Quantifying methane emissions from coal mining ventilation shafts using an unmanned aerial vehicle (UAV)-based active AirCore system. (December 2021)

• Record Type: Journal Article
• Authors: Andersen, Truls; Vinkovic, Katarina; de Vries, Marcel; Kers, Bert; Necki, Jaroslaw; Swolkien, Justyna; Roiger, Anke; Peters, Wouter; Chen, Huilin
• Is Part Of: Atmospheric environment. Volume 12(2021)
• Publication Date: 2021-12
• Subjects: Methane emissions -- Coal mining -- UAV -- Point sources -- Inverse Gaussian
• DOI: 10.1016/j.aeaoa.2021.100135
• Languages: English
• ISSNs: 2590-1621

Abstract

Abstract: A large quantity of CH4 is emitted to the atmosphere via ventilation shafts of underground coal mines. According to the European Pollutant Release and Transfer Register (E-PRTR), hard coal mines in the Upper Silesia Coal Basin (USCB) are a strong contributor (447 kt CH4 in 2017) to the annual European CH4 emissions. However, atmospheric emissions of CH4 from coal mines are poorly characterized, as they are dispersed over large areas. As part of the Carbon Dioxide and CH4 Mission (CoMet) pre-campaign, a study of the USCB's regional CH4 emissions took place in August 2017. We flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 mole fractions downwind of a single coal mining ventilation shaft. Besides CH4, we also measured CO2, CO, atmospheric temperature, pressure, and relative humidity. Wind-speed and wind-direction measurements were made using a lightweight balloon-borne radiosonde. Fifteen UAV flights were performed flying perpendicular to the wind direction at several altitude levels, to effectively build a 'curtain' of CH4 mole fractions in a two-dimensional plane at a distance between 150 and 350 m downwind of a single ventilation shaft. Furthermore, we have developed an inverse Gaussian approach for quantifying CH4 emissions from a point source using the UAV-based observations, and have applied it as well as the mass balance approach to both simulated data and actual flight data to quantify CH4 emissions. The simulated data experiments revealed the importance of having multiple transects at different altitudes, appropriate vertical spacing between the individual transects, and proper distance between the center height of the plume and the center flight transect. They also showed that the inverse Gaussian approach performed better than the mass balance approach. Our estimate of the CH4 emission rates from the sampled shaft ranges from 0.5 to 14.5 kt/year using a mass balance approach, and between 1.1 and 9.0 kt/year using an inverse Gaussian method. The average difference between the mass balance and the inverse Gaussian approach was 2.3 kt/year. Based on the observed correlation between CO2 and CH4 (R-squared > 0.69), the CO2 emissions from the shaft were estimated to be between 0.3 and 9.8 kt/year. This study demonstrates that the UAV-based active AirCore system provides an effective way of quantifying coal mining shaft emissions of CH4 and CO2. Highlights: The UAV-based active AirCore is an effective sampling tool of quantifying point source emissions of greenhouse gases. Inverse Gaussian Approach outperforms Mass Balance Approach in estimating point source emissions. To achieve optimal performance of the Inverse Gaussian Approach, vertical spacing of UAV-based sampling is required to be smaller than 2.5 times the vertical distribution (σz) of the plume. Continuous and accurate wind measurements are essential to reduce the uncertainties of the quantifications.