RESUMEN
Brown carbon (BrC) is known to absorb light at subvisible wavelengths but its optical properties and sources are still poorly documented, leading to large uncertainties in climate studies. Here, we show its major wintertime contribution to total aerosol absorption at 370 nm (18-42%) at 9 different French sites. Moreover, an excellent correlation with levoglucosan (r2 = 0.9 and slope = 22.2 at 370 nm), suggesting important contribution of wood burning emissions to ambient BrC aerosols in France. At all sites, BrC peaks were mainly observed during late evening, linking to local intense residential wood burning during this time period. Furthermore, the geographic origin analysis also highlighted the high potential contribution of local and/or small-regional emissions to BrC. Focusing on the Paris region, twice higher BrC mass absorption efficiency value was obtained for less oxidized biomass burning organic aerosols (BBOA) compared to more oxidized BBOA (e.g., about 4.9 ± 0.2 vs. 2.0 ± 0.1 m2 g-1, respectively, at 370 nm). Finally, the BBOA direct radiative effect was found to be 40% higher when these two BBOA fractions are treated as light-absorbing species, compared to the non-absorbing BBOA scenario.
RESUMEN
Studies of air pollution effects during pregnancy generally only consider exposure in the outdoor air at the home address. We aimed to compare exposure models differing in their ability to account for the spatial resolution of pollutants, space-time activity and indoor air pollution levels. We recruited 40 pregnant women in the Grenoble urban area, France, who carried a Global Positioning System (GPS) during up to 3 weeks; in a subgroup, indoor measurements of fine particles (PM2.5) were conducted at home (n=9) and personal exposure to nitrogen dioxide (NO2) was assessed using passive air samplers (n=10). Outdoor concentrations of NO2, and PM2.5 were estimated from a dispersion model with a fine spatial resolution. Women spent on average 16 h per day at home. Considering only outdoor levels, for estimates at the home address, the correlation between the estimate using the nearest background air monitoring station and the estimate from the dispersion model was high (r=0.93) for PM2.5 and moderate (r=0.67) for NO2. The model incorporating clean GPS data was less correlated with the estimate relying on raw GPS data (r=0.77) than the model ignoring space-time activity (r=0.93). PM2.5 outdoor levels were not to moderately correlated with estimates from the model incorporating indoor measurements and space-time activity (r=-0.10 to 0.47), while NO2 personal levels were not correlated with outdoor levels (r=-0.42 to 0.03). In this urban area, accounting for space-time activity little influenced exposure estimates; in a subgroup of subjects (n=9), incorporating indoor pollution levels seemed to strongly modify them.