24 Jul 2023
 | 24 Jul 2023
Status: this preprint is currently under review for the journal AMT.

Application of a new UAV measurement methodology to the quantification of CO2 and CH4 emissions from a major coking plant

Tianran Han, Conghui Xie, Yayong Liu, Yanrong Yang, Yuheng Zhang, Yufei Huang, Xiangyu Gao, Xiaohua Zhang, Fangmin Bao, and Shao-Meng Li

Abstract. The development in unmanned aerial vehicle (UAV) technologies over the past decade has led to a plethora of platforms that can potentially enable greenhouse gas measurements over the 3-dimensional space. Here, we report the development of a new air sampler, consisting of a pumped stainless tube of 150 m in length with controlled time-stamping, and its deployment from an industrial UAV to quantify CO2 and CH4 emissions from the main coking plant stacks of a major steel maker in eastern China. During flights, the air sampler starts sampling as soon as the UAV takes off, and stops sampling after landing. The air sample is immediately analyzed upon retrieval with a CRDS gas analyzer for CO2 and CH4 mixing ratios. Laboratory tests show that the time series of CO2 and CH4 measured using the sampling system is smoothed when compared to online measurement by the CRDS analyzer. Further analyses show that the smoothing is akin to a convolution of the true time series signals with a heavy-tailed digital filter. For field test, the air sampler was mounted on the UAV and flown virtual boxes around two stacks in the coking plant at Shagang Steel Group. Mole fractions of CO2 and CH4 in air and meteorological parameters were measured from the UAV during the test flight. A mass-balance computational algorithm was used on the data to estimate the CO2 and CH4 emission rates from the stacks. Using this algorithm, the emission rates for the two stacks from the coking plant were calculated to be 0.12 ± 0.014 t h−1 for CH4 and 110 ± 18 t h−1 for CO2, the latter being in excellent agreement with material balance based estimates. A Gaussian plume inversion approach was also used to derive the emission rates and the results were compared with those derived using the mass-balance algorithm, showing a good agreement between the two methods.

Tianran Han et al.

Status: open (until 26 Sep 2023)

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  • RC1: 'Comment on amt-2023-113', Anonymous Referee #1, 05 Sep 2023 reply
  • RC2: 'Comment on amt-2023-113', Anonymous Referee #2, 08 Sep 2023 reply

Tianran Han et al.

Tianran Han et al.


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Short summary
This study reported an integrated UAV measurement platform for GHG monitoring and its application for emission quantification from a coking plant. The key element of this system is a newly designed air sampler, consisting of a 150-meter-long tube with remote-controlled time stamping. When comparing the top-down results to that derived from the bottom-up inventory method, the present findings indicated that the use of IPCC emission factors for emission calculations can lead to overestimation.