Search Results (979)

In response to the escalating climate crisis, reducing greenhouse gas emissions (GHG) has become a top priority for both the public and private sectors. The pavement industry plays a key role in this transition, offering innovative technologies that minimize environmental impacts without compromising performance. Among these, the incorporation of recycled tire rubber and warm-mix asphalt (WMA) additives represents a promising strategy to reduce energy consumption and resource depletion in road construction. This study conducts a comparative life cycle assessment (LCA) to evaluate the environmental performance of an asphalt pavement incorporating recycled rubber and a WMA additive—referred to as R-W asphalt—against a conventional hot-mix asphalt (HMA) pavement. The analysis follows the ISO 14040/44 standards, covering material production, transport, construction, and maintenance. Two service-life scenarios are considered: one assuming equivalent durability and another with a five-year extension for the R-W pavement. The results demonstrate environmental impact reductions of up to 57%, with average savings ranging from 32% to 52% across key impact categories such as climate change, land use, and resource use. These benefits are primarily attributed to lower production temperatures and extended maintenance intervals. The findings underscore the potential of R-W asphalt as a cleaner engineering solution aligned with circular economy principles and climate mitigation goals. Full article

The production of iron and steel plays a significant role in the anthropogenic carbon footprint, accounting for 7% of global GHG emissions. In the context of CO₂ mitigation, the steelmaking industry is looking to potentially replace traditional carbon-based ironmaking processes with hydrogen-based direct reduction of iron ore in shaft furnaces. Before industrialization, detailed modeling and parametric studies were needed to determine the proper operating parameters of this promising technology. The modeling approach selected here was to complement REDUCTOR, a detailed finite-volume model of the shaft furnace, which can simulate the gas and solid flows, heat transfers and reaction kinetics throughout the reactor, with an extension that describes the whole gas circuit of the direct reduction plant, including the top gas recycling set up and the fresh hydrogen production. Innovative strategies (such as the redirection of part of the bustle gas to a cooling inlet, the use of high nitrogen content in the gas, and the introduction of a hot solid burden) were investigated, and their effects on furnace operation (gas utilization degree and total energy consumption) were studied with a constant metallization target of 94%. It has also been demonstrated that complete metallization can be achieved at little expense. These strategies can improve the thermochemical state of the furnace and lead to different energy requirements. Full article

The intersection of green finance and artificial intelligence (AI) represents a rapidly emerging and high-impact research domain with the potential to reshape sustainable economic systems. This study presents a comprehensive bibliometric and network analysis aimed at mapping the scientific landscape, identifying research hotspots, and highlighting methodological trends at this nexus. A dataset of 268 peer-reviewed publications (2014–June 2025) was retrieved from the Web of Science Core Collection, filtered by the Business Economics category. Analytical techniques employed include Bibliometrix in R, VOSviewer, and science mapping tools such as thematic mapping, trend topic analysis, co-citation networks, and co-occurrence clustering. Results indicate an annual growth rate of 53.31%, with China leading in both productivity and impact, followed by Vietnam and the United Kingdom. The most prolific affiliations and authors, primarily based in China, underscore a concentrated regional research output. The most relevant journals include Energy Economics and Finance Research Letters. Network visualizations identified 17 clusters, with focused analysis on the top three: (1) Emission, Health, and Environmental Risk, (2) Institutional and Technological Infrastructure, and (3) Green Innovation and Sustainable Urban Development. The methodological landscape is equally diverse, with top techniques including blockchain technology, large language models, convolutional neural networks, sentiment analysis, and structural equation modeling, demonstrating a blend of traditional econometrics and advanced AI. This study not only uncovers intellectual structures and thematic evolution but also identifies underdeveloped areas and proposes future research directions. These include dynamic topic modeling, regional case studies, and ethical frameworks for AI in sustainable finance. The findings provide a strategic foundation for advancing interdisciplinary collaboration and policy innovation in green AI–finance ecosystems. Full article

The global climate crisis has driven unprecedented agreements among nations on carbon mitigation. With China’s commitment to carbon peaking and carbon neutrality targets, the building sector has emerged as a critical focus for emission reduction, particularly because office buildings account for over 30% of building energy consumption. However, a systematic and regionally adaptive low-carbon technology evaluation framework is lacking. To address this gap, this study develops a multidimensional decision-making system to quantify and rank low-carbon technologies for office buildings in Beijing. The method includes four core components: (1) establishing three archetypal models—low-rise (H ≤ 24 m), mid-rise (24 m < H ≤ 50 m), and high-rise (50 m < H ≤ 100 m) office buildings—based on 99 office buildings in Beijing; (2) classifying 19 key technologies into three clusters—Envelope Structure Optimization, Equipment Efficiency Enhancement, and Renewable Energy Utilization—using bibliometric analysis and policy norm screening; (3) developing a four-dimensional evaluation framework encompassing Carbon Reduction Degree (CRD), Economic Viability Degree (EVD), Technical Applicability Degree (TAD), and Carbon Intensity Degree (CID); and (4) conducting a comprehensive quantitative evaluation using the AHP-entropy-TOPSIS algorithm. The results indicate distinct priority patterns across the building types: low-rise buildings prioritize roof-mounted photovoltaic (PV) systems, LED lighting, and thermal-break aluminum frames with low-E double-glazed laminated glass. Mid- and high-rise buildings emphasize integrated PV-LED-T8 lighting solutions and optimized building envelope structures. Ranking analysis further highlights LED lighting, T8 high-efficiency fluorescent lamps, and rooftop PV systems as the top-recommended technologies for Beijing. Additionally, four policy recommendations are proposed to facilitate the large-scale implementation of the program. This study presents a holistic technical integration strategy that simultaneously enhances the technological performance, economic viability, and carbon reduction outcomes of architectural design and renovation. It also establishes a replicable decision-support framework for decarbonizing office and public buildings in cities, thereby supporting China’s “dual carbon” goals and contributing to global carbon mitigation efforts in the building sector. Full article

Designing optimal heritage tourism routes in secondary cities involves complex trade-offs between cultural richness, travel time, carbon emissions, spatial coherence, and group satisfaction. This study addresses the Personalized Group Trip Design Problem (PGTDP) under real-world constraints by proposing DRL–IMVO–GAN—a hybrid multi-objective optimization framework that integrates Deep Reinforcement Learning (DRL) for policy-guided initialization, an Improved Multiverse Optimizer (IMVO) for global search, and a Generative Adversarial Network (GAN) for local refinement and solution diversity. The model operates within a digital twin of Warin Chamrap’s old town, leveraging 92 POIs, congestion heatmaps, and behaviorally clustered tourist profiles. The proposed method was benchmarked against seven state-of-the-art techniques, including PSO + DRL, Genetic Algorithm with Multi-Neighborhood Search (Genetic + MNS), Dual-ACO, ALNS-ASP, and others. Results demonstrate that DRL–IMVO–GAN consistently dominates across key metrics. Under equal-objective weighting, it attained the highest heritage score (74.2), shortest travel time (21.3 min), and top satisfaction score (17.5 out of 18), along with the highest hypervolume (0.85) and Pareto Coverage Ratio (0.95). Beyond performance, the framework exhibits strong generalization in zero- and few-shot scenarios, adapting to unseen POIs, modified constraints, and new user profiles without retraining. These findings underscore the method’s robustness, behavioral coherence, and interpretability—positioning it as a scalable, intelligent decision-support tool for sustainable and user-centered cultural tourism planning in secondary cities. Full article

This study investigates strategies for urban-scale renewable energy integration through a photovoltaic-centric approach, with a case study of a district in Barcelona. The methodology integrates spatial and morphological data using a geographic information system (GIS)-based and clustering framework to address challenges of CO₂ emissions, air pollution, and energy inefficiency. Rooftop availability and photovoltaic (PV) design constraints are analysed under current urban regulations. The spatial analysis incorporates building geometry and solar exposure, while an evolutionary optimisation algorithm in Grasshopper refines shading analysis, energy yield, and financial performance. Clustering methods (K-means and 3D proximity) group PV panels by solar irradiance uniformity and spatial coherence to enhance system efficiency. Eight PV deployment scenarios are evaluated, incorporating submodule integrated converter technology under a solar power purchase agreement model. Results show distinct trade-offs among PV scenarios. The standard fixed tilted (31.5° tilt, south-facing) scenario offers a top environmental and performance ratio (PR) = 66.81% but limited financial returns. In contrast, large- and huge-sized modules offer peak financial returns, aligning with private-sector priorities but with moderate energy efficiency. Medium- and large-size scenarios provide balanced outcomes, while a small module and its optimised rotated version scenarios maximise energy output yet suffer from high capital costs. A hybrid strategy combining standard fixed tilted with medium and large modules balances environmental and economic goals. The district’s morphology supports “solar neighbourhoods” and demonstrates how multi-scenario evaluation can guide resilient PV planning in Mediterranean cities. Full article

Driven by stringent emission regulations, advanced combustion modes utilizing turbulent jet ignition technology are pivotal for enhancing the performance of marine low-speed natural gas dual-fuel engines. This review focuses on three novel combustion modes, yielding key conclusions: (1) Compared to the conventional DJCDC mode, the TJCDC mode exhibits a significantly higher swirl ratio and turbulence kinetic energy in the main chamber during initial combustion. This promotes natural gas jet development and combustion acceleration, leading to shorter ignition delay, reduced combustion duration, and a combustion center (CA50) positioned closer to the Top Dead Center (TDC), alongside higher peak cylinder pressure and a faster early heat release rate. Energetically, while TJCDC incurs higher heat transfer losses, it benefits from lower exhaust energy and irreversible exergy loss, indicating greater potential for useful work extraction, albeit with slightly higher indicated specific NOx emissions. (2) In the high-compression ratio TJCPC mode, the Liquid Pressurized Natural Gas (LPNG) injection parameters critically impact performance. Delaying the start of injection (SOI) or extending the injection duration degrades premixing uniformity and increases unburned methane (CH₄) slip, with the duration effects showing a load dependency. Optimizing both the injection timing and duration is, therefore, essential for emission control. (3) Increasing the excess air ratio delays the combustion phasing in TJCPC (longer ignition delay, extended combustion duration, and retarded CA50). However, this shift positions the heat release more optimally relative to the TDC, resulting in significantly improved indicated thermal efficiency. This work provides a theoretical foundation for optimizing high-efficiency, low-emission combustion strategies in marine dual-fuel engines. Full article

Renewable energy stands as a pivotal solution to environmental concerns, prompting substantial research and development endeavors to promote its adoption and enhance energy efficiency. Despite the recognized environmental superiority of renewable energy systems, there is a lack of globally standardized indicators specifically focused on renewable energy efficiency. This study aims to develop and apply a non-parametric data envelopment analysis (DEA) indicator, termed the Renewable Energy Indicator (REI), to measure environmental performance at the national level and to identify differences in renewable energy efficiency across countries grouped by development status and income level. The REI incorporates new factors such as agricultural methane emissions (thousand metric tons of ${\mathrm{CO}}_2$ equivalent), PM2.5 air pollution exposure (µg/m³), and aspects related to electricity, including consumption (as % of total final energy consumption), production from renewable sources, excluding hydroelectric (kWh), and accessibility in rural and urban areas (% of population with access), aligning with the emerging paradigm outlined by the United Nations. By segmenting the REI into global, developmental, and income group classifications, this study conducts the Mann–Whitney U test and the Kruskal–Wallis H tests to identify variations in renewable energy efficiency among different country groups. Our findings reveal top-performing countries globally, highlighting both developed (e.g., Sweden) and developing nations (e.g., Costa Rica, Sri Lanka). Central and North European countries demonstrate high efficiency, while those facing political and economic instability perform poorly. Agricultural-dependent nations like Australia and Argentina exhibit lower REI due to significant methane emissions. Disparities between developed and developing markets underscore the importance of understanding distinct socio-economic dynamics for effective policy formulation. Comparative analysis across income groups informs specific strategies tailored to each category. Full article

Achieving high quantum yields for Yb³⁺ ion emission in complexes with organic ligands is a challenging task, as most Yb³⁺ complexes with such ligands typically exhibit efficiencies below 3.5%. Our research demonstrates that the introduction of heavy atom-containing ancillary ligands, such as TPPO or TPAO, along with the careful engineering of the main β-diketone ligand, can increase the luminescence efficiency up to 20-fold by the alteration of the energy migration pathway. It is demonstrated that the combination of two distinct organic ligands leads to the blockage of singlet–triplet intersystem crossing (ISC), alongside electronic energy transfer from β-diketone to Yb³⁺ ions through charge transfer states. The synthesized complexes exhibit quantum yields of 6.5% and 7.0% in the solid state, which places them at the top globally among this class of materials with simple non-deuterated and non-fluorinated ligands. Full article

Driven by the urgent need to mitigate climate change and achieve net-zero emissions, carbon pricing has emerged as a critical policy tool in major economies worldwide. This study compares carbon pricing in the EU, China, Canada, and Singapore, evaluating effectiveness in emission reductions, with the EU ranking first with high carbon prices, road market coverage, and strict penalties, based on carbon price per capita. Conversely, Singapore’s position as fourth in carbon price per capita among these four most mature carbon markets, Singapore has a high GDP per capita and lower carbon prices. Canada’s fragmented provincial policies and China’s limited market coverage, despite being the top global emitter. Our analysis reveals three critical success factors: (1) higher carbon prices per capita are essential for carbon reduction, (2) the necessity of penalties on carbon price per capita from EUR 20–EUR 100, and (3) expanded market coverage maximizes impact. To address global disparities, we propose a Uniform Carbon Pricing Mechanism under the Global Carbon Resilience Framework (GCRF), based on carbon price per capita tiered pricing: EUR 100/t (developed), EUR 30–50 (developing), and EUR 5–15 (least-developed countries). This balanced system supports vulnerable regions while cutting emissions, proving that fair carbon pricing is crucial for climate goals and economic stability. Full article

Under the pressures of global climate change, the sustainable management of plant resources in alpine gorge regions faces severe challenges. P. aquilinum var. latiusculum is widely harvested and utilized by residents in the upper reaches of the Dadu River–Min River basin due to its high edible and medicinal value. This study employed ensemble models to simulate the potential distribution of P. aquilinum var. latiusculum in this region, predicting the impacts of future climate change on its distribution, the centroid migration of suitable habitats, and niche dynamics. A production dynamics model was also constructed to identify current and future potential cultivation areas by integrating ecological suitability and nutritional component synergies. The results show that current high-suitability areas and core cultivation zones of P. aquilinum var. latiusculum are predominantly distributed in patchy, fragmented patterns across the Wenchuan, Li, Mao, Luding, and Xiaojin Counties and Kangding City. Under climate change, the “mountain-top trap effect” drives a significant increase in high-suitability areas and core cultivation zones, while moderate-to-low-suitability areas and marginal cultivation zones decrease substantially. Meanwhile, suitable habitats and cultivation areas exhibit a northward migration trend toward higher latitudes. The most significant changes in suitable area and cultivation zone extent, as well as the most pronounced niche shifts, occur under high-emission climate scenarios. This research facilitates the development of suitability-based management strategies for P. aquilinum var. latiusculum in the study region and provides scientific references for the sustainable utilization of montane plant resources in the face of climate change. Full article

The historical peak in CO₂ emissions has intensified global environmental concerns, urging the identification of key determinants. While economic drivers are well-documented, political dimensions—especially democracy and institutional quality—are increasingly emphasized. However, the role of freedom of association and organization (AOF), a core democratic element, remains largely unexamined in this context. This study fills this gap by analyzing the impact of AOF on CO₂ emissions in the top 20 emitter countries from 2006 to 2022. The selection of these countries enables a focused assessment of the world’s primary polluters, ensuring high policy relevance. Using second-generation panel estimators, the Augmented Mean Group and the Common Correlated Effects Mean Group estimators, the analysis accounts for heterogeneity and cross-sectional dependence. Robustness is tested using the CS-ARDL method, confirming the stability of results. Empirical findings show that higher levels of AOF significantly reduce CO₂ emissions. Income and energy consumption increase emissions, while the effect of trade openness is statistically insignificant. These results suggest that strengthening associational freedoms can offer a dual benefit: advancing democratic norms and achieving environmental goals. Full article

Nitrogen oxides (NO_X) are important precursors of ozone and secondary aerosols. Accurate and timely NO_X emission estimates are essential for formulating measures to mitigate haze and ozone pollution. Bottom–up and satellite–constrained top–down methods are commonly used for emission inventory compilation; however, they have limitations of time lag and high computational demands. Here, we propose a machine learning model, WOA-XGBoost (Whale Optimization Algorithm–Extreme Gradient Boosting), to retrieve NO_X emissions. We constructed a dataset incorporating satellite observations and conducted model training and validation in the Shandong region with severe NO_X pollution to retrieve high spatiotemporal resolution of NO_X emission rates. The 10–fold cross–validation coefficient of determination (R²) for the NO_X emission retrieval model was 0.99, indicating that WOA-XGBoost has high accuracy. Validation of the model for the other year (2019) showed high agreement with MEIC (Multi–resolution Emission Inventory for China), confirming its strong robustness and good temporal transferability. The retrieved NO_X emissions for 2021–2022 revealed that emission rate hotspots were located in areas with heavy traffic flow. Among 16 prefecture–level cities in Shandong, Zibo exhibited the highest NO_X rate (>1 μg/m²/s), explaining its high NO₂ pollution levels. In the future, priority areas for emission reduction should focus on heavy industry clusters such as Zibo and high traffic urban centers. Full article

Excessive carbon dioxide (CO₂) emissions represent a critical challenge in mitigating global warming, necessitating advanced separation technologies for efficient carbon capture. Silica-based membranes have attracted significant attention due to their exceptional chemical, thermal, and mechanical stability under harsh operating conditions. In this study, we introduce a novel layered hybrid membrane designed based on amine-functionalized silica precursors, where a distinct affinity gradient is engineered by incorporating two types of amine-functionalized materials. The top layer was composed of high-affinity amine species to maximize CO₂ sorption, while a sublayer with milder affinity facilitated smooth CO₂ diffusion, thereby establishing a continuous solubility gradient across the membrane. A dual approach, combining comprehensive experimental testing and rigorous theoretical modeling, was employed to elucidate the underlying CO₂ transport mechanisms. Our results reveal that the hierarchical structure significantly enhances the intrinsic driving force for CO₂ permeation, leading to superior separation performance compared to conventional homogeneous facilitated transport membranes. This study not only provides critical insights into the design principles of affinity gradient membranes but also demonstrates their potential for scalable, high-performance CO₂ separation in industrial applications. Full article

To address severe ammonia gas and dust pollution coupled with resource waste in exhaust gases from urea prilling towers, a production process for gasified biochar-based slow-release fertilizer is proposed to achieve resource recovery of exhaust pollutants. Through phosphoric acid impregnation modification applied to gasified biochar, its ammonia gas adsorption capacity was significantly enhanced, with saturated adsorption capacity increasing from 0.61 mg/g (unmodified) to 32 mg/g. Coupled with the tower-top bag filter, the modified biochar combines with ammonia gas and urea dust in exhaust gases, subsequently forming biochar-based slow-release fertilizer through dehydration and granulation processes. Material balance analysis demonstrates that a single 400,000-ton/year urea prilling tower achieves a daily fertilizer production capacity of 55 tons, with 18% active ingredient content. The nitrogen content can be upgraded to national standards through urea supplementation. Economic analysis demonstrates a total capital investment of USD1.2 million, with an annual net profit of USD0.88 million and a static payback period of 1.36 years. This process not only achieves ammonia gas emission reduction but also converts waste biochar into high-value fertilizer. It displays dual advantages of environmental benefits and economic feasibility and provides an innovative solution for resource utilization of the exhaust gases from the urea prilling process. Full article