Comparative analysis of low-Earth orbit (TROPOMI) and geostationary (GeoCARB, GEO-CAPE) satellite instruments for constraining methane emissions on fine regional scales: application to the Southeast US

Sheng, Jianxiong; Jacob, Don; Maasakkers, Joannes D.; Zhang, Yuzhong; Sulprizio, Melissa P.

doi:10.5194/amt-2018-121

Cited by 6 publications

(11 citation statements)

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“…This is due to the temporal model error correlation between successive GeoCARB observations. Accounting for cloud cover would show more benefit from 4× day −1 observations, since a higher frequency of observations allows for a greater chance of sampling clear-sky conditions, although the benefit depends on the cloud persistence timescale (Sheng et al, 2018a).…”

Section: Performance Of Different Satellite and Surface Observing Sysmentioning

confidence: 99%

“…We find that TROPOMI and GeoCARB perform similarly when added to surface sites, and that their main benefit is to decrease the FAR. Accounting for clouds would show more benefit for GeoCARB because the finer pixels allow for more frequent clear-sky observations (Sheng et al, 2018a).…”

Section: Combining Satellite and Surface Observationsmentioning

confidence: 99%

“…Inverse analyses of SCIAMACHY and GOSAT data have focused on quantifying emissions at ∼ 100 km regional scales (Bergamaschi et al, 2013;Wecht et al, 2014a;Alexe et al, 2015;Turner et al, 2015). OSSEs have shown the potential for TROPOMI and GeoCARB to effectively constrain emissions at the 25-100 km scale without the multiyear averaging required by SCIAMACHY and GOSAT (Wecht et al, 2014b;Sheng et al, 2018a). Other OSSEs have examined the potential for satellites to quantify large point sources from plume observations (Buchwitz et al, 2013;Rayner et al, 2014;Varon et al, 2018).…”

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Detecting high-emitting methane sources in oil/gas fields using satellite observations

et al. 2018

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Abstract. Methane emissions from oil/gas fields originate from a large number of relatively small and densely clustered point sources. A small fraction of high-mode emitters can make a large contribution to the total methane emission. Here we conduct observation system simulation experiments (OSSEs) to examine the potential of recently launched or planned satellites to detect and locate these high-mode emitters through measurements of atmospheric methane columns. We simulate atmospheric methane over a generic oil/gas field (20–500 production sites of different size categories in a 50×50 km2 domain) for a 1-week period using the WRF-STILT meteorological model with 1.3×1.3 km2 horizontal resolution. The simulations consider many random realizations for the occurrence and distribution of high-mode emitters in the field by sampling bimodal probability density functions (PDFs) of emissions from individual sites. The atmospheric methane fields for each realization are observed virtually with different satellite and surface observing configurations. Column methane enhancements observed from satellites are small relative to instrument precision, even for high-mode emitters, so an inverse analysis is necessary. We compare L1 and L2 regularizations and show that L1 regularization effectively provides sparse solutions for a bimodally distributed variable and enables the retrieval of high-mode emitters. We find that the recently launched TROPOMI instrument (low Earth orbit, 7×7 km2 nadir pixels, daily return time) and the planned GeoCARB instrument (geostationary orbit, 2.7×3.0 km2 pixels, 2 times or 4 times per day return times) are successful (> 80 % detection rate, < 20 % false alarm rate) at locating high-emitting sources for fields of 20–50 emitters within the 50×50 km2 domain as long as skies are clear. They are unsuccessful for denser fields. GeoCARB does not benefit significantly from more frequent observations (4 times per day vs. 2 times per day) because of a temporal error correlation in the inversion, unless under partly cloudy conditions where more frequent observation increases the probability of clear sky. It becomes marginally successful when allowing a 5 km error tolerance for localization. A next-generation geostationary satellite instrument with 1.3×1.3 km2 pixels, hourly return time, and 1 ppb precision can successfully detect and locate the high-mode emitters for a dense field with up to 500 sites in the 50×50 km2 domain. The capabilities of TROPOMI and GeoCARB can be usefully augmented with a surface air observation network of 5–20 sites, and in turn the satellite instruments increase the detection capability that can be achieved from the surface sites alone.

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Section: Performance Of Different Satellite and Surface Observing Sysmentioning

confidence: 99%

Section: Combining Satellite and Surface Observationsmentioning

confidence: 99%

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Detecting high-emitting methane sources in oil/gas fields using satellite observations

et al. 2018

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“…This is due to the temporal model error correlation between successive GeoCARB observations. Accounting for cloud cover would show more benefit from 4×/day observations, since a higher frequency of observations allows a greater chance of sampling clear-sky conditions, although the benefit depends on the cloud persistence time scale (Sheng et al, 2018a).The ability of a satellite observing configuration to localize high-mode emitters thus depends not only on repeat time, resolution, and precision, but also on the density of emitters within a field. For the high-density fields of 100 and 500 emitters we find that only the next-generation satellite instrument is successful.…”

Section: Performance Of Different Satellite and Surface Observing Sysmentioning

confidence: 99%

“…Inverse analyses of SCIAMACHY and GOSAT data have focused on quantifying emissions at ~100 km regional scales (Bergamaschi et al, 2013;Wecht et al, 2014a;Alexe et al, 2015;Turner et al, 2015). OSSEs have shown the potential for TROPOMI and GeoCARB to effectively constrain emissions at the 25-100 km scale without the multiyear averaging required by SCIAMACHY and GOSAT (Wecht et al, 2014b;Sheng et al, 2018a). Other OSSEs have examined the potential for satellites to quantify large point sources from plume observations (Buchwitz et al, 2013;Rayner et al, 2014;Varon et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Detecting high-emitting methane sources in oil/gas fields using satellite observations

Cusworth¹,

Jacob²,

Sheng³

et al. 2018

Preprint

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Abstract. Methane emissions from oil/gas fields originate from a large number of relatively small and densely clustered point sources. A small fraction of high-mode emitters can make a large contribution to the total methane emission. Here we conduct observation system simulation experiments (OSSEs) to examine the potential of recently launched or planned satellites to detect and locate these high-mode emitters through measurements of atmospheric methane columns. We simulate atmospheric methane over a generic oil/gas field (20&#8211;500 production sites of different size categories in a 50&#8201;&#215;&#8201;50&#8201;km2 domain) for a 1-week period using the WRF-STILT meteorological model with 1.3&#8201;&#215;&#8201;1.3&#8201;km2 horizontal resolution. The simulations consider many random realizations for the occurrence and distribution of high-mode emitters in the field by sampling bi-modal probability density functions (pdfs) of emissions from individual sites. The atmospheric methane fields for each realization are observed virtually with different satellite and surface observing configurations. Column methane enhancements observed from satellites are small relative to instrument precision, even for high-mode emitters, so an inverse analysis is necessary. The inverse analysis can be regularized effectively using a L-1 norm to provide sparse solutions for a bi-modally distributed variable. We find that the recently launched TROPOMI instrument (low Earth orbit, 7&#8201;&#215;&#8201;7&#8201;km2 nadir pixels, daily return time) and the planned GeoCARB instrument (geostationary orbit, 2.7&#8201;&#215;&#8201;3.0&#8201;km2 pixels, 2&#215; or 4&#215;/day return time) are successful at locating high-emitting sources for fields of 20&#8211;50 emitters within the 50&#8201;&#215;&#8201;50&#8201;km2 domain but are unsuccessful for denser fields. GeoCARB does not benefit significantly from more frequent observations (4&#215;/day vs. 2&#215;/day) because of temporal error correlation in the inversion. It becomes marginally successful when allowing a 5-km error tolerance for localization. A next-generation geostationary satellite instrument with 1.3&#8201;&#215;&#8201;1.3&#8201;km2 pixels, hourly return time, and 1 ppb precision can successfully detect and locate the high-mode emitters for a dense field with up to 500 sites in the 50&#8201;&#215;&#8201;50&#8201;km2 domain. The capabilities of TROPOMI and GeoCARB can be usefully augmented with a surface air observation network of 5&#8211;20 sites, and in turn the satellite instruments increase the detection capability that can be achieved from the surface sites alone.

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Methane Mitigation: Methods to Reduce Emissions, on the Path to the Paris Agreement

Nisbet

Fisher

Lowry

et al. 2020

Reviews of Geophysics

235

131

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The atmospheric methane burden is increasing rapidly, contrary to pathways compatible with the goals of the 2015 United Nations Framework Convention on Climate Change Paris Agreement. Urgent action is required to bring methane back to a pathway more in line with the Paris goals. Emission reduction from “tractable” (easier to mitigate) anthropogenic sources such as the fossil fuel industries and landfills is being much facilitated by technical advances in the past decade, which have radically improved our ability to locate, identify, quantify, and reduce emissions. Measures to reduce emissions from “intractable” (harder to mitigate) anthropogenic sources such as agriculture and biomass burning have received less attention and are also becoming more feasible, including removal from elevated‐methane ambient air near to sources. The wider effort to use microbiological and dietary intervention to reduce emissions from cattle (and humans) is not addressed in detail in this essentially geophysical review. Though they cannot replace the need to reach “net‐zero” emissions of CO2, significant reductions in the methane burden will ease the timescales needed to reach required CO2 reduction targets for any particular future temperature limit. There is no single magic bullet, but implementation of a wide array of mitigation and emission reduction strategies could substantially cut the global methane burden, at a cost that is relatively low compared to the parallel and necessary measures to reduce CO2, and thereby reduce the atmospheric methane burden back toward pathways consistent with the goals of the Paris Agreement.

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Comparative analysis of low-Earth orbit (TROPOMI) and geostationary (GeoCARB, GEO-CAPE) satellite instruments for constraining methane emissions on fine regional scales: application to the Southeast US

Cited by 6 publications

References 0 publications

Detecting high-emitting methane sources in oil/gas fields using satellite observations

Detecting high-emitting methane sources in oil/gas fields using satellite observations

Detecting high-emitting methane sources in oil/gas fields using satellite observations

Methane Mitigation: Methods to Reduce Emissions, on the Path to the Paris Agreement

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