The Multi-Purpose Airborne Sensor Carrier MASC-3 for Wind and Turbulence Measurements in the Atmospheric Boundary Layer

Validating CFD Predictions of Flow over an Escarpment Using Ground-Based and Airborne Measurement Devices

Micrometeorological observations from a tower, an eddy-covariance (EC) station and an unmanned aircraft system (UAS) at the WINSENT test-site are used to validate a computational fluid dynamics (CFD) model, driven by a mesoscale model. The observation site is characterised by a forested escarpment in a complex terrain. A two-day measurement campaign with a flow almost perpendicular to the escarpment is analysed. The first day is dominated by high wind speeds, while, on the second one, calm wind conditions are present. Despite some minor differences, the flow structure, analysed in terms of horizontal wind speeds, wind direction and inclination angles shows similarities for both days. A real-time strategy is used for the CFD validation with the UAS measurement, where the model follows spatially and temporally the aircraft. This strategy has proved to be successful. Stability indices such as the potential temperature and the bulk Richardson number are calculated to diagnose atmospheric boundary layer (ABL) characteristics up to the highest flight level. The calculated bulk Richardson values indicate a dynamically unstable region behind the escarpment and near the ground for both days. At higher altitudes, the ABL is returning to a near neutral state. The same characteristics are found in the model but only for the first day. The second day, where shear instabilities are more dominant, is not well simulated. UAS proves its great value for sensing the flow over complex terrains at high altitudes and we demonstrate the usefulness of UAS for validating and improving models.

Gathering Pipeline Methane Emissions in Utica Shale Using an Unmanned Aerial Vehicle and Ground-Based Mobile Sampling

The United States Environmental Protection Agency Greenhouse Gas Inventory only recently updated the emission factors of natural gas gathering pipelines in April 2019 from the previous estimates based on a 1990s study of distribution pipelines. Additional measurements are needed from different basins for more accurate assessments of methane emissions from natural gas midstream industries and hence the overall climate implications of natural gas as the interim major energy source for the next decade. We conducted an unmanned aerial vehicle (UAV) survey and a ground-based vehicle sampling campaign targeting gathering pipeline systems in the Utica Shale from March to April in 2019. Out of 73 km of pipeline systems surveyed, we found no leaks on pipelines and two leaks on an accessory block valve with leak rates of 3.8 ± 0.4 and 7.6 ± 0.8 mg/s. The low leak frequency phenomenon was also observed in the only existing gathering pipeline study in Fayetteville Shale. The UAV sampling system facilitated ease of access, broadened the availability of pipelines for leak detection, and was estimated to detect methane leaks down to 0.07 g/s using Gaussian dispersion modeling. For future UAV surveys adopting similar instrument setup and dispersion models, we recommend arranging controlled release experiments first to understand the system’s detection limit and choosing sampling days with steady and low wind speeds (2 m/s).

Unmanned Aerial Systems for Investigating the Polar Atmospheric Boundary Layer—Technical Challenges and Examples of Applications

Unmanned aerial systems (UAS) fill a gap in high-resolution observations of meteorological parameters on small scales in the atmospheric boundary layer (ABL). Especially in the remote polar areas, there is a strong need for such detailed observations with different research foci. In this study, three systems are presented which have been adapted to the particular needs for operating in harsh polar environments: The fixed-wing aircraft M 2 AV with a mass of 6 kg, the quadrocopter ALICE with a mass of 19 kg, and the fixed-wing aircraft ALADINA with a mass of almost 25 kg. For all three systems, their particular modifications for polar operations are documented, in particular the insulation and heating requirements for low temperatures. Each system has completed meteorological observations under challenging conditions, including take-off and landing on the ice surface, low temperatures (down to −28 ∘ C), icing, and, for the quadrocopter, under the impact of the rotor downwash. The influence on the measured parameters is addressed here in the form of numerical simulations and spectral data analysis. Furthermore, results from several case studies are discussed: With the M 2 AV, low-level flights above leads in Antarctic sea ice were performed to study the impact of areas of open water within ice surfaces on the ABL, and a comparison with simulations was performed. ALICE was used to study the small-scale structure and short-term variability of the ABL during a cruise of RV Polarstern to the 79 ∘ N glacier in Greenland. With ALADINA, aerosol measurements of different size classes were performed in Ny-Ålesund, Svalbard, in highly complex terrain. In particular, very small, freshly formed particles are difficult to monitor and require the active control of temperature inside the instruments. The main aim of the article is to demonstrate the potential of UAS for ABL studies in polar environments, and to provide practical advice for future research activities with similar systems.

Orbit Angular Momentum MIMO with Mode Selection for UAV-Assisted A2G Networks

As an emerging solution for line-of-sight (LOS) wireless communications, in air-to-ground (A2G) channels, the unmanned aerial vehicle (UAV), and allowing the dynamic and flexible network deployments enables the supplement or/and replacement of the terrestrial base stations (BSs). However, in conventional multiple-input-multiple-output (MIMO) systems, high-speed communications are significantly limited by channel crosstalks and spectrum scarcities. An orbit angular momentum (OAM) wireless network, allowing co-existence of multiple physical channels within the same frequency band, offers new degrees of freedom to address this dilemma. In this paper, we investigate the UAV-based A2G radio vortex wireless networks and study its channel model. Then we propose a branch and bound search-based mode selection (BBS-MS) scheme, which uses the spatial distribution characteristics of vortex beams to optimize the spectrum efficiency (SE). Theoretical derivations and numerical results demonstrate that our developed BBS-MS scheme can obtain the optimal performance, which outperforms conventional OAM-based MIMO systems. Also, it possesses a lower complexity compared with exhaustive searches.

A Near-Field Gaussian Plume Inversion Flux Quantification Method, Applied to Unmanned Aerial Vehicle Sampling

The accurate quantification of methane emissions from point sources is required to better quantify emissions for sector-specific reporting and inventory validation. An unmanned aerial vehicle (UAV) serves as a platform to sample plumes near to source. This paper describes a near-field Gaussian plume inversion (NGI) flux technique, adapted for downwind sampling of turbulent plumes, by fitting a plume model to measured flux density in three spatial dimensions. The method was refined and tested using sample data acquired from eight UAV flights, which measured a controlled release of methane gas. Sampling was conducted to a maximum height of 31 m (i.e. above the maximum height of the emission plumes). The method applies a flux inversion to plumes sampled near point sources. To test the method, a series of random walk sampling simulations were used to derive an NGI upper uncertainty bound by quantifying systematic flux bias due to a limited spatial sampling extent typical for short-duration small UAV flights (less than 30 min). The development of the NGI method enables its future use to quantify methane emissions for point sources, facilitating future assessments of emissions from specific source-types and source areas. This allows for atmospheric measurement-based fluxes to be derived using downwind UAV sampling for relatively rapid flux analysis, without the need for access to difficult-to-reach areas.