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Martin Schön
,
Vasileios Savvakis
,
Maria Kezoudi
,
Andreas Platis
, and
Jens Bange

Abstract

Atmospheric aerosols affect human health and influence atmospheric and biological processes. Dust can be transported long distances in the atmosphere, and the mechanisms that influence dust transport are not fully understood. To improve the database for numerical models that simulate dust transport, measurements are needed that cover both the vertical distribution of the dust and its size distribution. In addition to measurements with crewed aircraft, uncrewed aircraft systems (UASs) provide a particularly suitable platform for this purpose. In this paper, we present a payload for the small fixed-wing UAS of the type Multiple-Purpose Airborne Sensor Carrier 3 (MASC-3) for aerosol particle measurements that is based on the optical particle counter (OPC) OPC-N3 (Alphasense, United Kingdom), modified by the addition of a dryer and a passive aspiration system (OPC-Pod). Based on field tests with a reference instrument in Mannheim, Germany, wind tunnel tests, and a comparison measurement with the UAS-mounted aerosol particle measurement Universal Cloud and Aerosol Sounding System (UCASS) during a dust event over Cyprus, we show that the OPC-Pod can measure particle number concentrations in the range of 0.66–31 μm as well as particle size distributions. The agreement of the OPC-Pod with UCASS is good. Both instruments resolve a vertical profile of the Saharan dust event, with a prominent dust layer between 1500 and 2800 m MSL, with particle number concentrations up to 35 cm−3 for particles between 0.66 and 31 μm.

Open access
Vasileios Savvakis
,
Martin Schön
,
Matteo Bramati
,
Jens Bange
, and
Andreas Platis

Abstract

The negative effects of relative humidity to measurements of particulate matter (PM) due to hygroscopic growth are often not inherently handled by low-cost optical particle counters (OPCs). This study presents a new approach in constructing a miniaturized diffusion dryer, for use with an OPC mounted on an uncrewed aircraft system (UAS), namely, the DJI S900 (weight of 7.5 kg and flight endurance of 20 min) for short-term measurements under humid conditions. In this work, an OPC of type N3 (Alphasense) was employed alongside the dryer, with experiments both in the laboratory and outdoors. Evaluation of the dryer’s performance in a fog tank showed effective drying from almost saturated air to 41% relative humidity for 35 min, which is longer than the endurance of the UAS, and therefore sufficient. Changes in the flow rate through the OPC-N3 with the dryer showed a 17% reduction compared to an absent dryer, but the measured PM values remained unaffected. Airborne measurements were taken from four hovering flights near a governmental air pollution station (Mannheim-Nord, Germany) under humid conditions (88%–93%) where the system gave agreeable concentrations when the dryer was in place, but significantly overestimated all PM types without it. At a rural area near the Boundary Layer Field Site Falkenberg (Lindenberg, Germany), operated by the German Meteorological Service (DWD), vertical profiles inside a low-altitude cloud showed sharp increase in concentrations when the UAS entered the cloud layer, demonstrating its capability to accurately detect the layer base.

Open access
Matteo Bramati
,
Martin Schön
,
Daniel Schulz
,
Vasileios Savvakis
,
Yongtan Wang
,
Jens Bange
, and
Andreas Platis

Abstract

The use of small uncrewed aircraft systems (UAS) can effectively capture the wind profile in the lower atmospheric boundary layer. This study presents a calibration process to estimate the horizontal wind vector using a rotary-wing UAS in hovering conditions. This procedure does not require wind tunnels or meteorological masts, only the data from the flight control unit and a specific set of calibration flights. A model based on the UAS drag coefficient was proposed and compared to a traditional approach. Validation flights at the German Weather Service MOL-RAO observatory showed that the system can accurately predict wind speed and direction. A modified DJI S900 hexacopter with a Styrofoam sphere casing was used for the study and calibrated for wind speeds between 1 and 14 m s−1. Power spectral density analysis showed the system’s ability to resolve atmospheric eddies up to 0.1 Hz. The overall root-mean-square error was less than 0.7 m s−1 for wind speed and less than 8° for wind direction.

Open access
Jakob Boventer
,
Matteo Bramati
,
Vasileios Savvakis
,
Frank Beyrich
,
Markus Kayser
,
Andreas Platis
, and
Jens Bange

Abstract

One of the most widely used systems for wind speed and direction observations at meteorological sites is based on Doppler Wind LiDAR (DWL) technology. The wind vector derivation strategies of these instruments rely on the assumption of stationary and homogeneous horizontal wind, which is often not the case over heterogeneous terrain. This study focuses on the validation of two DWL systems, operated by the German Weather Service (DWD) and installed at the boundary layer field site Falkenberg (Lindenberg, Germany), with respect to measurements from a small, fixed-wing uncrewed aircraft system (UAS) of type MASC-3. A wind vector intercomparison at an altitude range from 100 to 500 m between DWL and UAS was performed, after a quality control of the aircraft’s data accuracy against a cup anemometer and wind vane mounted on a meteorological mast also operating at the location. Both DWL systems exhibit an overall root mean square difference in wind vector retrieval of less than 22% for wind speed and lower than 18° for wind direction. The enhancement or deterioration of these statistics is analyzed with respect to scanning height and atmospheric stability. The limitations of this type of validation approach are highlighted and accounted for in the analysis.

Open access