Search Results (6,502)

South Africa’s manufacturing sector, a driving force for sustainable development, faces a profound challenge in decarbonizing without deindustrializing. This study provides an optimized, scenario-based assessment of the sector explicitly aligned with its Just Energy Transition Partnership (JETP) objectives. A novel framework is applied, integrating an extended Kaya–Logarithmic Mean Divisia Index (Kaya–LMDI) decomposition with scenario forecasting and Genetic Algorithm (GA) optimization. The decomposition disaggregates a conventional carbon intensity (CI) driver to include Electrification Share (ELE), Renewable Share (REN), and a newly defined Residual Carbon Factor (RCF) that captures direct fossil fuel use for industrial process heat. Historical analysis (2002–2022) shows that emissions growth was primarily driven by the RCF (224.1 MtCO₂, 160%) and Economic Activity (187.5 MtCO₂, 134%), partly offset by gains in Energy Intensity (−141.8 MtCO₂, 101.35%) and REN (−202.2 MtCO₂, −144.53%). Carbon emissions projections to 2040 reveal a critical sustainability trilemma: the Just Transition accelerated scenario (JTAS), despite achieving rapid renewable deployment, increases emissions by 469% as economic growth overwhelms decarbonization efforts. Conversely, the mathematically optimal (GA) pathway achieves a 90.8% reduction but only through structural contraction that implies socially unsustainable deindustrialization. This tension exposes the systemic limits of incremental decarbonization and underscores that a truly sustainable pathway requires transcending this binary choice by directly addressing the fossil fuel substrate of industrial production. Full article

Transit-Oriented Development (TOD), formalized by Calthorpe and Poticha in 1993, emerged to counter urban sprawl, reduce car dependency, and revitalize historical community centers. Rooted in “new urbanism”, TOD emphasizes integrated regional land-use planning and high-capacity public transportation. In the Middle East, TOD implementation remains understudied, particularly regarding heritage integration and social equity in arid climates. Doha’s rapid social and economic transformation presents both opportunities and risks: growth offers urban revitalization yet threatens to displace communities and dilute cultural identity. Shifts in urban planning have aimed to address sustainability, connectivity, and heritage preservation. This study examines Msheireb Downtown Doha (MDD) to assess how TOD can restore historic districts while managing gentrification, enhancing accessibility and promoting inclusiveness. A mixed-methods approach was applied, including 12 semi-structured interviews with stakeholders (Qatar Rail, Msheireb Properties, Ministry of Municipality and Environment), purposive surveys of 80 urban users, site observations, and spatial mapping. Using the Node-Place-People (NPP) model, the study evaluates TOD effectiveness across transportation connectivity (node), built environment quality (place), and equity metrics (people). The findings show that MDD successfully implements fundamental TOD principles through its design, which enhances connectivity, walkability, social inclusiveness, and heritage preservation. However, multiple obstacles remain: the “peripheral island effect” limits benefits to the core, pedestrian–vehicular balance is unresolved, and commercial gentrification is on the rise. This research provides evidence-based knowledge for GCC cities pursuing sustainable urban regeneration by demonstrating both the advantages of TOD and the necessity for critical, context-sensitive implementation that focuses on social equity together with physical transformation. Full article

The concept of sustainable development has emerged as a global consensus, forged in response to environmental constraints and critical reflection on conventional growth-oriented paradigms. It now serves as the overarching framework for addressing climate, ecological, and socio-economic crises. In the period after the adoption of the Sustainable Development Goals (SDGs) in 2016, there was an observable trend of increased integration of these objectives into the strategic frameworks of national and subnational entities. However, global assessments have indicated a divergence between the progress achieved and the trajectory delineated by the SDGs. The Earth system is demonstrating signs of decreased resilience, with widening inequalities and the emergence of multiple crises, thereby hindering the implementation of the 2030 Agenda for Sustainable Development. As the 2030 deadline approaches, a fundamental question arises for global development governance: what should be the future of the SDGs beyond 2030? While insufficient progress has prompted debates over the adequacy of the SDG framework, fundamentally revising or replacing the SDGs would risk undermining a hard-won international consensus forged through decades of negotiation and institutional investment. Based on a comprehensive review of the historical evolution of the sustainable development concept, this study argues that the SDGs represent a rare and fragile achievement in global governance. While insufficient progress has sparked debates about their effectiveness, fundamentally revising or replacing the SDGs would jeopardize the hard-won international consensus forged through decades of negotiations and institutional investments. This study further analyzes the latest progress on the SDGs and identifies emerging risks, aiming to explore how to accelerate and optimize sustainable development pathways within the existing SDG framework rather than propose a new global goal system. Based on both global experience and practice in China, four interconnected strategic priorities—namely, economic reform, social equity, environmental justice, and technology sharing—are proposed as a comprehensive framework to accelerate SDG implementation and guide the transformation of development pathways towards a more just, low-carbon, and resilient future. Full article

Recognizing the evolution of landscape patterns in the Chishui River source region is essential for protecting ecosystems and sustainable growth in the Yangtze River Basin and other similar areas. However, knowledge of landscape pattern evolution within the primary channel zone remains insufficient. To address this gap, the current study used 2000–2020 land-use, geography, and socio-economic data, integrating landscape pattern indices, land-use transfer matrices, dynamic degree, the GeoDetector model, and the PLUS model. Results revealed that forest and cropland remained the prevailing land-use types throughout 2000–2020, comprising over 85% of the landscape. Grassland had the highest dynamic degree (1.58%), and landscape evolution during the study period was characterized by increased fragmentation, enhanced diversity, and stable dominance of major forms of land use. Anthropogenic influence on different landscape types followed the order: construction land > cropland > grassland > forest > water bodies. Land-use change in this region is a complex process governed by the interrelationships among various factors. Scenario-based predictions demonstrate pronounced variability in various land types. These findings provided a more comprehensive understanding of landscape patterns in karst river source regions, provided evidence-based support for regional planning, and offered guidance for ecological management of similar global river sources. Full article

Technological innovation plays a vital role in enhancing the economic growth and sustainability of the forestry sector. However, research on the nature, dynamics, and impact of such innovations, particularly within small and medium-sized enterprises (SMEs), remains limited. The forestry sector is often characterised by low levels of technological advancement and a traditionally conservative attitude toward change. Limited expertise, financial constraints, and ownership structures further influence the potential for innovation. This study examines the development of innovation among SMEs in Lithuania’s forestry sector and its contribution to sustainable forest management. Forestry innovations are understood as new processes, products, or services introduced by forest owners and managers to improve management efficiency and sustainability. The study employed the method of a structured questionnaire survey to evaluate technological, organisational, and financial aspects of innovation adoption among small and medium-sized enterprises in the forestry sector. Drawing on comparative survey data from 2005 and 2024, the study analyses the types of innovations implemented by forestry enterprises, the factors driving or hindering their adoption, and the evolving trends in innovation application. The results reveal a significant shift toward digitalisation and technology-based management practices, suggesting that Lithuanian forestry enterprises are gradually transitioning toward a more innovation-driven model. These developments appear to be influenced by the EU Green Deal policy framework, evolving innovation support mechanisms, and broader socio-economic changes. Nonetheless, technological transformation introduces new challenges, including the need for workforce upskilling and enhanced adaptability to rapidly changing market conditions. Full article

The successful attainment of the Sustainable Development Goals (SDGs) necessitates robust monitoring frameworks capable of tracking progress toward tangible outcomes while capturing dynamic sustainability trajectories. However, existing SDG evaluation methods suffer from three critical limitations: (1) misalignment between global targets and national priorities, which undermines contextual relevance; (2) fragmented assessments that neglect holistic integration of social, economic, and ecological dimensions, thereby obscuring systemic interdependencies; and (3) insufficient longitudinal analysis, which restricts insights into temporal patterns of sustainable development and hinders adaptive policymaking. To address these gaps, we employed China’s 31 provinces as a case study and constructed an SDG indicator framework comprising 178 metrics—harmonizing global SDG benchmarks with China’s national development priorities. Using official statistics and open-source data spanning 2006–2021, we evaluate longitudinal SDG scores for all 17 goals (SDGs 1–17). Additionally, we developed a composite SDG index that considers the coupling coordination degree of the social–economic–ecological system and evaluated the index value under different economic region settings. Finally, we developed a two-threshold model to analyze the dynamic evolution of SDG conditions, incorporating temporal sustainability (long-term development resilience) and action urgency (short-term policy intervention needs) as dual evaluation dimensions. This model was applied to conduct a longitudinal analysis (2006–2021) across all 31 Chinese provinces, enabling a granular assessment of regional SDG trajectories while capturing both systemic trends and acute challenges over time. The results indicate that China’s social SDG performance improved substantially over the 2006–2021 period, achieving a cumulative increase of 126.53%, whereas progress in ecological SDGs was comparatively modest, with a cumulative growth of only 23.93%. Over the same period, the average composite SDG score across China’s 31 provinces increased markedly from 0.502 to 0.714, reflecting a strengthened systemic alignment between regional development trajectories and national sustainability objectives. Further analysis shows that all provinces attained a status of “temporal sustainability with low action urgency” throughout the study period, highlighting China’s overall progress in sustainable development. Nevertheless, pronounced regional disparities persist: eastern provinces developed earlier and have consistently maintained leading positions; central and northeastern regions exhibit broadly comparable development levels; and western regions, despite severe early-stage lagging, have demonstrated accelerated growth in later years. Our study holds substantial significance by integrating multi-dimensional indicators—spanning ecological, economic, and social dimensions—to deliver a holistic, longitudinal perspective on sustainable development. Full article

This study investigates whether national innovation systems contribute to sustainable well-being in emerging EU Member States by examining the long-run relationship between innovation performance and a multidimensional Quality of Life Index (QoLI). Using a balanced panel covering 2013–2024 for ten countries, the analysis integrates the Global Innovation Index, economic development dynamics, and demographic pressure to assess whether innovation-led progress translates into broad societal benefits. Panel cointegration tests confirm a stable long-run equilibrium among variables, while FMOLS estimation reveals three key results: (i) While the bivariate Pearson correlation indicates a positive association between innovation capacity and quality of life, the multivariate FMOLS estimation reveals a statistically significant negative long-run effect of innovation performance on QoLI, once economic development and demographic pressures are jointly controlled for. (ii) Economic development contributes positively to sustainable well-being, reinforcing the role of income-driven improvements in living conditions, and (iii) population size exerts a strong negative effect, reflecting demographic stress and unequal access to essential services. The findings indicate an innovation–well-being gap in which technological progress advances faster than the institutional and social mechanisms needed to ensure equitable diffusion. These results underscore the need to reorient innovation strategies toward inclusive growth, social accessibility, and environmental resilience so that innovation systems can effectively support sustainable well-being in emerging European economies. Full article

This study aimed to analyze the impact of the digital economy and artificial intelligence (AI) on GDP growth in 10 developed and developing countries during the period 2010–2024. It was based on the hypothesis that increased digitalization and AI investments promote sustainable economic growth by improving national productivity and efficiency, in accordance with modern technological growth theory, which links digital innovation to economic development. The study used tablet data comprising 150 observations, which were analyzed using fixed- and random-effects models, controlling for traditional variables such as employment, human capital, and investment. The results showed that the Digitalization Indicators (DIGI) had a significant positive impact on growth (fixed: 0.003479, p < 0.01; random: 0.003325, p < 0.01), and that investment in AI also had a significant positive impact (fixed: 0.063695, p < 0.05; random: 0.066548, p < 0.05). In contrast, workforce size had a limited impact, while education and human capital emerged as key drivers of sustainable growth (Constant: 0.003257, p < 0.01; Random: 0.003264, p < 0.01). The inclusion of dummy variables further differentiated between developed and developing countries in the random-effects model, reinforcing the economic interpretation of the findings. The study suggests that integrating digitalization, education, and investment in artificial intelligence is an effective strategy for promoting sustainable economic growth, while emphasizing the importance of workforce skills development to maximize its impact. Full article

Sustainability has become a central concern globally, and efforts to enhance it are being made across various fields. In line with this trend, corporate sustainability reports have become more widely published. These reports provide both financial and non-financial information on a company’s sustainability. In this context, this study aims to, first, analyze the key keywords contained in CEO messages. Second, it examines whether the keywords emphasized by CEOs change in response to shifts in corporate risk under economic uncertainty. Finally, it identifies how the categories of words included in these messages are classified. To address these research questions, text analysis was selected as the methodology. Specifically, a qualitative research approach using text mining and CONCOR analysis was conducted on the text from sustainability report. According to the Term Frequency and Term Frequency-Inverse Document Frequency analyses, the most frequently occurring keywords were ESG, Sustainable, Society, Stakeholders, Growth, Environment, Effort, and Future. Centrality analysis identified the following keywords as having high centrality: Sustainable, ESG, Society, Environment, Growth, Effort, and Stakeholders. Finally, CONCOR analysis revealed four clusters: Eco-friendly Energy, ESG Management, Global Crisis, and Technological Competitiveness. This study is significant in that it analyzes the major keywords and their changes within unstructured text data using text mining and CONCOR analysis, and it suggests the possibility of future quantitative analysis of non-financial information using these keywords. Full article

Agriculture in the European Union operates in a context where productivity, output growth, and sustainability increasingly shape policy priorities and economic choices. This research explores how these elements have interacted and influenced one another from 2000 to 2024, focusing on the dynamic relationships among economic performance, sustainability, labor productivity, and agricultural output across EU member states. The methodology is straightforward: it starts with factor analysis to uncover the fundamental structures linking key variables and to clarify connections that are often hidden in aggregated data. Building on these insights, a General Linear Model provides a clearer picture of how economic performance and sustainability affect changes in labor productivity and agricultural output, revealing the mechanisms through which these factors promote or hinder agricultural progress. To enhance understanding, cluster analysis groups EU countries according to shared patterns, enabling interpretation of national differences within broader structural trends rather than as isolated cases. The findings show that countries with stronger economies and more consistent sustainability initiatives tend to achieve higher productivity and output, while the clusters identified demonstrate significant differences that explain the diverse development paths within the Union. Full article

Two genetically engineered Bacillus subtilis strains, BMV9 and BsB6, were evaluated in terms of culture medium (effect of nutrients on surfactin yield) and potential biotechnological applications of surfactin in agriculture and the petrochemical industry. BMV9 (spo0A3; abrB*; ΔmanPA; sfp+) is, to date, the highest surfactin producer reported scientifically, and BsB6 is a sfp+ laboratory derivative strain that has also demonstrated considerable production potential. To assess their performance, fermentation experiments were conducted in shake flasks using two different culture media, a mineral salt medium and a complex medium, each supplemented with 2% (w/v) glucose. Lipopeptides (surfactin and fengycin) were extracted and quantified at multiple time points (up to 48 h) via high-performance thin-layer chromatography (HPTLC). Optical density, residual glucose, and pH were monitored throughout the cultivation. In parallel, microbial growth in both media were also validated in small-scale cultivation approaches. Antifungal activity of culture supernatants and lipopeptide extracts was tested against two Diaporthe species, key phytopathogens in soybean crops. Given the agricultural relevance of these pathogens, the biocontrol potential of lipopeptides represents a sustainable alternative to conventional chemical fungicides. Additionally, oil displacement tests were performed to evaluate the efficacy of surfactin in enhanced oil recovery (EOR), bioremediation, and related petrochemical processes. High-resolution LC-MS/MS analysis enabled structural characterization and relative quantification of the lipopeptides. Overall, these investigations provide a comprehensive comparison of strain production performance and the associated impact of cultivation media, aiming to define the optimal conditions for economically viable surfactin production and to explore its broader biotechnological applications in agriculture and the petrochemical industry. Full article

Driven by the energy transition within the framework of the United Nations Framework Convention on Climate Change, second-generation (2G) ethanol stands out as a technical and sustainable alternative to fossil fuels. Although first-generation ethanol, produced from saccharine and starchy feedstocks, represents an advance in mitigating emissions, its expansion is limited by competition with areas destined for food production. In this context, 2G ethanol, obtained from residual lignocellulosic biomass, emerges as a strategic route for diversifying and expanding the renewable energy matrix. Thus, this work discusses the current state of 2G ethanol technology based on the gradual growth in production and the consolidation of this route over the last few years. Industrial second-generation ethanol plants operating around the world demonstrate the high potential of agricultural waste as a raw material, particularly corn straw in the United States, which offers a lower cost and significant yield in the production of this biofuel. Similarly, in Brazil, sugarcane by-products, especially bagasse and straw, are consolidating as the main sources for 2G ethanol, integrated into the biorefinery concept and the valorization of by-products obtained during the 2G ethanol production process. However, despite the wide availability of lignocellulosic biomass and its high productive potential, the consolidation of 2G ethanol is still conditioned by technical and economic challenges, especially the high costs associated with pretreatment stages and enzymatic cocktails, as well as the formation of inhibitory compounds that compromise the efficiency of the process. Genetic engineering plays a particularly important role in the development of microorganisms to produce more efficient enzymatic cocktails and to ferment hexoses and pentoses (C₆ and C₅ sugars) into ethanol. In this scenario, not only are technological limitations important but also public policies and tax incentives, combined with the integration of the biorefinery concept and the valorization of (by)products, which prove fundamental to reducing costs, increasing process efficiency, and ensuring the economic viability and sustainability of second-generation ethanol. Full article

Globally, human capital is recognized as a structural determinant of economic growth, with evidence of a positive, bidirectional, and significant relationship between both variables. However, in Colombia, few studies have directly measured the influence of human capital on national economic growth. To date, there is no academic review that integrates and analyzes the available evidence on this link, even though such studies are fundamental for understanding the drivers of development, reducing structural inequalities, and guiding policies that promote productivity and social inclusion. This study conducted a literature review across major international and Colombian academic databases, with a specific focus on Colombia and a minimum 25-year observation window, to identify research gaps and establish conceptual foundations for future research. In total, 140 articles were reviewed. In general terms, the findings show that, although human capital is an essential driver of Colombia’s economic growth, its full impact is constrained by structural and regional inequalities, corruption, violence, labor informality, institutional fragmentation, and mismatches between education and labor market demands. These results underscore the need to expand empirical research to better measure its effects and to inform more inclusive and sustainable development policies. Full article

Despite growing research on sustainable aviation, multi-airport systems, and environmentally constrained capacity allocation, critical gaps persist. Existing studies often treat passenger choice, airline competition, and airport regulation in isolation, or evaluate environmental policies such as carbon taxation only as macro-level constraints. Consequently, the endogenous feedback among pricing, capacity reallocation, and regulatory intervention in shaping equilibrium outcomes within multi-airport systems remains underexplored, particularly within a unified dynamic framework that links low-carbon policies to operational decision-making. This study develops such a dynamic framework to support the sustainable transition of carbon-constrained multi-airport regions. Focusing on the Beijing–Tianjin multi-airport system and China’s “Dual Carbon” goals, we construct a three-layer iterative equilibrium game integrating passenger airport choice (modeled using a multinomial logit specification), airline capacity reallocation (formulated as an evolutionary game internalizing carbon taxes), and airport slot regulation (implemented through a multi-objective mechanism balancing economic revenue, hub connectivity, and environmental performance). An agent-based simulation of the Beijing/Tianjin–Nanchang route demonstrates robust convergence to a stable systemic equilibrium. Intensified competition reduces fares and improves accessibility, while capacity shifts from higher-cost Beijing airports to Tianjin Binhai Airport, whose market share rises from 10.6% to 34.0%. Airport utilization becomes more balanced, total airline profits increase slightly, and both total and per-passenger CO₂ emissions decline, indicating improved carbon efficiency despite demand growth. The results further identify a range of carbon-tax levels that jointly promote emission reduction and traffic rebalancing with limited profit loss. Full article

Ports are the major gateways of cities. Background: Sustainable growth requires ports to prioritize efficiency while balancing economic, social, and environmental goals. There is limited synthesized evidence on the sustainability evaluation of ports, including those of North America. In this paper, we propose a multi-step approach based on fuzzy DEA to evaluate the environmental performance of ports. Methods: In the first step, we identify indicators for environmental performance evaluation. The second step involves application of fuzzy DEA using the identified indicators to measure the environmental efficiency of ports. In the third step, a numerical illustration is provided using open data. The proposed model incorporates undesirable outputs and employs one set of constraints to make a production frontier. Results: The findings show wide differences in performance, ports reach higher scores when they use resources wisely plus keep emissions low, not merely when they expand. Conclusions: The proposed methodology provides a robust and comparable measurement of port environmental efficiency under uncertainty. Full article