Professorship of Environmental Sensing and Modeling TUM Department

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Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Analysis for Total Column CO 2 and CH 4 in Berlin using WRF-GHG combined with Differential Column Methodology (DCM) Xinxu Zhao (1), Julia Marschall (2), Stephan Hachinger (3), Christoph Gerbig (2), Jia Chen (1) Professorship of Environmental Sensing and Modeling, Department of Electrical and Computer Engineering, Technische Universität München (TUM), Munich, Germany (2) Max Planck Institute for Biogeochemistry, Department of Biogeochemical Systems, Jena, Germany (3) Leibniz Supercomputing Center (Leibniz-Rechenzentrum, LRZ) of Bavarian Academy of Sciences and Humanities, Garching, Germany Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 1

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Questions of the study: 1. How good is the performance of the WRF-GHG model in general? Ø Comparing model to case study in Berlin (cf. Hase et al, 2015) 2. Is it beneficial to use the differential column methodology (DCM) for the model analysis? Ø Comparing standard approach with DCM approach Ø Helping to understand the model results (e. g. , features of tracer emissions) Ø Cancel out the bias… Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 2

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich WRF-GHG Model: • High resolution; • Meteorological fields • Concentration estimates from different emission processes • etc. . From: WRF-GHG Technical Report Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 3

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich WRF-GHG Model: Model Domain: • 3 domains • Spatial resolutions: 9 km, 3 km & 1 km d 01 Berlin • 26 Vertical layers, up to 50 h. Pa External Data Sources: 1. VPRM tracer: MODIS satellite estimates 2. Anthropogenic tracer: EDGAR V. 4. 1 3. Meteorological fields: GFS 4. The initial and boundary conditions for concentration fields: CAMS Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 4

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Measurement Information: Heili Lind Tegel Char Tempelhof Mahls Licht Schönefeld Ø Measuring CO 2 and CH 4 concentrations Ø Ground-based remote sensing (EM 27/SUN) Ø Performed in July 2014 in Berlin (Hase et al, 2015) Hase, F. et al. Application of portable FTIR spectrometers for detecting greenhouse gas emissions Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germanyof the major city Berlin. Atmos. Chem. Phys. , 16, 10. 5194/amt-8 -3059 -2015, 2015. 5

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Evaluation of the WRF-GHG model: • Comparison of Wind Fields ( Wind Speeds & Wind Directions) Wind Speeds & Wind Directions at 10 m • Comparison of Concentration Fields Pressure weighted average CO 2 & CH 4 • Tracer Analysis CO 2: Anthropogenic emissions & Biogenic activities CH 4: Anthropogenic emissions & Soil uptake process Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 6

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Comparison of modeled and observed wind (at 10 m): Modeled wind speed is overlapping well with measurements Measured wind directions show larger variability than modeled wind directions Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 7

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Comparison of modeled and observed XCO 2 and XCH 4 XCO 2 [ppm] XCH 4 [ppb] 2. 7% bias (+50 ppb) Modeled XCO 2 fits well with measurements Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany Modeled XCH 4 is overestimated compared with measurements (DCM will help) 8

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich CO 2: Influence of anthropogenic and biogenic activities XCO 2 : • Biogenic activities are dominating • Anthropogenic influence is weak (see, however, DCM analysis) Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 9

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich CH 4: Influence of humane activities and soil uptake process XCH 4 : • Anthropogenic activities are dominating • Soil uptake process has almost no influence Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 10

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Differential Column Methodology (DCM): DCM is calculating differences between upwind and downwind sites • to cancel out the bias of XCH 4 • to highlight the influence of CO 2 anthropogenic activities DCM is applied using this equation : Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany Chen, J. et al. Differential column measurements using compact solar-tracking spectrometers, Atmos. Chem. Phys. , 16, 8479 -8498, doi: 10. 5194/acp-16 -8479 -2016, 2016 11

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich DCM result for CO 2: Wind directions and speeds are homogenous between upwind and downwind sites Human activities are dominating the variations of ∆XCO 2 within urban areas Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 12

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich DCM result for CH 4: Simulated ∆XCH 4 shows better agreement with measurements compared to the standard approach Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 13

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Conclusion and Outlook Ø WRF-GHG is a suitable tool for GHG transport analysis in urban areas (more cases, e. g. , Munich, Hamburg) Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 14

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Permanent Column Sensor Network Garching r = 20 km Markt Schwaben TUM Weßling Höhenkirchen Prevailing wind direction Worldwide first permanent fully-automated column network for CO 2, CH 4, CO, NO 2, O 3. Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 15

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Conclusion and Outlook Ø WRF-GHG is a suitable tool for GHG transport analysis in urban areas (more cases, e. g. , Munich, Hamburg) Ø Differential Column Methodology (DCM) can be an effective method to cancel out the bias caused, e. g. , from initialization conditions and highlight the regional emission sources Ø The WRF-GHG mesoscale simulation framework can be combined with microscale atmospheric transport models (CFD) for simulating crucial details of emission transport patterns Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 16

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical

Professorship of Environmental Sensing and Modeling TUM Department of Electrical and Computer Engineering Technical University of Munich Thank you for your attention! Zhao et al. | May 7 th, 2019 | WRF Workshp| Munich, Germany 17