DOI: 10.5061/dryad.fqz612k0w
title: Data from: Should we use ceiling fans indoors to reduce the risk of transmission of infectious aerosols?

description: The effects of ceiling fans on the transmission of infectious aerosols
 remain poorly understood, leading to conflicting recommendations. We
 conducted repeated experiments in a well-controlled chamber with a typical
 mixing ventilation system at three different ventilation rates with and
 without ceiling fans. We evaluated airborne infection risks for short- and
 long-range transmission routes based on size-resolved tracer particles
 measured at various locations. We found that the mixing ventilation
 without fans only effectively diluted the airborne particle concentration
 for the long-range route but not for the short-range. By using ceiling
 fans to enhance air mixing, tracer particles were distributed more
 homogeneously throughout the room, leading to up to 77% reduction in
 short-range particle exposure while a slight increase of less than 14% in
 long-range exposure. Based on the dilution-based Wells-Riley model, the
 changes in particle concentration translated to a maximum 47% reduction in
 short-range infection risk and a marginal 4% increase for long-range
 transmission. Based on the dilution factors obtained from the experiments,
 we developed a decision-making tool that uses the ventilation rate, the
 number of individuals at short- and long-range, and the disease's
 transmissibility to decide whether the use of ceiling fans is beneficial.
 Deploying ceiling fans always reduces the concentration of particles in
 the short range and, assuming a relationship between particles and
 pathogens, this directly translates to a diminished short-range risk.
 Based on the modeling of the overall risk, the benefits of fans are
 highest when the room is ventilated according to code, when masking
 measures are in place, and when the pathogen is not highly contagious.
description: # Data from: Should we use ceiling fans indoors to reduce the risk of
 transmission of infectious aerosols?
 [https://doi.org/10.5061/dryad.fqz612k0w](https://doi.org/10.5061/dryad.fqz612k0w) Authors: Jiayu Li, Sultan Zuraimi, Stefano Schiavon Contact Information ``` Name: Jiayu Li Institution: Center for the Built Environment, UC Berkeley, Berkeley, CA, USA Address: 390 Wurster Hall #1839, Berkeley CA 94720 Email: jiayu.li@berkeley.edu ``` Date of data collection: 2021-12-03 to 2022-01-13 ## Description of the data and file structure There are two main folders: `data` and `R`. `data` contains all the data files that have been used to generate the results in the work. `R` contains the R script files that are used to generate the results provided in the original work. 1. Files in `data`. 1. `raw_data.csv` contains raw data of tracer particle number concentration measured by the TSI OPS 3330 at different locations. * `n_conc`: measured number concentration of the tracer particles. * `location`: sampling locations refer to Figure 1 in the manuscript. * `bin`: the size range of the particle diameters in µm. * `Da`: the geometric mean of the particle diameters of the size range in µm. * `lower`: the lower boundary of the size range of the particles in µm. * `upper`: the upper boundary of the size range of the particles in µm. * `fan_1`: condition of the ceiling fan 1. * `fan_2`: condition of the ceiling fan 2. * `supplied_airflow_rate`: the ventilation rate of the chamber in cubic meters per hour. * `z`: sampling height in m. * `point_type`: classification of the sampling point regarding if it is at the occupants (dummies) or in the room. * `loc_name`: name of the sampling point. * `loc_type`: the classification of the sampling point regarding the transmission routes. * `test_id`: random number to differentiate different scenarios. * `sampling_seq`: the order of sampling for each instrument. * `datetime`: the date and time that measured the value. * `unit`: the serial no. of TSI OPS 3330 units that were used for particle sampling 2. `quanta_emission.csv` contains the quanta emission rates used in the manuscript. * `pathogen`: name of pathogen. * `lower`: the lower boundary of the quanta emission rate in quanta/h. * `upper`: the upper boundary of the quanta emission rate in quanta/h. 3. `em_dt.csv` contains the emission rates of tracer particles used in the manuscript. * `bin`: the size range of the particle diameters in µm. * `lower`: the lower boundary of the size range of the particles in µm. * `upper`: the upper boundary of the size range of the particles in µm. * `e_rate`: the mean of the tracer particle emission rates. * `e_rate_sd`: the standard deviation of the tracer particle emission rates. 4. `beta_dt.csv` contains the decay rates of tracer particles used in the manuscript. * `bin`: the size range of the particle diameters in µm. * `lower`: the lower boundary of the size range of the particles in µm. * `upper`: the upper boundary of the size range of the particles in µm. * `fan_on_off`: the conditions of ceiling fans. * `beta`: the decay rates of the particle. * `r_squared`: the r.squared value when fitting the decay curve. 2. Files in `R`. 1. `read_data.R` contains the script that read all the data into R. 2. `ploting_themes_and_functions.R` contains the themes and functions that need to run the R codes. Users need to install the packages mentioned in the file if they haven't done so. 3. `analysis_conc.R` contains code for Figures 2 and 3. 4. `analysis_dilu.R` contains code for Figure 4. 5. `anlysis_risk.R` and `analysis_risk_modelling.R` contains code for Figures 5 and 6.