Factors that influence surface PM_2.5 values inferred from satellite observations: perspective gained for the US Baltimore–Washington metropolitan area during DISCOVER-AQ

Abstract. During the NASA DISCOVER-AQ campaign over the US Baltimore, MD–Washington, D.C., metropolitan area in July 2011, the NASA P-3B aircraft performed extensive profiling of aerosol optical, chemical, and microphysical properties. These in situ profiles were coincident with ground-based remote sensing (AERONET) and in situ (PM_2.5) measurements. Here, we use this data set to study the correlation between the PM_2.5 observations at the surface and the column integrated measurements. Aerosol optical depth (AOD_{550 nm}) calculated with the extinction (550 nm) measured during the in situ profiles was found to be strongly correlated with the volume of aerosols present in the boundary layer (BL). Despite the strong correlation, some variability remains, and we find that the presence of aerosol layers above the BL (in the buffer layer – BuL) introduces significant uncertainties in PM_2.5 estimates based on column-integrated measurements (overestimation of PM_2.5 by a factor of 5). This suggests that the use of active remote sensing techniques would dramatically improve air quality retrievals. Indeed, the relationship between the AOD_{550 nm} and the PM_2.5 is strongly improved by accounting for the aerosol present in and above the BL (i.e., integrating the aerosol loading from the surface to the top of the BuL). Since more than 15% of the AOD values observed during DISCOVER-AQ are dominated by aerosol water uptake, the f(RH)_amb (ratio of scattering coefficient at ambient relative humidity (RH) to scattering coefficient at low RH; see Sect. 3.2) is used to study the impact of the aerosol hygroscopicity on the PM_2.5 retrievals. The results indicate that PM_2.5 can be predicted within a factor up to 2 even when the vertical variability of the f(RH)_amb is assumed to be negligible. Moreover, f(RH = 80%) and RH measurements performed at the ground may be used to estimate the f(RH)_amb during dry conditions (RH_BL < 55%).