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Exploring the patterns and optimization of high-density settlements to achieve zero-carbon heating in hot summer and cold winter area 探索夏热冬冷地区高密度聚落实现零碳供暖的模式与优化
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-12 DOI: 10.1016/j.scs.2026.107152
Yuqiu Liu, Zhengnan Zhou, Yichen Han, Chaohong Wang, Yingkai Lian, Haoran Chen, Wenqi Bai, Zhuoyang Jia
In China’s hot summer and cold winter (HSCW) area, historical policies have resulted in the absence of central heating. However, intensifying extreme weather and rising living standards recently have led to a surge in heating energy consumption, accompanied by substantial carbon emissions. This study explores the feasibility of achieving zero-carbon heating (ZCH) in the HSCW area, specifically deriving heating energy from electricity generated by photovoltaic (PV) systems. This paper first measures indoor temperature, energy consumption data, and simulates PV generation across 20 residential areas in two typical cities in the HSCW area, Wuhan and Shanghai. Then, sensitivity analysis and machine learning regression with Shapley additive explanations are conducted between 14 morphology parameters and 3 primary energy indicators: ratio of energy consumption to indoor-outdoor temperature difference, available qualified PV generation for heating energy consumption, and ratio of qualified surface area. Subsequently, the study employed multi-objective optimization to balance the energy indicators of three residential area prototypes: tower, slab, and courtyard. Analysis of measured data reveals that the openness index has the most significant influence on heating energy consumption, while facade area has the greatest impact on PV indicators. However, the trend in morphological parameters optimized for the ZCH objective varies depending on building type and plot size. Conclusively, all residential types can realize ZCH, with achievable proportions at 61.00% of slab-style, 37.30% of courtyard-style, and 18.35% of tower-style. This research proposes novel approaches for reducing carbon emissions in the HSCW high-density settlements, thus providing references for related cases.
在中国的夏热冬冷地区,历史上的政策导致了中央供暖的缺失。然而,最近极端天气的加剧和生活水平的提高导致供暖能源消耗激增,伴随而来的是大量的碳排放。本研究探讨了在高低温地区实现零碳供暖(ZCH)的可行性,特别是从光伏(PV)系统产生的电力中获取供暖能量。本文首先测量了室内温度、能耗数据,并模拟了武汉和上海两个典型城市20个住宅小区的光伏发电情况。然后,对14个形态参数与室内外温差能耗比、可用于供热能耗的合格光伏发电、合格表面积比3个主要能源指标进行敏感性分析和Shapley加性解释的机器学习回归。随后,采用多目标优化方法对塔楼、楼板、庭院三种住宅小区原型的能量指标进行平衡。实测数据分析表明,开度指标对采暖能耗的影响最为显著,而立面面积对光伏指标的影响最大。然而,为ZCH目标优化的形态参数的趋势取决于建筑类型和地块大小。综上所述,所有住宅类型均可实现ZCH,其中板式住宅可实现比例为61.00%,合院式住宅可实现比例为37.30%,塔式住宅可实现比例为18.35%。本研究为HSCW高密度住区的碳减排提出了新的思路,为相关案例提供参考。
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引用次数: 0
Integrated impacts of cool coatings, street orientations, and height variability on urban cooling in 3D high-rise building arrays: CFD simulation 三维高层建筑阵列中冷却涂层、街道朝向和高度变化对城市冷却的综合影响:CFD模拟
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-06 DOI: 10.1016/j.scs.2026.107127
Tianyi Guan , Jian Hang , Qingman Li , Lan Chen , Guanwen Chen , Hanying Dong , Zhiwen Luo
Using cool coatings on building envelopes and modifying urban morphologies, such as street orientations and building height variability, are recognized as effective urban cooling strategies. However, few studies evaluate the integrated cooling performance of these strategies in three-dimensional (3D) high-rise building arrays. Moreover, most existing performance evaluations of cool coatings focus on temperature drop, while rarely considering coating costs. As a novel contribution, this study systematically investigates the combined impacts of cool coatings (cool roofs (CR), cool roofs & walls (CR&W), cool roofs & east-west walls (CR&EWW), and cool roofs & high-rise walls (CR&HW)), street orientations (north-south vs. east-west), and building height layouts (uniform-height vs. varied-height) on building surface temperature and pedestrian-level microclimate under three summer solar heating conditions (8 am, 12 pm, and 4 pm) using computational fluid dynamics simulations. Uniquely, cooling intensity (°C/m2) is proposed to quantify the average surface temperature drop per unit of cool-coated surface area by incorporating coating costs into cooling performance evaluation. Results indicate that cool coatings reduce direct sunlit surface temperatures by up to 7.5 °C, with ensemble-average building envelope drops of 0.36–1.63 °C, while their impacts on pedestrian-level air temperature (drop < 0.3 °C) and wind velocity ratio (variation < 0.06) are minimal. CR&W, CR&EWW, and CR&HW cause significantly greater ensemble-average temperature drops than CR; however, when coating costs are considered, CR&W is less cost-effective than other configurations. CR&EWW and CR&HW offer a good trade-off between cooling effect and coating costs. Moreover, north-south orientation generally shows superior cooling performance with cool coatings over east-west orientation. Height variability differentially influences the cool coating performance for high-rise and low-rise buildings. This study offers valuable insights for optimizing the spatial deployment of cool coatings in compact subtropical cities.
在建筑围护结构上使用冷却涂层和改变城市形态,如街道朝向和建筑高度变化,被认为是有效的城市冷却策略。然而,很少有研究评估这些策略在三维(3D)高层建筑阵列中的综合冷却性能。此外,现有的冷涂层性能评估大多侧重于温度下降,而很少考虑涂层成本。作为小说的贡献,本研究系统地调查的结合影响降温涂料(降温屋顶(CR)、降温屋顶和墙壁(CR& W),降温屋顶,东西方墙(CR&恶),和降温屋顶,高层墙(CR& HW)),街道方向(南北和东西),和建筑高度布局(uniform-height比varied-height)在建筑表面温度和pedestrian-level小气候三个夏天太阳能加热条件下(8点,12点,和下午4点)使用计算流体动力学模拟。独特的是,通过将涂层成本纳入冷却性能评估,提出了冷却强度(°C/m2)来量化每单位冷涂层表面积的平均表面温度下降。结果表明,冷涂层可使阳光直射下的表面温度降低7.5°C,建筑围护结构整体平均温度下降0.36-1.63°C,而对行人水平空气温度(下降0.3°C)和风速比(变化0.06)的影响最小。CR&W、CR&;EWW和CR&;HW引起的总体平均温度下降明显大于CR;然而,当考虑涂层成本时,CR&;W比其他配置的成本效益更低。creww和crhw在冷却效果和涂层成本之间提供了很好的平衡。此外,南北取向的冷却涂层通常比东西取向的冷却涂层表现出更好的冷却性能。高度变化对高层和低层建筑冷涂层性能的影响是不同的。该研究为优化亚热带紧凑型城市冷涂料的空间部署提供了有价值的见解。
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引用次数: 0
Connection of cold-wet islands to mitigate urban thermal risk 连接冷湿岛屿,降低城市热风险
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-10 DOI: 10.1016/j.scs.2026.107143
Aokang Xu , Jing Shi , Haoyuan Feng , Xiangyun Meng
Under the synergistic effects of global climate change and rapid urbanization, the urban heat island effect is intensifying, posing significant challenges to sustainable urban development and public health and safety. Research indicates that the cooling impact of isolated cooling units on the urban thermal environment is limited, whereas networked cooling systems offer superior cooling benefits by improving landscape connectivity and functional integration. This study focuses on the main urban area of Wuhan, integrating morphological spatial pattern analysis, landscape connectivity assessment, and circuit theory to develop a cold-wet network (CWN). Subsequently, CWN communities were delineated based on connectivity, and the network’s robustness was evaluated under multiple attack strategies. Key conclusions include: The concept of the wet island complements the cold island to form the cold-wet island (CWI), providing a more comprehensive definition of cooling zones; Co-optimizing the structural components of CWN (i.e., CWIs and cold-wet corridors) significantly enhances network efficiency; Differentiated management of CWN communities, through localized optimization and cross-community coordination, strengthens overall network resilience; An actual attack strategy based on “shape-scale” metrics offers a quantitative basis for prioritizing CWI protection; Adding CWIs improves CWN robustness under actual attack scenarios, suggesting that increasing cooling units is a viable strategy for mitigating urban heat. This study aims to alleviate heat stress in the main urban area of Wuhan while providing a theoretical framework for climate-adaptive urban planning and sustainable development.
在全球气候变化和快速城市化的协同作用下,城市热岛效应不断加剧,对城市可持续发展和公共健康安全构成重大挑战。研究表明,孤立冷却装置对城市热环境的冷却影响有限,而网络化冷却系统通过改善景观连通性和功能整合提供了优越的冷却效益。本研究以武汉市主城区为研究对象,结合形态空间格局分析、景观连通性评价和线路理论,构建了武汉市主城区冷湿网络。随后,基于连通性划分了CWN社区,并在多种攻击策略下评估了网络的鲁棒性。主要结论包括:湿岛的概念是对冷岛的补充,形成了冷湿岛(CWI),提供了更全面的冷区定义;协同优化CWN的结构组件(即cws和冷湿走廊)可显著提高网络效率;CWN社区差异化管理,通过局部优化和跨社区协调,增强网络整体弹性;基于“形状尺度”指标的实际攻击策略为CWI保护的优先级提供了定量基础;添加cwi可以提高CWN在实际攻击场景下的鲁棒性,这表明增加冷却单元是缓解城市热量的可行策略。本研究旨在缓解武汉市主城区的热应激,同时为气候适应性城市规划和可持续发展提供理论框架。
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引用次数: 0
AI-integrated framework for green space optimization and air quality improvement: a futuristic approach toward sustainable urban development 绿色空间优化和空气质量改善的人工智能集成框架:实现可持续城市发展的未来主义方法
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-06 DOI: 10.1016/j.scs.2026.107117
Saidur Rahaman , Dongmei Cai , Yuhan Cheng , Xing Wei , Xianda Gong
Air pollution remains a critical concern in rapidly urbanizing cities, where accelerated development and the uneven distribution and limited accessibility of green spaces exacerbate environmental challenges. Although urban green spaces can mitigate pollution, their effectiveness is often constrained by inadequate planning and management strategies. To address these issues, this study proposes a multi-stage, scenario-driven green space optimization framework that applies data-driven modeling approaches to spatially assess and maximize pollutant-specific air quality benefits. The proposed methodology integrates remote sensing data, classification algorithms, vegetation indices, and hyperspectral and bioclimatic indicators to assess canopy health, structural characteristics, and guide species-level tree selection. Additionally, a GIS-based decision support system was developed to enable real-time, adaptive urban planning using sensor-linked air quality data. To validate the framework, a comprehensive case study was conducted in Hangzhou, China from 2014 to 2024, evaluating air quality, vegetation health, and key environmental drivers to promote sustainable urban development. The results demonstrated significant reductions in CO, PM2.5, PM10, NO2, and SO2 across most regions, while a slight increase in O3 was observed, highlighting the complex dynamics of secondary pollutants. The Random Forest–based optimisation framework reveals a nonlinear response of pollutant concentrations to NDVI–LAI enhancement, with PM2.5 and PM10 showing the most spatially coherent reductions under +10–20 % greening, while gaseous pollutants exhibit weaker, spatially heterogeneous responses; temporal quadrant analysis further indicates sustained-improvement dominance for NO2 and SO2, contrasted by greater instability and trade-off behaviour for O3 and PM10. The novelty of this study lies in introducing an AI-based optimization framework that leverages machine learning and spatial–temporal diagnostics to identify where and how urban green spaces can most effectively reduce different air pollutants, offering a practical decision-support approach beyond traditional correlation analyses. Future research should emphasize practical implementation by incorporating socioeconomic, health, and accessibility metrics to support the development of sustainable cities and a climate-resilient society.
在快速城市化的城市中,空气污染仍然是一个关键问题,在这些城市中,加速发展、绿色空间分布不均和可达性有限加剧了环境挑战。虽然城市绿地可以缓解污染,但其有效性往往受到规划和管理策略不足的限制。为了解决这些问题,本研究提出了一个多阶段、场景驱动的绿地优化框架,该框架应用数据驱动的建模方法对特定污染物的空气质量效益进行空间评估和最大化。该方法综合了遥感数据、分类算法、植被指数、高光谱和生物气候指标,以评估冠层健康状况、结构特征,并指导物种水平的树木选择。此外,还开发了一个基于gis的决策支持系统,利用传感器连接的空气质量数据实现实时、自适应的城市规划。为了验证该框架,2014年至2024年在中国杭州进行了全面的案例研究,评估了空气质量、植被健康和促进可持续城市发展的关键环境驱动因素。结果显示,大部分地区的CO、PM2.5、PM10、NO2和SO2均显著减少,而O3略有增加,凸显了二次污染物的复杂动态。基于随机森林的优化框架揭示了污染物浓度对NDVI-LAI增强的非线性响应,PM2.5和PM10在+10 - 20%的绿化下表现出最明显的空间相干性降低,而气态污染物则表现出较弱的空间异质性响应;时间象限分析进一步表明,NO2和SO2的持续改善优势,与O3和PM10的更大不稳定性和权衡行为形成对比。本研究的新颖之处在于引入了一个基于人工智能的优化框架,该框架利用机器学习和时空诊断来确定城市绿地在哪里以及如何最有效地减少不同的空气污染物,提供了一种超越传统相关分析的实用决策支持方法。未来的研究应强调实际实施,结合社会经济、健康和可及性指标,以支持可持续城市和气候适应型社会的发展。
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引用次数: 0
Beyond urban hierarchy: unveiling the spatial patterns of nonhierarchical carbon emissions 超越城市等级:揭示非等级碳排放的空间模式
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-14 DOI: 10.1016/j.scs.2026.107160
Jianyu Li, Mingxing Hu, Shumin Wang, Ziye Liu, Jingyue Huang
Against the background of sustainable development, the effective management of urban carbon emissions has become a critical governance issue. However, under the urban hierarchical framework, the tasks of controlling carbon emissions and pursuing sustainable development are significantly complex. Some categories of emissions often exhibit characteristics of nonhierarchical emissions (NHEs) that are detached from the urban hierarchy. For the innovation, different from ordinary hierarchy-based research, the purpose of NHEs is to uncover the spatial mechanism of carbon emissions that are not constrained by administrative or economic hierarchies. Based on prefecture-level city data from four selected years in China (2010, 2015, 2019, and 2022), this study employs a spatial error model (SEM) and local spatial autocorrelation analysis (LISA) to capture the geographical distribution of NHE across the country. Furthermore, a core distance metric is employed to investigate the spatial distribution patterns of NHEs and their relationships with regional core cities. The study finds that the NHEs related to consumption are more strongly associated with a significant polarization effect. These cities are located in the area around the core cities, where population agglomeration leads to unique spatial patterns in specific categories of carbon emissions. In contrast, production-oriented NHEs are in the inner land. These categories of emissions often exhibit NHEs due to differences in resource endowments among cities. These findings provide a foundation for the localized governance of carbon emissions in noncore cities and introduce a place-based research perspective into carbon emission management.
在可持续发展的背景下,城市碳排放的有效管理已成为一个关键的治理问题。然而,在城市层级框架下,控制碳排放和追求可持续发展的任务非常复杂。某些类别的排放往往表现出与城市等级分离的非等级排放(NHEs)特征。在创新方面,不同于一般基于层级的研究,NHEs的目的在于揭示不受行政或经济层级约束的碳排放空间机制。基于2010年、2015年、2019年和2022年4年中国地级市数据,采用空间误差模型(SEM)和局部空间自相关分析(LISA)捕捉全国NHE的地理分布。此外,本文还采用核心距离度量,探讨了国家卫生系统的空间分布格局及其与区域核心城市的关系。研究发现,与消费相关的国民健康指数与显著的极化效应关系更为密切。这些城市位于核心城市周边区域,人口集聚导致其在特定碳排放类别上具有独特的空间格局。相比之下,以生产为导向的国家卫生机构位于内陆地区。由于城市间资源禀赋的差异,这些类别的排放往往表现出NHEs。这些研究结果为非核心城市碳排放的本地化治理提供了基础,并为碳排放管理引入了基于地的研究视角。
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引用次数: 0
Towards sustainable social housing: An integrative life cycle and multi-criteria approach 迈向可持续社会住房:综合生命周期和多标准方法
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-15 DOI: 10.1016/j.scs.2026.107164
Ximena Luque Castillo , Lorena Yepes-Bellver , Victor Yepes
Structural systems for social housing must address pressing challenges of affordability, rapid execution, and long-term sustainability. However, choosing the most appropriate alternative requires balancing economic, environmental, social, and technical dimensions under uncertainty. This study applies a hybrid multi-criteria decision-making (MCDM) framework that combines the Best–Worst Method (BWM), fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), and the Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) to evaluate five construction systems: Light Steel Frame (LSF), bolt-connected sandwich panels (LBSPS), reinforced concrete walls (RCW), monolithic reinforced concrete (RCF-M), and cast-in-place reinforced concrete (RCF-CP). The framework combines life cycle-based assessments—LCA, LCC, and SLCA— with causal analysis to capture interdependencies among criteria and generate transparent sustainability rankings. Results consistently position LSF as the top performing alternative, reflecting its balance between efficiency, durability, and reduced maintenance. Social aspects collectively accounted for nearly 40% of the total weight, surpassing economic and environmental dimensions, highlighting the central role of labor conditions, community impacts, and functionality in sustainable housing. Sensitivity analyses demonstrated stable rankings and validated the hybrid framework under alternative MCDM methods and diverse scenario perturbations. The findings provide actionable insights for housing policy in developing contexts, where industrialized systems and participatory evaluation processes can jointly advance resource efficiency, affordability, and social well-being.
社会住房的结构体系必须解决可负担性、快速执行和长期可持续性等紧迫挑战。然而,选择最合适的替代方案需要在不确定性下平衡经济、环境、社会和技术层面。本研究采用混合多准则决策(MCDM)框架,结合最佳最差方法(BWM),模糊决策试验和评估实验室(DEMATEL),以及根据折衷方案(MARCOS)的替代方案测量和排名(MARCOS)来评估五种建筑体系:轻钢框架(LSF),螺栓连接夹芯板(LBSPS),钢筋混凝土墙(RCW),整体钢筋混凝土(RCF-M)和现浇钢筋混凝土(RCF-CP)。该框架将基于生命周期的评估(lca、LCC和SLCA)与因果分析相结合,以捕捉标准之间的相互依赖关系,并生成透明的可持续性排名。结果一致表明LSF是性能最好的替代方案,反映了它在效率、耐用性和减少维护之间的平衡。社会方面合计占总权重的近40%,超过了经济和环境方面,突出了劳动条件、社区影响和功能在可持续住房中的核心作用。敏感性分析显示了稳定的排名,并验证了混合框架在不同的MCDM方法和不同的情景扰动下的有效性。研究结果为发展中国家的住房政策提供了可行的见解,在发展中国家,工业化体系和参与式评估过程可以共同提高资源效率、可负担性和社会福祉。
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引用次数: 0
Anthropogenic heat amplification in industrial zones: Unraveling heat stress risk heterogeneity in river-sea dual-core cities 工业区人为热放大:揭示江海双核城市热应力风险异质性
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-11 DOI: 10.1016/j.scs.2026.107151
Yujie Li , Jingfu Cao , Mingcai Li , Song Jiang , Jie Yang , Rui Xin , Ping Qu , Jing Chen , Jing Wang
River-sea dual-core cities exhibit marked climatic disparities between coastal and inland zones. A comprehensive analysis is therefore needed to reveal how urban form, geography, and industry jointly shape heat stress. Taking Tianjin as a representative case, this study employs an integrated approach that combines multi-source remote sensing, field surveys, and a dense meteorological station network to develop a practical assessment framework for these complex thermal dynamics. Our findings reveal three distinct thermal regimes governed by different mechanisms: compact urban cores experience intense dry heat driven by building density; coastal areas face significant humid heat stress due to marine influence and sea breeze dynamics; and specialized industrial zones create thermal anomalies that transcend conventional local climate zone (LCZ) classifications. The research demonstrates that while LCZ framework captures urban morphological variations, it requires substantial refinement to incorporate geographical context and industrial processes. Notably, our case study of the Wangkou industrial cluster shows that intensive energy consumption generates an average anthropogenic heat flux of 6.78.9 W/m2, substantially reshaping local microclimates. This pattern challenges conventional urban classification systems. In response to these distinct thermal regimes, we recommend implementing zonal mitigation strategies, including cool infrastructure in urban cores, ventilation corridors in coastal areas, and specialized thermal regulations for industrial zones. This study proposes a transferable framework for assessing urban heat risks and offers scientific support for spatially-optimized, climate-resilient planning in similar cities globally.
江海双核城市在沿海和内陆地区表现出明显的气候差异。因此,需要进行全面的分析,以揭示城市形态、地理和工业如何共同形成热应力。本研究以天津市为例,采用多源遥感、野外调查和密集气象站网络相结合的综合方法,构建了复杂热动力学的实用评估框架。我们的研究结果揭示了由不同机制控制的三种不同的热状态:紧凑的城市核心经历由建筑密度驱动的强烈干热;沿海地区由于海洋影响和海风动力而面临显著的湿热应力;和专门的工业区创造了超越传统的当地气候带(LCZ)分类的热异常。研究表明,虽然LCZ框架捕捉到了城市形态的变化,但它需要大量的改进,以结合地理环境和工业过程。值得注意的是,我们对王口产业集群的案例研究表明,密集的能源消耗产生了6.7-8.9 W/m2的平均人为热通量,极大地重塑了当地的小气候。这种模式挑战了传统的城市分类系统。为了应对这些不同的热状况,我们建议实施区域性缓解策略,包括在城市核心地区建立制冷基础设施,在沿海地区建立通风走廊,并为工业区制定专门的热法规。本研究提出了一个可转移的城市热风险评估框架,为全球类似城市的空间优化和气候适应型规划提供科学支持。
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引用次数: 0
Cold stress mitigation by urban trees: Computational fluid dynamics analysis of deciduous and evergreen effects in winter environments 城市树木缓解冷应力:冬季环境中落叶和常绿树木效应的计算流体动力学分析
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-07 DOI: 10.1016/j.scs.2026.107131
Geon Kang , Wonsik Choi , Jeong-Hee Eum , Jae-Jin Kim
Extreme cold surges, increasingly observed in mid-latitude and subtropical cities, pose serious health and safety risks for pedestrians. While nature-based solutions such as urban trees are widely recognized for mitigating summer heat, their wintertime effects remain underexplored and inconsistent. Trees can simultaneously reduce convective heat loss by lowering wind speeds and diminish solar radiation, decreasing the mean radiant temperature (MRT) and potentially aggravating cold stress. This study employs a computational fluid dynamics (CFD) model, with one-way, offline coupling to a radiation model, to investigate how deciduous and evergreen trees influence pedestrian cold stress, evaluated using the Universal Thermal Climate Index (UTCI), in a high-density urban district of Daegu, South Korea, during a winter cold-surge event. Scenarios varied tree type and height to assess aerodynamic drag, shading, and cooling effects. Results show that wind speed was the dominant driver of UTCI (Pearson correlation coefficient, R ≈ –0.97), while air temperature (R ≈ 0.3) and MRT (R ≈ 0.15) acted as secondary modifiers. Evergreen trees reduced strong wind probabilities and alleviated severe cold stress (UTCI ≤ –13 °C) in exposed zones, with tall evergreens most effective during morning and nighttime. In contrast, in sheltered low-rise areas where winds were already weak, added shading lowered MRT and air temperature, leading to worsened thermal comfort in the afternoon. Deciduous trees had limited effects owing to low winter leaf area. These results emphasize that winter planting strategies must consider tree type, canopy height, and local morphology, with evergreens suited to wind-exposed corridors and deciduous or shorter trees more appropriate for sheltered zones.
在中纬度和亚热带城市,越来越多地观察到极端寒潮,给行人带来了严重的健康和安全风险。虽然基于自然的解决方案,如城市树木,被广泛认为可以缓解夏季炎热,但它们在冬季的效果仍未得到充分探索和一致。树木可以同时通过降低风速和减少太阳辐射来减少对流热损失,降低平均辐射温度(MRT),并可能加剧冷胁迫。本研究采用计算流体动力学(CFD)模型,与辐射模型进行单向离线耦合,研究落叶和常绿树木对行人冷应激的影响,并使用通用热气候指数(UTCI)对韩国大邱高密度城区冬季寒潮事件进行评估。不同的树木类型和高度来评估空气动力阻力、遮阳和冷却效果。结果表明:风速是UTCI的主要影响因子(Pearson相关系数R≈-0.97),气温(R≈0.3)和MRT (R≈0.15)是次要影响因子。常绿树木降低了露天区的强风发生概率,缓解了严寒胁迫(UTCI≤-13°C),其中高大的常绿树木在早晨和夜间效果最好。相比之下,在风已经很弱的有遮蔽的低层区域,增加遮阳会降低MRT和空气温度,导致下午的热舒适恶化。由于落叶乔木冬季叶面积小,影响有限。这些结果强调冬季种植策略必须考虑树木类型、冠层高度和当地形态,常绿树木适合风暴露的走廊,落叶或矮乔木更适合遮荫区。
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引用次数: 0
Spatiotemporal variations of surface and canopy urban heat islands intensities and their divergence modulated by aerosol-driven radiative forcing in eastern China's urban agglomerations 气溶胶驱动辐射强迫对中国东部城市群地表和冠层城市热岛强度的时空变化及其辐散度的调节
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2025-12-30 DOI: 10.1016/j.scs.2025.107106
Yimei Yuan , Xuhong Wang , Bingqian Li , Zihao Feng , Chengyu Wang , Jiahang Yang , Jiahui Yang
Urban agglomerations, as focal points of intense human and economic activities, face growing ecological and environmental challenges due to industrial clustering, high population density, and uncontrolled urban expansion. These factors collectively limit sustainable socioeconomic development and ecological balance. Despite extensive urban heat island intensity (UHII) research, the distinct patterns of surface (SUHII) and canopy (CUHII) urban heat island intensities, particularly their responses to aerosol-driven radiative forcing, remain poorly understood. Mann-Kendall trend analysis, random forest modeling, and aerosol radiative forcing assessment based on multisource remote sensing and ground meteorological station data (2003-2023) were integrated to analyze SUHII and CUHII variations across eight major eastern China's urban agglomerations. The key findings are as follows: (1) SUHII consistently surpasses CUHII, with greater daytime effects in southern urban agglomerations but reversed nighttime trends in northern urban agglomerations; (2) Daytime SUHII increased significantly at the 95% confidence level, peaking in spring and summer; nighttime CUHII increase more marked, with 50% of cities showing significant summer rises; and (3) the daytime SUHII is governed by surface characteristic factors, while the nighttime SUHII is jointly controlled by human activities and background climatic factors. Both the daytime and nighttime CUHII are primarily driven by human activities. (4) aerosol-driven spatially and seasonally heterogeneous radiative forcing increases the UHII in northern urban agglomerations (BTH, CP, and GP) but suppresses it in southern urban agglomerations (YRD, CY, and YRMR), except in winter (cooling effect). The results provide insights into UHII-aerosol interaction mechanisms and support region-specific thermal environment management strategies.
城市群作为人类活动和经济活动的集中地,由于产业集聚、人口密度高、城市无序扩张等原因,面临着日益严峻的生态环境挑战。这些因素共同制约着社会经济的可持续发展和生态平衡。尽管对城市热岛强度(UHII)进行了广泛的研究,但地表(SUHII)和冠层(CUHII)城市热岛强度的不同模式,特别是它们对气溶胶驱动的辐射强迫的响应,仍然知之甚少。基于2003-2023年多源遥感和地面气象站数据,综合Mann-Kendall趋势分析、随机森林模型和气溶胶辐射强迫评估,分析了中国东部8个主要城市群的SUHII和CUHII变化。主要发现如下:(1)SUHII持续优于CUHII,在南方城市群白天效应更大,而在北方城市群夜间趋势相反;(2)白天SUHII在95%置信水平上显著增加,在春夏季达到峰值;夜间CUHII增长更为明显,50%的城市在夏季出现显著增长;(3)白天受地表特征因子控制,夜间受人类活动和背景气候因子共同控制。白天和夜间的CUHII主要是由人类活动驱动的。(4)气溶胶驱动的空间和季节非均质辐射强迫增加了北部城市群(BTH、CP和GP)的UHII,但抑制了南部城市群(YRD、CY和YRMR)的UHII,冬季除外(冷却效应)。研究结果为深入了解uhii -气溶胶相互作用机制提供了见解,并为区域热环境管理策略提供了支持。
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引用次数: 0
Rooftop PV layout generation and optimization model for large-scale building cluster 大型建筑集群屋顶光伏布局生成及优化模型
IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Pub Date : 2026-02-01 Epub Date: 2026-01-06 DOI: 10.1016/j.scs.2026.107129
Rui Miao , Haoqing Zhu , Yi Zhang , Kanghua Li , Yuan Yuan , Pengyuan Shen , He Qi
Rooftop photovoltaic (PV) deployment at the cluster scale is critical for advancing urban decarbonization, yet existing methods often oversimplify available area estimation, neglect engineering constraints, and struggle to balance energy, economic, and environmental objectives. To address these gaps, this study proposes an integrated model comprising three modules: (1) high-fidelity identification of available rooftop area by explicitly excluding shadow area, obstacles with buffer zones, and maintenance pathways; (2) automated generation of 3D engineering-feasible PV layouts; and (3) a hybrid single- and multi-objective optimization with TOPSIS-based decision-making. Applied to a 245-building cluster in Shenzhen, the model identified 23,982 m² of available area (46.51 % ratio), more conservative than typical utilization-factor assumptions. It generated detailed 3D, module-level PV layouts for 198 buildings, enabling high-fidelity PV output simulation accounting for site-specific orientation, tilt, and shading. Across all budget levels, the optimized solutions outperformed 30,000 random alternatives, with internal rates of return ranging from 16.1 % to 19.2 %. Under the high-budget scenario, the CEB-optimal solution, which utilizes all technically feasible rooftops, achieves a 10-year cumulative energy yield of 61.61 GWh and carbon emission reductions of 27,725.59 t CO₂. By decoupling layout generation from optimization, the framework reduces computational complexity and enables efficient generation of optimized deployment solutions. The proposed framework facilitates large-scale rooftop PV deployment and contributes to the decarbonization of urban energy systems.
以集群规模部署屋顶光伏(PV)对于推进城市脱碳至关重要,但现有方法往往过于简化可用面积估算,忽视工程约束,难以平衡能源、经济和环境目标。为了解决这些差距,本研究提出了一个包含三个模块的集成模型:(1)通过明确排除阴影区域、带缓冲区的障碍物和维护路径,高保真地识别可用的屋顶区域;(2)自动化生成三维工程可行的光伏布局;(3)基于topsis的单目标和多目标混合优化决策。将该模型应用于深圳245栋建筑集群,得出可利用面积为23,982平方米(46.51%),比典型的利用因子假设更为保守。它为198座建筑生成了详细的3D、模块级光伏布局,实现了高保真的光伏输出模拟,考虑了场地特定的方向、倾斜和阴影。在所有预算水平上,优化后的解决方案都优于3万个随机选择方案,内部回报率在16.1%至19.2%之间。在高预算情景下,ceb最优方案利用了所有技术上可行的屋顶,10年累计发电量为61.61 GWh,碳排放量减少27,725.59吨二氧化碳。通过将布局生成与优化解耦,该框架降低了计算复杂度,并能够有效地生成优化的部署解决方案。拟议的框架促进了大规模的屋顶光伏部署,并有助于城市能源系统的脱碳。
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Sustainable Cities and Society
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