Search Results (106,481)

Regional integration is a foundation for coordinated regional development and an important pathway for promoting the green and low-carbon development (GLD) (In this paper, GLD refers to green and low-carbon development, while YRD refers to the Yangtze River Delta) of cities. Based on a systematic analysis of the theoretical mechanisms through which regional integration affects the GLD of cities, this study uses changes in the spatial scope of Yangtze River Delta (YRD) regional integration as a quasi-natural experiment and constructs a multi-period DID model to examine its impact. The results show that YRD regional integration significantly improves the GLD efficiency of cities. This conclusion remains valid after a series of robustness tests, including the parallel-trends test, year-by-year PSM-DID, and modern staggered DID estimators. The heterogeneity analysis shows that the promoting effect of regional integration is more significant for megacities, core cities, and especially Shanghai, while its effects on medium-sized cities and cities in Anhui Province have not yet emerged in the short term. The mechanism tests further show that YRD regional integration improves the GLD efficiency of cities mainly by optimizing the energy consumption structure, promoting industrial restructuring, enhancing government attention to GLD, and improving green innovation. The findings provide useful empirical insights for fully leveraging the green and low-carbon effects of YRD regional integration and for promoting GLD in the Yangtze River Economic Belt and even across China. Full article

Cash crop expansion has contributed to income growth among smallholder farmers in developing countries, but its long-term implications for soil fertility remain insufficiently understood. In particular, few studies have incorporated farmers’ perceptions of crop profitability and soil impacts into dynamic simulation models. This study examines the long-term effects of crop-choice behavior on soil fertility in Shan State, Myanmar, using a perception-based dynamic simulation model. Profit indices and soil-load indices for major cash crops were constructed from interviews with local farmers and applied to three crop-choice scenarios: profit maximization, continuous cropping restriction, and crop rotation. Soil fertility was simulated over a 50-year period under each scenario. Under the interview-derived parameter settings, the profit maximization scenario, corresponding to continuous cultivation of perilla, achieved both the highest cumulative profit and the highest level of soil fertility. In contrast, the continuous cropping restriction scenario resulted in the greatest decline in soil fertility because the replacement crop, peanut, was also perceived as imposing a relatively high soil load. Incorporating sweet potato into a four-year crop rotation substantially improved soil fertility compared with the continuous cropping restriction scenario, demonstrating that the effectiveness of crop rotation depends on the combination of crops included in the rotation. These findings suggest that farmers’ perceptions of crop profitability and soil impacts can strongly influence long-term land-use outcomes and highlight the importance of considering local farming knowledge when designing sustainable agricultural management strategies. Full article

Coordinating the synergistic development of ecological protection and recreational utilization is a core issue for the high-quality development of green spaces in metropolitan areas. Using the coupling coordination degree model (CCDM) and Moran’s I Outlier Clustering, this study spatially assesses the coupling coordination degree (CCD) between the ecological quality and recreation service intensity of the green spaces in the Suzhou-Wuxi-Changzhou region. It further employs the Geodetector model to identify the influencing factors affecting the CCD. The results show the following: (1) The overall regional coordination is low, with 83.96% of green spaces being in moderate-to-severe imbalance and only 16.04% reaching primary-to-intermediate coordination, highlighting a prominent supply–demand imbalance. (2) The spatial pattern exhibits a structure whereby values are “high in the center, low in the east and west”, showing significant spatial differentiation. (3) Among the influencing factors, socio-economic elements such as cultural attractiveness (q = 0.433) and economic development (q = 0.148) play a dominant role, indicating that imbalance is mainly driven by socio-economic factors. Accordingly, this study proposes spatial optimization strategies based on zonal management, balanced layout, and multi-dimensional drivers to promote balanced recreational supply, facilitate the synergy between ecological protection and recreational utilization, and achieve the sustainable development of regional green spaces. Full article

The Yili River Valley in Xinjiang is characterized by complex geological structures and frequent geological hazards, which seriously threaten local lives, property, and infrastructure. Improving the accuracy and interpretability of geological hazard assessment is therefore of great significance. To address this, nine factors, including elevation, distance from fault, and slope, were selected to construct a WOE-BPNN-SHAP coupled model. The weights of evidence (WOE) method was first used for factor correlation testing and to optimize the input of the BP neural network. The evaluation accuracies of WOE, WOE-DNN, and WOE-BP models were then compared, and the SHAP model was introduced to analyze the coupling relationships among factors. Results show that the WOE-BP model achieves the best predictive performance, with an AUC of 83.65%. Areas of extremely high-risk account for 8.63% of the study area, while higher-risk areas account for 15.39%. Elevation (1688–2847 m), distance from fault (<3000 m), precipitation (192.6–290.8 mm), and slope (>16°) are identified as the main driving factors. This coupled method provides a new technical approach for regional geological hazard assessment and offers a theoretical basis for disaster prevention, mitigation, and resilience building in the Yili River Valley. Full article

Climate-related disclosure has moved rapidly from a voluntary practice to a legal obligation, yet whether mandates improve the substance of corporate climate governance—rather than the volume of reporting—remains an open question. We exploit the staggered introduction of climate-disclosure mandates in the United Kingdom (2022) and France (2025), with the United States and Australia serving as never-treated and not-yet-treated comparison groups, to estimate the effect of mandatory disclosure on structured climate-governance quality. The outcome is the Transition Pathway Initiative (TPI) Management Quality score, an externally assessed 0–5 staircase of climate-governance practices, observed for 837 listed firms over 2015–2025 (2841 firm-year observations). Using two-way fixed effects, Sun–Abraham and Callaway–Sant’Anna estimators implemented in RStudio, we find no statistically significant effect of disclosure mandates on climate-governance quality: the preferred Callaway–Sant’Anna estimate is 0.082 levels (95% CI −0.221 to 0.385), precise enough to rule out effects larger than about 0.4 levels (≈0.4 standard deviations). Meanwhile, never-mandated US firms improved from a mean Management Quality of 1.4 to 3.1 over the decade, converging toward mandated jurisdictions. An anticipation-adjusted specification yields a positive and significant effect, but it benchmarks against pandemic-year assessments and should be read with caution. Disaggregating the score into its underlying indicators shows that board-level oversight and basic disclosure are near-universal among mandated firms, whereas transition-planning and capital-alignment practices remain rare in every jurisdiction, locating the unfinished governance agenda at the top of the staircase. The evidence suggests that disclosure mandates largely codified governance practices that investor- and market-driven pressures had already diffused, implying that regulators should pair disclosure requirements with substantive transition-plan obligations if the policy goal is governance change rather than transparency alone. Full article

Spatially explicit crop yield information is needed for regional environmental modeling, sustainability assessment, and agricultural decision support, yet official yield statistics are commonly reported only at aggregated administrative scales. This study introduces the NAYD R package, a reproducible geospatial workflow for converting county-level harvested area and yield statistics into spatially explicit production units and zonal clusters while preserving consistency with official records. County-level statistics from the USDA National Agricultural Statistics Service were integrated with USDA Cropland Data Layer crop masks, multi-sensor NDVI products, and satellite-derived evapotranspiration from OpenET SSEBop. An NDVI-based eligibility filter refined crop masks toward reported harvested area, while normalized NDVI and evapotranspiration layers were combined into spatial weighting surfaces and aggregated into contiguous production units and graph-based clusters. Case studies for cotton and winter wheat in Texas showed that the eligibility filter removed approximately 20–40% of CDL-classified pixels while maintaining consistency with reported harvested area and preserving plausible spatial gradients associated with irrigated and dryland systems. Evaluation against independent Texas A&M AgriLife variety trial data indicated that the disaggregated clusters reproduced plausible spatial patterns of yield variability while retaining the county-level NASS constraints. The workflow provides an open-source framework for generating statistically consistent production zones for regional crop modeling, environmental assessment, and sustainable agricultural planning. Full article

Terrestrial ecosystems serve as key carbon reservoirs and contribute substantially to global carbon cycling and climate regulation. Shaanxi Province (SP) is located along China’s north–south geographical boundary and climatic transition zone, making it crucial to understand how carbon stocks change within its ecosystems. This study analyzed the land-use patterns, influencing factors, and spatiotemporal dynamics of carbon storage across three regions (Shanbei, Guanzhong, and Shannan) in SP. The results indicated that: (1) From 2000 to 2020, cropland and barren land areas in SP decreased significantly, while the forest land area increased markedly. Total carbon storage in SP increased from 1688.55 Tg in 2000 to 1726.12 Tg in 2020, with the highest accumulation observed in Shannan, followed by Shanbei and Guanzhong. (2) Forest land acted as the most significant carbon sink; its contribution to SP’s total carbon storage increased from 54.98% in 2000 to 60.28% in 2020. (3) Carbon storage across the three regions was positively correlated with elevation, slope, soil silt content, and precipitation, but negatively correlated with soil sand content, gross domestic product, and population distribution. (4) Geographical detector analysis identified precipitation as the key influencing factor for carbon storage in Shanbei and Guanzhong, whereas the primary factors in Shannan were temperature, elevation, and slope. This study recommends future land use priorities: maintaining grassland dominance in Shanbei, scientifically optimizing the planning of cropland and impervious land in Guanzhong, and sustaining current forest protection and management in Shannan. These results provide vital quantitative support and important references for ecologically sustainable development and the realization of China’s dual-carbon goals in SP. Full article

Against the backdrop of global low-carbon transformation and China’s “dual-carbon” target, the logistics industry has become a key sector for carbon emission reduction due to its high energy consumption and significant spatial correlation characteristics. Taking 30 provinces in China from 2010 to 2022 as research samples, this paper uses the Super-SBM model to measure the carbon emission efficiency of the logistics industry, constructs a spatial correlation network based on the modified gravity model, and explores the structural characteristics and evolutionary logic of the network through social network analysis (SNA). Furthermore, the quadratic assignment procedure (QAP) regression is employed to reveal the driving factors of the spatial correlation effect. The results show that China’s logistics carbon emission efficiency presents an obvious “east-high west-low, south-high north-low” spatial pattern with significant positive agglomeration and stable spillover effects. A nationwide connected spatial correlation network has formed, with high connectivity, increasing density, and enhanced stability. Eastern coastal provinces are core nodes, central provinces act as bridges, and western provinces are at the network edge. The block model divides the network into net benefit, net spillover, and broker plates, revealing a spillover pattern from the edge to the core. QAP regression shows that energy intensity, transportation structure, economic level, policy support, and population size are negatively correlated with spatial correlation, and narrowing regional differences strengthens network connections. Full article

Using a sample of 68 listed banks in the MENAT region from 2017 to 2023, this study examines the effect of gender diversity on ESG disclosure and the moderating role of audit committees, employing the system GMM estimator to address potential endogeneity concerns. The results reveal that the proportion of women on boards has a positive impact on ESG disclosure. Nonetheless, the relation is negatively moderated by audit committees, revealing the boundaries of the beneficial effect of gender diversity in the presence of traditional governance. The findings should be interpreted with caution but suggest that gender diversity may be associated with improved transparency and sustainability practices among firms in the MENAT region. These results may inform policy discussions regarding the potential role of gender diversity in strengthening corporate governance and sustainability outcomes. Furthermore, the evidence provides indicative support for the need for audit committees to adopt more targeted monitoring approaches across individual ESG pillars to improve oversight effectiveness. Full article

Carbon capture and storage (CCS) represents a critical technology for achieving climate neutrality targets, particularly for regions with significant industrial CO₂ emissions. This study presents a comprehensive numerical simulation assessment of CO₂ geological storage potential in the Sarmatian formations of the Getic Platform, Romania, located near the Turceni power plant—one of Europe’s largest thermal power facilities. Using ECLIPSE 300 compositional simulator with the CO2STORE option, we developed reservoir dynamic models incorporating geological properties, fluid characteristics, and pressure–volume–temperature (PVT) data specific to the Sarmatian aquifer system. Multiple injection scenarios were evaluated, including configurations with 3, 4, and 5 injection wells at varying inter-well distances (2000–10,000 m). The simulations covered a 20-year injection period followed by 300 years of monitoring. While previous assessments have provided static capacity estimates for Sarmatian formations, this study presents the first dynamic simulation-based evaluation of multi-well injection scenarios and long-term CO₂ trapping behavior in this geological setting, directly linked to the Turceni Power Plant emissions profile. Results demonstrate that the study area (Zone V) can accommodate the target CO₂ injection rate of 2.07 × 10⁶ Sm³/day using five injection wells, with final reservoir pressure increasing only 7–9 bar above initial conditions, well below fracture pressure thresholds (~280 bar). Long-term simulations reveal favorable CO₂ trapping behavior, with significant portions immobilized through residual and dissolution trapping mechanisms. The static storage capacity was estimated at 2.44 × 10¹⁴ kg CO₂. These findings support the technical feasibility of large-scale CO₂ storage in Romanian Sarmatian formations, providing quantitative evidence for CCS implementation strategies in the region. Full article

Rural coastal communities are grappling with climate change impacts, including the increased frequency of extreme storm events. Achieving sustainability goals requires addressing environmental, social, and economic dimensions of these events. Social vulnerability indices provide a means of addressing social vulnerability to advance sustainability goals. While such indices offer a metric for assessing relative social vulnerability at a community scale, they often fail to capture more nuanced dimensions of vulnerability. Our exploratory qualitative case study employed two community-driven exercises to examine the impacts due to loss of power, heat, and access to emergency services stemming from a storm event. Participants representing public, conservation, social service, emergency management, and business sectors received a customized social vulnerability index prior to the community exercise, which examined social vulnerabilities associated with an extreme storm event. Participants completed pre- and post-exercise surveys. Transcripts and notes from discussions were analyzed qualitatively. The results provide a refined understanding of who is vulnerable to climate change impacts, the limitations of vulnerability indices in capturing these vulnerabilities, and the potential for community-centered approaches for developing customized vulnerability indices. Such approaches can inform more comprehensive preparation and recovery initiatives in response to increasing extreme storm events. Full article

The North Sea is becoming a shared renewable energy space in which offshore wind deployment, grid planning, market operation and environmental governance increasingly cross borders. This article asks how wind-resource complementarity can inform legal and institutional design for cross-border offshore wind cooperation. It combines a five-year representative-point wind-resource screening analysis using NASA POWER hourly data from 2021 to 2025 with functional legal–institutional analysis. The empirical analysis covers seven offshore or near-offshore representative screening points, hub-height correction to 100 m and 150 m, a wind-power proxy and wind-power-density proxy, low-wind frequency and low-wind event duration, monthly and interannual variability, pairwise correlation, CWCI and weighting sensitivity. The representative-point results suggest a mean 100 m corrected wind-speed range of 8.52 to 9.88 m/s, 4 m/s low-wind frequencies of 8.69% to 12.64%, and a maximum 4 m/s low-wind event of 173.0 h at NO_SOUTH. The baseline CWCI screening identifies DK West–BE Coast, DK West–FR Channel and UK East–FR Channel as leading within-sample pairs. The legal analysis uses these results as screening evidence for questions of data compatibility, hub-height assumptions, low-wind consultation, hybrid offshore grid governance, market coordination, cumulative environmental assessment, investment regulatory space and crisis dispute prevention. The article proposes an operational five-pillar framework with institutions, instruments, implementation steps and compliance pathways. It should be read as an exploratory evidence-to-law screening analysis, not a definitive wind-resource assessment, turbine-output model, capacity-factor estimate or grid-dispatch simulation. Full article

The aim of this article is to demonstrate the significance of Iceland’s Ring Road as a key route providing access to geotourism attractions and to discuss its role in shaping visitor traffic in the context of tourist feedback and the principles of sustainable tourism development. The study is based on an analysis of 223 online reviews concerning the Ring Road, supplemented by the author’s own field observations from travelling around Iceland. Opinions relating to natural and anthropogenic assets, tourist infrastructure, transport accessibility, travel safety, visitor concentration and the interpretation of geological heritage were analysed. The results indicate that the Ring Road is highly rated by tourists, primarily because of the exceptional natural assets located along and near the route. At the same time, the analysis revealed challenges related to traffic concentration at the most recognisable attractions, the uneven quality of tourist infrastructure, high costs, travel safety and the limited use of the educational potential of geosites. The findings show that online reviews, when combined with field observations, can serve as a useful source of knowledge about the practical conditions for the sustainable use of geotourism attractions in popular natural destinations. Full article

With the continuing advancement of global environmental change and rapid urbanization, rural human settlements are facing multiple pressures, including ecological degradation, spatial decline, population outflow, and functional weakening. Based on the vulnerability analysis framework, studies on rural vulnerability provide an important perspective for assessing villages’ risk exposure, disturbance response, and functional degradation when coping with internal and external disturbances. However, existing studies often rely on single-dimensional or linearly weighted evaluations, making it difficult to comprehensively reveal the coupling relationships among multiple discriminative variables and the spatial differentiation patterns of vulnerability. Taking rural areas in Hancheng City, Shaanxi Province, as the research object, this study selects 12 indicators from three dimensions—natural ecological constraints, settlement spatial organization, and public service support—to provide proxy representations of conditions related to potential rural vulnerability. K-means clustering was used to identify potential vulnerability configuration types under multidimensional indicator combinations. A Python-based XGBoost model was then employed as an interpretable surrogate model to assist in characterizing the clustering boundaries, while SHAP analysis was used to explain the key discriminative variables associated with type membership. The results show that the potential rural vulnerability configurations in Hancheng City present a significant west–central–east spatial differentiation pattern. Elevation, village core density, topographic wetness index, distance to town centers, accessibility of daily service facilities, distance to major roads, and normalized difference vegetation index are the main discriminative variables distinguishing different potential vulnerability configuration types. Among them, village core density shows a particularly strong explanatory role. Different key discriminative variables also exhibit evident nonlinear response characteristics across different potential types. Under the indicator system and the $K$ = 4 clustering scheme adopted in this study, the potential rural vulnerability configurations in Hancheng City can be summarized into four types: service-concentrated settlement type, complex terrain-constrained type, human–land coupling transitional type, and natural ecological isolation type. The findings reveal the spatial differentiation characteristics, variable combination relationships, and typological discriminative features of potential rural vulnerability configurations in Hancheng City. They can provide a case-based reference for identifying potential vulnerability, conducting spatial zoning diagnosis, and supporting classified governance in similar county-level rural areas within the loess hilly and gully region. In practical terms, this framework can serve as a diagnostic tool for local governments and planners in classified rural governance. It can be used to identify priority areas for public service and infrastructure investment, review key risk-control areas in complex terrain zones, delineate low-intensity use and protection boundaries in ecologically isolated areas, and guide differentiated resource allocation for different types of villages. Full article