With accelerating climate change and rising global energy consumption, the application of artificial intelligence (AI) and machine learning (ML) has emerged as a crucial tool for enhancing energy efficiency and mitigating the impacts of climate change. However, their implementation has a dual character: on one hand, AI facilitates sustainable solutions, including energy optimization, renewable energy integration and carbon reduction; on the other hand, the training and operation of large language models (LLMs) entail significant energy consumption, potentially undermining carbon neutrality efforts. Key findings include an analysis of 237 scientific publications from 2010 to 2024, which highlights significant advancements and obstacles to AI adoption across sectors, such as construction, transportation, industry, energy and households. The review showed that interest in the use of AI and ML in energy efficiency has grown significantly: over 60% of the documents have been published in the last two years, with the topics of sustainable construction and climate change forecasting attracting the most interest. Most of the articles are published by researchers from China, India, the UK and the USA, (28–33 articles). This is more than twice the number of publications from researchers around the rest of the world; 58% of research is concentrated in three areas: engineering, computer science and energy. In conclusion, the review also identifies areas for further research aimed at minimizing the negative impacts of AI and maximizing its contribution to sustainable development, including the development of more energy-efficient AI architectures and new methods of energy management.

The integration of artificial intelligence (AI) technologies is reshaping diverse domains of human activity, including natural resource management, urban and rural planning, agri-food systems, industry, energy, education, and healthcare. However, the impact of AI on the sustainability of local ecosystems remains insufficiently systematized. This highlights the need for a comprehensive review that considers spatial, sectoral, and socio-economic characteristics of regions, as well as interdisciplinary approaches to sustainable development. This study presents a scoping review of 198 peer-reviewed publications published between 2010 and March 2025, focusing on applied cases of AI deployment in local contexts. Special attention is given to the role of AI in monitoring water, forest, and agricultural ecosystems, facilitating the digital transformation of businesses and territories, assessing ecosystem services, managing energy systems, and supporting educational and social sustainability. The review includes case studies from Africa, Asia, Europe, and Latin America, covering a wide range of technologies—from machine learning and digital twins to IoT and large language models. Findings indicate that AI holds significant potential for enhancing the efficiency and adaptability of local systems. Nevertheless, its implementation is accompanied by notable risks, including socio-economic disparities, technological inequality, and institutional limitations. The review concludes by outlining research priorities for the sustainable integration of AI into local ecosystems, emphasizing the importance of cross-sectoral collaboration and scientific support for regional digital transformations.

The purpose of the article is to actualize the challenges faced by Ukrainian agriculture in the context of climate change and the impact of the economic activity of enterprises on the state of natural resources, as well as to consider the ways and mechanisms of the post-war transition of Ukrainian agriculture to sustainable development. In the study, we used monographic, comparative analysis, empirical, abstract, and logical methods. The first consequences of climate change in agricultural sectors of the planet are characterized. Increasing temperatures to a maximum level, longer periods of extreme heat, more intense droughts, increased moisture deficit during the growing season, winter thaws, the spread of pests and diseases, and other manifestations of climate change have a negative impact on agricultural production. In the context of climate change, as highlighted in the paper, these negative processes will significantly intensify, requiring an immediate transition from ecologically and socially destructive monoculture to agroecological agriculture, which is recognized as one of the most affordable, low-cost, socially oriented, and environmentally relevant ways to transition to sustainable development of the industry. The principles and institutional support for such a transition are revealed, taking into account the expected climate change and post-war consequences for Ukrainian agriculture.

This study investigates the cluster approach to optimize strategies for agricultural enterprises in Ukraine, emphasizing geographical proximity as a key factor in cluster formation. The research applies Kohonen Self-Organizing Maps (SOMs) and Ward’s hierarchical clustering to classify enterprises based on storage capabilities, transport logistics, crop yields, and military risk exposure. By analyzing these factors, this study identifies distinct patterns of innovation adoption, strategic management, and economic resilience among the clusters. The findings highlight variations in competitiveness and resource efficiency, providing a detailed understanding of regional economic performance. Unlike previous research, this study offers a novel integration of conflict-related risks into the clustering methodology, revealing new insights into how military factors influence cluster dynamics. Comprehensive maps and diagrams illustrate the spatial and economic distribution of clusters, aiding in visual interpretation. The results propose strategic measures tailored to enhance agricultural productivity and competitiveness, particularly in Ukraine’s current military context. This approach offers a more adaptive framework for managing agricultural enterprises, promoting resilience and long-term sustainability in global markets.

Achieving sustainable development in the low-carbon transition requires securing critical raw materials (CRMs) while reducing environmental burdens and strengthening industrial resilience (SDGs 7, 9, 12, 13). This review synthesizes 2016–2025 evidence on how the European Union’s policy package—the Critical Raw Materials Act (CRMA), the Batteries Regulation, the Ecodesign for Sustainable Products Regulation (ESPR) with Digital Product Passports (DPPs), and the recast Waste Shipments Regulation (WSR)—shapes markets for secondary supply in battery-relevant metals such as lithium, cobalt, nickel, copper, aluminum, and rare earths. We apply a structured scoping review protocol to map the state of the art across policy instruments (EPR, ecodesign/DPP, recycled content mandates, recovery targets, shipment controls) and value chain stages (collection, preprocessing, refining, manufacturing). The analysis highlights benefits, including clearer investment signals, improved traceability, and emerging opportunities for industrial symbiosis, but also identifies drawbacks such as heterogeneous standards, compliance costs, and trade frictions. Evidence gaps remain, especially in causal ex post assessments, price pass-through, and interoperability of MRV/DPP systems. The paper contributes by (i) providing an integrative framework linking policy instruments, value chain stages, and investment signals for secondary CRM supply, and (ii) outlining a research agenda for rigorous ex post evaluation, improved MRV/DPP data architectures, and better alignment between EU trade rules, circularity, and a just energy transition.

Amidst the growing challenges of climate change, the advancement of bioenergy in Ukraine emerges as a strategic imperative for achieving sustainable development, energy independence, and compliance with international climate commitments. As one of the key pillars of Ukraine’s economy, the agricultural sector holds vast potential for renewable energy production, utilizing both crop residues and dedicated energy crops. This study provides a comprehensive assessment of the current state and potential of agrobiomass, taking into account the destruction of infrastructure and the urgent need for soil restoration. The novelty of this research lies in its in-depth evaluation of Ukraine’s bioenergy potential under conditions of energy system destabilization and in the introduction of innovative solutions aimed at strengthening sectoral resilience. The findings highlight the critical importance of expanding bioenergy production while identifying key institutional and regulatory barriers that hinder its progress. This study proposes actionable strategies to overcome these challenges, including the adaptation of international best practices, regulatory framework enhancements, and the implementation of targeted government support programs. The insights are valuable not only for policymakers in Ukraine but also for other countries striving to accelerate the transition to renewable energy and establish sustainable decentralized energy systems. Future research directions include the development of cutting-edge biomass processing technologies, a thorough economic evaluation of bioenergy’s long-term impact on energy and environmental sustainability, and an in-depth exploration of bioenergy’s cross-border potential to enhance the energy security and resilience of the European Union.