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3 pages, 150 KiB

Open AccessEditorial

Atmospheric Measurements with Unmanned Aerial Systems (UAS)

by Marcelo I. Guzman

Atmosphere 2020, 11(11), 1208; https://doi.org/10.3390/atmos11111208 - 9 Nov 2020

Cited by 3 | Viewed by 4385

Abstract

This Special Issue provides the first literature collection focused on the development and implementation of unmanned aircraft systems (UAS) and their integration with sensors for atmospheric measurements on Earth [...] Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

Research

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24 pages, 25938 KiB

Open AccessArticle

Reviewing Wind Measurement Approaches for Fixed-Wing Unmanned Aircraft

by Alexander Rautenberg, Martin S. Graf, Norman Wildmann, Andreas Platis and Jens Bange

Atmosphere 2018, 9(11), 422; https://doi.org/10.3390/atmos9110422 - 28 Oct 2018

Cited by 43 | Viewed by 9135

Abstract

One of the biggest challenges in probing the atmospheric boundary layer with small unmanned aerial vehicles is the turbulent 3D wind vector measurement. Several approaches have been developed to estimate the wind vector without using multi-hole flow probes. This study compares commonly used [...] Read more.

One of the biggest challenges in probing the atmospheric boundary layer with small unmanned aerial vehicles is the turbulent 3D wind vector measurement. Several approaches have been developed to estimate the wind vector without using multi-hole flow probes. This study compares commonly used wind speed and direction estimation algorithms with the direct 3D wind vector measurement using multi-hole probes. This was done using the data of a fully equipped system and by applying several algorithms to the same data set. To cover as many aspects as possible, a wide range of meteorological conditions and common flight patterns were considered in this comparison. The results from the five-hole probe measurements were compared to the pitot tube algorithm, which only requires a pitot-static tube and a standard inertial navigation system measuring aircraft attitude (Euler angles), while the position is measured with global navigation satellite systems. Even less complex is the so-called no-flow-sensor algorithm, which only requires a global navigation satellite system to estimate wind speed and wind direction. These algorithms require temporal averaging. Two averaging periods were applied in order to see the influence and show the limitations of each algorithm. For a window of 4 min, both simplifications work well, especially with the pitot-static tube measurement. When reducing the averaging period to 1 min and thereby increasing the temporal resolution, it becomes evident that only circular flight patterns with full racetracks inside the averaging window are applicable for the no-flow-sensor algorithm and that the additional flow information from the pitot-static tube improves precision significantly. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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22 pages, 10074 KiB

Open AccessArticle

Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Measurement System Description and Mass Balance Approach

by Shuting Yang, Robert W. Talbot, Michael B. Frish, Levi M. Golston, Nicholas F. Aubut, Mark A. Zondlo, Christopher Gretencord and James McSpiritt

Atmosphere 2018, 9(10), 383; https://doi.org/10.3390/atmos9100383 - 1 Oct 2018

Cited by 65 | Viewed by 8363

Abstract

Natural gas is an abundant resource across the United States, of which methane (CH₄) is the main component. About 2% of extracted CH₄ is lost through leaks. The Remote Methane Leak Detector (RMLD)-Unmanned Aerial Vehicle (UAV) system was developed to [...] Read more.

Natural gas is an abundant resource across the United States, of which methane (CH₄) is the main component. About 2% of extracted CH₄ is lost through leaks. The Remote Methane Leak Detector (RMLD)-Unmanned Aerial Vehicle (UAV) system was developed to investigate natural gas fugitive leaks in this study. The system is composed of three major technologies: miniaturized RMLD (mini-RMLD) based on Backscatter Tunable Diode Laser Absorption Spectroscopy (TDLAS), an autonomous quadrotor UAV and simplified quantification and localization algorithms. With a miniaturized, downward-facing RMLD on a small UAV, the system measures the column-integrated CH₄ mixing ratio and can semi-autonomously monitor CH₄ leakage from sites associated with natural gas production, providing an advanced capability in detecting leaks at hard-to-access sites compared to traditional manual methods. Automated leak characterization algorithms combined with a wireless data link implement real-time leak quantification and reporting. This study placed particular emphasis on the RMLD-UAV system description and the quantification algorithm development based on a mass balance approach. Early data were gathered to test the prototype system and to evaluate the algorithm performance. The quantification algorithm derived in this study tended to underestimate the gas leak rates and yielded unreliable estimations in detecting leaks under 7

\times 10^{- 6}

m³/s (~1 Standard Cubic Feet per Hour (SCFH)). Zero-leak cases can be ascertained via a skewness indicator, which is unique and promising. The influence of the systematic error was investigated by introducing simulated noises, of which Global Positioning System (GPS) noise presented the greatest impact on leak rate errors. The correlation between estimated leak rates and wind conditions were investigated, and steady winds with higher wind speeds were preferred to get better leak rate estimations, which was accurate to approximately 50% during several field trials. High precision coordinate information from the GPS, accurate wind measurements and preferred wind conditions, appropriate flight strategy and the relative steady survey height of the system are the crucial factors to optimize the leak rate estimations. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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25 pages, 7815 KiB

Open AccessArticle

The Characteristics and Contributing Factors of Air Pollution in Nanjing: A Case Study Based on an Unmanned Aerial Vehicle Experiment and Multiple Datasets

by Shudao Zhou, Shuling Peng, Min Wang, Ao Shen and Zhanhua Liu

Atmosphere 2018, 9(9), 343; https://doi.org/10.3390/atmos9090343 - 2 Sep 2018

Cited by 37 | Viewed by 6309

Abstract

Unmanned aerial vehicle (UAV) experiments, multiple datasets from ground-based stations and satellite remote sensing platforms, and backward trajectory models were combined to investigate the characteristics and influential mechanisms of the air pollution episode that occurred in Nanjing during 3–4 December 2017. Before the [...] Read more.

Unmanned aerial vehicle (UAV) experiments, multiple datasets from ground-based stations and satellite remote sensing platforms, and backward trajectory models were combined to investigate the characteristics and influential mechanisms of the air pollution episode that occurred in Nanjing during 3–4 December 2017. Before the experiments, the position of the detector mounted on a UAV that was minimally disturbed by the rotation of the rotors was analyzed based on computational fluid dynamics (CFD) simulations. The combined analysis indicated that the surface meteorological conditions—high relative humidity, low wind speed, and low temperature—were conducive to the accumulation of PM_2.5. Strongly intense temperature inversion layers and the low thickness of the atmospheric mixed layer could have resulted in elevated PM_2.5 mass concentrations. In the early stage, air pollution was affected by the synoptic circulation of the homogenous pressure field and low wind speeds, and the pollutants mainly originated from emissions from surrounding areas. The aggravated pollution was mainly attributed to the cold front and strong northwesterly winds above 850 hPa, and the pollutants mostly originated from the long-distance transport of emissions with northwesterly winds, mainly from the Beijing‒Tianjin‒Hebei (BTH) region and its surrounding areas. This long-distance transport predominated during this event. The air pollution level and aerosol optical depth (AOD) were positively correlated with respect to their spatial distributions; they could reflect shifts in areas of serious pollution. Pollution was concentrated in Anhui Province when it was alleviated in Nanjing. Polluted dust, polluted continental and smoke aerosols were primarily observed during this process. In particular, polluted dust aerosols accounted for a major part of the transport stage, and existed between the surface and 4 km. Moreover, the average extinction coefficient at lower altitudes (<1 km) was higher for aerosol deposition. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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17 pages, 4969 KiB

Open AccessArticle

Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate

by Levi M. Golston, Nicholas F. Aubut, Michael B. Frish, Shuting Yang, Robert W. Talbot, Christopher Gretencord, James McSpiritt and Mark A. Zondlo

Atmosphere 2018, 9(9), 333; https://doi.org/10.3390/atmos9090333 - 23 Aug 2018

Cited by 72 | Viewed by 8836

Abstract

We describe a set of methods for locating and quantifying natural gas leaks using a small unmanned aerial system equipped with a path-integrated methane sensor. The algorithms are developed as part of a system to enable the continuous monitoring of methane, supported by [...] Read more.

We describe a set of methods for locating and quantifying natural gas leaks using a small unmanned aerial system equipped with a path-integrated methane sensor. The algorithms are developed as part of a system to enable the continuous monitoring of methane, supported by a series of over 200 methane release trials covering 51 release location and flow rate combinations. The system was found throughout the trials to reliably distinguish between cases with and without a methane release down to 2 standard cubic feet per hour (0.011 g/s). Among several methods evaluated for horizontal localization, the location corresponding to the maximum path-integrated methane reading performed best with a mean absolute error of 1.2 m if the results from several flights are spatially averaged. Additionally, a method of rotating the data around the estimated leak location according to the wind is developed, with the leak magnitude calculated from the average crosswind integrated flux in the region near the source location. The system is initially applied at the well pad scale (100–1000 m² area). Validation of these methods is presented including tests with unknown leak locations. Sources of error, including GPS uncertainty, meteorological variables, data averaging, and flight pattern coverage, are discussed. The techniques described here are important for surveys of small facilities where the scales for dispersion-based approaches are not readily applicable. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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29 pages, 14528 KiB

Open AccessArticle

Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)—The Hailuoto 2017 Campaign

by Stephan T. Kral, Joachim Reuder, Timo Vihma, Irene Suomi, Ewan O’Connor, Rostislav Kouznetsov, Burkhard Wrenger, Alexander Rautenberg, Gabin Urbancic, Marius O. Jonassen, Line Båserud, Björn Maronga, Stephanie Mayer, Torge Lorenz, Albert A. M. Holtslag, Gert-Jan Steeneveld, Andrew Seidl, Martin Müller, Christian Lindenberg, Carsten Langohr, Hendrik Voss, Jens Bange, Marie Hundhausen, Philipp Hilsheimer and Markus Schygulla Show full author list Hide full author list

Atmosphere 2018, 9(7), 268; https://doi.org/10.3390/atmos9070268 - 16 Jul 2018

Cited by 48 | Viewed by 11365

Abstract

The aim of the research project “Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)” is to substantially increase the understanding of the stable atmospheric boundary layer (SBL) through a combination of well-established and innovative observation methods as well as by [...] Read more.

The aim of the research project “Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)” is to substantially increase the understanding of the stable atmospheric boundary layer (SBL) through a combination of well-established and innovative observation methods as well as by models of different complexity. During three weeks in February 2017, a first field campaign was carried out over the sea ice of the Bothnian Bay in the vicinity of the Finnish island of Hailuoto. Observations were based on ground-based eddy-covariance (EC), automatic weather stations (AWS) and remote-sensing instrumentation as well as more than 150 flight missions by several different Unmanned Aerial Vehicles (UAVs) during mostly stable and very stable boundary layer conditions. The structure of the atmospheric boundary layer (ABL) and above could be resolved at a very high vertical resolution, especially close to the ground, by combining surface-based measurements with UAV observations, i.e., multicopter and fixed-wing profiles up to 200 m agl and 1800

m

agl, respectively. Repeated multicopter profiles provided detailed information on the evolution of the SBL, in addition to the continuous SODAR and LIDAR wind measurements. The paper describes the campaign and the potential of the collected data set for future SBL research and focuses on both the UAV operations and the benefits of complementing established measurement methods by UAV measurements to enable SBL observations at an unprecedented spatial and temporal resolution. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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16 pages, 12841 KiB

Open AccessArticle

Considerations for Atmospheric Measurements with Small Unmanned Aircraft Systems

by Jamey D. Jacob, Phillip B. Chilson, Adam L. Houston and Suzanne Weaver Smith

Atmosphere 2018, 9(7), 252; https://doi.org/10.3390/atmos9070252 - 5 Jul 2018

Cited by 72 | Viewed by 7969

Abstract

This paper discusses results of the CLOUD-MAP (Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics) project dedicated to developing, fielding, and evaluating integrated small unmanned aircraft systems (sUAS) for enhanced atmospheric physics measurements. The project team includes atmospheric scientists, meteorologists, engineers, [...] Read more.

This paper discusses results of the CLOUD-MAP (Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics) project dedicated to developing, fielding, and evaluating integrated small unmanned aircraft systems (sUAS) for enhanced atmospheric physics measurements. The project team includes atmospheric scientists, meteorologists, engineers, computer scientists, geographers, and chemists necessary to evaluate the needs and develop the advanced sensing and imaging, robust autonomous navigation, enhanced data communication, and data management capabilities required to use sUAS in atmospheric physics. Annual integrated evaluation of the systems in coordinated field tests are being used to validate sensor performance while integrated into various sUAS platforms. This paper focuses on aspects related to atmospheric sampling of thermodynamic parameters with sUAS, specifically sensor integration and calibration/validation, particularly as it relates to boundary layer profiling. Validation of sensor output is performed by comparing measurements with known values, including instrumented towers, radiosondes, and other validated sUAS platforms. Experiments to determine the impact of sensor location and vehicle operation have been performed, with sensor aspiration a major factor. Measurements are robust provided that instrument packages are properly mounted in locations that provide adequate air flow and proper solar shielding. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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21 pages, 3728 KiB

Open AccessArticle

New Setup of the UAS ALADINA for Measuring Boundary Layer Properties, Atmospheric Particles and Solar Radiation

by Konrad Bärfuss, Falk Pätzold, Barbara Altstädter, Endres Kathe, Stefan Nowak, Lutz Bretschneider, Ulf Bestmann and Astrid Lampert

Atmosphere 2018, 9(1), 28; https://doi.org/10.3390/atmos9010028 - 17 Jan 2018

Cited by 42 | Viewed by 7083 | Correction

Abstract

The unmanned research aircraft ALADINA (Application of Light-weight Aircraft for Detecting in situ Aerosols) has been established as an important tool for boundary layer research. For simplified integration of additional sensor payload, a flexible and reliable data acquisition system was developed at the [...] Read more.

The unmanned research aircraft ALADINA (Application of Light-weight Aircraft for Detecting in situ Aerosols) has been established as an important tool for boundary layer research. For simplified integration of additional sensor payload, a flexible and reliable data acquisition system was developed at the Institute of Flight Guidance, Technische Universität (TU) Braunschweig. The instrumentation consists of sensors for temperature, humidity, three-dimensional wind vector, position, black carbon, irradiance and atmospheric particles in the diameter range of ultra-fine particles up to the accumulation mode. The modular concept allows for straightforward integration and exchange of sensors. So far, more than 200 measurement flights have been performed with the robustly-engineered system ALADINA at different locations. The obtained datasets are unique in the field of atmospheric boundary layer research. In this study, a new data processing method for deriving parameters with fast resolution and to provide reliable accuracies is presented. Based on tests in the field and in the laboratory, the limitations and verifiability of integrated sensors are discussed. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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5243 KiB

Open AccessArticle

Data Analysis of the TK-1G Sounding Rocket Installed with a Satellite Navigation System

by Lesong Zhou, Zheng Sheng, Zhiqiang Fan and Qixiang Liao

Atmosphere 2017, 8(10), 199; https://doi.org/10.3390/atmos8100199 - 11 Oct 2017

Cited by 9 | Viewed by 6266

Abstract

This article gives an in-depth analysis of the experimental data of the TK-1G sounding rocket installed with the satellite navigation system. It turns out that the data acquisition rate of the rocket sonde is high, making the collection of complete trajectory and meteorological [...] Read more.

This article gives an in-depth analysis of the experimental data of the TK-1G sounding rocket installed with the satellite navigation system. It turns out that the data acquisition rate of the rocket sonde is high, making the collection of complete trajectory and meteorological data possible. By comparing the rocket sonde measurements with those obtained by virtue of other methods, we find that the rocket sonde can be relatively precise in measuring atmospheric parameters within the scope of 20–60 km above the ground. This establishes the fact that the TK-1G sounding rocket system is effective in detecting near-space atmospheric environment. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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10426 KiB

Open AccessEditor’s ChoiceArticle

Development of an Unmanned Aerial Vehicle for the Measurement of Turbulence in the Atmospheric Boundary Layer

by Brandon M. Witte, Robert F. Singler and Sean C. C. Bailey

Atmosphere 2017, 8(10), 195; https://doi.org/10.3390/atmos8100195 - 4 Oct 2017

Cited by 64 | Viewed by 9245

Abstract

This paper describes the components and usage of an unmanned aerial vehicle developed for measuring turbulence in the atmospheric boundary layer. A method of computing the time-dependent wind speed from a moving velocity sensor data is provided. The physical system built to implement [...] Read more.

This paper describes the components and usage of an unmanned aerial vehicle developed for measuring turbulence in the atmospheric boundary layer. A method of computing the time-dependent wind speed from a moving velocity sensor data is provided. The physical system built to implement this method using a five-hole probe velocity sensor is described along with the approach used to combine data from the different on-board sensors to allow for extraction of the wind speed as a function of time and position. The approach is demonstrated using data from three flights of two unmanned aerial vehicles (UAVs) measuring the lower atmospheric boundary layer during transition from a stable to convective state. Several quantities are presented and show the potential for extracting a range of atmospheric boundary layer statistics. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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4061 KiB

Open AccessArticle

Vertical Sampling Scales for Atmospheric Boundary Layer Measurements from Small Unmanned Aircraft Systems (sUAS)

by Benjamin L. Hemingway, Amy E. Frazier, Brian R. Elbing and Jamey D. Jacob

Atmosphere 2017, 8(9), 176; https://doi.org/10.3390/atmos8090176 - 17 Sep 2017

Cited by 41 | Viewed by 8198

Abstract

The lowest portion of the Earth’s atmosphere, known as the atmospheric boundary layer (ABL), plays an important role in the formation of weather events. Simple meteorological measurements collected from within the ABL, such as temperature, pressure, humidity, and wind velocity, are key to [...] Read more.

The lowest portion of the Earth’s atmosphere, known as the atmospheric boundary layer (ABL), plays an important role in the formation of weather events. Simple meteorological measurements collected from within the ABL, such as temperature, pressure, humidity, and wind velocity, are key to understanding the exchange of energy within this region, but conventional surveillance techniques such as towers, radar, weather balloons, and satellites do not provide adequate spatial and/or temporal coverage for monitoring weather events. Small unmanned aircraft, or aerial, systems (sUAS) provide a versatile, dynamic platform for atmospheric sensing that can provide higher spatio-temporal sampling frequencies than available through most satellite sensing methods. They are also able to sense portions of the atmosphere that cannot be measured from ground-based radar, weather stations, or weather balloons and have the potential to fill gaps in atmospheric sampling. However, research on the vertical sampling scales for collecting atmospheric measurements from sUAS and the variabilities of these scales across atmospheric phenomena (e.g., temperature and humidity) is needed. The objective of this study is to use variogram analysis, a common geostatistical technique, to determine optimal spatial sampling scales for two atmospheric variables (temperature and relative humidity) captured from sUAS. Results show that vertical sampling scales of approximately 3 m for temperature and 1.5–2 m for relative humidity were sufficient to capture the spatial structure of these phenomena under the conditions tested. Future work is needed to model these scales across the entire ABL as well as under variable conditions. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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1 pages, 153 KiB

Open AccessCorrection

Correction: Bärfuss et al. New Setup of the UAS ALADINA for Measuring Boundary Layer Properties, Atmospheric Particles and Solar Radiation. Atmosphere, 2018, 9, 28

by Konrad Bärfuss, Falk Pätzold, Barbara Altstädter, Endres Kathe, Stefan Nowak, Lutz Bretschneider, Ulf Bestmann and Astrid Lampert

Atmosphere 2018, 9(8), 306; https://doi.org/10.3390/atmos9080306 - 7 Aug 2018

Viewed by 3550

Abstract

The authors would like to correct the published article [1] concerning acknowledgments as follows[...] Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

2438 KiB

Open AccessEditor’s ChoicePerspective

Unmanned Aerial Systems for Monitoring Trace Tropospheric Gases

by Travis J. Schuyler and Marcelo I. Guzman

Atmosphere 2017, 8(10), 206; https://doi.org/10.3390/atmos8100206 - 23 Oct 2017

Cited by 56 | Viewed by 16768

Abstract

The emission of greenhouse gases (GHGs) has changed the composition of the atmosphere during the Anthropocene. Accurately documenting the sources and magnitude of GHGs emission is an important undertaking for discriminating the contributions of different processes to radiative forcing. Currently there is no [...] Read more.

The emission of greenhouse gases (GHGs) has changed the composition of the atmosphere during the Anthropocene. Accurately documenting the sources and magnitude of GHGs emission is an important undertaking for discriminating the contributions of different processes to radiative forcing. Currently there is no mobile platform that is able to quantify trace gases at altitudes <100 m above ground level that can achieve spatiotemporal resolution on the order of meters and seconds. Unmanned aerial systems (UASs) can be deployed on-site in minutes and can support the payloads necessary to quantify trace gases. Therefore, current efforts combine the use of UASs available on the civilian market with inexpensively designed analytical systems for monitoring atmospheric trace gases. In this context, this perspective introduces the most relevant classes of UASs available and evaluates their suitability to operate three kinds of detectors for atmospheric trace gases. The three subsets of UASs discussed are: (1) micro aerial vehicles (MAVs); (2) vertical take-off and landing (VTOL); and, (3) low-altitude short endurance (LASE) systems. The trace gas detectors evaluated are first the vertical cavity surface emitting laser (VCSEL), which is an infrared laser-absorption technique; second two types of metal-oxide semiconductor sensors; and, third a modified catalytic type sensor. UASs with wingspans under 3 m that can carry up to 5 kg a few hundred meters high for at least 30 min provide the best cost and convenience compromise for sensors deployment. Future efforts should be focused on the calibration and validation of lightweight analytical systems mounted on UASs for quantifying trace atmospheric gases. In conclusion, UASs offer new and exciting opportunities to study atmospheric composition and its effect on weather patterns and climate change. Full article

(This article belongs to the Special Issue Atmospheric Measurements with Unmanned Aerial Systems (UAS))

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