Search Results (4,937)

This study developed a comprehensive framework integrating ecosystem services (ESs), ecological adaptability, and ornamental value to guide tree species selection in historic cities constrained by soil salinization and subsurface heritage conservation. Taking Kaifeng, Henan Province, as a case study, we employed field surveys, i-Tree Eco, the Analytic Hierarchy Process, and K-means clustering to evaluate trees across protective, park, attached, and square green spaces. Results showed that carbon-related services dominated Kaifeng’s urban ES profile, with carbon storage (CS) and sequestration (CSE) value densities of 9.09 ¥·m⁻² and 0.84 ¥·m⁻²·y⁻¹, respectively. Air pollutant removal (AR) (0.21 ¥·m⁻²·y⁻¹) and P (0.009 ¥·m⁻²·y⁻¹) values remained comparatively low. Camphora officinarum Nees ex Wall delivered the highest annual ES value per tree (33.24 ¥·y⁻¹). Plaza greenery outperformed other space types in overall service provision, and deciduous broadleaf species generated greater ES value than evergreen conifers. Cluster analysis identified four functional groups: stress-tolerant pioneers, balanced adapters, high-efficiency carbon sinks, and ornamental specialists—each suited to specific green space contexts. This integrated framework offers a transferable approach for evidence-based tree selection in saline historic cities, supporting nature-based solutions in urban green space (UGS) planning. Full article

Urban nature and nature-based solutions are increasingly promoted to enhance public space experience and urban climate resilience. In Public and semi-public indoor settings, biophilic design is considered beneficial for stress reduction and mental health restoration through the introduction of natural elements such as plants. However, research focusing on the specific visual features of plants and the underlying mechanisms remains limited. Based on 200 indoor greenery images and their multi-dimensional feature vectors, and combined with questionnaire data from 253 valid participants, this study developed a quantitative framework of plant visual features and adopted a two-level analytical approach. At the image level, linear mixed-effects models (LMMs) were used to identify how plant features influenced immediate responses. At the group level, partial least squares structural equation modelling (PLS-SEM) was employed to examine how cumulative restorative experience translated into affective states, perceived restorativeness, and behavioural intention. The results showed that Green View Index (GVI) and species richness were the most stable positive features, while plant health status, certain planting modes, and spatial layer-related features also showed significant effects. Restorative experience influenced behavioural intention mainly through positive affect and perceived restorativeness. These findings provide evidence for biophilic design, offering quantitative support for incorporating indoor public space into broader urban nature and public space framework. Full article

Distance-decay models are fundamental to accessibility modeling; yet their alignment with actual travel behavior remains insufficiently examined in empirical terms. To help address this gap, we propose a dual-component Tanner–Gaussian decay model that seeks to mitigate two key limitations of traditional accessibility frameworks by simultaneously describing the phenomena of full decay and local peaks. The model is calibrated using survey data from an urban park in Hangzhou, China, and subsequently assessed on two additional datasets from Wuhan and Shanghai. Results indicate that: (1) traditional Gaussian functions may overestimate short-distance and underestimate long-distance accessibility, while Tanner functions tend to capture long-tail decay more effectively and appear more suitable for long-distance accessibility estimation; (2) the proposed dual-component model performs favorably in large samples, though its stability appears sensitive to sample size. By comparing the application of multiple accessibility models across three datasets, we highlight how their suitability varies depending on the specific context. This comparison may offer a reference that could assist designers in identifying underserved areas and supporting more equitable access to urban green spaces in the context of rapid urbanization. Full article

In people-centered urban planning, enhancing the well-being of residents and tourists is one of the core objectives. Tourist emotion serves not only as a key indicator of the tourism experience but also indirectly reflects the quality of a city’s public spaces and built environment. In recent years, user-generated content has provided abundant data for understanding human emotional responses in urban environments, while deep learning models offer new technological pathways for extracting spatial–emotional associations from such data. However, existing research lacks a systematic evaluation of emotion analysis models from an urban spatial perspective and their application to uncover the relationship between emotional distribution and spatial characteristics in specific urban contexts. Based on a dataset of 9419 manually annotated travel reviews from Harbin, this study developed a multi-level evaluation framework and conducted a systematic comparison of seven emotion analysis models. This study then screened for the optimal model combinations based on two dimensions—spatial location and emotion polarity—to create a model matching matrix for mapping Harbin’s emotion map. Subsequently, a regression analysis was performed to examine the relationship between emotions and built environment elements. The results show that the ERNIE model demonstrated the best overall performance. Road density, green space density, and accommodation facility density were positively correlated with emotion, while POI diversity showed a negative correlation. This study demonstrates that emotion analysis technology can serve as a valuable analytical tool for identifying spatial patterns of sentiment, thereby offering empirical support for optimizing spatial design parameters and advancing a more people-centered approach to urban development. Full article

In urban areas, green spaces have become the main refuge for biodiversity, providing essential habitat and resources for urban-adapted species. However, scientific evidence on the fitness consequences of urban green space management for urban populations remains scarce, limiting our ability to design successful conservation and management strategies. Here, we assess the fitness consequences of different levels of management practices in green spaces (i.e., high for areas with continuous intervention such as regular mowing and irrigation, and low for areas with minimal, sporadic maintenance) based on a 19-year long-term monitoring of the Eurasian Tree Sparrow (Passer montanus), a species with high behavioural plasticity in response to human-altered habitats. We formulated a unistate capture–mark–recapture model to estimate age-dependent survival while accounting for uncertainty in recapture probability. Furthermore, by means of GLMMs, we tested if the level of management influences reproductive parameters (i.e., breeding failure, number of eggs, nestlings, fledglings, brood number from the same year, breeding success). We found that high urban green space management caused a decline in adult survival, but we found no effect on juvenile survival. We also found lower breeding failure, a greater number of eggs, and larger brood numbers in the low management areas, but no differences were found in the number of nestlings and fledglings. Consequently, we found no differences in overall breeding success. Our results highlight the reduction in survival in a near-threatened passerine species due to routine green urban space management, in addition to differences in reproductive parameters depending on the degree of green urban space management. Overall, we confirm that the same species show several reproductive strategies with different breeding effort to reach similar breeding success, whatever the human context is. However, birds pay the cost in adult survival, and probably in shortening life span. Therefore, the management of urban green spaces has a negative impact on biodiversity in cities. It is necessary to review the management practices of these urban areas and promote practices that are friendly to biodiversity. Full article

This study investigates the rapid, often uncontrolled urban expansion in Khenchela, a medium-sized city in Algeria’s eastern High Plains, and its profound environmental repercussions amid semi-arid fragility. Drawing on sustainable urban development and resilience frameworks, it dissects pressures such as green space reduction (from 45 ha in 1998 to 33 ha in 2023, dropping per capita from 6.1 m² to 3 m² below WHO standards), water scarcity with 35% leakage losses waste mismanagement, informal settlements on hazardous lands, air/soil pollution, and climate vulnerabilities like heat waves and flooding. Employing a mixed-methods approach documentary analysis of (MPLUUP, LUP and MDP) plans, GIS cartography of spatial evolution (2000–2025), statistical demographics, field observations, and institutional critiques, the research exposes governance gaps: fragmented coordination, weak ecological integration, and resource shortages. It reveals socio-spatial disparities across functional zones, underscoring the need for adaptive, participatory strategies that promote polycentric and compact urban forms, enhanced biodiversity, efficient infrastructure, and inclusive governance to strengthen urban resilience. Full article

Urban green spaces are increasingly threatened by rapid urban expansion, making their continuous monitoring and prediction essential for sustainable urban management. This study investigates the spatiotemporal dynamics of urban garden landscapes in Shiraz, Iran, by integrating multi-temporal Landsat imagery, GIS analysis, and CA–Markov modeling. Landsat data from 2003, 2013, and 2023 were processed to derive the Normalized Difference Vegetation Index (NDVI), which was classified into four vegetation-density categories to quantify land-cover transitions. A CA–Markov framework implemented in IDRISI TerrSet (Version 20.0) was then employed to simulate spatial dynamics and predict vegetation changes for 2033. Results reveal a significant expansion of non-vegetated areas from 711.93 ha in 2003 to 976.66 ha in 2023, accompanied by a decline in dense vegetation from 403.68 ha to 382.64 ha. Model projections indicate a further reduction in dense vegetation to 239.35 ha by 2033, suggesting ongoing fragmentation of urban green infrastructure driven by development pressures. By combining time-series remote sensing, GIS-based spatial analysis, and predictive modeling, this study provides an integrative framework for detecting, interpreting, and forecasting urban land-cover change. The findings offer evidence-based insights to support sustainable urban planning, green infrastructure protection, and climate-resilient city management in rapidly growing urban environments. Full article

Urban green spaces provide essential ecosystem services, yet mismatches between subjective perceptions and objective assessments may constrain effective planning. This study examines the correspondence between perceived and measured ES across two contrasting urban green spaces in Shanghai: Century Park, a managed urban park, and Sanlin Green Space, a naturalistic urban forest. Objective ecosystem services (regulating, supporting, and cultural) were quantified using UAV-based biotope mapping and indicators including biophysical metrics (Net Primary Production, Water Retention, PM10 removal, and Land Surface Temperature), structural diversity indices (Shannon Diversity of land cover, vegetation, and tree structure), and visual–spatial proxies (Green View Index, Sky View Index, Water View Index, color metrics, and spatial openness). Subjective perceptions were derived from panoramic image-based questionnaires, with perception scores predicted using XGBoost and aggregated via SHapley Additive exPlanations (SHAP). Correlation analyses, spatial regression models, and partial least squares structural equation modeling were applied to explore relationships and pathways. Results show weak but significant positive associations in the urban park, whereas no overall correspondence was observed in the urban forest. Spatial mismatches were concentrated in biotopes with distinctive visual–ecological features and in fragmented areas. Green View Index is associated with higher perceptions in both sites, while the Sky View Index reduced perception in the forest context. These findings highlight strong context dependence in perceived–measured ecosystem service relationships and underscore the importance of integrating ecological structure and visual legibility in the design and management of the studied urban green spaces in Shanghai. Full article

Global urban development has fully entered the stage of stock renewal, and the synergy between public health and historic heritage conservation has become a core issue of urban sustainable development in the post-pandemic era. As special spatial units carrying urban cultural memories, historic districts generally face problems such as chaotic traffic functions, a lack of slow traffic spaces, and insufficient public health support. Existing studies lack a public health-oriented special evaluation system and a sustainable renewal path adapted to their characteristics. This paper systematically sorts out eight core impact paths of street built environment elements on public health and constructs a healthy street evaluation system for historic districts, including six dimensions (transportation facilities, green squares, ancillary facilities, street-front commerce, urban furniture, and street network) and 30 core elements combined with the spatial and cultural characteristics of historic districts. Taking five typical streets in the Liuhe Area of Hankou Historic District as an empirical case, a comprehensive evaluation is carried out using a combination of quantitative surveys, questionnaire surveys, and spatial analyses. The results show that the overall health performance of street space in the study area is low, with extremely unbalanced development across dimensions. The core shortcomings are concentrated in incomplete slow traffic systems, lack of public spaces, prominent parking chaos, and fragmented historic styles, and the health problems of streets with different functional types show significant typological differentiation characteristics. Based on this, this paper proposes five systematic renewal strategies, transportation system optimization, public space improvement, landscape system perfection, historic style activation, and long-term mechanism construction, for achieving the synergistic goals of historic culture conservation, public health promotion, and urban sustainable development. This study not only enriches the theoretical system of research on healthy spaces in historic districts but also provides a referable evaluation framework and practical approach for modern historic districts in China and other similar historic districts with comparable spatial textures and functional characteristics. Full article

With the accelerated transformation of green shipping and the advancement of ship electrification, lithium-ion batteries have become the core solution for ship propulsion due to their advantages of high energy density and zero emission. Efficient thermal management serves as a key technical support to ensure the safe and stable operation of batteries, extend their service life, and mitigate the risk of thermal runaway. Lithium-ion batteries accumulate heat during discharge, and pure phase change material (PCM) cooling systems are limited by low thermal conductivity, leading to excessive battery temperature rise and poor temperature uniformity. To address this problem, RT42 (a paraffin-based PCM with a melting temperature range of 311.15–316.15 K) was selected as the PCM in this study. The battery thermal management system (BTMS) coupling RT42 with a three-dimensional fin network structure was designed. Numerical simulations were conducted via ANSYS Fluent, and the enthalpy-porosity method was adopted to simulate the PCM phase change process. The effects of fin distribution, spacing and layer number on BTMS performance were systematically investigated and compared. Results show that the heat transfer process in the PCM can be significantly improved due to the three-dimensional fin network, and the battery maximum temperature can be reduced by 7.53 K compared with the pure PCM system. This study provides theoretical support for the design and optimization of high-efficiency BTMS. Full article

The built environment constitutes a significant factor influencing the physical and mental health of the elderly and has garnered sustained interdisciplinary attention in recent years. Based on 425 publications from the Web of Science database spanning 2001 to 2025, this study employed Citespace to conduct a quantitative analysis and synthesis of the relevant literature, aiming to explore the evolutionary trends, hotspot distributions, and pathways of influence regarding the impact of the built environment on elderly health. The results indicate a close positive correlation between the population ageing trend and annual publication growth. The total publication volume exhibited a shift from gradual to rapid growth, demonstrating a distinct phased evolutionary pattern. The research hotspots displayed a gradient structure of descending research intensity: “physical activity—quality of life—mental health.” The impact of the built environment (e.g., green space, street quality) on elderly health can be primarily categorised into three pathways: direct effects, physical activity, and mental health. Macro-level allocation of elderly care facilities and micro-level construction of age-friendly living circles represent the principal optimisation strategies currently employed to address elderly health needs. Finally, potential future research directions are discussed, encompassing aspects such as spatial scales, health representations, and mechanism expansion, with the aim of providing reference and insights for advancing the initiative of “healthy ageing.” Full article

To address insufficient carbon integration, weakly verifiable quality constraints, and unstable Pareto-set generation in construction-stage green decision-making, this study develops a multi-objective optimization model for construction mode configuration and an engineering-oriented genetic algorithm (GA) framework for Pareto solution generation under hard feasibility constraints. In a construction organization scenario, duration, cost, and carbon emissions are formulated as parallel objectives, while a quality threshold, explicit process logic, and basic resource and workface-feasibility conditions are incorporated to ensure engineering implementability. Construction-stage carbon emissions are quantified using the emission factor method under an auditable activity-level accounting framework. The configured GA framework is compared with the conventional GA, the Non-dominated Sorting Genetic Algorithm II, and the Non-dominated Sorting Genetic Algorithm III through repeated-run statistics and multi-metric evaluation. On the main case, it achieves the highest mean hypervolume (0.723 ± 0.074, mean ± standard deviation), the lowest mean spacing (0.076 ± 0.207), and the smallest average convergence generation (18.49 ± 2.57). The Pareto results reveal a clear trade-off among duration, cost, and carbon emissions, in which high-load beam-and-slab formwork and concrete-related activities dominate cost and carbon variation, whereas schedule advantage mainly depends on stronger compression of critical-chain activities and inter-floor handover. Full article

Rapid urbanization and the decline of inner-city areas have led to a sharp increase in vacant houses in large cities. Cities are increasingly converting vacant land into green space to mitigate associated negative externalities. This study quantifies the urban heat island (UHI) mitigation effects of green infrastructure using meta-analysis and applies the derived relationships to predict both on-site and surrounding cooling effects for vacant land. First, we conducted a meta-analysis of published studies reporting the cooling effects of green infrastructure and derived regression equations relating green-space area to (i) cooling within the green space, (ii) cooling in the surrounding area, and (iii) the spatial extent of the cooling effect. Second, we applied these equations to two high-density areas in Sungui-dong, Nam-gu, Incheon, Republic of Korea. The results suggest that introducing a neighborhood park at Site A (7559.5 m²) would reduce air temperature by up to 2.751 °C within the park and by 1.507 °C up to 62 m beyond the park boundary. A pocket park at Site C (992.1 m²) would reduce air temperature by up to 2.269 °C within the park and by approximately 0.92 °C in the surrounding area. These findings provide quantitative evidence that green infrastructure can serve as an effective environmental intervention and support the adoption of climate-responsive urban regeneration policies. Full article

Previous research has found an association between PM_2.5 exposure and worsening depression; however, studies specifically examining the harmful effects of individual PM_2.5 components are relatively limited. This national survey enrolled individuals aged 45 and older in mainland China, collecting personal data and assessing depression. Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10). Monthly exposure to PM_2.5 and its seven components—black carbon (BC), organic matter (OM), nitrate (NO₃⁻), sulfate (SO₄²⁻), ammonium (NH₄⁺), soil particles (SOIL), and sea salt (SS)—was matched to each participant’s residence. Linear mixed-effects models (LMEs) assessed the association between single pollutants and depression score, while weighted quantile sum (WQS) regression examined the effect of mixed exposure and identified the contribution of each component. Modifying effects of social activity and green space were also evaluated. A total of 9725 participants were included. In single-exposure models, each interquartile range (IQR) increase in PM_2.5 (29.18 μg/m³), BC (2.25 μg/m³), OM (7.18 μg/m³), SOIL (6.04 μg/m³), and SS (0.14 μg/m³) was significantly associated with an increase in depression score of 0.90 (95% CI: 0.59, 1.20), 0.71 (95% CI: 0.42, 1.09), 0.94 (95% CI: 0.61, 1.26), 0.51 (95% CI: 0.38, 0.63), and 0.53 (95% CI: 0.33, 0.73) points, respectively. In mixed-exposure models, each IQR increase in the mixture of all components was associated with a 1.104-point rise in depression score (95% CI: 0.901, 1.307), with BC having the largest weight (33.6%), followed by SOIL (28.59%) and SS (25.05%). The harmful effects of PM_2.5 and specific components on depression were lower among those who participated in social activities or lived in areas with higher levels of green space (p < 0.05). These findings suggest that the harmful effects of PM_2.5 on depression may be influenced by its components, and that social activity and green space could reduce the risk of depression associated with PM_2.5 and its components. Full article

Accelerated urbanization in Ulaanbaatar, Mongolia, has driven substantial changes in Land Use and Land Cover (LULC), threatening sustainable urban ecosystems. This study investigates historical LULC dynamics (2000–2021) and simulates future expansion scenarios through 2050 using a hybrid Machine Learning (ML) and Cellular Automata-Artificial Neural Network (CA-ANN) approach. Multi-temporal classification was performed using Support Vector Machine (SVM) and Random Forest (RF) algorithms. Both classifiers demonstrated high and comparable accuracy; SVM achieved an average Kappa coefficient of 0.8939 while RF achieved 0.8917, a marginal difference that should be interpreted with caution. Change detection analysis revealed a continuous expansion of built-up areas at the expense of dense forest and grassland, a trend driven largely by accessibility factors. Future projections indicate that even as the rate of urbanization may slow, encroachment on green spaces will persist without policy intervention. This research presents a replicable methodological workflow for monitoring urban sprawl and provides evidence to inform sustainable land management and reforestation strategies in rapidly developing urban regions. Full article