Articles | Volume 19, issue 17
https://doi.org/10.5194/acp-19-11279-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-11279-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Sep 2019
Research article |
| 06 Sep 2019
| 06 Sep 2019
Analysis of total column CO2 and CH4 measurements in Berlin with WRF-GHG
Xinxu Zhao
Department of Electrical and Computer Engineering, Technische Unversität München, Arcisstr. 21, 80333 Munich, Germany
Department of Biogeochemical Systems, Max Planck Institute of Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
Stephan Hachinger
Leibniz Supercomputing Centre (Leibniz-Rechenzenturm – LRZ), Bavarian Academy of Sciences and Humanities, Bolzmannstr. 1, 85748 Garching, Germany
Christoph Gerbig
Department of Biogeochemical Systems, Max Planck Institute of Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
Matthias Frey
Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76021 Karlsruhe,
Germany
Frank Hase
Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76021 Karlsruhe,
Germany
Department of Electrical and Computer Engineering, Technische Unversität München, Arcisstr. 21, 80333 Munich, Germany
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- Effect of atmospheric conditions and VPRM parameters on high-resolution regional CO2 simulations over East Asia M. Seo et al. 10.1007/s00704-023-04663-2
- The Analysis of OCO-2 Satellite Measurements of CO2 in the Vicinity of Russian Cities A. Nikitenko et al. 10.1134/S1024856020060111
- Improving urban CO2 spatial distribution modelling using multi-source data E. Sun et al. 10.1016/j.uclim.2024.101902
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- Lagrangian inversion of anthropogenic CO2 emissions from Beijing using differential column measurements K. Che et al. 10.1088/1748-9326/ac7477
28 citations as recorded by crossref.
- Determination of the emission rates of CO<sub>2</sub> point sources with airborne lidar S. Wolff et al. 10.5194/amt-14-2717-2021
- Comparison of CO2 Content in the Atmosphere of St. Petersburg According to Numerical Modeling and Observations G. Nerobelov et al. 10.1134/S0001433823020056
- MUCCnet: Munich Urban Carbon Column network F. Dietrich et al. 10.5194/amt-14-1111-2021
- Towards Robust Calculation of Interannual CO2 Growth Signal from TCCON (Total Carbon Column Observing Network) L. Labzovskii et al. 10.3390/rs13193868
- Tall tower eddy covariance measurements of CO2 fluxes in Vienna, Austria B. Matthews & H. Schume 10.1016/j.atmosenv.2022.118941
- Dairy Methane Emissions in California's San Joaquin Valley Inferred With Ground‐Based Remote Sensing Observations in the Summer and Winter S. Heerah et al. 10.1029/2021JD034785
- 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
- Complex Validation of Weather Research and Forecasting—Chemistry Modelling of Atmospheric CO2 in the Coastal Cities of the Gulf of Finland G. Nerobelov et al. 10.3390/rs15245757
- Validation of WRF-Chem Model and CAMS Performance in Estimating Near-Surface Atmospheric CO2 Mixing Ratio in the Area of Saint Petersburg (Russia) G. Nerobelov et al. 10.3390/atmos12030387
- Emission Monitoring Mobile Experiment (EMME): an overview and first results of the St. Petersburg megacity campaign 2019 M. Makarova et al. 10.5194/amt-14-1047-2021
- Analysis of CO<sub>2</sub>, CH<sub>4</sub>, and CO surface and column concentrations observed at Réunion Island by assessing WRF-Chem simulations S. Callewaert et al. 10.5194/acp-22-7763-2022
- Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data A. Vara-Vela et al. 10.5194/gmd-16-6413-2023
- 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
- Study of mid-latitude retrieval XCO2 greenhouse gas: Validation of satellite-based shortwave infrared spectroscopy with ground-based TCCON observations S. Karbasi et al. 10.1016/j.scitotenv.2022.155513
- Where to place methane monitoring sites in China to better assist carbon management X. Zhang et al. 10.1038/s41612-023-00359-6
- Using Multiscale Ethane/Methane Observations to Attribute Coal Mine Vent Emissions in the San Juan Basin From 2013 to 2021 A. Meyer et al. 10.1029/2022JD037092
- Experimental Estimates of Integral Anthropogenic CO2 Emissions in the City of St. Petersburg Y. Timofeyev et al. 10.1134/S0001433822030100
- Effect of atmospheric conditions and VPRM parameters on high-resolution regional CO2 simulations over East Asia M. Seo et al. 10.1007/s00704-023-04663-2
- The Analysis of OCO-2 Satellite Measurements of CO2 in the Vicinity of Russian Cities A. Nikitenko et al. 10.1134/S1024856020060111
- Improving urban CO2 spatial distribution modelling using multi-source data E. Sun et al. 10.1016/j.uclim.2024.101902
- Evaluation of simulated CO2 power plant plumes from six high-resolution atmospheric transport models D. Brunner et al. 10.5194/acp-23-2699-2023
- Anthropogenic CO2 emission estimates in the Tokyo metropolitan area from ground-based CO2 column observations H. Ohyama et al. 10.5194/acp-23-15097-2023
- Machine Learning to Predict Area Fugitive Emission Fluxes of GHGs from Open-Pit Mines S. Kia et al. 10.3390/atmos13020210
- Climate Impact Comparison of Electric and Gas‐Powered End‐User Appliances F. Dietrich et al. 10.1029/2022EF002877
- Quantification of Central and Eastern China's atmospheric CH4 enhancement changes and its contributions based on machine learning approach X. Ai et al. 10.1016/j.jes.2023.03.010
- Diurnal and Seasonal Variation of Area-Fugitive Methane Advective Flux from an Open-Pit Mining Facility in Northern Canada Using WRF M. Nambiar et al. 10.3390/atmos11111227
- Assessment of Urban CO2 Measurement and Source Attribution in Munich Based on TDLAS-WMS and Trajectory Analysis L. Lan et al. 10.3390/atmos11010058
- Lagrangian inversion of anthropogenic CO2 emissions from Beijing using differential column measurements K. Che et al. 10.1088/1748-9326/ac7477
Latest update: 18 Apr 2024
Short summary
The Weather Research and Forecasting model (WRF), coupled with greenhouse gas (GHG) modules (WRF-GHG), is considered to be a suitable basis for precise GHG transport analysis in urban areas, especially when combined with differential column methodology (DCM). DCM is an effective method not only for comparing models to observations independently of biases caused, for example, by initial conditions, but also for detecting and understanding sources of GHG emissions quantitatively in urban areas.
The Weather Research and Forecasting model (WRF), coupled with greenhouse gas (GHG) modules...
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