Search Results (9,327)

Excessive nitrogen (N) fertilizer usage in agriculture has prompted the exploration of sustainable strategies to enhance nitrogen use efficiency (NUE) while maintaining crop yield and quality. Processed tomatoes (Solanum lycopersicum L.) were grown for two years (2023 and 2024) following a two-way factorial randomized complete block (RCBD) design, considering three biostimulants and three N regimes as two factors, to assess their morphophysiological, biochemical, anatomical and yield performances. Nitrogen application significantly influenced biomass accumulation, the leaf area index (LAI), nitrogen uptake and yield with notable comparable values between reduced and optimal nitrogen dose, indicating improved nitrogen use efficiency. Biostimulants showed limited effects alone but enhanced plant performance under reduced nitrogen conditions, particularly improving chlorophyll content, crop growth, N uptake, yield and anatomical adaptations. Moreover, compared to 2024, biostimulant application enhanced tomato growth more evidently in 2023 due to environmental variations, likely due to the occurrence of stress conditions. Importantly, biostimulants, together with N regimes, i.e., optimal and reduced doses, showed improved anatomical traits, especially regarding leaf thickness and thickness between the two epidermises, indicating adaptive responses that may support sustained productivity under N-limited conditions. Among the biostimulants used, the processed tomatoes responded better to protein hydrolysate and endophytic N-fixing bacteria than to seaweed extract. These findings suggest that although biostimulants alone were not affected, integrating them with reduced N fertilization provides a viable strategy for optimizing tomato production, conserving resources and minimizing the environmental impact without compromising yield or quality. Full article

This study analyzes the strategic and institutional frameworks that precede the formulation of trade agreements, with a focus on the European Union’s external action and its link to the Sustainable Development Goals. Based on a documentary research design, this study examines official documents from the EU and the United Nations, as well as the academic literature indexed in Scopus and Web of Science. The methodological process involved four phases: systematic search, selection and classification, inductive content coding, and interpretative analysis. Through this process, this study identifies discursive patterns, normative tensions, and policy orientations that reveal the EU’s evolving approach to sustainable trade governance. The findings highlight the existence of a growing institutional alignment between trade policy and sustainable development frameworks, yet also expose persistent gaps in coherence and implementation. This article contributes to the academic debate by offering a critical and structured analytical lens to understand how trade agreements are politically and institutionally prefigured before their negotiation phase. Full article

The changing global climate and rapid urbanization make extreme rainstorm events frequent, and the flood disaster caused by rainstorm has become a prominent problem of urban public safety in China, which severely restricts the healthy and sustainable development of social economy. The weight calculation method of traditional risk assessment model is single and ignores the difference of multi-dimensional information space involved in risk analysis. This study constructs a flood risk assessment model by incorporating natural, social, and economic factors into an indicator system structured around four dimensions: hazard, exposure, vulnerability, and disaster prevention and mitigation capacity. A combination of the Analytic Hierarchy Process (AHP) and the entropy weight method is employed to optimize both subjective and objective weights. Taking the central urban area of Wuhan with a high flood risk as an example, based on the risk assessment values, spatial autocorrelation analysis, cluster analysis, outlier analysis, and hotspot analysis are applied to explore the spatial clustering characteristics of risks. The results show that the overall assessment level of flood hazard in central urban area of Wuhan is medium, the overall assessment level of exposure and vulnerability is low, and the overall disaster prevention and mitigation capability is medium. The overall flood risk levels in Wuchang and Jianghan are the highest, while some areas in Qingshan and Hanyang have the lowest levels. The spatial characteristics of each dimension evaluation index show obvious autocorrelation and spatial differentiation. These findings aim to provide valuable suggestions and references for reducing urban disaster risks and achieving sustainable urban development. 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

This study contributes to scientific theory by analyzing the models proposed within the framework of circular agriculture to determine how the three dimensions of sustainability—environmental, economic, and social—are integrated into their implementation. A systematic review was conducted on articles published between 2016 and 2025, indexed in the Scopus and Web of Science databases, as well as the relevant grey literature. The methodology employed an extensive content analysis designed to minimize bias, applying filters related to specific knowledge areas to delimitate the search scope and enhance the precision of the research. The findings reveal that the research on circular agriculture models is predominantly grounded in the principles of the circular economy and its associated indicators. Moreover, these models tend to focus on environmental metrics, often neglecting a comprehensive exploration of the social and economic dimensions of sustainable development. It can be concluded that a significant gap persists in the literature regarding the circularity of agriculture and its socio-economic impacts and the role of regulatory frameworks, aspects that future research must address in order to achieve sustainability in circular agriculture. Full article

Background: Growing disparities in development, governance, and logistics performance across countries pose challenges for global policymaking and Sustainable Development Goal (SDG) monitoring. This study proposes a classification of 137 countries based on multiple structural dimensions. The dataset for 2023 includes six components of the Logistics Performance Index (LPI), six dimensions of the Worldwide Governance Indicators (WGIs), and four proxies of the Human Development Index (HDI). Methods: The Uniform Manifold Approximation and Projection (UMAP) technique was used to reduce dimensionality and allow for meaningful clustering. Based on the reduced space, the K-means algorithm was employed to group countries with similar development characteristics. Results: The classification process allowed the identification of three distinct groups of countries, supported by a Hopkins statistic of 0.984 and an explained variance ratio of 87.3%. These groups exhibit structural differences in the quality of governance, logistics capacity, and social development conditions. Internal consistency checks and multivariate statistical analyses (ANOVA and MANOVA) confirmed the robustness and statistical significance of the clustering. Conclusions: The resulting classification offers a practical analytical tool for policymakers to design differentiated strategies aligned with national contexts. Furthermore, it provides a data-driven approach for comparative monitoring of the SDGs from an integrated and empirical perspective. Full article

Soil structural instability in reservoir riparian zones, induced by water level fluctuations, threatens sustainable land use by accelerating land degradation. This study examined the impact of water-level variations on soil aggregate composition and stability based on key indicators, including water-stable aggregate content (WSAC), mean weight diameter (MWD), and geometric mean diameter (GMD). The Savinov dry sieving, Yoder wet sieving, and Le Bissonnais (LB) methods were employed for analysis. Results indicated that, with decreasing water levels and increasing soil layer, aggregates larger than 5 mm decreased, while aggregates smaller than 0.25 mm increased. Rising water levels and increasing soil layer corresponded to reductions in soil stability indicators (MWD, GMD, and WSAC), highlighting a trend toward soil structural instability. The LB method revealed the lowest aggregate stability under rapid wetting and the highest under slow wetting conditions. Correlation analysis showed that soil organic matter positively correlated with the relative mechanical breakdown index (RMI) (p < 0.05) and negatively correlated with the relative slaking index (RSI), whereas soil pH was negatively correlated with both RMI and RSI (p < 0.05). Comparative analysis of aggregate stability methods demonstrated that results from the dry sieving method closely resembled those from the SW treatment of the LB method, whereas the wet sieving method closely aligned with the FW (Fast Wetting) treatment of the LB method. The Le Bissonnais method not only reflected the outcomes of dry and wet sieving methods but also effectively distinguished the mechanisms of aggregate breakdown. The study concluded that prolonged flooding intensified aggregate dispersion, with mechanical breakdown influenced by water levels and soil layer. Dispersion and mechanical breakdown represent primary mechanisms of soil aggregate instability, further exacerbated by fluctuating water levels. By elucidating degradation mechanisms, this research provides actionable insights for preserving soil health, safeguarding water resources, and promoting sustainable agricultural in ecologically vulnerable reservoir regions of the Yangtze River Basin. Full article

The Tibetan Plateau (TP) is experiencing higher warming rates than elsewhere, which may affect regional vegetation growth. Particularly on the Eastern Tibetan Plateau (ETP), where the topography is diverse and rich in biodiversity, it is necessary to clarify the drivers of climate and topography on vegetation cover. In this research, we selected the Shaluli Mountains (SLLM) in the ETP as the study area, monitored the spatial and temporal dynamics of the regional vegetation cover using remote sensing methods, and quantified the drivers of vegetation change using Geodetector (GD). The results showed a decreasing trend in annual precipitation (PRE) (−2.4054 mm/year) and the Palmer Drought Severity Index (PDSI) (−0.1813/year) in the SLLM. Annual maximum temperature (TMX) on the spatial and temporal scales showed an overall increasing trend, and the regional climate tended to become warmer and drier. Since 2000, fractional vegetation cover (FVC) has shown a fluctuating upward trend, with an average value of 0.6710, and FVC has spatially shown a pattern of “low in the middle and high in the surroundings”. The areas with non-significant increases (p > 0.05) and significant increases (p < 0.05) in FVC accounted for 46.03% and 5.76% of the SLLM. Altitude (q = 0.3517) and TMX (q = 0.3158) were the main drivers of FVC changes. As altitude and TMX increased, FVC showed a trend of increasing and then decreasing. The results of this study help us to clarify the influence of climate and topography on the vegetation ecosystem of the ETP and provide a scientific basis for regional biodiversity conservation and sustainable development. Full article

The intensification of anthropogenic pressures, particularly those related to agriculture driven by increasing demands for food and cash crops, generates negative environmental externalities. Assessing these externalities is essential to better identify and implement measures that promote the environmental sustainability of rural landscapes. This study aims to develop a multi-criteria assessment method of the negative environmental externalities of rural landscapes in the northern Benin agricultural basin, based on satellite-derived data. Starting from a 12-class land cover map produced through satellite image classification, the evaluation was conducted in three steps. First, the 12 land cover classes were reclassified into Human Disturbance Coefficients (HDCs) via a weighted sum model multi-criteria analysis based on nine criteria related to the negative environmental externalities of anthropogenic activities. Second, the HDC classes were spatially aggregated using a regular grid of 1 km² landscape cells to produce the Landscape Environmental Sustainability Index (LESI). Finally, various discretization methods were applied to the LESI for cartographic representation, enhancing spatial interpretation. Results indicate that most areas exhibit moderate environmental externalities (HDC and LESI values between 2.5 and 3.5), covering 63–75% (HDC) and 83–94% (LESI) of the respective sites. Areas of low environmental externalities (values between 1.5 and 2.5) account for 20–24% (HDC) and 5–13% (LESI). The LESI, derived from accessible and cost-effective satellite data, offers a scalable, reproducible, and spatially explicit tool for monitoring landscape sustainability. It holds potential for guiding territorial governance and supporting transitions towards more sustainable land management practices. Future improvements may include, among others, refining the evaluation criteria and introducing variable criteria weighting schemes depending on land cover or region. 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

Investigating the coevolution between ecosystem services (ES) and human well-being (HWB) holds significant implications for achieving the sustainable operation of human–environment systems. However, limited research has focused on ES-HWB interactions in ecotourism-dominated counties. To address this gap, this study takes Chun’an County in Zhejiang Province, China, as a case study, with the research objective of exploring the processes, patterns, and mechanisms of the coevolution between ecosystem services (ES) and human well-being (HWB) in ecotourism-dominated counties. By integrating multi-source heterogeneous data, including land use data, the normalized difference vegetation index (NDVI), and statistical records, and employing methods such as the dynamic equivalent factor method, the PLUS model, the coupling coordination degree model, and comprehensive evaluation, we analyzed the synergistic evolution of ES-HWB in Chun’an County from 2000 to 2020. The results indicate that (1) the ecosystem service value (ESV) fluctuated between 30.15 and 36.85 billion CNY, exhibiting a spatial aggregation pattern centered on the Qiandao Lake waterbody, with distance–decay characteristics. The PLUS model confirms ecological conservation policies optimize ES patterns. (2) The HWB index surged from 0.16 to 0.8, driven by tourism-led economic growth, infrastructure investment, and institutional innovation, facilitating a paradigm shift from low to high well-being at the county level. (3) The ES-HWB interaction evolved through three phases—disordered, antagonism, and coordination—revealing tourism as a key mediator driving coupled human–environment system sustainability via a pressure–adaptation–synergy transmission mechanism. This study not only advances the understanding of ES-HWB coevolution in ecotourism-dominated counties, but also provides a transferable methodological framework for sustainable development in similar regions. Full article

As urbanization processes are no longer characterized by simple linear expansion but exhibit leaping, edge-sparse, and discontinuous features, spatiotemporally continuous impervious surface coverage data are needed to better characterize urbanization processes. This study utilized GAIA impervious surface binary data and employed spatiotemporal aggregation methods to convert thirty years of 30 m resolution data into 1 km resolution spatiotemporal impervious surface coverage data, constructing a long-term time series annual impervious surface coverage dataset for the Beijing–Tianjin–Hebei region. Based on this dataset, we analyzed urban expansion processes and landscape pattern indices in the Beijing–Tianjin–Hebei region, exploring the spatiotemporal response relationships of ecological environment changes. Results revealed that the impervious surface area increased dramatically from 7579.3 km² in 1985 to 37,484.0 km² in 2020, representing a year-on-year growth of 88.5%. Urban expansion rates showed two distinct peaks: 800 km²/year around 1990 and approximately 1700 km²/year during 2010–2015. In high-density urbanized areas with impervious surfaces, the average forest area significantly increased from approximately 2500 km² to 7000 km² during 1985–2005 before rapidly declining, grassland patch fragmentation intensified, while in low-density areas, grassland area showed fluctuating decline with poor ecosystem stability. Furthermore, by incorporating natural and social factors such as Fractional Vegetation Coverage (FVC), Habitat Quality Index (HQI), Land Surface Temperature (LST), slope, and population density, we assessed the vulnerability of urbanization development in the Beijing–Tianjin–Hebei region. Results showed that high vulnerability areas (EVI > 0.5) in the Beijing–Tianjin core region continue to expand, while the proportion of low vulnerability areas (EVI < 0.25) in the northern mountainous regions decreased by 4.2% in 2020 compared to 2005. This study provides scientific support for the sustainable development of the Beijing–Tianjin–Hebei urban agglomeration, suggesting location-specific and differentiated regulation of urbanization processes to reduce ecological risks. Full article

This paper examines the effect of digital innovation on cost stickiness in manufacturing firms, focusing on the underlying mechanisms and contextual factors. Using data from Chinese A-share listed manufacturing firms from 2012 to 2023, we find that, first, for each one-unit increase in the level of digital technology, the cost stickiness index of enterprises decreases by an average of 0.4315 units, primarily through digital process innovation and digital business model innovation, whereas digital product innovation does not exhibit a statistically significant impact. Second, manufacturing servitization and the optimization of human capital structure are identified as key mediating mechanisms. Digital innovation promotes servitization by transitioning firms from product-centric to service-oriented business models, thereby reducing fixed costs and improving resource flexibility. It also optimizes human capital by increasing the proportion of high-skilled employees and reducing labor adjustment costs. Third, the effect of digital innovation on cost stickiness is found to be heterogeneous. Firms with high financing constraints benefit more from the cost-reducing effects of digital innovation due to improved resource allocation efficiency. Additionally, mid-tenure executives are more effective in leveraging digital innovation to mitigate cost stickiness, as they balance short-term performance pressures with long-term strategic investments. These findings contribute to the understanding of how digital transformation reshapes cost behavior in manufacturing and provide insights for policymakers and firms seeking to achieve sustainable development through digital innovation. Full article

In China’s Loess Plateau, sustainable agricultural end products are affected by an insufficiency of water resources. Rising crop water use efficiency (WUE) through field management pattern improvement is a crucial plan of action to address this issue. However, there is no agreement among researchers on the most appropriate field management practices regarding WUE, which requires further integrated quantitative analysis. We conducted a meta-analysis by quantifying the effect of agricultural practices surrounding nitrogen (N) fertilizer management. The two experimental cultivars were Yunhan–20410 and Yunhan–618. The subplots included nitrogen 0 kg·ha⁻¹ (N0), 90 kg·ha⁻¹ (N90), 180 kg·ha⁻¹ (N180), 210 kg·ha⁻¹ (N210), and 240 kg·ha⁻¹ (N240). Our results show that higher N rates (up to N210) enhanced water consumption during the node-flowering and flowering-maturity time periods. YH–618 showed higher water use during the sowing–greening and node-flowering periods but decreased use during the greening-node and flowering-maturity periods compared to YH–20410. The N210 treatment under YH–618 maximized water use efficiency (WUE). Increased N rates (N180–N210) decreased covering temperatures (T_max, T_min, T_aver) during flowering, increasing the level of grain filling. Spike numbers rose with N application, with an off-peak at N210 for strong-gluten wheat. The 1000-grain weight was at first enhanced but decreased at the far end of N180–N210. YH–618 with N210 achieved a harvest index (HI) similar to that of YH–20410 with N180, while excessive N (N240) or water reduced the HI. Dry matter accumulation increased up to N210, resulting in earlier stabilization. Soil water consumption from wintering to jointing was strongly correlated with pre-flowering dry matter biological process and yield, while jointing–flowering water use was linked to post-flowering dry matter and spike numbers. Post-flowering dry matter accumulation was critical for yield, whereas spike numbers positively impacted yield but negatively affected 1000-grain weight. In conclusion, our results provide evidence for determining suitable integrated agricultural establishment strategies to ensure efficient water use and sustainable production in the Loess Plateau region. Full article

This study, conducted in Mexico, evaluates the agricultural potential of three compost formulations BFS1, BFS2, and BFS3 produced from mining tailings and thermophilic microbial mats and collected from geothermal environments. The physicochemical characterization included pH, electrical conductivity (EC), macronutrients (N, P, K, Ca, Mg, and S), micronutrients (Fe, Zn, B, Cu, Mn, Mo, and Ni), organic matter (OM), and the carbon-to-nitrogen (C/N) ratio. All composts exhibited neutral pH values (7.38–7.52), high OM content (38.5–48.4%), and optimal C/N ratios (10.5–13.9), indicating maturity and chemical stability. Nitrogen ranged from 19 to 21 kg·t⁻¹, while potassium and calcium were present in concentrations beneficial for crop development. However, EC values (3.43–3.66 dS/m) and boron levels (>160 ppm) were moderately high, requiring caution in saline soils or with boron-sensitive crops. A semi-quantitative Compost Quality Index (CQI) ranked BFS3 highest due to elevated OM and potassium content, followed by BFS1. BFS2, while rich in nitrogen, scored lower due to excessive boron. One-way ANOVA revealed no significant difference in nitrogen (p > 0.05), but it did reveal significant differences in potassium (p < 0.01) and boron (p < 0.001) among formulations. These results confirm the potential of mining tailings—microbial mat composts are low-cost, nutrient-rich biofertilizers. They are suitable for field crops or as components in nursery substrates, particularly when EC and boron are managed through dilution. This study promotes the circular reuse of geothermal and industrial residues and contributes to sustainable soil restoration practices in mining-affected regions through innovative composting strategies. Full article