Potential of14C-based vs. ∆CO-based ∆ffCO2 observations to estimate urban fossil fuel CO2 (ffCO2) emissions

Abstract

Atmospheric transport inversions are a powerful tool for independently estimating surface CO2 fluxes from atmospheric CO2 concentration measurements. However, additional tracers are needed to separate the fossil fuel CO2 (ffCO2) emissions from non-fossil CO2 fluxes. In this study, we focus on radiocarbon (14C), the most direct tracer of ffCO2, and the continuously measured surrogate tracer carbon monoxide (CO), which is co-emitted with ffCO2 during incomplete combustion. In the companion paper by Maier et al. (2024), we determined discrete14C-based and continuous ∆CO-based estimates of the ffCO2 excess concentration (∆ffCO2) compared with a clean-air reference for the urban Heidelberg observation site in southwestern Germany. The ∆CO-based ∆ffCO2 concentration was calculated by dividing the continuously measured ∆CO excess concentration by an average14C-based∆CO/∆ffCO2 ratio. Here, we use the CarboScope inversion framework adapted for the urban domain around Heidelberg to assess the potential of both types of ∆ffCO2 observations to investigate ffCO2 emissions and their seasonal cycle. We find that, although they are more precise,14C-based ∆ffCO2 observations from almost 100 afternoon flask samples collected in the 2 years of 2019 and 2020 are not well suited for estimating robust ffCO2 emissions in the main footprint of this urban area, which has a very heterogeneous distribution of sources including several point sources. The benefit of the continuous ∆CO-based ∆ffCO2 estimates is that they can be averaged to reduce the impact of individual hours with an inadequate model performance. We show that the weekly averaged ∆CO-based ∆ffCO2 observations allow for a robust reconstruction of the seasonal cycle of the area source ffCO2 emissions from temporally flat a priori emissions. In particular, the distinct COVID-19 signal – with a steep drop in emissions in spring 2020 – is clearly present in these data-driven a posteriori results. Moreover, our top-down results show a shift in the seasonality of the area source ffCO2 emissions around Heidelberg in 2019 compared with the bottom-up estimates from the Netherlands Organization for Applied Scientific Research (TNO). This highlights the huge potential of ∆CO-based ∆ffCO2 to validate bottom-up ffCO2 emissions at urban stations if the ∆CO/∆ffCO2 ratios can be determined without biases.