Search Results (2,595)

Driven by the urgent need to decarbonize the logistics sector—where conventional vehicles exhibit high energy consumption and emissions, posing significant environmental sustainability challenges—electrification represents a pivotal strategy for reducing emissions and achieving sustainable urban freight transport. Despite rising global electric vehicle sales, the penetration rate of electric logistics vehicles (ELVs) remains comparatively low, impeding progress toward sustainable logistics objectives. Battery-swapping mode (BSM) has emerged as a potential solution to enhance operational efficiency and economic viability, thereby accelerating sustainable adoption. This model improves ELV operational efficiency through rapid battery swaps at centralized stations. This study constructs a tripartite evolutionary game model involving government, consumers, and BSM-ELV manufacturers to analyze market dynamics under diverse strategies. Key considerations include market scale, government environmental benefits, battery leasing/purchasing costs, lifecycle cost analysis (via discount rates), and resource efficiency (reserve battery ratio $\lambda$). MATLAB-2021b-based simulations predict participant strategy evolution paths. Findings reveal that market size and manufacturer expectations significantly influence governmental and manufacturing strategies. Crucially, incorporating discount rates demonstrates that battery leasing reduces consumer enterprises’ initial investment, enhancing economic sustainability and cash flow while offering superior total cost of ownership. Furthermore, gradual reduction of government subsidies effectively stimulates market self-regulation, incentivizes leasing adoption, and bolsters long-term economic/operational sustainability. Market feedback can guide policy adjustments toward fiscally sustainable support mechanisms. This study proposes the following management implications for advancing sustainable logistics: 1. Governments should phase out subsidies systematically to foster market resilience; 2. Manufacturers must invest in BSM R&D to improve efficiency and resource circularity; 3. Consumer enterprises can achieve economic benefits and emission reductions by adopting BSM-ELVs. Full article

Global ambitions for net-zero emissions and resource circularity are propelling industry from linear “make-use-dispose”models toward closed-loop value creation. Remanufacturing, which aims to restore end-of-life products to a “like-new” condition, plays a central role in this transition. However, its stochastic inputs and complex, multi-stage processes pose significant challenges to traditional production planning methods. This study delivers an integrated overview of remanufacturing scheduling by combining a systematic bibliometric review of 190 publications (2005–2025) with a critical synthesis of modelling approaches and enabling technologies. The bibliometric results reveal five thematic clusters and a 14% annual growth rate, highlighting a shift from deterministic, shop-floor-focused models to uncertainty-aware, sustainability-oriented frameworks. The scheduling problems are formalised to capture features arising from variable core quality, multi-phase precedence, and carbon reduction goals, in both centralised and cloud-based systems. Advances in human–robot disassembly, vision-based inspection, hybrid repair, and digital testing demonstrate feedback-rich environments that increasingly integrate planning and execution. A comparative analysis shows that, while mixed-integer programming and metaheuristics perform well in small static settings, dynamic and large-scale contexts benefit from reinforcement learning and hybrid decomposition models. Finally, future directions for dynamic, collaborative, carbon-conscious, and digital-twin-driven scheduling are outlined and investigated. Full article

Active galactic nuclei (AGNs) often exhibit broad-line regions (BLRs), populated by high-velocity clouds in approximately Keplerian orbits around the central supermassive black hole (SMBH) at subparsec scales. During episodes of intense accretion at super-Eddington rates, the accretion disk can launch a powerful, radiation-driven wind. This wind may overtake the BLR clouds, forming bowshocks around them. Two strong shocks arise: one propagating into the wind, and the other into the cloud. If the shocks are adiabatic, electrons and protons can be efficiently accelerated via a Fermi-type mechanism to relativistic energies. In sufficiently dense winds, the resulting high-energy photons are absorbed and reprocessed within the photosphere, while neutrinos produced in inelastic $pp$ collisions escape. In this paper, we explore the potential of super-accreting AGNs as neutrino sources. We propose a new class of neutrino emitter: an AGN lacking jets and gamma-ray counterparts, but hosting a strong, opaque, disk-driven wind. As a case study, we consider a supermassive black hole with $M_{\mathrm{BH}}={10}^6{M}_{\odot }$ and accretion rates consistent with tidal disruption events (TDEs). We compute the relevant cooling processes for the relativistic particles under such conditions and show that super-Eddington accreting SMBHs can produce detectable neutrino fluxes with only weak electromagnetic counterparts. The neutrino flux may be observable by the next-generation IceCube Observatory (IceCube-Gen2) in nearby galaxies with a high BLR cloud filling factor. For galaxies hosting more massive black holes, detection is also possible with moderate filling factors if the source is sufficiently close, or at larger distances if the filling factor is high. Our model thus provides a new and plausible scenario for high-energy extragalactic neutrino sources, where both the flux and timescale of the emission are determined by the number of clouds orbiting the black hole and the duration of the super-accreting phase. Full article

This study addresses this gap by proposing a multilevel fuzzy evaluation model combined with an analytic hierarchy process (AHP) to quantify the greenness of furniture products across their entire lifecycle. Focusing on an office desk as a case study, we developed an indicator system encompassing environmental attributes, resource efficiency, energy consumption, economic costs, and quality performance. Weighting results revealed that environmental attributes (27.2%) and resource efficiency (27.2%) dominated the greenness evaluation, with material recycling rate (33.5%) and solid waste pollution (24.3%) as critical sub-indicators. The prototype achieved a moderate greenness score of 70.38/100, highlighting optimization potential in renewable material adoption (10% current rate) and modular design for disassembly. Mechanically recycled materials could reduce lifecycle emissions by 18–25% in key categories. The model demonstrates scalability for diverse furniture types and informs policy-making by prioritizing high-impact areas such as toxic material reduction and energy-efficient manufacturing, thus amplifying its global and interdisciplinary multiplier effects. Full article

Under the background of “double carbon” and sustainable development, aimed at the problem of resource capacity planning in the integrated energy system (IES), at improving the economy of system planning operation and renewable energy (RE) consumption, and at reducing carbon emissions, this paper proposes a multi-objective bi-level sustainability planning method for IES considering the bilateral response of supply and demand and hydrogen utilization. Firstly, the multi-energy flow in the IES is analyzed, constructing the system energy flow framework, studying the support ability of hydrogen utilization and the bilateral response of supply and demand to system energy conservation, emission reduction and sustainable development. Secondly, a multi-objective bi-level planning model for IES is constructed with the purpose of optimizing economy, RE consumption, and carbon emission. The non-dominated sorting genetic algorithm II (NSGA-II) and commercial solver Gurobi are used to solve the model and, through the simulation, verify the model’s effectiveness. Finally, the planning results show that after introducing the hydrogen fuel cells, hydrogen storage tank, and bilateral response, the total costs and carbon emissions decreased by 29.17% and 77.12%, while the RE consumption rate increased by 16.75%. After introducing the multi-objective planning method considering the system economy, RE consumption, and carbon emissions, the system total cost increased by 0.34%, the consumption rate of RE increased by 0.6%, and the carbon emissions decreased by 43.61t, which effectively provides reference for resource planning and sustainable development of IES. Full article

To investigate the distribution law of gas migration in the gob area of a fully mechanized mining face, the similarity principle was employed, combined with Darcy’s law for porous media seepage, to derive the similarity criteria for simulating gas migration in the gob. An experimental platform for a similar model of the gob area in a fully mechanized mining face was designed and constructed, enabling the regulation of ventilation modes, working face airflow velocity, and gas release in the gob. By adjusting the layout of the tailgate, airflow velocity of the working face, and gas release rate, experimental studies were conducted on the gas flow, gas migration, and variation of gas concentration at the upper corner under different airflow velocities in “U ,” “U + I,” and “U + I” type ventilation modes. The results indicate that the ventilation mode determines the spatial variation law of airflow and gas migration in the gob; the airflow velocity of the working face governs the fluctuation degree and influence range of airflow and gas migration in the gob; and both the ventilation mode and airflow velocity affect gas accumulation at the upper corner. The “U + I” type ventilation mode is most effective in reducing gas concentration at the upper corner. Airflow velocities that are too low or too high are not conducive to gas emission at the upper corner, with the optimal control of gas concentration being achieved when the airflow velocity ranges from 1.5 to 2.5 m/s. The experimental results validate the distribution law of airflow and gas migration in the gob of a fully mechanized mining face, providing a basis for selecting ventilation process parameters for such mining operations. Full article

The star formation rate (SFR) is a crucial astrophysical characteristic for understanding the formation and evolution of galaxies, determining the interplay between the interstellar medium and stellar activity. The mainstream approach to studying stellar properties in galaxies relies on stellar population synthesis models. However, these methods neglect nebular emission, which can bias SFR estimates. Recent studies have indicated that nebular emission is non-negligible in strongly star-forming regions. However, targeted research is currently limited, particularly regarding galaxies at slightly higher redshifts ($z<0.4$). In this work, 696 star-formation galaxies with stellar mass in ${10}^9-{10}^{11}{M}_{\odot }$ are selected from the SDSS-DR18 and their spectra are fitted via the fitting analysis using differential evolution optimization (FADO) technique. FADO self-consistently fits both stellar and nebular emissions in galaxy spectra. The results show that the median $H_{\alpha }$ flux from FADO fitting differs from that of qsofitmore by approximately 0.028 dex. Considering the stellar mass effect, we found that although the nebular emission contribution (Nebular Ratio hereafter) is minimal, it increases modestly with redshift. We advocate explicitly accounting for nebular emission in the spectral fitting of higher-redshift galaxies, as its inclusion is essential to obtaining higher precision in future analyses. Full article

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

Optimizing aeration, fertilization, and irrigation is vital for improving greenhouse tomato production while mitigating soil greenhouse gas (GHG) emissions. This study investigated the combined effects of three aeration levels (A1: single Venturi, A2: double Venturi, CK: no aeration), two fertilization rates (F1: 180 kg/ha, F2: 240 kg/ha), and two irrigation levels (I1: 0.8 E_pan, I2: 1.0 E_pan) on tomato yield, CO₂, N₂O, and CH₄ emissions, net GHG emissions, net global warming potential (NGWP), and GHG intensity (GHGI) across Spring–Summer and Autumn–Winter seasons. Results showed that aeration and fertilization significantly increased CO₂ and N₂O emissions but reduced CH₄ emissions. Warmer conditions in Spring–Summer elevated all GHG emissions and yield compared to Autumn–Winter seasons. Tomato yield, net GHG emissions, NGWP, and GHGI were 12.05%, 24.3%, 14.46%, and 2.37% higher, respectively, in Spring–Summer. Combining the Maximal Information Coefficient and TOPSIS models, the optimal practice was A1-F1-I1 in Spring–Summer and A2-F1-I1 in Autumn–Winter seasons. These results provide a theoretical basis for selecting climate-smart management strategies that enhance yield and environmental sustainability in greenhouse tomato systems. Full article

This paper addresses the synergy between environmental and economic benefits in the green power trading market by constructing a collaborative game model for environmental rights value and electricity energy value. Based on this, a model for maximizing the benefits of flexible resource operation is proposed. Through the combination of non-cooperative and cooperative games, the conflict and synergy mechanisms of multiple stakeholders are quantified, and the Shapley value allocation rule is designed to achieve Pareto optimality. Simultaneously, considering the spatiotemporal regulation capability of flexible resources, dynamic weight adjustment, cross-period environmental rights reserve, and risk diversification strategies are proposed. Simulation results show that under the scenario of a carbon price of 50 CNY/ton (≈7.25 USD/ton) and a peak–valley electricity price difference of 0.9 CNY/kWh (≈0.13 USD/kWh), when the environmental weight coefficient α = 0.5, the total revenue reaches 6.857 × 10⁷ CNY (≈9.94 × 10⁶ USD), with environmental benefits accounting for 90%, a 15.3% reduction in carbon emission intensity, and a 1.74-fold increase in energy storage cycle utilization rate. This research provides theoretical support for green power market mechanism design and resource optimization scheduling under “dual-carbon” goals. Full article

Nitrous oxide (N₂O) is a potent greenhouse gas, with emissions occurring mostly from agricultural soils, especially acidic soils. This research aimed to elucidate the response of soils dominated by nitrification-driven N₂O production to alkaline amendments, given that nitrification is a key process in N₂O emission. This study investigated the impact of an alkaline mineral amendment (CSMP) on N₂O emission, nitrification rate, and functional gene abundance. Using a robotic automated incubation system, CSMP both alone and in combination with urea was applied to two acidic soils (CL: pH 5.81; WS: pH 4.91). The results demonstrated that, relative to the CK, the CSMP-only treatment significantly increased N₂O emissions by 18.4-fold in these acidic soils, with a 61.6-fold increase in the U + CSMP treatment. This very large increase was driven by a rise in AOB-amoA abundance and a concurrent decline in AOA-amoA, which was confirmed by structural equation modeling, which showed that the increase in pH strongly influenced N₂O emission primarily through AOB-amoA. Although CSMP is effective for reversing soil acidification, its use must be carefully managed to prevent stimulation of N₂O emissions. Future strategies should explore combining CSMP with approaches that can mitigate nitrification while maintaining its soil improvement benefits. This study provides critical insights for developing balanced management practices that address both soil health and climate change mitigation in acidic agricultural systems. Full article

The soft-reset process, or a sequence of charge emissions from a floating storage node through a transistor biased in a subthreshold bias condition, is modeled by a master (Kolmogorov–Bateman) equation. The Coulomb interaction energy after each one-charge emission leads to a stepwise potential increase, giving correlated emission rates represented by Boltzmann factors. The governing probability distribution function is a hypoexponential type, and its cumulants describe characteristics of the single-charge Coulomb interaction at room temperature on a mesoscopic scale. The cumulants are further extended into a complex domain. Starting from three fundamental assumptions, i.e., the generation of non-degenerated states due to single-charge Coulomb energy, the Markovian property of each emission event, and the independence of each state, a moment function is identified as a product of mutually prime elements (algebraically termed as prime ideals) comprising the eigenvalues or the lifetimes of the emission states. Then, the algebraic structure of the moment function is found to be highly analogous to that of an integer uniquely factored into prime numbers. Treating the lifetimes as analogs of the prime numbers, two types of zeta functions are constructed. Standard analyses of the zeta functions analogous to the prime number problem or the Riemann Hypothesis are performed. For the zeta functions, the analyticity and poles are specified, and the functional equations are derived. Also, the zeta functions are found to be equivalent to the analytic extension of the cumulants. Finally, between the number of emitted charges and the lifetime, a logarithmic relation analogous to the prime number theorem is derived. Full article

Background and Objectives: Breast cancer is a leading cause of cancer-related mortality, particularly in aggressive subtypes such as HER2-positive and triple-negative breast cancer (TNBC). Achieving a pathological complete response (pCR) after neoadjuvant therapy is strongly associated with improved survival outcomes in these subgroups, making the prediction of pCR a clinical priority. Sarcopenia, a progressive loss of skeletal muscle mass and strength, is increasingly recognized in cancer patients and has been linked to chemotherapy toxicity and poorer survival. However, its specific impact on pCR in HER2-positive and TNBC patients remains unclear. This study aimed to evaluate the association between radiologically defined sarcopenia, or a low skeletal muscle index (SMI), and pathological response in these subtypes, and to explore its potential as a predictive biomarker. Materials and Methods: This retrospective study included patients with HER2-positive or TNBC who received neoadjuvant therapy between January 2015 and October 2023. SMI was assessed using pre-treatment positron emission tomography images at the L3 vertebral level, with values < 38.5 cm²/m² considered as low. Univariate and multivariate logistic regression analyses were performed to identify factors associated with pCR. Results: A total of 85 patients were included, with low SMI present in 35 (41.2%). In univariate analysis, clinical stage and low SMI were associated with pCR. However, in the multivariate model, only low SMI remained an independent predictor. Patients without low SMI had higher odds of achieving pCR (odds ratio [OR] 4.13; 95% confidence interval [CI] 1.55–10.95; p = 0.004). Low SMI was also associated with higher rates of treatment-related toxicity (42.9% vs. 20.0%, p = 0.023). Conclusions: Pre-treatment low SMI is strongly associated with lower pCR rates in patients with HER2-positive and TNBC undergoing neoadjuvant therapy. These findings underscore the importance of early identification and management of radiologically defined sarcopenia to optimize treatment response and improve clinical outcomes. Full article

Against the backdrop of increasingly severe global carbon emissions and China’s commitment to achieving carbon peaking by 2030, accelerating the transition to a low-carbon economy has become an urgent priority. As fundamental microeconomic entities, enterprises play a crucial role in the national governance of carbon emissions. This study uses panel data on Chinese A share listed companies from 2019 to 2023 and employs fixed effects models that control for firm, year, and industry effect to analyze how ESG performance influences carbon emissions and through which mechanism. The findings indicate that improvements in ESG ratings significantly reduce firms’ carbon emissions. This effect operates primarily through the following two channels: (1) promoting green technological innovation, thereby enhancing environmental performance, and (2) increasing the attention of financial analysts, which strengthens external monitoring. The heterogeneity analysis further reveals that the mitigating effect of ESG improvement on carbon emissions is more pronounced in firms with a lower proportion of institutional ownership, while this effect is relatively weaker in firms with higher institutional ownership. This suggests that in contexts where institutional investors hold a smaller share, firms may place greater emphasis on the policy pressure and social responsibility expectations associated with ESG performance, thereby exhibiting stronger commitment to emission reduction actions. In contrast, in firms dominated by institutional investors, the implementation of ESG policy objectives may be partially compromised due to the investors’ short-term profit orientation. This study provides empirical evidence for firms to fulfill their environmental and social responsibilities and offers actionable insights for investors aiming to promote sustainable development. From a policy perspective, the findings also offer theoretical support for developing differentiated regulatory strategies based on variations in ownership and shareholding structures. Full article

Land use change significantly affects regional carbon emissions and ecosystem service value (ESV). Under China’s Dual Carbon Goals, this study takes Beijing-Tianjin-Hebei, experiencing rapid land use change, as the study area and counties as the study unit. This study employs a combination of methods, including carbon emission coefficients, equivalent-factor methods, bivariate spatial autocorrelation, and a multinomial logit model. These were used to explore the spatial relationship between land use carbon emissions and ESV, and to identify their key driving factors. These insights are essential for promoting sustainable regional development. Results indicate the following: (1) Total land use carbon emissions increased from 2000 to 2015, then declined until 2020; emissions were high in municipal centers; carbon sinks were in northwestern ecological zones. Construction land was the primary contributor. (2) ESV declined from 2000 to 2010 but increased from 2010 to 2020, driven by forest land and water bodies. High-ESV clusters appeared in northwestern and eastern coastal zones. (3) A significant negative spatial correlation was found between carbon emissions and ESV, with dominant Low-High clustering in the north and Low-Low clustering in central and southern regions. Over time, clustering dispersed, suggesting improved spatial balance. (4) Population density and cultivated land reclamation rate were core drivers of carbon–ESV clustering patterns, while average precipitation, average temperature, NDVI, and per capita GDP showed varied effects. To promote low-carbon and ecological development, this study puts forward several policy recommendations. These include implementing differentiated land use governance and enhancing regional compensation mechanisms. In addition, optimizing demographic and industrial structures is essential to reduce emissions and improve ESV across the study area. Full article