Building and Environment最新文献_第2页

Occupant activities and clothes detection based on semi-supervised learning for occupant-centric thermal control 基于半监督学习的居住者活动和衣物检测，实现以居住者为中心的热控制

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-10 DOI: 10.1016/j.buildenv.2024.112178

Real-time monitoring of metabolic rate (MET) and clothing insulation (CLO) is essential to ensure effective occupant-centric control (OCC) for thermal comfort. This study aims to develop multi-task model using semi-supervised learning to enhance occupant activities and clothes detection performance by utilizing both labeled and unlabeled data. The convolutional neural network-based model and training approach with pseudo labels to update all parameters comprehensively were proposed. The developed model is validated by conducting comparative analysis with state-of-the-art models and applying it in a real-world environment. The results demonstrate that the developed model, employing semi-supervised learning and the dual-phase training method (DPTM), achieves superior performance in activity and clothes detection outperforming previous studies with a 15.8 % higher mean Average Precision (mAP) for activity detection and a 25 % improvement for clothes detection. The findings highlight the potential of this multi-task model using semi-supervised learning to automate data collection improving the accuracy of estimating occupant thermal comfort. This approach can dynamically optimize indoor environments tailored to individual needs within the OCC framework, enhancing thermal comfort and energy efficiency through precise monitoring of occupant information.

实时监测新陈代谢率（MET）和衣物隔热性能（CLO）对于确保有效的以居住者为中心的热舒适控制（OCC）至关重要。本研究旨在利用半监督学习技术开发多任务模型，通过同时使用标记和未标记数据来提高乘员活动和衣物检测性能。研究提出了基于卷积神经网络的模型和使用伪标签全面更新所有参数的训练方法。通过与最先进的模型进行对比分析，并将其应用于实际环境中，对所开发的模型进行了验证。结果表明，所开发的模型采用了半监督学习和双阶段训练方法（DPTM），在活动和衣服检测方面取得了优于以往研究的性能，活动检测的平均精度（mAP）提高了 15.8%，衣服检测的平均精度提高了 25%。研究结果凸显了这种采用半监督学习的多任务模型在自动收集数据方面的潜力，从而提高了估算居住者热舒适度的准确性。这种方法可以在 OCC 框架内根据个人需求动态优化室内环境，通过精确监测居住者信息提高热舒适度和能源效率。

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引用次数: 0

Chemical speciation and oxidative potential of PM10 in different residential microenvironments: bedroom, living room and kitchen 不同住宅微环境（卧室、起居室和厨房）中 PM10 的化学成分和氧化潜能

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-10 DOI: 10.1016/j.buildenv.2024.112181

Exposure to particulate matter (PM) and its chemical constituents in residential microenvironments has become a major health concern worldwide. The oxidative potential (OP) has been proposed as a metric for estimating the PM capacity to induce oxidative stress and, consequently, health effects. In the present study, PM₁₀ was daily monitored simultaneously in the bedroom, living room and kitchen of three dwellings for one week in a small town of Portugal, to perform a detailed characterisation of its organic and inorganic constituents and the determination of the OP. Bedrooms (B) were found to be a hotspot of PM₁₀ concentrations (B1 = 22.7 μg m^-3; B2 = 19.5 μg m^-3; B3 = 68.1 μg m^-3). PM₁₀-bound elements varied significantly between microenvironments in all dwellings. Lower molecular weight polycyclic aromatic hydrocarbons (PAHs) were found to be between 14 and 72 times higher than high molecular weight PAHs in bedrooms. The mean volume-normalised OP determined by the dithiothreitol and ascorbic acid assays varied within the 0.01-0.38 nmol min⁻¹ m^-3 and 0.03-0.53 nmol min⁻¹ m^-3 ranges, respectively. Quinones, oxy-aromatic, aromatic and alkyl-aromatic compounds stood out in bedrooms. Strong and significantly positive relationship between OP and black carbon, Cu and Br were observed, indicating common redox active species mainly associated with traffic emissions. Sr, Fe, Zn and Zr presented higher concentrations in dwelling 3, exhibiting excellent positive correlation with OP, indicating that the Sahara dust intrusion recorded in that house may have contributed to the formation of more redox active species thought to drive antioxidant depletion responses.

暴露于住宅微环境中的颗粒物（PM）及其化学成分已成为全球关注的主要健康问题。有人提出用氧化潜能值（OP）来估算可吸入颗粒物诱发氧化应激的能力，进而估算其对健康的影响。在本研究中，对葡萄牙一个小镇上三栋住宅的卧室、起居室和厨房的 PM10 进行了为期一周的每日同步监测，以详细分析其有机和无机成分的特性，并测定其氧化潜能值。发现卧室（B）是 PM10 浓度的热点（B1 = 22.7 μg m-3；B2 = 19.5 μg m-3；B3 = 68.1 μg m-3）。在所有住宅中，不同微环境中的 PM10 结合元素差异很大。在卧室中，低分子量的多环芳烃（PAHs）比高分子量的多环芳烃（PAHs）高出 14 到 72 倍。通过二硫苏糖醇和抗坏血酸测定法确定的平均体积归一化 OP 分别在 0.01-0.38 nmol min-1 m-3 和 0.03-0.53 nmol min-1 m-3 范围内变化。醌类化合物、氧芳香族化合物、芳香族化合物和烷基芳香族化合物在卧室中表现突出。观察到 OP 与黑碳、铜和溴之间存在明显的强正向关系，这表明常见的氧化还原活性物种主要与交通排放有关。锰、铁、锌和锆在 3 号住宅中的浓度较高，与 OP 呈极好的正相关关系，表明该住宅中记录的撒哈拉沙尘入侵可能导致了更多氧化还原活性物种的形成，这些物种被认为会推动抗氧化剂耗竭反应。

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引用次数: 0

Effects of perceived office environment on the subjective well-being of workers: Insights from a structural equation modeling analysis 办公环境对员工主观幸福感的影响：结构方程模型分析的启示

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-10 DOI: 10.1016/j.buildenv.2024.112180

Well-being is a positive mental state that includes evaluations and affective reactions individuals make about their experiences, including life evaluation, affect, and eudaimonia. The importance of well-being is underscored by its association with productivity, health, and longevity. Despite extensive research on well-being related to demographics, personality traits, and satisfaction in various life domains, it remains unclear how and to what extent the office environment impacts workers' well-being. Therefore, this study explores the impact of the office environment on workers' subjective well-being, using structural equation modeling. Conducted with 1438 white-collar workers working in 61 offices in Tokyo, Japan, the survey assessed perceived office environment and measured subjective well-being based on guidelines from the OECD. The key findings indicate a significant association of the office environment with life domain factors such as satisfaction with one's job, work–life balance, private life, and subjective health, which are positively correlated with overall subjective well-being. In particular, common-area environments within the office such as spaces that promote refreshment and conversation have the most significant impact on well-being. The analysis model also revealed that the perceived quality of the office environment had a positive correlation with subjective well-being even after adjusting for demographic information such as age, gender, and personality traits. This research provides valuable insights for improving the design of office environments to foster workers' well-being.

幸福感是一种积极的心理状态，包括个人对其经历的评价和情感反应，包括生活评价、情感和幸福感。幸福感与生产力、健康和长寿的关系凸显了幸福感的重要性。尽管对幸福感与人口统计学、人格特质和各种生活领域的满意度相关的研究非常广泛，但办公环境如何以及在多大程度上影响员工的幸福感仍不清楚。因此，本研究采用结构方程模型探讨了办公环境对员工主观幸福感的影响。调查对象是在日本东京 61 个办公室工作的 1438 名白领，根据经济合作与发展组织（OECD）的指导方针，对感知到的办公环境进行了评估，并对主观幸福感进行了测量。主要研究结果表明，办公环境与生活领域因素（如对工作的满意度、工作与生活的平衡、私人生活和主观健康）有显著关联，而这些因素与总体主观幸福感呈正相关。尤其是办公室内的公共区域环境，如促进茶点和交谈的空间，对幸福感的影响最为显著。分析模型还显示，即使在调整了年龄、性别和个性特征等人口统计学信息后，办公环境的感知质量与主观幸福感仍呈正相关。这项研究为改进办公环境设计以促进员工的幸福感提供了宝贵的见解。

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引用次数: 0

A novel measurement for evaluating the capture efficiency of local ventilation system using background oriented schlieren 利用面向背景的 Schlieren 评估局部通风系统捕获效率的新型测量方法

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-10 DOI: 10.1016/j.buildenv.2024.112185

In-situ measurement of the capture efficiency of local ventilation systems (CELV) is a challenge in field of indoor air quality control. This study introduced a novel method for assessing the capture efficiency using background oriented schlieren (BOS). A 1:4 model experimental platform was constructed to investigate the feasibility. The CELV was compared using both the BOS and the tracer gas method, and the optimization of BOS device parameters for better CELV results was investigated. The results showed that the CCD camera-BOS could detect thermal airflows with a temperature difference over 40 K. The best post-processing algorithm for CELV by BOS, which was combined density gradient variation-rate and gray-scale method (CE-DGR&GS), was closely matched the results of the tracer gas method (CE-SF₆), with a correlation of 0.97. When the capture efficiency exceeded 90%, the deviation between the two methods was less than 10%. However, when the ventilation system captured poorly, the CELV by CE-DGR&GS was over-estimated. Higher NR of BOS image causes large deviation of the calculated capture efficiency, and CELV by BOS under the same flow can differ by as much as 40 % by various cameras. A high-pixel CCD camera with a long focal length lens (f ≥ 35 mm, ISO≤100, f_# = 16) was recommended. The interrogation window size for cross-correlation algorithms could be 33%–66% of the collected image pixel resolution. To achieve sufficient optical sensitivity, the distance ratio Z_d/Z_b was suggested to be 1:2. This study provides a cost-effective and entrie flow-field measurement for assessing local ventilation capture efficiency.

现场测量局部通风系统（CELV）的捕获效率是室内空气质量控制领域的一项挑战。本研究介绍了一种利用背景定向裂片（BOS）评估捕获效率的新方法。为研究其可行性，构建了一个 1:4 模型试验平台。使用 BOS 和示踪气体法对 CELV 进行了比较，并研究了如何优化 BOS 设备参数以获得更好的 CELV 结果。结果表明，CCD 摄像机-BOS 可以检测到温差超过 40 K 的热气流。BOS 对 CELV 的最佳后处理算法是密度梯度变化率和灰度组合法（CE-DGR&GS），与示踪气体法（CE-SF6）的结果非常接近，相关性达到 0.97。当捕获效率超过 90% 时，两种方法之间的偏差小于 10%。然而，当通风系统捕获效率较低时，CE-DGR&GS 方法的 CELV 被高估。BOS 图像的 NR 越高，计算出的捕获效率偏差就越大，在相同流量下，不同相机的 BOS CELV 可相差高达 40%。建议使用长焦距镜头的高像素 CCD 相机（f ≥ 35 mm，ISO≤100，f# = 16）。交叉相关算法的询问窗口大小可为采集图像像素分辨率的 33%-66%。为达到足够的光学灵敏度，建议距离比 Zd/Zb 为 1:2。这项研究为评估局部通气捕获效率提供了一种经济有效的室内流场测量方法。

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引用次数: 0

Microscale thermal variations in a walkable urban area during hot days: Analysis through mobile measurements and Day PET Signatures 炎热天步行城区的微尺度热变化：通过移动测量和日 PET 签名进行分析

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-10 DOI: 10.1016/j.buildenv.2024.112176

This article analyzes the thermal variations of a small urban area recently transformed in the city center of Nantes, France, which has been designed to promote walkability and make it comfortable in summer. A measurement method based on mobile climate metrology, which offers high spatial resolution, was developed. Four measurements were conducted per day over five days between June and September 2023. The data was analyzed using the concept of the Day PET Signature (DPS), which reflects the dynamics of a point in space over the course of the day through variations in the Physiological Equivalent Temperature (PET) index. Four clusters of DPS were identified in the dataset, enabling the accurate assessment of the thermal diversity existing in the study area at different times of the day in summer. The results demonstrate that the observed differences between clusters are solely attributable to the radiative conditions at the distinct positions analyzed. The concept of a Radiative Portrait is introduced in order to characterize the thermal diversity of the study area. In contrast to the TMRT synthetic index, the Radiative Portrait provides a detailed breakdown of the fluxes, revealing the intensity of short- and long-wave radiation in top, bottom and lateral orientations. The combination of the Radiative Portrait and the PET class qualification provides a comprehensive understanding of the local climatescapes in summer.

本文分析了法国南特市中心最近改造的一个小型城市区域的热变化，该区域的设计旨在提高步行能力，使其在夏季更加舒适。我们开发了一种基于移动气候计量的测量方法，该方法具有很高的空间分辨率。在 2023 年 6 月至 9 月的五天时间里，每天进行四次测量。该方法通过生理等效温度（PET）指数的变化反映了空间中某一点在一天中的动态变化。数据集中确定了四个 DPS 群组，从而能够准确评估研究区域夏季一天中不同时段的热多样性。结果表明，观测到的群组间差异完全归因于所分析的不同位置的辐射条件。为了描述研究区域的热多样性，引入了辐射肖像的概念。与 TMRT 合成指数不同的是，辐射肖像对通量进行了详细分解，揭示了顶部、底部和横向的短波和长波辐射强度。辐射肖像 "与 "PET 等级鉴定 "相结合，可全面了解当地夏季的气候景观。

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引用次数: 0

Application of logistic function in a new PMV modification model for elderly people: Combining age and TSV 在新的老年人 PMV 修正模型中应用 logistic 函数：结合年龄和 TSV

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-10 DOI: 10.1016/j.buildenv.2024.112182

The accurate prediction of thermal perception paves the way to create a thermal comfort environment. This study proposes a modified predicted mean vote (PMV) model for elderly people. Data from three age groups in two pensioners’ buildings are collected and divided: 80 % for calculating key parameters (B and BT) via logistic function, establishing the mPMV model, and 20 % for validation data. The model is further validated by a subset of the ASHRAE Global Thermal Comfort Database II. The mPMV model demonstrated improved prediction quality over the original PMV model, reducing mean mean absolute error (MAE), standard deviation (SD), and coefficient of variation of root mean square error (CVRMSE) by 0.67, 0.36, and 1.26, respectively, in the experimental data. However, due to various scene classifications in the ASHRAE data, the prediction quality of the mPMV model remains basically unchanged compared with the PMV model, with minor increases in MAE and CVRMSE and a decrease in SD. With the elimination of the climate differences, the mean MAE, SD and CVRMSE of the mPMV model reduces by 0.19, 0.16 and 0.29 compared with the PMV model. In addition, the mPMV model outperforms the other three modified models across all three age groups of the experimental data, but this advantage is only observed in the younger elderly group of the ASHRAE data. This study can offer methodological assistance in predicting the thermal sensation for elderly people and contribute to creating a thermal environment accordant to their thermal preferences.

准确预测热感知为创造热舒适环境铺平了道路。本研究提出了一种针对老年人的改进型预测平均投票（PMV）模型。研究收集了两栋养老院中三个年龄组的数据，并对其进行了划分：其中 80% 用于通过逻辑函数计算关键参数（B 和 BT），建立 mPMV 模型，20% 用于验证数据。ASHRAE 全球热舒适数据库 II 的一个子集进一步验证了该模型。与原始 PMV 模型相比，mPMV 模型提高了预测质量，在实验数据中将平均绝对误差（MAE）、标准偏差（SD）和均方根误差变异系数（CVRMSE）分别降低了 0.67、0.36 和 1.26。然而，由于 ASHRAE 数据中的各种场景分类，与 PMV 模型相比，mPMV 模型的预测质量基本保持不变，MAE 和 CVRMSE 略有增加，SD 有所下降。在消除气候差异后，mPMV 模型的平均 MAE、SD 和 CVRMSE 与 PMV 模型相比分别减少了 0.19、0.16 和 0.29。此外，在所有三个年龄组的实验数据中，mPMV 模型都优于其他三个修正模型，但这一优势只体现在 ASHRAE 数据中的年轻老年人组。这项研究为预测老年人的热感觉提供了方法上的帮助，有助于创造符合老年人热偏好的热环境。

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引用次数: 0

A data-driven approach to discover hidden complicated relationships of energy variables and estimate energy consumption in U.S. homes 采用数据驱动方法发现能源变量之间隐藏的复杂关系，并估算美国家庭的能源消耗量

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-10 DOI: 10.1016/j.buildenv.2024.112175

The U.S. government has committed to improving building energy efficiency. In many buildings, residential homes are one of the largest end-users of energy consumption. Today, many U.S. homes have been in use for decades and they are now outdated, poorly insulated and equipped. Retrofitting existing homes is therefore urgent to improve the quality of Americans’ life and reduce environmental impact from energy waste. To support successful retrofits, this study proposes a decision tree-based analytical model to identify the complex relationships between residential energy variables of physical and socio-economic characteristics using the Residential Energy Consumption Survey (RECS). For this, a model-based recursive partitioning (MOB) algorithm was applied in the decision tree models for understanding energy consumption in residential buildings. The results discovered the most influential energy variables for retrofits and identified heterogeneous relationships on energy consumption for different climatic regions. Also, the findings from decision tree models offer estimations for residential energy consumption in different U.S. climate zones, depending on the combinations of design and operating energy variables. The proposed equations for the EUI estimations can be used to predict the impact of energy variables on primary residential load components (i.e., cooling, heating, domestic hot water loads) to support effective retrofits for architects and homeowners in the future.

美国政府一直致力于提高建筑能效。在许多建筑中，住宅是能源消耗最大的终端用户之一。如今，许多美国住宅已经使用了几十年，它们已经过时，隔热性能差，设备简陋。因此，为了提高美国人的生活质量，减少能源浪费对环境的影响，对现有住宅进行改造迫在眉睫。为了支持成功的改造，本研究提出了一个基于决策树的分析模型，利用住宅能源消耗调查（RECS）来识别物理和社会经济特征的住宅能源变量之间的复杂关系。为此，在决策树模型中应用了基于模型的递归分割（MOB）算法，以了解住宅建筑的能源消耗情况。研究结果发现了对节能改造最有影响的能源变量，并确定了不同气候区域能源消耗的异质性关系。此外，决策树模型的研究结果还根据设计和运行能源变量的组合，对美国不同气候区的住宅能耗进行了估算。所提出的 EUI 估算方程可用于预测能源变量对主要住宅负荷成分（即制冷、供暖、生活热水负荷）的影响，从而为建筑师和业主未来的有效改造提供支持。

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引用次数: 0

Building usage prediction in complex urban scenes by fusing text and facade features from street view images using deep learning 利用深度学习融合街景图像中的文字和立面特征，预测复杂城市场景中的建筑物使用情况

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-09 DOI: 10.1016/j.buildenv.2024.112174

Building usage maps are inputs to many urban planning applications, however, the existing methods and the available data have limitations in generating instance-level high-resolution usage maps. In this study we tackle this problem by utilizing Street View Images (SVIs) and proposing a novel ensemble learning architecture that leverages building facade features and text extracted from hoardings, posters, etc. on buildings to predict the usage class. A pre-trained object detection model i.e., Grounding DINO, is implemented to efficiently identify buildings. A novel manually labeled training data of detected buildings corresponding to their usage is used to extract features from building facades across diverse Indian cities (Hyderabad, Mumbai, Bangalore, Delhi) using Vision Transformer (ViT) model. Following this, CLIPSeg a pre-trained segmentation model is used to recognizes text specifically on building elements like signs, posters, and banners. We then leverage GPT-3.5 Turbo, a Large Language Model (LLM), fine-tuned with a specifically designed few-shot prompting method, to infer building usage from the recognized text. To achieve optimal performance, the proposed ensemble linear metaclassifier combines predictions from ViT and LLM model. The predicted building usages are attributed to their corresponding locations to develop spatial maps. An analysis of our framework compared against ground truth data collected from various Indian cities reveals significantly accurate outcomes. Our findings highlight the utility of textual information in classifying utilities and commercial buildings, while features extracted from vision models prove more informative for residential buildings. Our approach can automate the generation of roadside building attributes and usage details on a larger scale.

建筑物使用地图是许多城市规划应用的输入，然而，现有方法和可用数据在生成实例级高分辨率使用地图方面存在局限性。在这项研究中，我们利用街景图像（SVI）解决了这一问题，并提出了一种新颖的集合学习架构，利用建筑物外立面特征和从围板、海报等提取的文字来预测建筑物的使用类别。为了有效识别建筑物，我们采用了一个预先训练好的物体检测模型，即接地 DINO。使用 Vision Transformer (ViT) 模型从印度不同城市（海得拉巴、孟买、班加罗尔和德里）的建筑物外立面提取与建筑物用途相对应的新颖人工标注训练数据。然后，使用预先训练好的分割模型 CLIPSeg 来识别标识、海报和横幅等建筑元素上的特定文本。然后，我们利用 GPT-3.5 Turbo 大语言模型 (LLM)，通过专门设计的少量提示方法进行微调，从识别的文本中推断出建筑物的用途。为了达到最佳性能，建议的集合线性元分类器结合了 ViT 和 LLM 模型的预测结果。预测出的建筑物使用情况将归因于其相应的位置，从而绘制出空间地图。将我们的框架与从印度多个城市收集的地面实况数据进行对比分析，结果显示准确度非常高。我们的研究结果凸显了文本信息在公用事业和商业建筑分类中的实用性，而从视觉模型中提取的特征则被证明对住宅建筑更有参考价值。我们的方法可以在更大范围内自动生成路边建筑物的属性和使用细节。

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引用次数: 0

Effects of traffic noise on the psychophysiological responses of college students: An EEG study 交通噪音对大学生心理生理反应的影响：脑电图研究

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-09 DOI: 10.1016/j.buildenv.2024.112171

Traffic noise harms public health, but the specific mechanisms are not fully understood. To understand how traffic noise at different sound pressure levels (SPLs) affects psychophysiological responses, this study examined five SPLs of traffic noise: 40, 45, 50, 55, and 60 dB. 38 young college students were recruited for Profile of Mood States (POMS) evaluations and measurements of electrocardiogram and electroencephalogram. The study found that traffic noise exposure led to a 0.95–1.64-fold increase in mood disturbance compared to no sound, with 60 dB traffic noise causing a significantly greater increase compared to other SPLs. As SPL increased, ΔLF/HF increased by 0.01–0.83, indicating heightened stress levels. Traffic noise also induced stress responses in the brain, with α power reduced by 13.08–24.15 % compared to no sound. High SPL traffic noise significantly harmed brain comfort. Compared to 40–45 dB, exposure to 50–60 dB traffic noise significantly increased α power by 28.66–85.80 % (p < 0.05). Additionally, 60 dB traffic noise increased the likelihood of supercritical brain activity by 32.49 % compared to no sound. Psychological response changes were closely related to physiological response changes. Δα power, particularly in the frontal and parietal lobes, was the strongest predictor of the increase in total mood disturbance, suggesting these lobes should be the focus of future traffic noise-brain studies. The study emphasizes the need for a comprehensive evaluation of the negative effects of traffic noise from a psychophysiological perspective, highlighting the harm of high SPLs. The findings provide valuable insights for developing indoor acoustic environment standards.

交通噪声危害公众健康，但其具体机制尚不完全清楚。为了了解不同声压级（SPL）的交通噪声如何影响心理生理反应，本研究考察了五种声压级的交通噪声：40、45、50、55 和 60 dB。研究人员招募了 38 名年轻大学生，对他们进行了情绪状态档案 (POMS) 评估，并测量了心电图和脑电图。研究发现，与无声相比，暴露于交通噪声会导致情绪紊乱增加 0.95-1.64 倍，与其他声压级相比，60 分贝交通噪声导致的情绪紊乱增加幅度更大。随着声压级的增加，ΔLF/HF 增加了 0.01-0.83，表明压力水平升高。交通噪音也会引起大脑的应激反应，与无声相比，α 功率降低了 13.08-24.15%。高声压级交通噪音会严重损害大脑的舒适度。与 40-45 分贝相比，暴露于 50-60 分贝的交通噪声会使 α 功率显著增加 28.66-85.80 %（p < 0.05）。此外，与无声相比，60 分贝的交通噪声使大脑超临界活动的可能性增加了 32.49%。心理反应变化与生理反应变化密切相关。Δα功率，尤其是额叶和顶叶的Δα功率，是预测总情绪障碍增加的最强指标，这表明这些脑叶应该是未来交通噪声-大脑研究的重点。这项研究强调了从心理生理学角度全面评估交通噪声负面影响的必要性，并突出强调了高声压级的危害。研究结果为制定室内声学环境标准提供了宝贵的见解。

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引用次数: 0

Integrating aromatic plants into indoor biophilic environments: Species selection based on psychophysiological effects and bioactive volatile compounds 将芳香植物融入室内亲生物环境：基于心理生理效应和生物活性挥发性化合物的物种选择

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-10-09 DOI: 10.1016/j.buildenv.2024.112169

To explore aromatic plants suitable for indoor biophilic environments and their impact on long-term indoor residents' psychophysiological health, a combined method using subjective ratings, objective electrophysiological signals, and aroma characteristics was employed. The study assessed 12 indoor plants' aromas and analyzed aroma components and their potential to intervene in psychophysiological health. Results showed that different plants had varying effects on psychophysiological health, some (e.g., Vicks Plant, rosemary) showed positive impacts across most measures, while others (e.g., basil, catnip) showed negative impacts. The aroma of false incense showed significant gender differences in its effects. Smelling Vicks Plants for 5 min significantly reduced heart rate (HR), increased heart rate variability (HRV), and enhanced vigor, positively correlated with volatile organic compounds (VOCs) and terpenes like linalool and limonene. Higher VOCs emission was associated with lower HR and reduced anger. Cluster analysis grouped Vicks Plant and rosemary based on aroma composition and effects on psychophysiological responses, providing a basis and framework for subsequent exploration of aromatic plants with psychophysiological regulation capabilities in indoor biophilic environments.

为了探索适合室内亲生物环境的芳香植物及其对长期居住在室内的人的心理生理健康的影响，研究采用了主观评分、客观电生理信号和芳香特征相结合的方法。研究评估了 12 种室内植物的香气，分析了香气成分及其干预心理生理健康的潜力。结果显示，不同植物对心理生理健康的影响各不相同，有些植物（如维克斯植物、迷迭香）在大多数测量指标上都表现出积极影响，而其他植物（如罗勒、猫薄荷）则表现出消极影响。假香的香气在效果上显示出明显的性别差异。嗅闻 Vicks Plants 5 分钟可显著降低心率（HR）、增加心率变异性（HRV）并增强活力，这与挥发性有机化合物（VOCs）以及芳樟醇和柠檬烯等萜烯类化合物呈正相关。挥发性有机化合物排放量越高，心率变异性越低，愤怒情绪越低。聚类分析根据芳香成分和对心理生理反应的影响对 Vicks 植物和迷迭香进行了分组，为后续探索室内亲生物环境中具有心理生理调节能力的芳香植物提供了基础和框架。

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引用次数: 0