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• W4313305135 endingPage "109967" @default.
• W4313305135 startingPage "109967" @default.
• W4313305135 abstract "CO2-based infection risk monitoring is highly recommended during the current COVID-19 pandemic. However, the CO2 monitoring thresholds proposed in the literature are mainly for spaces with fixed occupants. Determining CO2 threshold is challenging in spaces with changing occupancy due to the co-existence of quanta and CO2 remaining from previous occupants. Here, we propose a new calculation framework for deriving safe excess CO2 thresholds (above outdoor level), Ct, for various spaces with fixed/changing occupancy and analyze the uncertainty involved. We categorized common indoor spaces into three scenarios based on their occupancy conditions, e.g., fixed or varying infection ratios (infectors/occupants). We proved that the rebreathed fraction-based model can be applied directly for deriving Ct in the case of a fixed infection ratio (Scenario 1 and Scenario 2). In the case of varying infection ratios (Scenario 3), Ct derivation must follow the general calculation framework due to the existence of initial quanta/excess CO2. Otherwise, Ct can be significantly biased (e.g., 260 ppm) when the infection ratio varies greatly. Ct can vary significantly based on specific space factors such as occupant number, physical activity, and community prevalence, e.g., 7 ppm for gym and 890 ppm for lecture hall, indicating Ct must be determined on a case-by-case basis. An uncertainty of up to 6 orders of magnitude for Ct was found for all cases due to uncertainty in emissions of quanta and CO2, thus emphasizing the role of accurate emissions data in determining Ct." @default.
• W4313305135 created "2023-01-06" @default.
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• W4313305135 date "2023-04-01" @default.
• W4313305135 modified "2023-09-23" @default.
• W4313305135 title "Safe CO2 threshold limits for indoor long-range airborne transmission control of COVID-19" @default.
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• W4313305135 doi "https://doi.org/10.1016/j.buildenv.2022.109967" @default.
• W4313305135 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36597420" @default.
• W4313305135 hasPublicationYear "2023" @default.
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