The nexus between in-car aerosol concentrations, ventilation and the risk of respiratory infection

We examined the trade-offs between in-car aerosol concentrations, ventilation and respiratory infection transmission under three ventilation settings: windows open (WO); windows closed with air-conditioning on ambient air mode (WC-AA); and windows closed with air-conditioning on recirculation (WC-RC). Forty-five runs, covering a total of 324 km distance on a 7.2-km looped route, were carried out three times a day (morning, afternoon, evening) to monitor aerosols (PM_2.5; particulate matter < 2.5 μm and PNC; particle number concentration), CO₂ and environmental conditions (temperature and relative humidity). Ideally, higher ventilation rates would give lower in-car pollutant concentrations due to dilution from outdoor air. However, in-car aerosol concentrations increased with ventilation (WO > WC-AA > WC-RC) due to the ingress of polluted outdoor air on urban routes. A clear trade-off, therefore, exists for the in-car air quality (icAQ) versus ventilation; for example, WC-RC showed the least aerosol concentrations (i.e. four-times lower compared with WO), but corresponded to elevated CO₂ levels (i.e. five-times higher compared with WO) in 20 mins. We considered COVID-19 as an example of respiratory infection transmission. The probability of its transmission from an infected occupant in a five-seater car was estimated during different quanta generation rates (2-60.5 quanta hr^-1) using the Wells-Riley model. In WO, the probability with 50%-efficient and without facemasks under normal speaking (9.4 quanta hr^-1) varied only by upto 0.5%. It increased by 2-fold in WC-AA (<1.1%) and 10-fold in WC-RC (<5.2%) during a 20 mins trip. Therefore, a wise selection of ventilation settings is needed to balance in-car exposure in urban areas affected by outdoor air pollution and that by COVID-19 transmission. We also successfully developed and assessed the feasibility of using sensor units in static and dynamic environments to monitor icAQ and potentially infer COVID-19 transmission. Further research is required to develop automatic-alarm systems to help reduce both pollutant exposure and infection from respiratory COVID-19 transmission.

Characterization of PM2.5 exposure concentration in transport microenvironments using portable monitors

Recently, portable monitors have been increasingly used to quantify air pollutant concentrations at high spatiotemporal resolution. A sampling campaign was conducted to measure the fine particulate matter (PM_2.5) and carbon monoxide (CO) exposure concentrations in transport microenvironments (TMEs) in Hong Kong in January and June 2015 using TSI DustTrak and Q-Trak portable monitors. The objectives were to: (1) calibrate DustTrak and Q-Trak; (2) evaluate variability between seasons and microenvironments; (3) estimate indoor/outdoor relationships; and (4) determine minimum sample size. Calibration equations, obtained through side-by-side measurement against stationary reference methods in winter and summer, were applied to correct the measured PM_2.5 data set. In general, PM_2.5 concentrations in all TMEs were significantly higher in winter than in summer. The mean PM_2.5 concentration in winter was lower for underground sections of the Mass Transit Railway (MTR) metro system (31 μg/m³) than for other TMEs, whereas in summer TMEs had mean PM_2.5 concentrations in the range of 10-15 μg/m³, with above-ground MTR train as an exception, at 23 μg/m³. PM_2.5 concentrations measured in TMEs were strongly correlated with nearby air quality monitoring stations (AQMSs) measurements in winter, but in summer there was little correlation. The minimum sample size estimates varied more among TMEs in summer versus winter because of the differences in PM_2.5 concentration distributions related to changes in ambient PM_2.5 concentrations and ventilation practices. This study provides a feasible protocol on the calibration and application of portable monitors in TME air quality measurement and develops a method for estimating minimum sample size.