Assessing Methane Emissions from Global Space-Borne Observations

Frankenberg, Christian; Meirink, Jan Fokke; Weele, M. van; Platt, U.; Wagner, Thomas

doi:10.1126/science.1106644

Cited by 422 publications

(448 citation statements)

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“…The combined datasets provide the longest time series of globally averaged CH 4 abundance. Since the early 2000s, remotely sensed retrievals of CH 4 have provided CH 4 atmospheric columnaveraged mole fractions (Buchwitz et al, 2005a;Frankenberg et al, 2005;Butz et al, 2011;Crevoisier et al, 2009;. Fourier transform infrared (FTIR) measurements at fixed locations also provide methane column observations .…”

Section: Atmospheric Observationsmentioning

confidence: 99%

“…The atmospheric observation density has improved in the tropics with satellite-based column-averaged methane mixing ratios (Buchwitz et al, 2005b;Frankenberg et al, 2005;Butz et al, 2011). However, the optimal usage of satellite data remains limited by systematic errors in satellite retrievals (Bergamaschi et al, 2009;Locatelli et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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The global methane budget 2000–2012

Saunois

Bousquet

Poulter

et al. 2016

Earth Syst. Sci. Data

947

733

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Abstract. The global methane (CH 4 ) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH 4 over the past decade. Emissions and concentrations of CH 4 are continuing to increase, making CH 4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH 4 sources that overlap geographically, and from the destruction of CH 4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). . Top-down inversions consistently infer lower emissions in China (∼ 58 Tg CH 4 yr −1 , range 51-72, −14 %) and higher emissions in Africa (86 Tg CH 4 yr −1 , range 73-108, +19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models.The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40 % on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions.

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Section: Atmospheric Observationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The global methane budget 2000–2012

Saunois

Bousquet

Poulter

et al. 2016

Earth Syst. Sci. Data

947

733

View full text Add to dashboard Cite

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“…Our basic retrieval approach for δD largely follows retrievals from SCIAMACHY (e.g., Frankenberg et al, 2005aFrankenberg et al, , 2008Frankenberg et al, , 2009) using the IMAP-DOAS (Iterative Maximum a Posteriori-Differential Optical Absorption Spectroscopy) algorithm (Frankenberg et al, 2005b) with instrument-specific adaptions and ECMWF meteorological data for pressure, temperature and a priori humidity profiles. CO 2 is the only interfering species, and the disk-integrated solar line-list is adapted from the full-physics CO 2 retrievals used for GOSAT (originally developed for TCCON retrievals).…”

Section: Hdo/h O Retrieval Setup From Gosatmentioning

confidence: 99%

Water vapor isotopologue retrievals from high-resolution GOSAT shortwave infrared spectra

et al. 2013

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Remote sensing of the isotopic composition of water vapor can provide valuable information on the hydrological cycle. Here, we demonstrate the feasibility of retrievals of the relative abundance of HDO (the HDO/H2O ratio) from the Japanese GOSAT satellite. For this purpose, we use high spectral resolution nadir radiances around 6400 cm−1 (1.56 μm) to retrieve vertical column amounts of H2O and HDO. Retrievals of H2O correlate well with ECMWF (European Centre for Medium-Range Weather Forecasts) integrated profiles (r2 = 0.96). Typical precision errors in the retrieved column-averaged deuterium depletion (δD) are 20–40&permil;. We compare δD against a TCCON (Total Carbon Column Observing Network) ground-based station in Lamont, Oklahoma. Using retrievals in very dry areas over Antarctica, we detect a small systematic offset in retrieved H2O and HDO column amounts and take this into account for a bias correction of δD. Monthly averages of δD in the June 2009 to September 2011 time frame are well correlated with TCCON (r2 = 0.79) and exhibit a slope of 0.98 (1.23 if not bias corrected). We also compare seasonal averages on the global scale with results from the SCIAMACHY instrument in the 2003–2005 time frame. Despite the lack of temporal overlap, seasonal averages in general agree well, with spatial correlations (r2) ranging from 0.62 in September through November to 0.83 in June through August. However, we observe higher variability in GOSAT δD, indicated by fitted slopes between 1.2 and 1.46. The discrepancies are likely related to differences in vertical sensitivities but warrant further validation of both GOSAT and SCIAMACHY and an extension of the validation dataset

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“…The atmospheric CH 4 concentrations have been doubted since preindustrial time (Frankenberg et al, 2005), and most of the CH 4 is produced from fossil fuel combustion, wetlands, rice paddies, waste management and ruminants (Zhuang et al, 2009). Over the past decade, researchers have suggested that CH 4 emissions from reservoirs contribute considerably to anthropogenic CH 4 (Giles, 2006;Zheng et al, 2011a).…”

Section: Introductionmentioning

confidence: 99%

Preliminary report on methane emissions from the Three Gorges Reservoir in the summer drainage period

Yang

Wang

et al. 2011

Journal of Environmental Sciences

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Recently reported summertime methane (CH 4 ) emissions (6.7 ± 13.3 mg CH 4 /(m 2 ·hr)) from newly created marshes in the drawdown area of the Three Gorges Reservoir (TGR), China have triggered broad concern in academic circles and among the public. The CH 4 emissions from TGR water surfaces and drawdown areas were monitored from 3rd June to 16th October 2010 with floating and static chambers and gas chromatography. The average CH 4 emission flux from permanently flooded areas in Zigui, Wushan and Yunyang Counties was (0.33 ± 0.09) mg CH 4 /(m 2 ·hr). In half of these hottest months of the year, the wilderness, cropland and deforested drawdown sites were aerobic and located above water level, and the CH 4 emissions were very small, ranging from a sink at 0.12 mg CH 4 /(m 2 ·hr) to a source at 0.08 mg CH 4 /(m 2 ·hr) except for one mud-covered site after flood. Mean CH 4 emission in flooded drawdown sites was 0.34 mg CH 4 /(m 2 ·hr). The emissions from the rice paddy sites in the drawdown area were averaged at (4.86 ± 2.31) mg CH 4 /(m 2 ·hr). Excepting the rice-paddy sites, these results show much lower emission levels than previously reported. Our results indicated considerable spatial and temporal variation in CH 4 emissions from the TGR. Human activities and occasional events, such as flood, may also affect emission levels. Long-term CH 4 measurements and modeling in a large region are necessary to accurately estimate greenhouse gas emissions from the TGR.

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Assessing Methane Emissions from Global Space-Borne Observations

Abstract: Our iterative maximum a posteriori (IMAP) DOAS algorithm (12) is based on optimal estimation (S1,S2) and uses the depth of the absorption structures of the respective

Cited by 422 publications

References 24 publications

The global methane budget 2000–2012

The global methane budget 2000–2012

Water vapor isotopologue retrievals from high-resolution GOSAT shortwave infrared spectra

Preliminary report on methane emissions from the Three Gorges Reservoir in the summer drainage period

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