气候变化领域集成服务门户(CCPortal): Quantifying sources of Brazil's CH4 emissions between 2010 and 2018 from satellite data

CCPortal

DOI	10.5194/acp-20-13041-2020
	Quantifying sources of Brazil's CH4 emissions between 2010 and 2018 from satellite data
	L. Tunnicliffe R.; L. Ganesan A.; J. Parker R.; Boesch H.; Gedney N.; Poulter B.; Zhang Z.; Walter D.; Rigby M.; Henne S.; Young D.; O'Doherty S.
发表日期	2020
ISSN	1680-7316
起始页码	13041
结束页码	13067
卷号	20 期号:21
英文摘要	Brazil's CH4 emissions over the period 2010- 2018 were derived for the three main sectors of activity: anthropogenic, wetland and biomass burning. Our inverse modelling estimates were derived from GOSAT (Greenhouse gases Observing SATellite) satellite measurements of XCH4 combined with surface data from Ragged Point, Barbados, and the high-resolution regional atmospheric transport model NAME (Numerical Atmospheric-dispersion Modelling Environment). We find that Brazil's mean emissions over 2010- 2018 are 33:63:6Tgyr1, which are comprised of 19:0 2:6Tgyr1 from anthropogenic (primarily related to agriculture and waste), 13:01:9Tgyr1 from wetlands and 1:7 0:3Tgyr1 from biomass burning sources. In addition, between the 2011-2013 and 2014-2018 periods, Brazil's mean emissions rose by 6:95:3Tgyr1 and this increase may have contributed to the accelerated global methane growth rate observed during the latter period. We find that wetland emissions from the western Amazon increased during the start of the 2015-2016 El Nino by 3:72:7Tgyr1 and this is likely driven by increased surface temperatures. We also find that our estimates of anthropogenic emissions are consistent with those reported by Brazil to the United Framework Convention on Climate Change. We show that satellite data are beneficial for constraining national-scale CH4 emissions, and, through a series of sensitivity studies and validation experiments using data not assimilated in the inversion, we demonstrate that (a) calibrated ground-based data are important to include alongside satellite data in a regional inversion and that (b) inversions must account for any offsets between the two data streams and their representations by models. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
英文关键词	biomass burning; data inversion; GOSAT; inverse analysis; methane; numerical model; quantitative analysis; satellite data; surface temperature; wetland; Amazonia; Brazil
语种	英语
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/168959
作者单位	School of Geographical Sciences, University of Bristol, Bristol, United Kingdom; School of Chemistry, University of Bristol, Bristol, United Kingdom; National Centre for Earth Observation, University of Leicester, Leicester, United Kingdom; Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, United Kingdom; Met Office Hadley Centre, Joint Centre for Hydrometeorological Research, Exeter, United Kingdom; Nasa Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, United States; Department of Geographical Sciences, University of Maryland, College Park, United States; Max Planck Institute for Biogeochemistry, Jena, Germany; Max Planck Institute for Chemistry, Mainz, Germany; Empa Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
推荐引用方式 GB/T 7714	L. Tunnicliffe R.,L. Ganesan A.,J. Parker R.,et al. Quantifying sources of Brazil's CH4 emissions between 2010 and 2018 from satellite data[J],2020,20(21).
APA	L. Tunnicliffe R..,L. Ganesan A..,J. Parker R..,Boesch H..,Gedney N..,...&O'Doherty S..(2020).Quantifying sources of Brazil's CH4 emissions between 2010 and 2018 from satellite data.Atmospheric Chemistry and Physics,20(21).
MLA	L. Tunnicliffe R.,et al."Quantifying sources of Brazil's CH4 emissions between 2010 and 2018 from satellite data".Atmospheric Chemistry and Physics 20.21(2020).