| 11 May 2026
Isotope-based investigation of methane sources in Hamburg, Germany
Abstract. Methane (CH4) is the second most important anthropogenic greenhouse gas and reducing CH4 emissions can lead to climate benefits on the timescale of a decade. Knowledge of the most important sources in different regions is important for designing and implementing successful mitigation strategies. We present a detailed investigation into the source mix of CH4 emissions in Hamburg, Germany, using measurements of the CH4 mole fraction and isotopic composition by combining data from multiple observational campaigns and an atmospheric transport model. Measurements of CH4 isotopic composition were performed for eight months using isotope-ratio mass spectrometry (IRMS) at the Geomatikum building in the city centre, 82 m above ground level. The isotopic composition clearly demonstrates that the observed CH4 enhancements originated mainly from microbial sources. Supporting meteorological and hydrological data provide context for explaining the temporal CH4 variability. The highest observed CH4 enhancements are sharp peaks from microbial sources that occur only during low tides and when air is advected from the south, where the Elbe River and the Hamburg harbour are located. Measurements with a mobile analyser along the river confirm that large emissions occur from the banks of the Elbe River during low tides. Our integrated approach demonstrates the benefit of combining detailed measurements (isotopes and mobile) and high-resolution modelling for accurately attributing greenhouse gas sources in complex environments.
General Comments
This is a very interesting manuscript on the topical subject of methane emissions. It is well-written throughout, although I have many small requests for increased clarity in the detailed comments. The topic of the tidal emissions is very important and I wonder if the tidal range during the spikes could be explored more as during the autumn period when many of these events were identified there could be much lower water events and far more mud flat exposed.
The discussion is very Hamburg centric and there isn’t much comparative evidence from rivers beyond the Elbe. I think that the discussion could be strengthened with information about other locations where this tidal emissions phenomenon has been observed, to give a global perspective on this emissions inventory omission.
One thing that did annoy me slightly, and it just needs a little more clarity, is the frequent mention that the emissions only occur when the sediments are exposed, while at the same time saying frequently that they only occur when the river level is below 600cm. What is the 600cm? Is this the depth at the centre of the river? This is why it is important to include the tidal range relative to an average river water depth, which I presume is significantly greater than 600cm. For example, is it 700 ± 100cm when there is a small tidal range and 700 ±200cm when there is a large tidal range?
Detailed Comments
Introduction
Line 27 – in situ implies that the instrument is stationary. You need a bit more clarity between instruments that are mobile such as the Picarro G2210i and IRMS that are moved between different fixed sites.
Methods
Line 63 - ‘At a height of 83 m’ would be better.
Line 73 – Using ‘we’ may be appropriate in many contexts, but I don’t think it is for remote automated measurements.
Line 76 – Inlet is attached to the 70 m balcony. This is 13 m below the top of the building. Is the inlet here or at the top? Earlier you say that wind flow is not obstructed by buildings. Where are the meteorological sensors situated?
Line 85 – The 10 ppb mole fraction reproducibility is based on the IRMS peak. Is this taken into account in the modelling errors? Have you compared this with averaging of 1Hz mole fraction measurements of CH4 at the time of inlet sampling?
Figure 1 - Would be helpful to know what type of farms these are as only some types are going to be significant contributors of CH4. What is the difference between greenery and forest? Do you mean grassland?
Line 102 - When you are measuring in a tidal setting and also talking about high buildings, I wouldn’t use elevated for higher concentrations as it could be confused with height.
Line 106 – Did you use the same inlet line and height for the Picarro as for the IRMS previously in 2021?
Line 113 – For citations be consistent as per journal requirements, either alphabetical or chronological.
Lines 114-117 – Is it just a wind station or a weather station. Previously you say that the inlet is at 70 m and here you say that the weather station is at 80 m, but only 1.3 m from the air inlet. I presume there is less turbulence near the top of the building as in your discussion of location on the highest building in the area.
Line 128 – What is the minimum length for diurnal peaks? It is the inversion height that rises and lowers and the peak height responds to that, so the peaks in the summer months may be less than 8 hours duration, which could be less than your maximum for spikes.
Line 132 - Keeling and Pataki both did Keeling plots for CO2 measurements and Rockmann et al. were not the first use this method for CH4. This was used back into the 1990s.
Line 145 - Keeling plot intercepts are not always the same during the rise and fall of a peak due to atmospheric dynamics of diurnal inversion development and break-up. Are you using the whole of the diurnal peak to generate the plots or just the rise?
Line 147 – I would re-emphasise here that you are using the CH4 mole fraction estimate from the IRMS peaks with a precision of ±10 ppb, as this will contribute to your reliability cut-off point.
Line 161 – Needs more clarity here as you talk about total domain emissions of 18.3 Tg/yr, more than the whole of the EU, but earlier you mention a domain of 200 km x 160 km. I presume that the emission is for the whole of the FLEXPART model area, which is much bigger than the domain area. Just needs minor restructuring of the paragraph.
Table 2 – What year does your background isotopic signature represent? It is now closer to -48‰ for mid and high northern latitudes, but you are modelling 2021 data, so this should be clarified.
Results
Lines 184-185 – A citation for this known general phenomenon would be helpful for this type of modelling.
Figures 3 and B1 = You have a pyrogenic category in the legend, but your graphs don’t cover a big enough range of isotopic space to show it. Why do the simulations show a straight line with very little deflection toward the centre of the waste domain?
Figure 3 caption – Took me a while to realise what the coloured bars are showing so maybe ned to add ‘from light (Aug 2021) to darker (Mar 2022)’
Line 210 – ‘The sharp peaks occur more frequently in autumn than in winter.’ Have you considered greater tidal range in autumn as a contributing factor - more exposed mud flats?
Line 221 – What do you mean by ‘as the emissions of waste are relatively stable.’ The isotopic signature of waste for the region could be stable even if the emissions change significantly.
Line 244 – 6 m/s is not low and from the range presented the average could be higher than the 3.2 ± 1.9 m/s in the previous paragraph.
Figure 5 – It is surprising that you have such low boundary layer height for such high wind speeds. If the sample population is the same in (d) and (f) then there must be some boundary layers of <200m for wind speeds >10 m/s. If it isn’t the same peak population then please make it clear.
Figure 6 caption – ‘when the river level was below 600 cm.’ See general comment at start. What does the 600cm relate to, because for me 6 m water depth is not going to expose any river bed.
Figure 7 caption – As you have changed instruments for the 2024 survey it is worth mentioning that the raw data is 1 Hz frequency Aeris data.
Section 3.5.2 – this is where I think that some discussion of tidal ranges would be useful, as mentioned in the general comments, as it relates to the amount of sediment exposed. Figures D1 and D2 seem to show this information for short periods of time and appear to show tidal ranges of around 4 m.
Line 315 – Location 9 is close to the agricultural area. Could run-off from the fields be influencing or enhancing CH4 emissions at this location.
Conclusions
Lines 346-347 – Do you really think that you have a distinct isotopic signature for the rivers from the agricultural sources? It is not obvious from the isotopic cross plots. If you are convinced of it I would include a short discussion section emphasising the evidence.
Supplementary Information
The Appendix D header is before Figure C3.
Figures D1 and D2. It is not obvious in the lower parts which parameter is in red and which is in blue. Why are the wind speed scales so different between the two figures?