气候变化领域集成服务门户(CCPortal): 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

CCPortal

DOI	10.5194/acp-22-13881-2022
	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
	Shi, Tianqi; Han, Zeyu; Han, Ge; Ma, Xin; Chen, Huilin; Andersen, Truls; Mao, Huiqin; Chen, Cuihong; Zhang, Haowei; Gong, Wei
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	13881
结束页码	13896
卷号	22 期号:20 页码:16
英文摘要	There are plenty of monitoring methods to quantify gas emission rates based on gas concentration measurements around the strong sources. However, there is a lack of quantitative models to evaluate methane emission rates from coal mines with less prior information. In this study, we develop a genetic algorithm-interior point penalty function (GA-IPPF) model to calculate the emission rates of large point sources of CH4 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 Pniowek 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 +/- 19.8 to 1452.4 +/- 60.5 kg h(-1) on 18 August 2017 and from 348.4 +/- 12.1 to 1478.4 +/- 50.3 kg h(-1) on 21 August 2017. Results show that CH4 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.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000874785200001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273915
作者单位	Wuhan University; Wuhan University; Wuhan University; Nanjing University; University of Groningen; Wuhan University
推荐引用方式 GB/T 7714	Shi, Tianqi,Han, Zeyu,Han, Ge,et al. 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[J],2022,22(20):16.
APA	Shi, Tianqi.,Han, Zeyu.,Han, Ge.,Ma, Xin.,Chen, Huilin.,...&Gong, Wei.(2022).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.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(20),16.
MLA	Shi, Tianqi,et al."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".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.20(2022):16.