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Attribution of recent increases in atmospheric methane through 3-D inverse modelling

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posted on 2019-08-19, 09:18 authored by J McNorton, C Wilson, M Gloor, RJ Parker, H Boesch, W Feng, R Hossaini, MP Chipperfield
The atmospheric methane (CH4) growth rate has varied considerably in recent decades. Unexplained renewed growth after 2006 followed 7 years of stagnation and coincided with an isotopic trend toward CH4 more depleted in 13C, suggesting changes in sources and/or sinks. Using surface observations of both CH4 and the relative change of isotopologue ratio (δ13 CH4) to constrain a global 3-D chemical transport model (CTM), we have performed a synthesis inversion for source and sink attribution. Our method extends on previous studies by providing monthly and regional attribution of emissions from six different sectors and changes in atmospheric sinks for the extended 2003-2015 period. Regional evaluation of the model CH4 tracer with independent column observations from the Greenhouse Gases Observing Satellite (GOSAT) shows improved performance when using posterior fluxes (R =0:94-0.96, RMSE= 8:3- 16.5 ppb), relative to prior fluxes (R =0:60-0.92, RMSE= 48:6-64.6 ppb). Further independent validation with data from the Total Carbon Column Observing Network (TCCON) shows a similar improvement in the posterior fluxes (R =0:87, RMSE= 18:8 ppb) compared to the prior fluxes (R =0:69, RMSE= 55:9 ppb). Based on these improved posterior fluxes, the inversion results suggest the most likely cause of the renewed methane growth is a post-2007 1:8± 0:4% decrease in mean OH, a 12:9±2:7% increase in energy sector emissions, mainly from Africa-Middle East and southern Asia-Oceania, and a 2:6±1:8%increase in wetland emissions, mainly from northern Eurasia. The posterior wetland flux increases are in general agreement with bottom-up estimates, but the energy sector growth is greater than estimated by bottom-up methods. The model results are consistent across a range of sensitivity analyses. When forced to assume a constant (annually repeating) OH distribution, the inversion requires a greater increase in energy sector (13:6±2:7 %) and wetland (3:6±1:8 %) emissions and an 11:5±3:8% decrease in biomass burning emissions. Assuming no prior trend in sources and sinks slightly reduces the posterior growth rate in energy sector and wetland emissions and further increases the magnitude of the negative OH trend. We find that possible tropospheric Cl variations do not influence δ13CH4 and CH4 trends, although we suggest further work on Cl variability is required to fully diagnose this contribution. While the study provides quantitative insight into possible emissions variations which may explain the observed trends, uncertainty in prior source and sink estimates and a paucity of δ13CH4 observations limit the robustness of the posterior estimates.

Funding

This work was supported by the NERC MOYA project (NE/N015657/1). Martyn P. Chipperfield and Manuel Gloor acknowledge support from NERC grants GAUGE (NE/K002244/1) and AMAZONICA (NE/F005806/1). Rob J. Parker was funded via an ESA Living Planet Fellowship with additional funding from the UK National Centre for Earth Observation and the ESA Greenhouse Gas Climate Change Initiative (GHG-CCI). Hartmut Boesch was supported by ESA GHG-CCI. Chris Wilson, Rob J. Parker, and Hartmut Boesch acknowledge funding support as part of NERC's National Centre for Earth Observation, contract number PR140015. The TOMCAT runs were performed on the Arc3 supercomputer at the University of Leeds. We thank the Japanese Aerospace Exploration Agency, National Institute for Environmental Studies, and the Ministry of Environment for the GOSAT data and their continuous support as part of the Joint Research Agreement. The GOSAT retrievals used the ALICE High Performance Computing Facility at the University of Leicester. NOAA atmospheric CH4 and δ13CH4 values were obtained from the ESRL GMD Carbon Cycle Cooperative Global Air Sampling Network (https://esrl.noaa.gov/, last access: 5 October 2017). TCCON atmospheric column CH4 values were obtained from the TCCON data archive (https://tccondata.org/). The authors would also like to thank Matt Rigby for advice with 13CH4 modelling.

History

Citation

Atmospheric Chemistry and Physics, 2018, 18 (24), pp. 18149-18168

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Physics and Astronomy

Version

  • VoR (Version of Record)

Published in

Atmospheric Chemistry and Physics

Publisher

European Geosciences Union (EGU), Copernicus Publications

issn

1680-7316

eissn

1680-7324

Acceptance date

2019-12-10

Copyright date

2018

Available date

2019-08-19

Publisher version

https://www.atmos-chem-phys.net/18/18149/2018/

Notes

All model data used in this study are available through the University of Leeds FTP server. For access please contact Martyn P. Chipperfield (m.chipperfield@leeds.ac.uk).

Language

en

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