Retrieving CH4-emission rates from coal mine ventilation shafts using UAV-based AirCore observations and the genetic algorithm–interior point penalty function (GA-IPPF) model

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Abstract 4 based on concentration samples. This model can provide optimized dispersion parameters and self-calibration, thus lowering the requirements for auxiliary data accuracy. During the Carbon Dioxide and Methane Mission (CoMet) pre-campaign, we retrieve CH4 -emission rates from a ventilation shaft in Pniówek coal mine (Silesia coal mining region, Poland) based on the data collected by an unmanned aerial vehicle (UAV)-based AirCore system and a GA-IPPF model. The concerned CH4 -emission rates are variable even on a single day, ranging from 621.3 ± ± - 1 ± ± - 1 4 concentration data reconstructed by the retrieved parameters are highly consistent with the measured ones. Meanwhile, we demonstrate the application of GA-IPPF in three gas control release experiments, and the accuracies of retrieved gas emission rates are better than 95.0 %. This study indicates that the GA-IPPF model can quantify the CH4 -emission rates from strong point sources with high accuracy.

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: Retrieving CH₄-emission rates from coal mine ventilation shafts using UAV-based AirCore observations and the genetic algorithm–interior point penalty function (GA-IPPF) model ; volume:22 ; number:20 ; year:2022 ; pages:13881-13896 ; extent:16
Atmospheric chemistry and physics ; 22, Heft 20 (2022), 13881-13896 (gesamt 16)

Creator: Shi, Tianqi
Han, Zeyu
Han, Ge
Ma, Xin
Chen, Huilin
Andersen, Truls
Mao, Huiqin
Chen, Cuihong
Zhang, Haowei
Gong, Wei

DOI: 10.5194/acp-22-13881-2022

URN: urn:nbn:de:101:1-2022110304270926828422

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:34 AM CEST

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Shi, Tianqi
Han, Zeyu
Han, Ge
Ma, Xin
Chen, Huilin
Andersen, Truls
Mao, Huiqin
Chen, Cuihong
Zhang, Haowei
Gong, Wei

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Retrieving CH<sub>4</sub>-emission rates from coal mine ventilation shafts using UAV-based AirCore observations and the genetic algorithm–interior point penalty function (GA-IPPF) model

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