AS3.12

MEMO² was a 4-years European Training Network with more than 20 collaborators from 7 countries. The project contributed significantly to the targets of the EU with a focus on methane (CH₄). CH₄ emissions are a major contributor to Europe’s global warming impact, and the official inventories of emissions and estimates derived from direct atmospheric measurement show significant discrepancies. However, effective emission reduction can only be achieved if sources are properly quantified, and mitigation efforts are verified. MEMO² contributed to advanced combinations of measurement and modelling which are needed to achieve such quantification.

With respect to the recently released EU methane strategy and the implementation of independent verification of emissions by atmospheric measurements, we will present some examples of relevant results from MEMO² up to now:

Urban CH₄ emissions: We can now detect and quantify CH₄ leaks in cities at the street-level with mobile nigh precision analysers. Similar studies have been carried out in >10 EU cities and in collaboration with interested network operators those measurements are ready to be rolled out at larger scale.

Oil and gas production: We carried out a large study in the oil and gas production region in Romania (ROMEO), with aircraft, drones and vehicles. The final results are close to publication and help to improve the emission verification.

Coal mining: In collaboration with CoMet, another science project, we quantified the CH₄ emissions from the Upper Silesian coal mining area. The collaboration and its results contribute to the development of an independent and objective emission monitoring system

Modelling: Micro-scale plume modelling is significantly improved. Those models e.g. help to simulate a measurement day as we had during our field campaign in Romania and improve sampling and measurement strategies.

How to cite: Walter, S. and Röckmann, T. and the the MEMO2 Team: MEMO2: MEthane goes MObile – MEasurements and MOdelling, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3244, https://doi.org/10.5194/egusphere-egu21-3244, 2021.

Romania has been a pioneer country in oil and gas (O&G) exploration in Europe and is the largest producer of O&G in Central and Eastern Europe. However, many installations are old and production levels are decreasing. The ROMEO measurement campaign was carried out in Romania to evaluate methane emissions form onshore O&G operations in Romania in 2019 (ROMEO, 2019). In this program, Technical University of Denmark (DTU) and TNO used mobile-van-based measurements in combination with tracer release to quantify emissions. A total set of 200 oil and gas wells, and facilities were evaluated and emissions were quantified. Methane emission rates ranged largely between about 0.02 and 38 g s^-1, following a “heavy-tailed” lognormal distribution. A small number of sites (5%) were responsible for 55% of the total emission. Decreasing emissions only from the few high-emitters would effectively decrease methane emissions from the investigated area. This shows the value of site-specific evaluation from the ground. In this presentation, the mobile measurement equipped vans will be shown and methodological issues will be addressed. Also the results in terms of the emission distribution will be presented. The outcome of this study can help the Romanian O&G companies to set priorities in leak repair, which can then lead to a quick win in emission reduction.

References

ROMEO, 2019. ROMEO - ROmanian Methane Emissions from Oil & gas. URL http://romeo-memo2.wikidot.com/ (last accessed 13.01.21).

How to cite: Velzeboer, I., Delre, A., Hensen, A., van den Bulk, P., and Scheutz, C.: Evaluation of oil and gas methane emissions in Romania using mobile measurements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8935, https://doi.org/10.5194/egusphere-egu21-8935, 2021.

Goal of the CCAC project is to observe urban emission of natural gas over Canada and different countries in Europe. Our team was responsible for the Silesia and Sub-Carpathia regions in southern Poland. In this presentation we will focus on the methane emission measurements from gas pipelines, storages, gas wells as well as gathering and processing facilities, which was realized by our team in years 2018-2020.

South eastern Poland is rather rural part of the country with rich history of oil and gas industry going back to the XVI-th century. Currently Carpathians and Carpathian Foredeep regions gas industry produces 1.35 BILLIONS of m³ [1]

The measurements have been carried out since summer 2016 mainly with Micro-Portable Greenhouse Gas Analyzer ‘Los Gatos Research, MGGA-918’ mounted on board of a car. We also had capability to deploy analyser in difficult terrain with its own power supply. During our measurements our team visited over 300 gas wells. We found that over half of these sites show elevated methane concentrations which can be attributed to either gas well itself or soil fractures around site. Transects paths were designed to follow pipelines. This allowed us to monitor possible leaks from the natural gas infrastructure. However there are numerous possible sources in close proximity of pipelines. We will discuss detection methods and variability study for dozens of transects. As of the 2017 only 9 gathering and processing facilities report release which states the emission of 1.8*10⁶ m³ CH₄ per year. One of the focus points of our project was to estimate how uncertain were methane emission from O&G in Poland which at current phase concludes methane emission of 7.5-40 kt CH4/year

During the presentation we will outline challenges in carrying out measurements with GPM, OTM 33a methods that were performed alongside large-area screening. We are developing oversized flow chamber method. Mobile structure is built in the shape of a dome. It has the radius of 3 meters which gives the chamber volume of 49 m³.

This work was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies.

[1]PSG, „Bilans zasobów złóż kopalin w Polsce wg stanu na 31 XII 2019 r,” PIG-PIB, Warsaw, 2020.

How to cite: Jagoda, P., Nęcki, J., Bartyzel, J., Korbeń, P., Kud, M., Florczyk, G., and Król, S.: The extent of methane emission associated with the natural gas industry in southeastern Poland., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12214, https://doi.org/10.5194/egusphere-egu21-12214, 2021.

Methane (CH₄) emissions from coal production are one of the main sources of anthropogenic CH₄ in the atmosphere. Poland is the second largest hard coal producer in the European Union with the Polish area of the Upper Silesian Coal Basin (USCB) as a part of it. Emission estimates for CH₄ from USCB for individual coal mine ventilation shafts range between 0.03kt CH₄/yr and 25.9kt CH₄/yr, amounting to a basin total of roughly 465kt CH₄/yr (E-PRTR database, 2014). During CoMet (Carbon Dioxide and Methane Mission 2018) four ground-based, portable FTIR (Fourier transform infrared) spectrometers EM27/SUN were deployed in the USCB. We arranged these instruments in fixed locations in the North, East, South, and West of the USCB in approx. 50km distance to the center of the basin. This set-up ensures both, upwind and downwind measurements of CH₄ for the prevailing wind directions. Subtracting upwind from downwind XCH₄ observations gives the net methane enhancement of the region in between two selected instruments. These enhancements are also modeled with the Lagrangian particle dispersion model Flexpart. The model is driven by WRF wind simulations calculated in a nested domain using data assimilation of 3D wind-lidar data measured at three locations in the area of interest. The residuals between modeled and measured enhancements are minimized with a Phillips-Tikhonov regularized, non-negative least squares approach using the E-PRTR inventory data as a-priori information. The regularization parameters are graphically chosen via L-curve determination. Simulation uncertainty is expressed through an ensemble of different model runs, each with altered, basic meteorological parameters. The model generally matches the E-PRTR inventory data within it's error range for a small number (6 to 10) of coal mine ventilation shafts, whereas it suggests higher emission rates than the E-PRTR for more involved point sources (>30).

How to cite: Luther, A., Kleinschek, R., Kostinek, J., Stanisavljevic, M., Dandocsi, A., Forstmaier, A., Defratyka, S., Scheidweiler, L., Wildmann, N., Dubravica, D., Hase, F., Frey, M., Chen, J., Dietrich, F., Knote, C., Nęcki, J., Roiger, A., and Butz, A.: Estimating coal mine methane emissions using ground-based FTIR spectrometry, WRF driven Lagrangian dispersion modelling, and a regularized inversion approach, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12751, https://doi.org/10.5194/egusphere-egu21-12751, 2021.

Emissions from fossil fuels are one of the primary sources of atmospheric methane (CH₄) growth. However, estimates of anthropogenic CH₄ emissions still show large uncertainties on global and regional scales. Differences in CH₄ isotopic source signatures δ¹³C and δD can help to constrain different source contributions (e.g. fossil, thermogenic, or biogenic).

The Upper Silesian Coal Basin (USCB) represents one of the largest European CH₄ emission source regions, with more than 500 Gg CH₄ yr^-1 released by more than 50 coal mine ventilation shafts. During the CoMet (Carbon Dioxide and Methane Mission) campaign in June 2018 methane observations were conducted from a variety of platforms including aircraft and cars. Beside the continuous sampling of atmospheric methane concentration, numerous air samples were taken from inside the ventilation shafts, around the ventilation shafts (1‑2 km distance) and aboard the DLR Cessna Caravan aircraft and analyzed in the laboratory for the isotopic composition of CH₄.

The ground-based samples allowed determining the source signatures of individual ventilation shafts. These signatures displayed a considerable range between different shafts and also varied from day to day. The airborne samples contained a mixture of methane emissions from several mines and thus enabled accurately determining the signature of the entire region. The mean isotopic signature of methane emissions over the USCB derived from the aircraft samples was -51.9 ± 0.5 ‰ for δ¹³C and -233 ± 6 ‰ for δD. This is in between the range of other microbial and thermogenic coal reservoirs, but more depleted in δD than previous USCB studies reported based on samples taken within the mines. Signatures of methane enhancements sampled upwind of the mines and in the free troposphere clearly showed the presence of methane of biogenic origin (e.g. wetlands, waste, ruminants).

Furthermore, we simulated the methane isotopologues using the on-line three-times nested global regional chemistry climate model MECO(n). We implemented a submodel extension, which includes the kinetic fractionation and uses the isotopic source signatures determined by the ground-based observations. We compare the regional simulations to flask samples taken during CoMet.

How to cite: Fiehn, A., Kostinek, J., Eckl, M., Galkowski, M., Gerbig, C., Röckmann, T., Menoud, M., Maazallahi, H., Schmidt, M., Korben, P., Necki, J., Stanisavljevic, M., Swolkien, J., Nickl, A.-L., Winterstein, F., Mertens, M., Jöckel, P., Fix, A., and Roiger, A.: Isotopic characterization of coal mine methane in the Upper Silesian Coal Basin, Poland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6056, https://doi.org/10.5194/egusphere-egu21-6056, 2021.

Methane (CH₄) emissions from human activities are a threat to the resilience of our current climate, and to the adherence of the Paris Agreement goals. The stable isotopic composition of methane (δ¹³C and δ²H) allows to distinguish between the different CH₄ origins. A significant part of the European CH₄ emissions, 10 % in 2016, comes from the Upper Silesian Coal Basin (USCB). 

Measurements of CH₄ mole fraction (χ(CH₄)), δ¹³C and δ²H in CH₄ in ambient air were performed continuously during 6 months in 2018 and 2019 at Krakow, Poland. In addition, CH₄ samples were collected during parallel mobile campaigns, from multiple CH₄ sources in the footprint area of continuous measurements. The resulting isotopic signatures from natural gas leaks, coal mine fugitive emissions, landfill and sewage, and ruminant emissions were statistically different. The use of δ²H in CH₄ is crucial to distinguish the fossil fuel emissions in the case of Krakow, because their relatively depleted δ¹³C values overlap with the ones of microbial sources. The observed χ(CH₄) time series showed a regular daily night-time accumulations, sometimes combined with irregular pollution events during the day. The isotopic signatures of each peak were obtained using the Keeling plot method, and generally fall in the range of thermogenic CH₄ formation, with δ¹³C between -55.3 and -39.4 ‰ V-PDB, and δ²H between -285 and -124 ‰ V-SMOW. They compare well with the signatures measured for gas leaks in Krakow and USCB mines. 

The CHIMERE transport model was used to compute the CH₄ time series at the study location, based on two emission inventories. The χ(CH₄) are generally under-estimated in the model. The isotopic signatures of all pollution events over the entire time periods were extracted from Keeling plots applied on each peaks, for both observed and modelled time series using the EDGAR v5.0 inventory. The results indicate that a higher contribution from fuel combustion sources in the inventory would lead to a better agreement. The isotopic mismatches between model and observations are mainly caused by uncertainties in the assigned isotopic signatures for each source category, and how they are classified in the inventory. These uncertainties are larger for emissions close to the study site, which are more heterogenous than the ones advected from the USCB coal mines. Our isotope approach proves here to be very sensitive in this region, thus helping to improve emission estimates.

How to cite: Menoud, M., van der Veen, C., Necki, J., Stanisavljevic, M., Szenási, B., Pison, I., Bousquet, P., and Röckmann, T.: Isotopic characterisation of methane emissions from Krakow, Poland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10697, https://doi.org/10.5194/egusphere-egu21-10697, 2021.

Atmospheric CH4 mixing ratios resumed their increase in 2007 after a plateau during the period 1999-2006, suggesting a change of mix between sources and/or varying sinks. Exploiting observations within an inverse modeling framework (top-down estimates) is a powerful approach that reconciles observed and simulated CH4 mixing ratios using prior knowledge of CH4 sources and sinks. It is nevertheless challenging to efficiently differentiate co-located emissions from different sectors categories with CH4 observations alone. As a result, understanding CH4 burden changes and attributing these changes to specific source variations are difficult. CH4 source isotopic signatures differ between emission categories (biogenic, thermogenic and pyrogenic), and can therefore be included to disentangle overlapping sources. 

However, assimilating 13CH4 observations using inversion methods is challenging, especially with a variational framework. Here, a new 3-D variational inverse modeling framework implemented within the Community Inversion Framework [Berchet et al., 2020] and designed to assimilate 13CH4 and CH3D observations along CH4 observations is presented. This system is capable of optimizing emissions and associated source signatures of multiple emission categories independently at the pixel scale. Multiple tracers are transported by the LMDz 3-D model in order to properly simulate the clumped isotopologues of CH4. 

We present very briefly the technical implementation of such multi-constraints in the variational system and show preliminary results of long-term inversions for the period 1998-2018.

Berchet, A., Sollum, E., Thompson, R. L., Pison, I., Thanwerdas, J., Broquet, G., Chevallier, F., Aalto, T., Bergamaschi, P., Brunner, D., Engelen, R., Fortems-Cheiney, A., Gerbig, C., Groot Zwaaftink, C., Haussaire, J.-M., Henne, S., Houweling, S., Karstens, U., Kutsch, W. L., Luijkx, I. T., Monteil, G., Palmer, P. I., van Peet, J. C. A., Peters, W., Peylin, P., Potier, E., Rödenbeck, C., Saunois, M., Scholze, M., Tsuruta, A., and Zhao, Y.: The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2020-407, in review, 2020.

How to cite: Thanwerdas, J., Saunois, M., Berchet, A., Pison, I., and Bousquet, P.: Running a new 3-D variational inversion system to assimilate isotopic observations along with CH4 observations., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4077, https://doi.org/10.5194/egusphere-egu21-4077, 2021.

Methane is an important greenhouse gas with a range of anthropogenic sources, including livestock farming and fossil fuel production. It is important that methane emissions can be correctly attributed to their source, to aid climate change policy and emissions mitigation efforts. For source attribution, many ‘top-down’ models of atmospheric methane use spatial maps of sources from emissions inventory data coupled with an atmospheric transport model. However, this can cause difficulties if sources are co-located or if there is uncertainty in the sources’ spatial distributions.

To help with this issue and reduce overall uncertainty in estimates of methane emissions, recent methods have used observations of a secondary trace gas and its correlation with methane to infer methane emissions from a target sector. Most previous work has assumed a fixed emissions ratio between the two gases, which often does not reflect the true range of possible emission ratios. In this work, measurements of atmospheric ethane and its emissions ratio relative to methane are used to infer emissions of methane from fossil fuel sources. Instead of assuming a fixed emission ratio, our method allows for uncertainty in the emission ratio to be statistically propagated through the inverse model and incorporated into the sectoral estimates of methane emissions. We further demonstrate the inaccuracies that can result in an assessment of fossil fuel methane emissions if this uncertainty is not considered.

We present this novel method for modelling sectoral methane emissions with examples from a synthetic data experiment and give results from a case study of UK methane emissions. Methane and ethane observations from a tall tower network across the UK were used with this model to produce monthly estimates of UK fossil fuel methane emissions with improved uncertainty characterisation.

How to cite: Ramsden, A., Ganesan, A., Western, L., Manning, A., Rigby, M., Say, D., Wisher, A., Arnold, T., Rennick, C., Levy, P., Young, D., and O'Doherty, S.: Quantifying methane emissions from fossil fuel sources using a Bayesian inverse model and observations of ethane with an uncertain emissions ratio, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8869, https://doi.org/10.5194/egusphere-egu21-8869, 2021.

The efficient and precise monitoring (detection, localization, and quantification) of fugitive methane (CH₄) emissions is essential in preventing and mitigating greenhouse gas (GHG) emissions from oil and gas industrial facilities and landfills. Various strategies of mole fraction sampling within or in the vicinity of the sites and of atmospheric inversions have been developed for such a monitoring. Many studies have ensured the constant improvement of instrumentation, of measurement strategies and atmospheric inversion techniques.

In this context, we participated in two controlled-release experiments at the TOTAL Anomaly Detection Initiatives (TADI) test site (Lacq, France) in October 2018 and 2019, dedicated to evaluate the ability of different local-scale atmospheric measurement and inverse modeling systems to localize and quantify point sources. We also conducted a series of 18 campaigns to regularly quantify methane emissions from the active “Butte-Bellot” landfill (about 35 km south-east of Paris) since 2018. We developed and applied different inversion approaches to process mobile or fixed-point measurements, which, in both cases, rely on a Gaussian dispersion model to simulate the atmospheric plume from the potential source location or mole fraction sensitivity at the measurement time and location to emissions at the potential source locations.

The series of CH₄ and carbon dioxide (CO₂) controlled releases in TADI covered a wide range of release rates (~0.1 to 200 gCH₄/s and 0.2 to 200 gCO₂/s) and durations from 4 to 8 minutes (brief) to 25 to 75 minutes (longer). During the corresponding campaigns, we conducted both near-surface mobile and fixed-point (~2-4 m height) in situ atmospheric measurements based on Picarro CRDS, LGR (MGGA and UGGA), and LI-COR (LI-7810) instruments. Both inversions based on mobile measurements and those based on the fixed-point measurements provide estimates with a 20-30% average error for the CH₄ and CO₂ release rates, whatever the duration of the releases. The use of fixed-point measurements during long releases allow for a more precise localization of sources with an average location error of ~8m.

The analysis of the CH₄ mobile measurements at the “Butte-Bellot” landfill reveals the difficulties in exploiting measurements close to such a site with diffuse emissions whose spatial distribution is difficult to characterize, heterogeneous and highly variable in time. The series of estimates of the total CH₄ emissions from the site based on remote mobile plume cross-sections, based on atmospheric inversions, are discussed.

This presentation will highlight positive perspectives opened by the proposed inversion approaches and by our results and discuss options for further improvements when processing both types of measurements.

How to cite: Kumar, P., Broquet, G., Caldow, C., Laurent, O., Yver-Kwok, C., Cropley, F., Fontanier, B., Shah, A., Lozano, M., Defratyka, S., Gichuki, S., Lauvaux, T., Rivera, R., Berthe, G., Martin, F., Noirez, S., Duclaux, O., Juery, C., Bouchet, C., and Ciais, P. and the TRACE team: Local-scale atmospheric inversions to monitor CH4 emissions from industrial sites using mobile and/or fixed-point measurements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12743, https://doi.org/10.5194/egusphere-egu21-12743, 2021.

Methane (CH₄) emissions from landfills contribute to global warming, impacting significantly the environment and human health. Landfill CH₄ emissions strongly depend on changes in barometric pressure, inducing short-term CH₄ emission variation of several orders of magnitude. Estimating the temporal variability of CH₄ emitted into the atmosphere could help us reducing the uncertainties of annual emission estimates from landfills. In this study, we focus on the temporal variability of CH₄ emissions under the impact of barometric pressure changes.

CH₄ emissions of a closed landfill (Skellingsted, Western Zealand, Denmark) were measured with two different methods from December 2019 to June 2020; continuously with the eddy covariance method (EC) and discretely with the dynamic tracer dispersion method (TDM). The EC method allows continuous measurements from a confined surface area, with most likely limited representativeness of the whole landfill site due to the considerable horizontal heterogeneity. The TDM method is able to quantify the emission from the whole site insensitive of the topography with the limited representativeness for the temporal variability.

CH₄ emissions to the atmosphere measured by the TDM and fluxes measured by the EC ranged from to 0 to almost 100 kg h^-1 and from 0 to 10 μmol m^-2 s^-1, respectively. The CH₄ fluxes measured continuously using the EC method were highly correlated with the emissions from the periodic measurements using the TDM and fluctuated according to the pressure tendency. Under decreasing barometric pressure the highest CH₄ emissions where observed, while increasing barometric pressure suppressed them almost to 0.

Our results demonstrate the value of implementing two different complementary measurement techniques in parallel that will help to quantify total annual CH₄ emission from a landfill. EC method provides continuous measurements describing accurately the temporal variation of emissions, while TDM method is able to quantify emissions from the whole site.

How to cite: Kissas, K., Ibrom, A., Kjeldsen, P., and Scheutz, C.: Temporal variability of methane emissions from a closed landfill at Denmark, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12518, https://doi.org/10.5194/egusphere-egu21-12518, 2021.