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MUCCnet: Munich Urban Carbon Column network

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Dietrich, Florian, Chen, Jia, Voggenreiter, Benno, Aigner, Patrick, Nachtigall, Nico, Reger, Björn·2021·Atmospheric Measurement Techniques
DOI 10.5194/amt-14-1111-2021

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Abstract

In order to mitigate climate change, it is crucial to understand urban greenhouse gas (GHG) emissions precisely, as more than two-thirds of the anthropogenic GHG emissions worldwide originate from cities. Nowadays, urban emission estimates are mainly based on bottom-up calculation approaches with high uncertainties. A reliable and long-term top-down measurement approach could reduce the uncertainty of these emission inventories significantly. We present the Munich Urban Carbon Column network (MUCCnet), the world's first urban sensor network, which has been permanently measuring GHGs, based on the principle of differential column measurements (DCMs), since summer 2019. These column measurements and column concentration differences are relatively insensitive to vertical redistribution of tracer masses and surface fluxes upwind of the city, making them a favorable input for an inversion framework and, therefore, a well-suited candidate for the quantification of GHG emissions. However, setting up such a stationary sensor network requires an automated measurement principle. We developed our own fully automated enclosure systems for measuring column-averaged CO 2 , CH 4 and CO concentrations with a solar-tracking Fourier transform spectrometer (EM27/SUN) in a fully automated and long-term manner. This also includes software that starts and stops the measurements autonomously and can be used independently from the enclosure system. Furthermore, we demonstrate the novel applications of such a sensor network by presenting the measurement results of our five sensor systems that are deployed in and around Munich. These results include the seasonal cycle of CO 2 since 2015, as well as concentration gradients between sites upwind and downwind of the city. Thanks to the automation, we were also able to continue taking measurements during the COVID-19 lockdown in spring 2020. By correlating the CO 2 column concentration gradients to the traffic amount, we demonstrate that our network is capable of detecting variations in urban emissions. The measurements from our unique sensor network will be combined with an inverse modeling framework that we are currently developing in order to monitor urban GHG emissions over years, identify unknown emission sources and assess how effective the current mitigation strategies are. In summary, our achievements in automating column measurements of GHGs will allow researchers all over the world to establish this approach for long-term greenhouse gas monitoring in urban areas.

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Authors
Dietrich, F., Chen, J., Voggenreiter, B., Aigner, P., Nachtigall, N., & Reger, B.
Affiliations
Technical University of Munich (DE)
Corresponding author
  • Dietrich, Florian
  • Chen, Jia
  • Aigner, Patrick
ORCID
Venue
Atmospheric Measurement Techniques
Publisher
Copernicus GmbH
Published
2021-02-11
Volume
14
Issue
2
Pages
1111-1126
ISSN
  • 1867-1381 (ISSN-L)
  • 1867-8548
DOI
10.5194/amt-14-1111-2021
OpenAlex
W3128109717
Cited by
98
References
1
Citations by year
2026: 5 · 2025: 13 · 2024: 18 · 2023: 10 · 2022: 31 · 2021: 21
FWCI
8.30
Type
journal article
Language
en
Open access
Licence
Locations
  • Atmospheric measurement techniques (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • mediaTUM (Technical University of Munich) (submittedVersion, cc-by)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
  • mediaTUM (Technical University of Munich) (submittedVersion, other-oa)
Funders
  • Environmental Defense Fund
  • European Commission (291763)
  • Deutsche Forschungsgemeinschaft (CH 1792/2-1, 291763, INST 95/1544)
  • Technische Universität München (291763)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric and Environmental Gas Dynamics
  • Physical Sciences › Chemistry › Spectroscopy › Spectroscopy and Laser Applications
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric chemistry and aerosols
Keywords
urban greenhouse gas emissions, methane, carbon monoxide, seasonal CO2 cycle, vehicle emissions, COVID-19 lockdown, inverse modeling, Munich

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