Search Results (2,274)

Over the past 30 years, the City of Portland, Oregon, USA, has emerged as a national leader in green stormwater infrastructure (GSI). The initial impetus for implementing sustainable stormwater infrastructure in Portland stemmed from concerns about flooding and water quality in the city’s two major rivers, the Columbia and the Willamette. Heavy rainfall often led to combined sewer overflows, significantly polluting these waterways. A partial solution was the construction of “The Big Pipe” project, a large-scale stormwater containment system designed to filter and regulate overflow. However, Portland has taken a more comprehensive and long-term approach by integrating sustainable stormwater management into urban planning. Over the past three decades, the city has successfully implemented GSI to mitigate these challenges. Low-impact development strategies, such as bioswales, green streets, and permeable surfaces, have been widely adopted in streetscapes, pathways, and parking areas, enhancing both environmental resilience and urban livability. This perspective highlights the history of the implementation of Portland’s GSI programs, current design and performance standards, and challenges and lessons learned throughout Portland’s recent history. Innovative approaches to managing runoff have not only improved stormwater control but also enhanced green spaces and contributed to the city’s overall climate resilience while addressing economic well-being and social equity. Portland’s success is a result of strong policy support, effective integration of green and gray infrastructure, and active community involvement. As climate change intensifies, cities need holistic, adaptive, and community-centered approaches to urban stormwater management. Portland’s experience offers valuable insights for cities seeking to expand their GSI amid growing concerns about climate resilience, equity, and aging infrastructure. Full article

With the growth of the global population and the increasing scarcity of arable land, traditional agricultural production is confronted with multiple challenges, such as efficiency improvement, precision operation, and sustainable development. The progressive advancement of artificial intelligence (AI) technology has created a transformative opportunity for the intelligent upgrade of agricultural equipment. This article systematically presents recent progress in computer vision, machine learning (ML), and intelligent sensing. The key innovations are highlighted in areas such as object detection and recognition (e.g., a K-nearest neighbor (KNN) achieved 98% accuracy in distinguishing vibration signals across operation stages); autonomous navigation and path planning (e.g., a deep reinforcement learning (DRL)-optimized task planner for multi-arm harvesting robots reduced execution time by 10.7%); state perception (e.g., a multilayer perceptron (MLP) yielded 96.9% accuracy in plug seedling health classification); and precision control (e.g., an intelligent multi-module coordinated control system achieved a transplanting efficiency of 5000 plants/h). The findings reveal a deep integration of AI models with multimodal perception technologies, significantly improving the operational efficiency, resource utilization, and environmental adaptability of agricultural equipment. This integration is catalyzing the transition toward intelligent, automated, and sustainable agricultural systems. Nevertheless, intelligent agricultural equipment still faces technical challenges regarding data sample acquisition, adaptation to complex field environments, and the coordination between algorithms and hardware. Looking ahead, the convergence of digital twin (DT) technology, edge computing, and big data-driven collaborative optimization is expected to become the core of next-generation intelligent agricultural systems. These technologies have the potential to overcome current limitations in perception and decision-making, ultimately enabling intelligent management and autonomous decision-making across the entire agricultural production chain. This article aims to provide a comprehensive foundation for advancing agricultural modernization and supporting green, sustainable development. Full article

We investigate whether China’s Value-Added Tax (VAT) Credit Refund policy influences firms’ sustainable development capability (SDC), which reflects innovation-driven growth and green development. Exploiting the 2018 implementation of the VAT Credit Refund policy as a quasi-natural experiment, we employ a difference-in-differences (DID) approach and find causal evidence that the policy significantly enhances firms’ SDC. This suggests that fiscal instruments like VAT refunds are valued by firms as drivers of long-term sustainable and high-quality development. Our mediating analyses further reveal that the policy promotes firms’ SDC by strengthening artificial intelligence (AI) capabilities and facilitating intelligent transformation. This mechanism “AI Capability Building—Intelligent Transformation” aligns with the socio-technical systems theory (STST), highlighting the interactive evolution of technological and social subsystems in shaping firm capabilities. The heterogeneity analyses indicate that the positive effect of VAT Credit Refund policy on SDC is more pronounced among small-scale and non-high-tech firms, firms with lower perceived economic policy uncertainty, higher operational diversification, lower reputational capital, and those located in regions with a higher level of marketization. We also find that the policy has persistent long-term effects, with improved SDC associated with enhanced ESG performance and green innovation outcomes. Our findings have important implications for understanding the SDC through the lens of STST and offer policy insights for deepening VAT reform and promoting intelligent and green transformation in China’s enterprises. Full article

In the context of both domestic and international economic landscapes, regional policy has emerged as an increasingly influential factor shaping the developmental trajectories of Chinese enterprises. Despite its growing significance, the extant literature lacks a comprehensive and systematically visualized synthesis that encapsulates the scope and trends of research in this domain. This study addresses this critical gap by conducting an integrative bibliometric and qualitative review of the academic output related to regional policy and Chinese firm growth. Drawing on a final dataset comprising 3428 validated academic publications—selected from an initial pool of 3604 records retrieved from the Web of Science Core Collection between 1991 and 2022, the research employs a two-stage methodological framework. In the first phase, advanced bibliometric tools, and software applications, including RStudio, Bibliometrix, VOSviewer, and CitNetExplorer, are utilized to implement techniques such as keyword co-occurrence analysis, thematic clustering, and the tracing of thematic evolution over time. These methods facilitate rigorous data cleansing, breakpoint identification, and the visualization of intellectual structures and emerging research patterns. In the second phase, a targeted qualitative review is conducted to evaluate the influence of regional policies on Chinese firms across three critical stages of business development: start-up, expansion, and maturity. The findings reveal that regional policy interventions generally exert a positive influence on firm performance throughout all stages of development. Notably, a significant concentration of citation activity occurred prior to 2017; however, post-2017, the volume of scholarly publications, journal-level impact (as measured by h-index), and author-level influence experienced a marked increase. Among the 3428 analyzed publications, a substantial portion—2259 articles—originated from Chinese academic institutions, highlighting the strong domestic research interest in the subject. Furthermore, since 2015, there has been a discernible shift in keyword co-occurrence trends, with increasing scholarly attention directed towards sustainable development issues, particularly those related to carbon dioxide emissions and green innovation, reflecting evolving policy priorities and environmental imperatives. Full article

China has identified the high-quality development of its green manufacturing transition as the top priority for upgrading their industrial structure system which will lead to the sustainable development of an innovation ecosystem. To assess their progress in this area, this study selects the panel data of 31 provinces in China from 2011 to 2021 and constructs an evaluation index system for the green transformation of the manufacturing industry from four dimensions: environment, resources, economy, and industrial structure. This not only comprehensively and systematically reflects the dynamic changes in the green transformation of the manufacturing industry but also addresses the limitations of currently used indices. The entropy value method is used to calculate the comprehensive score of the green transformation of the manufacturing industry, while the key factors influencing the convergence of the green transformation of the manufacturing industry are further explored. The results show that first, the overall level of the green transformation of the manufacturing industry has significantly improved as evidenced by an approximate 32% increase. Second, regional differences are significant with the eastern region experiencing significantly higher levels of transformation compared to the central and western regions, along with a decreasing trend from the east to the central and western regions. From a policy perspective, the findings suggest that tailored production methods for each region should be adopted with a greater emphasis on knowledge exchanges to promote green transition in less developed regions. In addition, further regulations are required which, in part, focus on increasing the degree of openness to the outside world to promote the level of green manufacturing transition. Full article

The successful deployment of sustainable building construction (SBC) is connected to sound knowledge sharing. Concerning SBC, knowledge sharing has been identified to directly and indirectly increase innovation, environmental performance, cost saving, regulatory compliance awareness and so on. The necessity of enhancing SBC practice globally has been emphasised by earlier research. Consequently, this study aims to investigate knowledge-sharing elements to enhance SBC in South Africa (SA). Utilising a questionnaire survey, this study elicited data from 281 professionals in the built environment. Data analysis was performed with “descriptive statistics”, the “Kruskal–Wallis H-test”, and “principal component analysis” to determine the principal knowledge-sharing features (KSFs). This study found that “creating public awareness of sustainable practices”, the “content of SBC training, raising awareness of green building products”, “SBC integration in professional certifications”, an “information hub or repository for sustainable construction”, and “mentoring younger professionals in sustainable practices” are the most critical KSFs for SBC deployment. These formed a central cluster, the Green Education Initiative and Eco-Awareness Alliance. The results achieved a reliability test value of 0.956. It was concluded that to embrace the full adoption of SBC, corporate involvement is critical, and all stakeholders must embrace the sustainability paradigm. It is recommended that the principal knowledge-sharing features revealed in this study should be carefully considered to help construction stakeholders in fostering knowledge sharing for a sustainable built environment. Full article

Avocado (Persea americana), originally from Mesoamerica, has emerged as a focus of intense scientific and industrial interest due to its unique combination of nutritional richness, bioactive potential, and technological versatility. Its pulp, widely consumed across the globe, is notably abundant in monounsaturated fatty acids, especially oleic acid, which can comprise over two-thirds of its lipid content. In addition, it provides significant levels of dietary fiber, fat-soluble vitamins such as A, D, E and K, carotenoids, tocopherols, and phytosterols like β-sitosterol. These constituents are consistently associated with antioxidant, anti-inflammatory, glycemic regulatory, and cardioprotective effects, supported by a growing body of experimental and clinical evidence. This review offers a comprehensive and critical synthesis of the chemical composition and functional properties of avocado, with particular emphasis on its lipid profile, phenolic compounds, and phytosterols. It also explores recent advances in environmentally sustainable extraction techniques, including ultrasound-assisted and microwave-assisted processes, as well as the application of natural deep eutectic solvents. These technologies have demonstrated improved efficiency in recovering bioactives while aligning with the principles of green chemistry. The use of avocado-derived ingredients in nanostructured delivery systems and their incorporation into functional foods, cosmetics, and health-promoting formulations is discussed in detail. Additionally, the potential of native cultivars and the application of precision nutrition strategies are identified as promising avenues for future innovation. Taken together, the findings underscore the avocado’s relevance as a high-value matrix for sustainable development. Future research should focus on optimizing extraction protocols, clarifying pharmacokinetic behavior, and ensuring long-term safety in diverse applications. Full article

In recent years, growing concerns over environmental degradation and deepening awareness of the necessity of sustainable development have propelled green and low-carbon energy transition into a focal issue for both academia and policymakers. By decomposing energy transition into the transformation of energy structure and the upgrading of energy efficiency, this study investigates the impact and mechanisms of green finance on energy transition across 30 provinces (municipalities and autonomous regions) in China, with the exception of Tibet. In addition, the impact of climate change is incorporated into the analytical framework. Empirical results demonstrate that green finance development significantly accelerates energy transition, a conclusion robust to rigorous validation. Analysis of the mechanism shows that green finance promotes energy transition through the facilitation of technological innovation and the upgrade of industrial structures. Moreover, empirical evidence reveals that climate change undermines the promotional influence of sustainable finance on energy system transformation. The magnitude of this suppression varies nonlinearly across provincial jurisdictions with differing energy transition progress. Regional heterogeneity analyses further uncover marked discrepancies in climate–finance interactions, demonstrating amplified effects in coastal economic hubs, underdeveloped western provinces, and regions with mature eco-financial markets. According to these findings, actionable policy suggestions are put forward to strengthen green finance and accelerate energy transition. Full article

With the increasing global emphasis on sustainable development goals, and in the context of pursuing high-quality sustainable development of the economy and enterprises, this study empirically examines the effect of digital finance on corporate financing constraints and the impact on corporate green innovation with a sample of China’s A-share-listed companies in the period of 2011–2020 and explores the issue from the perspectives of management power and corporate social responsibility (CSR) at the micro level of enterprises. The empirical results show that digital finance can indeed alleviate corporate financing constraints. Still, the synergistic effect of the two on corporate green innovation produces a “quantitative and qualitative separation” effect, which only promotes the enhancement of iconic green innovation, and the effect on substantive green innovation is not obvious. The power of management and CSR performanceshave different moderating roles in the alleviation of financing constraints by the empowerment of digital finance. Management power and corporate social responsibility have different moderating effects on digital financial empowerment to alleviate financing constraints. The findings of this study enrich the research in related fields and provide more basis for the promotion of digital financial policies and more solutions for the high-quality development of enterprises. Full article

In response to global sustainability challenges and digital transformation, this conceptual paper explores the intersection of Artificial Intelligence (AI), Human Resource Management (HRM), and Circular Economy (CE). Drawing on Resource-Based View, Stakeholder Theory, Institutional Theory, and the Socio-Technical Systems perspective, we propose an integrated framework in which AI and HRM function as complementary enablers of sustainable, circular transformation. The framework identifies enablers (e.g., green HRM, digital infrastructure), barriers (e.g., ethical concerns, skill gaps), and contextual mediators. This study contributes to sustainability and digital innovation literature and suggests practical pathways for ethically aligning workforce and AI capabilities in CE adoption. Full article

As a critical external mechanism driving green innovation, institutional and competitive pressure often coexist and jointly shape firms’ strategic responses. However, existing studies primarily focus on the individual effects of these pressures, with limited attention to their interactive impacts on green innovation. Drawing on optimal distinctiveness theory, this study proposes a “pressure–response” analytical framework that classifies institutional and competitive pressure combinations into congruent (i.e., high–high or low–low) and incongruent (i.e., high–low or low–high) pressure contexts based on their relative intensities. It further examines how these distinct configurations affect two types of green innovation: strategic green innovation (StrGI) and substantive green innovation (SubGI). Using panel data from Chinese A-share listed firms between 2010 and 2022, the empirical results reveal that under congruent pressure contexts, the alignment of institutional and competitive pressures tends to suppress green innovation. In contrast, under incongruent contexts, the misalignment between the two pressures significantly promotes green innovation. Regarding innovation motivation, the high institutional–low competitive pressure context more significantly promotes StrGI, while the low institutional–high competitive pressure context has a more prominent effect on SubGI. In addition, this study also investigates the mediating roles of StrGI and SubGI on ESG performance. The findings provide theoretical support and policy implications for improving green transition policies and institutional frameworks, as well as promoting sustainable corporate development. Full article

Green innovation is a critical driver of sustainable development, yet it often faces efficiency challenges in rapidly industrializing economies. This study investigates the effect of China’s Circular Economy Demonstration Policy (CEDP) on urban green innovation efficiency (GIE) using city-level panel data from 2010 to 2021. Employing a difference-in-differences (DID) approach, we find that CEDP significantly enhances GIE, with the policy effect becoming statistically significant after a three-year lag and accumulating over time. Robustness tests, including placebo analyses, alternative dependent variables, and propensity score matching, confirm the validity of the results. Mechanism analysis reveals that the policy improves green innovation primarily by reducing capital distortion, promoting market integration, and enhancing resource allocation efficiency. Further heterogeneity analyses show that the positive effects are stronger in central cities, capital cities, and eastern regions, reflecting the role of local economic and institutional conditions. The study concludes with policy implications emphasizing regionally tailored implementation, capacity building, and long-term commitment to maximize green innovation outcomes. Full article

In the rock–soil–biology–water ecosystem, rock weathering provides essential plant nutrients. However, its supply is insufficient for rising crop demands under population growth and climate change, while excessive fertilizer causes soil degradation and pollution. This study innovatively irrigated with carbonate rock leachates to enhance soil nutrient availability. A pot experiment with lettuce showed that irrigation significantly increased soil NO₃⁻-N (+102.20%), available K (+16.45%), available P (+17.95%), Ca (+6.04%), Mg (+11.65%), and Fe (+11.60%), and elevated the relative abundance of Firmicutes. Lettuce biomass per plant rose by 23.78%, with higher leaf minerals (P, K, Ca, and Mg) and antioxidants (carotenoids and ascorbic acid). A field experiment further confirmed improvement of soil nutrient availability and peanut yield. This carbonate rock leachate irrigation technique effectively enhances soil quality and crop productivity/quality, offering a sustainable approach for green agriculture. Full article

This study aims to enhance the performance of an innovative steel slag–ceramsite foam concrete (SSCFC) to advance sustainable green building materials. An eco-friendly composite construction material was developed by integrating industrial by-product steel slag (SS) with lightweight ceramsite. Employing a three-factor, three-level orthogonal experimental design at a fixed density of 800 kg/m³, 12 mix proportions (including a control group) were investigated with the variables of water-to-cement (W/C) ratio, steel slag replacement ratio, and ceramsite replacement ratio. The governing mechanisms of the W/C ratio, steel slag replacement level, and ceramsite replacement proportion on the SSCFC’s fluidity and compressive strength (CS) were elucidated. The synergistic application of range analysis and analysis of variance (ANOVA) quantified the significance of factors on target properties, and partial least squares regression (PLSR)-based prediction models were established. The test results indicated the following significance hierarchy: steel slag replacement > W/C ratio > ceramsite replacement for fluidity. In contrast, W/C ratio > ceramsite replacement > steel slag replacement governed the compressive strength. Verification showed R² values exceeding 65% for both fluidity and CS predictions versus experimental data, confirming model reliability. Multi-criteria optimization yielded optimal compressive performance and suitable fluidity at a W/C ratio of 0.4, 10% steel slag replacement, and 25% ceramsite replacement. Full article

China’s economy is shifting from an era of rapid expansion to one focused on high-quality development, making it imperative to tackle environmental degradation linked to energy use. Understanding how New Quality Productive Forces (NQPF) interact with energy efficiency, along with the mechanisms driving this relationship, is essential for economic transformation and long-term sustainability. This study establishes an evaluation framework for NQPF, integrating technological, green, and digital dimensions. We apply fixed-effects models, the spatial Durbin model (SDM), a moderation model, and a threshold model to analyze the influence of NQPF on Green Total Factor Energy Efficiency (GTFEE) and its spatial implications. This underscores the necessity of distinguishing it from traditional productivity frameworks and adopting a new analytical perspective. Furthermore, by considering dimensions such as input, application, innovation capability, and market efficiency, we reveal the moderating role and heterogeneous effects of artificial intelligence (AI). The findings are as follows: The development of NQPF significantly enhances GTFEE, and the conclusion remains robust after tail reduction and endogeneity tests. NQPF has a positive spatial spillover effect on GTFEE; that is, while improving the local GTFEE, it also improves neighboring regions GTFEE. The advancement of AI significantly strengthens the positive impact of NQPF on GTFEE. AI exhibits a significant U-shaped threshold effect: as AI levels increase, its moderating effect transitions from suppression to facilitation, with marginal benefits gradually increasing over time. Full article