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.
The rapid evolution of geoinformatics technologies, particularly through the adoption of Unmanned Aircraft Systems (UAS), has brought significant changes to the collection, processing, and analysis of spatial data. UAS are increasingly integrated into Geographic Information Systems (GIS), remote sensing, and spatial analysis, enhancing efficiency and accuracy in applications such as precision agriculture and infrastructure management. However, limited empirical research has examined the consequences of their integration for operational efficiency, regulatory compliance, and related management practices in the Greek context. This study evaluates how UAS integration into the operations of Greek geoinformatics firms enhances efficiency and supports compliance with Greek and European regulatory frameworks. A qualitative multi-case study methodology is employed across five Greek geoinformatics service providers, and data are collected through semi-structured interviews and secondary sources. Findings indicate that UAS integration improves the quality of spatial data, reduces data collection costs, and facilitates regulatory compliance of these firms. Finally, the study highlights the emergence of optimal operational management policies of UAS including standardized end-to-end workflows, clear role allocation and compliance responsibilities, systematic QA/QC procedures, proactive regulatory monitoring (PDRA/SORA readiness), which strengthen and promote innovative geoinformatics technologies.
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.
Human civilization threatens the life support functions generated by global ecosystems. Humanity must forge an ecological civilization to avoid collapse. We apply evolutionary theory to the human system, with an emphasis on the economy, to understand how we have arrived at our current predicament and to suggest paths forward. Neoliberal economic theory claims that within markets, the self-interested behavior of individuals and firms maximizes societal welfare, while some strands of evolutionary theory claim that selfish individuals will outcompete their selfish conspecifics. Yet, cooperation is ubiquitous. Humans have become more interdependent than ever. We present a theoretical argument that the structure of the global economy is best explained by multilevel selection (MLS)—an evolutionary process wherein competitive individuals outcompete cooperative individuals within groups, while cooperative groups outperform competitive groups. MLS helps explain why both cooperation and selfishness co-exist, with cooperation the most adaptive social behavior at higher-scales. We conclude that achieving an ecological civilization will not only require cooperation at the global scale, but also the forging of a new relationship between humans and the rest of nature, akin to the relationship between a human cell and the human body.
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.
