributed 72 % of total thermodynamic rarity, largely due to nickel in stainless steel. Photovoltaic modules and hydrogen systems, though lighter in mass, showed elevated rarity from tellurium, platinum, and iridium. Hydrogen storage offered higher energy density (MJ/kWh) than lithium iron phosphate batteries under the studied conditions.

Replacing stainless steel with coated carbon steel where feasible, favouring wind over photovoltaics in suitable contexts, and developing alternative photovoltaic technologies can reduce critical material use without compromising function. These strategies demonstrate how thermodynamic rarity metrics can be integrated into sustainable module design to address multiple Sustainable Development Goals.

Abstract

Context and background: Poor nutrition among children and adolescents is a major contributor to global health and sustainability challenges, driving obesity, type 2 diabetes, and food waste in schools.

Motivation: Educational institutions are uniquely positioned to shape healthy and sustainable dietary behaviors, yet the effectiveness of school-based interventions has not been systematically evaluated with respect to both health outcomes and sustainability indicators.

Hypothesis: We hypothesized that multi-component, whole-school interventions are more effective than single-focus programs in improving nutrition, reducing food waste, and supporting progress toward the UN Sustainable Development Goals (SDGs).

Methods: Following PRISMA 2020 guidelines, we systematically reviewed 12 peer-reviewed studies published between 2010 and 2023, assessing their quality with JBI tools and extracting data on intervention types, outcomes, and sustainability metrics.

Results: The review found that whole-school, multi-component interventions achieved an average 15–25% improvement in fruit and vegetable intake, a 10–18% reduction in food waste, and measurable decreases in greenhouse gas emissions linked to dietary choices, while single-focus interventions showed limited effects.

Conclusions: School-based interventions, particularly those adopting a systemic whole-school approach, can simultaneously advance SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), and SDG 12 (Responsible Consumption and Production), and a standardized set of sustainability indicators is urgently needed to guide future research and policy.