Ventilation rate plays a significant role in preventing the airborne transmission of diseases in indoor spaces. Classrooms are a considerable challenge during the COVID-19 pandemic because of large occupancy density and mainly poor ventilation conditions. The indoor CO2 level may be used as an index for estimating the ventilation rate and airborne infection risk. In this work, we analyzed a one-day measurement of CO2 levels in three schools to estimate the ventilation rate and airborne infection risk. Sensitivity analysis and Bayesian calibration methods were applied to identify uncertainties and calibrate key parameters. The outdoor ventilation rate with a 95% confidence was 1.96±0.31ACH for Room 1 with mechanical ventilation and fully open window, 0.40±0.08 ACH for Rooms 2, and 0.79±0.06 ACH for Room 3 with only windows open. A time-averaged CO2 level < 450 ppm is equivalent to a ventilation rate > 10 ACH in all three rooms. We also defined the probability of the COVID-19 airborne infection risk associated with ventilation uncertainties. The outdoor ventilation threshold to prevent classroom COVID-19 aerosol spreading is between 3-8 ACH, and the CO2 threshold is around 500 ppm of a school day (< 8 hr) for the three schools.
Natural ventilation is widely applied in buildings considering its potential of improving indoor air quality and saving building energy costs. However, to evaluate its viability and determine the ventilation rates quickly and relatively accurately during early design stage is challenging. This paper explores a fast and accurate evaluation approach in the form of empirical equations to estimate the ventilation rate and potential of wind-driven natural ventilation. By using computational fluid dynamics (CFD) with results validated for both cross and single natural ventilation strategies, this study conducted a series of simulations to determine critical ventilation coefficients for the empirical equations as functions of wind direction, speed and building height.The proposed evaluation approach could help architects and engineers to evaluate the viability of natural ventilation during early building design. This approach was also demonstrated to evaluate the potential of natural ventilation in 65 cities of North America so a series of natural ventilation potential maps were generated for a better understanding of natural ventilation potential in different climates and for the climate-conscious design of buildings in North America.
We have investigated the impact of reduced emissions due to COVID-19 lockdown measures in spring 2020 on air quality in Canada’s four largest cities: Toronto, Montreal, Vancouver, and Calgary. Observed daily concentrations of NO2, PM2.5, and O3 during a “pre-lockdown” period (15 February–14 March 2020) and a “lockdown” period (22 March–2 May 2020), when lockdown measures were in full force everywhere in Canada, were compared to the same periods in the previous decade (2010–2019). Higher-than-usual seasonal declines in mean daily NO2 were observed for the pre-lockdown to lockdown periods in 2020. For PM2.5, Montreal was the only city with a higher-than-usual seasonal decline, whereas for O3 all four cities remained within the previous decadal range. In order to isolate the impact of lockdown-related emission changes from other factors such as seasonal changes in meteorology and emissions and meteorological variability, two emission scenarios were performed with the GEM-MACH air quality model. The first was a Business-As-Usual (BAU) scenario with baseline emissions and the second was a more realistic simulation with estimated COVID-19 lockdown emissions. NO2 surface concentrations for the COVID-19 emission scenario decreased by 31 to 34% on average relative to the BAU scenario in the four metropolitan areas. Lower decreases ranging from 6 to 17% were predicted for PM2.5. O3 surface concentrations, on the other hand, showed increases up to a maximum of 21% close to city centers versus slight decreases over the suburbs, but Ox (odd oxygen), like NO2 and PM2.5, decreased as expected over these cities.
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