Indoor Environments最新文献_第8页

Estimating air exchange rates in thousands of elementary school classrooms using commercial CO2 sensors and machine learning 利用商用二氧化碳传感器和机器学习技术估算数千个小学教室的空气交换率

Indoor Environments

Pub Date : 2025-03-06 DOI: 10.1016/j.indenv.2025.100083

Yirong Yuan , Masanao Yajima , Jinho Lee , Katherine H. Walsh , Brenden Tong , Lauren Main , Lauren Bolton , M. Patricia Fabian

In the post-COVID-19 pandemic era, maintaining clean air in school classrooms has become critical for ensuring student health and safety. Air exchange rate (AER), which measures the number of air replacements in a room per hour, is a standard metric for assessing ventilation, with recommended targets provided by organizations worldwide. Installing comprehensive carbon dioxide (CO₂) monitoring in schools has expanded opportunities for automating AER estimation, but most schools have limited computational resources and analytical capacity. To address this, we developed a cost-effective and scalable method to estimate AER by leveraging end-of-school day carbon dioxide concentrations recorded with thousands of commercial sensors in classrooms. This method assumes well-mixed conditions and replicates the tracer gas technique, leveraging statistical machine learning and knowledge of classroom operations to automate AER calculations at the end of occupied periods. We analyzed data from 3206 sensors across 125 schools in a large urban school district in the Northeastern United States and identified 648,956 CO₂ decay curves over one school year. After applying data screening criteria, we calculated 323,776 AER values, averaging 84 values (SD = 40) per classroom. Calculated AER ranged from < 0.1–64 h⁻¹, averaging 3.0 h⁻¹ (SD = 2.9). The average AER in schools with central mechanical ventilation was 1.8 times higher than in schools without mechanical ventilation. The method is optimized to use parallel and high-performance computing resources, and calculates daily air exchange rates for an entire classroom over an academic school year in a few seconds, an entire school in a few minutes, and the entire school district in a few hours. To our knowledge, this is the largest deployment of commercial CO₂ sensors in schools that publicly share data. The AER calculation method is scalable and efficient, and automates cleaning, selection, and processing of CO₂ data from commercial sensors, with methods and code transferable to other schools collecting similar large-scale data.

在后covid -19大流行时代，保持学校教室的清洁空气对于确保学生的健康和安全至关重要。空气交换率（AER）衡量的是房间内每小时更换空气的次数，是评估通风的标准指标，世界各地的组织都提供了推荐的目标。在学校安装全面的二氧化碳（CO2）监测系统扩大了自动化AER估计的机会，但大多数学校的计算资源和分析能力有限。为了解决这个问题，我们开发了一种经济有效且可扩展的方法，通过利用教室中数千个商用传感器记录的放学后二氧化碳浓度来估计AER。该方法假设了良好的混合条件，并复制了示踪气体技术，利用统计机器学习和课堂操作知识，在占用期结束时自动计算AER。我们分析了美国东北部一个大型城市学区125所学校的3206个传感器的数据，确定了一学年的648,956条CO₂衰减曲线。在应用数据筛选标准后，我们计算了323,776个AER值，平均每个教室84个值（SD = 40）。计算的AER范围为<； 0.1-64 h−1，平均值为3.0 h−1 （SD = 2.9）。有中心机械通气学校的AER平均值是无中心机械通气学校的1.8倍。该方法利用并行和高性能计算资源进行了优化，并在几秒钟内计算出整个教室在一个学年中的每日空气交换率，在几分钟内计算出整个学校的空气交换率，在几小时内计算出整个学区的空气交换率。据我们所知，这是在公开共享数据的学校中最大的商用二氧化碳传感器部署。AER计算方法具有可扩展性和高效率，可自动清洗、选择和处理来自商用传感器的CO2数据，方法和代码可移植到收集类似大规模数据的其他学校。

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引用次数: 0

Exposure of children and adolescents to volatile organic compounds in indoor air: Results from the German Environmental Survey 2014–2017 (GerES V) 儿童和青少年暴露于室内空气中挥发性有机化合物：2014-2017年德国环境调查结果（GerES V）

Indoor Environments

Pub Date : 2025-03-01 DOI: 10.1016/j.indenv.2025.100082

Annika Fernandez Lahore , Robert Bethke , Anja Daniels , Konrad Neumann , Stefan Ackermann , Nadine Schechner , Klaus-Reinhardt Brenske , Enrico Rucic , Aline Murawski , Marike Kolossa-Gehring , Wolfram Birmili

Indoor air concentrations of volatile organic compounds (VOC) were determined in the living environments of German children and adolescents between 2014 and 2017 during the German Environmental Survey (GerES) V. Passive sampling on Tenax TA tubes over 7 days and subsequent thermodesorption/gas chromatographic analysis yielded concentrations of 61 compounds from the groups of alcohols, alkanes, aromatics, carboxylic acid esters, glycol ethers, halogenated hydrocarbons, siloxanes, and terpenes as well as a value for total VOC (TVOC). The most abundant single compounds were decamethylcyclopentasiloxane (D5), limonene, α-pinene, butyl acetate, toluene, and 2-ethylhexanol, with geometric mean concentrations ranging between 12 and 4.5 µg/m³ . The guideline values established by the German Committee on Indoor Guidance Values (AIR) were exceeded in less than 1.3 % of participants when considered as a sum parameter for cyclic dimethylsiloxanes, monocyclic monoterpenes, bicyclic terpenes, C9-C14 alkanes, and xylenes. The concentrations of most compounds were lower in GerES V (2014/17) compared to the previous cycle GerES IV (2003/06). The concentrations of individual compounds showed moderate associations with exposure factors as identified from questionnaire data including the socio-economic status of the household, migration background, smoking status, the presence of wooden furniture, renovations in the test room, the age of the house, outdoor pollution (proximity to road traffic), as well as the age and sex of the participants.

在2014年至2017年德国环境调查（GerES） v期间，在德国儿童和青少年的生活环境中测定了室内空气中挥发性有机化合物（VOC）的浓度。在Tenax TA管上进行了7天的被动采样，随后进行了热解吸/气相色谱分析，产生了61种化合物的浓度，这些化合物来自醇、烷烃、芳烃、羧酸酯、乙二醇醚、卤化烃、硅氧烷、和萜烯以及总挥发性有机化合物（TVOC）的值。最丰富的单一化合物是十甲基环戊硅氧烷（D5）、柠檬烯、α-蒎烯、乙酸丁酯、甲苯和2-乙基己醇，几何平均浓度在12 ~ 4.5 µg/m³ 之间。当考虑到环二甲基硅氧烷、单环单萜烯、双环萜烯、C9-C14烷烃和二甲苯的总和参数时，德国室内指导值委员会（AIR）确定的指导值超过了不到1.3 %的参与者。与上一个周期GerES IV（2003/06）相比，GerES V（2014/17）中大多数化合物的浓度较低。单个化合物的浓度显示出与暴露因素的适度关联，这些暴露因素从问卷数据中确定，包括家庭的社会经济地位、移民背景、吸烟状况、有无木制家具、试验室的装修情况、房屋的年龄、室外污染（靠近道路交通）以及参与者的年龄和性别。

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引用次数: 0

Causal effects estimation: Using natural experiments in observational field studies in building science 因果效应估计：在建筑科学的实地观察研究中使用自然实验

Indoor Environments

Pub Date : 2025-03-01 DOI: 10.1016/j.indenv.2025.100080

Ruiji Sun , Stefano Schiavon , Gail Brager , Haiyan Yan , Thomas Parkinson

Correlational analysis, such as linear regression, does not imply causation. This paper introduces and applies a causal inference framework and a specific method, regression discontinuity, to thermal comfort field studies. The method utilizes policy thresholds in China, where the winter district heating policy is based on cities' geographical locations relative to the Huai River. The approximate latitude of the Huai River can be considered as a natural, geographical threshold, where cities near the threshold are quite similar, except for the availability of district heating in cities north of the threshold, creating a situation similar to a randomized experiment. Using the regression discontinuity method, we quantify the causal effects of the experiment treatment (district heating) on the physical indoor environments and subjective responses of building occupants. We found that mean indoor operative temperatures were 4.3 °C higher, and mean thermal sensation votes were 0.6 warmer due to the district heating. In contrast, using conventional correlational analysis, we demonstrate that the correlation between indoor operative temperature and thermal sensation votes does not accurately reflect the causal relationship between the two. We also show that the indoor operative temperature could be either positively or negatively correlated with occupants’ thermal satisfaction. However, we cannot conclude that increasing the indoor operative temperature in these circumstances will necessarily lead to higher or lower thermal satisfaction. This highlights the importance of causal inference methods in thermal comfort field studies and other observational studies in building science, where the regression discontinuity method might apply.

相关分析，如线性回归，并不意味着因果关系。本文介绍并应用了一个因果推理框架和一种具体的方法，即回归不连续，来进行热舒适领域的研究。该方法利用了中国的政策阈值，在中国，冬季区域供热政策是基于城市相对于淮河的地理位置。淮河的大致纬度可以被认为是一个自然的地理阈值，在阈值附近的城市非常相似，除了阈值以北的城市区域供暖的可用性，造成类似于随机实验的情况。利用回归不连续方法，我们量化了实验处理（区域供热）对室内物理环境和建筑居住者主观反应的因果关系。我们发现，由于区域供热，平均室内操作温度升高了4.3°C，平均热感觉投票升高了0.6°C。相比之下，使用传统的相关分析，我们证明室内操作温度和热感觉投票之间的相关性并不能准确反映两者之间的因果关系。我们还发现，室内工作温度与居住者的热满意度可能呈正相关或负相关。然而，我们不能得出结论，在这些情况下，增加室内工作温度一定会导致更高或更低的热满意度。这突出了因果推理方法在热舒适领域研究和建筑科学中的其他观察研究中的重要性，其中回归不连续方法可能适用。

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引用次数: 0

Demonstration of a novel tracer gas method to investigate indoor air mixing and movement 一种新型示踪气体方法的演示，用于研究室内空气混合和运动

Indoor Environments

Pub Date : 2025-02-20 DOI: 10.1016/j.indenv.2025.100081

Chai Yoon Um , William W. Delp , Rowan C. Blacklock , Brett C. Singer

This paper reports on equipment and procedures that enable the application of the pulsed tracer method to study air movement, contaminant transport, and mixing in rooms. We use ethanol as a non-toxic tracer and a network of low-cost, fast response (2 s) metal oxide sensors to measure airborne concentrations at high frequency. The method was demonstrated in a 158 m³ room of the FLEXLAB facility at Lawrence Berkeley National Laboratory, with an overhead HVAC system with controllable supply airflow and temperature. The room was configured as a meeting space with 8 simulated occupants. The sensors were mounted in a 3 × 4 grid in the upper room (0.3 m from the 2.74 m ceiling), in the middle height of the room at 1.1–1.4 m, and at several locations 0.1–0.4 m from the floor. Vaporized ethanol was released in pulses of 20 s. Sensors were cross-calibrated in-situ to provide quantitative information about relative concentrations and exposures. Results show that the method provides quantitative information about air movement patterns and mixing. For example, mixing throughout the room took 3–4 min with high supply airflow at neutral temperature and 7.5–9 min with heated supply air provided at a lower rate. The test can be used to evaluate whether air movement from the occupied zone to the upper room is fast enough to achieve the extremely high air cleaning rates that are possible with upper room germicidal ultraviolet disinfection (GUV) systems under ideal mixing conditions.

本文报道了能够应用脉冲示踪法研究室内空气运动、污染物输送和混合的设备和程序。我们使用乙醇作为无毒示踪剂和低成本、快速响应（2 s）的金属氧化物传感器网络，以高频测量空气中的浓度。该方法在劳伦斯伯克利国家实验室FLEXLAB设施的158 m3房间中进行了演示，该房间具有可控制供应气流和温度的架空HVAC系统。这个房间被配置为一个有8个模拟居住者的会议空间。传感器安装在上部房间（距离2.74 米的天花板0.3 米）的3 × 4网格中，在房间的中间高度1.1-1.4 米，在距离地板0.1-0.4 米的几个位置。蒸发的乙醇以20 s的脉冲释放。传感器在现场交叉校准，以提供有关相对浓度和暴露的定量信息。结果表明，该方法提供了空气运动模式和混合的定量信息。例如，在中性温度下，在高送风情况下，整个房间的混合时间为3-4 min，而在低送风速度下，在加热送风情况下，混合时间为7.5-9 min。该测试可用于评估空气从占用区到上层房间的运动是否足够快，以实现在理想混合条件下上层房间杀菌紫外线消毒（GUV）系统可能实现的极高空气清洁率。

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引用次数: 0

Corrigendum to “Ventilation characteristics in a hospital where a COVID-19 outbreak occurred in the winter of 2020” [Indoor Environ. 2 (2025) 100065] 《2020年冬季发生新冠肺炎疫情的医院通风特征》的勘误表[室内环境，2 (2025)100065]

Indoor Environments

Pub Date : 2025-02-05 DOI: 10.1016/j.indenv.2025.100076

Motoya Hayashi , Sayaka Murata , Koki Kikuta

引用次数: 0

Implementing Bayesian inference on a stochastic CO2-based grey-box model 基于随机co2灰盒模型的贝叶斯推理实现

Indoor Environments

Pub Date : 2025-01-29 DOI: 10.1016/j.indenv.2025.100079

Shujie Yan , Jiwei Zou , Chang Shu , Justin Berquist , Vincent Brochu , Marc Veillette , Danlin Hou , Caroline Duchaine , Liang (Grace) Zhou , Zhiqiang (John) Zhai , Liangzhu (Leon) Wang

The COVID-19 pandemic brought global attention to indoor air quality (IAQ), which increases public’s awareness on monitoring indoor ventilation conditions significantly. Indoor CO₂ monitoring has been widely accepted as an effective way for indicating IAQ conditions, attributed to its close relationships with indoor air change rates. However, real-time estimation of air change rates or CO₂ emission rates from CO₂ measurement data remains challenging due to uncertainties in factors like random air movements, dynamic conditions (e.g., weather and occupancy), and the limitations of deterministic equations. This study addresses these challenges by applying Bayesian inference to a stochastic CO₂-based grey-box model, enabling the accurate estimation of ventilation and CO₂ emission rates while accounting for uncertainty. The model’s accuracy and robustness were validated through CO₂ tracer gas experiments, employing constant injection and decay methods in a large-scale aerosol chamber. Both prior and posterior predictive checks (PPC) were performed to verify this approach. The approach proposed by this study improves the interpretation of CO₂ monitoring data, thereby facilitating the future real-time IAQ management.

新冠肺炎疫情引起了全球对室内空气质量（IAQ）的关注，这大大提高了公众对室内通风状况监测的认识。由于与室内空气变化速率密切相关，室内CO2监测已被广泛接受为指示室内空气质量状况的有效方法。然而，由于随机空气运动、动态条件（如天气和占用）以及确定性方程的局限性等因素的不确定性，从二氧化碳测量数据中实时估计空气变化率或二氧化碳排放率仍然具有挑战性。本研究通过将贝叶斯推理应用于随机二氧化碳灰盒模型来解决这些挑战，从而在考虑不确定性的同时准确估计通风和二氧化碳排放率。通过在大型气溶胶室中采用恒定注入和衰减方法的CO2示踪气体实验，验证了模型的准确性和鲁棒性。进行了先验和后验预测检查（PPC）来验证该方法。本研究提出的方法改善了CO2监测数据的解释，从而促进了未来室内空气质量的实时管理。

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引用次数: 0

CO2 levels and SARS-CoV-2 transmission in public schools: A retrospective cohort study in Montreal (Canada) 加拿大蒙特利尔公立学校二氧化碳水平与SARS-CoV-2传播的回顾性队列研究

Indoor Environments

Pub Date : 2025-01-27 DOI: 10.1016/j.indenv.2025.100077

Olivier Séguin , Dorra Ghorbal , Gabrielle Denault , Karine Trudeau , Patrick Poulin , Catherine Dea , Stéphane Perron

Scientific evidence suggests that SARS-CoV-2 is transmitted primarily through close contact with susceptible individuals and that the risk of transmission increases during prolonged exposure in confined, inadequately ventilated and densely occupied spaces. In response to concerns related to inadequate ventilation for students and staff, CO₂ concentrations were measured in all of Montreal’s public elementary and high schools during winter of 2020–21. This study aims to evaluate the associations between ventilation system types, mid-class CO₂ concentrations and SARS-CoV-2 transmission amongst Montreal's public school’s attendees during the 2020–2021 school year. Data on building ventilation types, CO₂ measurements and school characteristics such as total enrollment and socioeconomic status (SES), were sourced from Ministry of Education’s administrative data for the 2020–2021 school year. During this pandemic period, the Montreal Public Health Department investigated COVID-19 cases among students and staff in public elementary and high schools, gradually developing a regional database of school cases and outbreaks from intervention files. Negative binomial regression models were employed to examine associations between mid-class CO₂ concentrations and COVID-19 incidence rates for both total cases and those acquired within schools. Regression models were adjusted for school types, neighborhood COVID-19 incidence rates and school SES. The mid-class CO₂ concentrations median was 1050 ppm in the 384 school buildings. CO₂ concentrations were associated with ventilation systems, with schools using natural ventilation exhibiting higher concentrations compared to three other types of mechanical ventilation. No positive association was observed between the incidence rates of school-acquired cases and higher mid-class CO₂ concentrations in both unadjusted and adjusted models.

科学证据表明，SARS-CoV-2主要通过与易感个体的密切接触传播，并且在密闭、通风不足和人员密集的空间中长期暴露会增加传播风险。为了回应对学生和工作人员通风不足的担忧，在2020-21年冬季，蒙特利尔所有公立小学和高中的二氧化碳浓度都进行了测量。本研究旨在评估2020-2021学年蒙特利尔公立学校学生中通风系统类型、中产阶级二氧化碳浓度和SARS-CoV-2传播之间的关系。建筑通风类型、二氧化碳测量和学校特征（如总入学人数和社会经济地位（SES））的数据来自教育部2020-2021学年的行政数据。在这次大流行期间，蒙特利尔公共卫生部门调查了公立小学和高中的学生和工作人员的COVID-19病例，逐步从干预文件中建立了学校病例和疫情的区域数据库。采用负二项回归模型来检验中产阶级二氧化碳浓度与总病例和学校内获得病例的COVID-19发病率之间的关系。根据学校类型、社区COVID-19发病率和学校社会经济状况调整回归模型。384所学校的中产阶级二氧化碳浓度中位数为1050 ppm。二氧化碳浓度与通风系统有关，与其他三种类型的机械通风相比，使用自然通风的学校表现出更高的浓度。在未调整和调整的模型中，学校获得性病例的发生率与较高的中产阶级二氧化碳浓度之间均未观察到正相关。

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引用次数: 0

Cognition, economic decision-making, and physiological response to carbon dioxide 认知、经济决策和对二氧化碳的生理反应

Indoor Environments

Pub Date : 2025-01-27 DOI: 10.1016/j.indenv.2025.100074

Stefan Flagner , Thomas Meissner , Steffen Künn , Piet Eichholtz , Nils Kok , Rick Kramer , Wouter van Marken-Lichtenbelt , Cynthia Ly , Guy Plasqui

This study examines the isolated effect of carbon dioxide on cognition, economic decision-making, and the physiological response in healthy adults. The experiment took place in an air-tight respiration chamber controlling the environmental conditions. In a single-blind, within-subject study design, 20 healthy participants were exposed to artificially induced carbon dioxide concentrations of 3,000 ppm and 900 ppm in randomized order, with each exposure lasting for 8 h. A high ventilation rate and an air pollutant filter were used to keep concentrations of volatile organic compounds and fine particles equally low in both conditions. Cognition tests were conducted twice during the 8 h and physiological parameters were measured continuously over the 8 h. No evidence on a robust statistically significant effect of carbon dioxide on either cognitive or physiological outcome variables were found. These findings imply that the human body is able to deal with exposure to indoor carbon dioxide concentration of 3,000 ppm for a limited time without suffering significant cognitive decline, changes in decision-making or showing any physiological response.

本研究考察了二氧化碳对健康成人的认知、经济决策和生理反应的孤立影响。实验在一个控制环境条件的密闭呼吸室内进行。在单盲、受试者内研究设计中，20名健康参与者按随机顺序暴露在人为诱导的3000 ppm和900 ppm的二氧化碳浓度中，每次暴露持续8小时。高通风率和空气污染物过滤器用于在两种条件下保持挥发性有机化合物和细颗粒的浓度同样低。在8小时内进行两次认知测试，并在8小时内连续测量生理参数。没有证据表明二氧化碳对认知或生理结果变量有显著的统计学影响。这些发现表明，人体能够在有限的时间内暴露于室内浓度为3000 ppm的二氧化碳中，而不会出现显著的认知能力下降、决策能力改变或任何生理反应。

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引用次数: 0

Personal air cleaning by a user-tracking robot equipped with a nanofiber air cleaner in a large work space 配备纳米纤维空气净化器的用户跟踪机器人在大型工作空间内进行个人空气净化

Indoor Environments

Pub Date : 2025-01-27 DOI: 10.1016/j.indenv.2025.100078

Chengzhong Deng , Zhuolun Niu , Chun Chen

In large work spaces, such as logistics warehouses, implementing whole-space air cleaning to protect the workers’ health can be costly. To tackle this issue, the present study developed a user-tracking robot equipped with a nanofiber air cleaner to achieve personal air cleaning for a moving worker in a large work space. First, nanofiber air filters with low pressure drop were fabricated using the electrospinning technique. An air cleaner with a deflector for directing the airflow towards the user’s breathing zone and the nanofiber air filters was assembled and then integrated into a user-tracking robot. Experiments were conducted to measure the clean air delivery rate (CADR) of the nanofiber air cleaner, evaluate the accuracy of the user-tracking algorithm, and determine the optimal deflector setup and user-to-robot distance. Field tests were conducted to evaluate the personal air cleaning performance of the proposed method by comparison with a stationary nanofiber air cleaner. The results show that the user-tracking algorithm of the user-tracking robot was accurate, with an average absolute error in the user-to-robot distance of 4 cm. The user-tracking robot with nanofiber air cleaner outperformed the stationary nanofiber air cleaner by reducing the concentration of 0.3–0.4 μm particles in the breathing zone of the user by 16.4 %. Furthermore, compared with commercial panel-type high-efficiency particulate air (HEPA) filters, the use of nanofiber air filters can extend the battery service life, consequently facilitating the practical application of the moving robot.

在大型工作空间，如物流仓库，实施整个空间的空气清洁以保护工人的健康可能代价高昂。为了解决这个问题，本研究开发了一种配备纳米纤维空气清洁器的用户跟踪机器人，以实现大型工作空间中移动工人的个人空气清洁。首先，采用静电纺丝技术制备了具有低压降的纳米纤维空气过滤器。组装了一个带有偏转板的空气净化器，用于将气流引导到用户的呼吸区，并将纳米纤维空气过滤器集成到用户跟踪机器人中。实验测量了纳米纤维空气净化器的洁净空气输送率（CADR），评估了用户跟踪算法的准确性，确定了最佳偏转板设置和用户与机器人的距离。通过与固定式纳米纤维空气净化器的对比，对该方法的个人空气净化性能进行了现场测试。结果表明，用户跟踪机器人的用户跟踪算法是准确的，在用户到机器人距离上的平均绝对误差为4 cm。使用纳米纤维空气净化器的用户跟踪机器人比固定式纳米纤维空气净化器将用户呼吸区0.3 ~ 0.4 μm颗粒浓度降低了16.4 %，优于固定式纳米纤维空气净化器。此外，与商用板式高效微粒空气过滤器（HEPA）相比，纳米纤维空气过滤器的使用可以延长电池的使用寿命，从而促进移动机器人的实际应用。

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引用次数: 0

Corrigendum to “Towards equitable and sustainable indoor air quality guidelines – A perspective on mandating indoor air quality for public buildings” [Indoor Environ. 2 1 (2025) 100070] “迈向公平和可持续的室内空气质素指引-从公共建筑物室内空气质素规定的角度看问题”的勘误表[室内环境，21 (2025)100070]

Indoor Environments

Pub Date : 2025-01-21 DOI: 10.1016/j.indenv.2025.100075

Ulla Haverinen-Shaughnessy , Marzenna R. Dudzinska , Samy Clinchard , Sani Dimitroulopoulou , Xiaojun Fan , Piet Jacobs , Henna Maula , Amelia Staszowska , Oluyemi Toyinbo , Ju-Hyeong Park

引用次数: 0