Urban air quality reflects the combined effects of topography, built form, and emission sources, producing pronounced spatial and temporal variability in pollutant dispersion. This study investigates how urban morphological features-building density, green-space distribution, and transportation corridors-shape these dispersion patterns by deploying unmanned aerial vehicles (UAVs) equipped with Air Quality Index (AQI) sensors. Multi-altitude, high-resolution drone transects were conducted across contrasting urban settings to capture fine-scale pollutant distributions and their dynamics. The measurements reveal localized hotspots and zones of limited dispersion that align with variations in building layout, vegetation presence, and traffic intensity. Compared with fixed-site monitors, the UAV approach resolves vertical and horizontal gradients that are otherwise missed, providing complementary evidence of three-dimensional micro-scale heterogeneity. Taken together, the results indicate that decisions on urban design and infrastructure placement materially influence air-quality outcomes. These findings support the integration of UAV-based observations with conventional monitoring networks to inform targeted mitigation measures, exposure-aware mobility planning, and evidence-based strategies for public health and urban sustainability.
To address the challenge of further reducing impurities in raw materials for high-purity melting of industrial-superalloys such as GH4169D, this study employed a CALPHAD-based high-throughput computational approach to establish the composition-phase stability-impurity behavior relationship. A low-melting-point, high-cleanliness Ni–Cr–Nb master alloy was developed and characterized with oxygen and nitrogen contents of 76 ppm and 36 ppm, respectively, and an inclusion number density of approximately 540 ± 20 cm−2 and an average inclusion size of 2.2 ± 0.15 μm, demonstrating excellent cleanliness and compositional controllability. In industrial-scale 3-ton GH4169D melting trials using the Ni–Cr–Nb master alloy, the oxygen content was reduced from 12 ppm to 8 ppm. The inclusion number densities at the ingot center, R/2 position, and edge were decreased by 7.75%, 36.1%, and 81.5%, respectively, while the maximum inclusion size was reduced from approximately 28 μm to 9–17 μm. The results indicate that the developed master alloy effectively suppresses the formation, growth, and radial segregation of inclusions in GH4169D, significantly enhancing its metallurgical uniformity and cleanliness. Furthermore, melting efficiency increased by 52.6%, and production costs decreased by approximately 2.3% per ton, highlighting substantial process and economic advantages. This work establishes a closed-loop research framework integrating “CALPHAD-based experimental design—industrial pilot-scale validation—production-line metallurgical quality evaluation”. It confirms the effectiveness of the master alloy strategy for high-purity scale-up superalloy production and provides a transferable technological pathway for the compositional design and industrial application of other master alloy systems and commercial alloys.
In recent years, visible-light-induced transformations have taken a central role in driving forward the progress of modern organic synthesis. Despite the abundance of synthetic strategies enabling access to aryl- and alkyl-centered radicals, the exploitation of photochemistry to generate highly reactive alkenyl radicals has remained notably underdeveloped. Herein, we report a sustainable strategy for generating alkenyl radicals based on a photocatalytic single-electron transfer process. Through systematic optimization of conditions such as photocatalysts, light sources, and additives, we confirmed that radical reactions can efficiently occur under metal-free conditions using styrenylthiophene salt as radical donors, thiuram derivatives as radical acceptors, and 4CzIPN (1,2,3,5-tetrakis(carbazol-9-yl)-4,6-dicyanobenzene) as the photocatalyst. This method is operationally simple, environmentally friendly, and does not require the addition of precious metal reagents, providing a novel strategy for the methodology of alkenyl radical generation.
The objective of marine ecological safety necessitates the development of comprehensive, integrated strategies for oil spill management, encompassing advanced monitoring and effective remediation. This paper introduces and validates a novel integrated methodology and conceptual framework for autonomous marine environmental safety. The core of this framework lies in the merging of AI-assisted monitoring capabilities with a multi-agent Unmanned Aerial Vehicle (UAV) system for targeted dispersant delivery. UAV systems, within this methodology, function as a cost-effective and readily deployable operational platform. The study details the primary development stages of the methodology-driven system and presents empirical results from in-situ field trials. The framework leverages artificial intelligence (AI) tools developed and validated for slick monitoring, which execute primary segmentation for spill detection and subsequent secondary segmentation to categorize the slick into thickness uniformity maps. Datasets of actual marine oil slick imagery were compiled to facilitate robust deep learning of the underlying neural network architectures. The study explores scientific feasibility, specifically employing Laser-Induced Fluorescence (LIF) spectroscopy to classify oil product grades and assess the ecological impact of various remediation agents on local phytoplankton communities. This integrated method for spill response is underpinned by successful field validation results. The full methodology was tested during actual oil spill incidents in the waters of Peter the Great Bay from 2019 to 2024. The article presents experimental validation of a new concept and methodology of integrated environmental safety of marine areas by a multi-agent UAV system in the event of oil product spills.
Although fossil fuels are the primary source of energy in the world, their greenhouse gas emissions and other pollutants provide serious environmental problems. This study uses a gasoline blend with ethanol and methanol to examine the emissions and performance of a spark ignition (SI) engine. An experimental design focused on engine input factors such as load and fuel blends. Brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), and emissions of carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx) were examined about these parameters using Taguchi’s L16 orthogonal array and ANOVA via Minitab 18. The results show that 80% engine load and a 15% blend for both ethanol and methanol provide the best engine performance, greatly lowering BSFC and raising BTE. Notably, 20% engine load and 15% blend result in the lowest CO emissions, whilst 20% load and 0% blend result in the lowest NOx emissions. Also, 20% load and 15% blend result in the lowest HC emissions. This study highlights the potential of alternative fuel blends to improve engine efficiency and reduce hazardous emissions.
In the context of the global carbon neutrality strategy, syngas fermentation technology has emerged as a research hotspot in biomanufacturing because it can recover and convert industrial exhaust gas. Relying on the Wood-Ljungdahl pathway in acetogens, this technology converts gaseous substrates, such as CO and CO2, into high-value-added chemicals. However, bottlenecks including low gas-liquid mass-transfer efficiency and challenges with scale-up, severely limit its industrialization. The review focuses on core research-level topics, including the key enzymatic mechanisms of acetogens, metabolic regulation strategies, and high-throughput strain construction technologies; systematically analyzes the feed gas pretreatment process, design principles of large-scale reactors, fermentation process optimization, efficient product separation and purification technologies, and full-process integration at the process level; and summarizes techno-economic analysis and global policy support for industrial application. Finally, it thoroughly analyzes the core challenges of this technology across core mechanisms, engineering operations, economic markets, and industrial chain coordination, and outlines the future development direction of the technology. By systematically collating the syngas fermentation technology system and its industrialization bottlenecks, this review provides references for its industrialization. It is positioned to boost the economic viability and industrial appeal of the CCUS system, acting as a pivotal engine for advancing deep industrial decarbonization and fostering emerging green industries.
Electrical discharge machining (EDM) remains indispensable for high-precision machining of advanced and hard-to-machine materials; however, its broader industrial adoption is constrained by high energy consumption, unstable discharge behavior, dielectric degradation, and limited integration of sustainable and intelligent manufacturing strategies. Although existing reviews address micro-EDM and environmentally benign EDM individually, a consolidated and critical synthesis linking discharge physics, sustainability bottlenecks, and intelligent process control has remained limited. This review systematically analyzes highly cited and recent studies (2020–2024) indexed in Scopus and Web of Science, focusing on micro-EDM, green dielectric systems, hybrid-assisted EDM, and intelligent EDM technologies. The synthesized literature identifies key bottlenecks, including deterioration of the inter-electrode environment, inefficient debris evacuation, dielectric decomposition, and the absence of standardized sustainability performance metrics. The analysis reveals a clear convergence toward hybrid-assisted, sustainability-driven EDM strategies, in which coupled plasma–thermal–chemical interactions govern material removal and surface integrity rather than purely thermal effects. Comparative findings indicate that ultrasonic assistance is most effective for micro-scale and brittle materials, magnetic field assistance enhances plasma stability in conductive metallic systems, and biodegradable or water-based dielectrics significantly reduce environmental impact while maintaining acceptable machining performance. Furthermore, intelligent EDM approaches integrating sensor-based monitoring, AI-assisted optimization, and digital-twin frameworks show strong potential for adaptive control, although industrial deployment remains limited by sensing robustness and system integration challenges. Overall, this review proposes a structured roadmap for transitioning EDM toward intelligent, energy-efficient, and sustainable industrial manufacturing.
The cosmetics industry is undergoing a historic transition from natural extraction to precision biomanufacturing. Amino acid derivatives, as a kind of core functional cosmetic ingredient, have witnessed synthetic biology–based production technologies overcome traditional bottlenecks in efficiency and cost. In this Perspective, grounded in recent advances in the construction of amino acid derivative cell factories, we propose the core trends for the future development of cosmetic ingredients: enzyme engineering, dynamic metabolic control, and irrational strategies are converging to enable both functional customization and production intelligence. Star molecules such as ergothioneine, spermidine, and bioactive peptides are poised to redefine the boundaries of anti-aging efficacy, while AI-driven R&D paradigms offer broad prospects but must still overcome cost, regulatory, and consumer perception barriers. We emphasize that only by establishing an integrated “efficient synthesis–precise delivery–validated activity” end-to-end chain can cosmetic ingredients move from laboratory to market, achieving an industrial leap from chemical addition to biological empowerment.
This paper argues that since the Earth system is the organizational framework within which we find our place, and the ultimate arbitrator of ecological, social and economic sustainability and well-being, then any strategy that would deliver a prosperous, functional and flourishing future must circle around the properties of this complex system and be aware of the implications of these characteristics for our own activities and decisions. To do otherwise would be a strategy of doubtful value. The nature of the Earth system is then explored. We examine the global and the local aspects of this system, in terms of many worlds in one world, the pluriverse. The ecological, social, and economic pluriverses are seen to be nested within one another, and are each emergent entities that arise from the Earth system as a whole. The economies of the biosphere are examined across individual, population, community, and ecosystem levels, across a range of biomes, each of which is specialized in accordance with local conditions. In terms of human economic activities, it is suggested that regional strategies and policies are required, rather than global approaches such as the sustainable development goals. These must be designed to maximize ecosystem functioning and human well-being, which are themselves required for successful net economic growth. Furthermore, human economic activity in each region should resonate with the natural economies in that region. Finally, this thinking is applied to the urban setting, drawing on the work of Geddes and Magnaghi, exploring this in terms of the Earth system and its emergent local outcomes, the ecological, social, and economic pluriverse.
Recent advancements in unmanned aerial vehicle (UAV) technology have enabled flexible, high-resolution monitoring of atmospheric CO2, particularly in complex or otherwise inaccessible environments. This study employs Computational Fluid Dynamics (CFD) to investigate the downwash flow field of a quadcopter UAV in hover condition with the objective of identifying low-disturbance regions suitable for accurate atmospheric sensor placement. A quadcopter model was simulated using the SST k-ω turbulence model. Simulations were performed at rotor speeds ranging from 1000 to 6000 rpm. Results show that the strongest downwash and turbulence occur directly beneath the rotors, while airflow above the central fuselage and regions laterally distant from the rotors remain significantly calmer. The findings strongly recommend placing gas sensors either above the drone body or sufficiently far horizontally from the rotor plane to minimize measurement errors caused by propeller-induced flow.