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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 16 Jan 2019

Research article | 16 Jan 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Analysis of Total Column CO2 and CH4 Measurements in Berlin with WRF-GHG

Xinxu Zhao1, Julia Marshall2, Stephan Hachinger3, Christoph Gerbig2, and Jia Chen1 Xinxu Zhao et al.
  • 1Electrical and Computer Engineering, Technische Unversität München, 80333 Munich, Germany
  • 2Max Plank Institute of Biogeochemistry, 07745 Jena, Germany
  • 3Leibniz Supercomputering Center (Leibniz-Rechenzenturm, LRZ) of Bavarian Academy of Sciences and Humanities, Bolzmannstr. 1, 85748 Garching, Germany

Abstract. Though they cover less than 3 % of the global land area, urban areas are responsible for over 70 % of the global greenhouse gas (GHG) emissions and contain 55 % of the global population. A quantitative tracking of GHG emissions in urban areas is therefore of great importance, with the aim of accurately assessing the amount of emissions and identifying the emission sources. The Weather Research and Forecasting model (WRF) coupled with GHG modules (WRF-GHG) developed for mesoscale atmospheric GHG transport, can predict column-averaged abundances of CO2 and CH4 (XCO2 and XCH4). In this study, we use WRF-GHG to model the Berlin area at a high spatial resolution of 1 km. The simulated wind and concentration fields were compared with the measurements from a campaign performed around Berlin in 2014 (Hase et al., 2015). The measured and simulated wind fields mostly demonstrate good agreement and the simulated XCO2 agrees well with the measurement. In contrast, a bias in the simulated XCH4 of around 2.7 % is found, caused by relatively high initialization values for the background concentration field. We find that an analysis using differential column methodology (DCM) works well for the XCH4 comparison, as corresponding background biases then cancel out. From the tracer analysis, we find that the enhancement of XCH4 is highly dependent on human activities. The XCO2 signal in the vicinity of Berlin is dominated by anthropogenic behavior rather than biogenic activities. We conclude that DCM is an effective method for comparing models to observations independently of biases caused, e.g., by initial conditions. It allows us to use our high resolution WRF-GHG model to detect and understand sources of GHG emissions quantitatively in urban areas.

Xinxu Zhao et al.
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Status: open (until 13 Mar 2019)
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Xinxu Zhao et al.
Xinxu Zhao et al.
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Short summary
Based on the case study for Berlin, WRF-GHG is concluded to be a suitable basis for precise GHG transport analysis in urban areas, especially when combined with Differential Column Methodology (DCM). DCM is not only useful for the direct evaluation of measurements but also helps us to understand the results of tracer transport models, cancelling out the bias caused, e.g., by initialization conditions, and highlighting regional emission sources.
Based on the case study for Berlin, WRF-GHG is concluded to be a suitable basis for precise GHG...