EGU2020-19237
https://doi.org/10.5194/egusphere-egu2020-19237
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Greenhouse Gas Emission Estimate Using a Fully-automated Permanent Sensor Network in Munich

Florian Dietrich, Jia Chen, Benno Voggenreiter, and Xinxu Zhao
Florian Dietrich et al.
  • Technical University of Munich, Department of Electrical and Computer Engineering, Environmental Sensing and Modeling, Munich, Germany (flo.dietrich@tum.de)

To effectively mitigate climate change, it is indispensable to know the locations of the emission sources and their respective emission strength. As the majority of greenhouse gases (GHG) such as carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO) are generated in cities, our focus lies in the emission determination of urban areas. For this reason, we established a fully-automated sensor network in Munich, Germany to permanently measure GHGs.

Our permanent network is based on the differential column measurement principle [1] and measures the city emissions using five FTIR spectrometer systems (EM27/SUN from Bruker [2]). For these spectrometers we built a self-developed enclosure system and equipped them with several sensors (e.g. computer vision based solar radiation sensor) to measure the column-averaged concentrations of CO2, CH4 and CO in a fully-automated way. The difference between the column amounts inside and outside of the city reflects the pollutants abundance generated in the city. Four stations are placed at the city outskirts to capture the inflow/outflow column amounts in arbitrary wind conditions. One inner-city station, which has already been operating successfully since 2016 [3], is serving as a permanent downwind site for half of the city.

With the help of atmospheric transport models, combined with a Bayesian inverse modelling approach, those concentration differences are transferred into spatially resolved emission estimates of the city. After testing the network in two campaigns (2017 and 2018), the network is finally long-term operating since summer 2019 and continuously measures the GHG concentrations in Munich. We will show both the hardware achievements and first measurement and emission results after ten month of operation.

[1] Chen et al.: Differential column measurements using compact solar-tracking spectrometers. Atmos. Chem. Phys., 16: 8479–8498, 2016.

[2] Gisi et al.: XCO2-measurements with a tabletop FTS using solar absorption spectroscopy, Atmos. Meas. Tech., 5, 2969-2980, 2012

[3] Heinle and Chen: Automated Enclosure and Protection System for Compact Solar-Tracking Spectrometers, Atmos. Meas. Tech., 11, 2173-2185, 2018

How to cite: Dietrich, F., Chen, J., Voggenreiter, B., and Zhao, X.: Greenhouse Gas Emission Estimate Using a Fully-automated Permanent Sensor Network in Munich, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19237, https://doi.org/10.5194/egusphere-egu2020-19237, 2020

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Presentation version 2 – uploaded on 07 May 2020 , no comments
Adding more information about the inverse modeling framework and additional results.
Presentation version 1 – uploaded on 04 May 2020 , no comments