Articles | Volume 18, issue 13
https://doi.org/10.5194/amt-18-3147-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Improving the quantification of peak concentrations for air quality sensors via data weighting
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- Final revised paper (published on 15 Jul 2025)
- Supplement to the final revised paper
- Preprint (discussion started on 22 Jan 2025)
- Supplement to the preprint
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2024-4080', Anonymous Referee #1, 17 Feb 2025
- AC2: 'Reply on RC1', Caroline Frischmon, 25 Mar 2025
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RC2: 'Comment on egusphere-2024-4080', Anonymous Referee #2, 03 Mar 2025
- AC1: 'Reply on RC2', Caroline Frischmon, 25 Mar 2025
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Caroline Frischmon on behalf of the Authors (25 Mar 2025)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (30 Mar 2025) by Albert Presto
RR by Anonymous Referee #1 (12 Apr 2025)
ED: Publish subject to technical corrections (27 Apr 2025) by Albert Presto
AR by Caroline Frischmon on behalf of the Authors (27 Apr 2025)
Manuscript
I appreciate the work in this paper as it provides guidance for other users of sensors seeking to measure pollutants that do not vary much diurnally and present as rare, intermittent transient events with the vast majority of data being at some baseline level. Overall it is a good study that highlights the importance of weighting collocation data for such pollutants.
Comments:
1. In section 2.1 there is no mention of the TVOC sensors make/models used.
2. I noticed throughout most of the paper and figures, sigmoidal weighting is discussed/appears before piecewise weighting, so consider switching the order of Sections 2.4.1 and 2.4.2 to be consistent.
3. Both sections 2.4.1 and 2.4.2 use a "X" variable to describe either a percentile or an offset, which is confusing. Consider using a different variable other than "X" to describe one of those. In addition, Section 2.6 uses lowercase "x" instead of uppercase "X" by mistake.
4. In section 3, the subsection numbering is unusual (e.g. 3.0.1 rather than 3.1 or 3.1.1); consider using nonzero subsection numbering.
5. In general I find Figs. 4-9 not easy to decipher.
For the sensitivity plots, perhaps there are too many weighting parameters shown on the same plot, but I find it difficult to see which weighting parameters are performing best in order to connect it with the in-text statements of which weighting parameters were further explored (e.g., "Therefore, we chose to further analyze the sigmoidal z_sigmoid=3 andn percentile_piecewise=95th").
For the timeseries/scatterplots, I likewise am having trouble distinguishing whether the sigmoidal or piecewise scatterplots are hugging the 1-1 line closer. I think there could be some refinement of Figs 4-9 to help make it clearer on how the reader can also arrive to the in-text conclusions.