This cumulative dissertation investigates the potential of radiocarbon (14C)-based and carbon
monoxide (∆CO)-based fossil fuel CO2 (∆ffCO2) estimates from the urban observation site
Heidelberg to deduce the seasonal cycle of the ffCO2 emissions in the Rhine Valley. For
this, the CarboScope inversion system is used to investigate the benefit of few but accurate
14C-based ∆ffCO2 estimates from about 100 hourly flask samples collected in 2019 and 2020,
compared to a continuous ∆CO-based ∆ffCO2 record with about 4 times larger uncertainty.
The urban observation site with large ffCO2 point sources in the vicinity places special
demands on the transport model. Therefore, a method is developed for the high-resolution
Weather Research and Forecasting - Stochastic Time-Inverted Lagrangian Transport model
(WRF-STILT) to represent the effective emission heights of point sources. This work shows
that the 14C-based ∆ffCO2 observations contain the seasonal cycle of the ffCO2 emissions,
but do not lead to robust inversion results. In contrast, the continuous ∆CO-based ∆ffCO2
estimates provide robust and data-driven seasonal cycles that show the distinct COVID-19
signal in 2020 and are suitable for validating the amplitude and phasing of the seasonal cycle
of the emission inventories in the main footprint of Heidelberg
