Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-1111-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-1111-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Feb 2021
Research article |
| 11 Feb 2021
| 11 Feb 2021
MUCCnet: Munich Urban Carbon Column network
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Benno Voggenreiter
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Patrick Aigner
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Nico Nachtigall
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Björn Reger
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
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30 citations as recorded by crossref.
- An Interpolation Method to Reduce the Computational Time in the Stochastic Lagrangian Particle Dispersion Modeling of Spatially Dense XCO2 Retrievals D. Roten et al. 10.1029/2020EA001343
- Experimental Estimates of Integral Anthropogenic CO2 Emissions in the City of St. Petersburg Y. Timofeyev et al. 10.1134/S0001433822030100
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- Retrievals of XCO2, XCH4 and XCO from portable, near-infrared Fourier transform spectrometer solar observations in Antarctica D. Pollard et al. 10.5194/essd-14-5427-2022
- Assessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion framework T. Jones et al. 10.5194/acp-21-13131-2021
- Low-cost urban carbon monitoring network and implications for china: a comprehensive review H. Jiang et al. 10.1007/s11356-023-29836-4
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- What Are the Different Measures of Mobility Telling Us About Surface Transportation CO2 Emissions During the COVID‐19 Pandemic? J. Gensheimer et al. 10.1029/2021JD034664
- Recovery of sparse urban greenhouse gas emissions B. Zanger et al. 10.5194/gmd-15-7533-2022
- Investigation of spaceborne trace gas products over St Petersburg and Yekaterinburg, Russia, by using COllaborative Column Carbon Observing Network (COCCON) observations C. Alberti et al. 10.5194/amt-15-2199-2022
- Tall tower eddy covariance measurements of CO2 fluxes in Vienna, Austria B. Matthews & H. Schume 10.1016/j.atmosenv.2022.118941
- Improved calibration procedures for the EM27/SUN spectrometers of the COllaborative Carbon Column Observing Network (COCCON) C. Alberti et al. 10.5194/amt-15-2433-2022
- Pyra: Automated EM27/SUN Greenhouse Gas Measurement Software P. Aigner et al. 10.21105/joss.05131
- Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model X. Zhao et al. 10.5194/acp-23-14325-2023
- Quantification of CH<sub>4</sub> emissions from waste disposal sites near the city of Madrid using ground- and space-based observations of COCCON, TROPOMI and IASI Q. Tu et al. 10.5194/acp-22-295-2022
- A portable reflected-sunlight spectrometer for CO2 and CH4 B. Löw et al. 10.5194/amt-16-5125-2023
- Versatile and Targeted Validation of Space-Borne XCO2, XCH4 and XCO Observations by Mobile Ground-Based Direct-Sun Spectrometers A. Butz et al. 10.3389/frsen.2021.775805
- Impact of Workplace on the Risk of Severe COVID-19 T. Nakamura et al. 10.3389/fpubh.2021.731239
- Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network A. Luther et al. 10.5194/acp-22-5859-2022
- Mapping the spatial distribution of NO<sub>2</sub> with in situ and remote sensing instruments during the Munich NO<sub>2</sub> imaging campaign G. Kuhlmann et al. 10.5194/amt-15-1609-2022
- Using a portable FTIR spectrometer to evaluate the consistency of Total Carbon Column Observing Network (TCCON) measurements on a global scale: the Collaborative Carbon Column Observing Network (COCCON) travel standard B. Herkommer et al. 10.5194/amt-17-3467-2024
- Greenhouse gas column observations from a portable spectrometer in Uganda N. Humpage et al. 10.5194/amt-17-5679-2024
- Regional disparities, dynamic evolution, and spatial spillover effects of urban-rural carbon emission inequality in China J. Wei et al. 10.3389/fevo.2024.1309500
- Quantification of methane emissions in Hamburg using a network of FTIR spectrometers and an inverse modeling approach A. Forstmaier et al. 10.5194/acp-23-6897-2023
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- Secondary PM<sub>2.5</sub> decreases significantly less than NO<sub>2</sub> emission reductions during COVID lockdown in Germany V. Balamurugan et al. 10.5194/acp-22-7105-2022
Latest update: 13 Dec 2024
Short summary
Climate change is one of the defining issues of our time. However, most of the current emission estimates are based on calculations, not on actual measurements as it is difficult to quantify the emissions of large sources such as cities. This study shows how to use the relatively new approach of column measurements to quantify urban greenhouse gas emissions in an exact way using only a few compact measurement systems. The approach can be used to evaluate the effectiveness of mitigation policies.
Climate change is one of the defining issues of our time. However, most of the current emission...
