Estimating methane emissions in the Arctic nations using surface observations from 2008 to 2019

被引:5
作者
Wittig, Sophie [1 ]
Berchet, Antoine [1 ]
Pison, Isabelle [1 ]
Saunois, Marielle [1 ]
Thanwerdas, Joel [1 ]
Martinez, Adrien [1 ]
Paris, Jean-Daniel [1 ]
Machida, Toshinobu [2 ]
Sasakawa, Motoki [2 ]
Worthy, Douglas E. J. [3 ]
Lan, Xin [4 ,5 ]
Thompson, Rona L. [6 ]
Sollum, Espen [6 ]
Arshinov, Mikhail
机构
[1] UVSQ, Lab Sci Climat & Environm, CEA, CNRS, Gif Sur Yvette, France
[2] Natl Inst Environm Studies, Ctr Global Environm Res, Tsukuba, Japan
[3] Environm & Climate Change Canada, Climate Res Div, Toronto, ON, Canada
[4] Univ Colorado Boulder, Cooperat Inst Res Environm Sci, Boulder, CO USA
[5] NOAA Global Monitoring Lab, Boulder, CO USA
[6] Norsk Inst Luftforskning NILU, Kjeller, Norway
基金
欧盟地平线“2020”;
关键词
PARTICLE DISPERSION MODEL; INVERSION FRAMEWORK; TECHNICAL NOTE; FLUXES; GAS; QUANTIFICATION; NETWORK; CANADA; OIL; CH4;
D O I
10.5194/acp-23-6457-2023
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Arctic is a critical region in terms of global warming. Environmental changes are already progressing steadily in high northern latitudes, whereby, among other effects, a high potential for enhanced methane (CH4) emissions is induced. With CH4 being a potent greenhouse gas, additional emissions from Arctic regions may intensify global warming in the future through positive feedback. Various natural and anthropogenic sources are currently contributing to the Arctic's CH4 budget; however, the quantification of those emissions remains challenging. Assessing the amount of CH4 emissions in the Arctic and their contribution to the global budget still remains challenging. On the one hand, this is due to the difficulties in carrying out accurate measurements in such remote areas. Besides, large variations in the spatial distribution of methane sources and a poor understanding of the effects of ongoing changes in carbon decomposition, vegetation and hydrology also complicate the assessment. Therefore, the aim of this work is to reduce uncertainties in current bottom-up estimates of CH4 emissions as well as soil oxidation by implementing an inverse modelling approach in order to better quantify CH4 sources and sinks for the most recent years (2008 to 2019). More precisely, the objective is to detect occurring trends in the CH4 emissions and potential changes in seasonal emission patterns. The implementation of the inversion included footprint simulations obtained with the atmospheric transport model FLEXPART (FLEXible PARTicle dispersion model), various emission estimates from inventories and land surface models, and data on atmospheric CH4 concentrations from 41 surface observation sites in the Arctic nations. The results of the inversion showed that the majority of the CH4 sources currently present in high northern latitudes are poorly constrained by the existing observation network. Therefore, conclusions on trends and changes in the seasonal cycle could not be obtained for the corresponding CH4 sectors. Only CH4 fluxes from wetlands are adequately constrained, predominantly in North America. Within the period under study, wetland emissions show a slight negative trend in North America and a slight positive trend in East Eurasia. Overall, the estimated CH4 emissions are lower compared to the bottom-up estimates but higher than similar results from global inversions.
引用
收藏
页码:6457 / 6485
页数:29
相关论文
共 80 条
[61]   Variational inverse modeling within the Community Inversion Framework v1.1 to assimilate δ13C(CH4) and CH4: a case study with model LMDz-SACS [J].
Thanwerdas, Joel ;
Saunois, Marielle ;
Berchet, Antoine ;
Pison, Isabelle ;
Vaughn, Bruce H. ;
Michel, Sylvia Englund ;
Bousquet, Philippe .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2022, 15 (12) :4831-4851
[62]   FLEXINVERT: an atmospheric Bayesian inversion framework for determining surface fluxes of trace species using an optimized grid [J].
Thompson, R. L. ;
Stohl, A. .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2014, 7 (05) :2223-2242
[63]   Methane fluxes in the high northern latitudes for 2005-2013 estimated using a Bayesian atmospheric inversion [J].
Thompson, Rona L. ;
Sasakawa, Motoki ;
Machida, Toshinobu ;
Aalto, Tuula ;
Worthy, Doug ;
Lavric, Jost V. ;
Myhre, Cathrine Lund ;
Stohl, Andreas .
ATMOSPHERIC CHEMISTRY AND PHYSICS, 2017, 17 (05) :3553-3572
[64]   Detectability of Arctic methane sources at six sites performing continuous atmospheric measurements [J].
Thonat, Thibaud ;
Saunois, Marielle ;
Bousquet, Philippe ;
Pison, Isabelle ;
Tan, Zeli ;
Zhuang, Qianlai ;
Crill, Patrick M. ;
Thornton, Brett F. ;
Bastviken, David ;
Dlugokencky, Ed J. ;
Zimov, Nikita ;
Laurila, Tuomas ;
Hatakka, Juha ;
Hermansen, Ove ;
Worthy, Doug E. J. .
ATMOSPHERIC CHEMISTRY AND PHYSICS, 2017, 17 (13) :8371-8394
[65]   Shipborne eddy covariance observations of methane fluxes constrain Arctic sea emissions [J].
Thornton, Brett F. ;
Prytherch, John ;
Andersson, Kristian ;
Brook, Ian M. ;
Salisbury, Dominic ;
Tjernstrom, Michael ;
Crill, Patrick M. .
SCIENCE ADVANCES, 2020, 6 (05)
[66]  
TINER R.W., 2015, REMOTE SENSING WETLA
[67]   Flex_extract v7.1.2-a software package to retrieve and prepare ECMWF data for use in FLEXPART [J].
Tipka, Anne ;
Haimberger, Leopold ;
Seibert, Petra .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2020, 13 (11) :5277-5310
[68]   CH4 Fluxes Derived from Assimilation of TROPOMI XCH4 in CarbonTracker Europe-CH4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes [J].
Tsuruta, Aki ;
Kivimaki, Ella ;
Lindqvist, Hannakaisa ;
Karppinen, Tomi ;
Backman, Leif ;
Hakkarainen, Janne ;
Schneising, Oliver ;
Buchwitz, Michael ;
Lan, Xin ;
Kivi, Rigel ;
Chen, Huilin ;
Buschmann, Matthias ;
Herkommer, Benedikt ;
Notholt, Justus ;
Roehl, Coleen ;
Te, Yao ;
Wunch, Debra ;
Tamminen, Johanna ;
Aalto, Tuula .
REMOTE SENSING, 2023, 15 (06)
[69]   Methane budget estimates in Finland from the CarbonTracker Europe-CH4 data assimilation system [J].
Tsuruta, Aki ;
Aalto, Tuula ;
Backman, Leif ;
Krol, Maarten C. ;
Peters, Wouter ;
Lienert, Sebastian ;
Joos, Fortunat ;
Miller, Paul A. ;
Zhang, Wenxin ;
Laurila, Tuomas ;
Hatakka, Juha ;
Leskinen, Ari ;
Lehtinen, Kari E. J. ;
Peltola, Olli ;
Vesala, Timo ;
Levula, Janne ;
Dlugokencky, Ed ;
Heimann, Martin ;
Kozlova, Elena ;
Aurela, Mika ;
Lohila, Annalea ;
Kauhaniemi, Mari ;
Gomez-Pelaez, Angel J. .
TELLUS SERIES B-CHEMICAL AND PHYSICAL METEOROLOGY, 2019, 71 :1-20
[70]  
Uttal T., 2013, EGU201311819