Christian Fruck

Methane (CH₄), alongside carbon dioxide (CO₂), is a key driver of anthropogenic climate change. Reducing CH₄ is crucial for short-term climate mitigation. Waste-related activities, such as landfills, are a major CH₄ source, even in developed countries. Atmospheric concentration measurements using remote sensing (RS) offer a powerful way to quantify these emissions. We study waste facilities near Madrid, Spain, where satellite data indicated high CH₄ emissions. For the first time, we combine passive imaging (Methane Airborne Mapper 2D – Light, MAMAP2DL) and active lidar (CO₂ and CH₄ Atmospheric Remote Monitoring – Flugzeug, CHARM-F) remote sensing aboard the German High Altitude and Long Range Research Aircraft (HALO), supported by in situ instruments, to quantify CH₄ emissions. Using the CH₄ column data and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis v5 (ERA5) model wind information validated by airborne measurements, we estimate landfill emissions through a cross-sectional mass balance approach. Strong emission plumes are traced up to 20 km downwind on 4 August 2022, with the highest CH₄ column anomalies observed over active landfill areas in the vicinity of Madrid, Spain. Total emissions are estimated to be up to ∼ 13 t h⁻¹. Single co-located plume crossings from both instruments agree well within 1.2 t h⁻¹ (or 13 %). Flux errors range from ∼ 25 % to 40 %, mainly due to boundary layer (BL) and wind speed variability. This case study not only showcases the capabilities of applying a simple but fast cross-sectional mass balance approach, along with its limitations due to challenging atmospheric boundary layer conditions, but also demonstrates, to our knowledge, the first successful use of both active and passive airborne remote sensing to quantify methane emissions from hotspots and independently verify their emissions.

Methane (CH₄), alongside carbon dioxide (CO₂), is a key driver of anthropogenic climate change. Reducing CH₄ is crucial for short-term climate mitigation. Waste-related activities, such as landfills, are a major CH₄ source, even in developed countries. Atmospheric concentration measurements using remote sensing offer a powerful way to quantify these emissions. We study waste facilities near Madrid, Spain, where satellite data indicated high CH₄ emissions. For the first time, we combine passive imaging (MAMAP2DL) and active lidar (CHARM-F) remote sensing aboard the German research aircraft HALO, supported by in situ instruments, to quantify CH₄ emissions. Using the CH₄ column data and ECMWF-ERA5 model wind information validated by airborne measurements, we estimate landfill emissions through a cross-sectional mass balance approach. Strong emission plumes are traced up to 20 km downwind on the 4^th August 2022, with the highest CH₄ column anomalies observed over active landfill areas in the vicinity of Madrid, Spain. Total emissions are estimated at ~13 th^-1. Single co-located plume crossings from both instruments agree well within 1.2 th^-1 (or 13 %). Flux errors range from ~25 to 40 %, mainly due to boundary layer and wind speed variability. This case study not only showcases the capabilities of applying a simple but fast cross-sectional mass balance approach, as well as its limitations due to challenging atmospheric boundary layer conditions, but also demonstrates the, to our knowledge, first successful use of both active and passive airborne remote sensing to quantify methane emissions from hot spots and independently verify their emissions.

Methane (CH₄), alongside carbon dioxide (CO₂), is a key driver of anthropogenic climate change. Reducing CH₄ is crucial for short-term climate mitigation. Waste-related activities, such as landfills, are a major CH₄ source, even in developed countries. Atmospheric concentration measurements using remote sensing offer a powerful way to quantify these emissions. We study waste facilities near Madrid, Spain, where satellite data indicated high CH₄ emissions. For the first time, we combine passive imaging (MAMAP2DL) and active lidar (CHARM-F) remote sensing aboard the German research aircraft HALO, supported by in situ instruments, to quantify CH₄ emissions. Using the CH₄ column data and ECMWF-ERA5 model wind information validated by airborne measurements, we estimate landfill emissions through a cross-sectional mass balance approach. Strong emission plumes are traced up to 20 km downwind on the 4^th August 2022, with the highest CH₄ column anomalies observed over active landfill areas in the vicinity of Madrid, Spain. Total emissions are estimated at ~13 th^-1. Single co-located plume crossings from both instruments agree well within 1.2 th^-1 (or 13 %). Flux errors range from ~25 to 40 %, mainly due to boundary layer and wind speed variability. This case study not only showcases the capabilities of applying a simple but fast cross-sectional mass balance approach, as well as its limitations due to challenging atmospheric boundary layer conditions, but also demonstrates the, to our knowledge, first successful use of both active and passive airborne remote sensing to quantify methane emissions from hot spots and independently verify their emissions.

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.

Methane (CH₄), alongside carbon dioxide (CO₂), is a key driver of anthropogenic climate change. Reducing CH₄ is crucial for short-term climate mitigation. Waste-related activities, such as landfills, are a major CH₄ source, even in developed countries. Atmospheric concentration measurements using remote sensing offer a powerful way to quantify these emissions. We study waste facilities near Madrid, Spain, where satellite data indicated high CH₄ emissions. For the first time, we combine passive imaging (MAMAP2DL) and active lidar (CHARM-F) remote sensing aboard the German research aircraft HALO, supported by in situ instruments, to quantify CH₄ emissions. Using the CH₄ column data and ECMWF-ERA5 model wind information validated by airborne measurements, we estimate landfill emissions through a cross-sectional mass balance approach. Strong emission plumes are traced up to 20 km downwind on the 4^th August 2022, with the highest CH₄ column anomalies observed over active landfill areas in the vicinity of Madrid, Spain. Total emissions are estimated at ~13 th^-1. Single co-located plume crossings from both instruments agree well within 1.2 th^-1 (or 13 %). Flux errors range from ~25 to 40 %, mainly due to boundary layer and wind speed variability. This case study not only showcases the capabilities of applying a simple but fast cross-sectional mass balance approach, as well as its limitations due to challenging atmospheric boundary layer conditions, but also demonstrates the, to our knowledge, first successful use of both active and passive airborne remote sensing to quantify methane emissions from hot spots and independently verify their emissions.

To reduce and mitigate anthropogenic greenhouse gas surface fluxes from industrial sites, their sources must be, firstly, identified or localized and, secondly, accurately quantified. For methane (CH4), the second most important anthropogenic greenhouse gas, the quantification of its diverse emitters is still a challenge. Due to their nature, these emitters can reach dimensions from point sources to hundreds of square kilometres for fossil fuel (gas, oil, coal) exploitation sites or up to several square kilometres in case of waste disposal sites. Although, CH4 emissions from, e.g., waste disposal sites can be computed from activity data combined with landfill models, a high potential for unintended and poorly quantified leakages remain due to, e.g., potential ruptures in the landfill cover. Consequently, the exact localization and quantification of those leakages is a necessary step towards reducing CH4 emissions from waste disposal sites.To have better knowledge and insights into anthropogenic and natural greenhouse gas emissions, a team of scientists has assembled a comprehensive suite of instruments aboard the German Research aircraft HALO (High Altitude and Long Range Research Aircraft) during the CoMet 2.0 Arctic mission conducted in Canada in August and September 2022. Although the campaign was primarily intended to observe and quantify CH4 and CO2 emissions and disentangle anthropogenic from natural sources at the high northern latitudes of Canada, a test flight over Spain revealed unexpectedly high and still persistent emissions from two landfills in Madrid - Valdemingomez and Pinto, previously also pointed out in an ESA story based on satellite observations. Both were investigated by means of passive and active remote sensing, as well as in situ airborne techniques.The measurements of the passive airborne remote sensing instrument MAMAP2D-Light, developed at the University of Bremen, delivers atmospheric concentration anomaly maps of CH4 and CO2. Here, its imaging capabilities are used to pin-point the origin of the CH4 emissions across the targeted landfills and to quantify their emissions. MAMAP2D-Light’s concentration maps are combined with highly accurate CH4 column concentration measurements from the integrated-path differential-absorption lidar CHARM-F (CO2 and CH4 Remote Monitoring-Flugzeug), developed by German Aerospace Center (DLR) in Oberpfaffenhofen. Additionally, airborne CH4 in situ mole fractions were measured by the Jena Instrument for Greenhouse Gases (JIG) and supplemented with wind data within the emission plume in order to complement the remote sensing observations.This contribution will present top-down emission estimates from measurements of all aforementioned instruments, operated quasi-simultaneously, i.e. within a time span of approximate 2 hours, over the targeted area in Madrid in August 2022.

The CoMet 2.0 Arctic airborne measurement campaign of 2022 targeted a variety of natural as well as anthropogenic sources of CH4, mostly in Canada, such as landfills, coal mines, power plants or fossil fuel exploitation sites. Many anthropogenic emission targets consist of a few strong emitters with small or negligible spatial extension. In these cases, emission plumes can readily be observed by passive imaging spectrometers, through the observed enhancement in column averaged CH4. However, over oil and gas fields such as the Lloydminster area at the Alberta/Saskatchewan border, with numerous individual wells extending over large areas, this is much more difficult since individual plumes are lower in magnitude and may even overlap. In such cases it may not be possible to resolve plumes from individual sources, but the total flux can still be estimated using a budget approach. Nevertheless, limitations arise from spatial and temporal variations in the wind field, regarding proper quantification of the source strengths.In this contribution we present our strategy for source attribution, combining measurements by the airborne CHARM-F greenhouse-gas lidar and the MAMAP2DL imaging spectrometer with emission inventories and inverse modeling. A similar approach has already been successfully applied to CHARM-F data recorded over the Upper Silesian Coal Basin during the CoMet 1.0 campaign. CHARM-F is an Integrated-Path Differential-Absorption (IPDA) lidar that provides vertical column concentrations of CO2 and CH4 up to the flight altitude along the flight track. The advantages of lidar are the insensitivity to illumination conditions and a low intrinsic bias. MAMAP2DL is a passive airborne push broom imaging spectrometer that measures spatially resolved changes in relative column concentrations of CH4 and CO2. During the CoMet 2.0 Arctic campaign in August and September 2022, CHARM-F and MAMAP2DL have been deployed onboard the German research aircraft HALO, alongside a suite of complementary instruments for in-situ measurements of CH4, CO2 and other trace gases. We introduce our methods for data treatment and inverse modelling and show first results from this approach.

Airborne and satellite based lidar remote sensing combines the advantages of high measurement accuracy, large-area coverage and low-ambient-light measurement capability. The Merlin airborne demonstrator CHARM-F is an Integrated-Path Differential-Absorption (IPDA) lidar providing vertical column concentrations of carbon dioxide and methane up to the flight altitude along the flight track. It operated onboard the German HALO (high-altitude long-range) research aircraft during the CoMet 2.0 Arctic campaign in August and September 2022 over natural and anthropogenic sources of CO2 and CH4 in Canada. Natural methane fluxes from wetlands generally produce weak atmospheric concentration enhancements of the measured atmospheric column (

Methane (CH₄), alongside carbon dioxide (CO₂), is a key driver of anthropogenic climate change. Reducing CH₄ is crucial for short-term climate mitigation. Waste-related activities, such as landfills, are a major CH₄ source, even in developed countries. Atmospheric concentration measurements using remote sensing offer a powerful way to quantify these emissions. We study waste facilities near Madrid, Spain, where satellite data indicated high CH₄ emissions. For the first time, we combine passive imaging (MAMAP2DL) and active lidar (CHARM-F) remote sensing aboard the German research aircraft HALO, supported by in situ instruments, to quantify CH₄ emissions. Using the CH₄ column data and ECMWF-ERA5 model wind information validated by airborne measurements, we estimate landfill emissions through a cross-sectional mass balance approach. Strong emission plumes are traced up to 20 km downwind on the 4^th August 2022, with the highest CH₄ column anomalies observed over active landfill areas in the vicinity of Madrid, Spain. Total emissions are estimated at ~13 th^-1. Single co-located plume crossings from both instruments agree well within 1.2 th^-1 (or 13 %). Flux errors range from ~25 to 40 %, mainly due to boundary layer and wind speed variability. This case study not only showcases the capabilities of applying a simple but fast cross-sectional mass balance approach, as well as its limitations due to challenging atmospheric boundary layer conditions, but also demonstrates the, to our knowledge, first successful use of both active and passive airborne remote sensing to quantify methane emissions from hot spots and independently verify their emissions.

Nitrous oxide (N₂O) is the third most important greenhouse gas modified by human activities after carbon dioxide and methane. This study examines the feasibility of airborne differential absorption lidar to measure N₂O concentration enhancements over agricultural, fossil fuel combustion, industrial, and biomass burning sources. The mid-infrared spectral region, where suitably strong N₂O absorption lines exist, challenges passive remote sensing by means of spectroscopy due to both low solar radiation and thermal emission. Lidar remote sensing is principally possible thanks to the laser as an independent radiation source but has not yet been realized due to technological challenges. Mid-infrared N₂O absorption bands suitable for remote sensing are investigated. Simulations show that a spectral trough position between two strong N₂O lines in the 4.5 µm band is the favored option. A second option exists in the 3.9 µm band at the cost of higher laser frequency stability constraints and less measurement sensitivity. Both options fulfill the N₂O measurement requirements for agricultural areal or point-source emission quantification (0.5 % measurement precision, 500 m spatial resolution) with technically realizable and affordable transmitter (100 mW average laser power) and receiver (20 cm telescope) characteristics for integrated-path differential absorption lidar that measures the column concentration beneath the aircraft. The development of an airborne N₂O lidar is feasible yet would benefit from progress in infrared laser transmitter and low-noise-detection technology. It will also serve as a precursor to space versions, which are still out of reach due to the lack of space technology.