MUCCnet - Munich Urban Carbon Column network
Column Greenhouse Gas Concentrations
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What do the concentration timeseries above tell us about actual GHG-emissions?
- GHG = Green House Gas
- Concentration = the ratio between the number of molecules of gas x in the air column to the total number of gas molecules in the air column
- Emission = how many gas particles of x are produced per time and per ground area
We are only measuring the concentration in the air column above our sensors. Therefore we need to answer the question “Where did these particles come from?”
Sensor footprints – short “footprints” – are telling us about the context of these concentrations. A large emission source next to a sensor increases the detected concentration way more than an emission source located far away. Which emitters affect the sensor value by how much is summarized by a footprint. This is determined by the wind direction which implies the transport direction of gas particles.
Footprints do not specifically list certain emitters, but rather contain an “area which influences the sensor value”. The map below includes footprints for the MUCCNET stations on June 2nd 2020.
You can select the same day in the concentration plot above.
In the morning the yellow station (WEST) detects the highest concentration. The footprint tells us that the reason for that is the wind coming from the east. Once the wind shifts to north, the WEST-sensor-value evens out.
In addition to the measured concentrations and the three-dimensional wind field, the model used requires initial emission estimates for each individual emission cell. For this purpose, we use a so-called emission inventory (here: TNO-GHGco), as shown in the figure below.
Through calculations, such inventories roughly determine the emissions of individual cells based on parameters such as settlement and traffic density, number and size of industrial emitters, agriculture, etc. We use these values shown in the map as initial values for our model and correct each individual cell using our globally unique dataset of measured greenhouse gas concentrations.
In contrast to the calculated values of an emission inventory, only real measurements can detect previously unknown emission sources and can correct wrongly quantified emission sources. Thus, we make an essential contribution to determine the actual urban emission values with high spatial and temporal resolution.