Building and Environment最新文献

{"title":"A new index based on Gini coefficient for evaluating the distribution uniformity of environmental parameters in buildings","authors":"Mengwei Zhao ,&nbsp;Pan Xiao ,&nbsp;Chao Liang ,&nbsp;Chaoyuan Wang ,&nbsp;Baoming Li ,&nbsp;Weichao Zheng","doi":"10.1016/j.buildenv.2025.112910","DOIUrl":"10.1016/j.buildenv.2025.112910","url":null,"abstract":"<div><div>The traditional coefficient of variation (CV) is the most commonly used index to evaluate the distribution uniformity of environmental parameters in buildings. However, there is no benchmark for the CV to judge how uniform the distribution of environmental parameter is. To address it, a new index based on Gini coefficient, i.e., revised Gini coefficient (Gini_rev) through the dimensionless normalization, was proposed to evaluate the distribution uniformity in this study. The indoor air velocity, temperature, and CO₂ concentration distribution in a commercial broiler building with cross and tunnel ventilation modes were obtained to demonstrate the Gini_rev. What is more, the evaluation effects of the traditional CV and proposed Gini_rev were compared, and the ventilation performances of the cross and tunnel ventilation modes were discussed. The results show that: (1) the maximums of the Gini_rev and CV were 0.604 and 2.105, respectively, which indicates that the Gini_rev can be ensured to be between 0 and 1 to provide a clear benchmark; (2) when assessing the uniformity of indoor air velocity, temperature, and CO₂ concentration simultaneously, the fluctuation ranges of the Gini_rev and CV were 0.084∼0.604 and 0.049∼2.105, respectively, which indicates that the Gini_rev can provide a unified comparison criterion; (3) the Gini_rev of the environmental parameters distribution with tunnel ventilation was larger than that with cross ventilation, reaching up to 36 % and 25 % for the air temperature and CO₂ concentration, respectively. The proposed Gini_rev in this study will help evaluate, design and control the indoor environment in buildings.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112910"},"PeriodicalIF":7.1,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828674","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":"Assessment between indoor environmental quality aspects and productivity in buildings: a systematic literature review","authors":"Mateus Pedrosa Braga,&nbsp;Iasmin Lourenço Niza,&nbsp;Evandro Eduardo Broday","doi":"10.1016/j.buildenv.2025.112983","DOIUrl":"10.1016/j.buildenv.2025.112983","url":null,"abstract":"<div><div>Due to changes in people's living and working patterns, studies into indoor environmental quality (IEQ) have become increasingly relevant due to their influence on people's health, comfort and, above all, productivity. By selecting studies using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), this study carried out a literature review to identify the main models that assess people's productivity based on the four tangible aspects of IEQ (indoor air quality, thermal, acoustic and visual comfort). Three research questions were answered after using bibliometric analysis, hierarchical clustering, and meta-analysis. The main conclusions of this study are: (i) Seventy-three productivity models related to aspects of IEQ were identified, involving twenty-four different parameters, the temperature being the most recurrent one in the predictive models; (ii) The dendrogram, generated by the hierarchical clustering, formed six different groups, where parameters related to thermal comfort and indoor air quality remaining together; (iii) After analyzing the main characteristics of each model, verifying their main strengths and weaknesses, it was verified that the representativeness of the sample, climatic and cultural biases, psychosocial factors, subjective perceptions and the scope of the IEQ aspects, the data collection methodology and statistical validation are determining factors for the reliability of the models. (iv) Meta-analysis consolidated studies on the correlation of productivity models, revealing a predominance of positive correlations but with high heterogeneity (I² = 98.39 %). This suggests a publication bias, suggesting an under-representation of non-significant or negative results. The presence of this variation reflects the need to consider contextual factors when discussing IEQ aspects, which can depend on local characteristics, cultural expectations and occupants' habits.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112983"},"PeriodicalIF":7.1,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143825839","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 Novel Methodology for Evaluating Urban Surface Overheating and Its Impact on Pedestrians' Radiative Heat Exposure using Infrared Thermography","authors":"Giulia Lamberti,&nbsp;Davide Della Vista,&nbsp;Francesco Leccese,&nbsp;Giacomo Salvadori","doi":"10.1016/j.buildenv.2025.112981","DOIUrl":"10.1016/j.buildenv.2025.112981","url":null,"abstract":"<div><div>Climate change has raised outdoor surface temperatures, increasing pedestrians' vulnerability to heat stress. In this context, there is a lack of a methodology that captures the effects of directional radiation from urban environments on the human body, considering the relative positioning of pedestrians and surfaces. This paper proposes a methodology to evaluate the effects of surface temperatures on urban microclimate and pedestrian thermal comfort using infrared thermography. A 3D model of the urban environment was generated with projected thermographic images, also including a human body model to calculate view factors between each body segment and the surrounding surfaces. These view factors, combined with the surrounding temperatures, allow the determination of radiative heat flux from urban surfaces to each body part.</div><div>The methodology was applied to three scenarios in Pisa using an AVIO TVS-600 thermal camera (320 × 240 pixels, IFOV 1.4 mrad, resolution 0.15°C): an open field, an urban canyon, and a semi-open area. Temperatures ranged from 15.0°C to 54.6°C, with longwave radiation fluxes to pedestrians varying due to view factors and solar radiation exposure of surfaces, peaking at around 500 W/m², especially those impacting the head section.</div><div>The results are valuable for mapping longwave radiation and assessing pedestrian exposure to improve urban planning. They are also useful to evaluate the impact of longwave radiation on thermal comfort, analysing radiant asymmetries and variations in thermal perception across different body parts. Future studies should apply this methodology to enhance urban planning by addressing pedestrian thermal stress, including measurement campaigns with participants.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112981"},"PeriodicalIF":7.1,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816249","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":"Understanding the effect of outdoor pollution episodes and HVAC type on indoor air quality","authors":"Tristalee Mangin ,&nbsp;Zachary Barrett ,&nbsp;Zachary Palmer ,&nbsp;Dillon Tang ,&nbsp;Sean Nielson ,&nbsp;Darrah Sleeth ,&nbsp;Kerry Kelly","doi":"10.1016/j.buildenv.2025.112978","DOIUrl":"10.1016/j.buildenv.2025.112978","url":null,"abstract":"<div><div>This study evaluated the impact of poor outdoor air quality on indoor air quality over 18 months using 21 low-cost PM_2.5 sensors (at 17 indoor and two outdoor locations) with a focus on inversion, dust, and wildfire smoke events. In addition to the impact of outdoor air quality on indoor air quality, this study evaluated how different heating, ventilation, and air conditioning (HVAC) systems affect the infiltration of outdoor PM_2.5 in commercial buildings. Wildfire smoke events had the largest impact on indoor air quality. Infiltration factors averaged over all locations for inversion, dust, and wildfire smoke events were 0.07, 0.10, and 0.37, respectively. Additionally, HVAC systems equipped with an air-side economizer showed higher PM_2.5 infiltration factors compared to other systems regardless of pollution event.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112978"},"PeriodicalIF":7.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816289","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 IMPACT ON STRESS REDUCTION: A STUDY OF CORRELATED COLOR TEMPERATURE IN WORKPLACE DESIGN UTILIZING NEUROARCHITECTURE PRINCIPLES","authors":"Shahenda Amr Fekry ,&nbsp;Samir Sadek Hosny ,&nbsp;Hanan Sabry ,&nbsp;Fatma Fathy","doi":"10.1016/j.buildenv.2025.112972","DOIUrl":"10.1016/j.buildenv.2025.112972","url":null,"abstract":"<div><div>Several studies have examined lighting in workplace environments, however little research has focused on how different correlated color temperatures (CCT) affect stress reduction. This study aims to identify the most effective lighting condition for stress recovery by comparing the stress-reducing effects of 4000K and 6000K CCTs utilizing Neuroarchitecture principles. By understanding how different elements of a built environment affect the human brain, neuroarchitecture aims to create more effective, harmonious, and human-centered spaces.</div><div>An experiment was conducted with 36 participants (aged 19 to 26, mean age 22.5), who completed a stressful memory task before being exposed to a virtual workplace environment under both lighting conditions. The recovery process was repeated for each CCT, and heart rate responses—measured via pulse oximeter while participants wore a virtual reality (VR) headset—were used as an objective stress indicator. A post-experiment survey evaluated subjective preferences.</div><div>Results indicated that both lighting conditions reduced stress, but the 6000K environment offered a slight advantage in promoting relaxation. Additionally, 80.5% of participants reported feeling less stressed under the 6000K condition, although 50% showed a discrepancy between their subjective preferences and heart rate data. This study provides valuable insights for workplace design, emphasizing the role of lighting in supporting employees’ well-being.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112972"},"PeriodicalIF":7.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807707","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":"Inhalation exposure to indoor air pollutants during moderate- and high-intensity physical exercise in commercial fitness microenvironments","authors":"Cátia Peixoto ,&nbsp;Maria do Carmo Pereira ,&nbsp;Simone Morais ,&nbsp;Klara Slezakova","doi":"10.1016/j.buildenv.2025.112967","DOIUrl":"10.1016/j.buildenv.2025.112967","url":null,"abstract":"<div><div>Physical exercise benefits are known, but exposure data across different exercise environments, and activities remain limited. This study estimated indoor air concentrations and inhalation doses of gaseous (total volatile organic compounds – TVOCs, CO₂) and particulate (PM₁₀, PM_2.5, and ultrafine – 20–1000 nm) pollutants during highly–intense (spinning, dance fitness, and total body workout - TBW) and moderately–intense (body &amp; mind, muscle group-specific and self-defence techniques) in 138 exercise group classes. The USEPA methodology was used to assess inhalation doses across different ages (3 – &lt;61 years old) and genders. CO₂ (mean±SD) ranged from 1368±19 mg/m³ (in TBW) – 2727±32 mg/m³ (self-defence-adults), with the protection threshold (2250 mg/m³) being exceeded in adult self-defence classes. TVOCs exceeded 4–18 times protective limits (0.6 mg/m³) in all classes (mean±SD: 2.49±0.06 mg/m³ in body &amp; mind – 10.62±0.53 mg/m³ in self-defence adults). Across different activities, PM widely varied (mean±SD: PM₁₀=20.8 ± 0.3 – 220.8 ± 9.7 µg/m³; PM_2.5 = 9.1 ± 0.3 – 63.5 ± 1.3 µg/m³; UFP=6267±72 – 9917±224 #/cm³) with especially PM₁₀ higher during vigorous human movements; 1.1–4.4 and 1.1–2.5 times exceeding the protective threshold (PM₁₀: 50 µg/m³; PM_2.5: 25 µg/m³) for PM₁₀ and PM_2.5, respectively. High-intensity classes led to 1.1 (16 to &lt;21 yrs) – 1.5 (31 to &lt;41 yrs) times higher total inhalation doses (i.e., Σ<em>D</em>=D_PM10+D_CO2 +D_TVOCs) than moderate-intensity classes, and ΣD for men was higher (1–8 % in high- and moderate-intensity, respectively) than for women. Finally, ΣD of child population in self-defence classes were up to 1.99 times higher than those of adults (in self-defence class) of both genders.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112967"},"PeriodicalIF":7.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839554","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":"Fine-grained local climate zone classification using graph networks: A building-centric approach","authors":"Siyu Li ,&nbsp;Pengyuan Liu ,&nbsp;Rudi Stouffs","doi":"10.1016/j.buildenv.2025.112928","DOIUrl":"10.1016/j.buildenv.2025.112928","url":null,"abstract":"<div><div>Local Climate Zone (LCZ) classification provides a refined framework for urban climate studies, particularly in assessing the urban heat island effect. Traditional LCZ mapping approaches primarily rely on remote sensing data and machine learning methods. Recent advancements have explored multi-source data with deep learning models, such as convolutional neural networks, to enhance LCZ classification accuracy. However, these methods are often limited by inappropriate resolutions of spatial units and overlook the impact of spatial proximity on classification results. To overcome these challenges, this study proposes a building-centric LCZ classification approach that leverages street view imagery, points of interest, and transport stops/stations with graph neural networks, specifically using the GraphSAGE model, to classify built-type LCZ classes. This innovative approach captures local-level urban environmental features while accounting for the influence of spatial relationships between buildings, significantly improving built-type LCZ classification accuracy and refining the spatial scale to the building level. Applied to three cities – Singapore, Berlin, and the urban core area of Sydney – our approach achieves an overall accuracy of 96%, 94%, and 82%, respectively. The models exhibit better performance than traditional remote sensing-based LCZ classification. Importantly, the inclusion of spatial distance shows a significant influence on building-centric LCZ classification accuracy. The building-centric graph network approach offers a more precise tool for LCZ mapping at the building level, prompting urban climate assessment and aiding in the design of climate-resilient cities in the face of rapid urbanization and climate change.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112928"},"PeriodicalIF":7.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807708","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":"Research on the generation method of outdoor design parameters for summer air-conditioning based on machine learning and dynamic time warping","authors":"Honglian Li,&nbsp;Suwan Jiang,&nbsp;Mengli Wang,&nbsp;Jiaxiang Lei","doi":"10.1016/j.buildenv.2025.112968","DOIUrl":"10.1016/j.buildenv.2025.112968","url":null,"abstract":"<div><div>In order to combat global climate change and promote sustainable development, nations globally are advancing towards carbon neutrality. Building energy-saving is vital for carbon neutrality, crucially involving the alignment of air conditioning design parameters with local climates. Currently, standards around the world generally use a statistical non-guaranteed rate method for selecting air conditioning design parameters, neglecting the correlation between dry-bulb temperature (DBT) and wet-bulb temperature (WBT). This results in imprecise parameters, impacting system design and energy efficiency optimization. This study uses Support Vector Machine Regression (SVR) and Kernel Density Estimation (KDE) to model the complex relationship between outdoor meteorological parameters, improving air conditioning outdoor design parameters by integrating the nuanced relationship between DBT and WBT through the air state non-guaranteed rate. In addition, the same hourly variation coefficients are used across different regions in China, ignoring regional differences. The paper adopts the Dynamic Time Warping (DTW) algorithm to enhance design parameter accuracy by reflecting temporal climatic variations, thus optimizing air conditioning energy efficiency. The results show that this method provides more accurate outdoor design parameters than those derived from Chinese standards and the ASHRAE Handbook, thereby better representing the hourly changes in regional climates. The use of EnergyPlus simulations on a representative office building model clearly demonstrates that the cooling load on the design day is significantly reduced compared to the Chinese standard method, thereby confirming both the practical feasibility and the improved accuracy of the research method.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112968"},"PeriodicalIF":7.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800680","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":"Evaluating the adaptation potential and retrofitting effectiveness of existing residential buildings in severe cold regions of China under climate change","authors":"Dayang Wang ,&nbsp;Qi Dong ,&nbsp;Cheng Sun","doi":"10.1016/j.buildenv.2025.112982","DOIUrl":"10.1016/j.buildenv.2025.112982","url":null,"abstract":"<div><div>Global climate change is intensifying extreme climate risks in the built environment, particularly in severe cold regions where summer overheating is emerging as a critical issue. Existing Retrofitting Strategies predominantly target winter heating efficiency, often overlooking summer cooling needs, resulting in potential indoor heat accumulation and increased cooling energy demand. This study utilizes the IPCC's Shared Socioeconomic Pathwaysto generate future climate projections for Harbin, China. Building Performance Simulation combined with Machine Learning is employed to evaluate energy consumption patterns in existing residential buildings under various future climate scenarios. Results reveal that while winter warming contributes to a reduction in Heating Energy Use Intensity, the frequency and severity of summer heat events significantly elevate Cooling Energy Use Intensity. Highly insulated buildings, if not supported by effective Shading Structure Length and Opening Glass Window Ratio strategies, may suffer from severe thermal discomfort during summer. SHapley Additive exPlanations analysis identifies Insulation Materials (IM) as the primary contributor to winter energy savings, but also a factor in summer heat retention. Meanwhile, SSL, Glass Type, and OGWR are found to significantly impact summer cooling efficiency and Nighttime Ventilation performance.</div><div>To improve adaptive capacity, this study proposes a holistic retrofitting framework incorporating high-performance envelope materials, external shading devices, and NV. The results underscore the need to transition from winter-centric retrofitting approaches to strategies that optimize year-round energy performance and Thermal Comfort. This research provides actionable insights for architects, engineers, and policymakers in the pursuit of low-carbon, energy-efficient, and climate-resilient residential buildings.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"278 ","pages":"Article 112982"},"PeriodicalIF":7.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807679","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":"Erratum to “Accuracy, generalizability, and extrapolation ability of physics-based, data-driven, and hybrid models for real-life cooling towers”","authors":"Jin Hong Kim ,&nbsp;Young Sub Kim ,&nbsp;Hyeong Gon Jo ,&nbsp;Eiji Urabe ,&nbsp;Junghyon Mun ,&nbsp;Yukyung Shin ,&nbsp;Yongsung Park ,&nbsp;Cheol Soo Park","doi":"10.1016/j.buildenv.2025.112937","DOIUrl":"10.1016/j.buildenv.2025.112937","url":null,"abstract":"","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"277 ","pages":""},"PeriodicalIF":7.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}