Different carbon dioxide (CO

A profound understanding of the carbon cycle requires closing the atmospheric
CO

Regression-based determination of source signature using a Keeling
plot. For clarity of illustration, we only draw three data points instead of
five, which we use for our computation.

A possibility to distinguish between different
CO

In the last decade, new optical instrumentation has been developed,
simplifying continuous isotopologue measurements. This has led to an
increasing deployment of these instruments, thereby increasing the temporal
and spatial resolution of

Many studies have successfully used the Keeling or Miller–Tans plot method
(

In this study, we discuss the possible pitfalls of CO

For a continuous long-term dataset, we suggest an automatic routine to
determine the mean isotopic signature of the source mix. It is similar to the
moving Keeling plot for CH

In order to prevent pitfalls in the regression-based determination of mean
isotopic signature, we set a few criteria for the moving Keeling plots to
“filter” out situations in which a Keeling plot cannot be performed. These
filter criteria are also similar in type to the ones introduced by

A prerequisite for the Keeling plot is that
the source mix and the background need to stay constant during the
investigated period (see Fig.

As mentioned before, the determination of a mean isotopic signature is not
per se possible during the day when CO

In the next section, we show that with these filter criteria – i.e., (i) error
of the Keeling plot intercept

We apply the moving Keeling plot method to a modeled CO

We apply the same filter criteria to the calculated mean source signature of
the STILT-modeled dataset

Source signature as calculated with the STILT model following
Eq. (

We have now evaluated the moving Keeling plot method and the used filter
criteria based on the model data and tested whether they allow a bias-free
retrieval of the mean source signature. In Fig.

Comparison between modeled reference source signature (blue) and the
moving Keeling plot intercept (red), which is regression-based using the
modeled CO

Figure

Note that with the criteria established in Sect.

We now apply this approach to real measured Heidelberg data. We use the
CO

Our 4-year record of the mean source signature in Heidelberg (see
Fig.

Moving Keeling plot method-based source signature in Heidelberg from
2011 until mid-2015. The black line is the smoothed measured source
signature, and the blue line gives the smoothed modeled source signature
(both 50th-percentile filter with window size

We now want to elaborate what quantitative information can be drawn from the
mean source signature record in Heidelberg about its components. For an urban
continental measurement site, we have to assume that there are at least two
main source types of CO

As noted, a quantification of the relative shares of fossil fuel and the
biospheric CO

We have noted that, in order to obtain information from

To calculate the isotopic end members of

To determine

To estimate

The uncertainty of the isotopic end members in Fig.

The derived uncertainty of

We cannot assume that the isotopic end members

Many measurement stations are currently being equipped with new optical
instruments which measure

We therefore developed filter criteria and show that the routine and accurate
determination of

By applying the moving Keeling plot method to a real dataset measured in
Heidelberg, we were able to determine the source signature over the course of
4 years. We find a distinct seasonal cycle of the mean source signature
with values of about

We showed that for the urban site of Heidelberg we can use the
observation-based mean source signature record to estimate the isotopic end
member

Finally, we could show that, even though it is not possible to determine the
isotopic end members throughout the year, it is possible to refute certain
literature values. For example, a respiration signature of

The CO

We use the STILT model

For the reference modeled mean source signature we use a “moving”
background. In particular, we chose the minimum CO

A necessary prerequisite of determining the mean source signature correctly
at a measurement site is a good quality of CO

Since April 2011, atmospheric trace gas mole fractions are measured with an
in situ Fourier transform infrared (FTIR) spectrometer at 3 min time
resolution at the Institut für Umweltphysik in Heidelberg (Germany,
49

The intermediate measurement precision of the FTIR is about 0.05 ppm for
CO

Continuous Heidelberg hourly FTIR record of

The CO

Sanam Noreen Vardag developed the moving Keeling plot method in conjunction with Ingeborg Levin. Sanam Noreen Vardag verified this approach using pseudo data from the STILT model and applied the approach to measured data. The measured data were partly taken by Samuel Hammer (until September 2011) and mainly by Sanam Noreen Vardag (September 2011 to June 2015). The final discussion and manuscript writing profited from input from all three authors.

This work has been funded by the InGOS EU project (284274) and national ICOS BMBF project (01LK1225A) funded by the German Ministry of Education and Research (contract number: 01LK1225A). We thank NOAA/ESRL and INSTAAR for making their observational data from Mace Head and Mauna Loa available on the WDCGG website. Further, we acknowledge the financial support given by Deutsche Forschungsgemeinschaft and Ruprecht-Karls-Universität Heidelberg within the funding program Open Access Publishing. Edited by: F. Joos Reviewed by: two anonymous referees