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Search Results (382)

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Keywords = IAQ

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22 pages, 3070 KiB  
Article
Analysis of the Interplay between Indoor Air Quality and Thermal Comfort in University Classrooms for Enhanced HVAC Control
by Giulia Lamberti, Francesco Leccese and Giacomo Salvadori
Energies 2024, 17(20), 5053; https://doi.org/10.3390/en17205053 - 11 Oct 2024
Viewed by 607
Abstract
While aspects of indoor environmental quality, such as thermal comfort, indoor air quality (IAQ), acoustic, and visual comfort, are usually studied separately, their interactions are crucial yet often overlooked. Understanding how these factors influence each other is essential for a comprehensive perception of [...] Read more.
While aspects of indoor environmental quality, such as thermal comfort, indoor air quality (IAQ), acoustic, and visual comfort, are usually studied separately, their interactions are crucial yet often overlooked. Understanding how these factors influence each other is essential for a comprehensive perception of the indoor environment. This paper investigates the relationship between indoor air quality (IAQ) and thermal comfort using an extensive field investigation conducted in university classrooms during the heating season, collecting 712 samples of subjective responses correlated with environmental measurements. Key findings reveal significant correlations between subjective responses related to the thermal environment and those related to air quality. Perceived control over the thermal environment shows stronger correlations with IAQ responses than with thermal responses, particularly with perceived ventilation (r = 0.41), COVID-19 risk (r = 0.28), and air quality (r = 0.28). Additionally, environmental parameters demonstrate stronger correlations with thermal responses than with IAQ responses. Higher CO2 concentration is associated with increased thermal sensation and decreased thermal preference and perceived control. Conversely, IAQ responses remain relatively stable with changes in indoor operative temperature. The difference between the operative temperature to which the occupants are exposed and their expressed neutral temperature widens as CO2 concentration rises, indicating a reduced adaptive capacity of occupants which is associated with increasing CO2 levels. These insights are crucial for providing HVAC system management strategies that consider the interaction between different aspects of IEQ, aiming to improve occupants’ well-being and reduce energy consumption. Full article
(This article belongs to the Special Issue Adaptive Thermal Comfort and Energy Use in Buildings)
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<p>Internal and external views of Italian (<b>a</b>) and French (<b>b</b>) classrooms.</p>
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<p>Running mean outdoor temperature (<b>a</b>) and adaptive graph (<b>b</b>) for the monitored periods. Legend: Comfort temperature (dashed line); Category I (dashed and dotted line); Category II (dotted line); and Category III (solid line).</p>
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<p>Heatmap showing the correlations between subjective responses. The numbers show the correlation coefficients (r).</p>
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<p>Heatmap showing the correlations between environmental parameters and the thermal comfort (<b>a</b>) or air quality (<b>b</b>) answers. The numbers show the correlation coefficients (r).</p>
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<p>Relationships between CO<sub>2</sub> and thermal responses (<b>a</b>); CO<sub>2</sub> and IAQ responses (<b>b</b>); (<b>c</b>) T<sub>op</sub> and thermal responses; and T<sub>op</sub> and IAQ responses (<b>d</b>).</p>
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<p>Weighted regression analysis considering the operative temperature and TSV. The dotted line represents the weighted regression, while the circles indicate the clustered TSV in 0.5 °C intervals of T<sub>op</sub>.</p>
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<p>Boxplot of neutral temperatures (<b>a</b>) and mean difference between T<sub>op</sub> and T<sub>N</sub> (<b>b</b>) at different CO<sub>2</sub> concentration ranges.</p>
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20 pages, 2477 KiB  
Article
Utilizing an Arduino Uno-Based System with Integrated Sensor Data Fusion and Filtration Techniques for Enhanced Air Quality Monitoring in Residential Spaces
by Ivan Rudavskyi, Halyna Klym, Yuriy Kostiv, Ivan Karbovnyk, Illia Zhydenko, Anatoli I. Popov and Marina Konuhova
Appl. Sci. 2024, 14(19), 9012; https://doi.org/10.3390/app14199012 - 6 Oct 2024
Viewed by 869
Abstract
This study presents an air quality monitoring system that employs the Arduino Uno microcontroller. The system is augmented with a moving average filter and data fusion techniques from BME680 and CCS811 sensors, which are designed to process and combine data from these sensors. [...] Read more.
This study presents an air quality monitoring system that employs the Arduino Uno microcontroller. The system is augmented with a moving average filter and data fusion techniques from BME680 and CCS811 sensors, which are designed to process and combine data from these sensors. The system was tested and analyzed empirically across a range of residential environments in order to validate its efficacy. The findings indicated that the typical IAQ level in a bedroom was approximately 20 units. However, this level increased significantly, reaching 140 units, within minutes after the introduction of a 17% perfume spray. In contrast, the use of an aromatic diffuser resulted in a smaller increase in IAQ to 40 units, which returned to normal levels after ventilation. Moreover, the analysis demonstrated that the kitchen and bathroom exhibited inferior air quality in comparison to the bedroom. This was evidenced by elevated VOC and humidity levels, which were observed to be 10–20% higher due to the combined effects of household activities and inadequate ventilation. This study makes a significant contribution to the field of air quality monitoring by proposing a solution that employs sensor technology and data processing methods to enhance the quality of life within residential spaces. Full article
(This article belongs to the Special Issue Air Quality in Indoor Environments, 2nd Edition)
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<p>External appearance of the developed system.</p>
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<p>Functional electrical circuit diagram of the system.</p>
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<p>Results of temperature, humidity, VOC, and CO<sub>2</sub> calibrations.</p>
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<p>Temperature (<b>a</b>), humidity (<b>b</b>), VOC (<b>c</b>), and CO<sub>2</sub> (<b>d</b>) comparisons of the three systems.</p>
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<p>Dataset for carbon dioxide.</p>
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<p>Dataset for humidity.</p>
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<p>Dataset for indoor air quality.</p>
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<p>Dataset for volatile organic compounds.</p>
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<p>Dataset for outside temperature.</p>
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<p>Dataset for outside humidity.</p>
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<p>Variations in CO<sub>2</sub> levels (<b>a</b>) as well as VOC Levels and IAQ (<b>b</b>) throughout the day.</p>
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<p>Correlation between VOC and temperature.</p>
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<p>Correlation between VOC and humidity.</p>
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<p>Correlation between VOC and CO<sub>2</sub>.</p>
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<p>Impact of aromatic diffuser and perfume on CO<sub>2</sub> (<b>a</b>), IAQ (<b>b</b>), and VOC (<b>c</b>) with predicted values and marked air quality indexes marked in <a href="#applsci-14-09012-t001" class="html-table">Table 1</a>.</p>
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<p>Impact of aromatic diffuser and perfume on CO<sub>2</sub> (<b>a</b>), IAQ (<b>b</b>), and VOC (<b>c</b>) with predicted values and marked air quality indexes marked in <a href="#applsci-14-09012-t001" class="html-table">Table 1</a>.</p>
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15 pages, 2590 KiB  
Article
CO2 Levels in Classrooms: What Actions to Take to Improve the Quality of Environments and Spaces
by Gaetano Settimo, Luciana Indinnimeo, Marco Inglessis, Marco De Felice, Roberta Morlino, Annalisa di Coste, Fabiana Carriera, Cristina Di Fiore and Pasquale Avino
Sustainability 2024, 16(19), 8619; https://doi.org/10.3390/su16198619 - 4 Oct 2024
Viewed by 938
Abstract
Indoor air quality (IAQ) is a crucial priority, especially since people spend most of their time indoors. Indoor air can be more polluted than outdoor air due to sources such as building materials, cleaning products, and heating systems. This condition can affect health [...] Read more.
Indoor air quality (IAQ) is a crucial priority, especially since people spend most of their time indoors. Indoor air can be more polluted than outdoor air due to sources such as building materials, cleaning products, and heating systems. This condition can affect health and productivity, especially in schools and work environments. Students spend about a third of their day in classrooms, and studies have shown that poor IAQ can cause respiratory and allergic problems, especially among children, who are more vulnerable. Poor ventilation and excessive CO2 concentration are indicators of suboptimal indoor air quality, which can lead to symptoms such as headaches, fatigue, and worsening asthma. In Italy, the lack of specific legislation on indoor air quality in schools is a problem, but improved ventilation, both natural and mechanical, and monitoring of CO2 levels are recommended to prevent negative health consequences. This paper aims to describe a methodology to improve IAQ in schools. The paper discusses the results of a study conducted on CO2 and PM10 levels measured in real time in cold season (Nov–Mar) in different classrooms of primary and secondary schools present in a large Italian urban area in order to understand the IAQ state and identify possible improvement actions. Full article
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<p>Layout (above and frontal layout sections) of a typical classroom and the related positions of the sampler (blue: student desk; green; teacher desk; orange: instrument desk).</p>
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<p>Comparison between a DustTrak monitor for measuring outdoor aerosol (blue line) and a SidePack monitor for measuring indoor aerosol (orange line). The correlation equation between the two data sets is y = 1.137x − 0.861 whereas the agreement (as R<sup>2</sup>) is 0.811.</p>
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<p>Typical CO<sub>2</sub> fluctuations (ppm) during school and no-school activities in relationship with the temperature (T °C) and relative humidity (RH %) changes.</p>
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<p>Typical PM<sub>2.5</sub> indoor behavior related to the PM<sub>2.5</sub> outdoor and CO<sub>2</sub> levels.</p>
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<p>Two-days trends of CO<sub>2</sub> and PM<sub>2.5</sub> indoor and outdoor in a Rome school where different activities are present in the morning and in the afternoon.</p>
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34 pages, 3203 KiB  
Systematic Review
Feasibility and Affordability of Low-Cost Air Sensors with Internet of Things for Indoor Air Quality Monitoring in Residential Buildings: Systematic Review on Sensor Information and Residential Applications, with Experience-Based Discussions
by Yong Yu, Marco Gola, Gaetano Settimo, Maddalena Buffoli and Stefano Capolongo
Atmosphere 2024, 15(10), 1170; https://doi.org/10.3390/atmos15101170 - 30 Sep 2024
Viewed by 992
Abstract
In residential buildings that are private, autonomous, and occupied spaces for most of the time, it is necessary to maintain good indoor air quality (IAQ), especially when there are children, elderly, or other vulnerable users. Within the development of sensors, their low-cost features [...] Read more.
In residential buildings that are private, autonomous, and occupied spaces for most of the time, it is necessary to maintain good indoor air quality (IAQ), especially when there are children, elderly, or other vulnerable users. Within the development of sensors, their low-cost features with adequate accuracy and reliability, as well as Internet of Things applications, make them affordable, flexible, and feasible even for ordinary occupants to guarantee IAQ monitoring in their homes. This systematic review searched papers based on Scopus and Web of Science databases about the Low-Cost Sensors (LCS) and IoT applications in residential IAQ research, and 23 studies were included with targeted research contents. The review highlights several aspects of the active monitoring strategies in residential buildings, including the following: (1) Applying existing appropriate sensors and their target pollutants; (2) Applying micro-controller unit selection; (3) Sensors and devices’ costs and their monitoring applications; (4) Data collection and storage methods; (5) LCS calibration methods in applications. In addition, the review also discussed some possible solutions and limitations of LCS applications in residential buildings based on the applications from the included works and past device development experiences. Full article
(This article belongs to the Special Issue Enhancing Indoor Air Quality: Monitoring, Analysis and Assessment)
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<p>Flowchart of the bibliographic review process.</p>
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<p>Themes of selected papers (<b>a</b>) and years of the included publications (<b>b</b>).</p>
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<p>Sensor measured parameters and mentioned times.</p>
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<p>MCUs used in the included publications. Images (<b>g</b>,<b>i</b>) are taken by Y.Y. (one of the authors), (<b>a</b>) is from [<a href="#B41-atmosphere-15-01170" class="html-bibr">41</a>], (<b>b</b>) is from [<a href="#B42-atmosphere-15-01170" class="html-bibr">42</a>], (<b>c</b>) is from [<a href="#B43-atmosphere-15-01170" class="html-bibr">43</a>], (<b>d</b>) is from [<a href="#B44-atmosphere-15-01170" class="html-bibr">44</a>], (<b>e</b>) is from [<a href="#B45-atmosphere-15-01170" class="html-bibr">45</a>], (<b>f</b>) is from [<a href="#B46-atmosphere-15-01170" class="html-bibr">46</a>], (<b>h</b>) is from [<a href="#B47-atmosphere-15-01170" class="html-bibr">47</a>] respectively.</p>
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<p>Two different versions of the esp8266 board with totally different conditions in sleep mode (photos by Y.Y., one of the authors).</p>
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18 pages, 1133 KiB  
Article
Is More Really More? Evidence of a Curvilinear Relationship between the Extent of Telework and Employees’ Temporal Alignment of Work and Private Life in Germany
by Alexandra Mergener, Timothy Rinke and Ines Entgelmeier
Soc. Sci. 2024, 13(10), 508; https://doi.org/10.3390/socsci13100508 - 27 Sep 2024
Viewed by 359
Abstract
Studies exploring not only whether, but also to what extent, telework can improve employees’ ability to coordinate private and work-related demands are largely absent. Using a probability-based large-scale survey of employees in Germany (N = 14,999), this study provides evidence of an inverted [...] Read more.
Studies exploring not only whether, but also to what extent, telework can improve employees’ ability to coordinate private and work-related demands are largely absent. Using a probability-based large-scale survey of employees in Germany (N = 14,999), this study provides evidence of an inverted U-shaped relationship between the extent of telework and employees’ temporal alignment of work and private life, i.e., their success in considering personal and family matters when scheduling work. When telework comprised up to 40 percent of the total working time, employees were observed to temporally align their work and private life better than those who only worked on-site. Additional analyses indicated that particularly men, and even more so fathers, experience improved work and private life alignment with frequent teleworking. For women with and without children, however, highly extensive teleworking not only loses its positive effect, but is associated with less success in aligning work and private life compared to non-teleworking. To be able to benefit from telework, even when it is used extensively, clear rules are needed, for example, regarding expectations of accessibility for paid work as well as for home and care work. Full article
(This article belongs to the Section Work, Employment and the Labor Market)
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<p>Average probabilities of the temporal alignment of work and private life by telework intensity (estimates of Model 2). Source: BIBB/BAuA Employment Survey 2018. Sample includes employees aged 18–65. Authors’ own calculations.</p>
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<p>Average probabilities of the temporal alignment of work and private life by telework intensity for women with and without young children (estimates of Model 3a). Source: BIBB/BAuA Employment Survey 2018. Sample includes employees aged 18–65. Authors’ own calculations.</p>
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<p>Average probabilities of the temporal alignment of work and private life by telework intensity for men with and without young children (estimates of Model 3b). Source: BIBB/BAuA Employment Survey 2018. Sample includes employees aged 18–65. Authors’ own calculations.</p>
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22 pages, 2775 KiB  
Article
Indoor Air Quality at an Urban Primary School in Madrid (Spain): Influence of Surrounding Environment and Occupancy
by Elisabeth Alonso-Blanco, Francisco Javier Gómez-Moreno, Elías Díaz-Ramiro, Marcos Barreiro, Javier Fernández, Ibai Figuero, Alejandro Rubio-Juan, Jesús Miguel Santamaría and Begoña Artíñano
Int. J. Environ. Res. Public Health 2024, 21(10), 1263; https://doi.org/10.3390/ijerph21101263 - 24 Sep 2024
Viewed by 660
Abstract
Monitoring indoor air quality (IAQ) in schools is critical because children spend most of their daytime inside. One of the main air pollutant sources in urban areas is road traffic, which greatly influences air quality. Thus, this study addresses, in depth, the linkages [...] Read more.
Monitoring indoor air quality (IAQ) in schools is critical because children spend most of their daytime inside. One of the main air pollutant sources in urban areas is road traffic, which greatly influences air quality. Thus, this study addresses, in depth, the linkages of meteorology, ambient air pollution, and indoor activities with IAQ in a traffic-influenced school situated south of Madrid. The measurement period was from 22 November to 21 December 2017. Simultaneous measurements of indoor and outdoor PM1, PM2.5, and PM10 mass concentrations, ultrafine particle number concentration (PNC) and equivalent black carbon (eBC) were analyzed under different meteorological conditions. PNC and eBC outdoor concentrations and their temporal trend were similar among the sampling points, with all sites being influenced in the same way by traffic emissions. Strong correlations were found between indoor and outdoor concentrations, indicating that indoor pollution levels were significantly affected by outdoor sources. Especially, PNC and eBC had the same indoor/outdoor (I/O) trend, but indoor concentrations were lower. The time delay in indoor vs. outdoor concentrations varied between 0.5 and 2 h, depending on wind speed. Significant differences were found between different meteorological conditions (ANOVA p-values < 2.14 × 10−6). Atmospheric stability periods led to an increase in indoor and outdoor pollutant levels. However, the highest I/O ratios were found during atmospheric instability, especially for eBC (an average of 1.2). This might be related to rapid changes in the outdoor air concentrations induced by meteorology. Significant variations were observed in indoor PM10 concentrations during classroom occupancy (up to 230 µg m−3) vs. non-occupancy (up to 19 µg m−3) days, finding levels higher than outdoor ones. This was attributed to the scholarly activities in the classroom. Conversely, PNC and eBC concentrations only increased when the windows of the classroom were open. These findings have helped to establish practical recommendations and measures for improving the IAQ in this school and those of similar characteristics. Full article
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<p>The blue circle in the map shows the location of the school selected for this study and the red arrow indicates its building scheme (<b>top</b>), identifying the sampling point locations (<b>bottom</b>): classroom A (<b>A</b>), classroom B (<b>B</b>), and external checkpoint outside the school grounds (<b>C</b>).</p>
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<p>Temporal evolution of PNC, eBC, PM<sub>10</sub>, and trace gases (SO<sub>2</sub>, NO, NO<sub>2</sub>, and O<sub>3</sub>) obtained at the external checkpoint and meteorology information (upper and lower temperature (upper and lower T, respectively), relative humidity (RH), wind speed and direction (WS and WD, respectively), precipitation (P), solar radiation (SR), and atmospheric pressure (AP)) obtained at the CIEMAT site during the period of monitoring. In the graph, “Stability” refers to atmospheric stability periods, “Intermediate” to intermediate atmospheric periods, and “Instability” to atmospheric instability periods. The main surface pressure analysis maps and dust load maps describing the different atmospheric periods identified in this study are incorporated on top of the figure.</p>
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<p><b>Upper panel</b>: Simultaneous time series of outdoor PNC and eBC measured at the three sampling points. <b>Lower panel</b>: Temporal variation of meteorological parameters (upper and lower temperature (upper and lower T, respectively), relative humidity (RH), wind speed and direction (WS and WD, respectively), precipitation (P), solar radiation (SR), and atmospheric pressure (AP)) obtained at CIEMAT site during the period 15–19 December 2017.</p>
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<p>Box plot of 10 min indoor and outdoor concentrations for all pollutants (PNC, PM<sub>10</sub>, PM<sub>2.5</sub>, PM<sub>1</sub>, and eBC) measured in the two classrooms (A and B) during a non-occupancy (weekend) period (from 15 December 2017, at 21:10 UTC to 17 December 2017, at 20:10 UTC) with all available data. In the graph, the prefix “Out” refers to outdoor, whereas “In” indicates indoor measurements.</p>
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<p>Simultaneous time series of indoor/outdoor (I/O) pollutants (PNC, PM<sub>10</sub>, PM<sub>2.5</sub>, PM<sub>1</sub>, and eBC) measured at classrooms A and B during two non-occupancy periods (weekends and vacation), from (<b>A</b>) 6 to 11 December 2017 (left panel) and (<b>B</b>) 16 to 18 December 2017 (right panel), with stable and ventilated atmospheric conditions, respectively. In the graph, the prefix “Out” refers to outdoor, whereas “In” indicates indoor measurements.</p>
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<p>Simultaneous time series of indoor/outdoor (I/O) pollutants (PNC, PM<sub>10</sub>, PM<sub>2.5</sub>, PM<sub>1</sub>, and eBC) measured at classroom A. Examples of the three different activities in the classroom considered in this study are (<b>A</b>) an occupancy period, (<b>B</b>) a window-open period during occupancy, and (<b>C</b>) an open-window period without occupancy. The red dotted line in PNC represents the optimal detection range of the indoor CPC (0–1 × 10<sup>4</sup> cm<sup>−3</sup>), in PM<sub>10</sub> this dotted line represents the WHO 24 h standard of 45 µg m<sup>−3</sup>, and in PM<sub>2.5</sub> it represents the WHO 24 h standard of 15 µg m<sup>−3</sup> for indoor ambient air levels. In the graph, the prefix “Out” refers to outdoor, whereas “In” indicates indoor measurements.</p>
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25 pages, 3500 KiB  
Article
A Co-Location Study of 87 Low-Cost Environmental Monitors: Assessing Outliers, Variability, and Uncertainty
by Sanyogita Manu and Adam Rysanek
Buildings 2024, 14(9), 2965; https://doi.org/10.3390/buildings14092965 - 19 Sep 2024
Viewed by 651
Abstract
While field research in indoor air quality (IAQ) increasingly uses large numbers of low-cost sensors, detailed validation of each sensor is becoming infeasible, ignored, or undeclared. Questions remain about whether these sensors meet manufacturer or third-party specifications and whether their utility improves with [...] Read more.
While field research in indoor air quality (IAQ) increasingly uses large numbers of low-cost sensors, detailed validation of each sensor is becoming infeasible, ignored, or undeclared. Questions remain about whether these sensors meet manufacturer or third-party specifications and whether their utility improves with some validation, even under imperfect conditions. This study details the outcomes of a co-location experiment with 87 low-cost IAQ monitors, conducted with the objective of verifying their performance in measuring total volatile organic compounds (tVOCs), particulate matter 2.5 (PM2.5), carbon dioxide (CO2), temperature, and relative humidity. The monitors were installed next to professional-grade reference IAQ instruments in an office with controlled ventilation. A mixed validation methodology was used, involving outlier detection, uncertainty quantification, and performance metric calculations. Results showed that CO2, temperature, and humidity sensors reliably met manufacturer specifications, while tVOC sensors had significant accuracy issues, deviating by up to 79% from reference measurements—substantially more than the stated uncertainty of ±20%. PM2.5 sensors were more consistent but had an error margin of ±27%, compared to the stated ±15%. A total of 5 of the 87 sensors (5.7%) were outliers for at least one IAQ indicator. Despite the need for further long-term validation, this study highlights the importance of performing an experimental evaluation of low-cost IAQ monitors before field deployment. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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<p>Experimental space.</p>
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<p>Sequence of experiments and data analysis.</p>
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<p>Scatter plots showing the measurements from the cluster of TIs compared to a reference for <span class="html-italic">t</span>VOCs, PM<sub>2.5</sub>, CO<sub>2</sub>, temperature, and relative humidity. Each point represents a test reading, with the dashed blue line indicating a perfect match to the reference readings (slope = 1) and red dots highlighting outliers with a Z-score &gt; 4.</p>
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<p>Statistical analysis of evaluation metrics for the cluster of 87 TIs for <span class="html-italic">t</span>VOCs, PM<sub>2.5</sub>, CO<sub>2</sub>, temperature, and relative humidity. The dashed lines indicate the benchmarks based on <a href="#buildings-14-02965-t005" class="html-table">Table 5</a>; the “single threshold” line corresponds to the second scoring system. The absence of dashed lines in a subplot indicates the lack of benchmarks for the combination of IAQ indicator and evaluation metric.</p>
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<p>Performance scores for the cluster of tested devices across various evaluation metrics. * Indicates that both MAE and MNB scores share the same column, where MAE scores apply to temperature and relative humidity, and MNB scores apply to <span class="html-italic">t</span>VOC, PM<sub>2.5</sub> and CO<sub>2</sub> concentrations.</p>
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<p>Posterior empirical cumulative density function (eCDF) distributions of specific error, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>δ</mi> </mrow> <mrow> <mi>x</mi> </mrow> </msub> </mrow> </semantics></math>, across the evaluated measurement devices (outliers excluded).</p>
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19 pages, 11112 KiB  
Case Report
Simulating the Natural Seasonal Ventilation of a Classroom in Poland Based on Measurements of the CO2 Concentration
by Katarzyna Nowak-Dzieszko, Maciej Mijakowski and Jarosław Müller
Energies 2024, 17(18), 4591; https://doi.org/10.3390/en17184591 - 13 Sep 2024
Viewed by 507
Abstract
There are many different factors affecting indoor air quality: environmental ones such as temperature, humidity, human activities within the building, smoking, cooking, and cleaning, but also external pollutants such as particulate matter, biological contaminants, and viruses or allergens. This study investigated the indoor [...] Read more.
There are many different factors affecting indoor air quality: environmental ones such as temperature, humidity, human activities within the building, smoking, cooking, and cleaning, but also external pollutants such as particulate matter, biological contaminants, and viruses or allergens. This study investigated the indoor air quality (IAQ) of a primary-school classroom in Cracow, Poland, based only on CO2 concentration levels exhaled by occupants. In the 1960s, over a thousand schools were built in Poland using similar technology. Most of them are still in use, and in many cases, modernization works are being carried out to improve their building envelope and the comfort of their use. The analyzed school is one of several hundred similar ones in southern Poland. Therefore, analyzing the possibilities of improving IAQ is an important topic, and the results can be used in the modernization process for many other buildings. Measurements indicated that the CO2 levels significantly exceeded acceptable standards, signaling poor air quality during usage time. This problem was connected mainly with the low efficiency of the natural ventilation system being used in the classroom. It is worth emphasizing that this type of ventilation system is the most commonly used ventilation solution in Polish schools. To address this problem, the classroom environment was simulated using CONTAM software, and the model was validated by comparing the simulated measurement data against the collected measurement data. Next, simulations for the entire heating season in Cracow were conducted, revealing that the IAQ remained consistently poor throughout this period. These findings highlight the persistent problem of inadequate ventilation in the classroom, which can have adverse effects on the health and performance of students and teachers. This article shows the usefulness of CONTAM for modeling not only gravity ventilation but also the window-opening process. The validated CONTAM model will be subsequently utilized to simulate annual IAQ conditions under various ventilation strategies in order to identify the most effective methods for maintaining acceptable IAQ while minimizing energy consumption. In our future analysis, the validated model will be used to test the following systems: demand-controlled ventilation (DCV), exhaust ventilation, and DCV/balanced ventilation with heat recovery. Full article
(This article belongs to the Section G: Energy and Buildings)
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<p>(<b>a</b>,<b>b</b>) East elevation of analyzed school building. (<b>c</b>) View of the classroom. (<b>d</b>) iBros remote sensor set measuring CO<sub>2</sub>, temperature and humidity.</p>
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<p>CO<sub>2</sub> concentration in the classroom on 4 January 2019.</p>
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<p>Average CO<sub>2</sub> concentration in the classroom on 1 February 2019 between 10:50 a.m. and 12:30 a.m., taken from 6 sensors. Two 45 min lessons with a break at 11:30–11:45—windows opened.</p>
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<p>CONTAM model of the classroom—screen from the program.</p>
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<p>The adjustment of CO<sub>2</sub> concentration in the classroom on 4 January 2021 to the simulation curve from CONTAM program (black line). Color lines represent data from different sensors.</p>
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<p>Density and distribution of probability for indoor CO<sub>2</sub> concentration error.</p>
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<p>Relation of CO<sub>2</sub> concentration between measurements and model calculations.</p>
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<p>Outdoor temperature profile for Cracow. Analyzed period of time between 1 November and 31 March.</p>
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<p>Wind speed profile for Cracow. Analyzed period of time between 1 November and 31 March.</p>
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<p>Changes in the indoor CO<sub>2</sub> concentration between 1 November and 31 March.</p>
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<p>(<b>a</b>) Changes in the indoor CO<sub>2</sub> concentration during five working days; (<b>b</b>) ventilation air flow during five working days; (<b>c</b>) changes in the indoor CO<sub>2</sub> concentration during one working day; (<b>d</b>) changes in the ventilation air flow during one working day.</p>
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<p>(<b>a</b>) Changes in the indoor CO<sub>2</sub> concentration during five working days; (<b>b</b>) ventilation air flow during five working days; (<b>c</b>) changes in the indoor CO<sub>2</sub> concentration during one working day; (<b>d</b>) changes in the ventilation air flow during one working day.</p>
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<p>(<b>a</b>) Ventilation air flow vs. outdoor temperature; (<b>b</b>) indoor CO<sub>2</sub> concentration vs. outdoor temperature; (<b>c</b>) ventilation air flow vs. indoor CO<sub>2</sub> concentration; (<b>d</b>) air heating power demand vs. outdoor temperature.</p>
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<p>Daily profile of concentrations for the working days in the analyzed period of time.</p>
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<p>Daily profile of the ventilation air flows for the working days in the analyzed period of time.</p>
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<p>Density and distribution of probability for indoor CO<sub>2</sub> concentration during occupied hours.</p>
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41 pages, 12863 KiB  
Review
Factors Affecting the Indoor Air Quality and Occupants’ Thermal Comfort in Urban Agglomeration Regions in the Hot and Humid Climate of Pakistan
by Muhammad Usama Haroon, Bertug Ozarisoy and Hasim Altan
Sustainability 2024, 16(17), 7869; https://doi.org/10.3390/su16177869 - 9 Sep 2024
Viewed by 1046
Abstract
The World Air Quality Index indicates that Pakistan ranks as the third most polluted country, regarding the average (Particulate Matter) PM2.5 concentration, which is 14.2 times higher than the World Health Organization’s annual air quality guideline. It is crucial to implement a [...] Read more.
The World Air Quality Index indicates that Pakistan ranks as the third most polluted country, regarding the average (Particulate Matter) PM2.5 concentration, which is 14.2 times higher than the World Health Organization’s annual air quality guideline. It is crucial to implement a program aimed at reducing PM2.5 levels in Pakistan’s urban areas. This review paper highlights the importance of indoor air pollution in urban regions such as Lahore, Faisalabad, Gujranwala, Rawalpindi, and Karachi, while also considering the effects of outdoor air temperature on occupants’ thermal comfort. The study aims to evaluate past methodological approaches to enhance indoor air quality in buildings. The main research question is to address whether there are statistical correlations between the PM2.5 and the operative air temperature and whether other indoor climatic variables have an impact on the thermal comfort assessment in densely built urban agglomeration regions in Pakistan. A systematic review analysis method was employed to investigate the effects of particulate matter (PM2.5), carbon oxides (COx), nitrogen oxides (NOx), sulfur oxides (SOx), and volatile organic compounds (VOCs) on residents’ health. The Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) protocol guided the identification of key terms and the extraction of cited studies. The literature review incorporated a combination of descriptive research methods to inform the research context regarding both ambient and indoor air quality, providing a theoretical and methodological framework for understanding air pollution and its mitigation in various global contexts. The study found a marginally significant relationship between the PM2.5 operative air temperature and occupants’ overall temperature satisfaction, Ordinal Regression (OR) = 0.958 (95%—Confidence Interval (CI) [0.918, 1.000]), p = 0.050, Nagelkerke − Regression (R2) = 0.042. The study contributes to research on the development of an evidence-based thermal comfort assessment benchmark criteria for the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Global Thermal Comfort Database version 2.1. Full article
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<p>Working schematic of pre-filters and HEPA filters [<a href="#B41-sustainability-16-07869" class="html-bibr">41</a>].</p>
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<p>Working schematic of multi-stage filtration system [<a href="#B43-sustainability-16-07869" class="html-bibr">43</a>].</p>
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<p>Air conditioning system active carbon filter [<a href="#B47-sustainability-16-07869" class="html-bibr">47</a>].</p>
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<p>Köppen–Geiger climate classification map, Lahore, Pakistan [<a href="#B52-sustainability-16-07869" class="html-bibr">52</a>].</p>
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<p>Flow design of conceptual framework. Drawn by author.</p>
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<p>(<b>a</b>) Input variables selected to complete the data mining process. (<b>b</b>) Missing patterns were excluded from the dataset.</p>
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<p>Dry bulb temperature during day- and night-time. Data source: <a href="https://clima.cbe.berkeley.edu" target="_blank">https://clima.cbe.berkeley.edu</a> (accessed on 25 March 2024).</p>
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<p>Bubble plot of age and relative humidity. Data source: <a href="https://repository.uel.ac.uk/item/8q774" target="_blank">https://repository.uel.ac.uk/item/8q774</a> (accessed on 25 March 2024).</p>
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<p>Yearly relative humidity chart for Lahore. Data source: <a href="https://clima.cbe.berkeley.edu" target="_blank">https://clima.cbe.berkeley.edu</a> (accessed on 25 March 2024).</p>
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<p>Psychometric chart. Data source: <a href="https://clima.cbe.berkeley.edu" target="_blank">https://clima.cbe.berkeley.edu</a> (accessed on 25 March 2024).</p>
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<p>Natural ventilation yearly bar Chart. Data source: <a href="https://clima.cbe.berkeley.edu" target="_blank">https://clima.cbe.berkeley.edu</a> (accesses on 25 March 2024).</p>
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<p>Universal thermal climate index (UTCI) heat stress map. Data source: <a href="https://clima.cbe.berkeley.edu" target="_blank">https://clima.cbe.berkeley.edu</a> (accesses on 25 March 2024).</p>
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<p>Bubble plot between length of residency and outdoor heat stress index. Data source: <a href="https://repository.uel.ac.uk/item/8q774" target="_blank">https://repository.uel.ac.uk/item/8q774</a> (accessed on 25 March 2024).</p>
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<p>Forest plot of outdoor air temperature and thermal sensation vote of occupants. Data source: <a href="https://repository.uel.ac.uk/item/8q774" target="_blank">https://repository.uel.ac.uk/item/8q774</a> (accessed on 25 March 2024).</p>
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<p>Boxplot for the distribution of indoor air temperature. Data source: <a href="https://cbe-berkeley.shinyapps.io/comfortdatabase/" target="_blank">https://cbe-berkeley.shinyapps.io/comfortdatabase/</a> (accessed on 25 March 2024).</p>
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<p>Boxplot for the distribution of PMV values. Data source: <a href="https://cbe-berkeley.shinyapps.io/comfortdatabase/" target="_blank">https://cbe-berkeley.shinyapps.io/comfortdatabase/</a> (accessed on 25 March 2024).</p>
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<p>Scatter plot relationship between PMV and indoor air temperature. Data source: <a href="https://cbe-berkeley.shinyapps.io/comfortdatabase/" target="_blank">https://cbe-berkeley.shinyapps.io/comfortdatabase/</a> (accessed on 25 March 2024).</p>
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<p>Scatter plot relationship between TSV and indoor air temperature. Data source: <a href="https://cbe-berkeley.shinyapps.io/comfortdatabase/" target="_blank">https://cbe-berkeley.shinyapps.io/comfortdatabase/</a> (accessed on 25 March 2024).</p>
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<p>ASHRAE thermal comfort adaptive model between indoor radiant temperature and monthly mean outdoor temperature. Data source: <a href="https://cbe-berkeley.shinyapps.io/comfortdatabase/" target="_blank">https://cbe-berkeley.shinyapps.io/comfortdatabase/</a> (accessed on 25 March 2024).</p>
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<p>Satisfaction graph between PMV and percentage dissatisfied. Data source: <a href="https://cbe-berkeley.shinyapps.io/comfortdatabase/" target="_blank">https://cbe-berkeley.shinyapps.io/comfortdatabase/</a> (accessed on 25 March 2024).</p>
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<p>(<b>a</b>) Skewness and kurtosis of in situ recorded indoor relative humidity (RH); (<b>b</b>) histogram of indoor RH; (<b>c</b>) normality analysis of indoor RH; (<b>d</b>) whisker graph of indoor RH.</p>
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<p>(<b>a</b>) Skewness and kurtosis of in situ recorded operative air temperature; (<b>b</b>) histogram of operative air temperature; (<b>c</b>) normality analysis of operative air temperature; (<b>d</b>) whisker graph of operative air temperature.</p>
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<p>(<b>a</b>) Skewness and kurtosis of in situ recorded operative air temperature; (<b>b</b>) histogram of operative air temperature; (<b>c</b>) normality analysis of operative air temperature; (<b>d</b>) whisker graph of operative air temperature.</p>
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20 pages, 5317 KiB  
Article
Indoor Air Quality Management in Dubai: Assessing the Efficacy of Air Purifiers, Photocatalysts, and Window Ventilation in Reducing HCHO
by Chuloh Jung and Shams Mohammed Alshamasi
Buildings 2024, 14(9), 2815; https://doi.org/10.3390/buildings14092815 - 7 Sep 2024
Viewed by 686
Abstract
This study investigates the characteristics of formaldehyde (HCHO) concentration and its reduction in newly constructed apartment buildings in Dubai. It addresses the significant health risks of high HCHO levels due to poor ventilation and extensive use of VOC-emitting materials. The research explores the [...] Read more.
This study investigates the characteristics of formaldehyde (HCHO) concentration and its reduction in newly constructed apartment buildings in Dubai. It addresses the significant health risks of high HCHO levels due to poor ventilation and extensive use of VOC-emitting materials. The research explores the effectiveness of various mitigation strategies, including air purifiers, photocatalyst applications, and window ventilation, in the living room, master bedroom (MBR), Room 1, and Room 2. HCHO concentrations were measured under different conditions: sealed windows, operation of an air purifier with a VOCs filter, and the application of a photocatalyst. The study followed a quantitative approach, recording real-time HCHO levels over 24 h. Results indicated that sealing windows led to HCHO concentrations surpassing the domestic standard of 0.1 ppm, with the MBR recording the highest concentration at 0.73 ppm. The air purifier showed minimal impact within the first 8 h but achieved an 18% reduction after 24 h of operation. Applying a photocatalyst to room surfaces resulted in a 50% reduction in HCHO levels. Ventilation through window openings significantly improved air exchange rates, with the air exchange per hour (ACH) increasing proportionally with window opening size. Smaller rooms with larger window-to-volume ratios, such as Room 1 and Room 2, maintained HCHO concentrations below the WHO standard of 0.1 ppm with partial window openings. The study concludes that window ventilation is the most effective strategy for reducing HCHO concentrations, highlighting the importance of integrating comprehensive ventilation designs in modern residential buildings to ensure healthier indoor environments in Dubai. Full article
(This article belongs to the Special Issue Indoor Environmental Quality and Human Wellbeing)
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<p>City Walk Residences by Meraas.</p>
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<p>Master Plan of City Walk Residences by Meraas.</p>
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<p>Concentration Measurement and Window Opening Locations.</p>
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<p>HCHO Concentration in Each Room when Window Closed.</p>
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<p>HCHO Concentration before and after Operating the Air Purifier.</p>
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<p>HCHO Concentration before and after Photocatalyst Construction of MBR.</p>
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<p>HCHO Concentration before and after Photocatalyst Construction of Room 2.</p>
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<p>MBR Ventilation Frequency According to Window Opening Conditions.</p>
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<p>HCHO Concentration according to Open Windows in Living Room.</p>
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<p>HCHO Concentration according to Open Windows in Master Bedroom.</p>
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<p>Indoor and Outdoor Temperature Change.</p>
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<p>Relationship between HCHO Concentration and Temperature and Humidity.</p>
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21 pages, 9247 KiB  
Article
Built-In Environmental Construction Mechanism and Sustainable Renewal Strategies of Traditional Qiang Dwellings in Western China
by Menglong Zhang, Yufei He, Liangzhen Huang, Ran Xiong and Yin Zhang
Sustainability 2024, 16(16), 7122; https://doi.org/10.3390/su16167122 - 19 Aug 2024
Viewed by 704
Abstract
Indoor air quality (IAQ) has a significant impact on human health, as people spend 90% of their time in various indoor environments. Therefore, research on IAQ is extremely necessary. However, current research on traditional Qiang residences in western Sichuan mainly focuses on the [...] Read more.
Indoor air quality (IAQ) has a significant impact on human health, as people spend 90% of their time in various indoor environments. Therefore, research on IAQ is extremely necessary. However, current research on traditional Qiang residences in western Sichuan mainly focuses on the indoor thermal environment and heritage protection, with relatively little attention paid to IAQ. This study investigates the IAQ of traditional Qiang residences in western Sichuan, which have open fire pits as the core of daily life, exploring the impact of passive renovation strategies on the indoor air quality. Using simulation methods, this study employs passive strategies, such as increasing the size of windward windows, changing ventilation methods, relocating the fire pit, and enlarging interior partition openings, to improve and optimize the IAQ through natural ventilation. The results show that when the windward window sizes are 0.8 m × 1.9 m and 0.7 m × 1.55 m, the reduction in the indoor CO2 concentration is the greatest, with a maximum decrease of 0.024% at the 1.5 m plane. This paper proposes passive renovation strategies to improve the indoor air quality of Qiang residences in western Sichuan. These strategies effectively enhance the indoor air quality of Qiang residences and address the research gap on indoor air quality in regional Qiang residences in western Sichuan. The insights and methods presented contribute to the improvement of the indoor air quality in traditional buildings and support the sustainable development of traditional architecture. Full article
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<p>Geographical information location map.</p>
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<p>Summer climate infographic: (<b>a</b>) summer temperatures; (<b>b</b>) wind rose chart.</p>
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<p>Schematic diagram of Qiang dwellings in cross-section.</p>
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<p>Partial construction plan of Qiang dwellings: (<b>a</b>) roof construction; (<b>b</b>) wall construction.</p>
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<p>(<b>a</b>) Fire pit location; (<b>b</b>) schematic diagram of the fire pit.</p>
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<p>Status and floor plan of the residence. (<b>a</b>) Current status of residential buildings. (<b>b</b>) Functional diagram. (The floor plan in the figure was surveyed and drawn by the author).</p>
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<p>Computational domain of outdoor wind field.</p>
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<p>Indoor CO<sub>2</sub> concentrations under extreme conditions without any windows or doors.</p>
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<p>Indoor CO<sub>2</sub> concentrations with different window-to-wall ratios on the windward side.</p>
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<p>Indoor CO<sub>2</sub> concentrations under different ventilation methods.</p>
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<p>Indoor CO<sub>2</sub> concentrations at different fire pit locations.</p>
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<p>Indoor CO<sub>2</sub> concentrations with different interior partition openings.</p>
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11 pages, 238 KiB  
Article
Assessment of Perceived Indoor Air Quality in the Classrooms of Slovenian Primary Schools and Its Association with Indoor Air Quality Factors, for the Design of Public Health Interventions
by An Galičič, Jan Rožanec, Andreja Kukec, Sašo Medved and Ivan Eržen
Atmosphere 2024, 15(8), 995; https://doi.org/10.3390/atmos15080995 - 19 Aug 2024
Viewed by 578
Abstract
From a public health perspective, it is necessary to improve indoor air quality (IAQ) in schools. This study aims to assess the state of perceived IAQ in Slovenian school classrooms and its association with the selected IAQ factors to improve the understanding of [...] Read more.
From a public health perspective, it is necessary to improve indoor air quality (IAQ) in schools. This study aims to assess the state of perceived IAQ in Slovenian school classrooms and its association with the selected IAQ factors to improve the understanding of perceived IAQ for designing public health interventions aimed to improve IAQ in schools. A national cross-sectional study was performed in all 454 Slovenian primary schools in the school year 2019/2020. The questionnaires were filled out by the 3rd-grade teachers with the support of the caretakers. Teachers rated the IAQ in the classroom as the worst in winter. We found that the teachers’ perceived IAQ in the classroom is statistically significantly associated with the micro location of the school and some of the IAQ factors. Poor IAQ is associated with reduced manual airing of classrooms due to the thermal comfort of the occupants. Interventions should be aimed at improving occupants’ adaptive behaviors to increase the frequency of natural ventilation in classrooms. Full article
(This article belongs to the Special Issue Health Impacts Related to Indoor Air Pollutants)
13 pages, 2181 KiB  
Article
Relative Health Risk Reduction from an Advanced Multi-Modal Air Purification System: Evaluation in a Post-Surgical Healthcare Setting
by Dino Pisaniello and Monika Nitschke
Int. J. Environ. Res. Public Health 2024, 21(8), 1089; https://doi.org/10.3390/ijerph21081089 - 17 Aug 2024
Viewed by 836
Abstract
Advanced air treatment systems have the potential to reduce airborne infection risk, improve indoor air quality (IAQ) and reduce energy consumption, but few studies reported practical implementation and performance. PlasmaShield®, an advanced multi-modal HVAC-integrated system, was directly compared with a standard [...] Read more.
Advanced air treatment systems have the potential to reduce airborne infection risk, improve indoor air quality (IAQ) and reduce energy consumption, but few studies reported practical implementation and performance. PlasmaShield®, an advanced multi-modal HVAC-integrated system, was directly compared with a standard MERV-13 system in a post-surgical paediatric healthcare setting. The evaluation entailed monitoring of multi-size airborne particles, bioaerosols and key IAQ parameters. Measurements were taken for outside air, supply air and air in the occupied space for 3 days prior to, and after, the installation of the PlasmaShield system. Compared with the existing arrangement, very significant reductions in particle number concentrations were observed in the occupied space, especially with virus-like submicron particles. Significant reductions in airborne culturable bacteria and fungi were observed in the supply air, with more modest reductions in the occupied space. In the case of virus-like particles, there was an eight-fold improvement in equivalent clean air, suggesting a five-fold infection risk reduction for long-range exposure. The data suggest multiple benefits of airborne particle and bioaerosol reduction, with applications beyond healthcare. Long-term studies are recommended to confirm the combined IAQ, health and energy benefits. Full article
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<p>Ventilation layout of the recovery suite with air sampling locations 1–3: outdoor air, supply air and recovery suite room air.</p>
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<p>Six PlasmaShield units located in the air handling unit air mixing plenum.</p>
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<p>Box and whisker plot of the distribution of VLP particles (count per m<sup>3</sup>) in the recovery room pre- and post-intervention.</p>
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<p>Box and whisker plot of the distribution of BLP-sized particles (count per m<sup>3</sup>) in the recovery room pre- and post-intervention.</p>
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<p>The Wells–Riley equation, highlighting the infection risk relationship with the room ventilation rate.</p>
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19 pages, 891 KiB  
Article
Indoor Environmental Quality and Effectiveness of Portable Air Cleaners in Reducing Levels of Airborne Particles during Schools’ Reopening in the COVID-19 Pandemic
by Florentina Villanueva, Fátima Felgueiras, Alberto Notario, Beatriz Cabañas and Marta Fonseca Gabriel
Sustainability 2024, 16(15), 6549; https://doi.org/10.3390/su16156549 - 31 Jul 2024
Viewed by 944
Abstract
Educational buildings tend to fail in the contagion containment of airborne infectious diseases because of the high number of children, for several hours a day, inside enclosed environments that often have inadequate indoor air quality (IAQ) conditions. This study aimed to assess indoor [...] Read more.
Educational buildings tend to fail in the contagion containment of airborne infectious diseases because of the high number of children, for several hours a day, inside enclosed environments that often have inadequate indoor air quality (IAQ) conditions. This study aimed to assess indoor environmental quality and test the effectiveness of portable air cleaners (PACs) in alleviating airborne particle levels in schools of Central–Southern Spain during the period of reopening after the lockdown due to the COVID-19 outbreak. To accomplish this, three sampling campaigns were organized from September to December 2020 to consistently monitor temperature and relative humidity, carbon dioxide, and particulate matter in nineteen classrooms (seven school buildings). Results showed that although the recommendation of maintaining the windows open throughout the day seemed to be effective in promoting, in general, proper ventilation conditions (based on CO2 levels). For the colder campaigns, this practice caused notorious thermal comfort impairment. In addition, a great number of the surveyed classrooms presented levels of PM2.5 and PM10, attributable to outdoor and indoor sources, which exceeded the current WHO guideline values. Moreover, considering the practice of having the windows opened, the installation of 1 unit of PACs per classroom was insufficient to ensure a reduction in particle concentration to safe levels. Importantly, it was also found that children of different ages at different education levels can be exposed to significantly different environmental conditions in their classrooms; thus, the corrective measures to employ in each individual educational setting should reflect the features and needs of the target space/building. Full article
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<p>Boxplots represent the levels of each air parameter measured in the 7 school buildings surveyed in the 3 monitoring campaigns. The bottom and the top of the boxes represent the 25th and 75th percentiles. The band near the middle of the box and the X represent the median and the mean values, respectively. The ends of the whiskers indicate 10th and 90th percentiles. Dashed lines represent relevant limit values applicable to CO<sub>2</sub> (limit values recommended before (1000 ppm) and during COVID-19 pandemic (700 ppm), PM<sub>2.5</sub> and PM<sub>10</sub> (15 and 45 μg/m<sup>3</sup>, repectively, in accordance with WHO guidelines).</p>
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<p>Boxplots representing the airborne particulate concentrations measured in the classrooms in which a portable air cleaner (PAC) was installed, discriminating the levels assessed in the sampling campaign(s) conducted before and after the installation of PACs (outliers not shown).</p>
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24 pages, 3462 KiB  
Systematic Review
Cost-Related Drivers and Barriers of Passivhaus: A Systematic Literature Review
by Kajavathani Panchalingam, Eziaku Onyeizu Rasheed and James Olabode Bamidele Rotimi
Sustainability 2024, 16(15), 6510; https://doi.org/10.3390/su16156510 - 30 Jul 2024
Viewed by 917
Abstract
Passivhaus (PH) has gained global recognition for its energy-efficient features despite a 5% to 10% higher construction cost than traditional houses, especially within European countries. However, its adoption and popularity have not met the same fate in other countries like New Zealand. The [...] Read more.
Passivhaus (PH) has gained global recognition for its energy-efficient features despite a 5% to 10% higher construction cost than traditional houses, especially within European countries. However, its adoption and popularity have not met the same fate in other countries like New Zealand. The higher upfront cost has been critical to the slow adoption of the PH movement in New Zealand. This study aimed to demystify the mist around the cost of PHs with a focus on the effects of drivers and barriers on their life cycle costs (LCCs). As such, a systematic literature review was conducted to provide a comprehensive understanding of the cost implications associated with PH. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) review method, we examined 71 past studies on PHs from 2005 to 2023. We found that the drivers of PHs include reduced heating demand, increased thermal comfort, and indoor air quality (IAQ). Research showed that the rising market for PHs is fueled by climate change, environmental awareness, innovative materials and technologies, individual commitment, improved regulations, pilot studies, research efforts, and governmental funding and initiatives. However, PHs face significant challenges such as increased complexity, advanced technology, higher initial investments compared to conventional and low-energy houses, national requirements, overheating, difficulties in affording the technologies, and a lack of options in the market. Despite the wealth of research on the economic aspects of PH, there is a lack of in-depth studies exploring the LCC of PHs focusing on cost commitments and benefits. Such studies are essential for assessing and optimising the cost-effectiveness of PH, considering different climates and regions, and comparing them with other low energy standards. The findings of our review provide a crucial focus for PH stakeholders in assessing the long-term financial viability of PH projects, thereby improving decision-making and facilitating effective planning for sustainable and cost-effective housing. Full article
(This article belongs to the Section Green Building)
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<p>Selection criteria for the literature review using the PRISMA review process (adapted from [<a href="#B39-sustainability-16-06510" class="html-bibr">39</a>]).</p>
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<p>Keyword cloud illustrating major themes in past studies on PHs.</p>
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<p>The network between keywords of the selected papers.</p>
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<p>Thematic diagram showing the basic themes under global PH research.</p>
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<p>SankeyMATIC diagram of cost-related drivers and barriers to PH adoption. ↑—Increase; ↓—Decrease.</p>
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