Quantification of methane emission rates from coal mine ventilation shafts using airborne remote sensing data

Abstract

The quantification of emissions of the greenhouse gas methane is essential for attributing the roles of anthropogenic activity and natural phenomena in global climate change. Our current measurement systems and networks, whilst having improved during the last decades, are deficient in many respects. For example, the emissions from localised and point sources such as landfills or fossil fuel exploration sites are not readily assessed. A tool developed to better understand point sources of the greenhouse gases carbon dioxide and methane is the optical remote sensing instrument MAMAP (Methane airborne MAPper), operated from aircraft. After a recent instrument modification, retrievals of the column-averaged dry air mole fractions for methane <i>X</i>CH<sub>4</sub> (or for carbon dioxide <i>X</i>CO<sub>2</sub>) derived from MAMAP data have a precision of about 0.4% or better and thus can be used to infer emission rate estimates using an optimal estimation inverse Gaussian plume model or a simple integral approach. <br><br> CH<sub>4</sub> emissions from two coal mine ventilation shafts in western Germany surveyed during the AIRMETH 2011 measurement campaign are used as examples to demonstrate and assess the value of MAMAP data for quantifying CH<sub>4</sub> from point sources. While the knowledge of the wind is an important input parameter in the retrieval of emissions from point sources and is generally extracted from models, additional information from a turbulence probe operated on-board the same aircraft was utilised to enhance the quality of the emission estimates. Although flight patterns were optimised for remote sensing measurements, data from an in situ analyser for CH<sub>4</sub> were found to be in good agreement with retrieved dry columns of CH<sub>4</sub> from MAMAP and could be used to investigate and refine underlying assumptions for the inversion procedures. <br><br> With respect to the total emissions of the mine at the time of the overflight, the inferred emission rate of 50.4 kt CH<sub>4</sub> yr<sup>−1</sup> has a difference of less than 1% compared to officially reported values by the mine operators, while the uncertainty, which reflects variability of the sources and conditions as well as random and systematic errors, is about ±13.5%

Natural and anthropogenic methane fluxes in Eurasia: a mesoscale quantification by generalized atmospheric inversion

“…Recent developments (e.g. Krings et al, 2013) point to the possibility of using 1-D or 2-D high resolution snapshots of the hotspot plumes to infer information about very local emissions. Integrated comparison of the observed and simulated plumes in the CH 4 columns could then be implemented in a mesoscale inversion system.…”

A wide field-of-view imaging DOAS instrument for two-dimensional trace gas mapping from aircraft

“…Below the aircraft, the wind speed varies between 6.1 and 9.2 m s −1 with an average of 8.3 m s −1 . A small bias of +0.7 m s −1 in the COSMO-DE wind speed data for the respective time and region has been identified by Krings et al (2013) in comparison to the AIMMS-20 wind probe. Taking the bias into account, a wind speed of 7.6 m s −1 is used.…”

“…The research aircraft is equipped with an AIMMS-20 (Aircraft-Integrated Meteorological Measurement System), comprising an AHRS (Attitude and Heading Reference System) and a GPS (Global Positioning System). The main target of the research flight was the observation of pollution plumes from a coal mine with a coal-fired power plant close by, the RWE Power AG Kraftwerk Ibbenbüren, at coordinates 7.748 • E and 52.289 • N. One research focus addressed the emissions of methane, CH 4 , from ventilation shafts (Krings et al, 2013), for which the flight patterns were primarily selected. The medium-sized power plant generates an average power of around 840 MW, it has a 275 m high exhaust stack and uses extensive flue gas cleaning facilities.…”

“…This relationship has also been used, e.g. by Wang et al (2006), Heue et al (2008) and Krings et al (2013). Local wind data are a prerequisite for the emission calculations.…”

“…Considering that the atmospheric stability class valid for the present campaign day was rated as slightly unstable (Krings et al, 2013), dispersion leads to a substantial spreading of several hundred metres within the boundary layer at a distance of 6 km from the stack. From this perception and the measurements of the vertical mixing layer extent, a homogeneous distribution of NO 2 below the aircraft is assumed for the wind averaging at this location.…”