Search Results (2,857)

The development of the digital economy has become a significant driving force for the innovation of green technology in the manufacturing sectors. Green technology innovation in the manufacturing sectors is not only a key engine for realizing economic green transformation and achieving the goal of achieving peak carbon emissions by 2030 and carbon neutrality by 2060, but also an important path for cultivating new quality productivity. Based on Schumpeter’s endogenous growth theory, in this study, we constructed an analytical model with a unified framework of digital economic development and environmental regulation, systematically explored the mechanism of digital economic development with respect to green technological innovation in the manufacturing sectors and the moderating effect of environmental regulation, and carried out empirical research based on panel data at the provincial level and the level of the subdivided manufacturing sectors in China. We found that the development of the digital economy promotes green technology innovation in the manufacturing industry. However, according to the theory of increasing marginal information costs, it shows a significant nonlinear relationship. Absorptive capacity is the key means of support that manufacturing enterprises can leverage to improve their level of green technological innovation. Environmental regulation plays a crucial role in guiding green technological innovation in the manufacturing sectors. A further heterogeneity analysis showed that the development of the digital economy exerts a stronger positive impact on green technological innovation in cleaner-production-oriented manufacturing sectors and those located in regions with more advanced financial regions and in technology-intensive industries. This study provides theoretical support for understanding the driving mechanisms of green technological innovation in the manufacturing sector against the backdrop of the digital economy, offering practical implications for optimizing environmental regulation policies and enhancing the level of green development in manufacturing. Full article

Through the Study on the Development of a Sustainable Public Transport System and a Non-Motorized Mobility System, in October 2022, the City of Ludbreg and the local municipalities of Martijanec, Sveti Đurđ, Veliki Bukovec, and Mali Bukovec jointly agreed to develop a sustainable transport system focused on passenger mobility. This agreement included co-financing the Study, which supports local development and promotes the efficient use of EU funds allocated for the 2021–2027 period. The Study emphasizes the integration of public transport, walking, and cycling, alongside the sustainable use of private vehicles, in alignment with European and national strategic frameworks aimed at reducing CO₂ emissions and improving quality of life. However, the City of Ludbreg aims to further enhance the municipal public transport system, not only within the city but also across the entire Northern Croatia region. As a first step, in addition to optimizing the existing public transport service and defining an optimal bus route network, the goal is to establish a modern public transport system that is more attractive to users, offers greater comfort, ensures higher accessibility, and minimizes negative environmental impacts. By improving service quality, the system is expected to attract more users and create new mobility opportunities, contributing to demographic revitalization, employment growth, environmental protection, energy efficiency, lower transport costs, an improved standard of living, and broader economic development in Ludbreg and the surrounding region. Full article

Ensuring food quality and safety is a growing challenge in the food industry, where early detection of contamination or spoilage is crucial. Using gas sensors combined with Artificial Intelligence (AI) offers an innovative and effective approach to food identification, improving quality control and minimizing health risks. This study aims to evaluate food identification strategies using supervised learning techniques applied to data collected by the BME Development Kit, equipped with the BME688 sensor. The dataset includes measurements of temperature, pressure, humidity, and, particularly, gas composition, ensuring a comprehensive analysis of food characteristics. The methodology explores two strategies: a neural network model trained using Bosch BME AI-Studio software, and a more flexible, customizable approach that applies multiple predictive algorithms, including DT, LR, kNN, NB, and SVM. The experiments were conducted to analyze the effectiveness of both approaches in classifying different food samples based on gas emissions and environmental conditions. The results demonstrate that combining electronic noses (E-Noses) with machine learning (ML) provides high accuracy in food identification. While the neural network model from Bosch follows a structured and optimized learning approach, the second methodology enables a more adaptable exploration of various algorithms, offering greater interpretability and customization. Both approaches yielded high predictive performance, with strong classification accuracy across multiple food samples. However, performance variations depend on the characteristics of the dataset and the algorithm selection. A critical analysis suggests that optimizing sensor calibration, feature selection, and consideration of environmental parameters can further enhance accuracy. This study confirms the relevance of AI-driven gas analysis as a promising tool for food quality assessment. Full article

Infrastructure construction is a major contributor to carbon emissions, primarily due to the extensive use of mineral materials such as cement and aggregates, which release significant amounts of carbon dioxide during production and use. While existing research has predominantly centered on the applications of concrete, the present study extends the investigation to encompass inorganic–organic composites, alloy materials, and wastewater treatment systems, with particular attention to bridging the gap between theoretical potential and practical implementation. This study identifies China, the USA, and India as leaders in this field, attributing their progress to abundant material resources and sustained policy support. Key findings reveal that while geopolymers can fully replace cement, substitution rates of less than 50% are optimal for high-performance concrete to maintain structural integrity and decarbonization benefits. Aggregate replacements using materials such as air-cooled blast furnace slag show 50–100% feasibility. This review further highlights the multifunctional potential of red mud, rice husk ash, fly ash, and blast furnace slag as cement replacements, aggregates, reinforcers, catalysts, adsorbents, and composite fillers. However, challenges such as unstable raw material supply, lack of standardization, and insufficient international collaboration persist; these issues have often been overlooked in prior research and viable solutions have not been proposed. To address these barriers, a triple-objective framework is introduced in this study, integrating sustainable infrastructure, resource recycling, and environmental remediation, supported by optimized production processes and policy models from leading nations. Future research directions emphasize comprehensive life cycle assessments and enhanced global cooperation to bridge the divide between resource-rich and resource-scarce regions. By synthesizing cross-disciplinary applications and actionable solutions, this work advances the transition toward sustainable infrastructure systems. Full article

Economic dispatch using wind power plants plays a role in reducing the price of electricity production by dispatching power among different generating units for thermal and wind power plants, and supplying load demand while meeting the power system equality and inequality constraints. Adding wind power plants to the economic dispatch model can significantly reduce electricity production costs and reduce carbon dioxide emissions. In this paper, fuel cost and emission minimization are considered as the objective function of the economic dispatch problem, taking into account transmission loss using the B matrix. The quadratic model of the fuel cost and emission criterion functions is modeled without considering a valve-point loading effect. The real power generation limits for both wind and conventional generating units are considered. In addition, a closed-form expression based on the incomplete gamma function is provided to define the impact of wind power, which includes the cost of wind energy, including overestimation and underestimation of available wind power using a Weibull-based probability density function. In this research work, Lagrange’s algorithm is proposed to solve the Wind–Thermal Economic Emission Dispatch (WTEED) problem. The developed Lagrange classical optimization algorithm for the WTEED problem is validated using the IEEE test systems with 6-, 10-, and 40-generation unit systems. The proposed Lagrange optimization method for WTEED problem solutions demonstrates a notable improvement in both economic and environmental performance compared to other heuristic optimization methods reported in the literature. Specifically, the fuel cost was reduced by an average of 4.27% in the IEEE 6-unit system, indicating more economical power dispatch. Additionally, the emission cost was lowered by an average 22% in the IEEE 40-unit system, reflecting better environmental compliance and sustainability. These results highlight the effectiveness of the proposed approach in achieving a balanced trade-off between cost minimization and emission reduction, outperforming several existing heuristic techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) under similar test conditions. The research findings report that the proposed Lagrange classical method is efficient and accurate for the convex wind–thermal economic emission dispatch problem. Full article

Environmental protection tax (EPT), as a major tool to improve air quality and reduce carbon emissions, is of great significance for promoting urban low-carbon transformation. In this context, this paper has compiled a dataset from 282 Chinese cities during 2006–2022 and empirically identify the implication of EPT for carbon emissions at the city level by using the intensity difference-in-differences (I-DID) model. The result discloses that EPT greatly lowers carbon emissions by an average of 10.9% compared to non-pilot cities. Even after conducting some robustness checks, the result remains unchanged. Mechanism testing reveals that EPT curbs carbon emissions through enhancing energy utilization efficiency, fostering green technological advancements, and modernizing urban industries. Meanwhile, we show that EPT exerts a more substantial effect on carbon emissions in innovative cities, central and western cities, non-industrial-based cities, and non-resource-dependent cities. More importantly, EPT greatly promotes imitation and learning in neighboring regions, forming a radiation impact upon carbon reduction in surrounding areas. Hence, these results offer an important decision-making guide for optimizing the EPT system, strengthening the coordinated governance of carbon emission across regions, and ultimately promoting urban low-carbon development. Full article

This study evaluates the environmental benefits of retrofitting conventional diesel-powered waterbuses in Venice with a series hybrid electric powertrain comprising three generator sets and dual electric propulsion motors. Using real-world operational profiles recorded during typical passenger service, a quasi-static simulation model was developed to assess energy and emission performance. Real-world speed and torque data were collected from a conventional waterbus during regular passenger service to accurately reflect real operational conditions, including driver behavior and the sea state. These profiles were used as inputs to a quasi-static simulation model to assess the hybrid system’s energy efficiency and emission performance. Dynamic programming was applied to derive emissions-optimal control strategies, targeting trade-offs between nitrogen oxides (NOx) and unburned hydrocarbons (HC). The results demonstrate emission reductions of up to 31% in NOx and 15% in HC, confirming the strong potential of hybridization for urban maritime transport. The paper also examines component-level behavior under optimal control and discusses practical considerations for implementing these strategies in real-time applications. These findings support the strategic value of hybrid retrofitting and fleet renewal for reducing the environmental footprint of passenger ferries and improving air quality in sensitive coastal urban environments. Full article

The exponential increase in global solid waste generation poses significant environmental, economic, and social challenges, particularly in rapidly urbanizing regions. Traditional waste management methods that focus on handling and disposal have proven unsustainable because of their negative impacts on air, soil, and water quality, and their contribution to greenhouse gas emissions. In response, the concept of zero-waste cities, rooted in circular economy principles, has gained increasing attention in recent years. This study proposes a comprehensive and integrated waste management system designed to optimize resource recovery across four distinct waste streams: household, healthcare, green/organic, and inert. The system integrates four specialized facilities: a Secondary Sorting Facility, Energy Recovery Facility, Composting Facility, and Inert Processing Facility, coordinated through a central Primary Sorting Hub. By enabling interconnectivity between these processing units, the system facilitates material cascading, maximizes the reuse and recycling of secondary raw materials, and supports energy recovery and circular nutrient flow. The anticipated benefits include enhanced operational efficiency, reduced environmental degradation, and generation of multiple revenue streams. However, the implementation of such a system faces challenges related to high capital investment, technological complexity, regulatory fragmentation, and low public acceptance. Overcoming these limitations will require strategic planning, stakeholder engagement, and adaptive governance. Full article

Carbon dots (CDs) derived from renewable biomass are emerging as sustainable alternatives to traditional nanomaterials for applications in bioimaging, sensing, and photonics. In this study, we reported a one-step synthesis of photoluminescent CDs from Laurus nobilis leaves particularly spread in the Mediterranean area. The resulting nanoparticles (NPs) exhibited average diameters of 3–5 nm and high colloidal stability in water. Structural analysis by X-Rays Diffraction revealed the presence of amorphous graphitic domains, while infrared spectroscopy confirmed oxygenated functional groups on the CD surface. Spectrofluorimetric analysis showed excitation-dependent blue–green emission with a maximum at 490 nm that can be applied also as label agents for cells. The environmental sustainability of the synthetic procedure was evaluated through a Life Cycle Assessment (LCA), highlighting that the current impacts were primarily associated with electricity consumption, due to the laboratory-scale nature of the process. These impacts are expected to decrease significantly with future scale-up and process optimization. Full article

This innovative study introduces an eco-conscious and cost-effective approach to synthesizing gelatin-based carbon dots (CDs) via two distinctive methods: hydrothermal processing in a muffle furnace (CDs-MF) and domestic microwave (CDs-MW). Both strategies harness natural, low-cost materials and prioritize simplicity, sustainability, and environmental friendliness, culminating in effective fluorescent sensing of the pesticide thiamethoxam (TMX). For the hydrothermal route, the investigation explores two purification approaches—ultracentrifugation (CDs-MF-C) and 0.22 µm syringe filtration (CDs-MF-F)—while the microwave-derived CDs (CDs-MW) undergo dialysis alone. This study aims to investigate how synthesis and purification impact the CDs structural, morphological, and photophysical characteristics. The difference in size was obtained from transmission electron microscopy (TEM): 30–40 nm for CDs-MF-C, 12–15 nm for CDs-MF-F, and 3–6 nm for CDs-MW. Fluorescence emission performance reveals that CDs-MF-F performs a fluorescence quantum yield of 27%, CDs-MF-C at 23%, and CDs-MW at a modest 3%. All variants exhibit TMX detection via fluorescence quenching through the inner filter effect (IFE). Analytically, CDs-MF-C stands out with the lowest detection limit (LOD = 0.396 ppm) and quantification limit (LOQ = 1.317 ppm), followed by CDs-MF-F (LOD = 0.475 ppm; LOQ = 1.585 ppm) and CDs-MW (LOD = 0.549 ppm; LOQ = 1.831 ppm). These findings emphasize the unique interplay between the synthesis pathway, purification strategy, and functional performance, demonstrating the critical importance of tuning structural properties for optimizing carbon-dot sensors. Full article

The transition of South Africa from coal-dependent energy systems to renewable energy alternatives presents economic and environmental trade-off complexities that require empirical investigation. This study employed threshold-switching dynamic models, NARDL analysis, and threshold Granger causality tests to investigate nonlinear relationships between renewable energy generation, economic growth, and carbon dioxide emissions in South Africa from 1980 to 2023. The threshold-switching dynamic models revealed critical structural breakpoints: a 56.4% renewable energy threshold for carbon dioxide emissions reduction, a 397.9% trade openness threshold for economic growth optimisation, and a 385.32% trade openness threshold for coal consumption transitions. The NARDL bounds test confirmed asymmetric effects in the carbon dioxide emissions and renewable energy relationship. The threshold Granger causality test established significant unidirectional causality from renewable energy to carbon dioxide emissions, economic growth to carbon dioxide emissions, and bidirectional causality between coal consumption and trade openness. However, renewable energy demonstrated no significant causal relationship with economic growth, contradicting traditional growth-led energy hypotheses. This study concluded that South Africa’s energy transition demonstrates distinct regime-dependent characteristics, with renewable energy deployment requiring critical mass thresholds to generate meaningful environmental benefits. The study recommended that optimal trade integration and renewable energy thresholds could fundamentally transform the economy’s carbon intensity while maintaining sustainable growth patterns. Full article

Background: Port congestion contributes significantly to operational inefficiency and environmental impact in maritime logistics. With tightening EU regulations such as the Emissions Trading System (EU ETS) and FuelEU Maritime, understanding and mitigating the economic and environmental effects of vessel delays is increasingly critical. This study focuses on a single bulk cargo pier at Constanta Port (Romania), which has experienced substantial traffic fluctuations since 2021, and examines operational and environmental performance through a queuing-theoretic lens. Methods: The authors have applied an M/G/1/∞/FIFO/∞ queuing model to vessel traffic and service time data from 2021–2023, supplemented by Monte Carlo simulations to capture variability in maneuvering and service durations. Environmental impact was quantified in CO₂ emissions using standard fuel-based emission factors, and a Cold Ironing scenario was modeled to assess potential mitigation benefits. Economic implications were estimated through operational cost modeling and conversion of CO₂ emissions into equivalent EU ETS carbon costs. Results: The analysis revealed high berth utilization rates across all years, with substantial variability in waiting times and queue lengths. Congestion was associated with considerable CO₂ emissions, which, when expressed in monetary terms under prevailing EU ETS prices, represent a significant financial burden. The Cold Ironing scenario demonstrated a substantial reduction in at-berth emissions and corresponding cost savings, underscoring its potential as a viable mitigation strategy. Conclusions: Results confirm that operational congestion at the studied berth imposes substantial environmental and financial burdens. The analysis supports targeted interventions such as Just-In-Time arrivals, optimized berth scheduling, and Cold Ironing adoption. Recommendations are most applicable to single-berth bulk cargo operations; future research should extend the approach to multi-berth configurations and incorporate additional operational constraints for broader generalizability. Full article

Recycled water is commonly considered an environmentally friendly alternative water source for urban water systems, which can not only serve as a solution for water scarcity, but also reduce wastewater discharge from sewage systems. However, owing to the high degree of energy consumption during recycled water production, the utilization of recycled water may be detrimental to greenhouse gas emission reduction. In this work, we conduct a detailed investigation into greenhouse gas emissions from different sources in a typical multisource urban water system in China. Furthermore, we develop an optimization model for water resource allocation based on the rime optimization algorithm and regret theory. The results show that although greenhouse gas emissions from recycled water exceed those from other sources, their impact can be eliminated through rational water resource allocation. Specifically, compared with the original water resource allocation, the optimal results effectively reduce pollutant emissions by 7.6~11.1% without excessively increasing water resource shortages and greenhouse gas emissions. Additionally, both subjective preferences and recycled water utilization conditions have significant impacts on the optimization results, which should be carefully selected according to practical situations and technologies. Overall, the methods developed in this study provide a new general framework for the water resource allocation of multisource urban water systems in the context of greenhouse gas emission reduction and recycled water utilization, which can be employed in other areas. Full article

Geopolymers represent an innovative and environmentally sustainable alternative to traditional construction materials, offering significant potential for reducing anthropogenic CO₂ emissions. Among these, phosphoric acid-activated metakaolin-based systems have attracted increasing attention for their chemical and thermal resilience. In this study, we present a comprehensive structural and mechanical evaluation of metakaolin-based geopolymers synthesized across a wide range of Al/P molar ratios (0.8–4.0). Six formulations were systematically prepared and analyzed using X-ray powder diffraction (XRPD), small-angle X-ray scattering (SAXS), Fourier-transform infrared spectroscopy (FTIR), solid-state nuclear magnetic resonance (ssNMR), and complementary mechanical testing. The novelty of this work lies in the integrated mapping of composition–structure–property relationships across the broad Al/P spectrum under controlled synthesis, combined with the rare application of SAXS to reveal composition-dependent nanoscale domains (~18–50 nm). We identify a stoichiometric window at Al/P ≈ 1.5, where complete acid consumption leads to a structurally homogeneous AlVI–O–P network, yielding the highest compressive strength. In contrast, acid-rich systems exhibit divergent flexural and compressive behaviors, with enhanced flexural strength linked to hydrated silica domains arising from metakaolin dealumination, quantitatively tracked by ²⁹Si MAS NMR. XRPD further reveals the formation of uncommon Si–P crystalline phases (SiP₂O₇, Si₅P₆O₂₅) under low-temperature curing in acid-rich compositions. Together, these findings provide new insights into the nanoscale structuring, phase evolution, and stoichiometric control of silica–alumino–phosphate geopolymers, highlighting strategies for optimizing their performance in demanding thermal and chemical environments. Full article

Technical losses (TLs) in power systems are an inevitable outcome of energy dissipation in components such as conductors, transformers, and transmission lines. These losses arise from the combined effects of material properties, operational conditions, and environmental factors, creating ongoing challenges for energy efficiency and grid sustainability. Their reduction requires a coordinated approach that integrates material improvements, smart grid technologies, and optimized operational practices. Reducing TLs not only improves economic efficiency but also contributes significantly to global sustainability efforts by enabling more efficient energy use and reducing carbon emissions associated with power generation. A review of recent publications shows that the literature on network losses is heavily skewed toward non-technical losses (NTLs), with TL-focused studies being fewer, often dated, and lacking comprehensive scope. This paper addresses the existing research gap by presenting a comprehensive, section-oriented taxonomy of TL mechanisms in power systems, accompanied by precise definitions for each category and a direct linkage between these categories and applicable loss mitigation measures. In addition, selected real-world projects and global initiatives aimed at reducing TLs, together with current regulatory approaches, emerging trends in this domain, and an assessment of the maturity level of technologies employed for TL reduction, are analyzed. This study aims to serve as a scientific reference to support future research and to guide policymakers, regulators, and utilities in developing more effective strategies for minimizing TLs. Full article