Search Results (1,541)

This research evaluates the financial sustainability of a basic income (BI) model funded through carbon taxation in Türkiye. Unlike classical BI models that provide unconditional transfers to everyone, this study proposes an income support scheme targeted only at those below the poverty line. The model seeks to balance limited resources with the goal of social equity. In this scenario, sectoral carbon taxation evolves progressively. The tax starts with the energy sector, which has the highest emissions, and subsequently shifts to industry and other sectors. Emissions will be reduced by 1% each year, while a carbon tax that starts at USD 12 per ton will be dynamically converted to TL based on the increasing exchange rate year by year. The simulation looks at 2023–2050 and computes annual revenue and expenditure forecasts for the period. The findings indicate that the revenues from carbon taxation are not only sufficient to cover the prioritized expenditure in the targeted basic income (TBI) scheme but also will lead to fiscal surplus in the long run. The research proposes for the first time a framework which integrates social protection and the environmental taxation of carbon, synergizing policies aimed at alleviating income disparity and climate change within Türkiye’s context. Full article

This paper investigates technological pathways for the conversion of coal-fired power plants toward sustainable energy sources, using an integrated multi-criteria decision-making approach that combines Proknow-C, AHP, and PROMETHEE. Eight alternatives were identified: full conversion to natural gas, full conversion to biomass, coal and natural gas hybridization, coal and biomass hybridization, electricity and hydrogen cogeneration, coal and solar energy hybridization, post-combustion carbon capture systems, and decommissioning with subsequent reuse. The analysis combined bibliographic data (26 scientific articles and 13 patents) with surveys from 14 energy experts, using Total Decision version 1.2.1041.0 and Visual PROMETHEE version 1.1.0.0 software tools. Based on six criteria (environmental, structural, technical, technological, economic, and social), the most viable option was full conversion to natural gas (ϕ = +0.0368), followed by coal and natural gas hybridization (ϕ = +0.0257), and coal and solar hybridization (ϕ = +0.0124). These alternatives emerged as the most balanced in terms of emissions reduction, infrastructure reuse, and cost efficiency. In contrast, decommissioning (ϕ = −0.0578) and carbon capture systems (ϕ = −0.0196) were less favorable. This study proposes a structured framework for strategic energy planning that supports a just energy transition and contributes to the United Nations Sustainable Development Goals (SDGs) 7 and 13, highlighting the need for public policies that enhance the competitiveness and scalability of sustainable alternatives. Full article

This study analyzed shoreline evolution (2000–2024) at Dalian World Peace Park’s sandy tourist beach using GEE, CoastSat, and DSAS. At the same time, combined with the grain size analysis of beach sediments before and after typhoons, the impact of extreme events on the shoreline line changes was explored. The DSAS shows a spatial differentiation pattern of the southern shoreline retreat trend zone, the central shoreline dynamic balance trend zone and the northern shoreline advance trend zone. The 2008 reclamation project altered hydrodynamics, creating an artificial headland effect that triggered significant northern shoreline advancement (max 74.16 m) and southern retreat (27.14 m), demonstrating unforeseen long-term trade-offs of large-scale interventions. Subsequent cobble structures, acting as a nature-based solution, enhanced sediment retention and wave energy refraction, promoting dynamic equilibrium and shoreline resilience. However, the 2017 double typhoon caused instantaneous retreat with finer, poorly sorted sediment, highlighting persistent vulnerability to extreme events. This study underscores the critical need for adaptive management within a sustainable shoreline development framework. Full article

Traditional urbanization prioritizes economic growth but often degrades the environment, challenging SDGs 9 and 13. China’s New-Type Urbanization Policy (NTUP) balances economic expansion, energy conservation, and environmental protection. By applying the difference-in-differences (DID) method, this study examines the causal effect of NTUP on urban air quality, taking the full implementation of NTUP in 2014 and the designated pilot cities as the policy shock and treatment group, respectively. Furthermore, we explore the mediating roles of land use efficiency and innovation efficiency in this relationship. The results show the following: (1) NTUP significantly lowers urban PM2.5, robust to confounders and selection bias; (2) land use and innovation efficiency mediate this effect, verified by Sobel and Bootstrap tests; and (3) policy effectiveness varies by city level, industrial base, and economic structure. These findings highlight NTUP’s environmental benefits and inform sustainable urbanization strategies globally. Full article

This study investigates the energy consumption characteristics of individual and clustered thermal storage electric heating systems, focusing on their sustainability implications for regional load distribution and user energy consumption patterns. Simulation results show that thermal storage electric heating shifts peak energy demand from daytime to nighttime low-price hours, reducing electricity costs and optimizing grid load balancing. As the proportion of thermal storage electric heating increases from 10% to 30%, the daytime minimum load reduction rate rises from 7% to 22%, while the nighttime maximum load increase rate increases from 16% to 63%. This operational mode supports sustainable energy usage by alleviating daytime grid peak pressure and leveraging low-cost, off-peak electricity for heat storage. The findings highlight the potential of thermal storage electric heating to enhance energy efficiency, integrate renewable energy, and promote grid stability, contributing to a more sustainable energy system. Full article

Despite numerous global initiatives, such as the Sustainable Development Goals (SDGs) and the implementation of environmental, social, and governance (ESG) metrics aimed at mitigating climate change, promoting social welfare, and addressing a variety of other causes, progress has been significantly slower than expected, particularly in developing economies. Thus, we attempted to link corporate ESG to sustainable development. It was also investigated whether ESG contributes to a reduction in corporate risk. Using panel data and the Generalized Method of Moments (GMM) technique, we examine the relationship between ESG scores and important financial risk indicators such as systematic risk (beta), stock price volatility, unsystematic risk, and the cost of capital (WACC). The findings show that corporations place a disproportionate emphasis on governance (G) rather than environmental (E) and social (S) characteristics. ESG and G governance were also found to be statistically significant predictors of financial risk. This disparity shows that companies may be using high governance scores to conceal underperformance in environmental and social issues, raising worries about greenwashing and superficial compliance. As a result, their contributions to SDGs such as affordable and clean energy (SDG 7), climate action (SDG 13), and reduced inequalities (SDG 10) are minimal. The findings highlight the need for a more open, balanced, and integrated ESG approach, one that not only promotes sustainable development but also improves long-term financial resilience. Full article

Hybrid thermoelectric generators (HTEGs) play a pivotal role in sustainable energy conversion by harnessing waste heat through the Seebeck effect, contributing to global efforts in energy efficiency and environmental sustainability. In practical sustainable energy systems, HTEG output performance is significantly influenced by uncertainties in the operational parameters (such as temperature differences and load resistance), material properties (including Seebeck coefficient and resistance), and structural configurations (like the number of series/parallel thermoelectric components), which impact both efficiency and system stability. This study employs the Sobol-sequence-sampling method to characterize these parameter uncertainties, analyzing their effects on HTEG output power and conversion efficiency using mean values and standard deviations as evaluation metrics. The results show that higher temperature differences enhance output performance but reduce stability, a larger load resistance decreases performance while improving stability, thermoelectric materials with high Seebeck coefficients and low resistance boost efficiency at the expense of stability, increasing series-connected components elevates performance but reduces stability, parallel configurations enhance power output yet decrease efficiency and stability, and greater contact thermal resistances diminish performance while enhancing system robustness. This research provides theoretical guidance for optimizing HTEGs in sustainable energy applications, enabling the development of more reliable, efficient, and eco-friendly thermoelectric systems that balance performance with environmental resilience for long-term sustainable operation. Full article

This study investigates the influence of hybrid filler systems comprising carbon black (CB), mica, and surface-modified mica (SM) on the properties of ethylene–propylene–diene monomer (EPDM)/butadiene rubber (PB) composites. To reduce the environmental issues associated with CB, mica was incorporated as a partial substitute, and its compatibility with the rubber matrix was enhanced through surface modification using ureidopropyltrimethoxysilane (URE). The composites with hybrid filler systems and surface modification were evaluated in terms of curing behavior, crosslink density, mechanical and elastic properties, and dynamic viscoelasticity. Rheological analysis revealed that high mica loadings delayed vulcanization due to reduced thermal conductivity and accelerator adsorption, whereas SM composites maintained comparable curing performance. Swelling tests showed a reduction in crosslink density with increased unmodified mica content, while SM-filled samples improved the network density, confirming enhanced interfacial interaction. Mechanical testing demonstrated that the rubber compounds containing SM exhibited average improvements of 17% in tensile strength and 20% in toughness. In particular, the CB20/SM10 formulation achieved a well-balanced enhancement in tensile strength, elongation at break, and toughness, surpassing the performance of the CB-only system. Furthermore, rebound resilience and Tan δ analyses showed that low SM content reduced energy dissipation and improved elasticity, whereas excessive filler loadings led to increased hysteresis. The compression set results supported the thermal stability and recovery capacity of the SM-containing systems. Overall, the results demonstrated that the hybrid filler system incorporating URE-modified mica significantly enhanced filler dispersion and rubber–filler interaction, offering a sustainable and high-performance solution for elastomer composite applications. Full article

Life cycle assessment (LCA) is a standardized tool (ISO 14040) used to evaluate the environmental impacts of products and processes across their entire life cycle, from raw material extraction to end-of-life disposal or recycling. It has become particularly important in the context of engineering materials, where sustainability considerations are critical. Despite challenges such as data quality limitations, variations in system boundary definitions, and methodological inconsistencies, LCA remains an essential tool for assessing and improving product sustainability. This work presents a foundational overview of LCA principles and describes a systematic, step-by-step procedure for its effective application. Additionally, this article revisits the fundamental concepts of carbon footprint (CF) analysis as a complementary tool for quantifying greenhouse gas emissions associated with products and activities. CF analysis underscores the necessity of adopting low-carbon materials and manufacturing processes to minimize embodied energy and reduce environmental emissions. Low-carbon materials are characterized by attributes such as being lightweight, recyclable, renewable, bio-based, locally sourced, and safe for public health. Their development balances the reduction of raw material and resource consumption during production, with increasing product performance, recyclability, and service life, reflecting a cradle-to-cradle, circular economy approach. The integration of LCA and CF methodologies provides an integral framework for assessing environmental performance and supports decision-making processes aligned with global sustainability targets. Full article

Optimizing thermoelectric (TE) performance in two-dimensional materials has emerged as a pivotal strategy for sustainable energy conversion. This study systematically investigates the regulatory mechanisms of uniaxial strain (−2% to +2%), temperature (300–800 K), and out-of-plane electric fields (0–1.20 eV/Å) on the thermoelectric properties of monolayer MoS₂ via first-principles calculations combined with Boltzmann transport theory. Key findings reveal that uniaxial strain modulates the bandgap (1.56–1.86 eV) and carrier transport, balancing the trade-off between the Seebeck coefficient and electrical conductivity. Temperature elevation enhances carrier thermal excitation, boosting the power factor to 28 × 10¹⁰ W·m⁻¹·K⁻²·s⁻¹ for p-type behavior and 27 × 10¹⁰ W·m⁻¹·K⁻²·s⁻¹ for n-type behavior at 800 K. The breakthrough lies in the exceptional suppression of lattice thermal conductivity (κ₁) by out-of-plane electric fields—at 1.13 eV/Å, κ₁ is reduced to single-digit values (W·m⁻¹·K⁻¹), driving ZT to ~4 for n-type MoS₂ at 300 K. This work demonstrates that synergistic engineering of strain, temperature, and electric fields effectively decouples the traditional trade-off among the Seebeck coefficient, conductivity, and thermal conductivity, providing a core optimization pathway for 2D thermoelectric materials via electric field-mediated κ₁ regulation. Full article

This on-farm study explored the effects of diverse pasture systems and seaweed bio-stimulants (AgriSea NZ Seaweed Products, Paeroa, New Zealand) on sheep performance, metabolic health, milk composition, and carcass characteristics. A 3 × 2 factorial design was used to compare three pasture systems; ryegrass-white clover (RW), a 23-species diverse mix (DI), and functionally diverse strip swards (ST), with (SW) or without (CO) a seaweed bio-stimulant. Ninety pregnant ewes were stratified by live weight and allocated across six treatment groups (15 ewes per treatment). Lambing occurred on treatment paddocks. At weaning, 90 lambs (15 per treatment) were selected based on body weight and sex balance to continue through to finishing. Pasture chemical composition differed among treatments: ST had lower fibre (neutral detergent fibre, NDF; acid detergent fibre, ADF) than RW and DI, while SW increased dry matter digestibility (DMD) and metabolisable energy (ME), and reduced NDF and ADF (p < 0.05). Strip pastures improved lamb average daily gain (ADG) by 17% from lambing to weaning compared to DI, and by 14% from weaning to finishing compared to RW (p < 0.05). Seaweed bio-stimulant treatment enhanced lamb ADG by up to 12% and improved carcass traits, including loin and shoulder yields (p < 0.05). Ewes and lambs on seaweed-treated pastures exhibited lower serum non-esterified fatty acid (NEFA) concentrations (p < 0.05), indicating better energy balance. Milk from ST and/or SW treated ewes had elevated omega-6 fatty acids and essential amino acids, suggesting enhanced nutritional value. These findings demonstrate that combining botanical diversity with natural bio-stimulants can improve animal growth, metabolic health, and product quality, offering a promising strategy for sustainable and welfare-oriented sheep production systems. Full article

Traditional crosslinked-polyethylene (XLPE) insulation suffers from high recycling costs and low efficiency due to its thermosetting properties. In contrast, thermoplastic polypropylene (PP), with advantages of melt recyclability, low energy consumption, and excellent comprehensive performance, has emerged as an ideal alternative to XLPE. This study conducts a comparative analysis of low-voltage cables insulated with PP, silane-crosslinked XLPE (XLPE-S), and UV-crosslinked XLPE (XLPE-U), focusing on production processes, mechanical properties, thermal stability, and electrical performance. Tensile test results show that PP exhibits the highest elongation at break (>600%) before aging, and its tensile strength (>20 MPa) after aging outperforms that of XLPE, indicating superior flexibility and anti-aging capability. PP exhibits a lower thermal elongation (<50%) at 140 °C compared to XLPE, and its high-crystallinity molecular structure endows better heat-resistant deformation performance. The volume resistivity of PP reaches 9.2 × 10¹⁵ Ω·m, comparable to that of XLPE-U (3.9 × 10¹⁵ Ω·m) and significantly higher than XLPE-S (3.0 × 10¹⁴ Ω·m). All three materials pass the 4-h voltage withstand test, confirming their satisfied insulation reliability. PP-insulated low-voltage cables demonstrate balanced performance in production efficiency, energy consumption cost, mechanical toughness, and electrical insulation. Notably, their recyclability significantly surpasses traditional XLPE, showing potential to promote green upgrading of the cable industry and providing a sustainable insulation solution for low-voltage power distribution systems. Full article

Objectives: Obesity has become a major health issue, with multifactorial etiologies involving lifestyle, genetic, and neuroendocrine mechanisms. Despite public health campaigns and lifestyle interventions, long-term weight loss is often difficult to achieve or sustain. This literature review aims to summarize current knowledge on the main molecular mechanisms that hinder weight loss and to summarize the newest therapeutic strategies targeting obesity. Methods: The literature review was conducted using PubMed, Scopus, and Web of Science databases, with a preference for peer-reviewed original articles, systematic reviews, and meta-analyses. Eligible studies were required to be published in the English language and within the last ten years (2015–2025), with the exception of historically significant publications. A total of 112 articles were included in our review. Results: Obesity is a complex, chronic, recurrent metabolic condition that requires personalized, multidisciplinary treatment approaches. In this review, we summarize the major molecular mechanisms underlying weight gain and weight maintenance in obesity. In this literature review, we address the metabolic memory and epigenetics that act through DNA and histone modifications and micro interfering RNAs, resulting in an energy imbalance that can be passed on to further generations. The dysfunction of adipose tissue contributes to chronic low-grade inflammation and insulin resistance, leading to more severe obesity. The ratio of white, beige, and brown adipocytes also plays an important role in regulating energy balance. Novel medical interventions offer promising results in attenuating these mechanisms against successful weight loss. Conclusions: Current interventions, including calorie restriction, physical activity, and pharmacological treatment together, may show great promise in combating obesity, but long-term efficacy and safety remain to be established. Full article

The assessment of grid-connected systems depends on their cost efficiency, reliability, and greenhouse gas (GHG) reduction potential. This study presents a multi-objective optimization framework for designing a grid-connected photovoltaic (PV) and battery energy storage (BES) system integrated with an electric vehicle (EV) for a household in Riyadh, Saudi Arabia. The framework aims to minimize the Cost of Energy (COE) and Loss of Power Supply Probability (LPSP) while maximizing the Renewable Energy Fraction (REF). Additionally, GHG emissions are evaluated as a result of these objectives. The EV operates in Vehicle-to-Home (V2H) mode, enhancing system flexibility and energy management. The optimization process employs two advanced metaheuristic techniques, Multi-Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Harris Hawks Optimization (MOHHO), to identify Pareto front solutions. Fuzzy logic is then applied to determine a balanced compromise among the economically optimal (minimum COE), renewable energy-oriented (maximum REF), and environmentally optimal (minimum GHG emissions) solutions. Simulation results show that the proposed system achieves a COE of USD 0.0554/kWh, a LPSP of 1.96%, and an REF of 92.55%. Although the COE is slightly higher than that of the grid, the system provides significant environmental and renewable energy benefits. This study highlights the potential of integrating dynamic EV management and advanced optimization techniques to enhance the performance of grid-connected systems. The findings demonstrate the effectiveness of combining Pareto-based optimization with fuzzy logic to achieve balanced solutions addressing economic, environmental, and renewable energy objectives, paving the way for sustainable energy systems in urban households. Full article

Buildings are significant contributors to global energy consumption and greenhouse gas emissions, with air conditioning systems representing a large share of this demand. Multi-building cooperative energy management is a promising solution for improving energy efficiency, but traditional control methods often struggle with dynamic environments and complex interactions. This study proposes an enhanced Soft Actor–Critic (SAC) algorithm, termed ORAR-SAC, to address these challenges in building cluster energy management. The ORAR-SAC integrates an Ordered Reward-based Experience Replay mechanism to prioritize high-value samples, improving data utilization and accelerating policy convergence. Additionally, an adaptive temperature parameter regularization strategy is implemented to balance exploration and exploitation dynamically, enhancing training stability and policy robustness. Using the CityLearn simulation platform, the proposed method is evaluated on a cluster of three commercial buildings in Beijing under time-of-use electricity pricing. Results demonstrate that ORAR-SAC outperforms conventional rule-based and standard SAC strategies, achieving reductions of up to 11% in electricity costs, 7% in peak demand, and 3.5% in carbon emissions while smoothing load profiles and improving grid compatibility. These findings highlight the potential of ORAR-SAC to support intelligent, low-carbon building energy systems and advance sustainable urban energy management. Full article