Advancing the low-carbon and resilient transformation of urban systems has become a crucial strategy for addressing the climate crisis. Current research predominantly focuses on either the effect of governance or the efficient utilization of urban systems, overlooking the potential structural mismatches and synergistic development governance logic between the two. This paper systematically proposes a theoretical research framework integrating the synergistic development of urban system effect and efficiency, and constructs a multi-level analytical methodology. Through an in-depth examination of 278 prefecture-level cities in China from 2010 to 2023, the following key conclusions emerge: (1) The overall level of synergistic development within urban systems has steadily increased. Specifically, the proportion of cities at low levels of synergistic development decreased from 65.11% to 17.63%, while the proportion at medium and high levels rose from 18.70% to 46.40%. (2) Spatial disparities in urban system coordination have progressively narrowed, as evidenced by the overall Gini coefficient decreasing from 0.195 to 0.153. (3) Key influencing factors for urban system coordination include foreign enterprise attraction, urban infrastructure development, and green technological innovation. Overall, this study reveals the long-standing structural mismatch between effect and efficiency in China’s urban system’s low-carbon resilience transformation, emphasizing the importance of their coordinated development. It provides theoretical foundations and empirical references for the sustainable development of urban low-carbon resilience transformation.

The adaptive reuse of industrial heritage is increasingly recognized as an effective low-carbon strategy that reduces resource consumption, lowers embodied carbon emissions, and supports sustainable urban transitions. Developing appropriate reuse strategies, however, requires a robust understanding of heritage value. As material evidence of China’s modern industrialization, railway-associated industrial heritage possesses the characteristics of linear cultural heritage. Yet systematic and multi-scalar value assessments from a linear heritage perspective remain limited. Focusing on the Guanzhong Section of the Longhai Railway—one of the most representative industrial development axes in Northwest China—this study establishes a two-level value assessment framework and conducts a comprehensive evaluation of fourteen textile industrial heritage units. At the individual level, five dimensions—historical significance, architectural features, structural integrity, authenticity, and rarity—were assessed through field investigation, and type-specific weights were introduced to correct structural imbalances between quantity and value across building categories. At the unit level, the Analytic Hierarchy Process (AHP) was employed to determine the weights of spatial–functional integrity, process completeness, railway connectivity, industrial landscape characteristics, and the integrated individual-level value. The results show that factory workshops and warehouses consistently exhibit the highest value, whereas structures and residential buildings, despite their numerical dominance, contribute relatively little. Spatially, a clear west–east gradient emerges: high-value units cluster in Baoji and Xi’an, medium-value units in Xianyang, and low-value units mainly in Weinan and surrounding counties. The findings indicate that textile industrial heritage along the Guanzhong Section forms a railway-linked linear cultural heritage system rather than isolated sites. The proposed evaluation framework not only supports heritage identification and conservation planning but also provides a theoretical basis for promoting low-carbon adaptive reuse of existing industrial buildings.

Urban sustainable development increasingly depends on interactions among multiple urban subsystems, yet existing studies often overlook cross-regional linkages and nonlinear development processes. This study investigates the coordinated development of urbanization, smart development, resilience, and low-carbon transition (USRL) from an efficiency perspective. Using panel data from 278 Chinese cities during 2010–2023, this work integrates the Super-SBM model, the Local–Tele Coupling Coordination Degree (LTCCD) framework, Dagum Gini decomposition, and machine learning techniques to examine the spatiotemporal evolution, spatial disparities, and driving mechanisms of coordinated development. The results show that coordinated development improved steadily over time, although subsystem evolution remained uneven, with resilience lagging behind other dimensions. Regional disparities gradually narrowed, but inter-regional differences remained the dominant source of spatial inequality. Innovation intensity, industrial upgrading, and high-quality foreign investment positively contributed to coordinated development, whereas fiscal and financial factors exhibited nonlinear effects. Interaction analysis further revealed that coordinated development is shaped by the combined influence of multiple drivers rather than by individual factors alone. Our findings suggest that urban sustainable development is jointly influenced by subsystem coordination, cross-regional interactions, and nonlinear development dynamics, highlighting the importance of integrating local and tele-coupling processes in urban sustainability research.

Against the backdrop of sustainable development and China’s Dual Carbon Goals, Digitalization, Urban Development, and Low-carbon Transition continuously interact to shape urban sustainable development. However, the long-term coordination of the Digitalization–Urban Development–Low-carbon Transition (DUL) system and its underlying mechanisms remain insufficiently understood. To address this research gap, using panel data for 289 prefecture-level and above cities in China from 2010 to 2024, this study constructs the DUL system and applies the CRITIC-Entropy Weight Method to evaluate the development levels of the three subsystems and the overall DUL system. The Local and Tele-coupling Coordination Degree (LTCCD) is employed to characterize long-term coordination, while the Dagum Gini coefficient and GeoDetector are used to examine regional disparities and driving mechanisms. Based on this analytical framework, the results show that: (1) the development levels of Digitalization, Urban Development, and Low-carbon Transition all improved continuously, but their evolutionary trajectories differed, resulting in asynchronous development of the DUL system; (2) LTCCD exhibited a sustained upward trend, with coordination gradually evolving from imbalance to coordination, although eastern China consistently outperformed the central and western regions; (3) regional disparities in LTCCD generally narrowed, while interregional differences remained the primary source of spatial disparities, with the largest gap occurring between eastern and western China; and (4) the driving mechanisms of LTCCD evolved over time, with the explanatory power of individual factors changing dynamically, whereas the interaction effects among multiple factors consistently exceeded those of single factors, indicating that the long-term coordinated development of the DUL system mainly depends on multi-factor synergy. Taken together, these findings reveal the spatiotemporal evolution and formation mechanisms of long-term coordinated development in the DUL system and provide theoretical insights for promoting coordinated urban development and low-carbon transition in the digital era.

Against the backdrop of sustainable transition, the coordinated improvement of carbon emission performance (CEP) and energy efficiency (EE), as well as its relationship with urban low-carbon resilience (LCR), warrants further investigation. Using panel data for 289 prefecture-level and above cities in China from 2010 to 2023, this study measures CEP–EE synergy and LCR and employs spatial autocorrelation analysis, the spatial Durbin model (SDM), the system generalized method of moments (SYS-GMM), and a panel threshold model to examine their spatial, dynamic, and nonlinear relationships. The results show that: (1) Both LCR and CEP–EE synergy exhibit an overall upward trend, although their spatial evolution is not synchronized, and both display significant positive spatial autocorrelation. (2) The SDM results reveal a significant positive relationship between CEP–EE synergy and local LCR, together with a significant positive spatial indirect effect. (3) The SYS-GMM results show that CEP–EE synergy remains significantly and positively associated with LCR after accounting for the dynamic persistence of LCR and potential endogeneity, and this finding is supported by robustness checks. (4) The threshold test supports the existence of a single threshold in technological innovation input (TII). CEP–EE synergy is significantly and positively associated with LCR across different TII regimes, while exhibiting some stage-dependent variation. These findings indicate that the coordinated improvement of CEP and EE and its spatial linkages constitute an important dimension for understanding urban LCR, while their relationship also varies across TII conditions. The study provides empirical evidence for differentiated and regionally coordinated approaches to high-quality urban transition.