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Found 6515 publications
Alleviating energy poverty through grid modernization: Micro-evidence from China's ultra-high-voltage transmission projects
Publication Name: Energy Policy
Publication Date: 2026-10-01
Volume: 217
Issue: Unknown
Page Range: Unknown
Description:
As renewable energy generation and ultra-high-voltage (UHV) transmission technologies continue to advance, long-distance power transmission is increasingly reshaping energy allocation and household welfare. Using data from the China Family Panel Studies (CFPS) and a stacked difference-in-differences (stacked DID) approach, this study examines the impact of UHV transmission projects on household energy poverty and explores the underlying channels. The results show that UHV projects significantly alleviate household energy poverty, and the findings remain robust across a series of robustness checks. Heterogeneity analysis indicates that the poverty-reducing effect is stronger for low-education households, low-income households, and households with elderly members, suggesting that UHV projects disproportionately benefit more vulnerable groups. We further find that UHV projects transmitting clean or mixed electricity have a stronger effect than those relying mainly on thermal power. Furthermore, the beneficial impact of UHV projects appears to be more pronounced under heightened geopolitical risk and uncertainty. The mechanism analysis suggests that UHV projects alleviate energy poverty primarily by expanding employment opportunities, facilitating labor reallocation away from agricultural activities, and reducing household electricity expenditure. These findings highlight the welfare implications of large-scale transmission infrastructure and suggest that grid integration can serve as an important policy instrument for simultaneously advancing energy security, clean energy transition, and energy poverty reduction.
Open Access: Yes
Numerical simulation on thermal performance of a flat-plate module with fins and nanoparticles in a latent energy storage system
Publication Name: Energy
Publication Date: 2026-09-30
Volume: 360
Issue: Unknown
Page Range: Unknown
Description:
Phase change materials are applied in heat storage systems because of their high latent heat. The low thermal conductivity of phase change materials limits the heat transfer rate. Rectangular grille fins, semicircular wave fins, cosine wave fins, and triangular wave fins are designed to enhance the heat transfer rate in flat-plate storage modules. The addition of Al2 O3 , CuO, and Fe3 O4 at 1 %, 3 %, 5 %, and 7 % volume fractions is investigated based on the triangular wave fins to improve the heat storage performance. Compared with the finless structure, the complete melting time of phase change materials is reduced by 4.70 %, 7.10 %, 9.15 %, and 10.71 % in rectangular grille fins, semicircular wave fins, cosine wave fins, and triangular wave fins modules. The heat storage power of a triangular fin module increases by 7.88 % relative to the finless module. The melting time is shortened for all nanoparticles as the volume fraction increases, accompanied by an increase in the average temperature. The melting rate of phase change materials is improved by 16.84 % with the addition of 7 % Al2 O3 nanoparticles and triangular wave fins relative to the bare cavity. Compared with pure phase change materials, the heat storage power is improved by 11.11 % owing to the synergistic effect of triangular wave fins and Al2 O3 nanoparticles. Enhancement strategies for latent heat storage systems are provided through the synergistic combination of periodic fins and nanoparticles.
Open Access: Yes
How data factors drive green productivity: Mechanisms and evidence
Publication Name: Energy
Publication Date: 2026-09-30
Volume: 360
Issue: Unknown
Page Range: Unknown
Description:
Data has become an increasingly important production factor in the green transition, yet its independent contribution to green total factor productivity (GTFP) remains insufficiently understood. Using panel data for 30 Chinese provinces from 2011 to 2023, this study constructs a composite index of data factors and measures GTFP using the SBM-GML approach. A two-way fixed effects framework is combined with mediation, threshold, and spatial econometric models to examine the effect of data factors on green productivity. Four main conclusions are obtained: (1) Data factors significantly promote GTFP. Economically, a one-standard-deviation increase in the index of data factors raises GTFP by 0.311, equivalent to 25.3% of the sample mean of GTFP. This result remains robust after a series of robustness and endogeneity tests, with the instrumental-variable estimate reaching 6.203. (2) Industrial structure upgrading, green technological innovation, and environmental regulation are important transmission channels. (3) The effect is nonlinear, with estimated thresholds of 0.238 and 0.239, and the promoting effect is strongest in the middle regime. (4) Data factors also generate positive spatial spillovers, part of which are transmitted through financial agglomeration. These findings underscore the important role of data factors development in advancing energy-efficient green transformation.
Open Access: Yes
Assessing climate uncertainty in green bonds: Evidence from machine learning and GARCH-MIDAS models
Publication Name: Environmental Impact Assessment Review
Publication Date: 2026-09-01
Volume: 121
Issue: Unknown
Page Range: Unknown
Description:
This paper employs a GARCH-MIDAS framework integrated with machine learning to investigate the impact of climate-related uncertainties on the volatility of the China's green bond market (GBM). By combining high-frequency financial data with multi-source, low-frequency climate uncertainty indicators, we examined how macro-financial conditions and climate risks jointly affect the dynamic changes of the GBM in China. Machine learning methods were used to identify and rank the key drivers of volatility. The research results indicate that traditional macro-financial variables remain the main determinants of the volatility in the green bond market, among which the impact of government bond yields is the most significant. Climate uncertainty information also has a significant impact on the volatility of green bonds. Moreover, incorporating climate uncertainty into the GARCH-MIDAS model significantly enhances its explanatory power, highlighting the importance of considering mixed-frequency risk factors in understanding China's green bond market dynamics. These findings underscore the crucial role of climate uncertainty in green bond pricing and indicate that combining machine learning with mixed-frequency volatility modeling can provide a more comprehensive framework for understanding the dynamics of the green bond market.
Open Access: Yes
Perceived fairness in access to higher education in wartime Ukraine: Social inequalities and trust in admission testing
Publication Name: Regional Science Policy and Practice
Publication Date: 2026-09-01
Volume: 18
Issue: 9
Page Range: Unknown
Description:
The accessibility of higher education during wartime is an essential tool for reducing inequality, retaining talent for post-war recovery, and advancing human development. To increase access to higher education amid a deficit in public finances, Ukraine has introduced mandatory Standardised Admission Testing to fairly assess academic achievement and create a level playing field when choosing a speciality and a higher education institution. At the same time, public perception of fairness and equality in university admissions has changed significantly during the war, as our study shows. Its empirical basis is data from a representative national survey conducted in 2021, 2023, and 2025, which included 5123 respondents. As found, young people, both before the full-scale invasion (2021) and during the full-scale war, placed the most trust in national testing, compared to older age groups, including the generation of parents. Besides, regional differences are evident: residents of the West had significantly higher trust in testing in 2021, but trust later increased in the central and eastern regions as well. Across all demographic characteristics, the share of respondents expressing trust increased in 2023 compared to 2021. In 2025, trust decreased significantly. The most consistent differences were observed by age and region, while income and settlement-type differences appeared primarily at the bivariate level or under specific contextual conditions. Thus, higher levels of trust were observed among residents of urban-type settlements and smaller cities, as well as among higher-income groups, although these patterns were not consistent across all models and waves. The results provide partial support for the proposed hypotheses and carry implications for state policies aimed at strengthening equal access to higher education for youth.
Open Access: Yes
Optimization-based decision workflow for designing regional renewable energy systems
Publication Name: Energy
Publication Date: 2026-09-01
Volume: 358
Issue: Unknown
Page Range: Unknown
Description:
The systematic planning of regional energy systems remains an issue of utmost importance for modern society. Thus, developing tools for effective design and communication with regional actors remains a relevant goal in research. This work presents an optimization-based decision workflow for regional energy planning aimed at enhancing stakeholder engagement and supporting informed decision-making during early design stages. Decision-making takes place within administrative units that exercise governmental functions through a top-down decentralization of responsibilities, often via federal structures. Within a given state, these units may include regions, counties, or political districts, as classified by the levels of the NUTS (Nomenclature of Territorial Units for Statistics) system. Consequently, within the decision-support process, stakeholders typically comprise the leaders of these administrative units, who possess substantive operational influence over the development of their respective entities. The proposed workflow integrates a rigorous optimization approach that permits the systematic generation of multiple solutions and the assessment of various scenarios for a given territory. The methodology is demonstrated through a case study in Carnica-Rosental, Austria, wherein four scenarios served as a platform for stakeholder dialogue and the development of integrated regional energy systems. The proposed workflow offers a powerful decision-support tool for systematic regional energy planning capable of providing insightful information about the region and serving as a platform for policymaking.
Open Access: Yes
Evaluation of recycled polyethylene terephthalate in asphalt concrete: Laboratory characterization and finite element modelling
Publication Name: Results in Engineering
Publication Date: 2026-09-01
Volume: 31
Issue: Unknown
Page Range: Unknown
Description:
The increasing generation of plastic waste and the growing demand for sustainable pavement materials have encouraged the incorporation of recycled polymers into asphalt mixtures. This study evaluates the engineering performance, microstructural characteristics, numerical response, and preliminary environmental implications of recycled polyethylene terephthalate (RPET)-modified asphalt concrete. RPET obtained from post-consumer plastic bottles was incorporated into asphalt mixtures through the dry process at dosages of 0–9% by weight of binder. Marshall stability, indirect tensile strength (ITS), repeated load dynamic creep (RLDC), scanning electron microscopy (SEM), and finite element modelling (FEM) were employed to assess the influence of RPET content on mixture behavior. Experimental results showed that increasing RPET content improved stiffness-related properties and rutting resistance. Marshall stability increased from 5.5 kN for the control mixture to 14.3 kN at 9% RPET, while ITS increased from 0.72 MPa to 1.02 MPa. RLDC results indicated a reduction in accumulated permanent strain from 3.20% to 1.85%, demonstrating enhanced resistance to deformation under repeated loading. SEM observations revealed comparatively uniform RPET dispersion at moderate dosages (3–5%), whereas higher contents showed localized particle agglomeration. FEM simulations demonstrated reduced surface deflection and improved stress distribution with increasing RPET-related stiffness. Preliminary life cycle assessment indicated modest embodied carbon reduction and potential cost savings. The findings suggest that RPET incorporation can enhance the mechanical and deformation-resistant characteristics of asphalt mixtures while contributing to plastic waste valorization and sustainability objectives. However, the results should be interpreted as comparative laboratory and numerical indicators rather than direct predictors of long-term field performance.
Open Access: Yes
Rethinking sustainable growth: technological and supply chain drivers of the U.S. production-based ecological footprint
Publication Name: Resources Conservation and Recycling Advances
Publication Date: 2026-09-01
Volume: 31
Issue: Unknown
Page Range: Unknown
Description:
The United States (U.S.) has one of the highest production-based ecological footprints (EFP) in the world. Consequently, reducing EFP is essential for ensuring ecological balance, protecting the environment, and reducing ecological degradation. However, the comparative analysis on the long-run associations of AI innovation (AIN), high-tech trade capability (HTTC), supply chain efficiency (SCE), information and communication technology investment growth (ICTIG), and GDP growth (GDPG) with EFP regarding the U.S. remains poorly understood. Using the autoregressive distributed lag (ARDL) method, this study shows a comparative analysis of the EFP’s determinants relying on the U.S. national level data from 1990 to 2023. Based on the ARDL findings, while AIN, SCE, and HTTC show statistically significant association with EFP in the long run, ICTIG and GDPG do not exhibit significant empirical association. Among three significant associations, AIN and SCE are associated with reductions in ecological footprint in the long run, indicating that the country has secured technology-driven ecological benefits and operational efficiency enhancement within the production dynamics by emphasizing AI innovation and efficient inventory management. In contrast, HTTC’s positive association represents significant ecological pressure with the high tech-industries technology advancement, driven by scale and rebound effects. All the results remained stable in FMOLS, DOLS, and CCR robustness tests. Besides, Granger causality indicates mixed predictive patterns of these relationships. The comparative analysis among these determinants' long-run associations with EFP significantly contributes to the single country level production-based ecological footprint literature and depicts several valuable empirical insights for policy actions by the federal government.
Open Access: Yes
Mathematical frameworks for left ventricular assist device therapy: Ventricular mechanics, blood rheology, haemodynamics, control, and nonlinear dynamics
Publication Name: Progress in Biophysics and Molecular Biology
Publication Date: 2026-09-01
Volume: 201
Issue: Unknown
Page Range: 152-174
Description:
Ventricular assist devices (VADs) integrate multiple branches of applied mechanics within a single implanted system, spanning rotor-scale haemodynamics, nonlinear ventricular wall mechanics, blood trauma, and closed-loop control under changing physiological loads. This review aims to unify five mathematical frameworks central to VAD modelling: ventricular mechanics, blood rheology and damage, partial differential equation (PDE)-based device haemodynamics, pump engineering, and nonlinear heart–device dynamics. By bringing these domains together, the review clarifies their interactions and highlights unresolved mathematical challenges that limit progress in design, control, and prediction. An expository narrative review was conducted in accordance with the Scale for the Assessment of Narrative Review Articles (SANRA); a completed SANRA checklist is provided as Supplementary Material. Relevant literature was identified through targeted searches of PubMed, Scopus, and Web of Science, supplemented by citation tracking. Studies were selected for mathematical relevance, with emphasis on formulations that recur across VAD research, reveal model limitations, or connect analytical structure to clinically important complications. Major LVAD complications, including pump thrombosis, haemolysis, suction instability, and acquired von Willebrand syndrome, map onto distinct but interacting mathematical domains. Important cross-disciplinary links emerge between statistical mechanics and continuum damage models, between bifurcation theory and proportional–integral controller design, and between reduced-order cardiovascular models and full fluid–structure interaction simulations. Several formulations currently used in clinical, or engineering practice appear to extend beyond their original validation range. The mathematical problems underlying VAD therapy are strongly coupled and, in several areas, remain open. Advances in fluid–structure interaction theory, first-principles haemolysis modelling, and bifurcation analysis of the heart–pump oscillator could substantially improve device design, controller safety, and clinical outcome prediction.
Open Access: Yes
