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Markey E, Hourihane Clancy J, Martínez-Bracero M, Sarda-Estève R, Baisnée D, McGillicuddy EJ, Sewell G, Skjøth CA, O'Connor DJ. Spectroscopic detection of bioaerosols with the wibs-4+: Anthropogenic and meteorological impacts. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 943:173649. [PMID: 38852865 DOI: 10.1016/j.scitotenv.2024.173649] [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: 03/11/2024] [Revised: 04/24/2024] [Accepted: 05/28/2024] [Indexed: 06/11/2024]
Abstract
This research builds upon a previous study that explored the potential of the modified WIBS-4+ to selectively differentiate and detect different bioaerosol classes. The current work evaluates the influence of meteorological and air quality parameters on bioaerosol concentrations, specifically pollen and fungal spore dynamics. Temperature was found to be the most influential parameter in terms of pollen production and release, showing a strong positive correlation. Wind data analysis provided insights into the potential geographic origins of pollen and fungal spore concentrations. Fungal spores were primarily shown to originate from a westerly direction, corresponding to agricultural land use, whereas pollen largely originated from a North-easterly direction, corresponding to several forests. The influence of air quality was also analysed to understand its potential impact on the WIBS fluorescent parameters investigated. Most parameters had a negative association with fungal spore concentrations, whereas several anthropogenic influences showed notable positive correlations with daily pollen concentrations. This is attributed to similar driving forces (meteorological parameters) and geographical origins. In addition, the WIBS showed a significant correlation with anthropogenic pollutants originating from combustion sources, suggesting the potential for such modified spectroscopic instruments to be utilized as air quality monitors. By combining all meteorological and pollution data along with WIBS-4+ channel data, a set of Multiple Linear Regression (MLR) analyses were completed. Successful results with R2 values ranging from 0.6 to 0.8 were recorded. The inclusion of meteorological parameters was dependent on the spore or pollen type being examined.
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Affiliation(s)
- Emma Markey
- School of Chemical Sciences, Dublin City University, D09 E432 Dublin, Ireland
| | | | | | - Roland Sarda-Estève
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CNRS-CEA-UVSQ, 91191 Saint-Aubin, France
| | - Dominique Baisnée
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CNRS-CEA-UVSQ, 91191 Saint-Aubin, France
| | - Eoin J McGillicuddy
- School of Chemical and Pharmaceutical Sciences, Technological University Dublin, D07 H6K8 Dublin, Ireland
| | - Gavin Sewell
- School of Chemical and Pharmaceutical Sciences, Technological University Dublin, D07 H6K8 Dublin, Ireland
| | - Carsten Ambelas Skjøth
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, P.O. Box 358, DK-4000 Roskilde, Denmark
| | - David J O'Connor
- School of Chemical Sciences, Dublin City University, D09 E432 Dublin, Ireland
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Sultan Z, Li J, Pantelic J, Schiavon S. Particle characterization in commercial buildings: A cross-sectional study in 40 offices in Singapore. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 927:172126. [PMID: 38569949 DOI: 10.1016/j.scitotenv.2024.172126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 03/10/2024] [Accepted: 03/29/2024] [Indexed: 04/05/2024]
Abstract
There is a knowledge gap in understanding how existing office buildings are protecting occupants from exposure to particles from both indoor and outdoor sources. We report a cross-sectional study involving weekly measurements of size-resolved indoor and outdoor particle concentrations in forty commercial building offices in Singapore. The outdoor and indoor particles size distributions were single mode with daytime peak number concentrations at 36.5 nm and 48.7 nm. Outdoor concentrations were significantly greater than indoors for all particle diameters. Indoor particle concentrations were generally low due to: 1) relatively high indoor particle removal (IPR) rates; 2) low indoor source strengths; and 3) low indoor particle of outdoor proportion (IPOP). We found that the ventilation system type had a substantial effect on indoor particle levels, IPR and IPOP. Through linear mixed model analyses, we identified dependencies of IPR rates with the use of MERV13 filters in supply air and filter maintenance frequency, IPOP with the use of MERV13 filters in the fresh air and supply air ducts and low particle source strength with regular daily cleaning presumably due to dust reservoir removal. Lastly, the contribution of outdoor sources was mainly seen for ultrafine and fine particles but less pronounced for coarse particles. This study provided detailed understanding of particle exposure in building offices and their influencing factors, facilitating future research on health impact of particle exposures.
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Affiliation(s)
- Zuraimi Sultan
- Berkeley Education Alliance for Research in Singapore (BEARS) Limited, Singapore.
| | - Jiayu Li
- Berkeley Education Alliance for Research in Singapore (BEARS) Limited, Singapore; University of California Berkeley, Center for the Built Environment, USA
| | - Jovan Pantelic
- Katholieke Universiteit Leuven, Belgium; Well Living Lab, USA
| | - Stefano Schiavon
- Berkeley Education Alliance for Research in Singapore (BEARS) Limited, Singapore; University of California Berkeley, Center for the Built Environment, USA
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Tastassa AC, Sharaby Y, Lang-Yona N. Aeromicrobiology: A global review of the cycling and relationships of bioaerosols with the atmosphere. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168478. [PMID: 37967625 DOI: 10.1016/j.scitotenv.2023.168478] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 10/31/2023] [Accepted: 11/08/2023] [Indexed: 11/17/2023]
Abstract
Airborne microorganisms and biological matter (bioaerosols) play a key role in global biogeochemical cycling, human and crop health trends, and climate patterns. Their presence in the atmosphere is controlled by three main stages: emission, transport, and deposition. Aerial survival rates of bioaerosols are increased through adaptations such as ultra-violet radiation and desiccation resistance or association with particulate matter. Current research into modern concerns such as climate change, global gene transfer, and pathogenicity often neglects to consider atmospheric involvement. This comprehensive review outlines the transpiring of bioaerosols across taxa in the atmosphere, with significant focus on their interactions with environmental elements including abiotic factors (e.g., atmospheric composition, water cycle, and pollution) and events (e.g., dust storms, hurricanes, and wildfires). The aim of this review is to increase understanding and shed light on needed research regarding the interplay between global atmospheric phenomena and the aeromicrobiome. The abundantly documented bacteria and fungi are discussed in context of their cycling and human health impacts. Gaps in knowledge regarding airborne viral community, the challenges and importance of studying their composition, concentrations and survival in the air are addressed, along with understudied plant pathogenic oomycetes, and archaea cycling. Key methodologies in sampling, collection, and processing are described to provide an up-to-date picture of ameliorations in the field. We propose optimization to microbiological methods, commonly used in soil and water analysis, that adjust them to the context of aerobiology, along with other directions towards novel and necessary advancements. This review offers new perspectives into aeromicrobiology and calls for advancements in global-scale bioremediation, insights into ecology, climate change impacts, and pathogenicity transmittance.
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Affiliation(s)
- Ariel C Tastassa
- Civil and Environmental Engineering, Technion - Israel Institute of Technology, 3200003 Haifa, Israel
| | - Yehonatan Sharaby
- Civil and Environmental Engineering, Technion - Israel Institute of Technology, 3200003 Haifa, Israel
| | - Naama Lang-Yona
- Civil and Environmental Engineering, Technion - Israel Institute of Technology, 3200003 Haifa, Israel.
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Seidkhani-Nahal A, Heydari H, Tavakolian A, Najafi ML, Miri M. The association of in-utero exposure to air pollution and atherogenic index of plasma in newborns. Environ Health 2024; 23:22. [PMID: 38369478 PMCID: PMC10875836 DOI: 10.1186/s12940-024-01059-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 02/01/2024] [Indexed: 02/20/2024]
Abstract
BACKGROUND Prenatal exposure to particulate matter (PM) and traffic was associated with the programming of cardiovascular diseases (CVDs) in early life. However, the exact underlying mechanisms are not fully understood. Therefore, we aimed to evaluate the association between in-utero exposure to PMs and traffic indicators with the atherogenic index of plasma (AIP) in newborns, which is a precise index reflecting an enhancement of lipid risk factors for CVDs. METHODS In this cross-sectional study, a total of 300 mother-newborn pairs were enrolled in Sabzevar, Iran. Spatiotemporal land-use regression models were used to estimate the level of PM1, PM2.5 and PM10 at the mother's residential address. The total length of streets in different buffers (100,300 and 500m) and proximity to major roads were calculated as indicators of traffic. The AIP of cord blood samples was calculated using an AIP calculator. Multiple linear regression models were used to examine the association of PM concentrations as well as traffic indicators with AIP controlled for relevant covariates. RESULTS PM2.5 exposure was significantly associated with higher levels of AIP in newborns. Each interquartile range (IQR) increment of PM2.5 concentration at the mothers' residential addresses was associated with a 5.3% (95% confidence interval (CI): 0.0, 10.6%, P = 0.04) increase in the AIP. Associations between PM1, PM10 and traffic indicators with cord blood level of AIP were positive but not statistically significant. CONCLUSION Our findings showed that in utero exposure to PM2.5 may be associated with CVDs programming through the increase of atherogenic lipids.
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Affiliation(s)
- Ali Seidkhani-Nahal
- Department of Clinical Biochemistry, Faculty of Medical Sciences, Ilam University of Medical Sciences, Ilam, Iran
| | - Hafez Heydari
- Department of Biochemistry, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
| | - Ayoub Tavakolian
- Emergency Department, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Moslem Lari Najafi
- Pharmaceutical Sciences and Cosmetic Products Research Center, Kerman University of Medical Sciences, Kerman, Iran
| | - Mohammad Miri
- Leishmaniasis Research Center, Department of Environmental Health, Sabzevar University of Medical Sciences, Sabzevar, Iran.
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Valverde M, Granados A, Milić M, Ceppi M, Sollano L, Bonassi S, Rojas E. Effect of Air Pollution on the Basal DNA Damage of Mother-Newborn Couples of México City. TOXICS 2023; 11:766. [PMID: 37755776 PMCID: PMC10537346 DOI: 10.3390/toxics11090766] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 08/23/2023] [Accepted: 09/05/2023] [Indexed: 09/28/2023]
Abstract
Environmental pollution of megacities can cause early biological damage such as DNA strand breaks and micronuclei formation. Comet assay tail length (TL) reflects exposure in the uterus to high levels of air pollution, primarily ozone and air particles (PM10), including mothers' smoking habits during pregnancy, conditions which can lead to low birth weight. In this biomonitoring study, we evaluated basal DNA damage in the cord blood cells of newborn children from Mexico City. We found a correlation between DNA damage in mothers and their newborns, including various parameters of environmental exposure and complications during pregnancy, particularly respiratory difficulties, malformations, obstetric trauma, neuropathies, and nutritional deficiencies. Mothers living in the southern part of the city showed double DNA damage compared to those living in the northern part (TL 8.64 μm vs. 4.18 μm, p < 0.05). Additionally, mothers' DNA damage correlates with exposure to NOx (range 0.77-1.52 ppm) and PM10 (range 58.32-75.89 μg/m3), as well maternal age >29. These results highlight the sensitivity of the comet assay in identifying differential in utero exposure for newborns whose mothers were exposed during pregnancy. They also suggest the importance of antioxidants during pregnancy and the role of the placental barrier in protecting the newborn from the DNA-damaging effects of oxidative pollution.
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Affiliation(s)
- Mahara Valverde
- Laboratorio de Genotoxicología, Instituto de Investigaciones Biomédicas, U.N.A.M., Mexico City 04510, Mexico; (M.V.); (A.G.)
| | - Adriana Granados
- Laboratorio de Genotoxicología, Instituto de Investigaciones Biomédicas, U.N.A.M., Mexico City 04510, Mexico; (M.V.); (A.G.)
| | - Mirta Milić
- Mutagenesis Unit, Institute for Medical Research and Occupational Health, Ksaverska Cesta 2, 10 001 Zagreb, Croatia;
| | - Marcello Ceppi
- Clinical Epidemiology Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy;
| | - Leticia Sollano
- Centro Médico Nacional 20 de Noviembre, I.S.S.S.T.E, Mexico City 03229, Mexico;
| | - Stefano Bonassi
- Unit of Clinical and Molecular Epidemiology, IRCCS San Raffaele, 00166 Rome, Italy
- Department of Human Sciences and Quality of Life Promotion, San Raffaele University, 00166 Rome, Italy
| | - Emilio Rojas
- Laboratorio de Genotoxicología, Instituto de Investigaciones Biomédicas, U.N.A.M., Mexico City 04510, Mexico; (M.V.); (A.G.)
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Santarpia JL, Klug E, Ravnholdt A, Kinahan SM. Environmental sampling for disease surveillance: Recent advances and recommendations for best practice. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2023; 73:434-461. [PMID: 37224401 DOI: 10.1080/10962247.2023.2197825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 02/15/2023] [Accepted: 03/10/2023] [Indexed: 05/26/2023]
Abstract
The study of infectious diseases includes both the progression of the disease in its host and how it transmits between hosts. Understanding disease transmission is important for recommending effective interventions, protecting healthcare workers, and informing an effective public health response. Sampling the environment for infectious diseases is critical to public health since it can provide an understanding of the mechanisms of transmission, characterization of contamination in hospitals and other public areas, and the spread of a disease within a community. Measurements of biological aerosols, particularly those that may cause disease, have been an ongoing topic of research for decades, and so a wide variety of technological solutions exist. This wide field of possibilities can create confusion, particularly when different approaches yield different answers. Therefore, guidelines for best practice in this area are important to allow more effective use of this data in public health decisions. This review examines air, surface and water/wastewater sampling methods, with a focus on aerosol sampling, and a goal of recommending approaches to designing and implementing sampling systems that may incorporate multiple strategies. This is accomplished by developing a framework for designing and evaluating a sampling strategy, reviewing current practices and emerging technologies for sampling and analysis, and recommending guidelines for best practice in the area of aerosol sampling for infectious disease.
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Affiliation(s)
- Joshua L Santarpia
- The Global Center for Health Security, University of Nebraska Medical Center, Omaha, NE, USA
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
- National Strategic Research Institute, Omaha, NE, USA
| | - Elizabeth Klug
- The Global Center for Health Security, University of Nebraska Medical Center, Omaha, NE, USA
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Ashley Ravnholdt
- The Global Center for Health Security, University of Nebraska Medical Center, Omaha, NE, USA
| | - Sean M Kinahan
- The Global Center for Health Security, University of Nebraska Medical Center, Omaha, NE, USA
- National Strategic Research Institute, Omaha, NE, USA
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7
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Wang J, Du W, Lei Y, Chen Y, Wang Z, Mao K, Tao S, Pan B. Quantifying the dynamic characteristics of indoor air pollution using real-time sensors: Current status and future implication. ENVIRONMENT INTERNATIONAL 2023; 175:107934. [PMID: 37086491 DOI: 10.1016/j.envint.2023.107934] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 04/12/2023] [Accepted: 04/12/2023] [Indexed: 05/03/2023]
Abstract
People generally spend most of their time indoors, making indoor air quality be of great significance to human health. Large spatiotemporal heterogeneity of indoor air pollution can be hardly captured by conventional filter-based monitoring but real-time monitoring. Real-time monitoring is conducive to change air assessment mode from static and sparse analysis to dynamic and massive analysis, and has made remarkable strides in indoor air evaluation. In this review, the state of art, strengths, challenges, and further development of real-time sensors used in indoor air evaluation are focused on. Researches using real-time sensors for indoor air evaluation have increased rapidly since 2018, and are mainly conducted in China and the USA, with the most frequently investigated air pollutants of PM2.5. In addition to high spatiotemporal resolution, real-time sensors for indoor air evaluation have prominent advantages in 3-dimensional monitoring, pollution peak and source identification, and short-term health effect evaluation. Huge amounts of data from real-time sensors also facilitate the modeling and prediction of indoor air pollution. However, challenges still remain in extensive deployment of real-time sensors indoors, including the selection, performance, stability, as well as calibration of sensors. In future, sensors with high performance, long-term stability, low price, and low energy consumption are welcomed. Furthermore, more target air pollutants are also expected to be detected simultaneously by real-time sensors in indoor air monitoring.
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Affiliation(s)
- Jinze Wang
- Key Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Wei Du
- Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science & Technology, Kunming 650500, China.
| | - Yali Lei
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Yuanchen Chen
- Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, China
| | - Zhenglu Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Kang Mao
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China
| | - Shu Tao
- Key Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Bo Pan
- Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science & Technology, Kunming 650500, China
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8
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Lee JYY, Miao Y, Chau RLT, Hernandez M, Lee PKH. Artificial intelligence-based prediction of indoor bioaerosol concentrations from indoor air quality sensor data. ENVIRONMENT INTERNATIONAL 2023; 174:107900. [PMID: 37012194 DOI: 10.1016/j.envint.2023.107900] [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: 01/16/2023] [Revised: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 06/19/2023]
Abstract
Exposure to bioaerosols in indoor environments, especially public venues that have a high occupancy and poor ventilation, is a serious public health concern. However, it remains challenging to monitor and determine real-time or predict near-future concentrations of airborne biological matter. In this study, we developed artificial intelligence (AI) models using physical and chemical data from indoor air quality sensors and physical data from ultraviolet light-induced fluorescence observations of bioaerosols. This enabled us to effectively estimate the bioaerosol (bacteria-, fungi- and pollen-like particle) and 2.5-µm and 10-µm particulate matter (PM2.5 and PM10) on a real-time and near-future (≤60 min) basis. Seven AI models were developed and evaluated using measured data from an occupied commercial office and a shopping mall. A long short-term memory model required a relatively short training time and gave the highest prediction accuracy of ∼ 60 %-80 % for bioaerosols and ∼ 90 % for PM on the testing and time series datasets from the two venues. This work demonstrates how AI-based methods can leverage bioaerosol monitoring into predictive scenarios that building operators can use for improving indoor environmental quality in near real-time.
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Affiliation(s)
- Justin Y Y Lee
- School of Energy and Environment, City University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yanhao Miao
- School of Energy and Environment, City University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Ricky L T Chau
- School of Energy and Environment, City University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Mark Hernandez
- Civil, Environmental and Architectural Engineering Department, Environmental Engineering Program, University of Colorado, Boulder, CO, USA
| | - Patrick K H Lee
- School of Energy and Environment, City University of Hong Kong, Hong Kong Special Administrative Region, China; State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong Special Administrative Region, China.
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Kapoor NR, Kumar A, Kumar A, Zebari DA, Kumar K, Mohammed MA, Al-Waisy AS, Albahar MA. Event-Specific Transmission Forecasting of SARS-CoV-2 in a Mixed-Mode Ventilated Office Room Using an ANN. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:16862. [PMID: 36554744 PMCID: PMC9779012 DOI: 10.3390/ijerph192416862] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 12/08/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
The emerging novel variants and re-merging old variants of SARS-CoV-2 make it critical to study the transmission probability in mixed-mode ventilated office environments. Artificial neural network (ANN) and curve fitting (CF) models were created to forecast the R-Event. The R-Event is defined as the anticipated number of new infections that develop in particular events occurring over the course of time in any defined space. In the spring and summer of 2022, real-time data for an office environment were collected in India in a mixed-mode ventilated office space in a composite climate. The performances of the proposed CF and ANN models were compared with respect to traditional statistical indicators, such as the correlation coefficient, RMSE, MAE, MAPE, NS index, and a20-index, in order to determine the merit of the two approaches. Thirteen input features, namely the indoor temperature (TIn), indoor relative humidity (RHIn), area of opening (AO), number of occupants (O), area per person (AP), volume per person (VP), CO2 concentration (CO2), air quality index (AQI), outer wind speed (WS), outdoor temperature (TOut), outdoor humidity (RHOut), fan air speed (FS), and air conditioning (AC), were selected to forecast the R-Event as the target. The main objective was to determine the relationship between the CO2 level and R-Event, ultimately producing a model for forecasting infections in office building environments. The correlation coefficients for the CF and ANN models in this case study were 0.7439 and 0.9999, respectively. This demonstrates that the ANN model is more accurate in R-Event prediction than the curve fitting model. The results show that the proposed ANN model is reliable and significantly accurate in forecasting the R-Event values for mixed-mode ventilated offices.
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Affiliation(s)
- Nishant Raj Kapoor
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Architecture and Planning Department, CSIR-Central Building Research Institute, Roorkee 247667, India
| | - Ashok Kumar
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Architecture and Planning Department, CSIR-Central Building Research Institute, Roorkee 247667, India
| | - Anuj Kumar
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Building Energy Efficiency Division, CSIR-Central Building Research Institute, Roorkee 247667, India
| | - Dilovan Asaad Zebari
- Department of Computer Science, College of Science, Nawroz University, Duhok 42001, Iraq
| | - Krishna Kumar
- Department of Hydro and Renewable Energy, Indian Institute of Technology, Roorkee 247667, India
| | - Mazin Abed Mohammed
- College of Computer Science and Information Technology, University of Anbar, Anbar 31001, Iraq
| | - Alaa S. Al-Waisy
- Computer Technologies Engineering Department, Information Technology College, Imam Ja’afar Al-Sadiq University, Baghdad 10064, Iraq
| | - Marwan Ali Albahar
- School of Computer Science, Umm Al-Qura University, Mecca 24382, Saudi Arabia
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