This study investigates the influence of three distinct water sources on the physical and chemical properties of soil in the Al-Hammar Marsh of southern Iraq. Fifteen geo-referenced soil samples were collected from zones affected by (i) Euphrates River freshwater, (ii) saline agricultural drainage from the Al-Khamisiya canal, and (iii) brackish water intrusion from the Aramco feeder channel. Samples were tested for gypsum content, pH, electrical conductivity (EC), organic matter (OM) content, bulk density, porosity, texture, and the concentration of basic ions. Spatial variability was evaluated utilizing geographic information system (GIS)-based interpolation methods. The highest salinity levels (mean EC, (EC)= 2,292 µS/cm) were found in regions influenced by the main outfall drain (MOD), marked by high concentrations of chloride and sulfate, reduced porosity, and heightened soil alkalinity. Conversely, Umm Al-Wudaa, affected by Euphrates freshwater, exhibited superior soil structure, elevated levels of OM (7.86%), and reduced salinity (EC = 1,960 $\mu$S/cm), signifying efficient natural leaching. Areas supplied by Aramco exhibited the presence of gypsum and marine ions, along with an intermediate salinity (EC = 2265 $\mu$S/cm). The places with the highest salinity were detected, and the dilution of salt downstream was confirmed via GIS analysis. The findings highlight the need for integrated salinity management in Al-Hammar Marsh through controlled freshwater releases, targeted soil amendments, wetland-based pretreatment of drainage inflows, and continuous GIS-supported monitoring.
Despite increasing attention to inclusive education, sustainability transitions under the Industry 5.0 paradigm remain constrained by the limited integration of socio-cultural barriers affecting marginalised groups. This study examines how harmful cultural practices (HCPs) and socio-economic conditions are associated with education access among 467 ethnic minority youth engaged in agri-startups, contributing theoretically by linking social norms and human capital perspectives within sustainability transition frameworks. A mixed-methods approach combining regression analysis and the Analytic Hierarchy Process (AHP) is employed to capture both statistical relationships and priority-setting mechanisms. The regression results indicate that early marriage (-0.171), gender bias (-0.199), and restrictive religious norms (-0.127) are associated with lower education access, while household income shows a significant positive association (0.722); the model is statistically significant with acceptable explanatory power (R² = 0.315; Adjusted R² = 0.280). The AHP results, based on expert evaluation, demonstrate consistent judgments (CR = 8.120%) and identify personal factors (0.341), particularly HCP awareness, as the highest priority, followed by socio-economic conditions (0.310), education and skills (0.212) and cultural–community factors (0.141). These findings suggest that although economic capacity is a dominant enabling factor, individual agency and behavioural change are critical for reducing harmful practices and improving access to education. However, education access reflects both actual and perceived opportunities due to infrastructural constraints in remote areas. Although the study is limited to data from marginalised youth in agri-startups, the findings highlight that education functions as a key enabling condition linking cultural transformation and livelihood improvement, offering policy-relevant insights for designing inclusive, human-centred education systems to support future-oriented Industry 5.0 transitions.
The aim of the submitted scientific article is to identify significant predictors of the sense of safety at the university and to compare their differences between the male and female populations of respondents. The empirical research was conducted in 2024 at Alexander Dubček University of Trenčín, with the participation of 358 respondents. Data were collected through an online questionnaire containing statements rated on a 5-point Likert scale, examining factors associated with informational influences, subjective concerns, and reflection on the Prague incident of December 2023. Descriptive statistics, correlation analysis, and multiple linear regression methods were used for analytical processing at a significance level of α = 0.05. The results showed that among women in this sample, the sense of safety was significantly associated with concerns about potential threats (X3) and the role of the incident at the Faculty of Arts of Charles University in Prague (X5). Among men in this sample, only factor X5 was confirmed as a key determinant, with its association being stronger than in women. Correlation analysis also indicated different patterns of perception—female respondents in this sample showed a higher sensitivity to subjective concerns, whereas male respondents in this sample appeared to respond more strongly to external security events. These findings confirm the importance of gender differences in shaping the sense of safety in the academic environment and highlight the need for targeted communication and security measures on the part of universities.
Photovoltaic (PV) panels experience significant efficiency degradation under elevated operating temperatures, making effective thermal regulation an important challenge for sustainable solar energy systems. Passive cooling techniques based on phase change materials (PCMs) have attracted considerable attention because of their latent heat storage capability; however, the low thermal conductivity of conventional paraffin-based PCMs restricts heat transfer performance during transient melting processes. This study investigates the thermal behavior of a PV cooling system employing paraffin enhanced with Ag–Al$_2$O$_3$–TiO$_2$ ternary nanoparticles and porous metal foam. A transient numerical model was developed using a Galerkin finite element approach combined with an adaptive mesh refinement technique to accurately capture the movement of the melting front and the associated thermal gradients. The thermal performance of the proposed cooling configuration was evaluated through temperature distribution, liquid fraction evolution, and PV electrical efficiency under transient operating conditions. The results showed that the incorporation of ternary nanoparticles and porous metal foam significantly enhanced heat diffusion and accelerated the melting process within the PCM domain. The liquid fraction increased by approximately 38.66% compared with the conventional PCM configuration, indicating more effective latent heat absorption and faster phase transition behavior. It was also found that the enhanced cooling system reduced the PV panel temperature by nearly 12.75% and improved the PV electrical efficiency by approximately 26.75% relative to the uncooled case. In addition, the incorporation of pure paraffin beneath the PV panel reduced the panel temperature by about 9.94%, confirming the effectiveness of latent heat storage for passive thermal regulation. The results indicate that the simultaneous utilization of ternary nano-enhanced PCM and porous metal foam provides an effective passive cooling strategy for PV thermal management. The proposed configuration offers improved thermal energy dissipation, enhanced phase change heat transfer characteristics, and promising potential for the development of high-performance solar energy systems.
Treatment of hydrazine-containing wastewater remains challenging due to the combined constraints of high energy demand, operational complexity, and the risk of secondary pollution. An integrated treatment system coupling boron-doped diamond Electrocatalytic Oxidation (ECO) with Disc-Tube Reverse Osmosis (DTRO) was developed, with particular attention to thermal regulation and system-level performance. The study departs from conventional equipment-oriented design by addressing the interplay between structural reliability, process integration, and heat dissipation during operation. The mechanical integrity of the supporting framework, welded joints, and lifting components was evaluated through finite element analysis under static and transport-induced loading conditions. In parallel, the thermal behavior of the reactor was examined through the design of an internal cooling system, enabling controlled removal of heat generated during electrochemical reactions. The results demonstrate that the optimized configuration satisfies strength requirements while maintaining stable thermal conditions within the reactor. The incorporation of internal salt circulation further reduces auxiliary input and contributes to more stable process operation. The proposed system provides a technically feasible approach for the treatment of hydrazine-containing wastewater, while offering a design framework in which structural performance and thermal management are addressed in a unified manner.
This study examines the effect of inserting an anisotropic porous layer on flow and heat transfer in a channel partially filled by this layer. The main objective of this study is to evaluate the influence of the porous layer’s anisotropy parameters, specifically: the anisotropic permeability ratio and the anisotropy orientation angle, as well as the permeability (related to the Darcy number $D a$) and thickness of the porous layer. Other parameters affecting flow and heat transfer, such as the Forchheimer inertia coefficient (Forchheimer drag coefficient) and the ratio of the thermal conductivities of the porous layer and the fluid, are also considered. The results, expressed in terms of velocity profiles, temperature profiles, Nusselt number, friction coefficient, and overall thermohydraulic performance, reveal several significant physical trends. The influence of the Forchheimer inertia coefficient on the Nusselt number becomes negligible when $Da$ is low ($Da$ $\ll$ 1), a regime where viscous effects dominate and attenuate the contribution of inertial forces to momentum transport. Conversely, the anisotropic permeability ratio and the anisotropy orientation angle in the porous layer strongly affect the flow structure and thermal response by altering the preferred direction of transport within this layer. The thickness of this layer induces an explicit compromise between improving heat transfer and increasing hydraulic resistance. Indeed, an intermediate thickness allows increasing the Nusselt number without disproportionately increasing pressure drops. Furthermore, in partially filled configurations, an effective thermal conductivity of the porous layer lower than that of the solid wall tends to concentrate the thermal gradient at the interface fluid/porous layer, which can locally intensify heat transfer compared to the case of a fully filled channel. Taken together, these results demonstrate how permeability, structural anisotropy parameters (anisotropic permeability ratio and anisotropy orientation angle), and porous layer thickness jointly control the thermal and hydraulic performance of the channel, and provide useful selection criteria for the design of partially porous channel thermal systems, in which intensifying heat transfer and minimizing pressure drop are competing objectives that must be achieved simultaneously.
Renewable Energy Communities (RECs) are increasingly recognized as decentralized energy systems capable of improving renewable energy integration, enhancing local self-consumption, and supporting the transition toward low-carbon energy infrastructures. However, the effective deployment of RECs still faces significant challenges related to the integration of spatial analysis, energy modelling, operational optimization, and socio-economic assessment within a unified framework. This study investigates an integrated multi-objective framework for the design, evaluation, and operational support of RECs through the combination of geospatial analysis, energy performance modelling, and digital decision-support tools developed within the ENEA Smart Energy Communities (SEC) platform. The proposed methodology was developed by integrating spatially explicit territorial datasets, renewable resource assessments, electricity demand profiles, and multidimensional key performance indicators (KPIs) within a coordinated analytical framework. Three complementary tools were implemented and evaluated: the geoCER geoportal for territorial-scale renewable energy planning and REC scenario modelling, the DHOMUS platform for residential load monitoring and self-consumption optimization, and the Local Token Economy (LTE) system for token-based user engagement and energy-aware behavioral incentives. The results showed that the integrated framework effectively supported the assessment of REC configurations under different territorial and operational conditions. In the Anguillara Sabazia case study, the REC configuration increased the Self-Consumption Index (SCI) from 30% to 65% and the Self-Sufficiency Index from 36% to 79%, while reducing the Energy Surplus Index from 70% to 35%. In the Sardinia case study, the scenario-based analysis demonstrated that renewable energy integration and coordinated energy sharing significantly improved territorial self-sufficiency under optimized REC configurations. The geospatial modelling approach also enabled the identification of suitable renewable deployment scenarios while considering environmental and territorial constraints. The results indicate that the integration of energy modelling, digital monitoring systems, and spatially explicit planning tools provides an effective pathway for improving the operational performance, flexibility, and scalability of RECs. The proposed framework offers practical support for decentralized energy planning, distributed renewable energy management, and data-driven decision-making processes in future community-based energy systems.
This study addresses the growing role of Renewable Energy Communities (RECs) in supporting decentralized renewable energy integration and improving local energy self-sufficiency within the European energy transition framework. The work aimed to evaluate the technical and economic feasibility of a municipal REC in Pattada, a small municipality located in Sardinia, Italy, through an energy balance analysis based on distributed photovoltaic generation and shared electricity consumption. A techno-economic assessment framework was developed by combining the estimated electricity production of municipally owned photovoltaic systems with the load profiles of municipal, commercial, and residential users participating in the REC. The photovoltaic energy production was estimated using the Photovoltaic Geographical Information System (PVGIS) simulation platform, while the shared energy within the REC was evaluated by considering the simultaneity between electricity generation and demand under different residential participation scenarios. The results showed that the municipal photovoltaic systems achieved an annual electricity production of approximately 506.41 MWh, while direct physical self-consumption remained limited to 3.10 MWh/year due to the mismatch between municipal demand and photovoltaic generation profiles. The analysis further showed that the REC reached an energy equilibrium condition with the participation of 285 residential users, corresponding to nearly 23% of the households within the municipality, allowing virtually shared energy to reach 425.92 MWh/year. The economic evaluation demonstrated that the municipal administration obtained the highest share of the overall economic return, mainly driven by electricity exported to the grid and incentive revenues associated with shared energy. The results indicate that the integration of municipally owned photovoltaic systems within REC configurations provides an effective approach for improving local energy sharing and enhancing the economic viability of distributed renewable energy systems in small municipalities. The proposed framework offers practical support for local administrations in planning renewable energy investments and optimizing REC configurations under real operating conditions.
Renewable Energy Communities (RECs) play an increasingly important role in decentralized energy systems by improving local renewable energy utilization, enhancing energy flexibility, and supporting low-carbon energy transitions. However, the integration of distributed energy resources (DERs), flexible electrical loads, and energy sharing mechanisms continues to create operational and management challenges for REC-based systems. This study investigates the energy management and optimization of a residential REC in Italy composed of photovoltaic (PV) generation, battery storage systems, and flexible air-conditioning loads. A detailed optimization framework was developed to coordinate DERs and flexible demand with the objective of maximizing shared energy utilization and related economic incentives while maintaining user comfort and avoiding additional electricity costs. The regulatory framework and operational structure of RECs in Europe and Italy were also examined to support the development of the proposed management strategy. The optimization process was conducted under different operating conditions to evaluate the influence of coordinated load management on REC performance. The results showed that the coordinated control of battery storage systems and air-conditioning units improved shared renewable energy utilization and increased the economic return associated with energy sharing. The optimized operation strategy also reduced electricity costs for users while improving the operational efficiency of the community energy system. The findings indicate that advanced energy management and load coordination strategies provide an effective approach for enhancing the performance of distributed renewable energy systems and supporting the practical implementation of REC-based energy infrastructures.
In the context of conflicting empirical evidence regarding the effectiveness of green bonds on renewable energy investment, this study posits that the inconsistency in prior findings may stem from overlooking the role of the institutional environment. Accordingly, the study aims to examine the direct association between green bonds and renewable energy investment while analyzing the moderating role of political stability in this relationship. Using a panel dataset of 236 country-year observations from 16 emerging Asian economies over the 2010–2024 period, the study employs a Fixed Effects Model (FEM) with interaction terms and Driscoll-Kraay standard errors, complemented by robustness checks using System Generalized Method of Moments (GMM) estimation. The results reveal that green bonds are positively associated with renewable energy investment ($\beta_1$ = 0.158; $p$ $<$ 0.01). More importantly, the positive interaction coefficient ($\beta_3$ = 0.092; $p$ $<$ 0.10) suggests that political stability amplifies the association between green bonds and renewable energy investment. While this interaction effect is only marginally significant in the main specification, it gains further support from the System GMM estimation ($\beta_1$ = 0.145; $p$ $<$ 0.05; $\beta_3$ = 0.105; $p$ $<$ 0.05) and from subsample analysis, which reveals that the association between green bonds and renewable energy investment is statistically insignificant in politically unstable countries but strongly positive in stable ones. The study concludes that political stability appears to be an important enabling condition for realizing the potential of green finance in accelerating decarbonization, implying that green bond market development should go hand in hand with institutional reform and environmental governance strengthening.
The reliability and interpretability of the Complex Proportional Assessment (COPRAS) method in multi-criteria decision-making (MCDM) have been critically re-evaluated. Although COPRAS has frequently been promoted as a method capable of separately assessing the influence of benefit and cost criteria without requiring explicit inversion of cost attributes, it is demonstrated that these claims are not fully supported by the mathematical structure of the method. A theoretical analysis reveals that COPRAS inherently relies on Sum normalization, through which hidden attribute prioritization and rating distortion may be introduced. Furthermore, it is shown that, in the presence of a single cost criterion, COPRAS becomes mathematically equivalent to the Weighted Sum Model (WSM) implemented with Sum normalization and a nonlinear inverse-sum transformation of cost criteria. Consequently, the purported methodological distinction between COPRAS and conventional additive aggregation approaches is substantially reduced. Particular attention is drawn to the nonlinear inversion embedded in the COPRAS formulation for cost criteria aggregation. Because the inverse transformation is applied to the total contribution of cost criteria rather than to individual criterion values, the resulting influence of cost attributes on the final utility score is shown to be only indirectly represented. Under certain conditions, significant discrepancies are produced between the nominal and actual contribution of cost criteria, thereby affecting both rating stability and ranking consistency. Through numerical demonstrations and comparative analyses, distortions in alternative ratings and rank reversals are identified when COPRAS results are compared with those obtained from the conventional WSM framework. The analysis further indicates that the observed inconsistencies are primarily associated with the combined effects of Sum normalization and nonlinear cost treatment. To address these limitations, the WSM integrated with a linear cost-transformation procedure based on the Reverse Sorting (ReS) algorithm is proposed as a more transparent and mathematically consistent alternative. The findings suggest that the application of COPRAS in practical MCDM problems should be approached with caution, particularly in decision environments where ranking sensitivity and interpretability are of critical importance.
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