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    Author(s): Zichong Chen; Timothy J. Griffis; John M. Baker; Dylan B. Millet; Jeffrey D. Wood; Edward J. Dlugokencky; Arlyn E. Andrews; Colm Sweeney; Cheng Hu; Randall K. Kolka
    Date: 2018
    Source: Journal of Geophysical Research: Biogeosciences. 123(2): 646-659.
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (1.0 MB)


    The methane (CH4) budget and its source partitioning are poorly constrained in the Midwestern United States. We used tall tower (185 m) aerodynamic flux measurements and atmospheric scale factor Bayesian inversions to constrain the monthly budget and to partition the total budget into natural (e.g., wetlands) and anthropogenic (e.g., livestock, waste, and natural gas) sources for the period June 2016 to September 2017. Aerodynamic flux observations indicated that the landscape was a CH4 source with a mean annual CH4 flux of +13.7 ± 0.34 nmol m-2 s-1 and was rarely a net sink. The scale factor Bayesian inversion analyses revealed a mean annual source of +12.3 ± 2.1 nmol m-2 s-1. Flux partitioning revealed that the anthropogenic source (7.8 ± 1.6 Tg CH4 yr-1) was 1.5 times greater than the bottom-up gridded United States Environmental Protection Agency inventory, in which livestock and oil/gas sources were underestimated by 1.8-fold and 1.3-fold, respectively. Wetland emissions (4.0 ± 1.2 Tg CH4 yr-1) were the second largest source, accounting for 34% of the total budget. The temporal variability of total CH4 emissions was dominated by wetlands with peak emissions occurring in August. In contrast, emissions from oil/gas and other anthropogenic sources showed relatively weak seasonality.

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    Chen, Zichong; Griffis, Timothy J.; Baker, John M.; Millet, Dylan B.; Wood, Jeffrey D.; Dlugokencky, Edward J.; Andrews, Arlyn E.; Sweeney, Colm; Hu, Cheng; Kolka, Randall K. 2018. Source partitioning of methane emissions and its seasonality in the U.S. Midwest. Journal of Geophysical Research: Biogeosciences. 123(2): 646-659.


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