the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Dec 2024
The Flying Laboratory FLab: Development and application of a UAS to measure aerosol particles and trace gases in the lower troposphere
Abstract. Unmanned aircraft systems (UAS) are gradually being established in environmental research to study boundary layer conditions and phenomena in situ; however, due to payload limitations, UAS can typically measure only a limited number of atmospheric variables simultaneously. Here we present the Flying Laboratory (FLab), a hexacopter equipped with six instruments to measure aerosol particles (particle number concentration and size distribution; PM1/2.5 and black carbon mass concentration), trace gases (CO2, O3), and meteorological variables (temperature, relative humidity, pressure, wind) in the lower troposphere in real time and with high temporal resolution. The instrumentation has been selected to provide an overview of relevant variables in urban and semi-urban environments and especially in the vicinity of aerosol sources. This paper describes the development of the technical setup of the Flying Laboratory, the characterization of the measurements with respect to horizontal and vertical motion of the UAS, and the optimization of measurement flight patterns. During two field experiments, FLab was applied to bridge the gap between ground-based and aircraft-based profiling measurements and to perform hourly vertical profiling flights up to 300 m above a ground-based reference station for eight hours. These applications demonstrate the capability of FLab to capture the evolution of the lower convective boundary layer during the day and the vertical particle transport in the afternoon up to 200 m above ground.
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RC1: 'Comment on egusphere-2024-3566', Anonymous Referee #1, 03 Jan 2025
This manuscript introduces the Flying Laboratory (FLab), a hexacopter equipped with six instruments to measure aerosol properties, trace gases, and meteorological parameters in real time with high temporal resolution. Designed to monitor urban and semi-urban environments near aerosol sources, FLab bridges the gap between ground-based and aircraft profiling. During field experiments, it performed hourly vertical profiling flights up to 300 m for eight hours, capturing lower convective boundary layer dynamics and afternoon vertical particle transport. This study details the FLab's technical setup, measurement characterization, and optimized flight patterns, showcasing its effectiveness in environmental monitoring. Overall, the manuscript is well-written. The results are interesting and valuable to the literature. I have some concerns especially for the measurement of wind and the impacts of flight speed on the pollutant measurement.
- Description of the UAS: Please provide additional details about the UAS, including its maximum flight speed, ascent and descent rates, and vertical and horizontal operational ranges. This information will help contextualize the measurements.
- Line 150: Include the full names of the instruments mentioned in the main text to ensure clarity and accessibility for readers unfamiliar with the abbreviations.
- Lines 155-156: The anemometer was installed 110 cm above the UAS. Please discuss how UAS vibrations during flight might influence wind measurements. Have any corrections, such as those derived from wind tunnel experiments, been implemented?
- Lines 155-156: Explain whether solar heating could affect the relative humidity and temperature measurements obtained by the anemometer.
- Line 161 CPC measurement: Provide further details on why the CPC and OZN did not require in-flight adjustments apart from calibration. Additionally, clarify the CPC inlet's placement and assess the potential impact of UAS-induced airflow on the measurements.
- Lines 218-219: Consider rephrasing to "If there is no difference in wind speeds, it indicates 100% agreement between the FLab and MoLa anemometers" for improved clarity. The current phrasing could be misinterpreted as suggesting no difference exists between the two, which contradicts Figure 2.
- Figure 2: Emphasize in the text that these results correspond to maximum propeller rotation rates. Propeller-induced disturbances may be smaller during hovering
- Lines 224-226: Clarify whether "lower mounting height" refers to the UAS or the anemometer. The current phrasing could lead to confusion and appear inconsistent with Figure 2.
- Lines 230-235: Again, have experiments, such as wind tunnel tests, been performed to assess the effects of UAS tilting on anemometer wind measurements? If not, consider providing recommendations for future research to address this potential limitation.
- Lines 280-281: 370 nm corresponds to the light absorption of brown carbon. It may not be appropriate to state that black carbon concentration was determined from the 370 nm measurement. Consider rephrasing to "light-absorbing species."
- Lines 302-303: Include a brief description of the Allan variance to help readers unfamiliar with this analytical method.
- Lines 333-336: Provide guidance on optimal averaging times for different instruments and discuss whether these recommendations might vary under different flight conditions, such as varying speeds or wind intensities.
- Lines 362-363: Rephrase or include an example to clarify the method of normalization used in the study.
- Lines 365-368: This could be due to the fact that the flights were conducted under relatively homogeneous conditions as the authors mentioned in line 277. However, how does the UAS perform in capturing pollutant concentration variations at different flight speeds over heterogeneous land surfaces?
- Figure 4e: Where did the authors obtain the DJI UAS wind speed data? Have the authors compared the DJI UAS wind speed data with anemometer measurements during hovering? Additionally, address the uncertainty associated with the anemometer and whether environmental factors such as temperature, humidity, and pressure could influence its performance.
- Lines 410-415: Clarify that the anemometer measured horizontal wind in this section.
- Lines 460-462: While the temperature and humidity sensors seem to equilibrate quickly at high flight speeds, how do the CPC and pollutant sensors compare? Their response times might be slower, particularly given their placement underneath the UAS. Have the authors tested how these sensors respond to rapid changes in flight conditions, such as transitioning from high-speed ascending flight to hovering? If they respond quickly, the concentrations would likely stabilize during hovering. If not, there could be delays or noticeable overshoots or drops in concentration readings during such transitions.
Citation: https://doi.org/10.5194/egusphere-2024-3566-RC1 -
RC2: 'Comment on egusphere-2024-3566', Anonymous Referee #2, 03 Jan 2025
Overview:
The manuscript outlines the development and testing of a Flying Laboratory Flab using an uncrewed aerial system equipped with various instruments to measure meteorological parameters and in situ trace gases and aerosol particles. The Flab is equipped with an anemometer for measuring wind speed and direction along with temperature, humidity and pressure, CO2 and O3 analyzers, instruments for measuring aerosol particles. The manuscript outlines various tests to determine data uncertainties and optimal flight parameters for data accuracy and precision. The treatment is thorough and the manuscript is well written. I recommend this manuscript for publication.
Minor Comments:
Lines 37-44: In addition to the limitations outlined by the authors, lidar instruments specifically have near-field dead zones and when used from the ground, cause there to be a lack of continuity between ground observations and remote observations. UAS are ideal for bridging this gap.
Line 125 and line 132-134. There are some statements here which are confusing. I believe that all of the language here is used to describe the aerosol instruments but when it states ‘an Arduino Uno is used to store the processed instrument data on a common SD card for all instruments’ it could be interpreted that all instruments on board are backed up to the SD card. Perhaps it would make more sense to describe that the ozone monitor and the aethalometer only use internal storage (is that the correct interpretation?). Start with the data storage that is independent and then qualify the integrated data storage (and transmittance) for the aerosol instruments as only for those aerosol instruments.
Line 151: Which instruments had RS232 interfaces which required modification. Just list parenthetically.
Line 371: requires a space between parentheses and ‘which’
Lines 410-415: The statement ‘the wind speed determined by the UAS is almost constant within 0.1 ms-1 with respect to the reference wind speed at all altitudes and vertical velocities’ implies that there should be some indication of the reference wind speed in Figures 5 and 6 but there is none. What do you mean by reference wind speed? Also the statement ‘the UAS-derived wind speed is unreliable with the payload attached’ is confusing. Are there observations of UAS-derived winds which are accurate but not so once the payload is attached? Reference performance of only UAS-derived winds with no payload or something to clarify. Or this paragraph needs some statement to agreement with reference wind speeds – the figures that are referenced are only comparing the anemometer and UAS but I don’t believe either of them to be considered reference.
Citation: https://doi.org/10.5194/egusphere-2024-3566-RC2
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