Building and Environment最新文献

{"title":"Evaluating Machine Learning Models for Sustainable Building Design: Energy, Emissions, and Comfort Metrics","authors":"Farshid Dehghan ,&nbsp;César Porras Amores ,&nbsp;Leila Khanmohammadi ,&nbsp;Rania Labib","doi":"10.1016/j.buildenv.2025.113582","DOIUrl":"10.1016/j.buildenv.2025.113582","url":null,"abstract":"<div><div>This study assesses six machine learning regression models—Random Forest (RF), K-Nearest Neighbors (KNN), Support Vector Regression (SVR), Artificial Neural Network (ANN), Extreme Gradient Boosting (XGBoost), and Linear Regression (LR)—for predicting building performance in a 79.35 m² residential unit in Sari, Iran (ASHRAE Zone 3A). The EnergyPlus model, calibrated with three years of utility data (2021–2023) per ASHRAE Guideline 14, used a synthetic dataset of 1826 configurations with 25 input variables. Five metrics were evaluated: Primary Energy Consumption (kWh), CO₂-equivalent Emissions (kg), Indoor Air Quality (IAQ, ppm), Predicted Percentage of Dissatisfied (PPD, %), and Visual Discomfort Hours (VDH, hr). The dataset was split into 60 % training and 40 % testing sets, with performance measured by RMSE, R², and MAPE. RF and XGBoost excelled, achieving test R² values of 0.9188–0.9578, reducing RMSE by up to 31 % compared to LR (R²: 0.35–0.50). Hyperparameter tuning via Grid Search and Bayesian Optimization improved accuracy, with XGBoost reaching an R² of 0.9578 for IAQ. Sensitivity and SHAP analyses highlighted ventilation and HVAC as key drivers. Scenario analysis with 1000 bootstrap iterations showed trade-offs: increased ventilation increased energy use by 110.7 % and emissions by 76.2 % but improved IAQ by 20.3 %. Optimization reduced energy consumption by 34.3 % and emissions by 38.1 %, enhancing comfort. RF and XGBoost are robust for sustainable building design optimization.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113582"},"PeriodicalIF":7.6,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144987975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Pattern-constrained deep learning model for urban canopy turbulence reconstruction from sparse sensor data","authors":"Yong Cao ,&nbsp;Peixing Xie ,&nbsp;Guoshuo Huang ,&nbsp;Wei Wang ,&nbsp;Wen-Li Chen ,&nbsp;Gang Hu ,&nbsp;Shuyang Cao","doi":"10.1016/j.buildenv.2025.113535","DOIUrl":"10.1016/j.buildenv.2025.113535","url":null,"abstract":"<div><div>Traditional numerical simulations for estimating the pedestrian-level wind environments are often computationally intensive and time-consuming. While machine learning-based reconstruction offers potential for efficient, high-fidelity estimation using sparse sensor data, challenges persist due to chaotic turbulence, architectural heterogeneity, and sensor sparsity. This study proposes a pattern-constrained generative adversarial network (PCG) to reconstruct instantaneous urban wind fields from sparse, flexibly distributed sensor measurements. The PCG framework integrates a contrastive learning-driven Flow Pattern Extraction Module (FPEM) that encodes aperiodic physical features, enabling the generative model to capture multi-scale turbulent structures. Validated on high-fidelity large-eddy simulation data from Niigata City, the PCG demonstrates significant improvements over baseline models, achieving <span><math><mo>&gt;</mo></math></span>15% improvement in most metrics (MSE, <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> and LPIPS). Key innovations include the capacity of FPEM to distill monotonic latent representations from chaotic flow dynamics and the adaptability to varying sensor numbers (16–48 sensors). Results show that the PCG maintains robust reconstruction accuracy even with non-optimal sensor configurations, outperforming conventional approaches in both numerical accuracy and spatial fidelity of flow patterns.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113535"},"PeriodicalIF":7.6,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial patterns of probability distributions for concentration fluctuations at the street network scale","authors":"Karine Klippel ,&nbsp;Elisa Valentim Goulart ,&nbsp;Torsten Auerswald ,&nbsp;Elson Galvão ,&nbsp;Patrick Marques Ciarelli ,&nbsp;Neyval Costa Reis Jr. ,&nbsp;Omduth Coceal","doi":"10.1016/j.buildenv.2025.113491","DOIUrl":"10.1016/j.buildenv.2025.113491","url":null,"abstract":"<div><div>This study investigates concentration fluctuations in street networks, focusing on the spatial dependence of their probability distribution functions (PDFs) and their representation through statistical models. Direct numerical simulations (DNS) of passive scalar dispersion were performed to characterize these fluctuations in a regular street network composed of rectangular buildings. The scalar was continuously released from a ground-level point source at an intersection, with a wind forcing angle of 45 degrees to the street orientation. Clustering analysis identified three regions within the plume: (1) the plume edge, with exponential-like distributions, high intermittency, and extreme skewness and kurtosis; (2) the transition region, with asymmetric distributions and reduced intermittency; and (3) the plume centre, exhibiting Gaussian-like distributions with negligible intermittency and near-zero skewness. Four theoretical distributions—Gamma, Beta, Lognormal, and Weibull—were evaluated for their ability to model these fluctuations. Gamma and Weibull provided the best fits overall, capturing variations in distribution shapes and accurately modelling moderate to extreme concentrations across the different regions. The Gamma distribution was the most consistent, demonstrating strong performance for both the 50th and 98th percentiles of the inverse cumulative density function (ICDF). Analyses of model performance for separate moments revealed that the Gamma model performed best in predicting the variance in high-fluctuation regions (cluster 1) whereas the Beta model showed superior results for skewness and kurtosis in low-fluctuation areas (cluster 3). All models failed to accurately capture higher-order moments (skewness and kurtosis) in cluster 1, with none demonstrating significant superiority, highlighting challenges in accurately modelling fat-tailed distributions.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113491"},"PeriodicalIF":7.6,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-resistance duct fitting design method based on the discrete adjoint principle: A case study of a duct tee","authors":"Yingying Wang ,&nbsp;Ran Gao ,&nbsp;Junkai Ren ,&nbsp;Ao Tian ,&nbsp;Yibu Gao ,&nbsp;Zhong Yu ,&nbsp;Yongzhen Guo ,&nbsp;Shengrui Yu","doi":"10.1016/j.buildenv.2025.113591","DOIUrl":"10.1016/j.buildenv.2025.113591","url":null,"abstract":"<div><div>Duct fittings are widely used in building fluid transmission and distribution systems, and the flow resistance that they generate results in significant energy consumption for these systems. To solve this problem, this paper proposes a low-resistance duct fitting shape optimization method that is based on the discrete adjoint principle. Compared with the traditional gradient-free optimization method, the discrete adjoint method can efficiently obtain the gradient information of the objective function about a large number of design variables, especially for complex structural optimization problems in high-dimensional design space. The method takes the governing equations of the flow field as constraints and constructs an augmented objective function by introducing Lagrange multipliers, from which the adjoint equations are derived to determine the distribution of the multipliers. The gradient of the objective function with respect to the design variables is then solved for. Next, the steepest descent method is used for iterative optimization, and the mesh deformation technology is applied to achieve free deformation of the mesh. To validate the effectiveness of this approach, a new type of tee with low resistance is designed by taking a T-shaped tee as an example. Numerical simulations and full-scale experiments are used to validate the optimization effect of the novel tee, and the visual field of the resistance distribution and energy loss of the tee is obtained through energy dissipation, which reveals the essential reason for resistance formation. The results show that at the same area ratio, when the flow ratio is 0.1‒0.9, the resistance reduction rate of the straight-direction section of the novel tee is 36 %‒92 %, which reduces the flow resistance significantly. The research results of this paper provide a new method for the optimization of duct fittings of building fluid transmission and distribution systems.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113591"},"PeriodicalIF":7.6,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lighting-based alertness enhancement in low-light environments: Spectral modulation effects and psychophysiological evidence","authors":"Bang Qin ,&nbsp;ZhongQiang Wu ,&nbsp;XiaoFei Yang ,&nbsp;Dan Li ,&nbsp;PeiYu Wu ,&nbsp;YiZhou Chu ,&nbsp;ShenFei Chen ,&nbsp;RongJun Zhang ,&nbsp;Qi Yao","doi":"10.1016/j.buildenv.2025.113589","DOIUrl":"10.1016/j.buildenv.2025.113589","url":null,"abstract":"<div><div>The non-visual responses, associated with circadian rhythm and alertness, can be predicted by melanopic equivalent daylight illuminance (m-EDI). Current lighting for alertness enhancement is often conducted under bright conditions, potentially causing discomfort glare in low-light environments. Metamerism refers to the phenomenon that different spectra produce the same visual stimulus, which allows the lighting to specifically activate non-visual responses without altering visual perception. However, there remains insufficient evidence to substantiate the ability of metameric light to enhance alertness under low-light conditions. In this study, we designed two lighting scenes with 42.6% m-EDI difference by changing the spectral composition, while maintaining low corneal illuminance (&lt;10 lx) and ensuring chromatic consistency. The alertness performance of twenty-three participants under these two lighting scenes was quantified by Karolinska Sleepiness Scale (KSS) scores, reaction time, and the electroencephalogram (EEG) frequency-band densities. The measured subjective and behavioral metrics show that high m-EDI lighting significantly diminishes subjective sleepiness (p = .006) and reduces reaction time (p = .004). Neurophysiologically, the EEG analyses disclose distinct cortical modulations, with high m-EDI lighting suppressing theta power in the temporal cortex (p = .02) and boosting beta activity in the occipital cortex (p = .02). In conclusion, the proposed lighting approach through spectra tuning demonstrates the feasibility of enhancing alertness in low-light conditions without increasing lighting intensity. The findings indicate that spectral-driven m-EDI optimization enables glare-free alertness enhancement, suggesting a new solution to address the circadian rhythm issues in night-shift and night-driving workplaces.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113589"},"PeriodicalIF":7.6,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quality assessment of peak pressure estimates in high-rise building using large eddy simulation","authors":"Pedro M. Brito ,&nbsp;Almerindo D. Ferreira ,&nbsp;Antonio C.M. Sousa","doi":"10.1016/j.buildenv.2025.113590","DOIUrl":"10.1016/j.buildenv.2025.113590","url":null,"abstract":"<div><div>Analysis of peak surface pressures is essential for specifying wind-resistant cladding of tall buildings. Large eddy simulation (LES) holds promise for predicting peak wind action, yet its reliability is challenged by uncertainties arising from extreme value analysis and grid-controlled scale filtering. This study postulates that quantifying numerical and modelling errors in the LES pressure solutions improves design reliability and guides grid resolution specifications for high-fidelity peak pressure prediction. Thus, the key objectives were to (<em>i</em>) map magnitudes of numerical (truncation) and modelling errors along facades—achieved here through the novel application of the systematic grid and model variation method—and (<em>ii</em>) assess the accuracy of low-uncertainty peak pressure solutions against experimental measurements. Simulations reproduced a benchmark from the Tokyo Polytechnic University, modelling a square-based building with height-to-breadth ratio of 5:1 subjected to orthogonal and oblique wind incidences. Peak pressure coefficients at 500 locations were extracted from a Gumbel distribution of extremes, recorded during 30 min of equivalent full-scale exposure to 100-year return wind speeds. Using an isotropic wall-tangent resolution of 96 cells per building breadth, the LES peak pressure results showed generally low uncertainty, with area-averaged numerical and modelling errors of 7.3 % and 4.1 %, respectively. This configuration demonstrated respectable accuracy: 55 %, 85 %, and 95 % of peak pressure predictions fell within ±10 %, ±20 %, and ±30 % of the experimental references. Ultimately, this work presents a systematic LES framework for reliable peak pressure prediction, well-suited for third-party reproduction.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113590"},"PeriodicalIF":7.6,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty analysis of cross-climate, occupancy behaviour and building scale on energy storage system for residential buildings using urban building energy model","authors":"Ammar Ali ,&nbsp;Usama Perwez ,&nbsp;Shahbaz Abbas ,&nbsp;Yasir Ahmad","doi":"10.1016/j.buildenv.2025.113586","DOIUrl":"10.1016/j.buildenv.2025.113586","url":null,"abstract":"<div><div>Uncertainty in energy demand and supply poses a significant challenge due to the variability of the urban environment and the feasibility constraint of the design process of renewable energy systems (RES). In this context, a hybrid-based uncertainty approach is proposed to quantify the impact of aleatory demand and epistemic supply uncertainties on the techno-economic performance of RES for residential buildings. This approach mainly involved the development of a demand-supply uncertainty framework using an urban building energy model (UBEM), considering the intersection of cross-climate variability, occupancy behaviour and building scales, and RES modelling for residential buildings. As a case study, the proposed approach is implemented on an urban residential building stock of Pakistan to explore a broader spectrum of scenarios, encompassing variations in cross-climatic conditions, occupancy behaviour, building scales and supply economics. The uncertainty analysis reveals the following findings: the building scales showed a significant compound effect with a relative deviation of four times more energy demand from smaller one; the share of battery storage decreases slightly up to 6 % owing to the increase in energy demand; energy storage systems (ESS) with higher efficiency and better lifetime resulted in minimal economic variability along with lower system design cost; and epistemic supply uncertainties resulted in a wider distribution of energy storage cost with variation in cross-climatic conditions. This study underscores the significance of geographical, human and scale-influenced sensitivities in selecting the optimal supply system deployment pathways.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113586"},"PeriodicalIF":7.6,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microclimatic benefits of urban shading trees: Synergies and trade-offs in Canberra, Australia","authors":"Baige Zhang,&nbsp;Matthew Brookhouse","doi":"10.1016/j.buildenv.2025.113584","DOIUrl":"10.1016/j.buildenv.2025.113584","url":null,"abstract":"<div><div>Urban forests, integral to Green Infrastructure (GI) and delivering Nature-based Solutions (NbS), play a pivotal role in mitigating the Urban Heat Island (UHI) effect and enhancing urban thermal comfort. The cooling effectiveness of urban trees is influenced by functional traits that determine their shading capacity and evapotranspiration rates. While trait-service relationships have been proposed to guide species selection for improved microclimate outcomes, their interplay with contextual factors, such as solar irradiance, remains underexplored. This study investigates the cooling potential of four morphologically distinctive urban tree species in Canberra, Australia, characterised by a distinctive inland Mediterranean climate. In contrast to many prior studies that rely on single heat metrics and summer midday snapshots, this study analyses seasonal and daytime variations by modelling interactions between seasons and surface materials, and between functional traits and solar irradiance. Linear mixed-effects models were employed to quantify the contribution and significance of these factors to reductions in Surface Temperature (ST) and Wet Bulb Globe Temperature (WBGT). Crown density emerged consistently as a significant trait that was positively correlated with reductions in both ST and WBGT, whereas other traits showed indicator-specific and context-dependent effects. Notably, traits that improve surface cooling might be counterproductive for thermal cooling, revealing potential trade-offs between UHI mitigation and thermal stress reduction. The findings underscore that trait-service relationships can vary with solar irradiance. This study highlights the need for strategic tree species selection, integrating appropriate functional traits within specific urban contexts, to optimise urban microclimatic benefits.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113584"},"PeriodicalIF":7.6,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequential temperature design in high-speed railway stations: A dynamic thermal strategy balancing thermal comfort and energy efficiency","authors":"Ye Yuan ,&nbsp;Meiling Li ,&nbsp;Junxi Gao ,&nbsp;Gang Liu ,&nbsp;Zongwu Xu ,&nbsp;Ying Chen ,&nbsp;Hanyuan Zhang","doi":"10.1016/j.buildenv.2025.113576","DOIUrl":"10.1016/j.buildenv.2025.113576","url":null,"abstract":"<div><div>High-speed railway stations, as representative sequential spaces, face the dual challenge of maintaining passenger thermal comfort while minimizing energy consumption. Conventional thermal design approaches, typically based on static and zone-isolated controls, oversimplify the dynamic and sequential nature of human spatial experience, leading to thermal misalignment and efficiency loss. This study proposes a dynamic thermal design strategy for the entire departure process in high-speed railway stations, aiming to balance thermal comfort and energy use. A representative station in a cold region of China was selected, and climate chambers were configured to simulate sequential spaces from the outdoor entrance to the check-in area. Thermal satisfaction data were collected under 24 summer and 18 winter temperature sequences, while energy demands for 200 configurations per season were obtained through energy simulations. Predictive models of overall thermal satisfaction (OTSAT) and energy use intensity (EUI) were developed using Random Forest Regression and Backpropagation Artificial Neural Networks. A multi-objective particle swarm optimization algorithm was employed to identify optimal sequential temperature profiles. Three representative solution types were extracted: energy-prioritized, comfort-oriented, and utopian. Compared to the baseline upper bound of OTSAT and the lower bound of EUI defined by standard temperature threshold ranges, the optimized sequential temperature solutions achieved seasonal improvements of up to 67.40 % in OTSAT and 34.75 % reductions in EUI. The findings provide practical guidance for thermal environment design, operational management, and potential revisions of thermal standards in high-speed railway stations.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113576"},"PeriodicalIF":7.6,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green and grey cooling: Mitigating pedestrians perceived temperature via urban shades","authors":"Xinyue Gu ,&nbsp;Jingqi Zhang","doi":"10.1016/j.buildenv.2025.113585","DOIUrl":"10.1016/j.buildenv.2025.113585","url":null,"abstract":"<div><div>Understanding how green (e.g., trees, parks) and grey (e.g., buildings) elements mitigate urban heat is crucial for climate-resilient urban planning. However, previous studies often lack large-scale, fine-grained analysis and causal inference, limiting their ability to inform effective interventions. This study utilizes a double machine learning (DML) model to estimate the causal impact of green and grey infrastructure on human-perceived temperature during summer. Leveraging shade on pedestrian pathways across more than 10,000 neighborhoods in the Netherlands, we quantify how green and grey infrastructure influence the perceived thermal comfort. Our results indicate that (1) Green and grey infrastructure significantly reduce human-perceived temperature; for every 1 % increase in shade percentage, Physiological Equivalent Temperature (PET) decreases by 0.018 °C; (2) Urban areas exhibit a stronger shading-induced cooling effect compared to rural areas, with treatment effects of shade percentage being -0.029 in urban areas and -0.011 in rural areas. This implies that for every 1 % increase in shade percentage, the perceived temperature in urban areas decreases by an additional 0.018 °C compared to rural areas; (3) Environments dominated by trees, the cooling effect of shade is better compared to those dominated by low green spaces; however, the cooling effect of shade are relatively similar between environments dominated by buildings and those dominated by other grey infrastructure such as stones, pavement, bare ground, and sand drifts. This study highlights the importance of integrating both natural and built shading strategies to optimize urban thermal comfort and guide future urban design.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"285 ","pages":"Article 113585"},"PeriodicalIF":7.6,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}