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Detection of Methane Emission from a Local Source Using GOSAT Target Observations
Open AccessArticle

Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations

1
Satellite Observation Center, Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba 305-8506, Japan
2
Climate System Research, Finnish Meteorological Institute, 00560 Helsinki, Finland
3
Department of Climate Change, National Climate Center, Beijing 100081, China
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Indian Institute of Tropical Meteorology, Dr. Homi Bhabha Road, Pashan, Pune 411 008, Maharashtra, India
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Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba 305-8506, Japan
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Deutscher Wetterdienst, 63067 Offenbach, Germany
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European Commission Joint Research Centre, 21027 Ispra, Italy
8
V.E. Zuev Institute of Atmospheric Optics, SB RAS, Tomsk 634055, Russia
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Center for Environmental Measurement and Analysis, National Institute for Environmental Studies, Tsukuba 305-8506, Japan
10
Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, ON M3H 5T4, Canada
11
Earth System Research Laboratory, NOAA, Boulder, CO 80305-3328, USA
12
Laboratoire des Sciences du Climat et de l’Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, France
13
Dipartimento di Scienze Pure ed Applicate, Università degli Studi di Urbino, piazza Rinascimento 6, 61029 Urbino, Italy
14
Max Planck Institute for Biogeochemistry, Hans-Knoell-Str. 10, 07745 Jena, Germany
15
ENEA, Laboratory for Observations and Measurements for Environment and Climate, Via Principe di Granatelli 24, 90139 Palermo, Italy
16
Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Victoria 3195, Australia
17
Institute for Atmospheric and Earth System Research/Physics, Faculty of Sciences, University of Helsinki, 00014 Helsinki, Finland
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(3), 375; https://doi.org/10.3390/rs12030375
Received: 24 December 2019 / Revised: 16 January 2020 / Accepted: 21 January 2020 / Published: 24 January 2020
(This article belongs to the Special Issue Remote Sensing of Carbon Dioxide and Methane in Earth’s Atmosphere)
We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries. View Full-Text
Keywords: inverse model; GOSAT; methane emission; anthropogenic; UNFCCC; wetland inverse model; GOSAT; methane emission; anthropogenic; UNFCCC; wetland
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Janardanan, R.; Maksyutov, S.; Tsuruta, A.; Wang, F.; Tiwari, Y.K.; Valsala, V.; Ito, A.; Yoshida, Y.; Kaiser, J.W.; Janssens-Maenhout, G.; Arshinov, M.; Sasakawa, M.; Tohjima, Y.; Worthy, D.E.J.; Dlugokencky, E.J.; Ramonet, M.; Arduini, J.; Lavric, J.V.; Piacentino, S.; Krummel, P.B.; Langenfelds, R.L.; Mammarella, I.; Matsunaga, T. Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations. Remote Sens. 2020, 12, 375.

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