Search Results (168)

Bike-Sharing Systems (BSS) are increasingly viewed as a sustainable and flexible component of urban mobility, particularly in rapidly growing cities such as Casablanca. The effectiveness of such systems depends, critically, on strategic planning decisions, most notably the number and location of stations. This study proposes a spatially explicit modeling framework to support the design of a BSS network based on urban demand characteristics. Ten categories of urban attractors are identified and grouped into four main criteria: socioeconomic activities; education, culture, and health; leisure spaces; and public mobility hubs. A modified Huff model is used to estimate the spatial distribution of potential demand and to identify candidate locations for bike-sharing stations. Walking accessibility is represented by shortest-path distances on the pedestrian network. Building on these demand estimates, the station deployment problem is formulated as a minimum set covering location problem whose objective is to determine the smallest number of stations required to cover a predefined proportion of total mobility demand within a 1000 m walking-network distance. Coverage is constrained separately for each arrondissement, while stations located near administrative boundaries may serve demand in neighboring arrondissements. At the baseline $\gamma =0.5$, the model selects 45, 70, and 154 stations for coverage targets of 60%, 80%, and 100%, respectively. The proposed approach provides a systematic and data-driven basis for BSS planning and helps integrate bike sharing into a more efficient, environmentally sustainable, and multimodal urban mobility system in Casablanca. Full article

Reducing disparities in industrial pollution emission intensity among cities is key to alleviating spatial environmental inequities within urban agglomerations and promoting inclusive regional sustainable development. Existing research primarily analyzes the impact of commodity market integration on pollution from a macroeconomic perspective, but there is a lack of research on the impact of factor market integration within urban agglomerations on disparities in industrial pollution emission intensity among cities across provincial borders. We use matched data from the China Industrial Enterprise Database and the China Polluting Enterprises Database covering the period 2000–2013, using the inverse of the dispersion of total factor productivity (TFP) to measure the degree of factor market segmentation, thereby assessing the level of factor market integration. By constructing datasets of city pairs within urban agglomerations and distinguishing between city pairs within one province and city pairs across provinces, we arrive at three main results: (1) There are significant differences in the level of integration of factor markets across China’s 11 major urban agglomerations, with the Pearl River Delta and Yangtze River Delta ranking highest, whilst inland urban agglomerations lag significantly behind. (2) For every 1% increase in factor market integration, the difference in industrial pollution emission intensity between cities decreases by approximately 0.58%. The emission reduction effect for inter-provincial city pairs is significantly weaker than that for intra-provincial city pairs, confirming the existence of a significant provincial boundary effect. (3) In regions with well-developed transportation infrastructure and where cities are relatively close to one another, the integration of factor markets across provincial borders plays a more significant role in reducing disparities in industrial pollution emission intensity among cities. These findings not only offer insights for pollution control across administrative boundaries within urban agglomerations but also provide empirical evidence for helping promote the sustainable development of urban agglomerations. Full article

Large-scale monitoring of land rights remains constrained by substantial time requirements, limited spatial coverage, and considerable human resource demands associated with conventional image interpretation and field verification. This study develops an operational Geospatial Artificial Intelligence (GeoAI) workflow for indicative monitoring of land-use compliance by integrating semantic segmentation of land cover within registered land rights (HAT) boundaries with spatial planning information. U-Net and SF-Net architectures were evaluated for temporal monitoring using two models: M3 based on 10 m Sentinel-2 imagery from 2017–2023 and M4 based on 0.07 m orthophotos from 2022–2023. Data augmentation increased the number of M3 samples from 445 to 3560 and M4 samples from 1106 to 8848. The U-Net M3 model achieved an F1-score of 0.961 and an IoU of 0.927, whereas the SF-Net M4 model achieved an F1-score of 0.969 and an IoU of 0.940. At Keera Plantation, the 28–29% difference in estimated oil palm area between M3 and field verification reflects inter-method variation in a heterogeneous landscape rather than model error alone. M3 processed the entire 680,380.99 ha administrative area of East Luwu Regency in only 4 min 31 s to assess operational scalability and monitoring efficiency. The proposed GeoAI workflow is effective for large-scale initial screening and prioritization. However, GeoAI outputs are intended as decision-support evidence and do not replace field verification or legally accountable administrative decision-making. Full article

Island terrain poses a significant challenge in tropical cyclone (TC) track prediction, particularly during the early development of TCs. Using the Weather Research and Forecasting (WRF) model, China Meteorological Administration (CMA) best-track data, and ERA5 reanalysis, we conducted control (CTRL), terrain-removal (Te0P), terrain-enhancement (Te2P), and no-land-sensible-heat (HFX0) experiments for Typhoon Yagi (2024) near Luzon during 1–3 September. CTRL showed a pronounced northward track bias. Te0P shifted westward and closer to observations, whereas Te2P further amplified the northward bias; HFX0 remained close to CTRL. Terrain-height changes substantially modified the surrounding mid-tropospheric environmental flow and asymmetric horizontal-advection potential-vorticity tendency (PVT_h). Although Te0P produced the closest track, its PVT_h orientation deviated most from ERA5, suggesting that the track improvement partly reflects a compensating reduction in the excessive northward response in CTRL rather than a uniformly more realistic dynamical structure. Land sensible heating mainly affected the boundary layer and nearby circulation, with weaker effects on the broader mid-tropospheric flow and track. These results show that terrain dynamics dominate the simulated track response, while land sensible heat provides secondary modulation, and highlights the need to evaluate track, environmental flow, and PVT_h jointly near complex islands. Full article

Balancing decarbonization with grid reliability requires managing renewable volatility through Renewable Portfolio Standards (RPSs) or Capacity Remuneration Mechanisms (CRMs) alongside carbon emission trading (CET). However, their comparative systemic impacts remain unclear. This study evaluates the strategic equivalence of CET-RPS and CET-CRM regulations using a Stackelberg duopoly model. We endogenize grid-side storage investment and parameterize source-storage synergy to establish a rigorous equivalence mapping anchored in a unified macroeconomic penetration target. The results reveal that the CRM exhibits dual systemic impacts contingent on technological readiness. Immature conditions necessitate excessive capacity prices, inducing speculative over-investment. Conversely, mature synergy creates a substitution effect that efficiently offsets public compensation budgets. Furthermore, the dynamic policy phase boundary demonstrates that stricter decarbonization targets require higher technological readiness for the CRM to dominate the RPS in social welfare. Additionally, imposing stringent administrative capacity derating factors on storage fails to alter its physical deployment, instead unintentionally transferring wealth to conventional high-carbon generators. Regulators must therefore synchronize capacity market deployment with storage technology maturity and adopt dynamic capacity accreditation to prevent such distributional distortions. Full article

Inter-provincial administrative boundary areas are particularly vulnerable to ineffective regional pollution governance because they are simultaneously affected by transboundary pollution diffusion and administrative fragmentation. Existing governance practices, however, continue to rely heavily on territorially based regulation and administrative coordination, while the potential of cross-regional green-technology collaboration to address boundary pollution has received insufficient attention. Using panel data for Chinese prefecture-level cities from 2011 to 2023, this study systematically examines the impact of green innovation collaboration (GIC) on pollution control in areas along interprovincial administrative boundaries through two-way fixed-effects, instrumental-variable, Heckman two-step, and spatial Durbin models. The results show that, first, GIC significantly reduces pollution in these areas, and this finding remains robust across a range of robustness checks. GIC also generates significant spatial spillovers: while reducing local boundary pollution, it improves air quality in neighboring cities. Second, the heterogeneity analysis indicates that this effect is more pronounced in cities facing greater pollution-control pressure, lower fiscal pressure, and higher levels of openness. The regional results also reveal certain differences. Third, the mechanism analysis shows that cross-regional collaborative governance and industrial upgrading constitute two relatively independent parallel transmission pathways rather than a sequential chain, and their relative contributions vary with city conditions. These findings provide empirical evidence for improving interprovincial collaborative governance, facilitating the cross-regional diffusion of green technologies, and implementing differentiated environmental policies. Full article

The core predicament of energy transition lies not in the availability of clean technologies, but in whether an economy possesses the institutional capacity and social foundation to systematically regulate its carbon-energy metabolic processes. Drawing upon co-evolutionary theory from evolutionary economics, this paper constructs a composite indicator of Low-Carbon Green Energy Eco-Co-evolution (LCEE) encompassing three functional dimensions: efficiency advancement, kinetic energy replacement, and boundary adherence. Concurrently, by integrating innovation ecosystem theory with inclusive development theory, we propose the concept of “Inclusive Potential of Regional Innovation Ecosystems” (IEP), characterizing the systemic potential for transforming innovation outcomes into social welfare across four dimensions: Knowledge Matrix Abundance (KMF), Cultural Capillary Permeation (CCP), Technological Community Succession (TCS), and Social Root Nourishment (SRN). Taking China’s 2016 intellectual property (IP) powerhouse construction pilot as the institutional prototype of Industrial Intellectual Property Upgrading Reform (IPR), we incorporate IPR, IEP, and LCEE into a unified causal analytical framework, proposing a testable transmission logic of ‘institutional supply → ecological development → co-evolutionary synergy. Using panel data from 30 Chinese provincial-level administrative regions over 2010–2022, we employ a Spatial Durbin Difference-in-Differences (SDM-DID) model to identify the direct and spatial spillover effects of IPR on LCEE, and embed a Double Machine Learning (DML) framework to test the mediating mechanism of IEP while controlling for high-dimensional nonlinear interference. The findings reveal that IPR exerts a significant and robust direct promoting effect on LCEE, generating positive spatial spillovers to neighboring regions through the public disclosure of patent information. IEP significantly promotes local LCEE, yet its spatial spillover lacks statistical support due to structural conflicts in inter-dimensional transmission attributes. IEP plays a significant partial mediating role between IPR and LCEE, with the indirect effect accounting for over one-third of the total effect, a finding robust to alternative machine learning algorithms, sample split adjustments, and exclusion of contemporaneous competing policies. Sub-path tests reveal that KMF bears the strongest mediating efficacy, serving as the primary transmission channel, while CCP exhibits full mediation—the institutional effect on LCEE in the cultural dimension depends almost entirely on the mediating transformation through the public cultural service system. Heterogeneity analysis further demonstrates full mediation in the Low-Carbon Green Energy Eco-Kinetic Replacement (KER) dimension, indicating that the institutional catalytic effect on clean energy substitution must be realized through IEP transformation. This paper provides empirical evidence for the proposed causal pathway through which institutional public goods indirectly enhance the synergistic quality of carbon-energy transition via the inclusive potential of innovation ecosystems, providing theoretical foundations and policy implications that, while grounded in China’s institutional context, may offer valuable reference points for emerging market economies facing similar dual pressures of technological constraints and green transition. Full article

Land-use conflicts in non-urbanized areas are fundamentally governance problems rather than purely environmental ones: sustainability outcomes increasingly depend on integrated, cross-sectoral decision-making reconciling forestry, agriculture, tourism, infrastructure, and urbanization within a finite land resource. This study examines whether statutory land acquisitions by a public forest administration can be understood as such a governance instrument rather than simply forest-area expansion, using an original transaction-level database of 911 land purchases by the Polish State Forests (Lasy Panstwowe) through statutory pre-emption rights between 2022 and mid-2026. The database covers 2806.1 hectares and, for the 903 transactions with a determinable price, approximately 114.2 million PLN. Using descriptive statistics, concentration indices (Gini, Herfindahl–Hirschman), an exploratory hedonic-style log–log regression of unit price on parcel area with location and year fixed effects, and a spatial-autocorrelation analysis (Moran’s I), the study examines spatial concentration, price differentiation, and parcel-size effects. Results show pronounced sub-regional concentration (county-level Gini = 0.615, more than double the voivodeship-level value of 0.284), a systematic price premium for parcels below 0.5 ha, and a dominant role of location over parcel size in explaining price variation (R-squared rising from 0.042 to 0.198 with location fixed effects); these are descriptive associations rather than causal estimates, given the absence of parcel-level quality covariates and a fully specified spatial–econometric model. The findings support interpreting statutory pre-emption purchases as a market-based institutional mechanism contributing to boundary rationalization, ownership consolidation, and mediation of competing land-use pressures, with implications for county-level monitoring and cross-sectoral coordination with spatial planning. Full article

The Central Environmental Protection Inspection (CEPI) represents a landmark institutional arrangement for the centralization of environmental supervision authority from local governments to the central government. It has played a significant role in correcting the distortion of local government incentives for environmental governance under decentralized management. However, the persistence and spatial heterogeneity of its policy effects remain to be further examined. This paper treats the CEPI, which was progressively implemented from 2016, as a quasi-natural experiment of centralizing environmental supervision authority. Using daily city-level panel data from 333 Chinese cities over the period 2015–2022, we employ a multi-cutoff time regression discontinuity design in time to evaluate its policy effects. The findings are threefold. First, the CEPI significantly reduces urban concentrations of AQI, PM_2.5, PM₁₀, SO₂, NO₂, and CO, while O₃ concentrations increase significantly over the same period, indicating that the centralization of supervision authority is effective in mitigating conventional primary pollutants but faces limitations in addressing secondary pollutants. Second, the policy effects vary across inspection rounds, with the first round and the “look-back” generating larger short-run coefficients than the second round. These differences in short-run inspection-period coefficients across rounds indicate that marginal policy responsiveness diminishes as the inspection program becomes institutionalized. Third, the policy effects display significant spatial heterogeneity: cities in northern regions, resource-based cities, and cities with historically moderate air quality experience more pronounced improvements, while the grouping effect of administrative hierarchy is not statistically significant for most pollutants. This indicates that the governance effects of centralizing supervision authority vary across city characteristics but do not simply follow an administrative hierarchy gradient. This study provides empirical evidence for understanding the boundary of the effectiveness of centralizing environmental supervision authority and offers policy implications for optimizing the vertical allocation of environmental governance responsibilities. Full article

Senior leadership turnover in Christian Higher Education Institutions (CHEIs) necessitates the identification of effective self-leadership practices that preserve intergenerational memory and Reformed traditions. Using a qualitative interpretative phenomenological analysis (IPA), this study explored the lived experiences of five senior-level administrators averaging 22.2 years of leadership experience in CHEIs. The findings identified five core themes shaping their leadership: (1) efficiency and Self-Awareness, characterized by the use of digital boundaries and organizational systems; (2) fulfillment, derived from a deep sense of “calling” and the institutional mission; (3) fortitude, built on theological principles of God’s sovereignty to navigate administrative stress; (4) applicability and Intellectualism, rooted in the Reformed confessional heritage and “treasure trove” of creeds; and (5) integration, where spiritual practices, such as breath prayers and scripture-based cues, are woven into professional routines. Crucially, the research revealed a significant disconnect where leaders utilized robust self-leadership strategies for professional growth but often struggled to apply parallel techniques (such as goal setting or self-observation) to their personal spiritual disciplines. The study concludes by proposing a Spiritual Self-Leadership Framework that integrates the Five Solas of the Reformation with self-leadership theory to provide a roadmap for individual sanctification and institutional flourishing. Full article

Understanding vegetation resilience gradient effects across hierarchical administrative borders is critical for cross-jurisdictional land management yet remains underexplored. This study integrates an AR(1) model with XGBoost-SHAP analysis to assess resilience and its drivers across provincial, municipal, and county borders in the Beijing–Tianjin–Hebei (BTH) region using NDVI data (2000–2025). The results show that (1) vegetation resilience across hierarchical border belts experienced an initial decline followed by recovery. A notable shift in resilience optimality was observed from city borders in 2005 to provincial borders by 2020. Gradient effects were stronger in northern city borders. The stable-fluctuating type dominated, followed by peak and valley types. (2) Precipitation, tree age, and altitude suppress gradient formation. Conversely, cross-boundary economic disparity, nighttime light differences, and land use composition tend to be associated with amplified gradient effects in a hierarchical manner: cropland and built-up expansion intensify gradients at provincial borders but reduce them at city borders, suggesting a potential role of governance coordination. (3) Based on these findings, a tiered governance framework is suggested—northern high-gradient provincial and city borders are proposed as priority areas for intensive interventions, while county borders (where gradient effects are weakest) may benefit from moderate, low-intensity interventions focused on maintaining land use continuity. At the provincial level, stronger inter-provincial coordination—through cross-boundary ecological compensation and harmonized environmental standards—may help mitigate gradient effects. Collectively, this study provides insights for cross-jurisdictional land governance in the BTH region and other analogous urban agglomerations. Full article

Conservation units for traditional village clusters are often delineated by administrative boundaries or spatial proximity. Yet rural built heritage is shaped by historical routes, terrain conditions, cultural homology, settlement morphology, and rural landscape settings. This mismatch is especially evident in mountainous regions, where conservation relevance does not necessarily follow planar distance. To address this issue, this study proposes relational contiguity as an operational concept for cluster-based conservation of traditional village heritage. Using 61 nationally recognized traditional villages in Gaoping City, Shanxi Province, China, as a case, we develop a socio-spatial network framework. The framework integrates composite node quality, cultural homology, MCR-based cost distance, inter-village association strength, and node-role differentiation into a modified spatial interaction model. This allows conservation relations to be identified as culturally meaningful, spatially plausible, and governance-relevant. The results show that only 167 of 1830 village pairs form effective links. This selective heritage conservation network is structured by the Dan River corridor, historical trade routes, high-value heritage nodes, and culturally homologous village groups. Four differentiated conservation units are identified: the fortified landscape conservation unit, the Dan River trade-corridor coordination unit, the landscape-ritual continuity unit, and the peripheral authenticity conservation unit. The study provides a planning support framework for translating inter-village heritage relations into coordinated conservation units for rural built heritage. Full article

In China’s national parks, Tianchuang were located on land within boundaries that are excluded from national park administration to reduce governance conflicts. According to existing research on boundary optimization of protected area, Tianchuang are routinely regarded as fixed constraints or contextual backgrounds rather than optimization targets. Based on systematic conservation planning (SCP) theory and integrated models of MaxEnt, InVEST, and Marxan, and taking Tianchuang as dynamically adjustable spatial variables, this study aims to explore the boundary optimization schemes of Tianchuang areas in Wuyishan National Park of China. The main findings are as follows: Firstly, highly suitable habitats for representative species are predominantly concentrated within the north-central region of the park, while Tianchuang patches generate significant edge effects and pose critical disturbances to ecosystem integrity. Secondly, human activity intensity demonstrates marked spatial heterogeneity, indicating distinct variations in socioeconomic impacts and management difficulties among Tianchuang patches. Thirdly, based on irreplaceability, landscape connectivity, and patch fragmentation, three optimization strategies are proposed, namely incorporation, retention, and provisional retention, balancing ecological protection and community development. This study provides a scientific basis for the differentiated management of Tianchuang areas in Wuyishan National Park and offers a practical pathway for the boundary optimization and spatial governance of protected areas in China. Full article

Smart-city governance increasingly relies on data infrastructures to connect public agencies, digital platforms, and urban services; however, complex emergencies continue to expose fragmentation in information sharing, administrative responsibilities, and cross-boundary coordination. A key unresolved question is whether data-driven policy experimentation can strengthen the institutional foundations of emergency collaboration. In this study, we examine China’s National Big Data Comprehensive Pilot Zones as a systemic governance intervention and apply a multi-period difference-in-differences model to estimate the effect of pilot-zone construction on the policy-text-based institutionalization of emergency collaboration, using provincial panel data for 30 Chinese provinces from 2010 to 2022. The results show that pilot-zone construction significantly strengthens institutionalized emergency collaboration in provincial policy systems. Mechanism tests provide evidence consistent with two complementary pathways: emergency-related technological innovation, measured by granted patents screened through IPC/CPC classifications and title–abstract keywords, supports task-specific capacities such as risk sensing, early warning, emergency communication, command support, and resource allocation; digital government strengthens administrative interoperability, data sharing, platform-based coordination, and standardized interdepartmental procedures. Heterogeneity analyses show stronger effects in eastern, middle-income, and severely aging regions, suggesting that policy effectiveness depends on implementation capacity, absorptive capacity, and emergency-service demand. This study contributes to systems governance and smart-city research by showing how data-driven policy experimentation can shape the formal institutionalization of emergency collaboration. The findings should be interpreted as evidence of institutionalized policy attention and formal collaborative arrangements rather than direct evidence of field-level emergency response performance. Full article

Maritime transportation, a traditionally polluting sector, is engaged in sustainable innovation; advanced detection of marine pollution incidents can help control improvements in this sector. However, coastal and marine environmental governance is increasingly constrained by fragmented monitoring architectures in which environmental, operational, and regulatory datasets remain distributed across institutions and jurisdictions. Comprehensive governance mechanisms that cross the sea–land continuum are limited. Public authorities, port administrations, research institutes, and private operators independently monitor marine pollution, vessel movements, coastal pressures, and urban and ecological risks; however, these data streams remain siloed across organizational, sectoral, and jurisdictional boundaries. The absence of interoperability, real-time exchange, and coordinated analytics generates a gap between monitoring capacity and regulatory effectiveness, resulting in delayed detection of multi-risks, such as pollution incidents. Weak governance and assignment of responsibility and largely reactive enforcement practices further reinforce the problem. Anticipatory interventions are needed to improve coastal and marine sustainability. This paper examines the EMMERA (East Med Cross-border Marine Environmental Risk Assessment through E-Platform Integrated Data Management) platform established by three port authorities as a data-centric intervention designed to address some of these structural limitations. Implemented in port and coastal environments in Cyprus, Greece, and Israel, EMMERA integrates heterogeneous static and dynamic data sources—including satellite observations, administrative records, vessel information, and drone-based monitoring—into a unified operational framework accessible to competent authorities. Through data fusion, cross-validation, and automated anomaly detection combined with targeted drone verification, the platform aims to transform fragmented monitoring streams into coherent, actionable environmental intelligence, strengthening the evidentiary basis for regulatory intervention. The paper presents the platform design and provides a baseline assessment. It argues that EMMERA’s primary contribution lies not in the introduction of additional monitoring tools, but in enabling more effective coastal and marine environmental governance through integrated data infrastructures. EMMERA is proposed as a governance-oriented integrated data infrastructure whose anticipated contribution lies in improving institutional interoperability, risk visibility, and evidence generation for environmental oversight, even as operational effectiveness will require future evaluation following sustained deployment. More broadly, the paper proposes that integrated data architectures can recalibrate environmental governance, shifting emphasis from post hoc documentation toward anticipatory, coordinated, and performance-oriented regulatory practices. Full article