Search Results (411)

The coupling coordination of urbanization and urban resilience is a key issue for achieving sustainable urban development. Taking 49 prefecture-level and above cities in the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) —China’s three major coastal urban agglomerations—as research objects, this paper constructs an evaluation index system for urbanization and urban resilience, and employs the CRITIC–entropy weight composite method, the coupling coordination degree model and kernel density estimation to measure the evolutionary characteristics of coupling coordination between urbanization and urban resilience in the three agglomerations during 2013–2023, and further identifies the key influencing factors using a panel fixed-effects model. The results show that (1) the coupling coordination degree of the three urban agglomerations increased continuously, with the PRD taking the lead in 2023 (0.6650), the YRD ranking second (0.6315) and the BTH ranking third (0.5627); however, their coupling coordination paths diverged markedly, specifically manifesting as a catch-up convergence pattern in the BTH, a balanced advancement pattern in the YRD and a polarization-divergence pattern in the PRD. (2) Opening-up and digital economy development are robust positive drivers of the coupling coordination level, and their positive effects are largely universal across regions; urban population agglomeration and government intervention constitute significant negative constraints, among which the inhibitory effect of government intervention exhibits genuine regional heterogeneity, being most prominent in the YRD, followed by the PRD, while failing the significance test in the BTH; technological innovation fails to pass the significance test; the full-sample effect of spatial structure is insignificant, but its influence exhibits significant regional heterogeneity, with a significantly positive association in the PRD. This study systematically reveals the regional differentiation rules governing the synergistic evolution of urbanization and resilience in the three urban agglomerations, providing empirical support for differentiated policies to promote the deep integrated development of urbanization and urban resilience. Full article

In the context of the global implementation of the United Nations 2030 Sustainable Development Goals (SDGs), urban green development serves as a core practical pathway to advance SDG8 (Decent Work and Economic Growth), SDG11 (Sustainable Cities and Communities), and SDG15 (Life on Land). This study constructed a three-dimensional evaluation framework encompassing the green economy, green ecology, and green society, and utilized panel data from 282 Chinese prefecture-level cities from 2009 to 2021. By integrating the CRITIC weighting method, spatial autocorrelation, the Standard Deviational Ellipse (SDE) approach, and the Dagum Gini decomposition, we systematically quantified multi-scale spatiotemporal evolution and disparity patterns at the national scale, as well as across four major economic zones and five core urban agglomerations. Nationwide, the composite green development index rose from 0.422 to 0.522 (+23.70%), while the overall Dagum Gini coefficient declined from 0.072 to 0.053 (−26.39%), with the spatial center of gravity gradually shifting toward the southwest. Eastern China persistently maintained the highest development level; Western China achieved the fastest cumulative growth (26.43%), and Northeastern China lagged behind with the lowest growth rate (20.10%). Among five major urban agglomerations, the Yangtze River Delta (YRD) and Pearl River Delta (PRD) shared an identical average score of 0.582, whereas the Chengdu–Chongqing (CC) agglomeration recorded the highest growth of 33.07%. This research contributes multi-scale empirical evidence for localized SDG implementation in China and provides differentiated policy insights for cross-regional green transition governance. Full article

Clarifying ecosystem service interactions under urbanization facilitates integrated ecological governance. This study took the rapidly urbanizing Su-Xi-Chang agglomeration in the Yangtze River Delta as the research area and applied the InVEST model to evaluate spatiotemporal variations in carbon storage, soil retention, water yield, and habitat quality from 2000 to 2023. The coupling coordination degree model and self-organizing map model were adopted to analyze urbanization–ecosystem interactions and the evolution of ecosystem service bundles, while the GeoDetector model was used to identify key socio-ecological drivers. The results reveal significant spatiotemporal divergences among the four ecosystem services. Carbon storage and habitat quality declined, while water yield and soil retention increased. Carbon storage and soil retention hotspots were persistently concentrated in the Yixing–Liyang Mountainous Area. Pairwise correlations further show that the synergy between water yield and soil retention strengthened over time, whereas their trade-offs with habitat quality intensified. The coupling coordination between urbanization and ecosystem services remained at a primary level yet exhibited a clear trajectory from imbalance toward optimization after 2010. Four ecosystem service bundles were identified, among which the urban-function-dominated bundle expanded by 190.39% from 2000 to 2023, indicating progressive spatial lock-in of urban land use. Differentiated zoning and targeted restoration strategies are proposed to reconcile urban development and ecological conservation. This study offers scientific references for ecological spatial optimization and refined ecological management in the Yangtze River Delta. Full article

This study examines urban green infrastructure (UGI) branding as a governance practice shaped by institutional homogenization and strategic responses within China’s multi-level policy framework. Against the backdrop of global sustainability agendas, UGI branding is conceptualized as a policy-oriented, symbolically embedded instrument for communicating cities’ commitments to green development and climate resilience. Using an institutional “identity–label–image” framework, integrated with policy diffusion theory and multi-center regional development models, we systematically analyze historical brand-label data from 27 core cities in the Yangtze River Delta. Our findings reveal three key patterns: (1) brand diffusion follows dual pathways of mandatory and imitative homogenization, with evolutionary rhythms tied to five-year planning cycles, generating discernible “policy waves”; (2) within polycentric regional structures, core cities act as institutional “interpreters” and benchmarks, while peripheral cities pursue imitation-driven differentiation, reflecting complex dynamics of collaboration and competition; and (3) urban identities expressed through brand labels progressively align with substantive sustainability transitions, aiming to enhance regional competitiveness and upward recognition. We conclude that UGI branding constitutes a deep-seated mechanism of sustainable urban governance, offering a novel theoretical lens on China’s institutional logic of city branding and providing actionable insights for optimizing collaborative brand governance and integrated green infrastructure planning in urban agglomerations. Full article

Digital infrastructure (DI) plays a dual role in the low-carbon transition. It supports economic operation but also consumes substantial energy. This study explores DI’s impact on carbon emission efficiency (CEE) using data on 41 cities in China’s Yangtze River Delta from 2011 to 2024. The methods used in this study include a two-way fixed effects model, mediation analysis, a panel threshold model, and a spatial Durbin model. The results show that the impact of DI on CEE is U-shaped. Industrial upgrading and technological innovation are the potential channels through which DI affects CEE. Energy efficiency has a single threshold value of 8.533. DI enhances CEE when energy efficiency exceeds this threshold. Spatial analysis indicates that both the direct and indirect effects of DI follow a U-shaped pattern. Heterogeneity analysis indicates that the environmental impact of DI varies depending on resource endowments, policy environments, and economic development levels. This study provides insights for global urban agglomerations to balance digital transformation and sustainable development. Full article

Urban agglomerations are increasingly exposed to shocks that extend across administrative boundaries through infrastructure systems, industrial chains, population mobility, and shared ecological spaces. Existing urban resilience research has predominantly assessed city-level capacity, while comparatively less attention has been paid to the relational structures associated with differences in resilience capacity and geographic proximity. This study examines the model-implied spatial correlation network of urban resilience across 41 cities in the Yangtze River Delta from 2013 to 2022. A multidimensional resilience index covering economic, infrastructure, social, and ecological dimensions was constructed using the entropy weight method and directed intercity interaction potentials were estimated using a modified gravity model and analyzed through social network analysis. The results show that overall resilience improved during the study period, although substantial cross-city disparities persisted. Under the baseline row-specific mean threshold, network density remained broadly stable, fluctuating between 0.2476 and 0.2506 and decreasing slightly from 0.2506 in 2013 to 0.2482 in 2022. The model-implied network remained fully reachable but relatively sparse, with persistent positional differentiation. Nanjing and Hangzhou consistently occupied leading total-degree positions, while Hefei, Nanjing, Hangzhou, Huangshan, and Chuzhou repeatedly exhibited relatively high betweenness. The block-model structure was also comparatively stable, with only three cities changing block membership between 2013 and 2022. Robustness analyses further showed that broad positional differentiation was more stable than exact density levels, outward-oriented rankings, and brokerage positions. Overall, improvements in city-level resilience did not translate into substantial densification or reorganization of the regional network, highlighting the need to distinguish internal resilience capacity from model-implied network position when designing differentiated regional coordination strategies. Full article

In an era prioritizing high-quality development and ecological civilization, optimal land resource allocation is vital for overcoming resource constraints and fostering new quality productive forces, with green technology innovation (GTI) serving as a key driver. Using data from 41 Yangtze River Delta cities (2003–2022), this study measures urban land resource misallocation (ULM) via the factor relative distortion coefficient and employs fixed effect, mediating effect, and spatial Durbin models to explore GTI’s impact and spatial spillovers on ULM. Results show a fluctuating yet rising ULM trend with significant spatial disparities. Land allocation efficiency is higher in central and southeastern coastal cities, while western and northern areas exhibit high-misallocation agglomeration. GTI significantly reduces ULM, particularly in non-resource-based cities, mainly through industrial structure optimization and agglomeration. Spatial spillover analysis reveals that GTI not only improves local land allocation but also positively influences neighboring regions via technology spillovers and industrial synergy. These findings suggest that incentive policies should strengthen GTI to enhance region-wide land utilization efficiency. Full article

Financial development can influence carbon emissions through capital allocation, technological support, and policy transmission. To investigate the inherent association between grassroots inclusive financial institutions and territorial green transformation, this study establishes a city-level panel dataset of the Yangtze River Delta urban agglomeration covering the period from 2010 to 2022. Within the analytical framework of the Spatial Durbin Model, this research decomposes the baseline effect, functional transmission pathways, and cross-sectional heterogeneity of the impact of the development of small loan company (SLC) providers on urban carbon intensity. The results show that SLC expansion significantly increases local carbon emission intensity and produces spatial spillover effects across neighboring cities. Mechanism analysis indicates that SLCs increase emissions mainly by supporting the expansion of small- and micro-sized enterprises in energy-intensive manufacturing sectors, while their role in promoting green technological innovation remains limited. Further analysis shows that local government willingness to pursue green transition weakens the carbon-increasing effect of SLCs, whereas digital inclusive finance strengthens it. The effect also varies by location and regulatory environment, with stronger effects in medium-distance cities and under lower regulatory intensity. These findings reveal how grassroots inclusive financial institutions affect regional carbon outcomes and offer policy implications for aligning inclusive finance with green transition goals. This paper innovatively transcends the conventional low-carbon research paradigm focusing on macro-finance and large formal financial institutions, and instead takes SLCs, a typical micro-level inclusive finance entity, to explore their unique paths affecting regional carbon emissions, and clarifies their action boundaries from multiple dimensions including government governance and digital finance empowerment, which enriches interdisciplinary research literature integrating inclusive finance and low-carbon economy. But this study has limitations: its sample is limited to the Yangtze River Delta urban agglomeration, so the universality of the conclusion needs further verification. This research provides theoretical support and policy reference for regulating the sustainable development of the small loan industry, promoting the integration of inclusive finance and green low-carbon transformation, and advancing high-quality regional low-carbon development. Full article

Low-carbon sustainable development requires a better understanding of how urban land expansion reshapes carbon emission patterns within and across cities. Impervious surface expansion is a visible land use expression of urbanization and a key carrier of energy consumption, industrial activity, and ecological loss. Yet, its cross-city effects on carbon emissions remain insufficiently understood, particularly in highly integrated urban agglomerations. Using a balanced panel of 41 cities in the Yangtze River Delta (YRD), China, from 2008 to 2022, this study combines EDGAR gridded CO₂ emissions, annual land cover data, global and local spatial autocorrelation analysis, and a two-way fixed-effects Spatial Durbin Model (SDM) to examine the local and spillover effects of impervious surface expansion. The results show that impervious surfaces and carbon emissions both evolved from core agglomeration toward peripheral diffusion, while carbon emissions maintained significant positive spatial autocorrelation, with Moran’s I remaining positive and significant throughout the study period. SDM estimates indicate that local impervious surface expansion significantly increases local carbon emissions, whereas the estimated indirect effect on neighboring cities is significantly negative. Effect decomposition confirms a positive direct effect and a negative indirect effect under both inverse-distance and contiguity weight matrices. A rolling-window analysis further shows that the negative spillover effect strengthened over time. These findings demonstrate that urban land hardening should be evaluated not only as a local emission driver but also as a spatially embedded process within regional carbon governance. By linking impervious surface expansion with spatial carbon emission interactions, this study contributes to sustainability research by providing empirical evidence for sustainable urban agglomeration development. Full article

To advance environmental sustainability, China proposed the Beautiful China Goals (BCGs) as its localized strategy, with urban agglomerations serving as the key implementation scale. To address the limitations of difficulty in identifying key tasks and insufficient regional applicability, this study develops a multi-goal evaluation system comprising 21 goals and 52 indicators rooted in the policy framework. Methodologically, a three-tiered assessment framework—goal, city, and region—is constructed for urban agglomerations, integrating spatial-temporal analysis, city-level two-dimensional diagnostics, and regional synergy quantification. The framework is applied to the Yangtze River Delta Urban Agglomeration (YRDUA), a national-level pilot area for the BCGs, over the period 2015–2023. Results indicate that: (1) progress toward the BCGs in the YRDUA increased by 5.7%, but full achievement by 2035 remains unlikely. Significant structural imbalances exist among the 21 goals, with infrastructure-related goals scoring higher than those related to institutional development, innovation, and carbon neutrality. Spatially, BCGs’ performance follows a “high southeast, low northwest” pattern, although distribution varied by goal, and regional equity has improved. (2) Fewer than half of the 41 cities had achieved “double high” states in both development magnitude and evenness by 2023, with cities following four distinct development pathways that reflect differing priorities and strategies for goal attainment. (3) Intercity cooperation in advancing the BCGs remains limited. Synergistic effects are relatively stronger for green production goals but weaker for ecological, technological, and institutional goals, with Ningbo, Suzhou, and Shaoxing emerging as key contributors to regional synergy. This framework offers a replicable tool for regional environmental planning and provides evidence for BCGs implementation strategies in China and beyond. Full article

Urban agglomerations concentrate activities that generate both PM2.5 pollution and carbon emissions, but the economic basis for governing them jointly remains unclear. Taking the Yangtze River Delta as a case, this study evaluates pollution–carbon co-governance from a marginal abatement cost (MAC) perspective. Using panel data for 41 cities from 2011 to 2023, we estimate shadow prices and MACs under joint and single-objective abatement scenarios with a non-radial directional distance function dual model. We then construct carbon-reduction and pollution-reduction cost-saving effects, classify synergy types, and examine their temporal, spatial, and nonlinear transition patterns. The results show that joint abatement generally lowers the MACs of both carbon mitigation and PM2.5 reduction, with stronger cost-saving on the pollution side. Under the baseline classification, the share of balanced synergy increases over time, and the balanced state shows high persistence in Markov transitions. Core cities show weaker measured cost-saving effects, which may reflect limited remaining low-cost co-abatement potential rather than weak governance. Semiparametric evidence further indicates that industrial upgrading, openness, and urbanization are nonlinearly associated with MACs and synergy balance. These findings suggest that urban pollution–carbon coordination should be guided by local cost structures and development stages. Full article

Decoupling economic growth from carbon emissions is central to the sustainable development of rapidly urbanizing economies, and urban agglomerations are the pivotal spatial units for delivering this transition under China’s dual-carbon goals, yet systematic cross-agglomeration comparisons that could inform differentiated sustainability policy remain scarce. Using panel data for 107 prefecture-level cities in five agglomerations—the Yangtze River Delta (YRD), Beijing–Tianjin–Hebei (BTH), Pearl River Delta (PRD), Chengdu–Chongqing (CY), and the middle reaches of the Yangtze River (MRYR)—across five benchmark years spanning 2005–2023, we combined a two-way fixed-effects environmental Kuznets curve (EKC) model, the Tapio decoupling model, and cross-sectional quadrant analysis to examine the growth–emission relationship in shape, decoupling dynamics, and spatial structure. All five agglomerations traced an inverted-U trajectory, with turning-point per capita gross domestic product (GDP) rising in the order CY < PRD < BTH < MRYR < YRD. Once fixed effects and structural controls were added, most quadratic terms became insignificant and reversed sign after the secondary-industry share and carbon intensity entered; only the PRD and BTH retained a significant nonlinear form. The net income effect is therefore largely monotonic, with the inverted U carried by industrial upgrading and energy-efficiency gains. Tapio decoupling followed a non-monotonic “improve-then-regress” path, with expansive negative decoupling re-emerging across all agglomerations during 2020–2023. Spatially, high-value clustering persisted in the YRD, weakened in the BTH after 2020, and concentrated on single cores in Chengdu and Wuhan. We accordingly propose sustainability-oriented low-carbon pathways differentiated jointly by agglomeration and quadrant. By showing that decoupling is stage-dependent and reversible rather than an automatic by-product of income growth, our findings indicate that durable progress toward regional sustainability hinges on structural transformation and coordinated governance tailored to each agglomeration’s stage of development. Full article

Urban functional zones (UFZ) serve as fundamental units of human activity, and their spatial configurations significantly influence urban carbon emissions. However, current research often overlooks the heterogeneity of UFZ forms and the complex, multi-scale relationships underlying their impact on emissions. To address this gap, this study investigates the Yangtze River Delta (YRD) urban agglomeration by delineating UFZ from the dual perspectives of block function and form. By integrating multi-scale spatial analysis with explainable machine learning, this study establishes a morphological indicator system covering three dimensions: density, morphology, and structure. The results reveal a pronounced scale dependency in the effects of UFZ form on carbon emission intensity (CEI), with optimal analytical scales identified at 14 km for density, 5 km for morphology, and 7 km for structure. Notably, variations within these dimensions lead to distinct patterns of impact intensity, even within the same functional category. Furthermore, most indicators exhibit nonlinear, threshold-dependent effects on CEI. These findings provide actionable guidance for fine-grained urban planning and carbon mitigation strategies. Full article

This study incorporates environmental regulation, green technological innovation, and industrial structure upgrading into a unified analytical framework. Collecting panel data from 71 core prefecture-level cities in the Chengdu–Chongqing, Middle Reaches of the Yangtze River and Yangtze River Delta urban agglomerations from 2011 to 2023, adopting fixed-effects, mediation, and moderation models to investigate how environmental regulation and green technological innovation affect industrial structure upgrading, through which mechanisms these effects occur, and how inclusive digital finance moderates these relationships. The findings reveal that command-and-control and guidance-based environmental regulations all exert positive effects on industrial structure upgrading. Green technological innovation serves as a mediating mechanism through which command-and-control environmental regulation promotes industrial structure upgrading. Inclusive digital finance acts as a boundary condition shaping the effect of environmental regulation on industrial structure upgrading. Further heterogeneity analysis reveals regional variation in how different types of environmental regulation affect industrial structure upgrading. This study proposes policy recommendations that urban agglomerations should attach greater importance to green innovation, enhance the breadth and depth of inclusive digital finance utilization, and establish appropriate local environmental regulatory support systems so as to promote industrial structure upgrading. Full article

Analyzing the impervious surface area (ISA) of China’s three major urban agglomerations and expansion pattern of representative cities is of great significance for formulating context-specific urban planning policies and enhancing the resilience of urban development. This research employs impervious surface expansion indicators to reveal the spatiotemporal dynamics of impervious surface area, and further applies the location centrality index (LCI) to investigate the expansion structures and patterns of five megacities. The results indicate that the ISA of China’s three major urban agglomerations expanded from 22,544.10 km² to 69,348.59 km² from 1985 to 2024; both the expansion rate and intensity have exhibited a distinct decelerating trend. However, significant regional variation exists in the peak expansion phases: the Guangdong–Hong Kong–Macao Greater Bay Area Urban Agglomeration (GBA) peaked during the Initial Exploratory Phase (1985–1995), whereas the Yangtze River Delta Urban Agglomeration (YRD) and Beijing–Tianjin–Hebei Urban Agglomeration (BTH) reached their peaks during the High-speed Development Phase (2005–2015). At the urban scale, LCI-based analysis of urban expansion across five megacities reveals that adjacency expansion type has become the predominant form of growth, exceeding 50% in most cities. These findings enhance our understanding of evolutionary trajectories of ISA within urban agglomerations and the expansion patterns of five megacities, providing a scientific basis for sustainable urban planning and urban resilience. Full article