Familiarity with the use of face coverings to reduce the risk of respiratory disease has increased during the coronavirus pandemic; however, recommendations for their use outside of the pandemic remains limited. Here, we develop a modeling framework to quantify the potential health benefits of wearing a face covering or respirator to mitigate exposure to particulate air pollution. This framework accounts for the wide range of available face coverings and respirators, fit factors and efficacy, air pollution characteristics, and exposure‐response data. Our modeling shows that N95 respirators offer robust protection against different sources of particulate matter, reducing exposure by more than a factor of 14 when worn with a leak rate of 5%. Synthetic‐fiber masks offer less protection with a strong dependence on aerosol size distribution (protection factors ranging from 4.4 to 2.2), while natural‐fiber and surgical masks offer reductions in the exposure of 1.9 and 1.7, respectively. To assess the ability of face coverings to provide population‐level health benefits to wildfire smoke, we perform a case study for the 2012 Washington state fire season. Our models suggest that although natural‐fiber masks offer minor reductions in respiratory hospitalizations attributable to smoke (2%–11%) due to limited filtration efficiency, N95 respirators and to a lesser extent surgical and synthetic‐fiber masks may lead to notable reductions in smoke‐attributable hospitalizations (22%–39%, 9%–24%, and 7%–18%, respectively). The filtration efficiency, bypass rate, and compliance rate (fraction of time and population wearing the device) are the key factors governing exposure reduction potential and health benefits during severe wildfire smoke events.

Traffic-related air pollution is associated with increased mortality and morbidity, yet few studies have examined strategies to reduce individual exposure while commuting. The present study aimed to quantify how choice of mode and route type affects personal exposure to air pollutants during commuting. We analyzed within-person difference in exposures to multiple air pollutants (black carbon (BC), carbon monoxide (CO), ultrafine particle number concentration (PNC), and fine particulate matter (PM_2.5)) during commutes between the home and workplace for 45 participants. Participants completed 8 days of commuting by car and bicycle on direct and alternative (reduced traffic) routes. Mean within-person exposures to BC, PM_2.5, and PNC were higher when commuting by cycling than when driving, but mean CO exposure was lower when cycling. Exposures to CO and BC were reduced when commuting along alternative routes. When cumulative exposure was considered, the benefits from cycling were attenuated, in the case of CO, or exacerbated, in the case of particulate exposures, owing to the increased duration of the commute. Although choice of route can reduce mean exposure, the effect of route length and duration often offsets these reductions when cumulative exposure is considered. Furthermore, increased ventilation rate when cycling may result in a more harmful dose than inhalation at a lower ventilation rate.

Aerosol emissions from biofuel combustion impact both health and climate; however, while reducing emissions through improvements to combustion technologies will improve health, the net effect on climate is largely unconstrained. In this study, we examine sensitivities in global aerosol concentration, direct radiative climate effect, and cloud-albedo aerosol indirect climate effect to uncertainties in biofuel emission factors, optical mixing state, and model nucleation and background secondary organic aerosol (SOA). We use the Goddard Earth Observing System global chemical-transport model (GEOS-Chem) with TwO Moment Aerosol Sectional (TOMAS) microphysics. The emission factors include amount, composition, size, and hygroscopicity, as well as optical mixing-state properties. We also evaluate emissions from domestic coal use, which is not biofuel but is also frequently emitted from homes. We estimate the direct radiative effect assuming different mixing states (homogeneous, core-shell, and external) with and without absorptive organic aerosol (brown carbon). We find the global-mean direct radiative effect of biofuel emissions ranges from −0.02 to +0.06 W m⁻² across all simulation/mixing-state combinations with regional effects in source regions ranging from −0.2 to +0.8 W m⁻². The global-mean cloud-albedo aerosol indirect effect (AIE) ranges from +0.01 to −0.02 W m⁻² with regional effects in source regions ranging from −1.0 to −0.05 W m⁻². The direct radiative effect is strongly dependent on uncertainties in emissions mass, composition, emissions aerosol size distributions, and assumed optical mixing state, while the indirect effect is dependent on the emissions mass, emissions aerosol size distribution, and the choice of model nucleation and secondary organic aerosol schemes. The sign and magnitude of these effects have a strong regional dependence. We conclude that the climate effects of biofuel aerosols are largely unconstrained, and the overall sign of the aerosol effects is unclear due to uncertainties in model inputs. This uncertainty limits our ability to introduce mitigation strategies aimed at reducing biofuel black carbon emissions in order to counter warming effects from greenhouse gases. To better understand the climate impact of particle emissions from biofuel combustion, we recommend field/laboratory measurements to narrow constraints on (1) emissions mass, (2) emission size distribution, (3) mixing state, and (4) ratio of black carbon to organic aerosol.