Local to regional methane emissions from the Upper Silesia Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Abstract. Coal mining accounts for ~ 12 % of the total anthropogenic methane emissions worldwide. The Upper Silesian Coal Basin, Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coalbed CH4 emissions into the atmosphere are poorly characterized. As part of the Carbon Dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May – June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150–300 m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speeds and directions. We have used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data, and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2 = 0.7 – 0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified though. As an alternative, we have developed three upscaling approaches, i.e., by scaling the E-PRTR annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate that are derived from the hourly emission inventory. These estimates are in the range of 325 – 447 kt CH4/year for the inverse Gaussian approach and 268 – 347 kt CH4/year for the mass balance approach, respectively. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions.

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Supplementary material to "Estimating CH<sub>4</sub>, CO<sub>2</sub>, and CO emissions from coal mining and industrial activities in the Upper Silesian Coal Basin using an aircraft-based mass balance approach"

10.5194/acp-2020-282-supplement ◽

2020 ◽

Author(s):

Alina Fiehn ◽

Julian Kostinek ◽

Maximilian Eckl ◽

Theresa Klausner ◽

Michał Gałkowski ◽

...

Keyword(s):

Mass Balance ◽

Coal Mining ◽

Coal Basin ◽

Industrial Activities ◽

Balance Approach ◽

Upper Silesian Coal Basin ◽

Supplementary Material ◽

Mass Balance Approach

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Review of "Estimating CH4, CO2, and CO emissions from coal mining and industrial activities in the Upper Silesian Coal Basin using an aircraft-based mass balance approach"

10.5194/acp-2020-282-rc2 ◽

2020 ◽

Author(s):

Anna Karion

Keyword(s):

Mass Balance ◽

Coal Mining ◽

Coal Basin ◽

Industrial Activities ◽

Balance Approach ◽

Upper Silesian Coal Basin ◽

Mass Balance Approach

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Evaluating the impact of storage-and-release on aircraft-based mass-balance methodology using a regional air-quality model

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-15461-2021 ◽

2021 ◽

Vol 21 (20) ◽

pp. 15461-15491

Author(s):

Sepehr Fathi ◽

Mark Gordon ◽

Paul A. Makar ◽

Ayodeji Akingunola ◽

Andrea Darlington ◽

...

Keyword(s):

Air Quality ◽

Mass Balance ◽

Emission Rate ◽

Meteorological Conditions ◽

Emission Rates ◽

Top Down ◽

Retrieval Accuracy ◽

Balance Approach ◽

The Impact ◽

Mass Balance Approach

Abstract. We investigate the potential for aircraft-based top-down emission rate retrieval over- and under-estimation using a regional chemical transport model, the Global Environmental Multiscale-Modeling Air-Quality and CHemistry (GEM-MACH). In our investigations we consider the application of the mass-balance approach in the Top-down Emission Rate Retrieval Algorithm (TERRA). Aircraft-based mass-balance retrieval methodologies such as TERRA require relatively constant meteorological conditions and source emission rates to reliably estimate emission rates from aircraft observations. Avoiding cases where meteorology and emission rates change significantly is one means of reducing emissions retrieval uncertainty, and quantitative metrics that may be used for retrieval accuracy estimation are therefore desirable. Using these metrics has the potential to greatly improve emission rate retrieval accuracy. Here, we investigate the impact of meteorological variability on mass-balance emission rate retrieval accuracy by using model-simulated fields as a proxy for real-world chemical and meteorological fields, in which virtual aircraft sampling of the GEM-MACH output was used for top-down mass balance estimates. We also explore the impact of upwind emissions from nearby sources on the accuracy of the retrieved emission rates. This approach allows the state of the atmosphere used for top-down estimates to be characterized in time and 3D space; the input meteorology and emissions are “known”, and thus potential means for improving emission rate retrievals and determining the factors affecting retrieval accuracy may be investigated. We found that emissions retrieval accuracy is correlated with three key quantitative criteria, evaluated a priori from forecasts and/or from observations during the sampling period: (1) changes to the atmospheric stability (described as the change in gradient Richardson number), (2) variations in the direction of transport, as a result of plume vertical motion and in the presence of vertical wind shear, and (3) the combined effect of the upwind-to-downwind concentration ratio and the upwind-to-downwind concentration standard deviations. We show here that cases where these criteria indicate high temporal variability and/or high upwind emissions can result in “storage-and-release” events within the sampled region (control volume), which decrease emission rate retrieval accuracy. Storage-and-release events may contribute the bulk of mass-balance emission rate retrieval under- and over-estimates, ranging in the tests carried out here from −25 % to 24 % of the known (input) emissions, with a median of −2 %. Our analysis also includes two cases with unsuitable meteorological conditions and/or significant upwind emissions to demonstrate conditions which may result in severe storage, which in turn cause emission rate under-estimates by the mass-balance approach. We also introduce a sampling strategy whereby the emission rate retrieval under- and over-estimates associated with storage-and-release are greatly reduced (to −14 % to +5 %, respectively, relative to the magnitude of the known emissions). We recommend repeat flights over a given facility and/or time-consecutive upwind and downwind (remote) vertical profiling of relevant fields (e.g., tracer concentrations) in order to measure and account for the factors associated with storage-and-release events, estimate the temporal trends in the evolution of the system during the flight/sampling time, and partially correct for the effects of meteorological variability and upwind emissions.

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Evaluating the Impact of Storage-and-Release on Aircraft-based Mass-Balance Methodology Using a Regional Air Quality Model

10.5194/acp-2021-343 ◽

2021 ◽

Author(s):

Sepehr Fathi ◽

Mark David Gordon ◽

Paul Andrew Makar ◽

Ayodeji Akingunola ◽

Andrea Darlington ◽

...

Keyword(s):

Air Quality ◽

Mass Balance ◽

Emission Rate ◽

Meteorological Conditions ◽

Emission Rates ◽

Top Down ◽

Retrieval Accuracy ◽

Balance Approach ◽

The Impact ◽

Mass Balance Approach

Abstract. We investigate the potential for aircraft-based top-down emission rate retrieval over- and under-estimation using a regional chemical transport model, the Global Environmental Multiscale-Modeling Air-Quality and CHemistry (GEM-MACH). In our investigations we consider the application of the mass-balance approach in the Top-down Emission Rate Retrieval Algorithm (TERRA). Aircraft-based mass-balance retrieval methodologies such as TERRA require relatively constant meteorological conditions and source emission rates to reliably estimate emission rates from aircraft observations. Avoiding cases where meteorology and emission rates change significantly is one means of reducing emissions retrieval uncertainty, and quantitative metrics that may be used for retrieval accuracy estimation are therefore desirable. Using these metrics has the potential to greatly improve emission rate retrieval accuracy. Here, we investigate the impact of meteorological variability on mass-balance emission rate retrieval accuracy by using model simulated fields as a proxy for real world chemical and meteorological fields, in which virtual aircraft sampling of the GEM-MACH output was used for top-down mass balance estimates. We also explore the impact of upwind emissions from nearby sources on the accuracy of the retrieved emission rates. This approach allows the state of the atmosphere used for top-down estimates to be characterized in time and 3D space; the input meteorology and emissions are “known”, and thus potential means for improving emission rate retrievals and determining the factors affecting retrieval accuracy may be investigated. We found that emissions retrieval accuracy is correlated with three key quantitative criteria, evaluated a priori from forecasts and/or from observations during the sampling period: (1) changes to the atmospheric stability (described as the change in gradient Richardson number), (2) variations in the direction of transport, as a result of plume vertical motion and in the presence of vertical wind shear, and (3) the combined effect of the upwind to downwind concentration ratio and the upwind to downwind concentration standard deviations. We show here that cases where these criteria indicate high temporal variability and/or high upwind emissions can result in “Storage-and-Release” events within the sampled region (control volume), which decrease emission rate retrieval accuracy. Storage-and-release events may contribute the bulk of mass-balance emission rate retrieval under- and over-estimates, ranging in the tests carried out here from −25 % to 24 % of the known (input) emissions, with a median of −2 %. Our analysis also includes two cases with unsuitable meteorological conditions and/or significant upwind emissions to demonstrate conditions which may result in severe storage, which in turn cause emission rate underestimates by the mass-balance approach. We also introduce a flight strategy whereby the emission rate retrieval under- and over-estimates associated with storage-and-release are greatly reduced (to −14 % to +5 % respectively, relative to the magnitude of the known emissions). We recommend repeat flights over a given facility in order to measure and account for the factors associated with storage-and-release events – to estimate the temporal trends in the evolution of the system during the flight/sampling time, and partially correct for the effects of meteorological variability and upwind emissions. Our analysis allows the increased costs associated with longer flight times to be weighed against quantitatively reduced uncertainty in the emission rate estimates.

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