On the potential of demand-controlled ventilation system to enhance indoor air quality and thermal condition in Australian school classrooms

Haddad, Shamila; Synnefa, Afroditi; Padilla-Marcos, Miguel Ángel; Paolini, Riccardo; Delrue, Steven; Prasad, Deo; Santamouris, M.

doi:10.1016/j.enbuild.2021.110838

Cited by 57 publications

(22 citation statements)

References 86 publications

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“…However, for a poorly-designed air conditioning system without sufficient ventilation air and uniform air diffuser locations, the effect of barrier height in reducing the infection rate remains to be verified. Moreover, it is essential to integrate these prevention strategies (such as physical barriers) with related control techniques, such as multi-mode ventilation system (Shao et al 2017), intelligent and online monitoring of air condition systems (Cao and Ren 2018), demand-controlled supply air devices (Haddad et al 2021). The design of physical barriers or air conditioning systems (including supply air openings and pipelines)…”

Section: Discussionmentioning

confidence: 99%

Mitigating COVID-19 infection disease transmission in indoor environment using physical barriers

Ren

Wang

et al. 2021

Sustainable Cities and Society

100

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During the normalized phase of COVID-19, droplets or aerosol particles produced by infected personnel are considered as the potential source of infection with uncertain exposure risk. As such, in densely populated open spaces, it is necessary to adopt strategies to mitigate the risk of infection disease transmission while providing sufficient ventilation air. An example of such strategies is use of physical barriers. In this study, the impact of barrier heights on the spread of aerosol particles is investigated in an open office environment with the well-designed ventilation mode and supply air rate. The risk of infection disease transmission is evaluated using simulation of particle concentration in different locations and subject to a number of source scenarios. It was found that a barrier height of at least 60cm above the desk surface is needed to effectively prevent the transmission of viruses. For workstations within 4m from the outlet, a 70cm height is considered, and with a proper ventilation mode, it is shown that the barriers can reduce the risk of infection by 72%. However, for the workstations further away from the outlet (beyond 4m), the effect of physical barrier cannot be that significant. In summary, this study provides a theoretical analysis for implementing physical barriers, as a low-cost mitigation strategy, subject to various height scenarios and investigation of their effectiveness in reducing the infection transmission probability.

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Section: Discussionmentioning

confidence: 99%

Mitigating COVID-19 infection disease transmission in indoor environment using physical barriers

Ren

Wang

et al. 2021

Sustainable Cities and Society

100

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“…In this study, we concentrated on VOCs with a high-to-medium vapor pressure including the carcinogens formaldehyde and benzene, which are considered as two of the most toxic substances in indoor air with guideline threshold values in the low ppb range according to the WHO [11]. Therefore, comprehensive VOC monitoring is required to provide a universal indicator for IAQ, e.g., as a basis for demand-controlled ventilation to reduce the overall burden on people [12].…”

Section: Introductionmentioning

confidence: 99%

High-Performance VOC Quantification for IAQ Monitoring Using Advanced Sensor Systems and Deep Learning

et al. 2021

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With air quality being one target in the sustainable development goals set by the United Nations, accurate monitoring also of indoor air quality is more important than ever. Chemiresistive gas sensors are an inexpensive and promising solution for the monitoring of volatile organic compounds, which are of high concern indoors. To fully exploit the potential of these sensors, advanced operating modes, calibration, and data evaluation methods are required. This contribution outlines a systematic approach based on dynamic operation (temperature-cycled operation), randomized calibration (Latin hypercube sampling), and the use of advances in deep neural networks originally developed for natural language processing and computer vision, applying this approach to volatile organic compound measurements for indoor air quality monitoring. This paper discusses the pros and cons of deep neural networks for volatile organic compound monitoring in a laboratory environment by comparing the quantification accuracy of state-of-the-art data evaluation methods with a 10-layer deep convolutional neural network (TCOCNN). The overall performance of both methods was compared for complex gas mixtures with several volatile organic compounds, as well as interfering gases and changing ambient humidity in a comprehensive lab evaluation. Furthermore, both were tested under realistic conditions in the field with additional release tests of volatile organic compounds. The results obtained during field testing were compared with analytical measurements, namely the gold standard gas chromatography mass spectrometry analysis based on Tenax sampling, as well as two mobile systems, a gas chromatograph with photo-ionization detection for volatile organic compound monitoring and a gas chromatograph with a reducing compound photometer for the monitoring of hydrogen. The results showed that the TCOCNN outperforms state-of-the-art data evaluation methods, for example for critical pollutants such as formaldehyde, achieving an uncertainty of around 11 ppb even in complex mixtures, and offers a more robust volatile organic compound quantification in a laboratory environment, as well as in real ambient air for most targets.

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“…They evaluated CO 2 , VOCs, and Particle Matter (PM) to see the effect of improving indoor air quality [15]. As a slightly advanced example, Haddad S. et al investigated Demand Control Ventilation (DCV) with natural ventilation in a warm climate zone in Australia and reported the improvement of the indoor environment [16]. The above studies were conducted in temperate climates.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Indoor Environment and Energy Consumption before and after Spread of COVID-19 in Schools in Japanese Cold-Climate Region

et al. 2022

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A report released by the WHO indicates that aerosols from infected people are one of the major sources of the spread of COVID-19. Therefore, as the COVID-19 infection caused by the SARS-CoV-2 virus spreads, it has become necessary to reconsider the design and operation of buildings. Inside school buildings in cold regions, not only is it not easy to increase ventilation during the winter, but it may also be difficult for students to attend classes while wearing masks during the summer because such buildings are not equipped with air-conditioning systems. In short, school buildings in cold climates have more problems than those in warm climates. We report on the results of indoor environmental measurement using our developed CO2-concentration meters, a questionnaire survey on students’ feeling of being hot or cold (i.e., ‘thermal sensation’), and a comparison of energy consumption before and after the spread of COVID-19 infection in schools in Sapporo, Japan, a cold-climate area. The results indicate that (1) more than 70% of the students participated in window ventilation by the CO2 meter, and (2) a relatively good indoor environment was maintained through the efforts of teachers and students. However, we also found that (1) 90% of the students felt hot in summer and (2) 40% felt cold in winter, (3) energy efficiency worsened by 7% due to increased ventilation, and (4) air quality was not as clean as desired during the coldest months of the year. Therefore, investment in insulation and air conditioning systems for school buildings is needed.

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On the potential of demand-controlled ventilation system to enhance indoor air quality and thermal condition in Australian school classrooms

Cited by 57 publications

References 86 publications

Mitigating COVID-19 infection disease transmission in indoor environment using physical barriers

Mitigating COVID-19 infection disease transmission in indoor environment using physical barriers

High-Performance VOC Quantification for IAQ Monitoring Using Advanced Sensor Systems and Deep Learning

Comparison of Indoor Environment and Energy Consumption before and after Spread of COVID-19 in Schools in Japanese Cold-Climate Region

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