Search Results (313)

Street design quality and socio-economic factors jointly influence housing prices, but their intertwined effects and spatial variations remain under-quantified. Housing prices not only reflect residents’ neighborhood experiences but also stem from the spillover value of public streets perceived and used by different users. This study takes Tianjin as a case and views the street environment as an immediate experience proxy for through-travelers, combining street view images and crowdsourced perception data to extract both subjective and objective indicators of the street environment, and integrating neighborhood and location characteristics. We use Geographical-XGBoost to evaluate the relative contributions of multiple factors to housing prices and their spatial variations. The results show that incorporating both subjective and objective street information into the Hedonic Pricing Model (HPM) improves its explanatory power, while local modeling with G-XGBoost further reveals significant heterogeneity in the strength and direction of effects across different locations. The results indicate that incorporating both subjective and objective street information into the HPM enhances explanatory power, while local modeling with G-XGBoost reveals significant heterogeneity in the strength and direction of effects across different locations. Street greening, educational resources, and transportation accessibility are consistently associated with higher housing prices, but their strength varies by location. Core urban areas exhibit a “counterproductive effect” in terms of complexity and recognizability, while peripheral areas show a “barely acceptable effect,” which may increase cognitive load and uncertainty for through-travelers. In summary, street environments and socio-economic conditions jointly influence housing prices via a “corridor-side–community-side” dual-pathway: the former (enclosure, safety, recognizability) corresponds to immediate improvements for through-travelers, while the latter (education and public services) corresponds to long-term improvements for residents. Therefore, core urban areas should control design complexity and optimize human-scale safety cues, while peripheral areas should focus on enhancing public services and transportation, and meeting basic quality thresholds with green spaces and open areas. Urban renewal within a 15 min walking radius of residential areas is expected to collaboratively improve daily travel experiences and neighborhood quality for both residents and through-travelers, supporting differentiated housing policy development and enhancing overall quality of life. Full article

Bats host a wide range of viruses, including several high-profile pathogens of humans and other animals. The COVID-19 pandemic raised the level of concern regarding the risk of spillover of bat-borne viruses to humans and, conversely, human-borne viruses to bats. From August 2020 to July 2021, we conducted viral surveillance on 254 bats from 10 species across urban, periurban, and rural environments in New Mexico, USA. We used a pan-coronavirus RT-PCR to assay rectal swabs and performed metagenomic sequencing on a representative subset of 14 rectal swabs and colon samples. No coronaviruses were detected by either RT-PCR or metagenomic sequencing. However, four novel viruses were identified: an adenovirus (proposed name lacepfus virus, LCPV), an adeno-associated virus (AAV), an astrovirus (AstV), and a genomovirus (GV). LCPV, detected in a big brown bat (Eptesicus fuscus), is more closely related to canine adenoviruses than to other bat adenoviruses, suggesting historical transmission between bats and dogs. All virus-positive bats were either juvenile or adult individuals captured in urban environments; none exhibited obvious clinical signs of disease. Our findings suggest limited or no circulation of enzootic coronaviruses or SARS-CoV-2 in southwestern U.S. bat populations during the study period. The discovery of a genetically distinct adenovirus related to canine adenoviruses highlights the potential for cross-species viral transmission and underscores the value of continued virome surveillance in animals living with and near humans. Full article

National parks are key tools for safeguarding ecosystem health, yet their conservation performance remains unclear. Comprehensive evaluations are crucial for guiding targeted and effective conservation strategies. This study employed the Vigor–Service–Resilience (VSR) framework together with causal inference models to assess the role of Huangshan National Park (HNP) in promoting ecosystem health and to examine the heterogeneity of its ecological outcomes from 2010 to 2020. The results indicate that (1) ecosystem health improved significantly across the region, with 69.5% of pixels showing positive change, particularly in ecosystem services and vigor; (2) compared with matched unprotected sites, HNP enhanced EH by 5.7% in 2010, 3.4% in 2015, and 6.5% in 2020, and also generating positive spillover effects within 30 km of its boundaries; (3) conservation impacts differed notably across socio-ecological conditions, with greater benefits observed in areas of lower elevation, gentle slopes, and reduced precipitation. These findings provide robust causal evidence of the protective value of HNP and underscore the importance of targeted and cost-efficient management strategies to optimize conservation outcomes and support sustainable regional development. Full article

This study aims to explore whether and how data elements affect the green total factor productivity (GTFP) of China’s logistics industry, and conducts empirical tests using the super-efficiency SBM model, Malmquist exponential model, and spatial Dubin model. Based on the relevant data of 30 provinces in China from 2013 to 2021, we employ the Super-efficiency SBM model and the Malmquist dynamic index model to calculate the green total factor productivity of the logistics sector. We then establish a three-tier evaluation framework for data elements, employ the entropy method to determine the weighting of each indicator, and utilize linear weighting to calculate the comprehensive evaluation value of data elements. By incorporating appropriate control variables and employing the spatial Durbin model, this study examines the impact of data elements on the GTFP of the logistics industry. It is found that data elements have a contributing effect on improving GTFP of the logistics industry in the local region as well as a positive spillover effect on the neighboring regions, and this is achieved by improving the level of technical progress. In addition, the coefficients are decomposed into direct, indirect, and total effects by partial differentiation, again verifying the above conclusions. This study investigates the impact of data elements on GTFP in the logistics industry from theoretical mechanisms and empirical tests, and analyzes the dual impact of data elements and other factors on the local region and neighboring regions. The findings of this study can provide references for better empowering the development of the logistics industry with data elements. Full article

Sustainable agricultural development requires ensuring food security while preserving essential ecological conditions. This study incorporated ecosystem service value and carbon emissions as the positive and negative ecological outputs of agriculture, respectively, to account for the AGEE of 31 Chinese provinces from 2012 to 2021 and to analyse its spatiotemporal characteristics. The Malmquist Index was employed to calculate the green total factor productivity (GTP) as a quantitative indicator of AGEE dynamics, providing further insights into the sources and equilibrium of AGEE growth, as well as provincial-level improvement paths. Furthermore, the Spatial Durbin Model was applied to systematically analyse the influencing factors and their associated spatial spillover effects. The results show the following: (1) AGEE demonstrated steady improvement, with a mean value of 0.576, and was spatially concentrated along a northeast–southwest axis, exhibiting regional disparities and polarisation. (2) GTP consistently exceeded 1, indicating overall AGEE growth, primarily driven by technological scale expansion. Regional imbalances in AGEE growth had emerged, with heterogeneous causes across economic regions. Three identified AGEE improvement paths—technological catch-up, green innovation, and technological progress—varied by province, with green innovation being the most common priority. (3) AGEE exhibited spatial autocorrelation, with rural income, adequate irrigation, and cropping structure promoting AGEE. Effective irrigation also exhibited a positive spatial spillover effect, whereas industrial structure hindered AGEE. These findings provide valuable insights for advancing green agricultural practices and sustainable regional development. Full article

As China advances toward its “Dual Carbon” goals, clarifying the role of the digital economy (DE) in reducing urban carbon emissions is of growing importance. This study uses panel data from 274 Chinese prefecture-level cities (2011–2022) and applies benchmark regression, the Spatial Durbin Model (SDM), two-regime SDM, threshold analysis, and mediation effect modeling to examine the impact of the DE on carbon emission intensity (CEI) and its spatial spillover effects. Results show that the DE significantly reduces CEI through both direct and indirect channels. Spatial analysis reveals that the DE’s spillover effect is most pronounced within a 500 km range. Regionally, the DE has a stronger inhibitory effect on CEI in eastern and western regions, while its effect in the central region is weaker or even reversed, likely due to reliance on carbon-intensive industries. Resource-based cities exhibit stronger spatial spillovers than non-resource-based ones, suggesting greater potential for DE-driven low-carbon transitions. A threshold effect is also identified at a DE index value of 0.0326, beyond which the marginal benefits decline. Pathway analysis indicates that while the DE improves production efficiency, it does not significantly promote green, high-value-added transformation, partially masking its carbon reduction effects. These findings highlight the need for tailored regional strategies to enhance the low-carbon potential of the DE. Full article

As a model compound for lignin derivatives, anisole and its conversion are crucial for the upgrading of biomass resources. Anisole molecule contains a characteristic aryl ether bond (C_aryl-O-CH₃); therefore, the selective cleavage of the C-O bond to efficiently produce high-value chemicals poses a significant challenge. Constructing bimetallic synergistic active sites through tuning the metal-support interface is considered an effective strategy. In this work, the WO₃-promoted Pt/SiO₂ catalysts were investigated to enhance the performance of anisole hydrodeoxygenation (HDO) to hydrocarbons. Experimental results demonstrate that WO₃ significantly promotes HDO selectivity, increasing from 37.8% to 86.8% at 250 °C. Moreover, moderate doping improves low-temperature (<250 °C) HDO activity, confirming the presence of synergistic effects. In contrast, excessive WO₃ suppresses anisole conversion. Characterization results reveal that WO₃ stabilizes metallic Pt and facilitates H₂ dissociation. Concurrently, strong hydrogen spillover between Pt and WO₃ promotes oxygen vacancy formation on WO₃. This transforms disordered adsorption of anisole on SiO₂ into directed adsorption of the anisole’s oxygen species onto WO₃. This work achieves high anisole HDO selectivity through the Pt-WO₃ interface tuning, offering novel insights for efficient lignin conversion. Full article

In the context of the urgent green transformation of China’s transportation sector, environmental regulation (ER) provides an essential opportunity to promote the green development of the transportation sector. This paper proposes a research framework to elucidate the spatial impacts of ER on transportation’s green transformation. First, the green total factor productivity (GTFP) level of China in 2018–2022 is assessed using the super efficiency SBM-GML model that considers non-desired outputs, and the spatial heterogeneity characteristics of transportation’s green transformation are analyzed. Then, the level of ER is quantified, and the spatial Durbin model is applied to reveal the spatial–regional heterogeneous linkage effect of ER on the green transformation of transportation. The results of the study are as follows: (1) The green level of China’s transportation has been increasing, but regional disparities are still obvious. Specifically, the spatial pattern of greening level is the Eastern region > Northeastern region > Central region > Western region. (2) The transportation’s green level of Chinese provinces, in general, shows strong spatial correlation, exhibiting increasingly obvious ‘high-high’ and ‘low-low’ clustering patterns. (3) Environmental regulation has a positive spatial spillover effect and a non-linear impact on the green development of transportation, showing an inverted ‘U’-shaped relationship. Further analysis reveals that there is obvious heterogeneity in the impact of ER on the green transformation of transportation in the eastern, central, and western regions. The results of the study provide reference values and suggestions for the formulation of more targeted regional transport development policies and dynamic environmental impact policies. Full article

This study examines how hotel characteristics and urban spatial context influence tourist satisfaction in Seoul, South Korea, by integrating sentiment analysis of online reviews with regression modeling. Drawing on 4500 TripAdvisor reviews from 75 hotels, sentiment scores were extracted using aspect-based sentiment analysis, and two regression approaches, ordinary least squares (OLS) and spatial autoregressive combined models, were applied to evaluate how hotel specific features, such as the age and scale of the hotels and room rates, and their geographic characteristics, such as the proximity to airports and cultural landmarks, affect both emotional sentiment and formal hotel ratings. The OLS model for sentiment scores identified the scale and rating of the hotels as well as the proximity to the airports as key predictors. Additionally, the spatial autoregressive combined model was also statistically significant, suggesting spatial spillover effects. A separate model for the traditional rating revealed weaker associations, with only the hotel’s opening year reaching significance. These findings highlight a divergence between emotional responses and structured ratings, with sentiment scores more sensitive to spatial context. This study offers practical implications for hotel managers and urban planners, emphasizing the value of incorporating spatial factors into hospitality research to better understand the tourist experience. Full article

The establishment of a new green space system based on the green belt has become a new trend in the world. Shanghai’s Outer Ring Ecological Park Belt (formerly the Outer Green Belt) faces challenges of spatial imbalance in recreational service distribution and mismatched supply and demand in functional allocation during its transition from an ecological barrier to a recreational service provider. An approach based on spatial spillover effects serves as a critical solution to address these issues. We integrate RPS and ROS models to build an evaluation framework, map recreational service supply for 2013, 2018, and 2023, delimit core areas via MSPA, and quantify spatial spillovers with models SLM and SEM. The results show that high-value areas of recreational service levels along the ecological park belt have driven the development of neighboring areas through spatial spillovers, with this promoting effect radiating outward from the core zones. As the distance from the core areas increases, the effect weakens, with 400 m as the maximum effect boundary, 1 km as the critical spillover boundary, and unstable effects with decreased significance beyond 2 km. We further conduct localized spatial spillover analysis using representative parks as case studies. The research provides theoretical support and implementation suggestions for the planning and construction of an ecological park belt. Full article

The integration of the digital and real economies (DRI) is an inevitable trend in future economic growth. This study measures DRI levels across 30 Chinese provinces from 2012 to 2022 using a coupling coordination model with panel data and empirically examines DRI’s impact on industrial structure upgrading (ISU) through fixed-effects models, mediation effect models, and panel threshold models. The findings reveal that (1) DRI promotes industrial structure upgrading, a conclusion that remains valid under robustness tests and endogeneity tests; (2) DRI can facilitate ISU by enhancing consumption levels, correcting factor distortions, and accelerating the marketization process; (3) there exists a threshold effect, with a positive effect of DRI on ISU based on the level of digital economy and the scale of the real economy as threshold variables; (4) the impact of DRI on ISU differs across different regions due to differences in policy support and resource allocation; (5) ISU has a significant spatial spillover effect, as shown by spatial econometric analysis. These conclusions offer a new perspective, practical policy implications for China’s high-quality economic development, and strategic insights to enhance industrial competitiveness in the global value chain. Full article

This research evaluates the suitability of Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT) for improving financial return predictions across 15 major worldwide stock indices. The proposed method uses graph modeling to represent financial index relationships which enables the detection of symmetric market dependencies including mutual spillover effects and bidirectional influence patterns. The symmetric network structures become most important during financial instability because market interdependencies strengthen at such times. The evaluation process compares these models against XGBoost and Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM) traditional forecasting approaches. The results of 30 time-series cross-validation experiments show that GNN models produce lower RMSE and MAE values, especially during financial crises and recovery phases and volatile market periods. The models show reduced advantages when markets remain stable. The research demonstrates that graph-based forecasting models which incorporate symmetry effectively detect complex financial relationships which leads to important implications for investment strategies and financial risk management and global economic forecasting. Full article

To advance global climate governance, this study investigates the carbon emission efficiency (CEE) of 110 Chinese resource-based cities (RBCs) using a super-efficiency SBM-GML model combined with kernel density estimation and spatial analysis (2006–2022). Spatial Durbin model (SDM) and geographically and temporally weighted regression (GTWR) further elucidate the driving mechanisms. The results show that (1) RBCs achieved modest CEE growth (3.8% annual average), driven primarily by regenerative cities (4.8% growth). Regional disparities persisted due to decoupling between technological efficiency and technological progress, causing fluctuating growth rates; (2) CEE exhibited high-value clustering in the northeastern and eastern regions, contrasting with low-value continuity in the central and western areas. Regional convergence emerged through technology diffusion, narrowing spatial disparities; (3) energy intensity and government intervention directly hinder CEE improvement, while rigid industrial structures and expanded production cause negative spatial spillovers, increasing regional carbon lock-in risks. Conversely, trade openness and innovation level promote cross-regional emission reductions; (4) the influencing factors exhibit strong spatiotemporal heterogeneity, with varying magnitudes and directions across regions and development stages. The findings provide a spatial governance framework to facilitate improvements in CEE in RBCs, emphasizing industrial structure optimization, inter-regional technological alliances, and policy coordination to accelerate low-carbon transitions. Full article

Establishing scientifically sound and equitable compensation standards is crucial for effective ecological compensation. This study focuses on the quantitative assessment of ecological compensation standards in the water-source areas of the South-to-North Water Diversion Project. Based on the dual perspective of cost and benefit, we embed a three-dimensional dynamic adjustment coefficient—water volume, water quality, and payment capacity—and fully considered spillover effects. Using the AHP-Entropy Method, the allocation ratio of the water-receiving area was scientifically divided, achieving differentiated distribution and dynamic adaptation of the compensation mechanism. The compensation allocation ratio for water-receiving areas was determined, ensuring differentiated distribution and dynamic adaptability in the compensation mechanism. The results show the following: (1) In 2023, the ecological compensation amount for Yangzhou, based on the cost method and the equivalent factor method, ranges from CNY 1.21 billion to 2.53 billion. The amount of compensation after the dynamic game between both parties can avoid the waste of resources caused by over-compensation, and at the same time make up for the shortcomings of under-compensation due to the current water price. (2) Ecological compensation is measured only from the single perspective of the water-source area, without considering the differences in the receiving area. This paper uses the AHP-entropy value method to combine and assign weights, and calculates the apportionment ratio of the main water-receiving areas of Shandong Province in the east line of the South-to-North Water Diversion: for the Jiaodong line, these are Qingdao 20.97% and Jinan 14.53%, and for the North Shandong line, they are Dongying 23.98%, Dezhou 13.68%, Liaocheng 9.47%, and Binzhou 17.37%. (3) The dynamic correction coefficient and game model can effectively balance the cost of protecting the water-source area and the receiving area’s ability to pay, and combination with the empowerment method enhances the regional difference in suitability. Full article

Land is a critical factor of production that contributes significantly to economic growth. However, conventional land use pattern in China has resulted in serious environmental pollution. Now enhancing green land use efficiency (GLUE) has emerged as an effective strategy for improving environmental quality. The development of the digital economy (DE), characterized by low cost and high efficiency, has demonstrated considerable potential in reducing environmental pollutants and enhancing resource allocation. This study employs an extensive analytical framework to analyze the impact of DE development on GLUE across 267 cities in China from 2011 to 2019. The results show that DE exerts a significant effect on improving GLUE, which remains valid after the execution of endogeneity and robustness tests. The research on mechanisms indicates that this promotional effect is primarily achieved through the innovation in green technology and the optimization of industrial structure. Extended empirical tests indicate there is a nonlinear trend, wherein the positive effect increasingly intensifies after green industry innovation and industrial structure optimization exceeds threshold values. There is also a significant short term spillover effect of DE on GLUE, supplemented by long term effects. These findings substantially improve our comprehension of the connection of DE and land use, while providing practical policy recommendations for promoting environmentally sustainable development and land green utilization. Full article