Search Results (342)

Based on structural equation modeling, the influence paths and group differences in residents’ low-carbon living behaviors and consumption behaviors were explored in six low-carbon pilot cities in China from the perspectives of low-carbon policy perception and low-carbon information dissemination. The results showed that residents in different pilot cities significantly differed in their low-carbon intention and low-carbon behavior, especially in Hangzhou and Chengdu, which had high low-carbon intention and low-carbon behavior. Low-carbon intention was the core driving force that promoted residents’ low-carbon behavior. Low-carbon policy perception and information dissemination impacted residents’ low-carbon intention and low-carbon behavior, with differences among different pilot cities. Residents in Chengdu and Wuhan showed a significant positive correlation in the direct and indirect paths of low-carbon policy perception on low-carbon behavior. In contrast, residents in Hangzhou showed a significant positive correlation in the impact path of low-carbon information dissemination on low-carbon consumption behavior. In addition, groups with different demographic characteristics significantly differed in the influence paths of their low-carbon behavior. Finally, targeted recommendations were proposed to promote differentiated strategies for implementing low-carbon behaviors, aiming to enhance public awareness and action capacity and support China’s low-carbon transition and carbon reduction goals. Full article

Cities need emergency-shelter systems that are computationally efficient, socially fair, and consistent with long-term goals for sustainable urban development. This paper proposes a GIS-integrated, two-stage location–allocation framework for urban earthquakes that jointly optimizes shelter siting and evacuee assignment under time-varying demand. The model incorporates equity constraints that cap extreme travel burdens for vulnerable groups and robust capacity safeguards against demand uncertainty, helping prevent over- or under-investment in shelter infrastructure and promoting efficient use of land and public resources. A customized Phased Nested Local Search (PNLS) heuristic enables city-scale application and is benchmarked against a mixed-integer programming baseline solved by CPLEX. In a district-level case study of Chengdu, China, the framework reduces total assignment distance by 12.3% and the 95th-percentile travel burden by 15.8% while maintaining feasibility during the peak demand window. The results show that integrating equity, robustness, and spatial efficiency in shelter planning can strengthen urban resilience and directly support SDG 11 on sustainable cities and communities. Full article

Rapid warming and expanding heat seasons are reshaping electricity demand in cities, with basin-type megacities like Chengdu facing amplified risks due to calm-wind, high-humidity conditions and fast-growing digital infrastructure. This study develops a Transformer-based, multi-model downscaling framework that integrates outputs from 17 CMIP6 global climate models (GCMs), dynamically re-weighted through self-attention to generate city-scale temperature projections. Compared to individual models and simple averaging, the method achieves higher fidelity in reproducing historical variability (correlation ≈ 0.98; RMSD < 0.05 °C), while enabling century-scale projections within seconds on a personal computer. Downscaled results indicate sustained warming and a seasonal expansion of cooling needs: by 2100, Chengdu is projected to warm by ~2–2.5 °C under SSP2-4.5 and ~3.5–4 °C under SSP3-7.0 (relative to a 2015–2024 baseline). Using a transparent, temperature-only Cooling Degree Day (CDD)–load model, we estimate median summer (JJA) electricity demand increases of +12.8% under SSP2-4.5 and +20.1% under SSP3-7.0 by 2085–2094, with upper-quartile peaks reaching +26.2%. Spring and autumn impacts remain modest, concentrating demand growth and operational risk in summer. These findings suggest steeper peak loads and longer high-load durations in the absence of adaptation. We recommend cost-aware resilience strategies for Chengdu, including peaking capacity, energy storage, demand response, and virtual power plants, alongside climate-informed urban planning and enterprise-level scheduling supported by high-resolution forecasts. Future work will incorporate multi-factor and sector-specific models, advancing the integration of climate projections into operational energy planning. This framework provides a scalable pathway from climate signals to power system and industrial cost management in heat-sensitive cities. Full article

The Sichuan–Yunnan region, a primary seismic-prone zone on the Qinghai–Tibet Plateau, has experienced heightened seismic exposure due to rapid urbanisation. In order to address the issue of disaster risks and to promote sustainable urban development, this study establishes an integrated urban seismic resilience evaluation framework based on the DPSIR (Driving–Pressure–State–Impact–Response) model. The CRITIC–AHP combined weighting method was utilised to determine indicator weights, and data from 37 prefecture-level cities (2010, 2015, 2020) were analysed to reveal spatial–temporal evolution patterns and correlations. The results demonstrate a consistent improvement in regional seismic resilience, with the overall index increasing from 0.501 in 2010 to 0.526 in 2020. Sichuan exhibited a “decline-then-rise” trend (0.570 to 0.566 to 0.585), while Yunnan demonstrated continuous growth (0.517 to 0.557). The spatial pattern underwent an evolution from “west–low, central–eastern–high” to “south–high, north–low”, with over half of the cities attaining relatively high resilience by 2020. Chengdu and Kunming have been identified as dual high-resilience cores, diffusing resilience outward to neighbouring regions. In contrast, mountainous areas such as Garze and Aba have been found to exhibit low resilience levels, primarily due to high seismic stress and limited socioeconomic capacity. Subsystem analysis has revealed divergent resilience pathways across provinces, while spatial autocorrelation has demonstrated fluctuating global Moran’s I values and temporary local clustering. This research provides a scientific foundation for seismic disaster mitigation and offers a transferable analytical framework for enhancing urban resilience in earthquake-prone regions globally. Full article

Research on culture-led urban change in China has shifted from inner-city clusters to peripheral zones where formal planning meets managed informality, yet two gaps remain. First, artistic production continues to be interpreted through a leasing lens that positions artists as temporary occupiers. Second, land is analysed largely at the macro scale of municipal supply and branding, while internal property rules and meso-level governance are overlooked. This paper mobilises the concept of assetisation to show how precarious cultural spaces become rule-bound assets through property-rights design. Fieldwork in Chengdu’s Blue Roof Art District draws on qualitative methods, including semi-structured interviews, policy and registration documents, and on-site observation. We examine which resources are assetised, how this occurs, and with what effects on publicness and spatial form. Our findings show that planning endorsement, the transfer of collective construction land for cultural use, and title registration with mortgageability codify eligibility, use and transfer. Studios are converted into owner-occupied assets tied to land value. Governance shifts from direct administrative control to asset management by owners and the site operator. While production stabilises and overt conflict declines, public interfaces narrow and enclave risks intensify when city priorities change. Empirically, the paper demonstrates how property-rights design operates as a meso-level governance tool that sets explicit trade-offs between stability and openness. Theoretically, it links producers to land value, bridging macro land regimes with micro political practice in urban peripheries and informing urban policy-making that prioritises sustainability. Full article

In response to frequent disruptions such as public health incidents and natural disasters, enhancing tourism ecological resilience (TER) has become crucial for achieving sustainable tourism development. This study constructs an evaluation index system for TER from three dimensions: resistance, recovery, and innovation. Employing the entropy weight method and fuzzy-set Qualitative Comparative Analysis (fsQCA), an empirical analysis was conducted on the spatiotemporal evolution and formation mechanisms of TER in the Chengdu-Chongqing Economic Circle (CCEC) from 2013 to 2023. The results indicate that: First, although an overall upward trend in TER was observed, significant regional disparities existed. Chongqing (0.634) and Chengdu (0.491) consistently led, while the average values for the other cities were generally below 0.155, revealing a pattern characterized by “dual-core prominence and peripheral lag”. Second, the impact of the pandemic exacerbated imbalances among subsystems, with resistance, recovery, and innovation capabilities all exhibiting core–periphery differentiation. Third, fsQCA results demonstrated that high resilience was driven by a “technology-service” core coupled with auxiliary conditions such as transportation or consumption, while low resilience stemmed from multiple systemic deficiencies, including insufficient government support, underdeveloped transportation, and weak technological innovation. This study provides configurational pathways and policy implications for building regional tourism resilience. Full article

Accelerated urbanization has induced marked biodiversity loss in metropolitan regions, with urban parks emerging as critical habitat patches for avian species within intensively developed built environments. As a global pioneer in park city conceptualization, Chengdu (China) has achieved notable advancements in urban green space extent and quality through systematic planning efforts. This investigation examines the avian–habitat relationships in Chengdu’s central urban area (2010–2020) using multispectral remote sensing data, employing the ENVI5.6 (Environment for Visualizing Images) software for spatial analysis, and applying the InVEST3.2.0 (Integrated Valuation of Ecosystem Services and Tradeoffs) model to identify high-quality habitats, evaluate landscape connectivity, and analyze community composition dynamics. Through a correlation analysis of seven environmental characteristic factors with avian biodiversity in 24 urban parks, the impact mechanism of avian habitat functions was explored. On this basis, measures such as optimizing the plant community structure of riverside greenways and road green spaces, expanding small-scale green spaces near parks, and so on are proposed to promote the enhancement of urban park habitat functions and the protection of avian biodiversity. Full article

Particulate matter (PM) concentration, especially PM_2.5, is a major culprit of environmental pollution from unreasonable energy system emissions that significantly affects visibility, climate, and public health. The prediction of PM_2.5 concentration holds significant importance in the early warning and management of severe air pollution, since it enables the provision of guidance for scientific decision-making through the estimation of impending PM_2.5 concentration. However, due to diversified human activities, seasonal factors and industrial emissions, the air quality data not only show local anomalous mutability, but also global dynamic change characteristics. This hinders existing PM_2.5 prediction models from fully capturing the aforementioned characteristics, thereby deteriorating the model performance. To address these issues, this study proposes a framework integrating multi-scale temporal convolutional networks (TCNs) and a transformer network (called MSTTNet) for PM_2.5 concentration prediction. Specifically, MSTTNet uses multi-scale TCNs to capture the local correlations of meteorological and pollutant data in a fine-grained manner, while using transformers to capture the global temporal relationships. The proposed MSTTNet’s performance has been validated on various air quality benchmark datasets in the cities of China, including Beijing, Shanghai, Chengdu, and Guangzhou, by comparing to its eight compared models. Comprehensive experiments confirm that the MSTTNet model can improve the prediction performance of 2.42%, 2.17%, 2.87%, and 0.34%, respectively, with respect to four evaluation indicators (i.e., Mean Absolute Error, Root Mean Square Error, Mean Absolute Percentage Error, and R-square), relative to the optimal baseline model. These results confirm MSTTNet’s effectiveness in improving the accuracy of PM_2.5 concentration prediction. Full article

Background/Objectives: This study characterized the endogenous peptide profile of human milk from a Chinese multicenter cohort (n = 200 mothers) using the Orbitrap Fusion Lumos LC-MS/MS. Methods: Samples were collected across different lactation stages (2 and 6 months postpartum) and seven geographic regions (Beijing, Chengdu, Guangzhou, Jinhua, Lanzhou, Weihai, and Zhengzhou). Results: In total, 6960 peptides derived from 621 proteins were identified. Peptides from the polymeric immunoglobulin receptor (PIGR) were more abundant in the 2nd month than the 6th month, providing a high antimicrobial activity and immune functions for the infants. Moreover, region-specific variations were observed, with milk from Lanzhou exhibiting significantly higher levels of β-casein (CASB) and butyrophilin subfamily 1 member A1 (BTN1A1) peptides compared to other cities. Conclusions: Furthermore, maternal dietary intake of oils and total fat correlated positively with the intensity of specific antimicrobial peptides, including CASB_199–216, CASB_200–226, and CASB_201–226. Infant growth parameters were inversely correlated with several antimicrobial peptides, although CASB_200–225 demonstrated positive associations. These findings offer novel insights into the dynamics of endogenous peptides in human milk and may guide breastfeeding recommendations and infant formula design. Full article

Urban heat exposure, which intensifies with climate change, poses serious threats to public health in rapidly growing cities. Traditional assessments rely on static land surface temperature, often overlooking the role of human mobility in exposure frequency. This study introduces a travel-related heat exposure index (THEI) that combines ride-hailing trajectories and remote sensing data to capture dynamic human–environment thermal interactions. Using Chengdu, China, as a case study, the THEI is combined with local indicators of spatial association to outline high-exposure risk zones (HERZ). XGBoost with SHAP and partial dependence plot (PDP) methods is also applied to identify the nonlinear effects of built environment factors. Results showed the following: (1) distinct spatial clustering of high travel-related heat exposure in central urban districts and transit hubs; (2) city-wide exposure is primarily driven by transportation accessibility and urban form, such as intersection density and floor area ratio; (3) in contrast, HERZ are more strongly associated with demographic and socioeconomic factors, including population density, housing price and road density; and (4) vegetation, measured by the normalized difference vegetation index, demonstrates a consistent negative effect across scales, highlighting its critical role in mitigating thermal risks. These findings emphasize the necessity of incorporating mobility-based exposure metrics and spatial heterogeneity into climate-resilient urban planning, with differentiated strategies tailored for city-wide versus high-risk zones. Full article

Tens of thousands of ordinary traditional settlements remain clustered within specific geographic regions of China. Efficient and objective rapid identification of these settlements is crucial for preserving rural cultural heritage. This study takes the traditional settlement Linpan in the Chengdu Plain as a case study, focusing on Pidu District of Chengdu City in Sichuan Province, and proposes an innovative approach for rapid large scale surveys of common traditional settlements using object detection technology. Based on the technical requirements, the spatial characteristics of Linpan settlements in the Chengdu Plain were refined. High-resolution satellite images from 2016 and 2023 of Pidu were processed and cropped, and a diversified training dataset was constructed. After annotation, multiple rounds of training were conducted to develop a detection model based on YOLOv11. The model was then applied to identify thousands of rural settlements across the 438 km² area of Pidu, followed by an evaluation of various detection parameters. The results demonstrate that this method can complete the identification of Linpan settlements across the entire Pidu in just 6–7 min, achieving a precision of 96.59% and a recall rate of 94.39%. In terms of efficiency and accuracy, this approach significantly outperforms visual interpretation and remote sensing interpretation methods. Furthermore, based on the detection results, the spatiotemporal distribution characteristics of Linpan settlements during the study period were analyzed. This study aims to improve the surveying methods for traditional villages sand advance their conservation from “static observation” to “dynamic analysis”. Full article

In the context of China’s “double carbon” goals, examining the spatial–temporal characteristics and influencing factors of the synergistic effect of pollution control and carbon reduction (SEPCR) in the Chengdu–Chongqing region (CCR) is crucial for advancing both air pollution (AP) control and carbon emissions (CE) mitigation. This study uses data on AP and CE from 2007 to 2022 and employs the coupling coordination degree (CCD) model, spatial autocorrelation analysis, and kernel density estimation to investigate the spatial–temporal distribution and dynamic evolution of the CCD between AP and CE in the CCR. Additionally, the Tobit regression model is applied to identify the key factors influencing this synergy. The results indicate that (1) during the study period, the air pollutant equivalents (APE) in the CCR showed a declining trend, while CE continued to increase; (2) the overall level of coupling coordination remained low, exhibiting an evolutionary pattern of initial increase, subsequent decrease, and then recovery, with synergistic effects showing slight improvement but significant fluctuations; (3) the SEPCR in the CCR was generally dispersed, exhibiting no significant spatial autocorrelation. A “core–periphery” structure emerged, with Chongqing and Chengdu as the core and peripheral cities forming low-value zones. Low–low clusters indicative of a “synergy poverty trap” also appeared; (4) economic development (PGDP), openness level (OP), and environmental regulation intensity (ER) are significant positive drivers, while urbanization rate (UR), industrial structure upgrading (IS), and energy consumption intensity (EI) exert significant negative impacts. Full article

This study investigated the spatiotemporal dynamics and driving mechanisms of urban expansion in the Chongqing Metropolitan Area by integrating multi-source big data and employing a suite of quantitative analytical methods. Drawing upon high-resolution remote sensing imagery, land-use datasets, socioeconomic statistics, and transportation network data spanning 2019 to 2023, the research revealed pronounced spatial and temporal heterogeneity in urban growth. Specifically, expansion manifested through a core-periphery spatial structure and temporal imbalances. The findings underscore a growing economic interconnectedness between core urban districts and peripheral cities such as Guang’an and Luzhou, giving rise to a multilayered and increasingly networked spatial-economic system. Moreover, urban expansion is shown to be tightly coupled with industrial distribution, transportation optimization, and regional integration strategies. In particular, the implementation of the Chengdu-Chongqing Twin-City Economic Circle has significantly facilitated cross-regional factor mobility and spatial restructuring, thereby accelerating coordinated development across the metropolitan area. Looking forward, urban expansion in the Chongqing Metropolitan Region is expected to continue leveraging transportation infrastructure and strategic industrial placement to advance regional economic integration. Full article

As cities densify and lifestyles become increasingly individualized, older adults face heightened risks of isolation and reduced wellbeing. Yet in historic Chinese neighborhoods, everyday socio-cultural practices—square dancing, Mahjong, community gardening and street markets—continue to foster social cohesion and spatial familiarity. This study employs Christopher Alexander’s pattern-language framework to examine how these practices are spatially embedded across six traditional neighborhoods in Chengdu. Drawing on systematic field observation, photographic surveys and typological mapping, it identifies recurring spatial configurations that support older adults’ participation and cultural continuity. While many canonical patterns remain relevant, the analysis shows how several require contextual reinterpretation to reflect Chinese collectivism, threshold sociability and informal public-space use. Synthesizing these insights, the paper develops a pattern-based design toolkit for culturally sensitive urban regeneration, contributing to age-friendly planning grounded in lived spatial practices. Although centered on six historic neighborhoods in Chengdu, the findings are intended primarily for Chinese heritage-led regeneration and—where comparable high-density morphologies, edge conditions and management regimes exist—are cautiously transferable to heritage districts elsewhere. Full article

Understanding food production (FP) supply–demand relationships is crucial for achieving Sustainable Development Goal 2 (SDG 2). Previous studies often assessed these relationships by overlaying supply and demand without considering food production flow (FPF). This study developed a framework from the perspectives of supply, demand, and flow to analyze the Agrifood System (AFS) of four major urban agglomerations in China: Beijing–Tianjin–Hebei, the Yangtze River Delta, the Pearl River Delta, and Chengdu–Chongqing. It applied the enhanced two-step floating catchment area model to simulate the magnitude and direction of four types of FPF—grains, vegetables, fruits, and meat—under three scenarios: intra-city flow, intra-provincial flow, and free flow. Results revealed mismatches in the FP supply–demand, and incorporating FPF improved these relationships. As flow restrictions eased, intra-city flows decreased, cross-regional flows expanded, and supply–demand imbalances were alleviated. Enhancing regional cooperation plays a key role in addressing the spatial mismatch between food supply and demand. These findings provide useful insights for addressing food supply–demand mismatches through more proper agricultural land allocation, better alignment of consumption patterns, and improvements in the flow system. Full article