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Estimating local CH4 emissions in the Upper Silesian Coal Basin using inverse modelling

Wolff, Sebastian and Reum, Friedemann and Kiemle, Christoph and Ehret, Gerhard and Quatrevalet, Mathieu and Wirth, Martin and Fix, Andreas (2022) Estimating local CH4 emissions in the Upper Silesian Coal Basin using inverse modelling. D-A-CH MeteorologieTagung 2022, 2022-03-21 - 2022-03-25, Leipzig, Deutschland. doi: 10.5194/dach2022-79.

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Official URL: https://meetingorganizer.copernicus.org/DACH2022/DACH2022-79.html

Abstract

Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG) with respect to radiative forcing. Since pre-industrial times, the globally averaged CH4 concentration in the atmosphere has risen by a factor of 2.5. A large fraction of global anthropogenic CH4 emissions originates from localized point sources, e.g. coal mine ventilation shafts. International treaties foresee GHG emission reductions, entailing independent monitoring and verification support capacities. Considering the spatially widespread distribution of point sources, remote sensing approaches are favourable, in order to enable rapid survey of larger areas. In this respect, active remote sensing by airborne lidar is promising, such as provided by the integrated-path differential-absorption lidar CHARM-F operated by DLR. Installed onboard the German research aircraft HALO, CHARM-F serves as a demonstrator for future satellite missions, e.g. MERLIN. CHARM-F simultaneously measures weighted vertical column mixing ratios of CO2 and CH4 below the aircraft. In spring 2018, during the CoMet field campaign, measurements were taken in the Upper Silesian Coal Basin (USCB) in Poland. The USCB is considered to be a European hotspot of CH4 emissions, covering an area of approximately 50 km × 50 km. Due to the high number of coal mines and density of ventilation shafts in the USCB, individual CH4 exhaust plumes can overlap. This makes simple approaches to determine the emission rates of single shafts, i.e. the cross-sectional flux method, difficult. Therefore, we use an inverse modelling approach to obtain an estimate of the individual emission rates. Specifically, we employ the Weather Research and Forecast Model (WRF) coupled to the CarbonTracker Data Assimilation Shell (CTDAS), an Ensemble Kalman Filter. CTDAS-WRF propagates an ensemble realization of the a priori CH4 emissions forward in space and time, samples the simulated CH4 concentrations along the measurement’s flight path, and scales the a priori emission rates to optimally fit the measured values, while remaining tied to the prior. Hereby, we obtain a regularized a posteriori best emission estimate for the individual ventilation shafts. Here, we report on the results of this inverse modelling approach, including individual and aggregated emission estimates, their uncertainties, and to which extent the data are able to constrain individual emitters independently.

Item URL in elib:https://elib.dlr.de/190032/
Document Type:Conference or Workshop Item (Speech)
Title:Estimating local CH4 emissions in the Upper Silesian Coal Basin using inverse modelling
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Wolff, SebastianDLR, IPahttps://orcid.org/0000-0001-6745-1947UNSPECIFIED
Reum, FriedemannDLR, IPAhttps://orcid.org/0000-0003-2488-6582UNSPECIFIED
Kiemle, ChristophDLR, IPAhttps://orcid.org/0000-0003-1231-2813UNSPECIFIED
Ehret, GerhardDLR, IPAUNSPECIFIEDUNSPECIFIED
Quatrevalet, MathieuDLR, IPAUNSPECIFIEDUNSPECIFIED
Wirth, MartinDLR, IPAhttps://orcid.org/0000-0001-5951-2252UNSPECIFIED
Fix, AndreasDLR, IPAhttps://orcid.org/0000-0003-2818-9290UNSPECIFIED
Date:March 2022
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI:10.5194/dach2022-79
Status:Published
Keywords:CH4, emission estimate, CoMet measurement campaign, lidar, inverse modelling, WRF, CTDAS
Event Title:D-A-CH MeteorologieTagung 2022
Event Location:Leipzig, Deutschland
Event Type:national Conference
Event Start Date:21 March 2022
Event End Date:25 March 2022
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Project MABAK, R - Project CO2-Emission monitoring, CO2Mon
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Lidar
Institute of Atmospheric Physics > Atmospheric Trace Species
Deposited By: Wolff, Sebastian
Deposited On:14 Nov 2022 07:49
Last Modified:24 Apr 2024 20:51

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