Source Partitioning of Methane Emissions and its Seasonality in the U.S. Midwest

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

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)646-659
Number of pages14
JournalJournal of Geophysical Research: Biogeosciences
Volume123
Issue number2
DOIs
StatePublished - Feb 2018

Bibliographical note

Funding Information:
This research was supported by the United States Department of Agriculture, USDA grant 2013-67019- 21364; the United States National Science Foundation (grant 1640337); and the USDA-ARS and NASA (grant NNX17AK18G). We express our sincere thanks to Minnesota Public Radio and Tom Nelson for the logistical support at the KCMP tall tower. The Minnesota Supercomputing Institute provides key computing resources and assistance. Data are hosted at http://www.biometeorology.umn.edu/research/data-archives and ESS-DIVE. We acknowledge the support of an MnDrive PhD fellowship to Z.C. J.D.W. acknowledges support from the U.S. Department of Energy Office of Science and Office of Biological and Environmental Research Program, through Oak Ridge National Laboratory’s Terrestrial Ecosystem Science (TES) Science Focus Area (SFA). ORNL is managed by UT-Battelle, LLC, for the U.S. DOE under contract DE-AC05-00OR22725.

Keywords

  • Bayesian inversion
  • aerodynamic flux
  • methane source partitioning
  • wetland emissions

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