Global methane emission estimates for 2000-2012 from CarbonTracker Europe-CH4 v1.0
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2017
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Source Geoscientific Model Development, 10(3), 29.
Tsuruta, A., Aalto, T., Backman, L., Hakkarainen, J., van der Laan-Luijkx, I. T., Krol, M. C., Spahni, R., Houweling, S., Laine, M., Dlugokencky, E., Gomez-Pelaez, A. J., van der Schoot, M., Langenfelds, R., Ellul, R., Arduini, J., Apadula, F., Gerbig, C., Feist, D. G., Kivi, R., ... Peters, W. (2017). Global methane emission estimates for 2000-2012 from CarbonTracker Europe-CH4 v1.0. Geoscientific Model Development, 10(3). https://doi.org/10.5194/gmd-10-1261-2017
Tsuruta, Aki, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, and Renato Spahni, et al.. "Global methane emission estimates for 2000-2012 from CarbonTracker Europe-CH4 v1.0." Geoscientific Model Development 10, no. 3 (2017). https://doi.org/10.5194/gmd-10-1261-2017.
Tsuruta, Aki, et al. "Global methane emission estimates for 2000-2012 from CarbonTracker Europe-CH4 v1.0." Geoscientific Model Development, vol. 10, no. 3, 2017. NOAA IR. https://doi.org/10.5194/gmd-10-1261-2017.
Details
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Journal Title:Geoscientific Model Development
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Personal Author:Tsuruta, Aki
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Aalto, Tuula
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Backman, Leif
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Hakkarainen, Janne
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van der Laan-Luijkx, Ingrid T.
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Krol, Maarten C.
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Spahni, Renato
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Houweling, Sander
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Laine, Marko
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Dlugokencky, Ed
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Gomez-Pelaez, Angel J.
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van der Schoot, Marcel
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Langenfelds, Ray
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Ellul, Raymond
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Arduini, Jgor
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Apadula, Francesco
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Gerbig, Christoph
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Feist, Dietrich G.
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Kivi, Rigel
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Yoshida, Yukio
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Peters, Wouter
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NOAA Program & Office:
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Description:We present a global distribution of surface methane (CH4) emission estimates for 2000-2012 derived using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, anthropogenic and biospheric CH4 emissions are simultaneously estimated based on constraints of global atmospheric in situ CH4 observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH4 to surface in situ observations, vertical profiles of CH4 made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH4) from the Total Carbon Column Observing Network (TCCON), and XCH4 from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH4 is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000-2012 are 516 +/- 51 Tg CH4 yr(-1), with an increase of 18 Tg CH4 yr(-1) from 2000-2006 to 2007-2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations (< 2 Tg CH4 yr(-1) difference), and much smaller than suggested by EDGAR v4.2 FT2010 inventory (33 Tg CH4 yr(-1)), which was used for prior anthropogenic emission estimates. The result is in good agreement with other published estimates from inverse modelling studies (16-20 Tg CH4 yr(-1)). However, this study could not conclusively separate a small trend in biospheric emissions (-5 to +6.9 Tg CH4 yr(-1)) from the much larger trend in anthropogenic emissions (15-27 Tg CH4 yr(-1)). Finally, we find that the global and North American CH4 balance could be closed over this time period without the previously suggested need to strongly increase anthropogenic CH4 emissions in the United States. With further developments, especially on the treatment of the atmospheric CH4 sink, we expect the data assimilation system presented here will be able to contribute to the ongoing interpretation of changes in this important greenhouse gas budget.
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Source:Geoscientific Model Development, 10(3), 29.
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DOI:
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Document Type:
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Rights Information:CC BY
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Compliance:Submitted
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[PDF - 2.85 MB]
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Main Document Checksum:urn:sha-512:6e6bb8a9248fa20b91496a62981b3ce8471d279004704479e74c5e1a333689622b5ddcbe62f75bc64c468dfc45915280e0814cc84abde35a631e288f403dca27
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Tsuruta, A., Aalto, T., Backman, L., Hakkarainen, J., van der Laan-Luijkx, I. T., Krol, M. C., Spahni, R., Houweling, S., Laine, M., Dlugokencky, E., Gomez-Pelaez, A. J., van der Schoot, M., Langenfelds, R., Ellul, R., Arduini, J., Apadula, F., Gerbig, C., Feist, D. G., Kivi, R., ... Peters, W. (2017). Global methane emission estimates for 2000-2012 from CarbonTracker Europe-CH4 v1.0. Geoscientific Model Development, 10(3). https://doi.org/10.5194/gmd-10-1261-2017
Tsuruta, Aki, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, and Renato Spahni, et al.. "Global methane emission estimates for 2000-2012 from CarbonTracker Europe-CH4 v1.0." Geoscientific Model Development 10, no. 3 (2017). https://doi.org/10.5194/gmd-10-1261-2017.
Tsuruta, Aki, et al. "Global methane emission estimates for 2000-2012 from CarbonTracker Europe-CH4 v1.0." Geoscientific Model Development, vol. 10, no. 3, 2017. NOAA IR. https://doi.org/10.5194/gmd-10-1261-2017.
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