UAV-based sampling systems to analyse greenhouse gases and volatile organic compounds encompassing compound-specific stable isotope analysis

نویسندگان

چکیده

Abstract. The study herein reports on the development and testing of sampling systems (and subsequent analytical setups) that were deployed an unmanned aerial vehicle (UAV) for purpose analysing greenhouse gases (GHGs) volatile organic compounds (VOCs) in lower atmospheric boundary layer. Two devices, both which can be mounted to UAV with a payload capability greater than 1 kg, tested respective analysis specific GHGs (carbon dioxide, CO2, methane, CH4) VOCs (chlorinated ethenes, CEs). gas analyses included measurements molar amounts stable carbon isotope ratios. In addition compound calibration laboratory, functionality samplers UAV-based was field. Atmospheric air either flushed through sorbent tubes VOC or collected sampled glass vials GHG analysis. measurement setup achieved analyte mass recovery rates 63 %–100 % (more favourable chlorinated ethenes), when prepared from gaseous liquid standards, reached precision (2σ) better 0.7 ‰ δ13C values range 0.35–4.45 nmol. UAV-equipped over two field campaigns designed (1) compare manual UAV-collected samples taken up vertical profile at forest site (2) identify potential emissions CH4 former domestic waste dump. CO2 whole ≤7.3 µmol mol−1 ≤0.3 ≤0.03 ≤0.2 working standards. results sample sufficiently accurate detect localise landfill secured dump using level flight. Vertical profiles location showed causally comprehensive pattern ratios but also falsification positional accuracy UAV-assisted due influence rotor downwash. demonstrate presented here represent viable tool background monitoring, as well evaluating identifying emission sources. By expanding part atmosphere practicably horizontal axes, UAV-capable systems, allow compound-specific (CSIA), may facilitate improved understanding surface–atmosphere fluxes trace gas.

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ژورنال

عنوان ژورنال: Atmospheric Measurement Techniques

سال: 2023

ISSN: ['1867-1381', '1867-8548']

DOI: https://doi.org/10.5194/amt-16-513-2023