Preprints
https://doi.org/10.5194/acp-2020-1262
https://doi.org/10.5194/acp-2020-1262

  04 Jan 2021

04 Jan 2021

Review status: this preprint is currently under review for the journal ACP.

Assessing Urban Methane Emissions using Column Observing Portable FTIR Spectrometers and a Novel Bayesian Inversion Framework

Taylor S. Jones1,2, Jonathan E. Franklin1, Jia Chen3, Florian Dietrich3, Kristian D. Hajny4, Johannes C. Paetzold3, Adrian Wenzel3, Conor Gately1,2, Elaine Gottlieb1, Harrison Parker5,6, Manvendra Dubey5, Frank Hase7, Paul B. Shepson4, Levi H. Mielke8, and Steven C. Wofsy1 Taylor S. Jones et al.
  • 1School of Engineering and Applied Sciences, Harvard University
  • 2Boston University
  • 3Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
  • 4Purdue University
  • 5Los Alamos National Laboratory
  • 6California Institute of Technology
  • 7Karlsruhe Institute of Technology
  • 8University of Indianapolis

Abstract. Cities represent a large and concentrated portion of global greenhouse gas emissions, including methane. Quantifying methane emissions from urban areas is difficult, and inventories made using bottom-up accounting methods often differ greatly from top-down estimates generated from atmospheric observations. Emissions from leaks in natural gas infrastructure are difficult to predict, and are therefore poorly constrained in bottom-up inventories. Natural gas infrastructure leaks and emissions from end uses can be spread throughout the city, and this diffuse source can represent a significant fraction of a city's total emissions.

We investigated diffuse methane emissions of the city of Indianapolis, USA during a field campaign in May of 2016. A network of five portable solar-tracking Fourier transform infrared (FTIR) spectrometers was deployed throughout the city. These instruments measure the mole fraction of methane in a total column of air, giving them sensitivity to larger areas of the city than in situ sensors at the surface.

We present an innovative inversion method to link these total column concentrations to surface fluxes. This method combines a Lagrangian transport model with a Bayesian inversion framework to estimate surface emissions and their uncertainties, together with determining the concentrations of methane in the air flowing into the city. Variations exceeding 10 ppb were observed in the inflowing air on a typical day, somewhat larger than the enhancements due to urban emissions (< 5 ppb downwind of the city). We found diffuse methane emissions of 73(±22) mol s−1, about 50 % of the urban total and 68 % higher than estimated from bottom-up methods, albeit somewhat smaller than estimates from studies using tower and aircraft observations. The measurement and model techniques developed here address many of the challenges present when quantifying urban greenhouse gas emissions, and will help in the design of future measurement schemes in other cities.

Taylor S. Jones et al.

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2020-1262', Anonymous Referee #1, 31 Jan 2021 reply

Taylor S. Jones et al.

Data sets

Indianapolis EM27/SUN Observations and Footprints for May 2016 Taylor Jones https://doi.org/10.7910/DVN/JWL4PK

Model code and software

Indianapolis EM27/SUN Observations and Footprints for May 2016 Taylor Jones https://doi.org/10.7910/DVN/JWL4PK

Taylor S. Jones et al.

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Short summary
Methane emissions from leaks in natural gas pipes are often a large source in urban areas, but they are difficult to measure on a city-wide scale. Here we use an array of innovative methane sensors distributed around the city of Indianapolis and a new method of combining their data with an atmospheric model to accurately determine the magnitude of these emissions, which are about 70 % larger than predicted. This method can serve as a framework for cities trying to account for their emissions.
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