the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Nov 2025
Ten years of measurements (2012–2022) of the atmospheric composition at Saclay/SIRTA Observatory in the Ile de France Region as part of ICOS and ACTRIS
Abstract. CO2 is the main contributor to global warming, and cities now account for more than two-thirds of emissions of this gas. Atmospheric observatories located on the outskirts of cities are therefore important facilities for measuring the impact on atmospheric composition of the emission reductions planned by cities. The Saclay observatory, part of the ICOS and ACTRIS research infrastructures and located 20 km southwest of Paris, has been monitoring greenhouse gases (CO2, CH4), reactive gases (NOx, O3, CO), and carbonaceous aerosols (eBC) since 2012. This study presents 10 years of monitoring of these compounds, characterizing diurnal, seasonal cycles and decadal trends. In order to best characterize the impact of Parisian emissions, we defined two sets of data depending on whether the station is downwind of Paris or, conversely, in background conditions with westerly winds. This strategy allows us to characterize the urban offset in the Saclay measurement series. The results show a significant decrease in the urban offset of compounds mainly linked to traffic emissions: -35.6 %, -52.3 %, and -56.7 % for CO, NOx, and eBClf. There was also a 15 % decrease in urban offset of CO2 between the 2012–2017 and 2019–2022 periods, a figure consistent with the Airparif inventories' estimate of the decrease in emissions in Paris over the same period.
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- RC1: 'Need access to original data', Anonymous Referee #1, 15 Dec 2025 reply
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RC2: 'Comment on essd-2025-602', Anonymous Referee #2, 23 Dec 2025
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This manuscript presents a comprehensive analysis of a ten-year dataset (2012–2022) of atmospheric composition measurements at the Saclay/SIRTA peri‑urban observatory near Paris. The study is timely, given the increasing importance of quantifying urban greenhouse gas and pollutant emissions, and the dataset itself is a significant contribution to the research community. The paper is generally well‑structured, methods are clearly described, and the use of wind‑sector separation to derive an “urban offset” is a sound and innovative approach for attributing concentration enhancements to Paris emissions. The co‑location of greenhouse gas and pollutant measurements within the ICOS and ACTRIS infrastructures adds considerable strength to the analysis. However, several aspects require clarification, expansion, or correction before the manuscript can be considered for publication.
1. The choice of wind sectors for defining “urban” (10–70°) and “rural” (190–280°) conditions is central to the analysis but is not sufficiently justified.
- Why were these specific angular ranges selected? A map showing the location of major emission sources (Paris center, other towns, major roads) relative to these sectors would greatly help readers assess whether the sectors truly isolate “Paris influence” vs. “background”.
- The wind‑speed filter of >4 m s⁻¹ for the rural sector is applied to “avoid the impact of nearby cities”, but no such filter is applied to the urban sector. Could low wind speeds in the urban sector lead to contamination from very local sources not representative of Paris outflow? Please justify this asymmetric treatment or consider applying a consistent wind‑speed threshold.
2. The authors mention that data gaps >30 days are not interpolated in the smoothing procedure, but it is unclear how this affects the trend analysis, especially for compounds with shorter records or more frequent gaps. A supplementary figure showing data coverage (hourly/monthly) for each species in each sector would be helpful. The instrument inter‑comparisons (GC vs. Picarro) in Appendix A are reassuring, but the text notes that values for some compounds are as low as 0.84. While slopes are near 1, some scatter is evident. A brief discussion on how this measurement uncertainty propagates into the urban offset calculation—especially for species with small offsets—would strengthen the methods section.
3. The 15% reduction in the CO₂ urban offset between 2012–2017 and 2019–2022 is highlighted as consistent with Airparif inventories. However, the strong influence of biospheric fluxes on CO₂ is acknowledged elsewhere in the text. How were inter‑annual variations in biospheric uptake/respiration (e.g., due to climate anomalies) accounted for when comparing these two periods? Could such variability partly explain the observed “break” between periods? A more detailed discussion on the challenges of attributing CO₂ changes solely to anthropogenic emission trends is needed.
4. The comparison between atmospheric ratios (ΔCO/ΔCO₂, ΔNOₓ/ΔCO₂) and inventory ratios is interesting, but the discussion is somewhat cursory. The manuscript states that atmospheric ratios are “lower than the ratio deduced from the inventory” and suggests biospheric fluxes as a possible explanation for CO₂. For NOₓ, the reactivity of NOₓ during transport is mentioned, but could there also be a systematic underestimation in the inventory’s spatial allocation or temporal profiles? A more quantitative exploration of these discrepancies (e.g., using a simple dispersion model) would elevate the discussion.
5. The methodology for eBC source apportionment (Sandradewi et al., 2008) is described, but the chosen values of αsf and αlf (1.85 and 0.9) are critical. Were these values validated for the Paris region? A brief justification or reference to local studies would be helpful. Additionally, the trends in eBCₛf (increase since 2020) are noted, but the discussion would benefit from linking this more explicitly to reported changes in wood‑burning practices (e.g., energy cost increases).
6. Abstract: “eBCₗf” is used without definition; please spell out “equivalent black carbon from liquid fuel” on first use.
7. Introduction: The sentence “Atmospheric studies have endeavoured to estimate urban CO₂ emissions. The study by Levin et al. (2011) have been analyzed…” contains a grammatical error (“have been” → “analyzed”). Please rephrase.
8. In Figure 5 (diurnal cycles), indicating the time axis in local time (CET/CEST) alongside UTC would improve readability for a regional audience.
9. The data DOI is provided, which is excellent. It would be helpful to also mention the expected availability date (upon publication?) and whether boundary‑layer height data are available through another repository.
10. Line 185: It is interesting to see O3 levels were higher in rural sector than urban sector. It could be transported precursors from nearby cities.
11. Typos and formatting:
- Page 2, line 55: “process tracers,” → “process tracers” (remove comma).
- Page 7, Table 2: “Tertiaire” should be “Tertiary” for consistency. The table caption mentions “BC” but the table header says “BC”; please verify.
- Page 12, line 235: “As mentionned above” → “As mentioned above”.
Citation: https://doi.org/10.5194/essd-2025-602-RC2
Data sets
Ten years of measurements (2012-2022) of the atmospheric composition at Saclay/SIRTA Observatory in the Ile de France Region as part of ICOS and ACTRIS L. Bouillon and M. Ramonet https://doi.org/10.57932/5C399263-A317-41B7-8900-184B177C4216
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This might be a good paper. But, to meet journal requirements and to complete this review properly, we need direct access to original data. Current URL leads only to repository, not to data. Please do not expect readers or users to search.