Preprints
https://doi.org/10.5194/amt-2024-49
https://doi.org/10.5194/amt-2024-49
21 May 2024
 | 21 May 2024
Status: this preprint is currently under review for the journal AMT.

A Low-cost UAV Coordinated Carbon observation Network (LUCCN): an analysis of environment impact on ground base measurement node

Xiaoyu Ren, Dongxu Yang, Yi Liu, Yong Wang, Ting Wang, Zhaonan Cai, Lu Yao, Tonghui Zhao, Jing Wang, and Zhe Jiang

Abstract. Most anthropogenic carbon dioxide (CO2) emissions originate from urban areas. To improve understandings of urban and regional emissions, we design and construct a low-cost UAV coordinated carbon observation network (LUCCN) which uses mid-accuracy (±1 ppm) CO2 sensors. In this paper, we introduce our multi-variable non-linear regression method for calibrating the non-dispersive infrared (NDIR) CO2 sensors for LUCCN’s ground stations. We tested our calibration method with concentration data collected at the Xinglong Atmospheric Background Observatory. With comparison against data simultaneously collected by a high-accuracy cavity ring-down spectrometer, we found the maximum standard deviation of LUCCN’s sensors to be 0.782 ppm in a controlled laboratory environment with a 1-second window size and 0.53 ppm in an outdoor environment with a 1-hour running average window size. As validation of LUCCN’s ground measurements, we identify and present consistent trends between local CO2 concentration variations and aerosol pollution events captured by the space-based moderate resolution imaging spectrometer (MODIS).

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Xiaoyu Ren, Dongxu Yang, Yi Liu, Yong Wang, Ting Wang, Zhaonan Cai, Lu Yao, Tonghui Zhao, Jing Wang, and Zhe Jiang

Status: open (until 06 Jul 2024)

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  • RC1: 'Comment on amt-2024-49', Anonymous Referee #1, 31 May 2024 reply
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Xiaoyu Ren, Dongxu Yang, Yi Liu, Yong Wang, Ting Wang, Zhaonan Cai, Lu Yao, Tonghui Zhao, Jing Wang, and Zhe Jiang
Xiaoyu Ren, Dongxu Yang, Yi Liu, Yong Wang, Ting Wang, Zhaonan Cai, Lu Yao, Tonghui Zhao, Jing Wang, and Zhe Jiang

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Short summary
We aim to verify the performance of the low-cost CO2 sensors (LUCCN). The measurements show that accuracies of LUCCNs are higher than the medium accuracy standard. And LUCCNs are also sensitive to the changes of CO2 concentrations. These results prove that the LUCCN can measure CO2 concentrations effectively, which means that LUCCN is a powerful tool to achieve the CO2 monitoring network.