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Biological invasions, driven by the spread of non-native species, have become a critical global issue because of their far-reaching ecological and socioeconomic impacts. Effective communication of the risks of biological invasions is essential for implementing robust policy and legislation and gaining public support for conservation efforts. However, current policies often suffer from fragmentation and ineffectiveness, largely due to inadequate risk communication and complex multi-level governance. To address this challenge, we develop a global framework designed to enhance clearer communication about biological invasion risks. The framework contextualizes key terms across three domains in invasion science: species invasiveness, risk analysis, and decision support tools. Using both diffusion-of-English and ecology-of-language paradigms, and following a three-step process involving preliminary consensus, AI querying, and ground-truthing with final consensus, we validate the framework in 70 non-English languages which, together with English, have official status in at least one country and collectively cover all 195 countries worldwide. Our findings reveal that while terminology for risk analysis is well established, terminology for species invasiveness and, especially, for decision support tools remains underdeveloped in many languages, hindering effective communication and policy implementation. Our framework underscores the importance of cultural and political neutrality. By promoting clearer risk communication among scientists, policymakers, and the public globally, we aim to reduce policy fragmentation and foster enhanced collaboration in risk mitigation. We recommend expanding multilingual decision support tools to include the full risk analysis process: risk identification, risk assessment, and risk management. This will support intergovernmental mitigation efforts and promote a unified global response to biological invasions.
This study investigates the techno-economic prospects of converting direct-air-captured CO2 into valuable chemicals to reduce capture costs and encourage wider use. Overall, twenty-three bulk chemicals are evaluated based on safety, reaction severity, catalyst recovery, fossil reliance, market demand, CO2 uptake, energy use, and 100 kt/y economics. Hazardous, endothermic, and homogenous catalyst routes are excluded, leaving five reasonable options, synthesized either via electrochemical or thermocatalytic route. For the former type of synthesis, oxalic acid turns out to be the most optimal while all the proposed solutions are found to be currently unprofitable for the thermocatalytic routes given green hydrogen cost. Nevertheless, dimethyl ether (DME) becomes financially attractive option for the scenario that is expected to take place by 2030 based on expected advancements in green hydrogen technology. Thus, DME is deemed to be the favored short-term method, barring hydrogen cost decreases, but oxalic acid is better suited for long-term development when its scale-up to industrial phase becomes feasible. The findings of this research will facilitate transformation of CO2, once recognized as a waste, into a valuable raw material encouraging CO2 capture despite the economic burden of direct air capture (DAC) technology. As a result, not only can the dire effects of global warming be mitigated, but a novel feedstock can also be introduced to the industry as an alternative to fossil fuels.
The article investigates the issue of five-level risk assessment of energy consumption anomalies using a Z-number-based soft computing model. In modern energy systems, sharp or gradual changes in consumption indicators may be associated with technical failures, inefficient usage, changes in production regimes, or external environmental factors. Therefore, it is important not only to detect anomalies in energy consumption but also to classify them correctly according to risk levels. The study substantiates the advantages of the Z-number approach, which supports decision-making under conditions of uncertainty and incomplete information. Since the Z-number model takes into account both the evaluation indicator and the reliability degree of that indicator, it enables a more realistic and flexible assessment of energy consumption risks. In the article, energy consumption anomalies are evaluated according to five risk levels: very low, low, medium, high, and very high. The proposed model, based on fuzzy logic, expert assessments, and soft computing principles, serves as a practical tool for early warning, monitoring, and planning preventive measures in energy management systems. The results of the study show that the Z-number-based approach can provide more effective results in processing uncertain data compared with classical statistical methods. In future studies, it is advisable to test the model on real energy consumption datasets and integrate it with artificial intelligence algorithms.
The paper explores the importance of applying innovative technologies in modern urban development. The primary focus of the article is on the role of technological approaches in the urbanization process of Baku, particularly the contribution of digital governance and green technologies in ensuring ecological sustainability. The first section explains the concept of Green Technologies and their potential for integration into the urban environment. These technologies are regarded as key factors in environmental protection, maintaining ecological balance, and the efficient use of energy resources. In the section on Urban Governance and Technology, smart city models implemented in Baku, digital management platforms, and methods for optimizing urban resources are presented. The article also allocates considerable attention to the modernization of infrastructure, highlighting examples of new technology applications in the renovation of transportation, water and sewage systems, and energy supply networks. The article provides information on innovative solutions used to reduce energy consumption in buildings and public spaces within the context of energy efficiency, as well as the implementation of alternative energy sources. The section on waste management analyzes the prospects for household waste sorting, recycling, and the application of zero-waste production technologies in Baku. The article also highlights the role of digital governance tools in ecological monitoring, traffic flow regulation, and optimization of public services in the city. By linking climate change and the urban environment, the article presents pilot projects implemented in Baku—such as initiatives under the “Smart City” concept—including the development of energy-efficient buildings, bicycle lanes, and ecological parks.
This article reviews the digital technologies currently used in sustainable tourism management and analyses the principal models and tools of digitalisation in the tourism industry. The role of information and communication technology in improving the management of tourism resources, raising service quality and supporting the environmental sustainability of destinations is examined, with particular attention to artificial intelligence, big data, the Internet of Things, digital platforms and geographic information systems in monitoring, forecasting and management decision-making. A comparative assessment of five technology groups is carried out against four criteria — purpose of use, type of information generated, influence on policy-making and relevance to sustainable development — and is complemented by a SWOT analysis. The review identifies the benefits of digital implementation, including the optimisation of tourist flows, the reduction of negative environmental impacts, improved safety and better interaction among market participants, and examines the constraints associated with cybersecurity, personal data protection, inadequate digital infrastructure and the shortage of qualified specialists. The analysis indicates that no single technology can by itself support sustainable tourism management, and that effectiveness is achieved only through the integration of these tools into a single digital ecosystem governed through public–private partnership.
