Search Results (2,192)

Artificial intelligence (AI) technology has become the core force driving industrial transformation in today’s world. In-depth exploration of the spillover effects between artificial intelligence and new energy, as well as high-carbon-emission industries is of great significance for optimizing the industrial structure, preventing systemic risks in the industrial system, and achieving high-quality development. Based on the DY and BK spillover index model under the TVP-VAR framework, this paper analyzes the spillover effects between artificial intelligence and new energy, as well as high-carbon-emission industries from a time–frequency perspective, and constructs a spillover network to analyze the risk spillover transmission path. Finally, it explores the optimal investment portfolio weights and investment hedging strategies in the financial market. The results show that there is a significant static spillover effect between artificial intelligence and new energy, as well as high-carbon-emission industries. The intensity of this effect follows the pattern of “short-term > medium-term > long-term”. Moreover, new energy and some high-carbon-emission industries (such as the non-ferrous metals industry, the petrochemical industry, and the chemical industry) are the net spillover sources, while artificial intelligence and some high-carbon-emission industries (such as the power industry, the building materials industry, and the aerospace industry) are the net receiving parties. The dynamic spillover effect exhibits significant time-varying characteristics, being significantly impacted by major events such as environmental protection policies, the COVID-19 pandemic, and technological innovations. The chemical industry is the largest spillover outputter in all frequency domains, while the building materials industry is the largest receiver. From the perspective of the spillover network, the artificial intelligence industry, as a key node of the spillover network, plays a crucial role in the transmission of risk spillover. From the perspective of investment practice, the minimum connectedness portfolio (MCoP) performs well in terms of risk hedging effectiveness and return performance and may be the best choice for investors to balance risk and return. Full article

Microalgal lipid extraction, particularly the subsequent solvent recovery phase, constitutes the primary energy bottleneck in algal-based biodiesel biorefineries. Recently, switchable polarity solvents (SPS), such as the tertiary amine N,N-dimethylcyclohexylamine (DMCHA), have emerged as promising ‘green’ alternatives capable of extracting lipids directly from wet biomass, theoretically bypassing energy-intensive drying and solvent recovery distillation stages. This study presents a rigorous techno-energetic and thermodynamic evaluation combined with supporting experiments for qualitative conclusions to scrutinize the actual viability of DMCHA-mediated extraction against conventional hexane benchmarks, across three process configurations using different biomass types: algal liquor, wet paste, and dried biomass. Contrary to widespread assumptions in the literature, fundamental thermodynamic calculations reveal that the energy required for amine regeneration via protonation/deprotonation mechanisms equals or exceeds that of conventional distillation. Furthermore, mitigating biomass drying inadvertently escalates overall downstream energy and economic penalties due to the excessive solvent volumes demanded by dilute aqueous matrices. Direct extraction from algal liquor displays a cost and energy consumption countably higher than the other scenario; precisely, a cost of 232 €/kg of lipids and energy consumption of 454 kWh/kg of lipids. Extraction from wet paste exhibits, indeed, a slightly lower energy consumption compared to the hexane process (respectively 51 kWh/h versus 72 kWh/kg), but, due to the CO₂ requirements, the cost is double (19 €/kg of lipids versus 8 €/kg of lipids). Ultimately, while switchable polarity chemistry offers a marginal reduction in process water footprints, it introduces substantial operational complexity, elevated carbon dioxide payloads, and severe solvent degradation risks, challenging its current readiness for industrial upscaling. Full article

Although the digital economy (DE) and sustainable urban systems have drawn growing attention, how DE drives urban energy transition (UET) remains insufficiently understood. Employing panel data from 266 Chinese cities spanning 2011–2021, this study applies fixed-effects, mediation, moderation, and spatial Durbin models to examine the impact of DE on UET. UET is measured by a composite index that captures energy system performance and transition readiness. The results show that DE is positively associated with UET, with a one-unit increase in DE corresponding to a 0.1566-unit increase in UET. This finding remains robust after employing an instrumental-variable approach and a battery of robustness checks, including an exogenous policy shock. This positive effect is partially mediated by reduced resource misallocation and industrial structure upgrading. When electricity intensity is treated as a moderating factor, cities with higher electricity intensity exhibit a more pronounced positive effect of DE on UET. Further evidence indicates that DE advances UET in the eastern, central, and western regions, but has a limited impact in the northeastern region. Additionally, DE exerts positive spillover effects, thereby advancing energy transition in neighboring cities. Full article

The production of building ceramics is an energy-intensive part of the industry, causing high CO₂ emission per production volume. In addition to the combustion of fossil fuels, CO₂ is emitted as a byproduct of calcium carbonate decomposition, a compound present in clay raw materials. In this paper, a method for reducing emissions by lowering the firing temperature of ceramics, thereby preventing the complete decarbonation of carbonate minerals, is presented. Thermal research has shown that lowering the firing temperature to 750 °C resulted in a 55% calcium carbonate decomposition and a reduction in CO₂ emissions by over 30 kg for every ton of clay used. At this temperature, sintering shrinkage mechanisms were not observed, which resulted in a reduction in the strength of the materials by almost 25% compared to samples fired at 900 °C. An attempt was made to compensate for the negative effects of lowering the firing temperature by adding ground glass cullet, which brought only partially positive results: an increase in flexural strength, but no change in compressive strength. Microscopic observations and phase composition studies indicate that lowering the firing temperature causes changes in the proportions of calcium compounds: increased amounts of calcite, and decreased amounts of silicates and calcium aluminosilicates. Full article

Reducing emissions is increasingly critical for mitigating the environmental impact of the iron and steel industry. Achieving this transition requires an accurate evaluation of carbon emission intensity for steel production, which relies on an in-depth analysis of carbon metabolism mechanisms across the entire steel production chain. Existing approaches predominantly focus on carbon tracing within material flows, which cannot deeply integrate carbon migration pathways with energy flows and thus fail to reveal the actual sources and transmission mechanisms of carbon emissions. To address this gap, this study develops a carbon metabolism simulation model of the steel manufacturing process that considers the coupling of material production with the energy network. The differentiated carbon metabolism patterns are characterized in terms of carbon fixation, migration, and dissipation to support more accurate carbon emission accounting and enable the formulation of targeted decarbonization strategies. The results show that the coking process fixes 72.51% of its carbon input. The sintering and pelletizing process shows typical carbon dissipation characteristics, with nearly 100% of input carbon discharged. Carbon emissions from steelmaking and the rolling process are mainly induced by indirect energy consumption. The total carbon dissipation of integrated steel production system is 440.62 kg-C/t-CS, with the ironmaking process contributing the largest share of 33.92%. Full article

Deep decarbonization of high-temperature industrial furnaces and kilns is essential for reducing greenhouse gas emissions in energy-intensive sectors. Hydrogen and hydrogen-enriched fuels are promising alternatives to conventional fossil fuels; however, their integration is not a straightforward fuel replacement. Owing to hydrogen’s high laminar burning velocity, wide flammability limits, low volumetric heating value, and water-vapor-rich combustion products, hydrogen substitution can substantially alter flame stability, heat transfer pathways, pollutant formation, and material service behavior. This review systematically summarizes the key technologies and application progress of hydrogen-based fuel substitution in high-temperature industrial systems. First, the thermophysical and kinetic differences between hydrogen and hydrocarbon fuels are analyzed. Subsequently, core enabling technologies are discussed, including flashback prevention, low-NOx combustion control, thermal-flow-field regulation, heat transfer optimization, and material compatibility under high-temperature, water-vapor-rich atmospheres. Application progress in representative scenarios—including metallurgy, heat treatment, petrochemical-fired heaters, waste treatment, rotary kilns, and cremation furnaces—is reviewed to identify scenario-specific constraints. The review indicates that successful hydrogen substitution requires a transition from isolated burner optimization toward system-level integration of combustion control, heat transfer management, emission mitigation, and material adaptation. Future research should prioritize integrated furnace design, long-term material service assessment, multi-fuel operating strategies, and data-driven control frameworks. Full article

Coal-dominated resource-based cities face a structurally embedded carbon-neutrality gap, shaped by the simultaneous pressures of industrial carbon lock-in and ecological fragility. China’s dual-carbon targets impose severe transition pressure on such regions, where carbon-intensive industries, strong path dependence, and limited decarbonization flexibility compound the challenge. Forest carbon sinks offer a cost-effective approach for offsetting residual emissions. However, water scarcity and restricted land-carrying capacity impose hard ecological ceilings on sink expansion in semi-arid areas such as the Loess Plateau. Existing studies have largely focused on national or provincial scales, with few addressing the coupled dynamics of industrial emissions and water-limited sink capacity at the county level. This study examines Shenmu, China’s largest coal-producing county-level city and a national energy-chemical industrial base. Using time-series data spanning 2010–2025, we project multi-scenario carbon emissions via an extended STIRPAT model with ridge regression, estimate forest carbon sink potential through a growing-stock (GS) gradient model cross-validated against GM(1,1), and systematically quantify the resulting carbon-neutrality gap. The results show that energy activities dominate total emissions throughout, consistently exceeding 90% of the aggregate. Under the baseline scenario, emissions reach 407.96 MtCO₂eq in 2060 without peaking; under moderate mitigation, emissions peak at 269.39 MtCO₂eq in 2050; under strengthened mitigation, emissions peak at 225.80 MtCO₂eq before 2040 and subsequently decline. Forest carbon sinks are projected to offset 2.1–11.2% of emissions by 2060 under all scenarios, constrained by climatic aridity, finite afforestation potential, and water–soil carrying capacity thresholds. The carbon-neutrality gap remains structurally positive across every scenario, reflecting a fundamental asymmetry between rigid emission growth and ecologically bounded sink capacity. These findings indicate that only an integrated pathway combining industrial restructuring, energy decarbonization, diversified ecological sinks, and CCUS deployment can substantially narrow the gap; carbon neutrality by 2060 is unattainable through natural sinks alone. Full article

Marine biowaste (fish and crustacean processing residues) is produced in tens of millions of tons annually, yet remains dramatically underutilized as a feedstock. Hydrothermal carbonization offers a technically attractive valorization route for these high-moisture, non-lignocellulosic materials, converting them to carbon-enriched hydrochar without the energy-intensive pre-drying required by pyrolysis. This focused review treats marine animal waste as the primary studies and micro- and macroalgal hydrothermal carbonization as a comparative benchmark to understand how the current research is going, the impact of production parameters, potential application, and possible research gaps to explore. Crustacean waste yields substantially more hydrochar (37–69%) than fish waste (15–34%) under equivalent conditions, driven by calcium carbonate retention in the solid phase. Unactivated hydrochars have low BET surface areas (<30 m²/g) and modest adsorption capacities (~10 mg/g). Acid deashing followed by KOH activation at 700 °C unlocks nanoporous structures with BET surface areas up to 680 m²/g and oxytetracycline adsorption capacities of 61.3 mg/g. Critical research gaps include the absence of techno-economic analysis, limited life-cycle assessment, and non-standardized reporting conventions. These must be addressed before upscaling to industrial viability can be achieved. Full article

Considering the implementation of the circular economy and the concept of sustainable development, there is a growing need to reduce resource consumption and the environmental impact of industrial processes. This is particularly important in the sugar industry, which is characterized by high energy intensity and a complex process structure. The aim of this paper is to conduct a narrative review of the latest research from 2021–2026 on the assessment of technological processes in the sugar industry from an energy and environmental perspective. The analysis includes approaches such as life-cycle assessment, carbon footprint analysis, energy indicators, and methods related to the circular economy. The results of the review indicate that existing research focuses primarily on selected process aspects, such as greenhouse gas emissions, energy consumption, or by-product management. However, approaches integrating environmental, energy, cost, and process analysis are lacking. This paper identifies a significant research gap and proposes a direction for filling it by integrating dynamic life-cycle assessment, exergy analysis, material flow and energy costing (MFCA), and process–energy modeling. This approach provides a comprehensive framework for process evaluation and supports the identification of improvement strategies that minimize energy consumption, environmental burdens, and production costs while preserving process efficiency. Full article

This study provides a comprehensive characterization of carbon dust adhesion on the anode surface induced by the anode effect (AE) in the Hall–Héroult process. The primary objective was to verify the hypothesis of electrophoretic carbon particle transport and its subsequent stabilization on the electrode substrate. Unlike previous studies conducted in horizontal configurations where gravitational sedimentation could interfere with observations, this research employs a unique vertical electrode setup to provide direct physical evidence of purely electrophoretic transport. Authentic industrial carbon dust was used as a tracer material, its presence on the high-purity graphite surface being definitively confirmed through the detection of trace markers (Mg, Ca) via SEM-EDS. The multiscale structural analysis revealed that spike initiation occurs through a dynamic arc-induced nucleation mechanism. Morphological observations suggest that micro-arc discharges during the AE provide the extreme localized energy for direct carbon-to-carbon “welding,” creating a conductive, porous scaffold on the vertical anode wall. XRD analysis identified crystalline cryolite (Na₃AlF₆) and chiolite (Na₅Al₃F₁₄) within this structure. It was demonstrated that these fluoride phases represent the solidified product of molten, acidic electrolyte infiltration into the carbonaceous matrix via capillary action, rather than acting as binders that crystallize during the process. Raman spectroscopy confirmed the disordered, amorphous nature of the captured dust (high D-band intensity), distinguishing it from the highly ordered graphite substrate. Confocal microscopy visualized the topographical evolution from isolated clusters to interconnected three-dimensional “islands” as a function of AE duration. The results demonstrate that the anode effect serves as a critical flashpoint where synergistic electrophoretic forces and localized thermal anomalies initiate the growth of stable, conductive carbon–matrix composite spikes, providing new insights for mitigating current efficiency losses in industrial smelters. Full article

Energy-intensive firms are key participants in China’s carbon emissions trading system (CETS). However, evidence on whether CETS promotes the green transformation (GT) of these firms remains limited. In this study, a multi-period difference-in-differences (DID) model is applied to investigate the impacts of CETS on the GT of 529 listed firms from six energy-intensive industries over the period 2007–2024. Results show that CETS significantly promotes GT, and the findings remain robust after parallel trend, placebo, propensity score matching (PSM)-DID, Goodman-Bacon decomposition, and alternative variable tests. Further analysis reveals that internal control and green technological innovation (Ginn) positively moderate the effects of CETS on the GT of energy-intensive firms. Heterogeneity analysis reveals that the promoting effect is more pronounced in highly competitive industries and among firms with stronger green reputations. These findings provide empirical evidence on the effectiveness of CETS in facilitating the GT of energy-intensive firms. Full article

Devoting attention to the mechanisms of enhancing energy efficiency through the transition to clean energy sources plays a vital and active role in moving forward towards environmental sustainability in the industrial economy. Industrial CO₂ emissions across the Gulf Cooperation Council (GCC) remain persistently high despite growing regional commitments to clean energy transition and sustainability. This study examines the key determinants of industrial CO₂ emissions in all six GCC member states over the period 2004–2022, focusing on energy efficiency, electricity consumption, oil use, trade openness, and economic growth. The analysis employs advanced panel econometric techniques, including cross-sectional dependence tests, second-generation unit root tests, and panel autoregressive distributed lag estimators, to identify both short-run and long-run relationships among the variables. The results reveal that in the short run, energy intensity is the sole statistically significant driver of industrial emissions. In the long run, energy intensity continues to increase emissions, while trade openness significantly reduces them. Neither oil consumption nor industrial electricity use exerts a significant positive long-run effect on emissions, pointing to a gradual decoupling driven by improving industrial energy efficiency and cleaner electricity generation. These findings suggest an emerging decoupling between industrial activity and carbon emissions in the GCC, driven by improvements in energy efficiency. For GCC economies pursuing economic diversification and net-zero targets, reducing industrial energy intensity and expanding low-carbon energy sources remain critical pathways toward sustainable industrial development. Full article

This study examines how the strategic integration of digital transformation and national innovation capacity contributes to accelerating sustainable development in Saudi Arabia by focusing on six Sustainable Development Goals (SDGs): SDG 4—Quality Education, SDG 7—Affordable and Clean Energy, SDG 8—Decent Work and Economic Growth, SDG 9—Industry, Innovation and Infrastructure, SDG 12—Responsible Consumption and Production, and SDG 13—Climate Action. Using annual data on ICT use, ICT access, R&D expenditure, and patent applications, the analysis evaluates both the direct and joint relationships between these indicators and SDG performance. Digital transformation is captured through ICT use and ICT access, while national innovation capacity is represented by R&D expenditure and patent applications, reflecting the input and output dimensions of formal innovation activity. The findings indicate that the direct long-run effects of digital transformation and national innovation capacity on the six SDGs are not statistically significant, suggesting that these domains have not yet become standalone drivers of educational advancement, clean-energy adoption, economic performance, industrial upgrading, sustainable resource management, or emissions reduction. In contrast, their interaction produces substantial positive effects on SDG 4, SDG 7, SDG 8, and SDG 9, highlighting improvements in educational quality, renewable energy transition, productivity, and industrial innovation. The interaction also has significant negative effects on SDG 12 and SDG 13, as reflected by reductions in CO₂ intensity and environmental pressures. These results indicate that meaningful progress toward the SDGs emerges when digital capabilities and national innovation capacity evolve jointly, rather than through isolated improvements in ICT infrastructure or innovation inputs. Robustness checks using a composite SDG index confirm the stability of these complementary effects. These findings suggest that Saudi Arabia can accelerate progress toward the SDGs by adopting integrated policies that link ICT expansion with stronger R&D systems, patent commercialization, technological innovation, and sustainability-oriented industrial transformation across education, energy, industry, resource efficiency, and climate action. Full article

This study examines how energy-security shocks shape macroeconomic resilience in import-dependent economies and which energy-management strategies remain robust under alternative shock conditions. Using a balanced panel of 18 mainly European energy-importing economies and Türkiye for 2000–2024, the study constructs a Macroeconomic Resilience Index (MRI) from five dimensions: GDP growth, inflation, unemployment, current account balance, and industrial production growth. Inflation and unemployment are treated as inverse resilience indicators, and a Principal Component Analysis (PCA)-based alternative index is used as a robustness check. Methodologically, the study develops a hybrid framework that first applies a Shock-Augmented Cross-Sectionally Dependent Panel Quantile ARDL model to estimate heterogeneous shock effects across resilience levels, and then translates the econometric evidence into a Shock-Conditioned Bayesian Network–Regret MCDM model for strategy prioritization. The findings show that exchange-rate pressure is the most consistent long-run vulnerability channel, while energy intensity weakens resilience across short-run, benchmark, and quantile robustness results. The renewable energy share supports resilience under some conditions, but its effect depends on complementary investments in storage, grid flexibility, and demand-side capacity. Scenario results indicate that exchange-rate pressure produces the weakest resilience profile. The positive MRI value observed during combined-crisis years should be interpreted cautiously, as additional sensitivity evidence indicates that it mainly reflects the 2021–2022 post-pandemic rebound rather than a beneficial effect of shocks. Bayesian Network results identify macro-financial stabilization, import-dependency reduction, energy efficiency, and grid reliability as key resilience drivers. The regret-based MCDM results rank energy efficiency improvement as the most robust strategy, followed by energy import diversification. The study contributes by linking dynamic macroeconometric shock analysis with probabilistic scenario modeling and regret-sensitive decision support, offering an evidence-informed framework for prioritizing energy-security strategies in the sampled import-dependent economies. Full article

The textile industry causes significant environmental problems because of its intensive use of water, energy, and chemicals. The stenter machines, which are commonly used in textile finishing processes, release air pollutants such as odor, volatile organic compounds (VOCs), and total organic carbon (TOC) into the atmosphere during drying and fixing processes carried out at high temperatures. The aim of this study was to investigate odor, VOC, and TOC emissions from the stacks of the stenter machines. In this study, odor, VOC, and TOC parameters were examined in samples from the stacks of stenter machines of nine different plants operating in the textile sector in Bursa, Turkey. The samples were analysed in accordance with EN 13725:2022 standard, EN 13649:2014 standard, and EN 12619:2013 standard for odor, VOC, and TOC parameters, respectively. Acetone, carbon tetrachloride, dibromochloromethane, ethylbenzene, tetrachlorethylene, toluene, and p + m-Xylene were the most common components. The TOC concentrations were determined in the range of 13.89–279.23 mg/Nm³. The odor concentrations were determined in the range of 4113–26,627 OU/m³. Full article