CO2 measurements in instrumental and vocal closed room settings as a risk reducing measure for a Coronavirus infection

  1. Manfred Nusseck
  2. Bernhard Richter
  3. Ludwig Holtmeier
  4. Dominik Skala
  5. Claudia Spahn

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Contaminated aerosols in room air are one of the transmission routes of the coronavirus. The amount of contaminated aerosols in the room seems to play an important role for the infection risk. In rooms without technical air refreshing systems, the aerosol concentration can be reduced with simple natural ventilation activity. Instrumental and vocal lessons and rehearsals take place in closed indoor rooms. Therefore it is important to optimize the necessary ventilation activity in order to keep the infection risk for musicians low. Therefore, knowledge about the maximum duration of the lesson or rehearsal for ventilation intervals are necessary. In this study, carbon dioxide concentration (CO2) as an indicator of the indoor air quality (IAQ) was measured during 47 music lessons and rehearsals at a university of music including 141 persons. From these measurements, the air exchange rates of the rooms and the CO2 emission rates per person were extracted. The results show that the CO2 emission in musical activities can be assigned to light and moderate activities between 28 l/h and 39 l/h. Wind instruments had the highest CO2 emissions. Singers showed low CO2 emission rates comparable to the control group which only spoke and listened. Recommendations for the frequency of ventilation breaks were derived from empirical data and allow for an individual risk assessment of instrumental and vocal lessons and rehearsals depending on room size and number of musicians.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.10.26.20218354: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    By using Matlab (R2020a), an exponential curve fitting of Eq.
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)
    The statistical analyses were conducted with SPSS (Version 27, Armonk, NY: IBM Corp.).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.10.26.20218354v1 on medRxiv