Fant 9831 publikasjoner. Viser side 378 av 394:
2014
2022
2014
2012
2013
2007
2016
2007
Optical properties of surface aerosols at Dome C, Antarctica, in 2007–2013 and their potential source areas are presented. Scattering coefficients (σsp) were calculated from measured particle number size distributions with a Mie code and from filter samples using mass scattering efficiencies. Absorption coefficients (σap) were determined with a three-wavelength Particle Soot Absorption Photometer (PSAP) and corrected for scattering by using two different algorithms. The scattering coefficients were also compared with σsp measured with a nephelometer at the South Pole Station (SPO). The minimum σap was observed in the austral autumn and the maximum in the austral spring, similar to other Antarctic sites. The darkest aerosol, i.e., the lowest single-scattering albedo ωo≈0.91, was observed in September and October and the highest ωo≈0.99 in February and March. The uncertainty of the absorption Ångström exponent αap is high. The lowest αap monthly medians were observed in March and the highest in August–October. The equivalent black carbon (eBC) mass concentrations were compared with eBC measured at three other Antarctic sites: the SPO and two coastal sites, Neumayer and Syowa. The maximum monthly median eBC concentrations are almost the same ( ng m−3) at all these sites in October–November. This suggests that there is no significant difference in eBC concentrations between the coastal and plateau sites. The seasonal cycle of the eBC mass fraction exhibits a minimum f(eBC) ≈0.1 % in February–March and a maximum ∼4 %–5 % in August–October. Source areas were calculated using 50 d FLEXPART footprints. The highest eBC concentrations and the lowest ωo were associated with air masses coming from South America, Australia and Africa. Vertical simulations that take BC particle removal processes into account show that there would be essentially no BC particles arriving at Dome C from north of latitude 10∘ S at altitudes
2022
Aerosol Optical Properties and Type Retrieval via Machine Learning and an All-Sky Imager
This study investigates the applicability of using the sky information from an all-sky imager (ASI) to retrieve aerosol optical properties and type. Sky information from the ASI, in terms of Red-Green-Blue (RGB) channels and sun saturation area, are imported into a supervised machine learning algorithm for estimating five different aerosol optical properties related to aerosol burden (aerosol optical depth, AOD at 440, 500 and 675 nm) and size (Ångström Exponent at 440–675 nm, and Fine Mode Fraction at 500 nm). The retrieved aerosol optical properties are compared against reference measurements from the AERONET station, showing adequate agreement (R: 0.89–0.95). The AOD errors increased for higher AOD values, whereas for AE and FMF, the biases increased for coarse particles. Regarding aerosol type classification, the retrieved properties can capture 77.5% of the total aerosol type cases, with excellent results for dust identification (>95% of the cases). The results of this work promote ASI as a valuable tool for aerosol optical properties and type retrieval.
MDPI
2023
2007
2007
Aerosol optical properties and distribution during the extreme Arctic haze event in spring 2006. NILU F
2006
2006
2009
2007
2007
2017