Search Results (358)

China’s urban low-carbon transition requires clearer city-level evidence on whether and how digitalization mitigates carbon emission intensity. Using panel data for 288 Chinese prefecture-level and above cities from 2013 to 2022, this study constructs a multidimensional Digital Economy Index and measures carbon emission intensity using EDGAR emissions and GDP at constant 2013 prices. We employ two-way fixed effects, instrumental variables, System GMM, robustness checks, mediation analysis, heterogeneity tests, and a Spatial Durbin Model. The results show that digital economy development significantly reduces urban carbon emission intensity, and this conclusion remains robust across alternative measurements, lag specifications, sample adjustments, fixed-effect structures, and endogeneity corrections. Mechanism analysis indicates that industrial structure rationalization and upgrading are key transmission channels, whereas technological innovation may generate short-term adjustment costs consistent with a “green paradox.” The carbon-reduction effect is stronger in old industrial base cities, cities with weaker initial innovation foundations, and cities with lower initial population density. Spatial analysis shows that digitalization generates significant carbon-reduction spillovers under geographical proximity, while economic-linkage-based spillovers are more complex. These findings provide theoretical and policy implications for digitally enabled and regionally coordinated urban decarbonization. Full article

Musculoskeletal disorders (MSDs) represent a critical global challenge to workforce productivity. In Thailand, these disorders are particularly prevalent in labor-intensive industries such as ice manufacturing, where workers face significant ergonomic hazards. Addressing this gap, the present study aimed to assess the occupational health, safety, and ergonomic risks facing workers in ice production facilities. This cross-sectional descriptive study investigated production workers who were employees in two of eight ice manufacturing plants in Surat Thani, Thailand, using the Rapid Entire Body Assessment (REBA) method. A structured occupational health and safety risk assessment questionnaire and the REBA evaluation form were used to collect data. All participants were male, averaging 30.4 (±8.5) years old. Regular pain areas included the upper/lower back, hips/thighs, shoulders, wrists, and ankles. Ergonomic assessments showed high overall risk due to heavy lifting, repetitive tasks, and cold environments. Based on REBA scores, 13.04% were in the very-high-risk group (score ≥ 11) and 65.22% in the high-risk group (score 8–10). Most production workers in ice plants faced high ergonomic risks, especially from postures affecting the upper and lower back. Training should be provided to promote awareness of risky postures and proper lifting techniques. Mechanical aids and back-support equipment are also recommended to help prevent musculoskeletal injuries. Full article

In the context of urban regeneration and the redevelopment of existing urban land and built assets, industrial heritage has become a cross-sectoral policy issue involving heritage conservation, spatial reuse, land governance and public cultural uses. Existing studies have primarily examined individual adaptive reuse projects and spatial strategies, whereas the long-term evolution of policy texts has received less systematic attention. Taking Shanghai as a case study, this paper constructs a clause-level corpus of industrial heritage-related policies issued between 2006 and 2025. The corpus comprises 524 clauses extracted from 86 policy documents covering heritage conservation, historic building conservation, cultural and creative industries, land use, planning, urban renewal and industrial tourism. Overall and stage-based Latent Dirichlet Allocation (LDA) models are combined with cross-period topic alignment to identify the structure and evolution of policy themes. The results show that Shanghai’s industrial heritage policies have been shaped not only by heritage conservation concerns, but also by industrial land governance, the transformation of underused industrial land, the regeneration of existing industrial spaces (EIS), industrial culture, tourism and public service provision. Four stages are identified: initial exploration, regulatory consolidation, revitalisation and renewal, and integrated consolidation. Across these stages, four major evolutionary pathways can be observed: industrial land supply and governance, renewal of EIS and old industrial areas (OIA), industrial heritage conservation and value recognition and the expansion of industrial culture, tourism and public services. The paper provides clause-level evidence for understanding industrial heritage governance in China’s urban regeneration context and highlights the need for stronger coordination between heritage, land, planning, industry, culture and tourism policies. Full article

Tourism development potential and observed development performance do not necessarily evolve synchronously, particularly in old industrial and restructuring regions where attraction supply, market linkage, and visitor experience may be spatially uneven. This study develops a multi-source diagnostic framework for identifying tourism potential–performance mismatch across the 14 prefecture-level cities of Liaoning Province, China. Drawing on Ctrip review texts, rating scores, timestamps, platform-displayed reviewer-origin labels, A-level scenic-spot point data, and annual official city-level tourism statistics, the study constructs three dimension-specific sub-indices—the Scenic Experience Index (ESI), the Market Linkage Index (MLI), and the Attraction Foundation Index (AFI)—and synthesizes them into a Comprehensive Potential Index (CPI). The CPI is then compared with an Observed Performance Index (OPI) constructed from domestic tourist arrivals and domestic tourism revenue for 2016–2022. The results show that attraction foundation contributes most strongly to composite tourism potential, while market linkage and scenic experience condition how this structural basis is associated with observed outcomes. The CPI–OPI comparison identifies three relationship types: matched, potential-leading, and performance-leading cities. Dalian and Shenyang are high-level matched cities, Benxi and Jinzhou are high-potential but under-converted cities, and Anshan and Dandong are performance-leading cities. These findings demonstrate that favorable structural tourism conditions are not automatically transformed into realized market performance. The study contributes a multidimensional, gap-analysis-based diagnostic architecture that can support tourism-related spatial planning and territorial governance in transitional regions. Full article

For old industrial urban agglomerations, low-carbon planning requires emission information at a finer spatial scale, but county-level energy statistics are often incomplete. This study focuses on the Central-Southern Liaoning Urban Agglomeration, a typical heavy-industrial region in Northeast China. County-level energy-related carbon emissions for 73 units from 2005 to 2024 are reconstructed by combining socioeconomic panel data with harmonized DMSP-OLS-like nighttime light data. On this basis, global and local spatial autocorrelation, Moran scatterplots, Markov and spatial Markov transition matrices, and a spatial STIRPAT-based Spatial Durbin Model are used to examine the spatial pattern, transition process, and driving factors of emissions. The results show that emissions continued to increase during the study period, although the growth rate became slower and no clear regional peak was observed. Moran’s I rose from 0.627 in 2005 to 0.675 in 2024, which means that county-level emissions became more spatially clustered. The traditional Markov matrix shows strong state persistence, with diagonal probabilities ranging from 0.8793 to 0.9852. The spatial Markov results further suggest that counties surrounded by high-emission neighbors face greater pressure to move upward. In the SDM results, the spatial autoregressive coefficient is significant at the 1% level, with rho = 0.537. GDPPC and POP show negative direct effects, SEC increases local emissions but has a negative indirect effect, and PE is positively related to local emissions. Spatially, high-emission counties are mainly distributed around Shenyang, Anshan, Liaoyang, Dalian, and other industrial cores, while eastern ecological counties remain at relatively low emission levels. These findings provide county-scale evidence for differentiated low-carbon governance in old industrial regions. Full article

Routine culling of day-old male chicks in the global poultry industry triggers severe resource waste and critical animal welfare crises, while non-destructive early sex identification techniques for embryonated quail eggs remain a prominent research gap. This study developed a novel Raman spectroscopy-based method for quail embryo sexing on incubation day 5, using an innovative “shell perforation without inner membrane damage” sampling strategy. The optimized GA-CARS-ELM model achieved 80.95% accuracy on the independent test set with 0.39 ms single-sample model inference time and 5.3 ± 0.5 min total per-egg processing time under manual operation, outperforming mainstream machine learning and deep learning algorithms. This work fills the relevant research gap and provides vital technical support for the development of automated pre-hatching sex sorting systems in poultry farming. Full article

Punjab, Pakistan, is experiencing severe groundwater depletion due to excessive and unplanned extraction, declining surface water availability, rapid population growth, and increasing climate variability. Groundwater has become the primary source of irrigation and drinking water across the province, contributing about 50%, 90% and 95% of the requirements of agricultural, domestic, and industrial water demands. Natural recharge rates have been reduced due to construction, pavements, and the lining of irrigation channels. This study presents the first pilot-scale Managed Aquifer Recharge (MAR) initiative implemented by the Irrigation Research Institute (IRI) of the Punjab Irrigation department. Floodwater has been diverted into the bed of the abandoned Old Mailsi Canal (OMC), which off-takes from Islam Headworks. About 144 recharge wells have been constructed in the bed of the OMC. During the 2025 flood season, approximately 12,000 acre-feet of floodwater was diverted and stored through engineered ponding, canal-bed rehabilitation, and recharge wells. A comprehensive monitoring program was established, including piezometers, automated data loggers, groundwater quality sampling, pumping tests, geophysical surveys, and sediment analyses. The results indicate a maximum groundwater level rise of up to 11 ft., with average increases ranging from 2.6 to 5.2 ft across the recharge ponds. Groundwater quality also showed an improvement following MAR implementation; electrical conductivity decreased from 900 to 650 μS/cm in Pond-I and from 850 to 750 μS/cm in Pond-III. These findings demonstrate that repurposing abandoned canal infrastructure for floodwater-based MAR provides a technically feasible, environmentally sustainable, and climate-resilient strategy for enhancing groundwater availability for sustainable management in Punjab and other water-stressed regions. Full article

Against the background of industrial transformation and urban regeneration in old industrial bases, understanding the spatial pattern and driving mechanisms of industrial heritage is essential for its conservation and sustainable use. This study investigates 277 industrial heritage sites in Liaoning Province (including nationally designated sites, potential heritage within cultural relic protection units at all levels, and sites recognized by the China Association for Science and Technology) using kernel density estimation, standard deviation ellipse, and the GeoDetector model. The results reveal a significantly clustered distribution characterized by “dense in central–southern Liaoning, sparse in the periphery,” forming three major agglomerations: the Shenyang core, the Anshan–Benxi–Liaoyang heavy industry triangle, and the Dalian coastal industrial belt. Temporally, the distribution shows distinct phases closely linked to industrial development history and major socio-political events. Land use, GDP, and climatic factors dominate the spatial differentiation, with GDP and annual average temperature exhibiting the strongest combined explanatory power (41.67%). Based on these dominant factors and the identified core agglomeration areas, differentiated protection and utilization strategies should be formulated for core versus peripheral areas, different industrial types, and various historical periods. This provides direct empirical evidence for industrial heritage management and cultural revitalization in old industrial regions. Full article

The rapid expansion of the digital economy is reshaping urban systems, yet the pathways through which digitalization drives urban green land use transition remain insufficiently understood. Using panel data from 279 Chinese cities, we measure Urban Green Land Use Efficiency (UGLUE) via a super-efficiency Slack-Based Measure (SBM) model and estimate digital economy effects through double machine learning (DML). We find that digital technology, digital industry, and digital infrastructure all positively influence UGLUE, with digital technology exerting the strongest effect, followed by digital industry, while digital infrastructure exerts the weakest direct effect. Urban spatial compactness (USC) mediates this relationship, functioning as a dominant transmission channel for both digital industry and digital technology, and a supplementary yet significant pathway for digital infrastructure, indicating that digitalization enhances UGLUE in part by promoting more compact urban forms. Effects are heterogeneous, as resource-based and old industrial cities benefit more from technological upgrades, while cities with higher administrative status gain more from broader digital development. These findings identify USC as a key transition pathway linking digitalization to sustainable land use outcomes, and provide evidence-based support for governance-differentiated digital economy policies that steer urban land use transition toward green and compact development trajectories. Full article

Existing research on the landscape patterns of urban parks and green spaces demonstrates a disproportionate focus across tiers within China’s urban hierarchy. Numerous studies have concentrated on economically developed first-tier cities, such as Beijing, Shanghai, and Guangzhou. In contrast, medium-to-large non-first-tier cities, especially provincial capitals and emerging cities within the first- and second tiers, have been relatively understudied, although they have received increasing attention in recent years. This bias extends regionally, with studies predominantly examining cities in the more developed central and eastern regions, while less-developed areas and lower-tier cities receive significantly less attention. This study tracks changes in park quantity, spatial concentration, patch structure and driver associations at three planning-related time points. Shenyang provides a distinct cold-region and old industrial city case, shaped by long winters, industrial renewal and outward urban growth. Furthermore, to inform park and green-space planning in Northeast China’s cold-climate cities, exemplified here by Shenyang, a major metropolis with a monsoon-influenced humid continental climate (Köppen Dwa), long cold winters, and relatively short warm summers, we document a shift in park distribution from the urban core to peripheral areas. Based on park vector layers reconstructed from planning documents, remote sensing interpretation and field verification, this study combined spatial analysis, landscape metric calculation and driver-association modeling. ArcGIS Pro was used to identify changes in distribution centers, directional extension and local clustering; FRAGSTATS 4.2 was used to calculate park landscape metrics; and SIMCA-P 14.1 was used to examine the statistical associations between selected landscape indicators and potential driving variables. The results show that the number and total area of parks in central Shenyang increased substantially from 2000 to 2024. Spatially, park distribution became less concentrated in the traditional inner city, while new clusters gradually appeared in peripheral districts and newly developed urban areas. The old urban core remained important, but its dominance weakened as park provision expanded outward. The landscape metric results further indicate that park expansion was accompanied by more irregular patch forms, stronger fragmentation and declining structural continuity. The driver association analysis suggests that climate conditions, population change, industrial restructuring, real estate investment, road construction and urban greening policies were related to different aspects of park landscape change. These associations should be interpreted as statistical relationships rather than direct causal effects. Overall, this study clarifies the spatial restructuring of park green spaces in a cold-region old industrial city and provides planning evidence for improving park connectivity, coordinating green space expansion with urban construction and supporting sustainable park system development in Northeast China. Full article

Land-use change substantially contributes to carbon emissions, yet systematic research on complex human–environment interactions in old industrial bases remains scarce. Here, we integrated multi-temporal land-use data and socio-economic statistics from 1990 to 2023 to analyze the spatiotemporal dynamics and drivers of land-use carbon emissions in Northeast China. The land-use transfer matrix, the carbon emission coefficient, exploratory spatiotemporal data analysis (ESTDA), standard deviational ellipses, and modified Kaya–LMDI models were applied. Construction land area expanded by 120%, with its share of total emissions increasing from 87% to 95%. Meanwhile, forest and grassland shrank, reducing their carbon sink capacity and increasing their net carbon emissions 1.9-fold. Spatially, emissions showed a weak global correlation but strong local lock-in (i.e., persistent stability of local spatial patterns over time), with the emission center of gravity shifting southwestward. Economic development was the dominant positive driver (provincial contribution rates: 275–529%), whereas energy intensity was the main mitigating factor (up to −409%). Population loss exerted a slight negative contribution, while energy structure showed only a weak inhibitory effect (−9.1%), reflecting the region’s path-dependent lock-in to fossil fuels. This study provides a scientific basis for differentiated carbon management strategies in Northeast China and analogous regions. Full article

The global poultry hatching industry faces severe challenges of resource waste and animal ethics issues due to the routine culling of day-old male chicks. Meanwhile, early sex identification of 4-day-incubated chicken embryos is limited by low accuracy, as embryos at this stage have weak, low-contrast blood vessels that are highly susceptible to interference from the eggshell’s texture. To address these issues, this paper proposes a non-destructive early sex identification method for chicken embryos based on an improved MobileViT-V3 model. Taking the lightweight hybrid architecture MobileViT-V3 as the backbone, we embedded a Micro Feature Enhancement module (MFE-Module) in Stage 3 to strengthen the extraction of fine vascular details, and a Multi-Scale Adaptive Attention Fusion module (MSAAF-Module) in Stage 4 to realize adaptive weighted screening of multi-source features. Experiments on the self-constructed dataset of 4-day-incubated embryos show that the improved model achieves a test set classification accuracy of 92.26%, with an F1-score of 92.15%, a recall rate of 92.12%, and a Kappa coefficient of 0.845. It outperforms mainstream models such as YOLOv12, ShuffleNetV2, ConvNeXt-T, ResNet, and Swin-ViT, with only 2.98 M parameters and an inference speed of 97.6 FPS, well exceeding the 30 FPS real-time requirement of industrial sorting lines and showing high potential for practical industrial deployment. This method provides a new scheme for non-destructive, high-precision, and high-efficiency early sex identification in poultry hatching. Full article

Urban pluvial flooding is becoming more severe in rapidly urbanizing cities under increasingly frequent extreme rainfall. Although Low Impact Development (LID) is widely used to improve infiltration and on-site stormwater retention, its hydrological performance may differ greatly across urban functional zones with distinct land-cover patterns, development intensity, and retrofit constraints. To address the lack of comparative evidence under consistent conditions, this study mapped land cover in five representative functional zones in Nanjing—old residential, new residential, commercial, industrial, and cultural/educational areas—and applied a unified CITYgreen (SCS-CN) framework under a 72 mm, 24 h, two-year design storm to simulate four standalone LID measures: ground-level greening, permeable pavement, green roofs, and grassed swales. Results showed big zone-dependent differences in hydrological benefits. Runoff reduction was greatest in highly impervious industrial and commercial areas, whereas the new residential zone showed only a marginal improvement due to its relatively favorable baseline retention conditions. Across all zones, measures that enhanced infiltration and near-surface storage performed best, with ground-level greening and permeable pavement achieving the highest retention efficiency. These findings highlight the importance of zoning-based, context-sensitive LID prioritization for urban renewal, sponge-city retrofitting, and stormwater planning in rapidly urbanizing cities. Full article

As unique settlements born of industrial civilization, workers’ residential areas carry rich heritage and the collective memory of communities they contain, endowing them with distinct historical and cultural significance. Assessing and enhancing their resilience are essential for both heritage preservation and sustainable community development. Despite the prevalence of such neighborhoods in China’s old industrial cities, systematic evaluation of their comprehensive resilience remains limited. To address this research gap, we take Taiyuan Mining Machinery Dormitory as a case study. Integrating multi-source spatial and demographic data, we construct a resilience evaluation framework based on the DPSIR model, comprising five criterion layers, 22 element layers, and 49 indicators. Combined with an obstacle degree model, it identifies key factors constraining resilience. Results indicate that comprehensive resilience of the study area is at a “moderate” level, with the “response” subsystem scoring notably low, reflecting insufficient stakeholder attention. Major obstacles include per capita shelter area, building quality, road accessibility, residents’ willingness to participate in governance, and organizational leadership capacity. Based on these findings, targeted strategies are proposed to enhance resilience amid increasing risks. This study contributes to community resilience theory and offers practical insights for the conservation and regeneration of workers’ residential areas under urban renewal. Full article

China’s Against the backdrop of the global low-carbon transition, balancing ecological protection and economic development has become a critical challenge. This study aims to examine whether and how the Low-Carbon City Pilot (LCCP) policy enhances urban industrial transformation momentum. Using panel data from 283 Chinese cities during 2008–2023, we employ a double machine learning (DDML) approach and use industrial robot installation density as a proxy for industrial development momentum. The results show that the LCCP policy significantly promotes industrial transformation and upgrading. Mechanism analysis indicates that the policy strengthens transformation momentum by enhancing government support and increasing public environmental awareness, particularly in cities with lower innovation costs. The effects are more pronounced in resource-based cities, non-old industrial bases, and economically developed cities, while also exacerbating regional disparities as more developed cities benefit more. These findings provide important implications for achieving coordinated development between carbon reduction and industrial transformation. Full article