Low-cost gas and particle sensors can enhance the spatial coverage of Air Quality (AQ) monitoring networks in urban settings. While their accuracy is insufficient to replace reference instruments, they may still capture spatial differences among different stations, as well as temporal trends and month-to-month variabilities at a specific location. To assess this, we conducted a 19-month study using two Vaisala AQ Transmitters-Monitors (Model AQT530), collocated with reference-grade instruments, at two AQ stations in Nicosia: an urban traffic and an urban background station. These two stations are ideal for the needs of this study considering that the reference measurements carried out there exhibit statistically significant spatial and temporal differences in pollutant concentrations when analysed over the entire period and on a monthly basis.

The AQT530 air quality monitor employs Low-Cost Sensors (LCSs) for gaseous pollutants (i.e., CO, NO2, NO and O3) and particulate matter (PM). Tests of the performance of the two AQT530 monitors during an initial period when those were collocated at the urban traffic station revealed high unit-to-unit agreements for the CO, NO and PM10, and good to moderate for the NO2, O3 and PM2.5 measurements. The CO and PM10 LCS measurements also effectively captured concentration differences between the two stations when averaged over the entire study period or monthly, with some exceptions for specific months. These LCSs successfully detected spatial concentration differences (i.e., monthly, daily and hourly) as long as those were above a certain threshold. Overall, the CO and PM sensors successfully tracked month-to-month trends over the entire study period, similarly to reference instruments, whereas NO2, NO, and O3 sensors struggled due to environmental sensitivities. Despite this, all sensors identified statistically significant month-to-month variations at the same station, with the PM2.5 measurements showing the strongest agreement with reference data. ... Read more

Aerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n250,dry with an uncertainty of 20 % to 40 % and Sdry with an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization of Ullrich et al. (2017) (applicable for the temperature range −50 to −33 ∘C) agree within 1 order of magnitude with the in situ observations of nINP; thus, the parameterization of Ullrich et al. (2017) can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations of DeMott et al. (2015, 2010) (applicable for the temperature range −35 to −9 ∘C) agree within 2 orders of magnitude with the in situ observations of INP concentrations (nINP) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations of DeMott et al. (2015) for dust and Ullrich et al. (2017) for soot. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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.
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