Aerosol absorption profiling is crucial for radiative transfer calculations and climate modelling. Here, we utilize the synergy of lidar with sun-photometer measurements to derive the absorption coefficient and single scattering albedo profiles during the ACTRIS-2 campaigns held in Germany, Greece and Cyprus. The remote sensing techniques are compared with in situ measurements in order to harmonize and validate the different methodologies and reduce the absorption profiling uncertainties.@en

The Alphasense optical particle counter (OPC) provides a low-cost and lightweight solution for measurements of the size and number concentration of airborne particulate matter (PM). The micro fan with which it is originally equipped cannot, however, achieve a high enough pressure differential for maintaining an adequate flow rate when connected to sampling/pretreatment aerosol lines, limiting its use for air quality monitoring. Here, we propose a simple modification on the sample flow system that enables the connection of the Alphasense OPC with sampling/pretreatment lines (e.g., dryers) commonly employed on ground observational sites, as well as its use onboard Unmanned Aerial Systems (UASs). Tests of the modified OPC using monodisperse polystyrene spherical (PS) particles having sizes between 0.8 and 2.5 μm show that both the sizing and counting performance of the modified instrument is in agreement with that of a calibrated reference OPC at concentrations from ca. 50 to 800 #/ml, which are typically encountered in the atmosphere in that size range. For particle number concentrations below or above this range, we observed a concentration-dependent counting efficiency, which can be corrected using a polynomial function derived from our measurements. Tests conducted under reduced pressure and temperature conditions demonstrate the capability of the modified OPC for accurately (i.e., within 13% deviation from the reference measurements) determining the size and number concentration of the sampled particles. The tests reported in this work show that the proposed modification can qualify the Alphasense OPC for use in both ground and aerial observations without affecting its performance, and at the same time maintaining its strongly desired characteristics (i.e., cost effectiveness and high portability).@en

In situ measurements using unmanned aerial vehicles (UAVs) and remote sensing observations can independently provide dense vertically resolved measurements of atmospheric aerosols, information which is strongly required in climate models. In both cases, inverting the recorded signals to useful information requires assumptions and constraints, and this can make the comparison of the results difficult. Here we compare, for the first time, vertical profiles of the aerosol mass concentration derived from light detection and ranging (lidar) observations and in situ measurements using an optical particle counter on board a UAV during moderate and weak Saharan dust episodes. Agreement between the two measurement methods was within experimental uncertainty for the coarse mode (i.e. particles having radii > 0.5ĝ€μm), where the properties of dust particles can be assumed with good accuracy. This result proves that the two techniques can be used interchangeably for determining the vertical profiles of aerosol concentrations, bringing them a step closer towards their systematic exploitation in climate models.@en

By means of available ice nucleating particle (INP) parameterization schemes we compute profiles of dust INP number concentration utilizing Polly-XT and CALIPSO lidar observations during the INUIT-BACCHUS-ACTRIS 2016 campaign. The polarization-lidar photometer networking (POLIPHON) method is used to separate dust and non-dust aerosol backscatter, extinction, mass concentration, particle number concentration (for particles with radius > 250 nm) and surface area concentration. The INP final products are compared with aerosol samples collected from unmanned aircraft systems (UAS) and analyzed using the ice nucleus counter FRIDGE.@en

Vertical profiles of the aerosol mass concentration derived from light detection and ranging (lidar) measurements were compared to airborne dried optical particle counter (OPC MetOne; Model 212) measurements during the INUIT-BACCHUS-ACTRIS campaign. The campaign took place in April 2016 and its main focus was the study of aerosol dust particles. During the campaign the NOA Polly-XT Raman lidar located at Nicosia (35.08 N, 33.22 E) was providing round-the-clock vertical profiles of aerosol optical properties. In addition, an unmanned aerial vehicle (UAV) carrying an OPC flew on 7 days during the first morning hours. The flights were performed at Orounda (35.1018 N, 33.0944 E) reaching altitudes of 2.5 km a.s.l, which allows comparison with a good fraction of the recorded lidar data. The polarization lidar photometer networking method (POLIPHON) was used for the estimation of the fine (non-dust) and coarse (dust) mode aerosol mass concentration profiles. This method uses as input the particle backscatter coefficient and the particle depolarization profiles of the lidar at 532 nm wavelength and derives the aerosol mass concentration. The first step in this approach makes use of the lidar observations to separate the backscatter and extinction contributions of the weakly depolarizing non-dust aerosol components from the contributions of the strongly depolarizing dust particles, under the assumption of an externally mixed two-component aerosol. In the second step, sun photometer retrievals of the fine and the coarse modes aerosol optical thickness (AOT) and volume concentration are used to calculate the associated concentrations from the extinction coefficients retrieved from the lidar. The estimated aerosol volume concentrations were converted into mass concentration with an assumption for the bulk aerosol density, and compared with the OPC measurements. The first results show agreement within the experimental uncertainty. This project received funding from the European Union’s Seventh Framework Programme (FP7) project BACCHUS under grant agreement no. 603445, and the European Union’s Horizon 2020 research and innovation programme ACTRIS-2 under grant agreement No 654109. @en