Search Results (3,202)

The exponential increase in global solid waste generation poses significant environmental, economic, and social challenges, particularly in rapidly urbanizing regions. Traditional waste management methods that focus on handling and disposal have proven unsustainable because of their negative impacts on air, soil, and water quality, and their contribution to greenhouse gas emissions. In response, the concept of zero-waste cities, rooted in circular economy principles, has gained increasing attention in recent years. This study proposes a comprehensive and integrated waste management system designed to optimize resource recovery across four distinct waste streams: household, healthcare, green/organic, and inert. The system integrates four specialized facilities: a Secondary Sorting Facility, Energy Recovery Facility, Composting Facility, and Inert Processing Facility, coordinated through a central Primary Sorting Hub. By enabling interconnectivity between these processing units, the system facilitates material cascading, maximizes the reuse and recycling of secondary raw materials, and supports energy recovery and circular nutrient flow. The anticipated benefits include enhanced operational efficiency, reduced environmental degradation, and generation of multiple revenue streams. However, the implementation of such a system faces challenges related to high capital investment, technological complexity, regulatory fragmentation, and low public acceptance. Overcoming these limitations will require strategic planning, stakeholder engagement, and adaptive governance. Full article

The circular economy (CE) aims to reduce environmental degradation by ensuring the continuous use of materials and energy resources, aligning with the decarbonization agenda. However, despite the rising acceptance of CE concepts, the economic and managerial aspects remain underexplored in policy and practice. Therefore, this study seeks to bridge the knowledge–practice gap by studying how technology-driven innovation, renewable energy, and energy efficiency interact with CE principles to advance sustainable environmental connections in a detailed manner. The economic analysis of this study was conducted using two base and moderation models, utilizing global data from 78 developing and developed countries, and applying Fixed Effect, Random Effect, and Generalized Method of Moments estimates. The samples were selected based on data availability from internationally recognized databases from 2010 to 2021. The key findings suggest that technology-driven innovation and renewable energy reduce carbon emissions, whereas gross domestic product (GDP) growth and energy efficiency show no standalone positive effects. Notably, moderation effects reveal that the integration of technology with GDP promotes sustainability outcomes, but energy efficiency and renewable energy interact negatively with emissions, a contradictory result warranting further policy investigation. CE-driven innovation promotes decarbonization by striking a balance between environmental preservation, economic expansion, and technology uptake. This study emphasizes region-specific techniques and offers policy insights for combining the CE with natural capital and green GDP. It increases the knowledge of how circular business models powered by technology support sustainable growth and the shift to a circular economy. Full article

This study develops a comprehensive analytical framework to examine how nations secure core positions in global supply chains (GSCs) for key industries. It combines a comparative analysis of advanced economies—Los Angeles (aerospace), Munich (high-end manufacturing), London (biopharmaceuticals), and Tokyo (automotive)—with a survey-based empirical assessment of Chinese industry practitioners. Using the Analytic Hierarchy Process (AHP), factor analysis and the Delphi method, an evaluation framework is constructed across five dimensions: technology, value, governance, resilience, and sustainability. The findings show that developed economies sustain their leadership through upstream innovation and standard-setting, coordination of high-value activities, integrated industrial ecosystems, and risk-buffering mechanisms. Empirical results reveal that while China demonstrates relative strengths in governance and value creation, it continues to lag in frontier technologies, resilience, and sustainability. Building on both comparative and empirical evidence, the study proposes strategic pathways for China’s key industries, including technological breakthroughs, innovation-driven clusters, governance reforms, digital resilience, and green cooperation. These insights provide actionable guidance for policymakers and highlight how latecomer economies can transform structural disadvantages into innovation momentum, evolving from participants to rule-setters in global supply chains. Full article

While the corporate adoption of artificial intelligence (AI) is accelerating, its environmental consequences remain insufficiently understood, particularly in absolute firm-level energy consumption. The main objective of this study is to empirically determine the causal impact of AI adoption on absolute firm-level energy consumption in Chinese publicly listed companies, with a particular focus on the mediating role of green innovation and the moderating role of digital capabilities. This study provides the first large-scale micro-level evidence on how AI adoption shapes corporate energy use, drawing on panel data from Chinese non-financial listed firms during 2011–2022. We construct a novel AI adoption index via Word2Vec-based textual analysis of annual reports and estimate its impact using firm fixed effects, instrumental variables, mediation models, and multiple robustness checks. Results show that AI adoption significantly reduces total energy consumption, with a 1% increase in AI intensity associated with an estimated 0.48% decrease in energy use. Green innovation emerges as a key mediating channel, while the energy-saving benefits are amplified in firms with advanced digital transformation and IT-oriented executive teams. Heterogeneity analyses indicate more substantial effects among large firms, private enterprises, non-energy-intensive sectors, and firms in digitally lagging regions, suggesting capability-driven and context-dependent dynamics. This study advances the literature on digital transformation and corporate sustainability by uncovering the mechanisms and boundary conditions of AI’s environmental impact and offers actionable insights for aligning AI investments with carbon reduction targets and industrial upgrading in emerging economies. Full article

This paper examines the evolving role of social economy organisations (SEOs) in advancing sustainability and contributing to the green transition. While traditionally focused on social inclusion and local development, SEOs are increasingly integrating environmental objectives into their operations, particularly through circular economy (CE) practices, decarbonisation strategies, and short food supply chains (SFSCs). Based on qualitative research and the analysis of 16 good practices from five European countries, the study demonstrates how SEOs create blended social and environmental value by combining economic, social, and ecological goals. The findings show that SEOs foster environmental sustainability by reducing resource consumption and carbon emissions, creating green jobs, strengthening local cooperation, and raising environmental awareness within communities. Importantly, SEOs emerge not only as service providers but also as innovators and agents of change in local ecosystems. The paper concludes with policy recommendations to enhance the role of SEOs in the green transition and identifies directions for future research, particularly regarding the measurement of their long-term environmental impact and the conditions enabling effective collaboration with public and private sector actors. Full article

This study investigates the factors influencing green purchase behavior in emerging economies, focusing on Indonesian consumers’ preferences for organic food products. While sustainability awareness is growing globally, limited research has examined how environmental knowledge and trust interact with marketing efforts to shape green purchasing decisions in developing market contexts like Indonesia. The research model incorporates five constructs: environmental knowledge (awareness of ecological issues), green trust (confidence in environmental claims), green marketing mix (eco-oriented strategies for product, price, place, and promotion), green purchase intention (likelihood of buying eco-friendly products), and green purchase behavior (actual sustainable buying decisions). Data from 211 valid respondents were analyzed using structural equation modeling. The results indicate that environmental knowledge directly influences green trust and the green marketing mix but not green purchase intention or behavior. Instead, it affects behavior indirectly through trust and intention. Contrary to expectations, green trust does not influence the green marketing mix, suggesting it may operate independently of marketing strategies. Similarly, the green marketing mix does not significantly influence green purchase intention or behavior, suggesting that marketing strategies alone may be insufficient in driving sustainable consumer choices. These findings highlight the important role of environmental knowledge in fostering consumer trust and indirectly guiding green purchasing behavior in emerging markets. By promoting sustainable consumption through knowledge and trust, this study offers insights into consumer behavior as a pathway to advancing planetary health. This study advances the Theory of Planned Behavior by integrating green trust and the green marketing mix to explain how trust and economic factors shape green purchasing behavior. Practical implications suggest that businesses should adopt targeted green marketing strategies, such as educational campaigns, eco-labeling, or certifications, to enhance environmental awareness, build consumer trust, and encourage sustainable purchasing decisions. This study contributes to the literature by examining how environmental knowledge indirectly influences green purchase behavior through the mediation of trust and intention within the context of an emerging market. Full article

The island of St Lucia has undergone a dramatic transformation in a matter of decades, metamorphosing from a monocrop banana economy to a high end tourist destination which generates billions of dollars of revenue for those who operate it. This transformation has, however, seen a tourism industry develop that relies on Western models of environmental destruction and degradation. For Rastafari communities in St Lucia this represents a direct challenge to a deeply green ecological ethic which lies at the heart of the movement. Instead, some offer an alternative—eco-tourism. Several Rastafari are today engaged in offering an experience to visitors which brings them closer to this naturality rather than separating them from. To do so, however, is not without challenge. Many Rastafari seek to avoid as far as is possible all forms of engagement with a ‘Babylonian’ system that has persecuted the movement and debased all around it. For these individuals, it is only through the establishment of agrarian communes entirely separate from governmental systems and means of production that Rastafari might achieve a spirituality and a living modality free from corruption. These Rastafari eco-tourism ventures offer an alternative to this vision in presenting a different path to a shared ambition of self-sufficiency. Through ethnographic research on the island this paper seeks to situate and explore Rastafari eco-tourism as a vision for community autonomy in St Lucia. Full article

Grape stems are an abundant by-product of winemaking and a promising source of phenolic antioxidants representing an underutilized biomass within the circular economy. Seven Vitis vinifera L. cultivars were analysed by HPLC DAD, with Merlot (Me), Cabernet Sauvignon (CS) and Italian Riesling (IR) identified as the richest sources. This comparative screening provided the basis for a multi-index optimization of extraction. A 2³ full factorial design (ethanol 30–60% v/v; 30–80 min; 25–65 °C) was used for optimization. The optimal green conditions—60% ethanol, 80 min, 65 °C—yielded 1.860 mg/g CA, 1.098 mg/g Q-gluc and 0.409 mg/g Q-glc, with the Merlot stems showing the highest extraction efficiency and Merlot consistently outperforming the other varieties. Kinetic modeling using an unsteady state diffusion model showed excellent agreement (R² ≈ 0.99, RMS < 2%), suggesting a leaching-diffusion mechanism. The thermodynamic parameters confirmed an endothermic, spontaneous and irreversible process with ΔH° between 19.5 and 36.6 kJ/mol, ΔS° between 69.1 and 131.6 J/molK and ΔG° between −1.1 and −9.2 kJ/mol, depending on the compound and grape stem variety. This study shows that grape stems can be efficiently utilised as a sustainable source of phenolic antioxidants, with potential applications in the production of functional foods and dietary supplements. This integration highlights the novelty of the study and supports the valorization of grape stems in the framework of sustainability and the circular economy. Full article

With the rapid advancement of artificial intelligence (AI), its deep integration into corporate operations has become the key driver for firms to reconfigure factor resources, boost green total factor productivity, and achieve green transformation. This analysis empirically investigates the influence of AI on corporate green transformation using panel data of China’s listed companies from 2015 to 2022. This research employs a multidimensional fixed effects linear model to analyze the relationship, finding that AI significantly enhances corporate green transformation. Mechanism analysis reveals that AI promotes green transformation by enhancing firm research and development (R&D) and firm green innovation capabilities. Heterogeneity analysis shows that the positive impact of AI on corporate green transformation is more significant in the eastern region, post-COVID−19, and in low-pollution industries. The impact is also significantly and positively moderated by the development of the non-state-owned economy and the development degree of product markets. These findings suggest that AI is a critical tool for promoting sustainable economic growth and green transformation in businesses. Full article

Lignocellulosic biomass like pistachio shells (PSs) is a promising feedstock for anaerobic digestion (AD), but lignin recalcitrance limits biodegradability. Conventional pretreatments suffer from high energy costs or inhibitor formation; here, potassium ferrate (PF) + low-thermal pretreatment offers a green alternative. A Box–Behnken Design was employed to optimize the PF dosage, pretreatment temperature, and time, with response variables including the methane (CH₄) yield, soluble chemical oxygen demand (SCOD)/total chemical oxygen demand (TCOD) ratio, and lignin removal efficiency. The optimized conditions (0.637 mmol/g total solids PF dose, 66.76 °C, 55.84 min) achieved a CH₄ yield of 171.00 mL CH₄/g volatile solids, representing a 4.3-fold increase compared to untreated PSs. The ANOVA results showed strong links between how much lignin was removed, the ratio of SCOD to TCOD, and the amount of CH₄ produced, with the interactions between temperature and time being the most important. This study highlights the potential of PF-based pretreatment as a cost-effective and environmentally sustainable strategy to maximize CH₄ yields from lignocellulosic waste, supporting renewable energy adoption and circular economy principles. Further studies should explore scalability and economic feasibility for industrial applications. Full article

This study aims to address the challenge of balancing historical preservation and sustainable material selection in ancient building renovations, particularly in regions with unique climatic conditions like Hunan Province. The research proposes a hybrid model integrating Genetic Algorithm-optimized Extreme Gradient Boosting (GA-XGBoost) and Long Short-Term Memory (LSTM) networks. The GA-XGBoost component optimizes hyperparameters to predict material performance, while the LSTM network captures temporal dependencies in environmental and material degradation data. A multi-objective optimization framework is developed to simultaneously prioritize preservation integrity and green performance. The methodology is validated through a case study on an ancient architectural complex in Rucheng, Hunan Province. Key results demonstrate that the hybrid model achieves superior accuracy in material selection, with an 18–23% reduction in embodied energy (compared to conventional AHP-TOPSIS methods) and a 21.9% improvement in prediction accuracy (versus standalone XGBoost with default hyperparameters). A multi-objective optimization framework is developed to simultaneously prioritize preservation integrity and green performance, with Pareto-optimal solutions identifying material combinations that balance historical authenticity (achieving 92% substrate compatibility) with substantial sustainability gains (18–23% embodied energy reduction). The model also identifies optimal material combinations, such as lime-pozzolan mortars with rice husk ash additives, which enhance moisture buffering capacity by 28% (relative to traditional lime mortar benchmarks) while maintaining 92% compatibility with original substrates (based on ASTM C270 compatibility tests). The findings highlight the model’s effectiveness in bridging heritage conservation and modern sustainability requirements. The study contributes a scalable and interpretable framework for green material selection, offering practical implications for cultural heritage projects worldwide. Future research directions include expanding the model’s applicability to other climate zones and integrating circular economy principles for broader sustainability impact. Preliminary analysis indicates the framework’s adaptability to other climate zones through adjustment of key material property weightings. Full article

This systematic review synthesizes evidence on economic instruments that mobilize renewable-energy investment in emerging economies, analyzing 50 peer-reviewed studies published between 2015 and 2025 under PRISMA 2020. We advance an Institutional Capacity Integration Framework that ties instrument efficacy to regulatory, market, and coordination capabilities. Green bonds have mobilized roughly USD 500 billion yet work only where robust oversight and liquid markets exist, offering limited gains for decentralized access. Direct subsidies cut renewable electricity costs by 30–50% and connect 45 million people across varied contexts, but pose fiscal–sustainability risks. Carbon pricing schemes remain rare given their administrative complexity, while multilateral climate funds show moderate effectiveness (coefficients 0.3–0.8) dependent on national coordination strength. Bibliometric mapping with Bibliometrix reveals three fragmented paradigms—market efficiency, state intervention, and international cooperation—and highlights geographic gaps: sub-Saharan Africa represents just 16% of studies despite acute financing barriers. Sixty-eight percent of articles employ descriptive designs, constraining causal inference and reflecting tensions between SDG 7 (affordable energy) and SDG 13 (climate action). Our framework rejects one-size-fits-all prescriptions, recommending phased, context-aligned pathways that progressively build capacity. Policymakers should tailor instrument mixes to institutional realities, and researchers must prioritize causal methods and underrepresented regions through focused initiatives for equitable global progress. Full article

In Central Asian countries (CACs) Yes. we agree to remove Highlights part atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change (UNFCCC). At the same time, regional integration, which should be a necessary condition for achieving the Sustainable Development Goals (SDGs) in the solving of general environmental problems, is not involved. This article shows the importance of a comprehensive analysis of greenhouse gas (GHG) and non-greenhouse emissions into the atmosphere for the entire Central Asian region as a single ecosystem. The energy intensity of national economies structure was chosen as the main factor determining the level of pollution. The analysis shows that over the past 30 years, the main part of the commodity exports (73.6–81.4%) of Kazakhstan and Turkmenistan has been fossil natural resources. There is a strong economic dependence on coal and other types of fuel, which leads to atmospheric emissions. The analysis shows that limited financial resources, lack of effective systemic monitoring and control of air quality that meets modern international requirements and standards, leads to absence of tangible changes in practice yet. Over 30 years in CACs, the share of CO₂ emissions associated with fuel combustion has not decreased and amounts to 78%. The key mechanisms for reducing atmospheric emissions are significantly increase investments in the transformation of the economies in the context of regional development, interstate cooperation, the introduction of environmental norms, standards harmonized with world ones, green technologies based on alternative energy, sustainable transport and logistics infrastructure. Full article

In confronting escalating economic uncertainty, achieving a win–win situation for low-carbon transition and improved employment structure will contribute to economic recovery and sustainable growth but also contribute to building a community with a shared future for mankind. A critical issue for China’s economy and societal welfare, as well as a core component of sustainable development, concerns whether low-carbon economic transition influences employment skill structure. This study utilizes data from 30 provinces (municipalities and autonomous regions) in China from 2006 to 2021. Employing the entropy method, a low-carbon economic development level indicator system was constructed from four aspects: low-carbon output, low-carbon consumption, low-carbon resources, and low-carbon environment to measure the low-carbon economy and explore its direct and indirect effects on employment skill structure and spatial effects. The research findings indicate that low-carbon economies not only directly and significantly promote employment skill structure optimization but also indirectly generate promotional effects through pathways such as industrial structure adjustment, green innovation’s innovative effects, and factor substitution effects of increased pollution control investment. Among these, the indirect impact of industrial structure adjustment contributes most substantially. Low-carbon economies’ influence on employment skill structures exhibits spatial spillover effects, with neighboring regions’ low-carbon economies exerting positive spillover effects on local skill structures. Additionally, significant negative interdependence exists among regional employment skill structures. Based on the aforementioned research conclusions, the following recommendations are proposed: accelerate low-carbon economy development and employment skill structure enhancement in central and western regions to diminish regional disparities; encourage green innovation and promote traditional industry upgrading and transformation; formulate regional coordinated development plans, thereby strengthening the low-carbon economy’s optimizing role upon employment skills structure; and increase educational investment and strengthen labor skill training. Full article

This study examines the integration of Environmental, Social, and Governance (ESG) principles within Romania’s residential real estate sector, concentrating on Constanța, a rapidly evolving urban centre in a transitional economy. Drawing on qualitative data from semi-structured interviews with local real estate professionals and secondary analysis of policy and market documents, the research uncovers inconsistencies in ESG implementation. Environmental compliance is advancing, largely driven by EU regulations such as the European Grean Deal, the Corporate Sustainability Reporting Directive and the Energy Performance of Buildings Directive. Voluntary certification schemes like BREEAM and LEED are emerging as benchmarks for environmental performance; however, their uptake remains limited and insufficiently tailored to local conditions. Meanwhile, the social and governance dimensions lag behind, characterised by inconsistent application and weak institutional backing. Key barriers to effective ESG integration in Romania’s residential real estate sector include weak regulatory enforcement, fragmented policies, limited green finance, low awareness, and a lack of standardised social value metrics. The study concludes that without moving beyond mere regulatory compliance to a framework embedding social inclusivity and adaptive governance, ESG efforts risk perpetuating existing inequalities. It calls for a reconceptualisation of ESG frameworks, developed for mature markets, to better suit transitional urban contexts and support long-term resilience in residential real estate. Full article