Global Atmospheric δ13CH4 and CH4 Trends for 2000-2020 from the Atmospheric Transport Model TM5 Using CH4 from Carbon Tracker Europe-CH4 Inversions

被引:0
|
作者
Mannisenaho, Vilma [1 ]
Tsuruta, Aki [1 ]
Backman, Leif [1 ]
Houweling, Sander [2 ,3 ]
Segers, Arjo [4 ]
Krol, Maarten [5 ,6 ]
Saunois, Marielle [7 ]
Poulter, Benjamin [8 ]
Zhang, Zhen [9 ]
Lan, Xin [10 ]
Dlugokencky, Edward J. [10 ]
Michel, Sylvia [11 ]
White, James W. C. [12 ]
Aalto, Tuula [1 ]
机构
[1] Finnish Meteorol Inst, FI-00101 Helsinki, Finland
[2] SRON Netherlands Inst Space Res, NL-2333 CA Leiden, Netherlands
[3] Vrije Univ Amsterdam, Dept Earth Sci, NL-1081 HV Amsterdam, Netherlands
[4] Netherlands Org Appl Sci Res TNO, Dept Climate Air & Sustainabil, NL-3508 TA Utrecht, Netherlands
[5] Wageningen Univ & Res Meteorol & Air Qual, Dept Environm Sci, NL-6700 AA Wageningen, Netherlands
[6] Univ Utrecht, Inst Marine & Atmospher Res Utrecht IMAU, Str Princetonpl 5, NL-3584 CC Utrecht, Netherlands
[7] MCF Univ Versailles St Quentin, CEA Orme Merisiers, Lab Sci Climat & Environm, F-91191 Gif Sur Yvette, France
[8] NASA, Goddard Space Flight Ctr, 8800 Greenbelt Rd, Greenbelt, MD 20771 USA
[9] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, 5825 Univ Res Ct,Suite 4001, College Pk, MD 20740 USA
[10] NOAA, Global Monitoring Lab GML, 325 Broadway, Boulder, CO 80305 USA
[11] Univ Colorado, Inst Arctic & Alpine Res INSTAAR, Campus Box 450, Boulder, CO 80309 USA
[12] Univ N Carolina, Dept Earth Marine & Environm Sci, Chapel Hill, NC 27514 USA
基金
芬兰科学院; 欧洲研究理事会;
关键词
methane; isotopes; atmospheric modelling; ISOTOPIC SOURCE SIGNATURES; METHANE EMISSIONS; FOSSIL-FUEL; SEASONAL-VARIATIONS; IMPACT; OH; VARIABILITY; ATTRIBUTION; CONSISTENT; HYDROGEN;
D O I
10.3390/atmos14071121
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study investigates atmospheric delta(CH4)-C-13 trends, as produced by a global atmospheric transport model using CH4 inversions from CarbonTracker-Europe CH4 for 2000-2020, and compares them to observations. The CH4 inversions include the grouping of the emissions both by delta(CH4)-C-13 isotopic signatures and process type to investigate the effect, and to estimate the CH4 magnitudes and model CH4 and delta(CH4)-C-13 trends. In addition to inversion results, simulations of the global atmospheric transport model were performed with modified emissions. The estimated global CH4 trends for oil and gas were found to increase more than coal compared to the priors from 2000-2006 to 2007-2020. Estimated trends for coal emissions at 30 degrees N-60 degrees N are less than 50% of those from priors. Estimated global CH4 rice emissions trends are opposite to priors, with the largest contribution from the EQ to 60 degrees N. The results of this study indicate that optimizing wetland emissions separately produces better agreement with the observed delta(CH4)-C-13 trend than optimizing all biogenic emissions simultaneously. This study recommends optimizing separately biogenic emissions with similar isotopic signature to wetland emissions. In addition, this study suggests that fossil-based emissions were overestimated by 9% after 2012 and biogenic emissions are underestimated by 8% in the inversion using EDGAR v6.0 as priors.
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页数:22
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