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Alqarni Z, Rezgui Y, Petri I, Ghoroghi A. Viral infection transmission and indoor air quality: A systematic review. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 923:171308. [PMID: 38432379 DOI: 10.1016/j.scitotenv.2024.171308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/03/2024] [Accepted: 02/25/2024] [Indexed: 03/05/2024]
Abstract
Respiratory disease transmission in indoor environments presents persistent challenges for health authorities, as exemplified by the recent COVID-19 pandemic. This underscores the urgent necessity to investigate the dynamics of viral infection transmission within indoor environments. This systematic review delves into the methodologies of respiratory infection transmission in indoor settings and explores how the quality of indoor air (IAQ) can be controlled to alleviate this risk while considering the imperative of sustainability. Among the 2722 articles reviewed, 178 were retained based on their focus on respiratory viral infection transmission and IAQ. Fifty eight articles delved into SARS-CoV-2 transmission, 21 papers evaluated IAQ in contexts of other pandemics, 53 papers assessed IAQ during the SARS-CoV-2 pandemic, and 46 papers examined control strategies to mitigate infectious transmission. Furthermore, of the 46 papers investigating control strategies, only nine considered energy consumption. These findings highlight clear gaps in current research, such as analyzing indoor air and surface samples for specific indoor environments, oversight of indoor and outdoor parameters (e.g., temperature, relative humidity (RH), and building orientation), neglect of occupancy schedules, and the absence of considerations for energy consumption while enhancing IAQ. This study distinctly identifies the indoor environmental conditions conducive to the thriving of each respiratory virus, offering IAQ trade-offs to mitigate the risk of dominant viruses at any given time. This study argues that future research should involve digital twins in conjunction with machine learning (ML) techniques. This approach aims to enhance IAQ by analyzing the transmission patterns of various respiratory viruses while considering energy consumption.
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Affiliation(s)
- Zahi Alqarni
- School of Engineering, Cardiff University, Cardiff CF24 3AA, UK; School of Computer Science, King Khalid University, Abha 62529, Saudi Arabia.
| | - Yacine Rezgui
- School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
| | - Ioan Petri
- School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
| | - Ali Ghoroghi
- School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
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Durán Del Amor MDM, Baeza Caracena A, Esquembre F, Llorens Pascual Del Riquelme M. New Methodology to Evaluate and Optimize Indoor Ventilation Based on Rapid Response Sensors. SENSORS (BASEL, SWITZERLAND) 2024; 24:1657. [PMID: 38475193 DOI: 10.3390/s24051657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 02/24/2024] [Accepted: 02/28/2024] [Indexed: 03/14/2024]
Abstract
The recent pandemic increased attention to the need for appropriated ventilation and good air quality as efficient measures to achieve safe and healthy indoor air. This work provides a novel methodology for continuously evaluating ventilation in public areas using modern rapid response sensors (RRS). This methodology innovatively assesses the ventilation of a space by combining a quantitative estimation of the real air exchange in the space-obtained from CO2 experimental RRS measurements and the characteristics of and activity in the space-and indoor and outdoor RRS measurements of other pollutants, with healthy recommendations from different organisations. The methodology allows space managers to easily evaluate, in a continuous form, the appropriateness of their ventilation strategy, thanks to modern RRS measurements and direct calculations (implemented here in a web app), even in situations of full activity. The methodology improves on the existing standards, which imply the release of tracer gases and expert intervention, and could also be used to set a control system that measures continuously and adapts the ventilation to changes in indoor occupancy and activity, guaranteeing safe and healthy air in an energy-efficient way. Sample public concurrence spaces with different conditions are used to illustrate the methodology.
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Affiliation(s)
- María Del Mar Durán Del Amor
- Department of Chemical Engineering, Faculty of Chemistry, Campus de Espinardo, University of Murcia, 30100 Murcia, Spain
| | - Antonia Baeza Caracena
- Department of Chemical Engineering, Faculty of Chemistry, Campus de Espinardo, University of Murcia, 30100 Murcia, Spain
| | - Francisco Esquembre
- Department of Mathematics, Faculty of Mathematics, Campus de Espinardo, University of Murcia, 30100 Murcia, Spain
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Zhang Y, Shankar SN, Vass WB, Lednicky JA, Fan ZH, Agdas D, Makuch R, Wu CY. Air Change Rate and SARS-CoV-2 Exposure in Hospitals and Residences: A Meta-Analysis. AEROSOL SCIENCE AND TECHNOLOGY : THE JOURNAL OF THE AMERICAN ASSOCIATION FOR AEROSOL RESEARCH 2024; 58:217-243. [PMID: 38764553 PMCID: PMC11101186 DOI: 10.1080/02786826.2024.2312178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 01/16/2024] [Indexed: 05/21/2024]
Abstract
As SARS-CoV-2 swept across the globe, increased ventilation and implementation of air cleaning were emphasized by the US CDC and WHO as important strategies to reduce the risk of inhalation exposure to the virus. To assess whether higher ventilation and air cleaning rates lead to lower exposure risk to SARS-CoV-2, 1274 manuscripts published between April 2020 and September 2022 were screened using key words "airborne SARS-CoV-2 or "SARS-CoV-2 aerosol". Ninety-three studies involved air sampling at locations with known sources (hospitals and residences) were selected and associated data were compiled. Two metrics were used to assess exposure risk: SARS-CoV-2 concentration and SARS-CoV-2 detection rate in air samples. Locations were categorized by type (hospital or residence) and proximity to the sampling location housing the isolated/quarantined patient (primary or secondary). The results showed that hospital wards had lower airborne virus concentrations than residential isolation rooms. A negative correlation was found between airborne virus concentrations in primary-occupancy areas and air changes per hour (ACH). In hospital settings, sample positivity rates were significantly reduced in secondary-occupancy areas compared to primary-occupancy areas, but they were similar across sampling locations in residential settings. ACH and sample positivity rates were negatively correlated, though the effect was diminished when ACH values exceeded 8. While limitations associated with diverse sampling protocols exist, data considered by this meta-analysis support the notion that higher ACH may reduce exposure risks to the virus in ambient air.
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Affiliation(s)
- Yuetong Zhang
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA
- Department of Mechanical Engineering, University of British Columbia, Vancouver, British Columnia, Canada
| | - Sripriya Nannu Shankar
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA
- Department of Environmental & Public Health Sciences, University of Cincinnati, Cincinnati, Ohio, USA
| | - William B. Vass
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA
| | - John A. Lednicky
- Department of Environmental and Global Health, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Z. Hugh Fan
- Mechanical and Aerospace Engineering, University of Florida, Gainesville, Florida, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA
| | - Duzgun Agdas
- Engineering School of Sustainable Infrastructure & Environment, University of Florida, Gainesville, Florida, USA
| | - Robert Makuch
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA
| | - Chang-Yu Wu
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, Florida, USA
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Qiu G, Zhang X, deMello AJ, Yao M, Cao J, Wang J. On-site airborne pathogen detection for infection risk mitigation. Chem Soc Rev 2023; 52:8531-8579. [PMID: 37882143 PMCID: PMC10712221 DOI: 10.1039/d3cs00417a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Indexed: 10/27/2023]
Abstract
Human-infecting pathogens that transmit through the air pose a significant threat to public health. As a prominent instance, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the COVID-19 pandemic has affected the world in an unprecedented manner over the past few years. Despite the dissipating pandemic gloom, the lessons we have learned in dealing with pathogen-laden aerosols should be thoroughly reviewed because the airborne transmission risk may have been grossly underestimated. From a bioanalytical chemistry perspective, on-site airborne pathogen detection can be an effective non-pharmaceutic intervention (NPI) strategy, with on-site airborne pathogen detection and early-stage infection risk evaluation reducing the spread of disease and enabling life-saving decisions to be made. In light of this, we summarize the recent advances in highly efficient pathogen-laden aerosol sampling approaches, bioanalytical sensing technologies, and the prospects for airborne pathogen exposure measurement and evidence-based transmission interventions. We also discuss open challenges facing general bioaerosols detection, such as handling complex aerosol samples, improving sensitivity for airborne pathogen quantification, and establishing a risk assessment system with high spatiotemporal resolution for mitigating airborne transmission risks. This review provides a multidisciplinary outlook for future opportunities to improve the on-site airborne pathogen detection techniques, thereby enhancing the preparedness for more on-site bioaerosols measurement scenarios, such as monitoring high-risk pathogens on airplanes, weaponized pathogen aerosols, influenza variants at the workplace, and pollutant correlated with sick building syndromes.
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Affiliation(s)
- Guangyu Qiu
- Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
- Institute of Environmental Engineering, ETH Zürich, Zürich 8093, Switzerland
- Laboratory for Advanced Analytical Technologies, Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf 8600, Switzerland
| | - Xiaole Zhang
- Institute of Environmental Engineering, ETH Zürich, Zürich 8093, Switzerland
- Laboratory for Advanced Analytical Technologies, Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf 8600, Switzerland
| | - Andrew J deMello
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg1, Zürich, Switzerland
| | - Maosheng Yao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, China
| | - Junji Cao
- Institute of Atmospheric Physics, Chinese Academy of Science, China
| | - Jing Wang
- Institute of Environmental Engineering, ETH Zürich, Zürich 8093, Switzerland
- Laboratory for Advanced Analytical Technologies, Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf 8600, Switzerland
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Du B, Siegel JA. Estimating Indoor Pollutant Loss Using Mass Balances and Unsupervised Clustering to Recognize Decays. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023. [PMID: 37378593 DOI: 10.1021/acs.est.3c00756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
Low-cost air quality monitors are increasingly being deployed in various indoor environments. However, data of high temporal resolution from those sensors are often summarized into a single mean value, with information about pollutant dynamics discarded. Further, low-cost sensors often suffer from limitations such as a lack of absolute accuracy and drift over time. There is a growing interest in utilizing data science and machine learning techniques to overcome those limitations and take full advantage of low-cost sensors. In this study, we developed an unsupervised machine learning model for automatically recognizing decay periods from concentration time series data and estimating pollutant loss rates. The model uses k-means and DBSCAN clustering to extract decays and then mass balance equations to estimate loss rates. Applications on data collected from various environments suggest that the CO2 loss rate was consistently lower than the PM2.5 loss rate in the same environment, while both varied spatially and temporally. Further, detailed protocols were established to select optimal model hyperparameters and filter out results with high uncertainty. Overall, this model provides a novel solution to monitoring pollutant removal rates with potentially wide applications such as evaluating filtration and ventilation and characterizing indoor emission sources.
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Affiliation(s)
- Bowen Du
- Department of Civil and Mineral Engineering, University of Toronto, Toronto, Canada M5S 1A4
- School of Architecture, Civil and Environmental Engineering, École Polytechnique Fedérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jeffrey A Siegel
- Department of Civil and Mineral Engineering, University of Toronto, Toronto, Canada M5S 1A4
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada M5T 1R4
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Wiryasaputra R, Huang CY, Kristiani E, Liu PY, Yeh TK, Yang CT. Review of an intelligent indoor environment monitoring and management system for COVID-19 risk mitigation. Front Public Health 2023; 10:1022055. [PMID: 36703846 PMCID: PMC9871550 DOI: 10.3389/fpubh.2022.1022055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 12/23/2022] [Indexed: 01/12/2023] Open
Abstract
The coronavirus disease (COVID-19) outbreak has turned the world upside down bringing about a massive impact on society due to enforced measures such as the curtailment of personal travel and limitations on economic activities. The global pandemic resulted in numerous people spending their time at home, working, and learning from home hence exposing them to air contaminants of outdoor and indoor origins. COVID-19 is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which spreads by airborne transmission. The viruses found indoors are linked to the building's ventilation system quality. The ventilation flow in an indoor environment controls the movement and advection of any aerosols, pollutants, and Carbon Dioxide (CO2) created by indoor sources/occupants; the quantity of CO2 can be measured by sensors. Indoor CO2 monitoring is a technique used to track a person's COVID-19 risk, but high or low CO2 levels do not necessarily mean that the COVID-19 virus is present in the air. CO2 monitors, in short, can help inform an individual whether they are breathing in clean air. In terms of COVID-19 risk mitigation strategies, intelligent indoor monitoring systems use various sensors that are available in the marketplace. This work presents a review of scientific articles that influence intelligent monitoring development and indoor environmental quality management system. The paper underlines that the non-dispersive infrared (NDIR) sensor and ESP8266 microcontroller support the development of low-cost indoor air monitoring at learning facilities.
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Affiliation(s)
- Rita Wiryasaputra
- Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung, Taiwan
- Department of Informatics, Krida Wacana Christian University, Jakarta, Indonesia
| | - Chin-Yin Huang
- Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung, Taiwan
| | - Endah Kristiani
- Department of Informatics, Krida Wacana Christian University, Jakarta, Indonesia
- Department of Computer Science, Tunghai University, Taichung, Taiwan
| | - Po-Yu Liu
- Division of Infection, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Ph.D. Program in Translational Medicine, National Chung Hsing University, Taichung, Taiwan
- Rong Hsing Research Center for Translational Medicine, National Chung Hsing University, Taichung, Taiwan
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan
- Genomic Center for Infectious Diseases, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Ting-Kuang Yeh
- Division of Infection, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Genomic Center for Infectious Diseases, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Chao-Tung Yang
- Department of Computer Science, Tunghai University, Taichung, Taiwan
- Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung, Taiwan
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Park SH, Yook SJ, Koo HB. Natural Ventilation and Air Purification for Effective Removal of Airborne Virus in Classrooms with Heater Operation. TOXICS 2022; 10:573. [PMID: 36287854 PMCID: PMC9607292 DOI: 10.3390/toxics10100573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/25/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
Mass COVID-19 infection cases in indoor spaces have been continuously reported since its global outbreak, generating increasing public interest in reducing the spread of the virus. This study considered a situation in which an infected individual continuously releases the virus into the air in a classroom, simulated by continuous injection of NaCl particles ≤ 5 μm, with heater operation during winter. The effects of applying natural ventilation and operating one or two air purifiers on the removal of virus-containing aerosols were experimentally compared and analyzed based on the spatiotemporal changes in NaCl concentration within the classroom. When a heater was operated with all windows shut, operating one and two air purifiers reduced the amount of the aerosol in indoor air by approximately 50 and 60%, respectively, compared to the case with no air purifier. Additionally, when the heater was operated with one or two air purifiers under natural ventilation, the amount of virus-containing aerosol in the air was reduced by 86-88% compared to the case with neither natural ventilation nor air purifier. Because natural ventilation significantly varies with weather conditions and particulate matter concentrations, combining natural ventilation with air purifiers in classrooms during winter needs to be adjusted appropriately.
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Affiliation(s)
- Su-Hoon Park
- School of Mechanical Engineering, Hanyang University, Seoul 04763, Korea
| | - Se-Jin Yook
- School of Mechanical Engineering, Hanyang University, Seoul 04763, Korea
| | - Hyun Bon Koo
- Department of Structural Engineering Research, Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Korea
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