Search

We review the capability of current and scheduled satellite observations of atmospheric methane in the shortwave infrared (SWIR) to quantify methane emissions from the global scale down to point sources. We cover retrieval methods, precision and accuracy requirements, inverse and mass balance methods for inferring emissions, source detection thresholds, and observing system completeness. We classify satellite instruments as area flux mappers and point source imagers, with complementary attributes. Area flux mappers are high-precision ( %) instruments with 0.1–10 km pixel size designed to quantify total methane emissions on regional to global scales. Point source imagers are fine-pixel ( m) instruments designed to quantify individual point sources by imaging of the plumes. Current area flux mappers include GOSAT (2009–present), which provides a high-quality record for interpretation of long-term methane trends, and TROPOMI (2018–present), which provides global continuous daily mapping to quantify emissions on regional scales. These instruments already provide a powerful resource to quantify national methane emissions in support of the Paris Agreement. Current point source imagers include the GHGSat constellation and several hyperspectral and multispectral land imaging sensors (PRISMA, Sentinel-2, Landsat-8/9, WorldView-3), with detection thresholds in the 100–10 000 kg h−1 range that enable monitoring of large point sources. Future area flux mappers, including MethaneSAT, GOSAT-GW, Sentinel-5, GeoCarb, and CO2M, will increase the capability to quantify emissions at high resolution, and the MERLIN lidar will improve observation of the Arctic. The averaging times required by area flux mappers to quantify regional emissions depend on pixel size, retrieval precision, observation density, fraction of successful retrievals, and return times in a way that varies with the spatial resolution desired. A similar interplay applies to point source imagers between detection threshold, spatial coverage, and return time, defining an observing system completeness. Expanding constellations of point source imagers including GHGSat and Carbon Mapper over the coming years will greatly improve observing system completeness for point sources through dense spatial coverage and frequent return times.

Methane is a potent yet underestimated contributor to global greenhouse gas emissions. We examined the characteristics of 255 sources of methane super-emitters identified by NASA’s Airborne Visible/InfraRed Imaging Spectrometer-Next Generation in 109 California oil fields. Super-emitter events were primarily associated with oil & gas wells, gas gathering pipelines, and storage tanks (73% of sources). Sources with persistence of 50% comprised 77% and 1% of sources and contributed to 59% and 4% of the total measured emissions, respectively. We estimate total onsite methane emissions from 24 oil fields as 2.3 to 3.4 times the estimated rate by the current official lifecycle assessment model for California’s Low Carbon Fuel Standard used for determining carbon intensity of crude oil production. These findings suggest that without considering direct observations of oil field methane super emitters, greenhouse gas emissions policy for the oil and gas sector is likely to underestimate emissions.

Anthropogenic carbon dioxide (CO₂) emissions dominate uncertainties in the global carbon budget. Global inventories, such as the National Greenhouse Gas Inventories, have latencies of 12–24 months and may not keep pace with rapidly changing infrastructure, particularly in the developing world. Our work reveals that airborne and satellite imaging spectrometers provide 3–30 m spatial resolution and accurate quantification of CO₂ emissions at the facility scale. Examples from 17 coal and gas fired power plants across the United States demonstrate robust correlation and 21% agreement on average between our remotely sensed estimates and simultaneous in situ measured emissions. We highlight four examples of coal-fired power plants in India, Poland, and South Korea, where we quantify significant carbon dioxide emissions from power plants where limited public emissions data exist. Leveraging previous work on methane (CH₄) plume detection, we present a strategy to exploit joint CO₂ and CH₄ plume imaging to quantify carbon emissions across widely distributed industrial infrastructure, including facilities that co-emit CO₂ and CH₄. We show an example of a coal operation, where we attribute 25% of greenhouse gas emissions to coal extraction (CH₄) and the remaining 75% to energy generation (CO₂). Satellite spectrometers could track high emitting coal-fired power plants that collectively contribute to 60% or more of global coal CO₂ emissions. Multiple revisits and coordinated targeting of these high emitting facilities by multiple spaceborne instruments will be key to reducing uncertainties in global anthropogenic CO₂ emissions and supporting emissions mitigation strategies.

Monitoring of anthropogenic carbon dioxide (CO2) emission sources with air- and space-borne remote sensing instruments relies on high-spatial resolution measurements. Such observations can be achieved at the expense of decreasing the spectral resolution of the instrument, which in turn complicates CO2 retrieval techniques due to the reduced information content of the spectra.In preparation for the CO2IMAGE mission (Δλ ~ 1.3 nm) – a compact satellite proposal currently in phase A at the German Aerospace Center (DLR) – we present here a dedicated study of CO2 monitoring capabilities with the airborne AVIRIS-NG sensor (Δλ ~ 5 nm). We conduct CO2 retrievals of several clear-sky AVIRIS-NG point source observations with the RemoTeC algorithm, based on the short-wave infrared absorption bands of CO2. Favorable state vector and spectral retrieval window configurations are identified that reduce correlations between the carbon dioxide and water vapor column concentrations and surface reflection properties. We also discuss the use of a posteriori correction methods to minimize biases in the retrieved CO2 fields and, finally, we carry out source rate estimates for these case studies.

The Permian Basin is known for its extensive oil and gas production, which has increased rapidly in recent years becoming the largest producing basin in the United States. It is also responsible for almost half of the methane emissions from all oil and gas producing regions in the country. Given the urgent need to reduce greenhouse gas emissions, it is crucial to identify and characterize the point sources of emissions. To this end, we have combined three new high-resolution hyperspectral sensors data onboard the GF-5, ZY1 and PRIMA satellites to create the first regional study to identify methane sources and measure the emitted quantities from each source. With data collected over several days in 2019 and 2020, we have identified a total of 37 point source emissions with flux rates >500kg/h, that is, a high concentration of extreme emission point sources that account for nearly 40% of the Permian annual emissions. Also, we have found that new infrastructure (post-2018) is responsible for almost 60% of the detected emissions, in many cases (21% of the cases) due to inefficient use of flaring of the gas that they cannot store. With this study, we demonstrate that hyperspectral satellite data are a powerful tool for the detection and quantification of strong methane point emissions.

Estimating methane (CH4) emission rates using quantitative CH4 retrievals from the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) requires the use of wind speeds. Model wind speeds have limited temporal and spatial resolution, meteorological station wind data are of variable quality and are often not available near observed plumes, and the use of ultrasonic anemometers co-located with methane sources is impractical for AVIRIS-NG flight campaigns with daily coverage of thousands of square kilometers. Given these limitations, this study focused on the use of the Twin Otter Doppler Wind Lidar (TODWL) to measure near surface winds and provide coincident measurements to CH4 plumes observed with AVIRIS-NG. In a controlled release experiment, TODWL observed wind speed and direction agreed well with ultrasonic anemometer measurements and CH4 emission rates derived from TODWL observations were more accurate than those using the ultrasonic anemometer or model winds during periods of stable winds. During periods exhibiting rapid shifts in wind speed and direction, estimating emission rates proved more challenging irrespective of the use of model, ultrasonic anemometer, or TODWL wind data. Overall, TODWL was able to provide reasonably accurate wind measurements and emission rate estimates despite the variable wind conditions and excessive flight level turbulence which impacted near surface measurement density. TODWL observed winds were also used to constrain CH4 emissions at a refinery, landfill, wastewater facility, and dairy digester. At these sites, TODWL wind measurements agreed well with wind observations from nearby meteorological stations, and when combined with quantitative CH4 plume imagery, yielded emission rate estimates that were similar to those obtained using model winds. This study demonstrates the utility of combining TODWL and AVIRIS-NG CH4 measurements and emphasizes the potential benefits of integrating both instruments on a single aircraft for future deployments.

[EN] Industrial emissions play a major role in the global methane budget. The Permian basin is thought to be responsible for almost half of the methane emissions from all U.S. oil- and gas-producing regions, but little is known about individual contributors, a prerequisite for mitigation. We use a new class of satellite measurements acquired during several days in 2019 and 2020 to perform the first regional-scale and high-resolution survey of methane sources in the Permian. We find an unexpectedly large number of extreme point sources (37 plumes with emission rates >500 kg hour(-1)), which account for a range between 31 and 53% of the estimated emissions in the sampled area. Our analysis reveals that new facilities are major emitters in the area, often due to inefficient flaring operations (20% of detections). These results put current practices into question and are relevant to guide emission reduction efforts., I.I.-L., L.G., J.G., and E.S.-G. are partly funded by an UPV-GFZ Potsdam EnMAP collaboration contract. Yuzhong Zhang is funded by the National Natural Science Foundation of China (project 42007198) and foundation of Westlake University.

The last five years have seen dramatic growth in the use of Visible Shortwave Infrared (VSWIR) and Thermal Infrared (TIR) imaging spectrometers to detect and characterize greenhouse methane sources. Targets include: dairy and animal husbandry emissions; landfills; fossil fuel extraction, storage, and transport infrastructure; geologic sources; natural emissions associated with sensitive arctic ecosystems; and more. These campaigns have resulted in significant new discoveries and advances in our understanding of the North American CH4 budget. Recent algorithm improvements have been critical for these campaigns, enabling robust statistical CH 4 measurement, fully-automated image-space source identification, and quantification of flux. Here we survey recent campaigns by NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG) and NASA's Hyperspectral Thermal Emission Spectrometer (HyTES). We describe their algorithmic advances and major findings.

This study derives methane emission rates from 92 airborne observations collected over 23 facilities including 5 refineries, 10 landfills, 4 wastewater treatment plants (POTWs), 2 composting operations, and 2 dairies in the San Francisco Bay Area. Emission rates are measured using an airborne mass-balance technique from a low-flying aircraft. Annual measurement-based sectorwide methane emissions are 19,000 ± 2300 Mg for refineries, 136,700 ± 25,900 Mg for landfills, 11,900 ± 1,500 Mg for POTWs, and 11,100 ± 3,400 Mg for composting. The average of measured emissions for each refinery ranges from 4 to 23 times larger than the corresponding emissions reported to regulatory agencies, while measurement-derived landfill and POTW estimates are approximately twice the current inventory estimates. Significant methane emissions at composting facilities indicate that a California mandate to divert organics from landfills to composting may not be an effective measure for mitigating methane emissions unless best management practices are instituted at composting facilities. Complementary evidence from airborne remote sensing imagery indicates atmospheric venting from refinery hydrogen plants, landfill working surfaces, composting stockpiles, etc., to be among the specific source types responsible for the observed discrepancies. This work highlights the value of multiple measurement approaches to accurately estimate facility-scale methane emissions and perform source attribution at subfacility scales to guide and verify effective mitigation policy and action.

Accurate and timely detection, quantification, and attribution of methane emissions from Underground Gas Storage (UGS) facilities is essential for improving confidence in greenhouse gas inventories, enabling emission mitigation by facility operators, and supporting efforts to assess facility integrity and safety. We conducted multiple airborne surveys of the 12 active UGS facilities in California between January 2016 and November 2017 using advanced remote sensing and in situ observations of near-surface atmospheric methane (CH4). These measurements where combined with wind data to derive spatially and temporally resolved methane emission estimates for California UGS facilities and key components with spatial resolutions as small as 1–3 m and revisit intervals ranging from minutes to months. The study spanned normal operations, malfunctions, and maintenance activity from multiple facilities including the active phase of the Aliso Canyon blowout incident in 2016 and subsequent return to injection operations in summer 2017. We estimate that the net annual methane emissions from the UGS sector in California averaged between 11.0 ± 3.8 GgCH4 yr−1 (remote sensing) and 12.3 ± 3.8 GgCH4 yr−1 (in situ). Net annual methane emissions for the 7 facilities that reported emissions in 2016 were estimated between 9.0 ± 3.2 GgCH4 yr−1 (remote sensing) and 9.5 ± 3.2 GgCH4 yr−1 (in situ), in both cases around 5 times higher than reported. The majority of methane emissions from UGS facilities in this study are likely dominated by anomalous activity: higher than expected compressor loss and leaking bypass isolation valves. Significant variability was observed at different time-scales: daily compressor duty-cycles and infrequent but large emissions from compressor station blow-downs. This observed variability made comparison of remote sensing and in situ observations challenging given measurements were derived largely at different times, however, improved agreement occurred when comparing simultaneous measurements. Temporal variability in emissions remains one of the most challenging aspects of UGS emissions quantification, underscoring the need for more systematic and persistent methane monitoring.

The Methane Source Finder is a web-based data portal developed under NASA’s CMS and ACCESS programs for exploring methane data in the state of California. This open access interactive map allows users to discover, analyze, and download data across a range of spatial scales derived from remote-sensing, surface monitoring, and bottom-up infrastructure information. This includes methane plume images and associated emission estimates derived from the 2016-2018 California Methane Survey using the airborne imaging spectrometer AVIRIS-NG. The fine spatial resolution (typically 3 m) AVIRIS-NG products when combined with the Vista infrastructure database of over 270,000 components statewide permits direct attribution of emissions to individual point source locations. These point source products have benefited from evaluation and feedback from state and local agencies and private sector companies and in some cases were used to directly guide leak detection and repair efforts. Additional data layers at local and regional scales provide context for point source emissions. These include methane flux inversions for the Los Angeles basin derived from surface observations and tracer transport modeling (3 km, 4 day resolution) as well as the CMS US methane gridded inventory (10 km, monthly resolution) over the state of California.

The 2016-2018 California Methane Survey used the airborne imaging spectrometer AVIRIS-NG to survey approximately 59,000 km2 and 272,000 individual facilities and infrastructure components. Over 500 strong methane point sources spanning the waste management, agriculture, and energy sectors were detected, geolocated, and quantified. In order to facilitate communication of results with scientists, stakeholder agencies in California, private sector companies, and the public, we developed the Methane Source Finder web-based data portal. This state of the art Earth science data visualization tool allows users to discover, analyze, and download data across a range of spatial scales derived from remote-sensing, surface monitoring, and bottom-up infrastructure information. In this presentation, we will highlight our overall science findings from the California Methane Survey and provide a number of examples where observed methane plumes were used to directly guide leak detection and repair efforts. Future plans include expanding the data portal beyond California and incorporating regional scale flux inversions derived from satellite observations. Methane Source Finder supports methane research (e.g., multi-scale synthesis), enables facility-scale mitigation, and improves public awareness of greenhouse gas emissions.

Methane emissions monitoring is rapidly expanding with increasing coverage of surface, airborne, and satellite instruments. However, no single methane instrument or observing strategy can both close emission budgets and pinpoint point sources on regional to global scales. Instead, we present a multi-tiered data analytics system that synthesizes information across various instruments into a single analytic framework. We highlight an example in Los Angeles, where we combine surface measurements from the Los Angeles megacities project, mountaintop measurements from the CLARS-FTS instrument, airborne AVIRIS-NG point source emission estimates, and TROPOMI total column retrievals into a single analytic framework. Surface, mountaintop, and satellite measurements are assimilated into a methane flux inverse model to constrain basin-wide emissions and pinpoint sub-basin methane hotspots. We show an example of a large urban landfill, whose anomalous emissions were detected by the inverse system, and validated using AVIRIS-NG methane plume maps. This general approach of quantifying both methane area and point source emissions is an avenue not just for closing regional to global scale budgets, but also for understanding which emission sources dominate the budget (i.e., so called methane super-emitters). We finally show how this multi-tiered analytic framework can be improved with future satellite missions, and present examples of unexpectedly large methane emissions that were detected by a new generation of satellite imaging spectrometers.

The strong radiative forcing by atmospheric methane has stimulated interest in identifying natural and anthropogenic sources of this potent greenhouse gas. Point sources are important targets for quantification, and anthropogenic targets have potential for emissions reduction. Methane point source plume detection and concentration retrieval have been previously demonstrated using data from the Airborne Visible InfraRed Imaging Spectrometer Next Generation (AVIRIS-NG). Current quantitative methods have tradeoffs between computational requirements and retrieval accuracy, creating obstacles for processing real-time data or large datasets from flight campaigns. We present a new computationally efficient algorithm that applies sparsity and an albedo correction to matched filter retrieval of trace gas concentration-pathlength. The new algorithm was tested using AVIRIS-NG data acquired over several point source plumes in Ahmedabad, India. The algorithm was validated using simulated AVIRIS-NG data including synthetic plumes of known methane concentration. Sparsity and albedo correction together reduced the root mean squared error of retrieved methane concentration-pathlength enhancement by 60.7% compared with a previous robust matched filter method. Background noise was reduced by a factor of 2.64. The new algorithm was able to process the entire 300 flightline 2016 AVIRIS-NG India campaign in just over 8 hours on a desktop computer with GPU acceleration., Comment: 13 pages, 11 figures

Atmospheric methane has been increasing since the beginning of the industrial era due to anthropogenic emissions. Methane has many sources, both natural and anthropogenic, and there continues to be considerable uncertainty regarding the contribution of each source to the total methane budget. Thus, remote sensing techniques for monitoring and measuring methane emissions are of increasing interest. Recently, the Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) has proven to be a valuable instrument for quantitative mapping of methane plumes. Despite this success, uncertainties remain regarding the sensitivity of the retrieval algorithms, including the influence of albedo and the impact of surfaces that may cause spurious signals. To explore these sensitivities, we applied the Iterative Maximum a Posterior Differential Optical Absorption Spectroscopy (IMAP-DOAS) methane retrieval algorithm to synthetic reflected radiances with variable methane concentrations, albedo, surface cover, and aerosols. This allowed for characterizing retrieval performance, including potential sensitivity to variable surfaces, low albedo surfaces, and surfaces known to cause spurious signals. We found that dark surfaces (below 0.10 μWcm^(−2)nm^(−1)sr^(−1) at 2139 nm), such as water and green vegetation, and materials with absorption features in the 2200–2400 nm range caused higher errors in retrieval results. We also found that aerosols have little influence on retrievals in the SWIR. Results from the synthetic scene are consistent with those observed in IMAP-DOAS retrievals for real AVIRIS-NG scenes containing methane plumes from a waste dairy lagoon and coal mine ventilation shafts. Understanding the effect of surface properties on methane retrievals is important given the increased use of AVIRIS-NG to map gas plumes from a diversity of sources over variable landscapes.

Matched filter (MF) techniques have been widely used for retrieval of greenhouse gas enhancements (enh.) from imaging spectroscopy datasets. While multiple algorithmic techniques and refinements have been proposed, the greenhouse gas target spectrum used for concentration enh. estimation has remained largely unaltered since the introduction of quantitative MF retrievals. The magnitude of retrieved methane and carbon dioxide enh., and thereby integrated mass enh. (IME) and estimated flux of point-source emitters, is heavily dependent on this target spectrum. Current standard use of molecular absorption coefficients to create unit enh. target spectra does not account for absorption by background concentrations of greenhouse gases, solar and sensor geometry, or atmospheric water vapor absorption. We introduce geometric and atmospheric parameters into the generation of scene-specific (SS) unit enh. spectra to provide target spectra that are compatible with all greenhouse gas retrieval MF techniques. For methane plumes, IME resulting from use of standard, generic enh. spectra varied from -22 to +28.7% compared to SS enh. spectra. Due to differences in spectral shape between the generic and SS enh. spectra, differences in methane plume IME were linked to surface spectral characteristics in addition to geometric and atmospheric parameters. IME differences for carbon dioxide plumes, with generic enh. spectra producing integrated mass enh. -76.1 to -48.1% compared to SS enh. spectra. Fluxes calculated from these integrated enh. would vary by the same %s, assuming equivalent wind conditions. Methane and carbon dioxide IME were most sensitive to changes in solar zenith angle and ground elevation. SS target spectra can improve confidence in greenhouse gas retrievals and flux estimates across collections of scenes with diverse geometric and atmospheric conditions., Comment: 13 pages, 5 figures, 3 tables

We examine the potential for global detection of methane plumes from individual point sources with the new generation of spaceborne imaging spectrometers (EnMAP, PRISMA, EMIT, SBG) scheduled for launch in 2019–2025. These instruments are designed to map the Earth's surface with a sampling distance as fine as 30 × 30 m2 but they have spectral resolution of 7–10 nm in the 2200–2400 nm band that should also allow useful detection of atmospheric methane. We simulate scenes viewed by EnMAP (10 nm spectral resolution, 180 signal-to-noise ratio) using the EnMAP End-to-End Simulation Tool with superimposed methane plumes generated by large-eddy simulations. We retrieve atmospheric methane and surface reflectivity for these scenes using the IMAP-DOAS optimal estimation algorithm. We find an EnMAP precision of 4–13 % for atmospheric methane depending on surface type, allowing effective single-pass detection of 100+ kg h−1 methane point sources depending on surface brightness, surface homogeneity, and wind speed. Successful retrievals over very heterogeneous surfaces such as an urban mosaic require finer spectral resolution. We simulated the EnMAP capability with actual plume observations over oil/gas fields in California from the airborne AVIRIS-NG sensor (3 × 3 m2 pixel resolution, 5 nm spectral resolution, SNR 200–400). We spectrally and spatially downsampled AVIRIS-NG images to match EnMAP instrument specifications and found that we could successfully detect point sources of ~ 100 kg h−1 over bright surfaces. Estimated emission rates inferred with a generic Integrated Mass Enhancement (IME) method agreed within a factor of 2 between EnMAP and AVIRIS-NG. Better agreement may be achieved with a more customized IME method. Our results suggest that imaging spectrometers in space could play a transformative role in the future for quantifying methane emissions from point sources on a global scale.

Methane is a powerful greenhouse gas and is targeted for emissions mitigation by the US state of California and other jurisdictions worldwide

Methane (CH4) impacts climate as the second strongest anthropogenic greenhouse gas and air quality by influencing tropospheric ozone levels. Space-based observations have identified the Four Corners region in the Southwest United States as an area of large CH4 enhancements. We conducted an airborne campaign in Four Corners during April 2015 with the next-generation Airborne Visible/Infrared Imaging Spectrometer (near-infrared) and Hyperspectral Thermal Emission Spectrometer (thermal infrared) imaging spectrometers to better understand the source of methane by measuring methane plumes at 1- to 3-m spatial resolution. Our analysis detected more than 250 individual methane plumes from fossil fuel harvesting, processing, and distributing infrastructures, spanning an emission range from the detection limit [Formula: see text] 2 kg/h to 5 kg/h through [Formula: see text] 5,000 kg/h. Observed sources include gas processing facilities, storage tanks, pipeline leaks, and well pads, as well as a coal mine venting shaft. Overall, plume enhancements and inferred fluxes follow a lognormal distribution, with the top 10% emitters contributing 49 to 66% to the inferred total point source flux of 0.23 Tg/y to 0.39 Tg/y. With the observed confirmation of a lognormal emission distribution, this airborne observing strategy and its ability to locate previously unknown point sources in real time provides an efficient and effective method to identify and mitigate major emissions contributors over a wide geographic area. With improved instrumentation, this capability scales to spaceborne applications [Thompson DR, et al. (2016) Geophys Res Lett 43(12):6571-6578]. Further illustration of this potential is demonstrated with two detected, confirmed, and repaired pipeline leaks during the campaign.

Emissions estimates of anthropogenic methane (CH 4 ) sources are highly uncertain and many sources related to energy production are localized yet difficult to quantify. Airborne imaging spectrometers like the next generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) are well suited for locating CH 4 point sources due to their ability to map concentrations over large regions with the high spatial resolution necessary to resolve localized emissions. AVIRIS-NG was deployed during a field campaign to measure controlled CH 4 releases at the Rocky Mountain Oilfield Testing Center (RMOTC) in Wyoming, U.S. for multiple flux rates and flight altitudes. Two algorithms were applied to AVIRIS-NG scenes, a matched filter detection algorithm and a hybrid retrieval approach using the Iterative Maximum a Posteriori Differential Optical Absorption Spectroscopy (IMAP-DOAS) algorithm and Singular Value Decomposition. Plumes for releases as low as 14.16 m 3 /h (0.09 kt/year) were consistently observed by AVIRIS-NG at multiple flight altitudes and images of plumes were in agreement with wind directions measured at ground stations. In some cases plumes as low as 3.40 m 3 /h (0.02 kt/year) were detected, indicating that AVIRIS-NG has the capability of detecting a wide range of fugitive CH 4 source categories for natural gas fields. This controlled release experiment is the first of its kind using AVIRIS-NG and demonstrates the utility of imaging spectrometers for direct attribution of emissions to individual point source locations. This is particularly useful given the large uncertainties associated with anthropogenic CH 4 emissions, including those from industry, gas transmission lines, and the oil and gas sectors.

This study evaluates a new generation of satellite imaging spectrometers to measure point source methane emissions from anthropogenic sources. We used the Airborne Visible and Infrared Imaging Spectrometer Next Generation(AVIRIS-NG) images with known methane plumes to create two simulated satellite products. One simulation had a 30 m spatial resolution with ~200 Signal-to-Noise Ratio (SNR) in the Shortwave Infrared (SWIR) and the other had a 60 m spatial resolution with ~400 SNR in the SWIR; both products had a 7.5 nm spectral spacing. We applied a linear matched filter with a sparsity prior and an albedo correction to detect and quantify the methane emission in the original AVIRIS-NG images and in both satellite simulations. We also calculated an emission flux for all images. We found that all methane plumes were detectable in all satellite simulations. The flux calculations for the simulated satellite images correlated well with the calculated flux for the original AVIRIS-NG images. We also found that coarsening spatial resolution had the largest impact on the sensitivity of the results. These results suggest that methane detection and quantification of point sources will be possible with the next generation of satellite imaging spectrometers.

Localized anthropogenic sources of atmospheric CH4 are highly uncertain and temporally variable. Airborne remote measurement is an effective method to detect and quantify these emissions. In a campaign context, the science yield can be dramatically increased by real-time retrievals that allow operators to coordinate multiple measurements of the most active areas. This can improve science outcomes for both single- and multiple-platform missions. We describe a case study of the NASA/ESA CO2 and MEthane eXperiment (COMEX) campaign in California during June and August/September 2014. COMEX was a multi-platform campaign to measure CH4 plumes released from anthropogenic sources including oil and gas infrastructure. We discuss principles for real-time spectral signature detection and measurement, and report performance on the NASA Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG). AVIRIS-NG successfully detected CH4 plumes in real-time at Gb s−1 data rates, characterizing fugitive releases in concert with other in situ and remote instruments. The teams used these real-time CH4 detections to coordinate measurements across multiple platforms, including airborne in situ, airborne non-imaging remote sensing, and ground-based in situ instruments. To our knowledge this is the first reported use of real-time trace-gas signature detection in an airborne science campaign, and presages many future applications. Post-analysis demonstrates matched filter methods providing noise-equivalent (1σ) detection sensitivity for 1.0 % CH4 column enhancements equal to 141 ppm m.

Fugitive emissions from waste disposal sites are important anthropogenic sources of the greenhouse gas methane (CH4). As a result of the growing world population and the recognition of the need to control greenhouse gas emissions, this anthropogenic source of CH4 has received much recent attention. However, the accurate assessment of the CH4 emissions from landfills by modeling and existing measurement techniques is challenging. This is because of inaccurate knowledge of the model parameters and the extent of and limited accessibility to landfill sites. This results in a large uncertainty in our knowledge of the emissions of CH4 from landfills and waste management. In this study, we present results derived from data collected during the research campaign COMEX (CO2 and Methane EXperiement) in late summer 2014 in the Los Angeles (LA) Basin. The objective of COMEX, which comprised aircraft observations of methane by the remote sensing Methane Airborne MAPper (MAMAP) instrument and a Picarro greenhouse gas in-situ analyser, was the quantitative investigation of CH4 emissions. Enhanced CH4 concentrations or "CH4 plumes" were detected downwind of landfills by remote sensing aircraft surveys. Subsequent to each remote sensing survey, the detected plume was sampled within the atmospheric boundary layer by in-situ measurements of atmospheric parameters such as wind information and dry gas mixing ratios of CH4 and carbon dioxide (CO2) from the same aircraft. This was undertaken to facilitate the independent estimation of the surface fluxes for the validation of the remote sensing estimates. During the COMEX campaign, four landfills in the LA Basin were surveyed. One landfill has repeatedly shown a clear emission plume. This landfill, the Olinda Alpha Landfill, was observed on four days during the last week of August and first days of September 2014. Emissions were estimated for all days using a mass balance approach. The derived emissions are between 13.0 and 18.2 kt CH4/yr with related uncertainties in the range of 17 % to 46 %. The comparison of the remote sensing and in-situ based CH4 emission rate estimates reveals good agreement within the error bars with an average absolute difference of around 2.3 kt CH4/yr. The US Environmental Protection Agency (EPA) reported inventory value is 11.5 kt CH4/yr in 2014, on average 3.0 kt CH4/yr (±1.5 kt CH4/yr) lower than our estimates acquired in late Summer 2014. This difference may in part be explained by a possible leak located on the south-western slope of the landfill, which we identified in the observations of the Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) instrument, flown contemporaneously aboard a second aircraft on one day.

The 2017 Arctic Boreal Vulnerability Experiment Airborne Campaign (AAC) was one of the largest, most complex airborne science experiments conducted by NASA’s Earth Science Division. Between April and November, the AAC involved ten aircraft in more than 200 science flights that surveyed over 4 million km2 in Alaska and northwestern Canada. Many flights were coordinated with same-day ground-based measurements to link process-level studies with geospatial data products derived from satellite sensors. The AAC collected data spanning the critical intermediate space and time scales that are essential for a comprehensive understanding of scaling across the ABoVE Study Domain and ultimately extrapolation to the pan-Arctic using satellite data and ecosystem models. The AAC provided unique opportunities to validate satellite and airborne remote sensing data and data products for northern high latitude ecosystems. The science strategy coupled domain-wide sampling with L-band and P-band synthetic aperture radar (SAR), imaging spectroscopy, full waveform LIDAR, atmospheric trace gases (including carbon dioxide and methane), as well as focused studies using Ka-band SAR and solar induced chlorophyll fluorescence. Targets of interest included field sites operated by the ABoVE Science Team as well as the intensive and/or long-term sites operated by US and Canadian partners.

Carbon dioxide is emitted from the combustion of fossil fuels and is an important contributor to anthropogenic climate change. Multiple current and planned satellite missions are designed to quantify atmospheric carbon dioxide concentrations on a global scale, but most of these sensors do not have the spatial resolution necessary to resolve point sources such as fossil fuel power plants. Airborne imaging spectrometer data, such as those from the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS), can have multiple, contiguous bands covering shortwave infrared (SWIR) absorption features produced by carbon dioxide. Therefore, high spatial resolution data from AVIRIS-like sensors may offer a means for detecting plumes and retrieving carbon dioxide concentrations for point source emissions. The objectives of this study include modeling minimum carbon dioxide anomalies detectable in AVIRIS data under different conditions and applying a Cluster-Tuned Matched Filter for detection of carbon dioxide plumes in simulated data and in AVIRIS images acquired over power plants. Radiative transfer simulations were used to model the residual radiance produced by increased absorption by carbon dioxide as concentration was elevated above background levels within a 0–500 m layer. Carbon dioxide anomalies, surface reflectance, water vapor concentration, solar zenith angle, sensor height, and aerosol scattering were varied in simulation sets and the resulting residual radiance spectra were compared against noise equivalent delta radiance (NEdL) for the “classic” and “next generation” AVIRIS instruments. Sensitivity to carbon dioxide anomalies improved with increased surface reflectance and declined with increased water vapor concentration, solar zenith angle, sensor height, and aerosol scattering. Zero to 500 m concentration anomalies as low as 100 parts per milion by volume (ppm) for AVIRIS C and 25 ppm for AVIRIS NG produced residual radiance values that exceeded SWIR NEdL. Carbon dioxide concentrations modeled for a generic power plant emissions scenario using a plume dispersion model were combined with randomly-generated reflectance spectra to create simulated images with varying surface reflectance and NEdL. For these simulated images, true positive and false positive detection rates improved as background reflectance increased and as NEdL decreased. Apparent plumes were detected in all four AVIRIS C images acquired over power plants, although the characteristics of the plumes varied according to solar-plume-sensor geometry. Improvements in modeling may allow retrieval of plume concentration, providing a valuable means for quantifying point source emissions and a basis for comparison with column concentrations retrieved from in situ measurements and coarse resolution satellite data.

In this study, a Cluster-Tuned Matched Filter (CTMF) technique was applied to data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over marine and terrestrial locations known to emit methane (CH4). At the Coal Oil Point marine seep field, prominent CH4 anomalies were consistent with advection from known areas of active seepage. For a region with natural CH4 and oil seepage located west of downtown Los Angeles, significant CH4 anomalies were identified for known sources at the La Brea Tar Pits and in close proximity to probable sources, including an office complex documented as venting CH4 continuously and hydrocarbon storage tanks on the Inglewood Oil Field. However, interpretation of anomalies was complicated by noise and false positives for surfaces with strong absorptions at the same wavelengths as CH4 absorption features. Segmentation of results identified 16 distinct locations of contiguous pixels with high CTMF scores and segments were classified into probable CH4 anomalies and confusers based on the spectral properties of the underlying surface over the full spectral range measured by AVIRIS. This technique is particularly well suited for application over large areas to detect CH4 emissions from concentrated point sources and should permit detection of additional trace gasses with distinct absorption features, including carbon dioxide (CO2) and nitrous oxide (N2O). Thus, imaging spectrometry by an AVIRIS-like sensor has the potential to improve high resolution greenhouse gas mapping, better constraining local sources.

The Airborne Methane Plume Spectrometer (AMPS) is a mature instrument concept that is ready for development at the Jet Propulsion Laboratory (JPL). At its core is a novel high-resolution imaging spectrometer that records solar reflected light between 1.99 and 2.42 pm at 1 nm resolution, including strong methane (CH4) bands in the short-wave infrared. The push-broom spectrometer will leverage recent advancements in grating design and large-format 2D focal plane arrays to enable — for the first time — the high spectral resolution necessary for trace gas retrievals combined with high-performance imaging capabilities developed for surface remote sensing. AMPS features a 36° field of view with 600 resolved spatial elements across track (1 mRad) and 431 pixels in the spectral dimension. All other aspects of the instrument, such as the telescope, cryo-cooler, image stabilizer, GPS, are identical to available airborne JPL spectrometers in operation. The AMPS design is based on the next generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG), which has been used for high resolution mapping of CH4 concentrations from a controlled release experiment [1] and over existing natural gas fields [2]. A real time CH4 plume detection capability originally developed for AVIRIS-NG and successfully demonstrated over oil fields [3] will also be implemented with AMPS. This will facilitate surveys over existing oil and gas fields to identify and attribute CH4 emissions to individual point source locations, permit adaptive surveys with repeat imaging of suspected sources, and allow real time communication to site operators or ground crews equipped with additional instruments to verify observed plumes. AMPS will enable quantitative imaging of CH4 plumes at unprecedented spatial resolution and precision. Using a slow moving platform such as a helicopter at 100 m flight altitude (60 m image swath) will permit imaging CH4 enhancements at 10 cm spatial resolution and an unprecedented accuracy of 0.05 g CH4/m2. This will allow robust detection of CH4 emissions as low as 0.17 m3/h (6 standard cubic feet per hour), an order of magnitude smaller than what current airborne systems can detect. Using fixed-wing aircraft, AMPS can also be flown faster and higher (1 to 8 km flight altitude), thereby providing larger image swaths (0.6 to 4.8 km swaths respectively) and effective large scale surveys. Mapping CH4 emissions to individual point source locations could allow site operators to identify and mitigate these emissions, which reflect both a potential safety hazard and lost revenue. For the regulatory and scientific communities, understanding the distribution (spatial, temporal) and size of these emissions is of interest given the large uncertainties associated with anthropogenic emissions, including industrial point source emissions and fugitive CH4 from oil and gas infrastructure.

The Aliso Canyon gas storage facility near Porter Ranch, California, produced a large accidental CH_4 release from October 2015 to February 2016. The Hyperion imaging spectrometer on board the EO-1 satellite successfully detected this event, achieving the first orbital attribution of CH_4 to a single anthropogenic superemitter. Hyperion measured shortwave infrared signatures of CH_4 near 2.3 μm at 0.01 μm spectral resolution and 30 m spatial resolution. It detected the plume on three overpasses, mapping its magnitude and morphology. These orbital observations were consistent with measurements by airborne instruments. We evaluate Hyperion instrument performance, draw implications for future orbital instruments, and extrapolate the potential for a global survey of CH_4 superemitters.

Airborne imaging spectroscopy has evolved dramatically since the 1980s as a robust remote sensing technique used to generate 2-dimensional maps of surface properties over large spatial areas. Traditional applications for passive airborne imaging spectroscopy include interrogation of surface composition, such as mapping of vegetation diversity and surface geological composition. Two recent applications are particularly relevant to the needs of both the oil and gas as well as government sectors: quantification of surficial hydrocarbon thickness in aquatic environments and mapping atmospheric greenhouse gas components. These techniques provide valuable capabilities for petroleum seepage in addition to detection and quantification of fugitive emissions. New empirical data that provides insight into the source strength of anthropogenic methane will be reviewed, with particular emphasis on the evolving constraints enabled by new methane remote sensing techniques. Contemporary studies attribute high-strength point sources as significantly contributing to the national methane inventory and underscore the need for high performance remote sensing technologies that provide quantitative leak detection. Imaging sensors that map spatial distributions of methane anomalies provide effective techniques to detect, localize, and quantify fugitive leaks. Airborne remote sensing instruments provide the unique combination of high spatial resolution (< 1 m) and large coverage required to directly attribute methane emissions to individual emission sources. This capability cannot currently be achieved using spaceborne sensors. In this study, results from recent NASA remote sensing field experiments focused on point-source leak detection, will be highlighted. This includes existing quantitative capabilities for oil and methane using state-of-the-art airborne remote sensing instruments. While these capabilities are of interest to NASA for assessment of environmental impact and global climate change, industry similarly seeks to detect and localize leaks of both oil and methane across operating fields. In some cases, higher sensitivities desired for upstream and downstream applications can only be provided by new airborne remote sensing instruments tailored specifically for a given application. There exists a unique opportunity for alignment of efforts between commercial and government sectors to advance the next generation of instruments to provide more sensitive leak detection capabilities, including those for quantitative source strength determination.