the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Using NOx as quantitative fossil fuel CO2 proxy in urban areas: challenges and benefits
Abstract. Continuously monitoring local excess fossil fuel CO2 concentrations remains challenging due to the absence of accurate, continuous 14CO2 measurements. Continuous estimates of fossil fuel CO2 (ffCO2) are made by observing continuously measurable proxies that are co-emitted during fossil fuel combustion. This paper investigates the potential and challenges of using in situ NOx observations in urban areas to quantitatively estimate hourly ffCO2 concentration enhancements, using observations at the ICOS pilot station in Heidelberg, Germany. The short atmospheric lifetime of NOx limits the use of the observed signal to a local area. Thus, a local background for NOx and ffCO2 was approximated using the Stochastic Time-Inverted Lagrangian Transport (STILT) model and bottom-up emission estimates from the Netherlands Organisation for Applied Scientific Research (TNO). Using 14CO2 data from 185 hourly integrated flask samples between 2020 and 2021, mean ratios of local excess NOx (∆NOx) to local excess ffCO2 (∆ffCO2) concentrations of 1.40 ppb ppm−1 for winter and 2.12 ppb ppm−1 for summer were calculated. These ratios were applied to the ∆NOx time series to construct continuous ∆ffCO2 estimates. The uncertainty of the ∆NOx-based ∆ffCO2 record was estimated at 3.94 ppm. Comparisons with 14CO2-based and ∆CO-based ∆ffCO2 estimates showed good agreement, while still demonstrating distinct behaviour for individual events. ∆NOx shows considerable potential as proxy for ffCO2 and as useful addition to ∆CO-based estimates, as both proxies have different footprints due to their lifetimes. A key challenge remains in reliably determining the seasonal and diurnal cycle of average ∆NOx to ∆ffCO2 ratios.
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Status: open (until 15 Sep 2025)
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RC1: 'Comment on egusphere-2025-2374', Maarten Krol, 24 Aug 2025
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This paper presents prospects of using NOx as a proxy to quantify fossil fuel CO2 contributions (ffCO2). The paper is mostly based on analysis of time series of NOx observations in Heidelberg. Although there are many aspects that complicate the NOx-based ffCO2 estimation, the authors do a good job in presenting the potential. The paper is overall clearly written, and I request only minor revision, specifically concerning:
- The interpretation of contributions from traffic and/or heating in different seasons
- The potential interpretation of night-time accumulation of NOx/CO/CO2 in summer, when the method works poorly due to short NOx lifetimes
Further comments are in the annotated pdf.
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RC2: 'Comment on egusphere-2025-2374', Anonymous Referee #2, 25 Aug 2025
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The manuscript entitled “Using NOx as quantitative fossil fuel CO2 proxy in urban areas: challenges and benefits” describes the use of NOx and 14CO2 measurements in Heidelberg (Germany) to estimate the seasonally averaged ratios of local excess NOx (ΔNOx) to local excess fossil fuel (ff) CO2 (ΔffCO2) concentrations and to derive ΔffCO2 concentrations from the NOx measurements. The analysis presented in the manuscript is overall sound and sufficiently detailed. However, I believe the scope of this study is too narrow, and I doubt that the presented results are sufficiently significant to warrant publication of the manuscript in ACP. My specific concerns and some suggestions are outlined below.
Major points
- The title of the manuscript is not quite appropriate, since the study addresses only one possible way to use NOx observations as a ffCO2 proxy, that is by using 14CO2 measurements. A more common way does not require the availability of rather scarce 14CO2 measurements but instead involves emission ratios from inventories. Hence, I suggest narrowing the title, for example as follows: “Using NOx as quantitative fossil fuel CO2 proxy based on 14CO2 measurements in urban areas: challenges and benefits”.
- It is quite obvious that variations of NOx (linearly scaled or not) should correlate with variation 14CO2 in vicinity of relatively strong local emission sources. It is also clear that this correlation can never be perfect due to atmospheric chemistry and the fact that the NOx-to-CO2 emission ratios differ for different source types. Furthermore, since the relationships between the NOx- and 14C-based ffCO2 are likely to differ (quantitatively) for various sites across the Europe and the world, the quantitative findings of this study are not necessarily relevant to any other sites. Thus the results of the study seem relatively trivial and the scientific message is unclear. Unfortunately, the authors did not show how the performance of the NOx-based ffCO2 record depends on the configuration of the local domain, even though they noted in the Introduction that “the choice of a suitable and common background for all species is of paramount importance”. A more detailed examination of this point (with dedicated test cases) could perhaps help justifying the study and generalizing its results.
- The NOx-based ΔffCO2 concentrations are representative of an area of about 30x80 km (according to Fig. 2). Hence, given that 14CO2 data are available in Europe from just a dozen or so operational sites, the proposed method can hardly help constrain the European carbon budget (unlike the original 14CO2 observations; see, e.g., https://doi.org/10.5194/acp-25-397-2025). However, the study’s significance in this context could be increased if the authors used their 14CO2 measurements to evaluate the inventory-based ΔNOx/ΔffCO2 ratios. A similar analysis (but in the case of the ΔCO/ΔffCO2 ratios) was conducted in a recent study authored by several co-authors of the given manuscript (https://doi.org/10.5194/acp-24-8183-2024).
Other points
L 41-42. I suggest clarifying here that the NOx concentration excesses (ΔNOx) are derived from in situ observations of both NOx and 14CO2 concentrations. Otherwise, this statement looks misleading.
L 82-83. Were the samples taken evenly throughout the day or mainly during certain hours?
L 104: “This would lead to a higher uncertainty of the derived ΔNOx-based ΔffCO2 estimates (see Sect. 2.3)”. This statement is actually not proven in Sect. 2.3.
Fig. 2(b): Values of the travel time are missing in the plot.
L 123-124. The sentence is hard to understand. I suggest rephrasing.
L 209: “40%”: Is this uncertainty for individual grid cells? If so, should not the uncertainty in the simulated NOx concentrations be much smaller than that (because random errors of emissions in different grid cells tend to compensate each other when these emissions mix in the atmosphere)?
Fig. 4. In Sect. 3.1, the authors discuss the seasonally averaged concentration ratios, but Fig. 4 shows scatter plots for all valid flask measurements. Could the authors provide similar scatter plots for summer and winter separately?
L 395: “concentrations show a strong correlation with R2 values over 0.8”. This statement appears to contradict the results reported on line 274 (for all summer samples … an R2 value of 0.55 is found), especially since the next sentence refers to the seasonal ratios.
Citation: https://doi.org/10.5194/egusphere-2025-2374-RC2
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