Methane (CH4) is known to be one of the most potent greenhouse gases (GHGs) and it plays a key role in climate change due to its high warming potential. It is of both natural and anthropogenic origin. The main anthropogenic emissions of CH4 come from agriculture, fossil fuels (gas, oil, coal), landfills and wastewater treatment plants.
Two of the largest landfills in Europe are the Pinto and Technology Park Valdemingómez landfills in Spain. Both landfills, which are only a couple of kilometres apart, are located in the south of Madrid metropolitan area. These sorts of landfills are considered extended sources of GHGs due to their surface area, which spans a few square kilometres. Understanding the emissions from such landfills is critical to accurately assess and mitigate their impact on climate change.
In summer 2024, a ground-based remote sensing field campaign was carried out around these two landfills to evaluate the capabilities and limitations of the deployed instruments, which were two shortwave hyperspectral infrared cameras mounted on tripods scanning the horizon. Such a camera has previously been used for detecting emissions of GHGs from point sources such as a power plant (Knapp et al., 2024). The campaign in Madrid aimed at testing the cameras’ capabilities regarding extended sources of CH4 such as landfills. During the campaign, these ground-based measurements were complemented by observations from different satellites (GHGSat, EnMAP and TROPOMI-SP5).
This work will describe the field campaign and retrieval techniques as well as present first results of the observations of the campaign. Moreover, an extended study of TROPOMI’s observations of the target landfills will be presented (2019 - 2024), comparing inferred CH4 emission rates to previous studies and to values reported to PRTR-Spain (Spanish Register of Emissions and Pollutant Sources).
How to cite: Alvaro-Diaz, A., Resch, L., Häffner, L., Rüther, L.-M., Knapp, M., Collado Rodríguez, A., Mielke, C., del Pino-Jiménez, A., Scheidweiler, L., Taquet, N., Prados-Roman, C., and Butz, A.: Madrid Methane Remote Sensing: first results of a landfill field campaign, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9717, https://doi.org/10.5194/egusphere-egu25-9717, 2025.
Methane is the second most potent anthropogenic source greenhouse gas (GHG), with a global warming potential of approximately 84 times that of carbon dioxide over a 20-year period. Methane accounts for nearly one-third of current global warming, and its emission mitigations are critical actions for slowing down global warming in the short time period. In Iran, methane emissions from the energy and waste sectors significantly contribute to the country's total GHG emissions. According on the report of the International Energy Agency (IEA) in 2024, oil and gas (O&G) production in Iran resulted in the release of approximately 6 million metric tons of methane, ranking the country among the top three global emitters. Based on limited data, it was previously estimated that 3.84 million metric of methane is released from Iran’s waste sector. However, with limited data and measurement-based campaigns, these estimates need refinements. National inventories further highlight substantial emissions from waste management practices, underscoring the need for effective mitigation strategies, which at the first step requires framing the level of emissions nationwide.
This study utilizes satellite remote sensing data, generated by UNEP's IMEO (United Nations Environment Programme International Methane Emissions Observatory) through its Methane Alert and Response System (MARS) and available via its Eye on Methane data platform, to quantify methane emissions from O&G and waste-related activities in Iran. Methane quantifications were derived by integrating data from multiple satellite platforms, including the Earth Surface Mineral Dust Source Investigation (EMIT) operated by National Aeronautics and Space Administration (NASA), Sentinel-5P and Sentinel-2 from the European Space Agency (ESA), Landsat (jointly operated by NASA and the US Geological Survey), and the Environmental Mapping and Analysis Program (EnMAP) of the German Aerospace Center (DLR). A total of 110 emission sources from O&G infrastructures were identified and visually verified through Google Earth, subsequently integrated into the MARS system for continuous monitoring. This study provides nationwide observations of methane emissions from top emitters, which can be used for reporting and emission mitigation in Iran.
How to cite: Maazallahi, H., Pourfayaz, F., Irakulis-Loitxate, I., and Avishan, M.: Satellite-based Detection and Quantification of Methane Emissions from Energy and Waste Sectors in Iran, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18300, https://doi.org/10.5194/egusphere-egu25-18300, 2025.
Methane (CH4) has a significant global warming potential and a short atmospheric lifetime, making it a critical target for climate change mitigation. In India, the primary contributors to methane emissions are domestic ruminants, fossil fuels, waste management, rice cultivation, and wetlands. In the present study, we explore the column-averaged dry-air mixing ratio measurements of methane (XCH₄) from the TROPOMI (Tropospheric Monitoring Instrument) aboard the ESA Copernicus Sentinel-5 Precursor satellite and the methane simulations from Weather Research and Forecasting model coupled with Chemistry (WRF-Chem-GHG) to quantify the Indian region methane emission. The investigation focuses on the seasonal and spatial variations of the anthropogenic component of methane over India and compares them with simulations to assess the uncertainties in the current understanding. An inversion analysis utilising these satellite observations will be presented to offer critical insights into current emission trends and improvements in emission inventories over India.
How to cite: Mathew, T. A., Pillai, D., Deshpande, M. V., Thilakan, V., and Kanakkassery, S. B.: Investigating Indian methane emission using TROPOMI retrievals and WRF-GHG modelling framework, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17057, https://doi.org/10.5194/egusphere-egu25-17057, 2025.
India ranks as the third-largest methane emitter globally, with methane emissions increasing by 30% since 1990. According to India’s most recent report to the United Nations Framework Convention on Climate Change (UNFCCC), anthropogenic methane emissions are estimated at 18.7 Tg/year. However, these estimates are based on bottom-up calculations using activity data and laboratory-derived emission factors, and India lacks a dense network of ground-based measurements to validate them.
Recent advances in satellite technology, offering higher spatial and temporal resolution, have enabled the exploration of areas without ground-based measurements. We use a blended product from the TROPOspheric Monitoring Instrument (TROPOMI) and the Greenhouse Gases Observing Satellite (GOSAT) in Bayesian inversions with the Integrated Methane Inversion framework (IMI) to estimate 2021 Indian methane emissions. Prior emissions include fossil fuel exploitationsources from the Global Fuel Exploitation Inventory (GFEI v2) and other anthropogenic sources from the Emissions Database for Global Atmospheric Research (EDGAR v7). Landfill emissions from 19 solid waste disposal sites across 12 cities are assigned prior emissions using estimates based on high-resolution GHGSat observations.
Our inversion improves agreement with the blended TROPOMI data, GOSAT data, and available surface observations. We estimate Indian methane emissions for 2021 at 34 (32–39) Tg/year, 15% higher than prior estimates. The anthropogenic posterior emission is 31 (30 – 37) Tg/year, 67% higher than UNFCCC reported values, consistent with previous studies such as Janardanan et al. (2020), Zhang et al. (2021), and Belikov et al. (2024). Compared to the prior estimate, we find higher emissions from landfills and the oil & gas sector, while coal emissions are found to be lower. An analysis of 12 Indian cities reveals that emissions in 3 cities align with prior estimates, while 8 cities exhibit significantly higher emissions. In these 8 cities, waste management (solid waste and wastewater) contributes most to total emissions. Additionally, GHGSat data indicate that landfill emissions account for 10% to 50% of emissions in these cities, highlighting the critical role of solid waste management in reducing emissions.
How to cite: Lama, S., Maasakkers, J. D., Zhang, X., Varon, D. J., Sulprizio, M. P., Estrada, L. A., Balasus, N., Parker, R. J., and Aben, I.: Evaluating national & urban Indian methane emissions using satellites , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17010, https://doi.org/10.5194/egusphere-egu25-17010, 2025.
The annual increase of atmospheric CO2 exhibits significant inter-annual variability, primarily driven by fluctuations in the terrestrial carbon cycle. These inter-annual changes in CO2 concentrations provide a unique opportunity to study the biosphere's carbon uptake and release in response to shifting precipitation patterns and temperature extremes. Semi-arid ecosystems have been identified as significantly contributing to the inter-annual global carbon sink dynamics. However, the sparse coverage of in-situ CO2 measurements on the southern hemisphere leads to uncertainties in measurement-based carbon flux estimates for the extensive semi-arid regions located there. Also, dynamic global vegetation models (DGVMs) show a large spread in their carbon flux estimates pointing to an incomplete representation of semi-arid carbon cycle processes in most of the models. We demonstrate the potential of satellite data to improve sub-continental scale carbon flux estimates on the southern hemisphere and analyse the underlying biogenic processes.
We here discuss monthly net CO2 fluxes from 2009 to 2018 derived by assimilating Greenhouse Gases Observing Satellite (GOSAT) XCO2 measurements in the global atmospheric inversion TM5-4DVar. For the three semi-arid regions in the southern hemisphere, i.e. Australia (Metz et al., 2023), South American Temperate region and South Africa (Metz et al., 2024), we find that the DGVMs are not consistent, but single models agree well with the satellite inversion fluxes and Solar Induced Fluorescence (SIF) measurements. While the satellite inversion can only provide net land-atmosphere fluxes, those selected DGVMs model the vegetation gross fluxes and allow further analyses of the carbon exchange processes. We find a net release of CO2 caused by enhanced soil respiration following soil rewetting at the beginning of the rainy season. These CO2 emissions strongly shape the seasonal cycle of carbon fluxes in all three semi-arid regions, and in Australia, dominate the interannual flux variability. Our findings suggest that rain pulses and soil rewetting events in semi-arid regions can be analysed using satellite observations. These processes play an important role in constraining the global carbon budget and should be represented more accurately in global carbon cycle models to improve the estimation of the global carbon budget.
Metz, E.-M., et al., (2023). Soil respiration–driven CO2 pulses dominate Australia’s flux variability. Science, 379(6639), 1332-1335., https://doi.org/10.1126/science.add7833
Metz, Eva-Marie, et al. "Seasonal and inter-annual variability of carbon fluxes in southern Africa seen by GOSAT." EGUsphere 2024 (2024): 1-35. https://doi.org/10.5194/egusphere-2024-1955
How to cite: Vardag, S. N., Metz, E.-M., Basu, S., Jung, M., Artelt, L., and Butz, A.: Rewetting Driven Soil Respiration Shapes the Variability of Terrestrial CO2 Fluxes in Semi-arid Regions of the Southern Hemisphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9944, https://doi.org/10.5194/egusphere-egu25-9944, 2025.
Satellite observations of CO2 concentrations have limited spatial coverage, which makes it difficult to derive compete gridded maps of CO2 emissions. On the other hand, the co-emitted anthropogenic NOx emissions can be derived almost on a daily basis using the observations from the TROPOMI instrument on the Sentinel 5P satellite. We introduce an innovative approach to indirectly infer and map anthropogenic CO2 emissions using the co-emitted NOx emissions derived from TROPOMI NO2 observations using the DECSO algorithm. The satellite-derived emissions over Europe are close to the reported emissions indicating a low uncertainty of currently reported European emissions. The reported CO2 emissions over the Middle East and Africa are underestimated by about 40 % according our results, revealing significant reporting uncertainties. Our approach demonstrates the capability for fast and independent quantifying and mapping CO2 emissions on a continental scale based on global satellite observations.
The derived annual CO2 emissions derived are compared with the CAMS CO2 emission inventory for country totals and for individual cities. The results demonstrate the potential for DECSO to quickly quantify and map anthropogenic CO2 emissions based on Sentinel 5P observations.
How to cite: van der A, R., Lin, X., de Laat, J., Ding, J., and Eskes, H.: CO2 emission maps inferred from co-emitted anthropogenic NOx emissions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16982, https://doi.org/10.5194/egusphere-egu25-16982, 2025.
GHGSat launched its first satellite dedicated to carbon dioxide monitoring in October 2023, joining GHGSat’s ten satellite methane-sensing constellation. All the satellites are designed to measure and attribute emissions at the facility level, leveraging their ~30 meter-scale spatial resolution. Understanding the detection threshold of both CO2 and CH4 satellites is crucial, not only as a fundamental performance metric, but also for interpreting observations where no emissions are detected (null observations). This understanding is especially important when combining observations from multiple sites or times.
For methane-sensitive satellites, GHGSat has built a large dataset of controlled releases, including both self-organized and third-party single-blind studies. Analysis of this dataset shows a detection threshold of 102 kg/hr, with a 50% probability of detection (PoD) at a wind speed of 3 m/s. One shortcoming is that controlled releases repeatedly measure the same sites at varying source rates, and the number of controlled release sites is limited. These sites might not represent the full spectrum of measurement conditions encountered by the constellation around the world. To address this issue, we adapt the non-linear PoD model developed by Conrad et al.[1] with the goal of providing site- and time-specific detection thresholds.
We will also present an update on the performance of GHGSat’s first CO2-sensitive satellite. We will highlight the difference between CH4 and CO2 point source detection such as co-emission of CO2 with aerosols, multiple release points at a given facility and the high elevation of the release points. We will also present a preliminary analysis of detection threshold by comparing detection events and continuous emission monitoring data available from some power plants.
[1] Conrad, B. M., Tyner, D. R. & Johnson, M. R. Robust probabilities of detection and quantification uncertainty for aerial methane detection: examples for three airborne technologies. Remote Sens. Environ. 288, 113499 (2023).
How to cite: Strupler, M., Deslières, A., Girard, M., Jervis, D., MacLean, J.-P., Marshall, D., McKeever, J., Osterland, B., Qudsi, Z., Ramier, A., Tarrant, E., and Young, D.: Detection Limits of the GHGSat Constellation for Carbon Dioxide and Methane, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6912, https://doi.org/10.5194/egusphere-egu25-6912, 2025.
To support the goals of the Paris Agreement, monitoring and verification support (MVS) capacities focussing on anthropogenic greenhouse gas emissions are being developed, such as the EU’s emerging Copernicus CO2 Service and Germany’s ITMS (Integriertes Treibhausgas-Monitoringsystem). Satellite concepts capable of measuring atmospheric CO2 and CH4 concentrations on small spatial scales (10s of meters) have emerged as potential contributors to such MVS systems, through their ability to image the exhaust plumes of individual facilities. To quantify emissions based on these plume images, traditional mass balance methods require an accurate knowledge of the effective speed of the wind that transports the detected CO2 or CH4 plume. Uncertainty in the wind speed is the largest source of uncertainty in the estimated emissions. It has been proposed, however, that machine learning approaches might be able to estimate emission rates directly from the turbulent plume images without the need to impose wind speeds from external sources.
Here, we present our progress on developing a deep-learning-based emission rate estimator for plume images using convolutional neural networks. Our main focus lies on the improvement of the quality and certainty of deep learning models. Therefore, we provide a model that is capable of providing estimates with, on average, little to no bias over a large scale of flux rates. We present a feasible solution to existing biases, leading to a Pearson correlation coefficient of 97.98% for true and estimated fluxes. In addition, our model provides error estimates alongside its flux predictions, making a first step towards improving the certainty of estimated predictions. Further, we present our progress on making the model more stable across different wind speed situations, and potentially extracting effective wind speed information directly from image data. Thus, we are working towards applying deep-learning-based methods in a more stable and powerful approach that is capable of efficiently analyzing large amounts of incoming data.
How to cite: Plewa, T., Frankenberg, C., Butz, A., and Marshall, J.: AI-driven point source estimation for future satellite missions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10953, https://doi.org/10.5194/egusphere-egu25-10953, 2025.
In the support of the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission, SRON Netherlands Institute for Space Research developed the Remote sensing of Trace gas and Aerosol Product (RemoTAP) algorithm. RemoTAP is able to achieve simultaneous retrieval of trace gases and aerosol using measurements from the Multi-Angle Polarimeter (MAP) and CO2I Imager aboard the CO2M mission. At the same time, it has the capability to perform the retrieval of trace gas from only CO2I measurements.
This study evaluates the performance of RemoTAP for combined MAP-CO2I and CO2I-only retrievals, respectively. We base our evaluation on synthetic CO2M measurements simulated for realistic atmospheric (aerosol, cirrus), surface, geometry conditions. MAP-CO2I retrieval method can reduce the regional bias in column-averaged dry-air mole fraction of CO2 (XCO2) by a factor of 3. It shows that only by the inclusion of MAP measurements, the large aerosol-induced biases can be mitigated, resulting in the retrievals that meet the mission requirement (precision <0.7 ppm and bias <0.5 ppm).
In addition, RemoTAP has other functions to further improve the accuracy of trace-gas retrievals. It is able to retrieve cirrus at pixels with an optically thin layer of cirrus cloud. Instead of retrieving cirrus, we also provide the option to filter cirrus-contained pixels by non-scattering retrieval, which results in more accurate XCO2 retrievals but with less yield. To account for the uncertainties in surface pressure, which is related to the calculation of dry air column, RemoTAP has the option to retrieve O2 column which is proportional to dry air column from measurements of NIR band. Besides, RemoTAP retrieves Solar-Induced chlorophyll Fluorescence (SIF) over vegetation surface. The retrieval of cirrus, surface pressure/O2 column and SIF is performed simultaneously with the retrieval of other physical parameters, and the error induced by these factors in the XCO2 retrieval can be mitigated. Finally, we developed a method to perform bias correction and quality filtering using a neural network approach.
How to cite: Lu, S., Fu, G., Landgraf, J., and Hasekamp, O.: Simultaneous retrieval of trace gases and aerosol using RemoTAP – the global orbit ensemble study for the CO2M mission, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20046, https://doi.org/10.5194/egusphere-egu25-20046, 2025.
The past two decades have seen tremendous improvements in greenhouse gas (GHG) remote sensing from space, including global area flux mappers like SCIAMACHY, GOSAT, OCO-2, GOSAT-2, TROPOMI and OCO-3 among others, with more missions planned, such as CO2M. In the past decade there has also been an increase in GHG point source imagers, a field that has grown rapidly after initial successes using AVIRIS-NG and subsequent VSWIR spectrometers (coarser spectral resolution over a broader range). While area flux mapper missions have been effective at measuring GHG with high accuracy, fundamental gaps persist in the humid tropics, where data yields are 2-3 orders of magnitude lower than elsewhere.
Here, we discuss the Carbon Investigation (Carbon-I), which was selected for a Phase A mission concept study within NASA’s Earth System Explorer call. Carbon-I provides a unique combination of global land coverage, high spatial resolution, and very high sensitivity required to quantify CH4, CO2, and CO emissions at both the area and point source scale. Given the importance of the tropics for global carbon budgets and in particular natural methane emissions, Carbon-I specifically targets the remaining data and knowledge gaps within the tropics, enabling a step change in our capabilities of observing the tropics with more even temporal and spatial sampling.
Carbon-I is a single-band spectrometer covering the 2040 to 2380 nm spectral range with 0.7nm spectral sampling and spatial sampling ranging from ~30m in a local target mode to ~300m for global land mapping. We will discuss the sweet spot in the tradeoff between spatial and spectral resolution, the multi-species trace gas capabilities (CH4, CO2, CO, HDO, H2O, N2O, potentially Ethane), the capabilities to measure GHG area fluxes and point sources while minimizing surface interferences and our approach to account for atmospheric scattering effects.
How to cite: Frankenberg, C., Michalak, A., Jacob, D., Thorpe, A., Yin, Y., Bruhwiler, L., Kebreab, E., Hoyt, A., Turner, A., Wennberg, P., Green, R., Sanghavi, S., Thompson, D., Brodrick, P., and Chadwick, D.: Carbon-I, a NASA Earth System Explorer Mission concept for Greenhouse Gas Observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14549, https://doi.org/10.5194/egusphere-egu25-14549, 2025.
Over the past year, the National Centre for Earth Observation have been working to establish the Greenhouse gas Emissions Monitoring network to Inform Net-zero Initiatives for the UK (GEMINI-UK), a key part of the UK Greenhouse gas Emissions Measurement Modelling Advancement (GEMMA) programme. The GEMINI-UK network comprises ten Bruker EM27/SUN shortwave infrared spectrometers, and has been designed to help quantify regional net greenhouse gas (GHG) emissions across the UK, complementary to in situ air sampling measurements collected by the existing tall tower network. Taken together with inverse modelling efforts, these data will form the backbone of a pre-operational GHG emissions monitoring framework for the UK.
The GEMINI-UK instruments observe column concentrations of carbon dioxide, methane, and carbon monoxide in cloud-free conditions, which we use in to constrain regional flux estimates of these gases by way of Bayesian inverse methods. Using a dataset of simulated measurements based on the GEOS-Chem atmospheric chemistry and transport model, we have designed the measurement network to deliver the biggest error reductions in carbon dioxide flux estimates. We are also working closely with the GEMINI-UK host partners, including UK universities, schools, and NERC facilities, with the goal of promoting the open access and transparency of the collected data. Continuous and autonomous operation of the EM27/SUNs is made possible at each site by using an automated weatherproof enclosure, based on a design developed by University of Edinburgh researchers, which previously enabled year-round measurements to be collected during the UK DARE-UK experiment in central London. In this presentation we describe the first data, current status, and longer-term goals of GEMINI-UK, including an ongoing evaluation of the GEMINI-UK EM27/SUN that operates alongside a higher specification TCCON spectrometer at the Rutherford Appleton Laboratory in Harwell, Oxfordshire.
How to cite: Humpage, N., Palmer, P., Kurganskiy, A., Feng, L., Woodwark, J., Doniki, S., and Weidmann, D.: First data from GEMINI-UK, the UK national network of ground-based greenhouse gas observing spectrometers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16209, https://doi.org/10.5194/egusphere-egu25-16209, 2025.
Top-down estimation of greenhouse gas emissions requires the combination of reliable measurements of their atmospheric concentrations with atmospheric inversions. The German Integrated Greenhouse Gas Monitoring System (ITMS) combines atmospheric in situ and satellite measurements, transport modelling and inverse estimation techniques aiming at an operational top-down monitoring of greenhouse gas emissions. We contribute to this effort by establishing highly consistent and accurate observations of column-average mole fractions of carbon dioxide (XCO2), methane (XCH4) and carbon monoxide (XCO) using eight FTIR instruments across Germany.
We operate spectrometers of the Collaborative Carbon Column Observing Network (COCCON, EM27/SUN) and Total Column Carbon Observing Network (TCCON) located such that the measurements cover spatial gradients on the urban, regional and national scale. Urban gradients are covered with five FTIR distributed across the Munich urban region (MCCnet). The regional scale is represented by two FTIR in Karlsruhe and Heidelberg (Rhein-Neckar region) and two FTIRs in the Bremen region in Northern Germany. All instruments together allow for measuring gradients on the national scale. These measurements provide the means to validate both satellite observations and modelling results on the spatial scales relevant for future emission inversions. To meet the stringent requirements for consistency among all stations, we operate an additional EM27/SUN as travel standard for side-by-side measurements with all instruments. As such, we tie all instruments to a common scale and, via TCCON, to the World Meteorological Organization (WMO) scale. Here, we present the ITMS-FTIR network with a special focus on our calibration efforts during the first year of operation.
How to cite: Löw, B., Feld, L., Grosch, L., Klappenbach, F., Kleinschek, R., Li, J., Luther, A., Makowski, M., Neumann, N., Sindram, M., Stauber, J., Chen, J., Hase, F., Warneke, T., and Butz, A.: The ITMS-FTIR network for Germany: Providing consistent XCO2, XCH4 and XCO data for satellite and model validation on the urban, regional and national scale, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11005, https://doi.org/10.5194/egusphere-egu25-11005, 2025.
Increasing concentrations of greenhouse gases (GHGs) in the atmosphere are the primary driver of the observed rise in global surface temperatures, meanwhile exceeding 1°C above pre-industrial levels. Addressing this challenge requires linking GHG concentrations to specific anthropogenic and natural sources as part of the global carbon budget. This study investigates the relationship between GHG concentrations measured in Thessaloniki, Greece, and potential long-range transport sources using a clustering approach.
The GHG data were obtained from the EM27/SUN Fourier Transform Infrared (FTIR) spectrometer, a ground-based low-resolution infrared spectrometer operated in the framework of the Collaborative Carbon Column Observing Network (COCCON) at a mid-latitude urban site. The instrument provides column-averaged dry air molar fractions of CH₄, CO₂, CO, and H₂O. Meteorological data for trajectory simulations were derived from the Global Data Assimilation System (GDAS) with a spatial resolution of 1° × 1°.
Clustering analysis was performed using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Seven-day kinematic back trajectories were calculated for the period 2019–2024 at two arrival heights, 1500 m and 3000 m above mean sea level. The findings aim to specify the influence of long-range transport on GHG concentrations over Thessaloniki, contributing to a more complete understanding of regional GHG source-receptor relationships and transport patterns.
How to cite: Panou, T., Mermigkas, M., Topaloglou, C., Balis, D., Dubravica, D., and Hase, F.: "Investigating Regional and Long-Range Transport Contributions to GHG Concentrations of a Mid-Latitude Urban Site" , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15708, https://doi.org/10.5194/egusphere-egu25-15708, 2025.
Reducing emissions of greenhouse gases (GHGs) from urban areas – currently accounting for 70% of the global budget – are an integral part of the solution to meet net zero targets (IPCC, 2022). As part of the GEMINI+Edinburgh project (GHG Emissions Monitoring network to Inform Net-zero Initiatives +Edinburgh, Kurganskiy et al., 2025) we have developed an observational framework to determine long-term trends in GHG emissions from the City of Edinburgh, Scotland.
To determine these emissions, we use column concentrations of CO2 and methane retrieved from six EM27/SUN Fourier transform solar absorption spectrometers (“EM27”, Bruker GmbH, Germany) deployed in a ring around Edinburgh with 5 – 8 km separation. The spectrometers use the sun as their open-path source to measure solar radiation (4000 - 12000 cm cm-1, 0.5 cm-1 spectral resolution) from which we retrieve column abundances of CO2, methane, CO, O2 and H2O. We apply an upwind-downwind mass balance approach to the data collected from these six spectrometers to estimate city-wide net emissions. Spatial variations in near-surface wind fields are captured by eight automatic weather stations (Vaisala WXT530) and sonic anemometers (Gill WindSonic 75) co-located with each EM27 and on additional tall buildings.
We have developed methods to ensure that GEMINI+Edinburgh delivers long-term (O10 year) and reliable measurements to enable reliable CO2 and methane emission trends. As delivered, the EM27 is not weatherproof and not designed for long-term outdoor and unsupervised operation. To overcome these challenges, we have encased each instrument in a purpose-built weatherproof enclosure (Karn Scientific Ltd., Edinburgh). We demonstrate the enclosure performance by using co-located measurements from (un)enclosed EM27s during a series of intercomparisons and characterising the effect of the enclosure’s BK7 glass window. We employ a data processing workflow to enable long-term automated operation of the network, including an instrument meta data system, data transfer, processing, quick-look diagnostics plots, and archiving.
IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. doi: 10.1017/9781009157926
Kurganskiy, A., Feng, L., Humpage, N., Palmer, P. I., Woodwark, A. J. P., Doniki, S., Weidmann, D., 2025. The Greenhouse gas Emission Monitoring network to Inform Net-zero Initiatives UK (GEMINI-UK): network design, theoretical performance, and initial data. Submitted to Atmospheric Measurement Techniques.
How to cite: Morrison, W., Woodwark, J., Finch, D., and Palmer, P.: A ground-based remote sensing measurement network designed to infer net emission of CO2 and methane from the City of Edinburgh, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17625, https://doi.org/10.5194/egusphere-egu25-17625, 2025.
Precise observations of anthropogenic greenhouse gas (GHG) and air pollutant emissions are essential for improving emission inventories and evaluating the potential of their reduction, supporting the global stocktake. The global coverage of ship-, aircraft-, and ground-based observations by public and private networks, together with satellite observations of GHGs and other trace gases, is expanding. However, observations and reference data over ocean and coastal regions remain scarce.
We conduct continuous cargo ship-based observations with a novel semi-automatic Fourier transform infrared (FTIR) spectrometer combined with a VIS (visible spectral range) grating spectrometer to measure the column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4), carbon monoxide (XCO) and the vertical column densities of nitrogen dioxide (VCDNO2). Combined with simultaneous in situ observations (CO2, CH4, CO, NO2), we aim to constrain anthropogenic emissions and contribute to a satellite validation framework for upcoming satellite missions like the Global Observing SATellite for Greenhouse gases and Water cycle (GOSAT-GW) or the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission. These missions are designed to identify and monitor anthropogenic emissions by observing the GHG CO2 and the short-lived combustion tracer NO2 simultaneously. With our novel setup, we have the capability to validate these concurrent observations.
The cargo ship operates along major anthropogenic emission sources on Japan’s coast between the Tokyo metropolitan area and the island of Kyushu in the southwest with a weekly round-trip schedule. We present the initial analysis results of the combined columnar and in situ observations for emission plume detection and inventory validation, and provide perspectives of the setup for satellite validation and anthropogenic emission monitoring.
How to cite: Müller, A., Tanimoto, H., Frey, M. M., Enders, V., Patra, P. K., Sugita, T., Kleinschek, R., Voss, K., Butz, A., Morino, I., Nakaoka, S., Nara, H., and Machida, T.: Towards Shipborne Emission Monitoring and Satellite Validation of CO2, CH4, CO, and NO2 Through Simultaneous Columnar and In Situ Observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17804, https://doi.org/10.5194/egusphere-egu25-17804, 2025.
Satellite remote sensing of global greenhouse gas (GHG) concentrations provides invaluable information about GHG sources and sinks, supporting efficient climate mitigation policies. Recently, the accuracy targets of upcoming GHG satellite missions have become increasingly stringent (2 ppb of CH4; 1 ppm of CO2).
Up to now, calibration and traceability of satellite GHG observations relies on two networks of ground-based remote sensing stations: the Total Carbon Column Observing Network (TCCON) and the COllaborative Carbon Column Observing Network (COCCON). Both networks are able to observe the same quantity as the satellite instruments: column-averaged dry-air mole fraction of CO2 and CH4. They also observe N2O, which will likely become another key GHG to be monitored in the future. For traceability, both networks rely on regular aircraft and balloon measurements with in-situ instruments that are traceable to the WMO scale for GHGs.
The 24GRD06 MetCTG project aims at greatly improving the accuracy of underlying spectral line parameters for the satellite GHG retrievals and validating the accuracy with in situ and ground-based observations. This will establish traceability to SI and improve data comparability and trustworthiness among GHG satellite missions. It will also improve consistency among ground-based sites and considerably reduce the need for costly aircraft calibrations.
The project joins the European metrology community with the TCCON and COCCON communities to provide the best ground-based reference for current and future GHG satellite missions.
Acknowledgments: The project (24GRD06 MetCTG) receives funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States.
How to cite: Feist, D. G., Birk, M., Prudenzano, D., Wagner, G., Li, G., Lüttschwager, A., Monte, C., Stosch, R., Taubert, D., Butz, A., Hase, F., Chen, J., Kivi, R., Seppa, J., Armante, R., Tran, H., Campargue, A., Kassi, S., Mondelain, D., Beltramino, G., Durbiano, F., Fernicola, V., Rosso, L., Lee, S., Chomski, M., Gruszczynski, M., Glowacki, P., Lisak, D., Masłowski, P., Ciuryło, R., Mohn, J., Brewer, P., Coleman, M., Gardiner, T., Nehrbass-Ahles, C., Pearce, R., Rennick, C., Tennyson, J., Polyansky, O., Harrison, J., Gozonunde, C., and Nasibli, H.: Implementation of SI-traceability in the TCCON and COCCON observations: the Metrology for Comparable and Trustworthy Greenhouse gas remote sensing datasets (24GRD06 MetCTG) project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15077, https://doi.org/10.5194/egusphere-egu25-15077, 2025.
Current spectrometers provide high-quality absorption spectra from both ground-based direct sun measurements and spaceborne backscatter measurements. Accurate retrievals of atmospheric CO2 concentrations from these measured spectra are fundamental for modelling large-scale atmosphere-surface exchange fluxes. When retrieving CO2 concentrations from measured spectra, high-quality spectroscopic reference data are essential to drive radiative transfer simulations and to enable accurate retrievals. Here, we investigate how various modern molecular absorption cross-section datasets affect CO2 retrievals in the 1.6 μm and 2 μm regions. This includes recent parameter sets derived from laboratory measurements at the German Aerospace Center (DLR e.V.) for line-mixing parameterizations (Birk et al., 2024) with separate continuum data, which were obtained in the frame of the ESA-funded project ISOGG (Improved Spectroscopy for satellite measurements Of Greenhouse Gases). We compare these new data to those from HITRAN 2020 (Gordon et al., 2022) with and without speed-dependent Voigt profile extension as well as to the ABSCO tables (Devi et al., 2016).
To evaluate the quality of the spectroscopic databases, we submit high-resolution direct-sun spectra collected by the TCCON (Total Carbon Column Observing Network) spectrometer at Karlsruhe to our RemoTeC retrieval algorithm under variation of the driving spectroscopic parameters. We evaluate the goodness of fit, systematic spectral residuals as well as spurious dependencies of the retrieved CO2 concentrations on slant airmass. We further use one year of GOSAT satellite measurements to assess whether and how differences in CO2 concentrations retrieved under variation of the spectroscopic parameters show dependencies on geophysical parameters such as latitude, season or surface type. Our analyses show that the new DLR cross sections and the HITRAN 2020 with speed dependence lead to noticeable improvements in spectral line modelling which in turn affects airmass dependencies as well as latitudinal and seasonal biases. Including the CO2 continuum from the DLR dataset further improves the fit quality. In contrast, using the ABSCO tables results in larger residuals and poorer fits compared to the standard HITRAN 2020 cross sections, particularly in the 2 μm region.
Birk, M., Röske, C., Wagner, G., & Hodges, J. T. (2024, June). New spectroscopic database of CO2 in the 1.6 and 2.0 µm spectral regions for remote sensing. The 17th International HITRAN Conference, Cambridge (MA), United States. https://elib.dlr.de/208834/
Devi, V. M., Benner, D. C., Sung, K., Brown, L. R., Crawford, T. J., Miller, C. E., Drouin, B. J., Payne, V. H., Yu, S., Smith, M. A. H., Mantz, A. W., & Gamache, R. R. (2016). Line parameters including temperature dependences of self- and air-broadened line shapes of 12C16O2: 1.6-μm region. Journal of Quantitative Spectroscopy and Radiative Transfer, 177, 117–144. https://doi.org/10.1016/j.jqsrt.2015.12.020
Gordon, I. E., Rothman, L. S., Hargreaves, R. J., Hashemi, R., Karlovets, E. V., Skinner, F. M., Conway, E. K., Hill, C., Kochanov, R. V., Tan, Y., Wcisło, P., Finenko, A. A., Nelson, K., Bernath, P. F., Birk, M., Boudon, V., Campargue, A., Chance, K. V., Coustenis, A., … Yurchenko, S. N. (2022). The HITRAN2020 molecular spectroscopic database. Journal of Quantitative Spectroscopy and Radiative Transfer, 277, 107949. https://doi.org/10.1016/j.jqsrt.2021.107949
How to cite: Thiemann, L., Schmitt, T., Birk, M., Röske, C., Wagner, G., and Butz, A.: Investigating the Impact of Modern Absorption Cross-Section Databases on CO2 Retrievals, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10453, https://doi.org/10.5194/egusphere-egu25-10453, 2025.
Monitoring greenhouse gas (GHG) emissions is crucial for mitigating global warming and the associated climate change. Various satellite missions are dedicated to measuring CO2 globally, demonstrating their capability to detect GHG emission hotspots and quantify emissions effectively. However, due to the limited revisit frequency and spatial coverage of contemporary high-resolution CO2 monitoring missions such as OCO-2 and OCO-3, continuous daily monitoring of CO2 emissions from specific sources remains challenging. To overcome these limitations, combining data from different satellite missions is a promising approach. Missions such as TROPOMI provide daily monitoring of various trace gas concentrations (e.g., NO2, CO, SO2).
CO2 is emitted from sources along with other species, such as CO and NO2. Therefore, it is possible to infer CO2 emissions from the emissions of co-emitted species. Compared to other co-emitted species, NO2 has a relatively short lifetime of a few hours to a day, which makes it easier to distinguish enhancements from background concentrations.
Individual power plant CO2 emissions are not reported in many parts of the world. Some countries, such as India, have started reporting daily coal consumption data for individual power plants since 2022. The amount of coal consumed can be used to estimate CO2 emissions due to its strong linear correlation with CO2 emissions. To overcome the limitations in reporting CO2 emissions from power plants globally, we evaluate the potential of TROPOMI NO2 measurements for monitoring CO2 emissions. This is achieved by comparing the derived daily NO2 emissions with the daily coal consumption of individual power plants in India.
A Gaussian plume (GP) model accounting for NO2 lifetime was used to estimate the daily NO2 emissions along with the NO2 lifetime. In our study, we also attempted to address a key issue found in previous literature: the presence of an additional emission source downwind of the main source can render both NO2 emission estimates and NO2 lifetime estimates unreliable. We address this issue by simultaneously modeling and fitting the NO2 emissions and NO2 lifetime of the additional source, in conjunction with the main power plant GP inversion framework.
Our findings show a moderate to good linear relationship between daily NO2 emissions and daily coal consumption of individual power plants. This suggests that TROPOMI NO2 measurements can effectively support the monitoring of CO2 emissions. Finally, this study highlights that upcoming satellite missions monitoring NO2 can be used, along with GHG satellite measurements, for regular monitoring of carbon emissions.
How to cite: Chen, J. and Balamurugan, V.: Assessing the Capability of Sentinel-5P (TROPOMI) NO2 Measurements to Monitor Point Source CO2 Emissions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18869, https://doi.org/10.5194/egusphere-egu25-18869, 2025.
Permafrost degradation in the Arctic is accelerating and expected to enhance greenhouse gas (GHG) emissions. The Arctic Methane and Permafrost Challenge (AMPAC) was initialized by NASA and ESA as a transatlantic networking action striving to promote scientific research and improve observational capabilities. Earth Observation technology must be harnessed, expanded and synergies exploited to accurately quantify and better understand the state of the permafrost and coincident methane emissions. AMPAC aims at improving the observation capacity over polar regions by evaluating dedicated campaign activities, by analyzing satellite data, and by identifying satellite retrieval improvements. AMPAC provides suggestions for the enhanced exploitation of the increasing Earth observation (EO) capacities of land surface, cryosphere, biosphere and atmosphere missions to enhance the scientific understanding of changes in Arctic permafrost regions and methane emissions and to bridge the gap between top-down (T-D) and bottom-up (B-U) estimates of methane fluxes in the changing Arctic.
In particular, monitoring of methane concentrations as well as landcover properties related to wetland and freeze/thaw dynamics is needed. Upcoming synthetic aperture radar missions and constellations of multiple multispectral sensors are expected to advance relevant monitoring capabilities significantly. This will allow better representation of seasonality and advance methane source attribution in general. In addition, continuity of current missions providing greenhouse gas observations, including methane, is crucial. Active optical instruments (lidar) developed for concentration retrieval are expected to substantially enhance detection capabilities across the Arctic.
We provide an overview of relevant current and approved atmosphere and land-focused satellite missions of NASA, NOAA, ESA and DLR/CNES with emphasis on advancements and remaining gaps in the context of AMPAC.
How to cite: Bartsch, A., Gay, B. A., Schüttemeyer, D., Malina, E., Miner, K., Grosse, G., Fix, A., Tamminen, J., Bösch, H., Parker, R. J., Rautiainen, K., Hashemi, J., and Miller, C. E.: The Potential for Future Satellite Missions to Advance the Arctic Methane Permafrost Challenge (AMPAC), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15004, https://doi.org/10.5194/egusphere-egu25-15004, 2025.
Spectrally high-resolution passive remote sensing imaging spectrometers are becoming increasingly important for reliable quantification of anthropogenic greenhouse gas (GHG) emissions from a wide variety of carbon dioxide (CO2) and methane (CH4) sources. These nadir-looking air- or spaceborne instruments collect backscattered solar radiation from the Earth's surface, from which 2D atmospheric concentration maps of CO2 and CH4 are retrieved. Using, for example, mass balance approaches, emission rates can be derived from the observed GHG concentration gradients or plumes.
Depending on the atmospheric conditions, these plumes can be Gaussian-like shaped or severely distorted by the prevailing turbulence during a single overpass. In the case of a calm atmosphere and special viewing geometries, combined with an elevated emission height, such as CO2 emissions from a coal-fired power plant chimney, the observed plume appears widened, or even two plumes are detected from the same point source in the imaging data. This secondary plume is shifted in the opposite direction to the position of the sun and the effect is most pronounced close to the emission source and the higher the point of release and the solar zenith angle (sza) are. The effect is less noticeable as the gases are better mixed both horizontally and vertically down to the surface when advecting further downwind of the source.
In this work, we will analyse passive remote sensing observations from the MAMAP2D-Light imaging spectrometer collected over a coal-fired power plant near Edmonton, Canada, during the CoMet 2.0 Arctic mission in 2022. The power plant was investigated for distinct double plume structures on two different days with near-perfect conditions (moderately high sza and sun perpendicular to the prevailing wind direction). We will compare these with simultaneously acquired observations from an active lidar remote sensing instrument (CHARM-F) flown aboard the same aircraft. As the CHARM-F instrument uses its own light source in the nadir viewing geometry, no plume splitting is expected. We will also show that the plume broadening or splitting in the passive remote sensing instrument does not lead to a double counting of molecules and thus not to an increased emission rate of the power plant estimated from the observations. Furthermore, we compare the MAMAP2D-Light concentration gradients with Gaussian plume model simulations using the conditions encountered during the flight, which also show a similar plume widening or double-plume structure as observed in the real measurements. This effect can, for example, also be used in an inverse manner to retrieve the plume height of emissions. Conclusions on the conditions this plume splitting is observed by imaging spectrometer will be discussed.
How to cite: Krautwurst, S., Borchardt, J., Wolff, S., Huhs, O., Fruck, C., Gerilowski, K., Kiemle, C., Quatrevalet, M., Wirth, M., Burrows, J. P., Fix, A., Bovensmann, H., and Boesch, H.: Ghost Plumes: Artificial splitting of greenhouse gas emission plumes in passive remote sensing observations in special viewing geometries, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6317, https://doi.org/10.5194/egusphere-egu25-6317, 2025.
Methane (CH₄) is a potent greenhouse gas that plays a significant role in global warming, with over 60% of CH₄ emissions attributed to human activities. A substantial portion of these anthropogenic emissions originates from a small number of super-emitters, making their monitoring crucial for understanding emission patterns and implementing targeted mitigation strategies. The TROPOspheric Monitoring Instrument (TROPOMI), onboard the ESA Sentinel-5P satellite, provides daily global observations of methane mixing ratios at high spatial resolution, enabling the detection and analysis of plumes associated with these super-emitters.
To detect methane plumes globally in TROPOMI data, a two-step machine learning pipeline is employed, with weekly results now officially part of the Copernicus Atmosphere Monitoring Service (CAMS) products. The first step utilizes a convolutional neural network to identify plume-like structures in the methane data. A support vector classifier is then applied to filter out retrieval artifacts, ensuring the accurate identification of true methane emissions. Detected plumes are categorized by emission rate, and human experts conduct final verifications. In this study, we present the results for the full year 2024, during which a total of 2,311 methane plumes were identified, providing a comprehensive overview of global super-emitter activity. Preliminary analysis based on bottom-up emission inventories shows that the majority of plumes are associated with oil and gas production, landfills, and coal mining activities.
This study provides a detailed analysis of methane plume detections for 2024, highlighting temporal variations and regional hotspots. By focusing on the detected plumes rather than the detection methodology, this work delivers valuable insights into the spatial and temporal dynamics of methane emissions. The findings contribute to the growing body of knowledge required to address super-emitter mitigation and support informed policymaking for reducing global methane emissions.
How to cite: Lopez Norena, A. I., Maasakkers, J. D., Schuit, B., Kurchaba, S., Dogniaux, M., Sharma, S., and Aben, I.: Global Detection and Analysis of Methane Plumes in 2024 Using TROPOMI Observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19252, https://doi.org/10.5194/egusphere-egu25-19252, 2025.
The greenhouse gases (GHG) methane (CH4) and carbon dioxide (CO2) have been emitted at an increasing rate since the Industrial Revolution, leading to amplified global warming. The Paris agreement, signed by 175 nations, represents the world’s first sound political framework to regulate GHG emissions. It entails a need to quantify GHG fluxes, ideally with global coverage.
Since the pioneering missions able to detect and quantify trace gases in the Troposphere, green gas monitoring instrument (GMI) and scanning imaging absorption spectrometer for atmospheric cartography (SCIAMACHY) almost 30 years ago, a number of satellite missions that provide global coverage have been launched and are used to serve that need. There is, however, a significant discrepancy between bottom-up GHG emission estimates from inventories and top-down estimates using a combination of space-borne GHG concentration measurements and atmospheric dispersion modeling. Over the last 12 years or so, a new generation of satellites-borne imaging spectrometers emerged with sub-kilometre pixel resolution, able to map trace gas plumes and thus able to quantify GHG fluxes directly at the source, contributing to improved GHG inventories. Among those are the first commercial Earth observation missions to monitor GHG sources.
The commercial AIRMO mission aims to quantify GHG fluxes, notably CH4, in the planetary boundary layer using a combination of push-broom spectrometer, pulsed micro-lidar and visible camera. Raw lidar and spectrometer data (level-0 data) are processed (level-1b) to retrieve satellite images of CH4 and CO2 (level-2), from which images of column averaged enhancements are retrieved (level-3) and mass flux from point sources (level-4) are derived. This work will report on results of a sensitivity analyses aimed to identify the variables with the highest impact on level-4 error, including instrumental parameters (e.g., signal-to-noise ratio SNR, integration time, detector smile) and environmental variables (e.g., wind speed, surface albedo, aerosols). The approach used here is a combination of top-down and bottom-up analysis. The top-down analysis starts from the level-4 requirement of 100 kgCH4 /h and estimates from this the required precision and accuracy (bias). The bottom-up analysis simulates, end to end (from level-0 to level-4) or between sub-levels, the error propagation, validating the top-down approach. From the sensitivity study an error budget is established.
How to cite: Queisser, M., Armadillo, E., Tomás, S., Vilaseca, D., and Stepanova, D.: End-to-end simulations for greenhouse gas monitoring from space with a spectrometer - lidar - camera sensor triplet, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8353, https://doi.org/10.5194/egusphere-egu25-8353, 2025.
Satellite observations of total column methane atmospheric mixing ratios (XCH4) combined with atmospheric transport inverse modeling offer enhanced capabilities to monitor the methane (CH4) emissions at regional scale.
The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite provides XCH4 with global daily coverage and a relatively high (5.5×7 km²) horizontal resolution since 2017. Widely used for the hotspot detection and quantification, TROPOMI-CH4 data is also exploited in regional and global CH4 flux inversions.
Three retrieval products of XCH4are produced and routinely updated from TROPOMI: the SRON official product, the WFMD product by the University of Bremen and the BLENDED product by the University of Harvard. The official dataset (v2.04) relies on the RemoTeC full-physics algorithm, which retrieves atmospheric methane concentration alongside atmospheric scattering properties. The WFMD scientific product is based on the University of Bremen’s Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) and a machine learning classifier for quality filtering. The BLENDED product combines S5P-TROPOMI and GOSAT-TANSO retrievals. It is a post-processed of the official TROPOMI product, correcting biases using a machine learning model trained on collocated observations from both instruments. Despite recent advances in retrieval techniques, inter-product comparisons reveal notable differences in quality filtering, observed XCH₄ values, and associated uncertainties. It leads to discrepancies in flux estimates derived from inversions, particularly at local and country scales.
We assimilate these three TROPOMI XCH4products into regional atmospheric inversions of CH₄ emissions over Europe at a 0.5°×0.5° resolution, for the year 2019. The inversions are conducted using the CHIMERE transport model within the inverse modeling platform Community Inversion Framework (CIF). In situ surface measurements are used for validation. We investigate the primary factors contributing to the inter-product differences, including albedo, aerosols and striping patterns. We also perform Observing System Simulation Experiments (OSSE) with synthetic pseudo-observations and perturbed prior fluxes to assess the sensitivity of the system to observations and isolate the causes of the differences in inversion results. We inquire into the impact of observation density, retrieval errors and inter-product biases on the posterior fluxes. The resulting methane emissions budgets are compared at pixel, country and regional scales, providing insights into the consistency of TROPOMI-based regional inversions.
How to cite: Berchet, A., Sicsik-Paré, A., Pison, I., Fortems-Cheiney, A., Broquet, G., and Potier, É.: Can we obtain consistent emissions in Europe from three different CH4 TROPOMI products?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16665, https://doi.org/10.5194/egusphere-egu25-16665, 2025.
Methane (CH4), a greenhouse gas 86 times more potent than carbon dioxide (CO2) over 20 years, has become one of the main drivers of climate change, with atmospheric levels doubling since pre-industrial times. Among its various natural and anthropogenic sources, such as oil and gas systems, coal mines, or landfills, the Darvaza gas crater in Turkmenistan stands out as a unique and persistent contributor. This crater, usually known as "Door to Hell", is located in the Amu-Darya basin, a geological formation replete with large quantities of oil and natural gas, in which methane is predominant. In 1971, a drilling operation for natural gas by a soviet geologist caused the ground to collapse. The resulting crater measured approximately 70 meters in diameter and 20 meters deep. To mitigate the release of hazardous gases, authorities ignited the escaping gas, burning without interruption so far. However, since last year, the fire in the crater has been reduced by the Turkmenistan government, as we can monitor using the VIIRS Fires and Thermal Anomalies product.
Our work focuses on detecting and quantifying the Darvaza methane emissions, trying to confirm whether there is a correlation between fire reduction and emissions. At the moment, we have detected more than 20 methane emissions using the hyperspectral imaging spectrometers EnMAP, PRISMA, and EMIT spaceborne instruments. The emissions range is between 1.000-3.000 kg/h, amounting to thousands of tonnes of CH4 annually.
In addition to quantifying emissions, we examined the chronology of the crater flames. By analyzing radiance and thermal bands from Landsat 4-5, we determined the onset of the crater fire in late 1987 or early 1988, a detail previously shrouded in uncertainty. This revelation contributes to the temporal analysis of this crater and provides key information for estimating the total amount of methane released by the Darvaza crater to date.
Lastly, the unique conditions at Darvaza—continuous methane release and decades of intense fire—may have significantly altered the surrounding environment. To explore this possibility, we investigate soil composition and mineralogy changes using geological indices. This analysis aims to understand the broader environmental impact of the crater, offering insights into the long-term effects of such phenomena.
How to cite: Valverde, A., Irakulis-Loitxate, I., Gorroño, J., and Guanter, L.: Analysis of Methane Emissions from the Darvaza Gas Crater, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11171, https://doi.org/10.5194/egusphere-egu25-11171, 2025.
Nations are accountable for their GHG emissions, and since the Paris Agreement, progress towards national emission reductions is tracked. To facilitate this, atmospheric inversion modelling is employed as the state of-the-art means to collect information from GHG observations to quantify sources and sinks. High-resolution estimation of GHG fluxes in Northern High Latitudes greatly benefits from developments in satellite data analysis and computational methods. FICOCOSS project develops these methods and assimilates OCO-2 satellite data in atmospheric inversion models (CIF-FLEXPART, CIF-TM5-MP) to estimate CO2 sources and sinks. We prepare for the high intensity CO2M satellite by developing more efficient computational methods related to e.g. large error covariance matrix operations and satellite retrieval processing. Preliminary findings indicate that more efficient methods can be developed for using satellite CO2 data in high resolution inversions.
How to cite: Aalto, T., Amoros, L., Lamminpää, O., Lindqvist, H., Mengistu, A., Mikkonen, A., Pietarila, M., Pihlajamäki, A., Tamminen, J., Tsuruta, A., and Ward, R.: Using satellite data and atmospheric inversion modelling to estimate CO2 budgets in nationally relevant scales: project FICOCOSS, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19645, https://doi.org/10.5194/egusphere-egu25-19645, 2025.
With the growing interest to identify and quantify methane (CH4) emissions from various sources around the globe, the development and launches of satellite imagers tracking CH4 plumes have accelerated during the past decade. Thanks to high-resolution images collected by PRISMA (30-m resolution), Sentinel-2 (20-m resolution), or Tanager-1 of Carbon Mapper (30-m resolution), it is now possible to sample CH4 plumes at small scales to enable source attribution and quantification at lower detection levels. However, high-resolution images also come with limitations, due to the dominance of small-scale turbulence physics near the source. Therefore, Large Eddy Simulation (LES) modelling becomes necessary to resolve the turbulence, leading to more robust emission quantification methods. The Fire Dynamics Simulation (FDS) model offers unique capabilities by allowing to introduce infrastructures, terrain topologies, and roughness, individual trees (incl. leaves, branches, tree shapes), surface temperature gradients, velocity of the gas release, velocity of the leaked air, and to simulate the dynamics of the plume at a high resolution near the source and coarse resolution away from the source (adaptive mesh refinement). Using such high-resolution LES modelling allows us to simulate the spatial structure of the CH4 plumes, at various distances from the source, under different meteorological conditions (forced by wind measurements or re-analysis products). We aim here to (i) define more rigorously the effective wind speed used by the Integral Mass Enhancement (IME) method, (ii) to determine the sensitivity to external parameters that affect the plume dynamics, and (iii) to analyze complicated plumes (excluded in current IME analyses) thanks to our LES simulations offering additional detections to current monitoring systems (e.g., MARS).
More specifically, we compare and evaluate the importance of all the environmental conditions (topography, obstacles) and the characteristics of the source (temperature, velocity, height) affecting the dynamics of the turbulent CH4 plumes to determine the most favorable conditions and the uncertainties in IME estimates diagnosed from satellites and aircraft measurement campaigns. We also determine the sensitivity of the emissions to the effective wind speed simulations as a function of distance to the source and its comparison with existing wind speed calculation methods (e.g., extrapolation from 10-m wind speed measurement) used in current mass balance approaches. This study leads us to discuss the use of high-resolution LES simulations in mass balance calculations to produce more reliable estimates of facility-level sources around the globe.
How to cite: Yuvaraj, R., Lauvaux, T., Abdallah, C., Chulakadabba, A., Wofsy, S., and Groshenry, A.: High resolution Turbulence modelling to improve complicated methane emissions observed from Satellite Imagery, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11707, https://doi.org/10.5194/egusphere-egu25-11707, 2025.
Posters virtual: Wed, 30 Apr, 14:00–15:45 | vPoster spot 5
EGU25-18600 | Posters virtual | VPS3
A tropical EM27/SUN network for satellite validation and long term observationsWed, 30 Apr, 14:00–15:45 (CEST) vPoster spot 5 | vP5.15
The EM27/SUN instrument is a FTIR spectrometer allowing to retrieve total atmospheric column abundance of CO2, CH4, CO and H2O. LSCE is currently developing a tropical network in the framework of the OBS4CLIM French project.
OBS4CLIM aims at deploying five EM27 at observatories located in tropical (Bolivia, French Guiana, Morocco, Ivory Coast) and background regions (Amsterdam Island, Indian Ocean) for long-term observations and satellite validation purposes (TROPOMI, OCO-2/3, GOSAT, MicroCarb). The chosen stations are also part of French National Observation Service and benefit from in situ greenhouse gas measurements.
The rapid growth of this EM27/SUN network requires developing tools to ensure data quality and availability. Therefore, LSCE has developed:
- An automatic data treatment chain based on PROFFAST (developed and maintained at KIT). Two models are used as a priori profiles (GGG2020, and CAMS) allowing to retrieve daily data in near real-time (NUBICOS project).
- Automatic enclosure systems to protect the instrument from a rough environment. This system allows increasing drastically the daily observations and data availability.
Four of the five stations are fully operational. We will present in details the network construction and the first measurement results.
How to cite: Lopez, M., Cassagne, M., Leuridan, H., Ticona, L., Burban, B., Mellouki, W., Hazan, L., and Ramonet, M.: A tropical EM27/SUN network for satellite validation and long term observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18600, https://doi.org/10.5194/egusphere-egu25-18600, 2025.
EGU25-10301 | ECS | Posters virtual | VPS3
A comprehensive analysis of regional spatiotemporal methane enhancements and trends in the Mediterranean, using ground-based FTIR measurements and CAMS observationsWed, 30 Apr, 14:00–15:45 (CEST) | vP5.16
Increased concentrations of greenhouse gases in the atmosphere have resulted in a rise in the Earth's average temperature in the last decades. Methane (CH4), the second most important anthropogenic greenhouse gas after carbon dioxide (CO2), is considered to be 2.6 times higher than pre-industrial levels (Jackson et al., 2024). CH4 is 28 times more efficient at trapping heat than CO2 over a 100-year period and 80 times more powerful over 20 years, even though it is present in smaller quantities in the atmosphere and has a shorter lifespan than CO2. A special interest lies in the monitoring of urban areas, because of their substantial role in global human-made emissions. Methane emissions include agriculture, particularly from livestock and rice paddies, which constitute the largest source, while fossil fuel activities contribute in the global methane budget as well. The rise in emissions from these sectors is mainly driven by increased activities in developing regions and the intensified extraction and use of fossil fuels, revealing an alarming growth rate of CH4.
In this study, we present the column-averaged dry air mole fractions of methane (XCH4) over Thessaloniki, Greece (Mermigkas et al., 2021), using a portable EM27/SUN ground-based FTIR spectrometer, operating under the umbrella of COllaborative Carbon Column Observing Network (COCCON), covering the period from 2019 to 2023. To analyze methane's long-term variability and trends, we incorporate reanalysis data from the Copernicus Atmosphere Monitoring Service (CAMS) and more specifically from the EAC4 (ECMWF Atmospheric Composition Reanalysis 4) (Inness et al., 2019). This combined dataset allows us to examine the increasing methane concentrations over time, highlighting significant regional enhancements observed in Greece and Italy from 2019 to 2023.
To separate excess signals from background variations, filters with a characteristic duration are used depending on whether long-range or short-range enhancements are of interest. Short-range variations of greenhouse gases can potentially capture signatures of anthropogenic emission enhancements. To that end, we subtract the corresponding 3-hourly averaged XCH4 value for the same season, as the 3-hourly data point. This process is repeated for each year (2019-2023) separately to remove long-term trends. This approach allows for a more accurate assessment of CH4 concentration anomalies, ensuring that seasonal patterns are appropriately considered in the analysis.
Acknowledgement
"This project has received funding from the European Union’s Horizon Europe Research and Innovation programme under Grant Agreement No 101182007".
References
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How to cite: Mermigkas, M., Kartsios, S., Hase, F., Topaloglou, C., Dubravica, D., Panou, T., Balis, D., and Amiridis, V.: A comprehensive analysis of regional spatiotemporal methane enhancements and trends in the Mediterranean, using ground-based FTIR measurements and CAMS observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10301, https://doi.org/10.5194/egusphere-egu25-10301, 2025.
