Abstract
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. The simulated XCO2 shows quite similar trends with the measurement but with approximately 1 ppm bias, while a bias in the simulated XCH4 of around 2.7 % is found. The bias could potentially be the result of relatively high background concentrations, the errors at the tropopause height, etc. We find that an analysis using differential column methodology (DCM) works well for the XCH4 comparison, as corresponding background biases are then canceled out. From the tracer analysis, we find that the enhancement of XCH4 is highly dependent on human activities. The XCO2 enhancement 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 major sources of GHG emissions in urban areas.
Highlights
The share of greenhouse gas (GHG) emissions released from urban areas has continued to increase as a result of urbanization (IEA, 2008; Kennedy et al, 2009; Parshall et al, 2010; IPCC, 2014)
We find that an analysis using differential column methodology (DCM) works well for the XCH4 comparison, as corresponding background biases are canceled out
In accordance with the geographical characteristics of the district and potential emission sources in Berlin, we focus on understanding the major emissions caused by vegetation photosynthesis and respiration (XCO2,VPRM) as well as anthropogenic activities (XCO2,anthro) for CO2 and by soil uptake (XCH4,soil) as well as human activities (XCH4,anthro) for CH4
Summary
The share of greenhouse gas (GHG) emissions released from urban areas has continued to increase as a result of urbanization (IEA, 2008; Kennedy et al, 2009; Parshall et al, 2010; IPCC, 2014). Our focus is on a highresolution (1 km) study of both CO2 and CH4 in Berlin and assessing the performance of WRF-GHG through comparing the simulated wind and concentration fields to observations from wind stations and ground-based solar-viewing spectrometers. The major goals of our work in this context are (1) to simulate high-resolution (1 km) CO2 and CH4 concentrations for Berlin using WRF-GHG, attributing the changes in concentrations to different emission processes, (2) to compare the simulation outputs with the observations from a column measurement network in Berlin (Hase et al, 2015), assessing the precision of WRF-GHG, and (3) to use DCM in the simulation analysis, testing the feasibly of this approach.
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