Abstract

Abstract. Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned for launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify and understand methane emissions through inverse analyses, from the global scale down to the scale of point sources and in combination with suborbital (surface and aircraft) data. Current global observations from Greenhouse Gases Observing Satellite (GOSAT) are of high quality but have sparse spatial coverage. They can quantify methane emissions on a regional scale (100–1000 km) through multiyear averaging. The Tropospheric Monitoring Instrument (TROPOMI), to be launched in 2017, is expected to quantify daily emissions on the regional scale and will also effectively detect large point sources. A different observing strategy by GHGSat (launched in June 2016) is to target limited viewing domains with very fine pixel resolution in order to detect a wide range of methane point sources. Geostationary observation of methane, still in the proposal stage, will have the unique capability of mapping source regions with high resolution, detecting transient "super-emitter" point sources and resolving diurnal variation of emissions from sources such as wetlands and manure. Exploiting these rapidly expanding satellite measurement capabilities to quantify methane emissions requires a parallel effort to construct high-quality spatially and sectorally resolved emission inventories. Partnership between top-down inverse analyses of atmospheric data and bottom-up construction of emission inventories is crucial to better understanding methane emission processes and subsequently informing climate policy.

Highlights

  • Methane is a greenhouse gas emitted by anthropogenic sources including livestock, oil–gas systems, landfills, coal mines, wastewater management, and rice cultivation

  • “Top-down” information from observations of atmospheric methane is often at odds with these estimates and differences need to be reconciled

  • Most inversions of SCIAMACHY and Gases Observing Satellite (GOSAT) satellite data for atmospheric methane have been done on the global scale, estimating emissions at the resolution of the chemical transport model (CTM) used as a forward model by applying an adjoint method (Bergamaschi et al, 2009, 2013; Spahni et al, 2011; Monteil et al, 2013; Cressot et al, 2014; Houweling et al, 2014; Alexe et al, 2015)

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Summary

Introduction

Methane is a greenhouse gas emitted by anthropogenic sources including livestock, oil–gas systems, landfills, coal mines, wastewater management, and rice cultivation. Near-future, and proposed satellite observations of atmospheric methane and assess their value for quantifying emissions, from regional scales down to the scale of individual point sources. Satellite measurements of atmospheric methane have been used to detect emission hotspots (Worden et al, 2012; Kort et al, 2014; Marais et al, 2014; Buchwitz et al, 2016) and to estimate emission trends (Schneising et al, 2014; Turner et al, 2016) They have been used in global inverse analyses to estimate emissions on regional scales (Bergamaschi et al, 2007, 2009, 2013; Monteil et al, 2013; Cressot et al, 2014; Wecht et al, 2014a; Alexe et al, 2015; Turner et al, 2015). As the demand for global monitoring of methane emissions grows, it is timely to review the capabilities and limitations of present and future satellite observations

Instruments and retrievals
Error characterization
Overview of inverse methods
Analytical method
Adjoint method
MCMC methods
Selection of emission state vector
Bottom-up inventory used as prior estimate
Positivity of the solution
Variability in the methane background
Methane sink in the troposphere
Stratospheric methane
Applications to SCIAMACHY and GOSAT data
Potential of future satellite observations
Observing requirements for regional and point sources
Findings
Conclusions and recommendations
Full Text
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