Search Results (295)

Ensuring a sustainable and healthy human environment in university dormitories is essential for students’ learning, living, and overall health and well-being. To address this need, we carried out a series of systematic field measurements of the noise levels at 30 dormitories in three representative major urban universities in a major provincial capital city in China and designed and implemented a comprehensive questionnaire and surveyed 1005 students about their perceptions of their acoustic environment. We proposed and applied a sustainability–health-oriented, multidimensional assessment framework to assess the acoustic environment of the dormitories and student responses to natural sound, technological sounds, and human-made sounds. Using the Structural Equation Modeling (SEM) approach combined with the field measurements and student surveys, we identified three categories and six factors on student health and well-being for assessing the acoustic environment of university dormitories. The field data indicated that noise levels at most of the measurement points exceeded the recommended or regulatory thresholds. Higher noise impacts were observed in early mornings and evenings, primarily due to traffic noise and indoor activities. Natural sounds (e.g., wind, birdsong, water flow) were highly valued by students for their positive effect on the students’ pleasantness and satisfaction. Conversely, human and technological sounds (traffic noise, construction noise, and indoor noise from student activities) were deemed highly disturbing. Gender differences were evident in the assessment of the acoustic environment, with male students generally reporting higher levels of the pleasantness and preference for natural sounds compared to female students. Educational backgrounds showed no significant influence on sound perceptions. The findings highlight the need for providing actionable guidelines for dormitory ecological design, such as integrating vertical greening in dormitory design, water features, and biodiversity planting to introduce natural soundscapes, in parallel with developing campus activity standards and lifestyle during noise-sensitive periods. The multidimensional assessment framework will drive a sustainable human–ecology–sound symbiosis in university dormitories, and the category and factor scales to be employed and actions to improve the level of student health and well-being, thus, providing a reference for both research and practice for sustainable cities and communities. Full article

Urban heat island circulation (UHIC) determines the wind and thermal environments in urban areas. For Loess Tableland valley towns, the evolution characteristics of the UHIC over this negative terrain are not well understood, and therefore, it is important to investigate the evolution characteristics. A city-scale computational fluid dynamics (CSCFD) model is used, and simulation results are validated by the water tank experiment. The evolution process over such negative terrain can be divided into transient and quasi-steady stages, and in the transient stage, the airflow pattern evolves from thermal convection to city-scale closed circulation, while that in the quasi-steady stage is only city-scale closed circulation. In order to further reveal the characteristics of city-scale closed circulation, the sensitivities of different factors influencing the start time, outflow time, mixing height and heat island intensity are analyzed, and the most significant factors influencing these four parameters are urban heat flux, slope height, slope height, and potential temperature lapse rate, respectively. Finally, the dimensionless mixing height and heat island intensity for the valley town increase by 56.80% and 128.68%, respectively, compared to those for the flat city. This study provides guidance for the location and layout of built-up areas in the valley towns. Full article

The growing mismatch between ecosystem service (ES) supply and demand underscores the importance of thoroughly understanding their spatiotemporal patterns and key drivers to promote ecological civilization and sustainable development at the regional level in China. This study investigates six key ES indicators across mainland China—habitat quality (HQ), carbon sequestration (CS), water yield (WY), sediment delivery ratio (SDR), food production (FP), and nutrient delivery ratio (NDR)—by integrating a suite of analytical approaches. These include a spatiotemporal analysis of trade-offs and synergies in supply, demand, and their ratios; self-organizing maps (SOM) for bundle identification; and interpretable machine learning models. While prior research studies have typically examined ES at a single spatial scale, focusing on supply-side bundles or associated drivers, they have often overlooked demand dynamics and cross-scale interactions. In contrast, this study integrates SOM and SHAP-based machine learning into a dual-scale framework (grid and city levels), enabling more precise identification of scale-dependent drivers and a deeper understanding of the complex interrelationships between ES supply, demand, and their spatial mismatches. The results reveal pronounced spatiotemporal heterogeneity in ES supply and demand at both grid and city scales. Overall, the supply services display a spatial pattern of higher values in the east and south, and lower values in the west and north. High-value areas for multiple demand services are concentrated in the densely populated eastern regions. The grid scale better captures spatial clustering, enhancing the detection of trade-offs and synergies. For instance, the correlation between HQ and NDR supply increased from 0.62 (grid scale) to 0.92 (city scale), while the correlation between HQ and SDR demand decreased from −0.03 to −0.58, indicating that upscaling may highlight broader synergistic or conflicting trends missed at finer resolutions. In the spatiotemporal interaction network of supply–demand ratios, CS, WY, FP, and NDR persistently show low values (below −0.5) in western and northern regions, indicating ongoing mismatches and uneven development. Driver analysis demonstrates scale-dependent effects: at the grid scale, HQ and FP are predominantly influenced by socioeconomic factors, SDR and WY by ecological variables, and CS and NDR by climatic conditions. At the city level, socioeconomic drivers dominate most services. Based on these findings, nine distinct supply–demand bundles were identified at both scales. The largest bundle at the grid scale (B3) occupies 29.1% of the study area, while the largest city-scale bundle (B8) covers 26.5%. This study deepens the understanding of trade-offs, synergies, and driving mechanisms of ecosystem services across multiple spatial scales; reveals scale-sensitive patterns of spatial mismatch; and provides scientific support for tiered ecological compensation, integrated regional planning, and sustainable development strategies. Full article

Nature-Based Solutions (NBSs) offer promising pathways to enhance ecological resilience and address urban water challenges, particularly in heritage cities where conventional gray infrastructure often fails to balance environmental needs with cultural preservation. This study proposes a strategic framework for the integration of NBSs into historic urban landscapes by employing Internal–External (IE) matrix modeling and an impact–uncertainty assessment, grounded in a structured evaluation of key internal strengths and weaknesses, as well as external opportunities and threats. The Internal Factor Evaluation (IFE) score of 2.900 indicates a favorable internal environment, characterized by the multifunctionality of NBS and their ability to reconnect urban populations with nature. Meanwhile, the External Factor Evaluation (EFE) score of 2.797 highlights moderate support from policy and public awareness but identifies barriers such as funding shortages and interdisciplinary coordination. Based on these findings, two strategies are developed: an SO (Strength–Opportunity) strategy, promoting community-centered and policy-driven NBS design, and a WO (Weakness–Opportunity) strategy, targeting resource optimization through legal support and cross-sectoral collaboration. This study breaks new ground by transforming theoretical NBS concepts into actionable, culturally sensitive planning tools that enable decision-makers to navigate the unique challenges of implementing adaptive stormwater and environmental management in historically constrained urban environments. Full article

This research addresses urban heat island intensification driven by urbanization using Dianchi Lake in Kunming, China, as a case study, aiming to quantitatively evaluate the spatial extent, intensity, and land cover sensitivity differences in the cooling effects of large urban water bodies across dry/wet seasons and complex urban landscapes (forest, cropland, and impervious surfaces) to provide a scientific basis for optimizing thermal environments in low-latitude plateau cities. Based on Landsat 8/9 satellite data from dry (January) and wet (May) seasons in 2020 and 2023 used for land surface temperature (LST) retrieval combined with land use data, buffer zone gradient analysis was adopted to quantify the spatial heterogeneity of key cooling indicators within 0–1500 m lakeshore buffers. The results demonstrated significant seasonal differences. The wet season showed a greater cooling extent (600 m) and higher intensity (6.0–6.6 °C) compared with the dry season (400 m; 2.4–3.9 °C). The land cover responses varied substantially, with cropland having the largest influence (600 m), followed by impervious surfaces (400 m), while forest exhibited a minimal effective cooling range (100 m) but localized warming anomalies at 200–400 m. Sensitivity analysis confirmed that impervious surfaces were the most sensitive to water-cooling, followed by cropland, whereas forest showed the lowest sensitivity. Full article

Urban forests are very important for the environment and for people, especially in semi-arid cities where there is not much greenery. This makes heat stress worse and makes the city less livable. This paper presents a comprehensive geospatial methodology for selecting afforestation sites in the expanding semi-arid urban area of Şanlıurfa, Turkey, characterized by minimal forest cover, rapid urbanization, and extreme weather conditions. We identified nine ecological and infrastructure criteria using high-resolution Sentinel-2 images and features from the terrain. These criteria include slope, aspect, topography, land surface temperature (LST), solar radiation, flow accumulation, land cover, and proximity to roads and homes. After being normalized to make sure they were ecologically relevant and consistent, all of the datasets were put together into a GIS-based Multi-Criteria Decision Analysis (MCDA) tool. The Analytic Hierarchy Process (AHP) was then used to weight the criteria. A deep learning-based semantic segmentation model was used to create a thorough classification of land cover, primarily to exclude unsuitable areas such as dense urban fabric and water bodies. The final afforestation suitability map showed that 151.33 km² was very suitable and 192.06 km² was suitable, mostly in the northeastern and southeastern urban fringes. This was because the terrain and subclimatic conditions were good. The proposed methodology illustrates that urban green infrastructure planning can be effectively directed within climate adaptation frameworks through the integration of remote sensing and spatial decision-support tools, especially in ecologically sensitive and rapidly urbanizing areas. Full article

The public–private partnerships (PPP) mode is very popular in public infrastructure projects. The PPP model for sponge city construction (SCC) provides an effective way to curb and manage the increasingly serious ecological water problems in China. The quantitative evaluation of value for money (VFM) is an evaluation method that obtains quantitative values through a certain calculation process. However, the current studies lack a dynamic quantitative evaluation of VFM for the entire life cycle of SCC PPP projects, and cannot observe the impact of key factors on the VFM value. By constructing a system dynamics (SD) model for the VFM quantitative evaluation of SCC PPP projects from the perspective of the whole life cycle, this study can intuitively and transparently observe the impact of key factors (such as discount rate and profit margin) on the evaluation results and feasibility of adopting a PPP model in the project, offering policymakers a tool to mitigate the risks of “Pseudo-PPP” projects. After collecting cases in Anhui province from the China PPP Center, this study constructed a life cycle VFM quantitative evaluation system dynamics model suitable for SCC PPP projects that consist of the public sector comparison (PSC) value and PPP value. The results indicate that the system dynamics model can be effectively applied to the dynamic quantitative evaluation of SCC PPP projects and clarify the influence degree on and sensitivity of various factors to the VFM value. Specifically, when the discount rate increases, the decrease in the PPP value is greater than that in the PSC value, leading to an increase in the VFM value. Moreover, a reasonable profit margin is more sensitive to the VFM value and decreases as the reasonable profit margin increases. In addition, choosing different availability service fee calculation methods will result in varying the adjustment range to a reasonable profit margin that drives the adoption of VFM quantitative evaluation. These research findings have provided a viable dynamic research methodology for the quantitative VFM evaluation of SCC PPP projects. This methodology enables the dynamic visualization and easy determination of the acceptable ranges for relevant factors, offers rational policy recommendations for the quantitative evaluation of key factor values, and thereby effectively prevents PPP project violations, promoting fair and reasonable cooperation between governments and private enterprises. Full article

Examining the relationship between built environment (BE) and urban vitality (UV) is beneficial for promoting urban planning, as it deepens the understanding of how spatial design shapes urban life and activity patterns. However, the nonlinear effects of BE on UV from a spatiotemporal perspective have not been fully explored. In this study, the central urban area of Chongqing at the block scale is selected as a research case. The Gradient Boosting Decision Tree with SHapley Additive exPlanations (GBDT-SHAP) model is used to examine the nonlinear impacts of BE on UV. The results show the following: (1) The BE has a stronger overall impact on UV during holidays. Road intersection density (RID) has the greatest impact on UV on weekdays and holidays, building density (BD) has the greatest impact on weekend mornings, cultural and leisure accessibility (CLA) has the greatest impact on weekend afternoons, and commercial accessibility (CA) has the most significant impact on weekend evenings; (2) the impacts of the BE on UV exhibit significant nonlinear characteristics, with BD and park and square accessibility (PSA) showing a first increasing and then inhibiting effect on UV; lower CA, CLA, and MSA have inhibitory effects on UV, with higher normalized difference vegetation index (NDVI) values similarly demonstrating such effects; building height (BH), bus stop density (BSD), road network density (RD), and RID have enhancing effects on UV; functional mix degree (FMD) and water proximity index (WPI) show different trends in different time periods; (3) there are significant interactive effects among BE such as BD and BH, CA; RD and WPI, MSA; FMD and BH, PSA; PSA and CLA. A comprehensive understanding of these interactive relationships is crucial for optimizing the BE to enhance UV. This study provides a theoretical basis for urban planners to develop more effective, time-sensitive strategies. Future research should explore these nonlinear and interactive effects across different cities and scales to further generalize the findings. Full article

The combined effects of rapid urbanization and climate change are increasingly exacerbating the risk of urban flooding. This study develops a data-efficient framework for estimating a city’s Urban Stormwater Carrying Capacity (USCC)—the maximum stormwater volume that can be safely infiltrated, stored, and conveyed. The framework couples three rainfall scenarios—frequent, heavy, and extreme—with nine widely adopted drainage and storage measures, ranging from green spaces and permeable pavements to pipes and underground emergency reservoirs, and expresses USCC through a streamlined water-balance equation. Applied to the 24 km² Zhangmian River district in Weifang, China, the framework yields capacities of 4.84, 5.86, and 9.80 × 10⁶ m³ for the three scenarios, respectively; underground reservoirs supply ≈ 40% of the extreme-event capacity. Sensitivity analysis shows that increasing the imperviousness coefficient from 0.65 to 0.85 raises peak drainage demand by 30.8%, whereas halving reservoir depth lowers total capacity by 27.8%. Because the method requires only rainfall depth, land-cover data, and basic facility dimensions, it enables rapid, transparent scenario testing and helps planners prioritize cost-effective upgrades. The approach is transferable to other cities and can be extended to incorporate water quality or digital-twin modules in future research. Full article

Rapid urbanization, climate variability, and land degradation are increasingly challenging traditional open-field farming systems. Soilless farming (SLF) has emerged as a complementary approach to enhance horticultural resilience in space-constrained and climate-stressed environments. This review critically evaluates the role of SLF within the broader framework of climate-smart agriculture (C-SA), with a particular focus on its applications in urban and peri-urban settings. Drawing on a systematic review of the existing literature, the study explores how SLF technologies contribute to efficient resource use, localized food production, and environmental sustainability. By decoupling crop cultivation from soil, SLF enables precise control over nutrient delivery and water use in enclosed environments, such as vertical farms, greenhouses, and container-based units. These systems offer notable advantages regarding water conservation, increased yield per unit area, and adaptability to non-arable or degraded land, making them particularly relevant for high-density cities, arid zones, and climate-sensitive regions. SLF systems are categorized into substrate-based (e.g., coco peat and rock wool) and water-based systems (e.g., hydroponics, aquaponics, and aeroponics), each with distinct design requirements, nutrient management strategies, and crop compatibility. Emerging technologies—including artificial intelligence, the Internet of Things, and automation—further enhance SLF system efficiency through real-time data monitoring and precision control. Despite these advancements, challenges remain. High setup costs, energy demands, and the need for technical expertise continue to limit large-scale adoption. While SLF is not a replacement for traditional agriculture, it offers a strategic supplement to bolster localized food systems and address climate-related risks in horticultural production. Urban horticulture is no longer a peripheral activity; it is becoming an integral element of sustainable urban development. SLF should be embedded within broader resilience strategies, tailored to specific socioeconomic and environmental contexts. Full article

Intelligent algorithms and decision models are key tools for improving the efficiency and adaptability of multi-objective optimization and allocation, and for achieving sustainable utilization of water resources. This study takes Hancheng City as a case study to develop a water resource optimization allocation model based on economic, social, and ecological benefits, analyzing and predicting the supply and demand of conventional and unconventional water resources in the study area. The model is solved using the NSGA algorithm, and solutions are screened from the Pareto front using the TOPSIS-CCDM two-level decision model, with the RSR method used for comparative verification. The results show that the schemes II-2022-21 (water shortage of 17,802.35 m³/d, economic benefits of 21,019,556.17 yuan, pollutant emissions of 745.92 tons), II-2027-ACS (shortage of 14,098.76 m³/d, economic benefits of 29,401,252.75 yuan, emissions of 712.07 tons), and II-2032-ACS (shortage of 12,709.33 m³/d, economic benefits of 36,660,367.83 yuan, emissions of 700.96 tons) are in line with the water resource allocation planning for Hancheng City before 2035. These schemes not only meet the regional planning requirements but also maximize economic benefits while minimizing water shortages and pollutant emissions. The study finds that NSGA-II has an advantage in selecting more coordinated schemes, while NSGA-III focuses more on the selectivity of specific targets. Although the TOPSIS-CCDM model performs well in comprehensive evaluation, it also exposes limitations such as sensitivity to data fluctuations and high computational complexity. By developing and applying advanced optimization and decision models, this study provides a scientific water resource allocation scheme for Hancheng City, supporting the sustainable management of regional water resources, and offering a reference for future research in addressing data uncertainties and improving computational efficiency. Full article

Water resource management is crucial for sustainable agricultural and ecological development, particularly in regions with complex land-use patterns and sensitive eco-systems. The Bashang region of Zhangjiakou city, located in the agro-pastoral ecotone of northern China, is an ecologically fragile area that is currently undergoing significant land use and climate changes. Despite the importance of understanding the interplay between land use, climate change, and water conservation, few studies have comprehensively evaluated their combined effects on regional water resources. This study addresses this gap by investigating the spatiotemporal changes in the water yield (WY) and water conservation capacity (WCC) of the Bashang region under different land use and climate scenarios for the year 2035. This research employs the FLUS model to predict the future land use and the InVEST model to estimate the WY and WCC under a natural development scenario (NDS), an agricultural production scenario (APS), an ecological protection scenario (EPS), and a land planning scenario (LPS). The results reveal that the WCC is primarily influenced by precipitation, land use, and the topography. This study finds that scenarios which focus on ecological protection and land use optimization, such as the EPS and LPS, significantly enhance the water conservation capacity of the study region Notably, the LPS scenario, which limits urban expansion and increases the amount of ecological land, provides the best balance between the water yield and conservation. The findings highlight the need for integrated approaches to land use and water resource management, particularly in agro-pastoral transitional zones. The unique contribution of this research lies in its comprehensive modeling approach, which combines land use, climate data, and water resource analysis, and which provides valuable insights for sustainable land and water management strategies. Full article

The rapid acceleration of urbanization, combined with the proliferation of impervious surfaces and the inherently low permeability of soil layers, has worsened urban waterlogging. This study explores the layout of filter element seepage wells within a sponge city framework to enhance rainwater infiltration and reduce surface water accumulation, proposing an optimized method for determining well spacing and depth. The optimization uses a multi-objective genetic algorithm to target the construction cost, seepage velocity, total head, and pore water pressure. A combined weighting method assigns weights to each aim, while the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) determines the perfect spacing and depth. The results show that the optimal spacing and depth of the filter element seepage wells are 1.572 m and 2.794 m, respectively. Compared to the initial plan, the optimized scheme reduces construction costs by 21.31%, increases the rainwater infiltration efficiency by approximately 200%, raises the total hydraulic head by 17.23%, and decreases the pore water pressure by 5.73%. Sensitivity analysis shows that the optimized scheme remains stable across different weight combinations. This optimized layout significantly improves both the infiltration capacity and cost-effectiveness. Full article

How can the shape of biodiversity inform us about cities’ ecoclimatic fitness and guide their development? Can we use species as the harbingers of climatic extremes? Eco-climatically sensitive species carry information about hydroclimatic change in their distribution, fitness, and preferential gradients of habitat suitability. Conversely, environmental features outside of the species’ fitness convey information on potential ecological anomalies in response to extremes to adapt or mitigate, such as through urban parks. Here, to quantify ecosystems’ fitness, we propose a novel computational model to extract multivariate functional ecological networks and their basins, which carry the distributed signature of the compounding hydroclimatic pressures on sentinel species. Specifically, we consider butterflies and their habitat suitability (HS) to infer maximum suitability gradients that are meaningful of potential species networks and flows, with the smallest hydroclimatic resistance across urban landscapes. These flows are compared to the distribution of urban parks to identify parks’ ecological attractiveness, actual and potential connectivity, and park potential to reduce hydroclimatic impacts. The ecosystem fitness index (EFI) is novelly introduced by combining HS and the divergence of the relative species abundance (RSA) from the optimal log-normal Preston plot. In Shenzhen, as a case study, eco-flow networks are found to be spatially very extended, scale-free, and clustering for low HS gradient and EFI areas, where large water bodies act as sources of ecological corridors draining into urban parks. Conversely, parks with higher HS, HS gradients, and EFIs have small-world connectivity non-overlapping with hydrological networks. Diverging patterns of abundance and richness are inferred as increasing and decreasing with HS. HS is largely determined by temperature and precipitation of the coldest quarter and seasonality, which are critical hydrologic variables. Interestingly, a U-shape pattern is found between abundance and diversity, similar to the one in natural ecosystems. Additionally, both abundance and richness are mildly associated with park area according to a power function, unrelated to longitude but linked to the degree of urbanization or park centrality, counterintuitively. The Preston plot’s richness–abundance and abundance-rank patterns were verified to reflect the stationarity or ecological meta-equilibrium with the environment, where both are a reflection of community connectivity. Ecological fitness is grounded on the ecohydrological structure and flows where maximum HS gradients are indicative of the largest eco-changes like climate-driven species flows. These flows, as distributed stress-response functions, inform about the collective eco-fitness of communities, like parks in cities. Flow-based networks can serve as blueprints for designing ecotones that regulate key ecosystem functions, such as temperature and evapotranspiration, while generating cascading ecological benefits across scales. The proposed model, novelly infers HS eco-networks and calculates the EFI, is adaptable to diverse sensitive species and environmental layers, offering a robust tool for precise ecosystem assessment and design. Full article

Evaluating the performance of sponge city practices under actual conditions is essential for managing urban stormwater. Existing studies in urban stormwater management have rarely employed numerical simulations to model hydrological processes under actual Three-Dimensional (3D) conditions. In this study, a numerical computational model is developed to simulate the hydrological processes and reveal the temporal and spatial variation of runoff in relation to impervious surfaces and concave herbaceous fields. The applicability of the 3D modules was evaluated using the Chicago rain pattern formula under three recurrence periods: precipitation within one, five, and ten years. The results indicate that the thickness and slope of planting soil are the most sensitive factors regarding sponge city performance, with comprehensive factors of 0.754 and 0.461. The optimal structural parameters of the concave herbaceous field were obtained as follows: aquifer height, 200 mm; planting soil thickness, 600 mm; planting soil slope, 1.5%; planting soil porosity, 0.45; overflow pipeline porosity, 0.3. The flood peak reduction rate, delay rate, and total runoff control rate were the best in a recurrence period of 5a, with 88.93%, 51.11%, and 78.76%, respectively. This study offers technical and conformed methodological support for simulating water quantity processes in sponge cities, and for the control of waterlogging and the recycling of runoff. Full article