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Apportionment and Inventory Optimization of Agriculture and Energy Sector Methane Emissions using Multi-month Trace Gas Measurements in Northern Colorado
  • +6
  • Griffin J Mead,
  • Daniel I Herman,
  • Fabrizio R Giorgetta,
  • Nathan A Malarich,
  • Esther Baumann,
  • Brian R Washburn,
  • Nathan R Newbury,
  • Ian Coddington,
  • Kevin C Cossel
Griffin J Mead
National Institute of Standards and Technology, Spectrum Technology and Research Division

Corresponding Author:[email protected]

Author Profile
Daniel I Herman
National Institute of Standards and Technology, Spectrum Technology and Research Division
Fabrizio R Giorgetta
National Institute of Standards and Technology, Spectrum Technology and Research Division
Nathan A Malarich
National Institute of Standards and Technology, Spectrum Technology and Research Division
Esther Baumann
National Institute of Standards and Technology, Spectrum Technology and Research Division
Brian R Washburn
National Institute of Standards and Technology, Spectrum Technology and Research Division
Nathan R Newbury
National Institute of Standards and Technology, Spectrum Technology and Research Division
Ian Coddington
National Institute of Standards and Technology, Spectrum Technology and Research Division
Kevin C Cossel
National Institute of Standards and Technology, Spectrum Technology and Research Division

Abstract

Quantifying sector-resolved methane fluxes in complex emissions environments is challenging yet necessary to improve emissions inventories and guide policy.  Here, we separate energy and agriculture sector emissions using a dynamic linear model analysis of methane, ethane, and ammonia data measured at a Northern Colorado site from November 2021 to January 2022. By combining these sector-apportioned observations with spatially resolved inventories and Bayesian inverse methods, energy and agriculture methane fluxes are optimized across the study’s ~850 km2 sensitivity area. Energy sector fluxes are synthesized with previous literature to evaluate trends in energy-sector methane emissions. Optimized agriculture fluxes in the study area were 3× larger than inventory estimates; we demonstrate this discrepancy is consistent with differences in the modeled vs. real-world spatial distribution of agricultural sources. These results highlight how sector-apportioned methane observations can yield multi-sector inventory optimizations in complex environments.
18 Oct 2023Submitted to ESS Open Archive
11 Dec 2023Published in ESS Open Archive