Abstract

Water footprint assessments of tropical export crops typically rely on long-term climatic averages, overlooking how interannual climate variability reshapes the balance between green and blue water use and limiting their reliability in regions governed by El Niño and La Niña phases. This study hypothesised that such variability modifies the green- and blue-water components by shifting the balance between rainfall and irrigation. It was tested for banana production in southern Guatemala using 402 farm-year observations across three production zones during 2018-2023, assessing green, blue and grey components across contrasting phases. The total water footprint ranged from 246 to 435 m³/t and differed significantly among zones, while the green contribution increased during wetter phases, and theoretical irrigation requirements increased by 25–30% during drier phases. Water footprint composition is therefore climate-phase dependent rather than stationary, making the integration of climate variability essential for reliable benchmarking.

Abstract

Paddy field dams support both agricultural production and flood mitigation. However, their recovery after dam functionality is restored, particularly within Land Improvement District-managed areas, has not been sufficiently studied. This study develops a hierarchical priority-zoning framework to guide recovery-based management in the Shin-Tonegawa Land Improvement District, Japan. Three key indicators – the actual drainage flow distance to the main drainage channel, the actual drainage flow distance to the final drainage point, and the potential storage volume – were calculated for individual paddy field plots and aggregated dam units. These indicators were then analysed using hierarchical clustering, decision-tree modelling, and analysis of variance to identify classes and assess the relative influence of each indicator. The findings show that hydraulic accessibility is the primary driver of recovery priority at both spatial scales. The plot-level results indicate that fields near the main drainage channel and outlet point can be drained quickly. At the dam level, downstream dams near the outfall must be prioritised to restore trunk-channel capacity and prevent upstream congestion. By integrating these two perspectives, this study proposes a nested recovery framework in which dam-level prioritisation structures system restoration, followed by plot-level triage within the prioritised dams.

Abstract

Hydrogen is increasingly deployed across production, storage, transport, and end-use systems, raising significant safety and risk-management challenges. This study presents a PRISMA-based systematic review of scientific and technical literature on hydrogen supply chain risk assessment methods published between 2010 and 2025, with searches completed on 20 September 2025. Using the context–intervention–mechanism–outcome framework, the review classifies and compares quantitative risk assessment, consequence modelling, safety barrier analysis, and monitoring-oriented approaches across supply chain stages. The results show a strong concentration on storage and transport applications and a predominance of static, scenario-based methodologies. Monitoring systems are generally treated as operational support tools rather than as inputs for dynamic probabilistic updating. The review identifies limitations in cross-stage integration, uncertainty treatment, and barrier-performance modelling, and highlights the need for more integrated and monitoring-informed hydrogen safety assessment frameworks.

Abstract

Off-grid electricity in energy-constrained communities can be supported by converting organic waste into biogas and electrical energy using affordable monitoring and predictive tools. This study developed an anaerobic digestion electricity-generation framework incorporating low-cost sensor-based monitoring and artificial neural network methane prediction. The modelling dataset comprised 61 daily records combining independently measured observations with controlled-profile augmentation across the investigated operating range. A wireless microcontroller-based sensing node monitored temperature and feedstock moisture, while temperature, biogas volume, carbon dioxide fraction, pH, hydrogen sulfide, and internal combustion engine operating time were used to predict methane. Methane output ranged from 6.50 to 12.09 cubic metres per day and daily electrical energy from 10.0 to 22.0 kilowatt-hours. On held-out test data, the neural network achieved a root mean square error of 0.593 cubic metres per day and a coefficient of determination of 0.856, whereas multiple linear regression achieved 0.416 and 0.929, respectively. The implied electrical conversion efficiency averaged 15.5%. The results demonstrate predictive feasibility within the investigated range, while the structured hybrid dataset and stronger linear baseline indicate that broader generalisation requires independently measured data under more variable operating conditions.

Abstract

Packed-bed solar air heaters have attracted considerable interest due to their ability to improve heat transfer efficiency. This study numerically investigates the influence of channel aspect ratio on the thermo-hydraulic performance of a packed-bed solar air heater filled with mixed-size aluminium spherical elements. Three-dimensional computational fluid dynamics simulations were performed in ANSYS 2023 R1 under steady-state turbulent flow conditions using the standard k–ε model. Four channel heights (8, 10, 12, and 14 cm) were evaluated while maintaining identical operating conditions. The results show that channel height significantly affects both heat transfer and pressure loss. The 12 cm channel height provided the best overall performance, achieving the highest outlet air temperature and thermal efficiency with a relatively low pressure drop. Compared with the lowest aspect ratio, the optimum configuration increased thermal efficiency by approximately 85% and the thermo-hydraulic performance factor by about 76%. These findings provide practical guidance for the design and optimization of high-performance packed-bed solar air heaters.

Abstract

The Journal of Sustainable Development of Energy, Water and Environment Systems (JSDEWES) is an international journal dedicated to the improvement and dissemination of knowledge on methods, policies and technologies for increasing the sustainability of development by decoupling growth from natural resources and replacing them with knowledge-based economy, taking into account its economic, environmental and social pillars, as well as methods for assessing and measuring sustainability of development, regarding energy, transport, water, environment and food production systems and their many combinations. In total, 80 manuscripts were published in Volume XIV, all of them reviewed by at least two reviewers. The Journal of Sustainable Development of Energy, Water and Environment Systems would like to thank reviewers for their contribution to the quality of the published manuscripts.

Abstract

Access to electricity remains limited for nearly 655 million people worldwide, primarily in rural and isolated communities. This study addresses the persistent challenge of planning electricity access in off-grid, data-scarce contexts, where the absence of historical consumption data hinders effective energy system design. A literature review was conducted to identify, classify, and analyse existing methods for estimating electricity demand based on six criteria: hierarchy, source of information, scale, modelling approach, temporal resolution, and time frame. Based on this analysis, a structured framework was proposed, integrating common insights and practices from previous studies and the authors’ experience. The framework outlines key steps, including community diagnosis, methodological selection, data collection, data processing and modelling, and result assessment. It provides guidance for selecting and applying appropriate methods and supports the comparison and evaluation of different approaches. The practical application of the proposed framework is illustrated through a case study in a rural electrification context. The framework assists in informing decisions in electrification projects and contributes to the design of cost-effective and context-appropriate energy systems. This contribution addresses a critical gap in rural electrification research and practice, particularly under conditions of limited data availability.

Abstract

The article identifies the minerals that cause salt deposition in various industrial sectors and provides information on reagents used to prevent salt deposition, emphasising a preference for reagents that are multifunctional, environmentally friendly and economically viable. Sodium and potassium salts of mono-, di-, and triisobutylamides of ethylenediaminetetraacetic acid were synthesised for testing as corrosion and scale-forming inhibitors in water systems at 50 ^oC. The structures of the synthesised compounds were confirmed by infrared spectroscopy, and their 10% solutions were prepared to determine the main physicochemical parameters. Inhibition of corrosion and salt deposition experiments were carried out at concentrations of 50, 100 and 150 mg L^-1. At 50 mg L^-1, the trisodium salt of the amide, synthesised from ethylenediaminetetraacetic acid and isobutylamine at a 1:1 molar ratio, exhibited the highest performance, providing 90% protection of the Steel-3 metal plates against corrosion and achieving 90% effectiveness against salt precipitation. Anti-corrosion and anti-scaling evaluations showed that increasing the salt concentration to 100 and 150 mg L^-1 led to a proportional increase in effectiveness. Analysis of the results also indicated that the mono-, di-, and trisodium salts exhibited greater inhibitory activity than their corresponding potassium salts. In terms of activity, both the sodium and potassium salts followed the order: mono- < di- < tri-. It has been established that the inhibition mechanism of steel corrosion in the presence of synthesised salts is due to chemisorption, following the classical Langmuir adsorption isotherm. Additionally, calculations were performed to correlate the electronic properties of the inhibitors with their experimental performance, identifying the carboxylate and amide groups as the primary active centres for adsorption. The theoretical results, including frontier molecular energy-level analysis and electron-transfer fractions, provided a convincing explanation for the superior efficiency of the trisodium salt, consistent with the experimentally observed activity order of mono- < di- < tri-.

Abstract

This paper presents a hardware-in-the-loop (HIL) validated design and implementation of a buck converter-based battery charger for a solar-powered golf car. The system utilizes an ESP32 microcontroller to execute a unified control function that seamlessly integrates Maximum Power Point Tracking (MPPT) via the Incremental Conductance algorithm with Constant-Current/Constant-Voltage (CC/CV) battery charging. A key contribution is the use of the Typhoon HIL 402 platform for high-fidelity, real-time simulation, which enabled the validation of control strategies and firmware before physical prototyping. This approach significantly reduced development time and risk. The simulation results demonstrated a high MPPT efficiency of >98.5 % and a smooth CC-CV transition. The subsequent physical prototype confirmed these results, achieving a measured MPPT efficiency of 97.8 % and a peak converter efficiency of 93.7 %, closely aligning with the simulation predictions. The study conclusively demonstrates the effectiveness of the proposed control strategy and the value of a HIL-centric development flow for power electronics systems.

Abstract

Decentralized renewable energy systems can provide a promising pathway for improving energy access in rural regions with limited grid reliability. This study conducts a techno-economic and environmental assessment of a household-scale hybrid energy system integrating a 1.65 kWp solar photovoltaic (PV) array with a fixed-dome biogas digester. System performance was evaluated using one year of field data and a 20 y economic model. At an 8 % discount rate, the system requires an initial investment of USD 1,227. It yields annual savings of USD 321.45, resulting in a net present value of USD 1,707.3, an internal rate of return of 23 %, and a discounted payback period of four years. The hybrid configuration achieves a net reduction of approximately 2.16 tCO₂e×y⁻¹. Results demonstrate that integrating PV and biogas improves economic viability and energy reliability, offering a sustainable solution for decentralized rural energy supply.

Abstract

South Africa faces escalating energy insecurity and water scarcity, rendering the transition to net-zero carbon and net-zero water buildings indispensable. However, their adoption remains slow and fragmented. This study applied a Multi-Level Perspective to examine how landscape, regime and niche dynamics operate across macro (national), meso (provincial and industry) and micro (municipal and project) levels, shaping net-zero carbon and net-zero water building adoption. Using qualitative data from semi-structured interviews with facility managers, municipal officials and built environment professionals, findings were thematically analysed using NVivo. Results highlight interdependent barriers across governance levels, including policy misalignment, weak financial incentives, uneven institutional capacity, skills shortages and operational constraints. Integrating these insights with sustainability transitions literature, the study proposes the Net Zero Building Acceleration Framework, which elucidates cross-level interdependencies and key leverage points. The framework offers a context-sensitive route for accelerating adoption through coordinated, governance-aligned interventions in South Africa and similar developing contexts.

Abstract

This paper links two aspects that are often studied separately: improving photovoltaic output through higher-efficiency photovoltaic modules and inverters, and increasing network transfer capability through dynamic line rating. The analysis considers a proposed 100 MW solar plant in Kuklibeg, Kosovo, and two 110 kV existing transmission lines for solar park connection, Line A and Line B. In Scenario 1, RETScreen is used to compare default photovoltaic modules with modules from default RETScreen product, Jinko Solar and Trina Solar under 95% and 98% inverter efficiencies. The best case is achieved with Jinko Solar and a 98% inverter, yielding 118,577 MWh/yr, 128,986 CO₂ t/yr avoided emissions, and reduced land use. Scenario 2 then evaluates whether this higher production can be integrated into the network using hourly static line rating and dynamic line rating on 15 July based on IEEE 738. While Line A can absorb the photovoltaic profile under both ratings, Line B experiences curtailment under static line rating and lower curtailment under dynamic line rating for the analysed case.

Abstract

This paper introduces the Development Compression Trap, a condition in which rapid macroeconomic progress outpaces institutional, social, and ecological capacity, producing fragile development. Unlike the middle-income trap, the Development Compression Trap captures structural misalignments between quantitative expansion and qualitative depth across institutions, human capital, and environmental governance. A multi-dimensional framework combining compression indicators, European Union benchmarking, and Data Envelopment Analysis is applied across four domains: human capital, growth, environment and energy, and infrastructure and institutions. Macedonia is used as the primary case study, complemented by a comparative assessment of Serbia, Montenegro, Bulgaria, Romania, Croatia, Slovenia, the European Union average, and Denmark. The results reveal persistent compression, including education expansion without quality, Gross Domestic Product growth without productivity gains, and environmental reforms without enforcement. Data Envelopment Analysis results confirm that outcomes underperform relative to inputs, indicating systemic inefficiencies.

Abstract

Improving energy and water efficiency in irrigation pumping systems is essential for sustainable resource management in irrigation-dependent regions. Although variable frequency drives are widely used, their overall impact on energy-water performance under real-world irrigation operating conditions remains insufficiently quantified. Laboratory and full-scale field experiments were conducted, including testing at the Teshiktosh-1 irrigation pumping station in Uzbekistan. Pump, electric drive, and overall unit efficiencies were evaluated using dimensionless indicators normalised to nominal rotational speed. Statistical analysis was used to derive empirical efficiency-frequency relationships. Pump and drive efficiencies decrease nonlinearly as rotational speed decreases. At moderate speed reductions (up to ~50% of nominal speed), electric drive losses dominate, whereas at lower speeds, pump losses become the primary contributor to total energy losses. The obtained relationships differ from classical affinity-law assumptions. Field validation confirmed their applicability. Variable frequency drives implementation enabled water savings of about 313.6 thousand m³ (≈16%) and seasonal energy savings of about 107,700 kWh (≈14%). The findings demonstrate that variable-speed control improves overall energy-water performance despite a partial reduction in efficiency at lower rotational speeds.

Abstract

The increasing availability of high-frequency electricity consumption data has created new opportunities for understanding complex energy behaviours beyond dominant global patterns. However, conventional statistical and deep learning models primarily focus on average trends and often overlook weakly expressed local structures embedded within time series. This study proposes an exploratory framework for identifying latent micro-patterns in multivariate electrical consumption data using a combination of entropy-based feature scoring, temporal residual analysis, anomaly detection, and density-based clustering. The methodology is applied to the individual household electric power consumption dataset from the University of California, Irvine repository. A dark value score combining entropy and rarity is introduced to identify variables potentially containing hidden informational structures. Residuals extracted from Long Short-Term Memory predictions are analysed using Isolation Forest and density-based clustering techniques to reveal statistically coherent micro-signals. Results show that these residual micro-structures are not random noise but exhibit identifiable temporal and statistical organization. Although clusters remain weakly separated, their distributions differ significantly from normal observations, supporting the existence of localized operational regimes invisible to dominant predictive models. The proposed framework provides an interpretable complementary perspective to traditional forecasting approaches and offers potential applications in anomaly detection, behavioural analysis, and intelligent energy monitoring.

Abstract

Accurate energy consumption prediction and therefore velocity prediction, over mid-term is essential for efficient vehicle operation, particularly in electric and hybrid vehicles where range and resource management are critical. However, most current models fail to account for the real-time variability in driver behaviour, especially in response to dynamic traffic situations.  This work proposes an adaptive system that identifies and adapts to behaviour patterns which are associated with repeatedly inaccurate predictions by comparing expected and actual driver actions. This allows the system to automatically learn from new behaviour patterns without the need for manual supervision. The proposed method is evaluated on exemplary driving situations extracted from open driving data. By fusing traffic context modelling with driver behaviour modelling, this method contributes to accurate velocity prediction systems, which can adapt to changes in driver behaviour over time.

Abstract

Green Infrastructure has become a central strategy in urban sustainability and climate adaptation agendas, yet its benefits are unequally distributed across cities. This review investigates how the unequal distribution of Green Infrastructure contributes to environmental injustice and green gentrification. A systematic literature review was conducted in accordance with the PRISMA framework, with complementary bibliometric support, based on fifteen peer-reviewed articles published between 2019 and 2024 and indexed in the Scopus database. The findings show that unequal access to Green Infrastructure is associated with the displacement of low-income residents, shifts in neighbourhood demographic profiles, and the reproduction of existing socio-spatial inequalities. The review also indicates that interventions not guided by equity-oriented planning may intensify exclusionary urban dynamics. The study synthesises current evidence on the relationship between Green Infrastructure, environmental injustice, and green gentrification, while highlighting the need for inclusive and participatory urban policies capable of protecting vulnerable communities and promoting more equitable access to environmental benefits.

Abstract

Wind turbine systems are designed to produce renewable energy and minimize fossil fuel dependency, thus bringing operational carbon emissions to the minimum. However, their sustainability goes beyond power generation as they also integrate materials such as steel, concrete, and non-recyclable composites. Therefore, circular economy concepts focusing on the use of recyclable materials, efficient manufacturing processes and innovative end-of-life solutions are important to ensure sustainability. Thus, a circular economy point of view on the state-of-the-art of such systems is of interest. However, despite abundant research conducted over the years, there is a lack of comprehensive quantitative studies relating circular economy strategies and components used in wind turbines. To fill this gap, this study presents a systematic literature mapping using an automated text analysis tool developed by the authors. The process quantifies the frequency (appearances per 10000 words) and correlation (Pearson) of circular economy indicators, environmental impacts, materials and wind turbine components, complemented by manual review of 540 research articles. The findings show that recycling and blades are the most quoted concepts with 9.7 and 8.7 appearances per 10000 words respectively, and significantly higher correlation than other indicators. Higher-tier circular economy strategies, such as reuse and reduce are less discussed which have 2.7 and 1.9 appearances per 10000 words respectively. Results also show a clear gap between current research focus and comprehensive circular economy implementation. In order to fill this gap, this study emphasizes prioritising higher-tiered economy strategies, and the necessity of better integrating design-for-disassembly, secondary material markets, policy support, social aspects and life cycle assessment approaches.

Abstract

This study hierarchizes the importance of technological, environmental, social, and policy factors on the energy efficiency of domestic refrigerators in Colombia, utilizing the Analytic Hierarchy Process method to prioritize determinants under real-life conditions and in low-income contexts. Through a systematic literature review and expert consultation, a hierarchical model of criteria and sub-criteria was developed to evaluate the relative impact of variables, including ambient temperature, door opening frequency, and regulatory standards, on electricity consumption. The results show that environmental criteria (58.57%) and social criteria (30.63%) jointly account for 89.20% of the expert-derived priority weight, exceeding the relative weights assigned to techno-thermodynamic and policy criteria. The importance of adapting regulations and educational programs to local conditions to improve energy performance is emphasized. This comprehensive prioritisation provides decision-support evidence for designing context-specific public and technological strategies to promote energy sustainability in the Colombia residential sector.

Abstract

Produced water from oil and gas extraction poses a major environmental challenge due to its high boron content and associated risks to ecosystems and human health. Traditional boron removal methods suffer from high costs, limited efficiency, and the generation of secondary pollutants. This study presents a comprehensive assessment of strontium chloride as a precipitating agent in an optimised chemical oxo-precipitation process for removing boron from produced water. Through systematic variation of critical operational parameters, including pH, reagent dosages, and mixing speed, the treatment achieved nearly 85% boron removal under optimal conditions. Toxicity evaluation using Lactuca sativa L. lettuce seeds revealed a 133% increase in the median lethal dose after treatment, demonstrating substantial mitigation of ecological risk. The process embodies key principles of green chemistry by minimising hazardous byproducts, employing safer chemicals, and reducing sludge generation compared with barium-based methods, thereby improving safety for both workers and the environment. Therefore, this methodology directly contributes to the United Nations Sustainable Development Goals by advancing water quality improvement, promoting the reuse of treated water, minimising pollutant discharges, and supporting the protection of terrestrial ecosystems and public health through sustainable innovation.