Long-term exposure to ambient fine particulate matter originating from traffic and residential wood combustion and the prevalence of depression.

INTRODUCTION: Air pollution has been suggested to be associated with depression. However, current evidence is conflicting, and no study has considered different sources of ambient particulate matter with an aerodynamic diameter below 2.5 µm (PM2.5). We evaluated the associations of long-term exposure to PM2.5 from road traffic and residential wood combustion with the prevalence of depression in the Helsinki region, Finland. METHODS: We conducted a cross-sectional analysis based on the Helsinki Capital Region Environmental Health Survey 2015-2016 (N=5895). Modelled long-term outdoor concentrations of PM2.5 were evaluated using high-resolution emission and dispersion modelling on an urban scale and linked to the home addresses of study participants. The outcome was self-reported doctor-diagnosed or treated depression. We applied logistic regression and calculated the OR for 1 µg/m3 increase in PM2.5, with 95% CI. Models were adjusted for potential confounders, including traffic noise and urban green space. RESULTS: Of the participants, 377 reported to have been diagnosed or treated for depression by a doctor. Long-term exposure to PM2.5 from road traffic (OR=1.23, 95% CI 0.86 to 1.73; n=5895) or residential wood combustion (OR=0.78, 95% CI 0.43 to 1.41; n=5895) was not associated with the prevalence of depression. The estimates for PM2.5 from road traffic were elevated, but statistically non-significant, for non-smokers (OR=1.38, 95% CI 0.94 to 2.01; n=4716). CONCLUSIONS: We found no convincing evidence of an effect of long-term exposure to PM2.5 from road traffic or residential wood combustion on depression.

Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoors.

We provide research findings on the physics of aerosol and droplet dispersion relevant to the hypothesized aerosol transmission of SARS-CoV-2 during the current pandemic. We utilize physics-based modeling at different levels of complexity, along with previous literature on coronaviruses, to investigate the possibility of airborne transmission. The previous literature, our 0D-3D simulations by various physics-based models, and theoretical calculations, indicate that the typical size range of speech and cough originated droplets ( d ⩽ 20 µ m ) allows lingering in the air for O ( 1 h ) so that they could be inhaled. Consistent with the previous literature, numerical evidence on the rapid drying process of even large droplets, up to sizes O ( 100 µ m ) , into droplet nuclei/aerosols is provided. Based on the literature and the public media sources, we provide evidence that the individuals, who have been tested positive on COVID-19, could have been exposed to aerosols/droplet nuclei by inhaling them in significant numbers e.g. O ( 100 ) . By 3D scale-resolving computational fluid dynamics (CFD) simulations, we give various examples on the transport and dilution of aerosols ( d ⩽ 20 µ m ) over distances O ( 10 m ) in generic environments. We study susceptible and infected individuals in generic public places by Monte-Carlo modelling. The developed model takes into account the locally varying aerosol concentration levels which the susceptible accumulate via inhalation. The introduced concept, 'exposure time' to virus containing aerosols is proposed to complement the traditional 'safety distance' thinking. We show that the exposure time to inhale O ( 100 ) aerosols could range from O ( 1 s ) to O ( 1 min ) or even to O ( 1 h ) depending on the situation. The Monte-Carlo simulations, along with the theory, provide clear quantitative insight to the exposure time in different public indoor environments.