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Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model

Zhao, Xinxu and Chen, Jia and Marshall, Julia and Gałkowski​​​​​​​, Michal and Hachinger, Stephan and Dietrich, Florian and Shekhar, Ankit and Gensheimer, Johannes and Wenzel, Adrian and Gerbig, Christoph (2023) Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model. Atmospheric Chemistry and Physics (ACP), 23 (22), pp. 14325-14347. Copernicus Publications. doi: 10.5194/acp-23-14325-2023. ISSN 1680-7316.

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Official URL: https://dx.doi.org/10.5194/acp-23-14325-2023

Abstract

To address ambitious goals of carbon neutrality set at national and city scales, a number of atmospheric networks have been deployed to monitor greenhouse gas (GHG) concentrations in and around cities. To convert these measurements into estimates of emissions from cities, atmospheric models are used to simulate the transport of various trace gases and help interpret these measurements. We set up a modelling framework using the Weather Research and Forecasting (WRF) model applied at a high spatial resolution (up to 400 m) to simulate the atmospheric transport of GHGs and attempt a preliminary interpretation of the observations provided by the Munich Urban Carbon Column Network (MUCCnet). Building on previous analyses using similar measurements performed within a campaign for the city of Berlin and its surroundings (Zhao et al., 2019), our modelling framework has been improved regarding the initialization of tagged tracers, model settings, and input data. To assess the model performance, we validate the modelled output against two local weather stations and two radiosonde observations, as well as observed column GHG concentrations. The measurements were provided by the measurement campaign that was carried out from 1 to 30 August 2018. The modelled wind matches well with the measurements from the weather stations, with wind speeds slightly overestimated. In general, the model is able to reproduce the measured slant column concentrations of CH4 and their variability, while for CO2, a difference in the slant column CO2 of around 3.7 ppm is found in the model. This can be attributed to the initial and lateral boundary conditions used for the background tracer. Additional mismatches in the diurnal cycle could be explained by an underestimation of nocturnal respiration in the modelled CO2 biogenic fluxes. The differential column method (DCM) has been applied to cancel out the influence from the background concentrations. We optimize its application by selecting suitable days on which the assumption of the DCM holds true: a relatively uniform air mass travels over the city, passing from an upwind site to a downwind site. In particular, the Stochastic Time-Inverted Lagrangian Transport (STILT) model is used here and driven by our WRF-modelled meteorological fields to obtain footprints (i.e. the potential areas of influence for signals observed at measurement stations), further used for interpreting measurement results. Combining these footprints with local knowledge of emission sources, we find evidence of CH4 sources near Munich that are missing or underestimated in the emission inventory used. This demonstrates the potential of this data-model framework to constrain local sources and improve emission inventories.

Item URL in elib:https://elib.dlr.de/200022/
Document Type:Article
Title:Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Zhao, XinxuTU München, München, Germanyhttps://orcid.org/0000-0002-2251-3451UNSPECIFIED
Chen, JiaTU München, München, Germanyhttps://orcid.org/0000-0002-6350-6610UNSPECIFIED
Marshall, JuliaDLR, IPAhttps://orcid.org/0000-0003-2648-128XUNSPECIFIED
Gałkowski​​​​​​​, MichalAGH University, Kraków, Polandhttps://orcid.org/0000-0003-1681-3965UNSPECIFIED
Hachinger, StephanLRZ Garching, GermanyUNSPECIFIEDUNSPECIFIED
Dietrich, FlorianTU München, München, Germanyhttps://orcid.org/0000-0002-3069-9946UNSPECIFIED
Shekhar, AnkitETH Zürich, Zürich, CHhttps://orcid.org/0000-0003-0802-2821UNSPECIFIED
Gensheimer, JohannesTU München, München, Germanyhttps://orcid.org/0000-0002-8422-4508UNSPECIFIED
Wenzel, AdrianTU München, München, Germanyhttps://orcid.org/0000-0001-6016-6174UNSPECIFIED
Gerbig, ChristophMPI für Chemie, Jena, Germany​​​​​​​https://orcid.org/0000-0002-1112-8603UNSPECIFIED
Date:20 November 2023
Journal or Publication Title:Atmospheric Chemistry and Physics (ACP)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:23
DOI:10.5194/acp-23-14325-2023
Page Range:pp. 14325-14347
Publisher:Copernicus Publications
ISSN:1680-7316
Status:Published
Keywords:greenhouse gases, remote sensing, methane, carbon dioxide, urban monitoring
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:other
DLR - Research area:Raumfahrt
DLR - Program:R - no assignment
DLR - Research theme (Project):R - no assignment
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Atmospheric Trace Species
Deposited By: Marshall, Julia
Deposited On:29 Nov 2023 15:36
Last Modified:29 Nov 2023 15:36

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