Urban emission estimates and validation of satellite-measured urban GHG concentration gradients using MUCCnet data (Munich Urban Carbon Column network)

Florian Dietrich,  Technical University of Munich,  flo.dietrich@tum.de (Presenter)
Jia Chen,  Technical University of Munich,  jia.chen@tum.de (Presenter)
Adrian Wenzel,  Technical University of Munich,  a.wenzel@tum.de
Maximilian Rißmann,  Technical University of Munich,  rissmannmax@gmail.com
Andreas Forstmaier,  Technical University of Munich,  andreas.forstmaier@tum.de
Friedrich Klappenbach,  Technical University of Munich,  ge79wul@mytum.de
Xinxu Zhao,  Technical University of Munich,  xinxu.zhao@tum.de
Taylor Jones,  Harvard University / Boston University,  tsjones@bu.edu
Jonathan Franklin,  Boston University,  jfranklin@g.harvard.edu
Matthäus Kiel,  JPL/Caltech,  matthaeus.kiel@jpl.nasa.gov
Greg Osterman,  Jet Propulsion Laboratory,  gregory.b.osterman@jpl.nasa.gov

In 2019, we established the Munich Urban Carbon Column network (MUCCnet) [1] that measures the column-averaged concentration gradients of CO2, CH4 and CO using the differential column methodology (DCM, [2]). The network consists of five ground-based FTIR spectrometers (EM27/SUN from Bruker [3]), which are deployed both on the outskirts of Munich and in the city center. The distance between each outer spectrometer and the center station is approximately 10 km. Each spectrometer is protected by one of our fully automated enclosure systems [4], allowing us to run the network permanently. In addition, data are available from three one-month measurement campaigns in Munich between 2017 and 2019, each using five to six spectrometers [5].
Our unique network structure and very large and continuous data set (>4.5 million data points measured on more than 500 days) capturing the urban-rural gradient serves as a very powerful tool to validate not only absolute values measured by GHG satellites but also concentration gradients. Since April 2020, OCO-2 has targeted Munich in target mode and OCO-3 in snapshot area mapping (SAM) mode 11 and 25 times, respectively. We show the first results of the concentration gradient validation as well as a Bayesian inversion framework [6] to quantify urban CH4 emissions.

Poster: Poster_Dietrich_0_163_25.pdf 

Presentation Type: Poster

Session: 4.2c Observations to quantify hot spots and local/urban emissions

Session Date: Thursday (6/17) 10:00 AM