the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Jun 2025
Global Emissions and Abundances of Chemically and Radiatively Important Trace Gases from the AGAGE Network
Abstract. Measurements from the Advanced Global Atmospheric Gases Experiment (AGAGE) combined with a global 12-box model of the atmosphere have long been used to estimate global emissions and surface mean mole fraction trends of atmospheric trace gases. Here, we present annually updated estimates of these global emissions and mole fraction trends for 42 compounds measured by the AGAGE network, including chlorofluorocarbons, hydrochlorofluorocarbons, hydrofluorocarbons, perfluorocarbons, sulfur hexafluoride, nitrogen trifluoride, methane, nitrous oxide, and selected other compounds. The data sets are available at https://doi.org/10.5281/zenodo.15372480. We describe the methodology to derive global mole fraction and emissions trends, which includes the calculation of semihemispheric monthly mean mole fractions, the mechanics of the 12-box model and the inverse method that is used to estimate emissions from the observations and model. Finally, we present examples of the emissions and mole fraction datasets for the 42 compounds.
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RC1: 'Comment on essd-2025-348', Anonymous Referee #1, 27 Jul 2025
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Review of “Global Emissions and Abundances of Chemically and Radiatively Important Trace Gases from the AGAGE Network”, by Luke M. Western et al.
General comments:
This manuscript provides the first systematic description of the methodology used by the AGAGE network to invert global emissions and mole fraction trends for 42 key trace gases based on a 12-box model, along with the release of a long-term updated dataset. This work fills a methodological transparency gap in the field of trace gas emission inversion and is of significant value for ozone layer assessments (WMO), climate change research (IPCC), and policy compliance (Montreal Protocol). The dataset is of high quality, with comprehensive compound coverage, and has been permanently archived through Zenodo (DOI: 10.5281/zenodo.15372480), aligning with the data-driven focus of the ESSD journal. Minor revisions are recommended before conditional acceptance, addressing the following specific issues.
First major comment:
Why didn’t the authors use MALTA, recently developed by Western et al. (2024), for the emission estimations in this paper? What are the differences in emission estimates for each compound between MALTA and the 12-box model? Does this mean that MALTA will not be used for this type of global emission estimation?
Second comment:
Do researchers still need to contact the principal investigators (PIs) of the measurement stations if they cite this paper to use the global mole fractions or emission estimates? Please clarify in the paper.
Third comment:
Each AGAGE baseline station is not located at the geometric center of its corresponding surface box in the 12-box model. This spatial mismatch could lead to representational errors, especially for species with regional emission gradients or temporal variability. How do the authors account for this spatial mismatch? And how does it affect the derived global mean mole fractions and the resulting emission estimates?
Specific comments:
- The document mentions the use of various instruments such as GC-MD, ADS, and Medusa GC-MS during different periods. However, the description of data continuity validation during instrument transitions (e.g., from ADS to Medusa) is insufficient. It is recommended to supplement the results of comparisons between different instruments during overlapping observation periods, quantify the range of deviations, and especially clarify the long-term consistency of methane observations between the GC-MD and CRDS systems (beyond the mentioned ratio of 1.0001±0007). Additionally, the impact of calibration scale conversion on historical data should be addressed.
- Section 7.1 mentions that “interannual repetition of meteorological data could lead to emission interannual variability errors,” but the impact of this issue has not been assessed. It is suggested to add a sensitivity test (e.g., comparing results using interannual varying meteorological fields) or cite Rigby et al. (2008) to quantify the uncertainty range.
- The transport parameters and loss processes (such as OH reactions and stratospheric losses) in the 12-box model are based on the latest literature (Burkholder and Hodnebrog, 2023), and the parameterization scheme is reasonable. The attention given to the prior emission independence in the Bayesian inversion framework (to avoid self-cycling of AGAGE data) is commendable. However, the prior assumption for some compounds (e.g., CFC-13, assumed to be 1/7 of CFC-115) lacks direct validation. It is recommended to include a sensitivity analysis to address this.
Technical corrections:
- The term “Semihemispheric” is inconsistently spelled (Section 5 vs. Section 4.1 “Semi-hemispheric”). The manuscript should standardize this term as “semihemispheric” following AGAGE conventions.
- Saunois et al. (2025) has been officially published (ESSD, 2025); citation information should be updated (volume, issue, pages).
- Line 43-44: For the sentence “g., ?Mühle et al., 2009”, it seems like there is an issue with the citation, as the question mark (?) is likely a placeholder or an error. It should be checked and corrected.
- Line 70-71: The original sentence “Oregon (45°N, 124°W°W)” contains an error with the extra “°W”.
- The hyphen used to connect years is inconsistent throughout the text; some instances use “–”while others use “-”. For example, in Line 195 and Line 199, it should be unified to “–” throughout the entire manuscript.
Conclusion
This manuscript provides a comprehensive and authoritative methodological framework for trace gas emission research, with high scientific rigor and valuable data. After addressing the recommended revisions to methodological details and improving the presentation of results, the work will significantly enhance the community’s understanding of halogenated greenhouse gases and ozone-depleting substances.
Citation: https://doi.org/10.5194/essd-2025-348-RC1
Data sets
Global Emissions and Abundances of Chemically and Radiatively Important Gases from the AGAGE Network Luke M. Western et al. https://doi.org/10.5281/zenodo.15372480
Model code and software
mrghg/py12box: v0.2.1 Matt Rigby and Luke Western https://doi.org/10.5281/ZENODO.6857447
mrghg/py12box_invert: v0.0.2 Matt Rigby and Luke Western https://doi.org/10.5281/ZENODO.6857794
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