Observing local CO<sub>2</sub> sources using low-cost, near-surface urban monitors

Shusterman, Alexis A.; Kim, Jinsol; Lieschke, Kaitlyn J.; Newman, Catherine; Wooldridge, Paul J.; Cohen, Ronald C.

doi:https://doi.org/10.5194/acp-18-13773-2018

Articles | Volume 18, issue 18

https://doi.org/10.5194/acp-18-13773-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-18-13773-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 18

Research article

|

28 Sep 2018

Research article |

| 28 Sep 2018

Observing local CO₂ sources using low-cost, near-surface urban monitors

Alexis A. Shusterman, Jinsol Kim, Kaitlyn J. Lieschke, Catherine Newman, Paul J. Wooldridge, and Ronald C. Cohen

Download

Final revised paper (published on 28 Sep 2018)
Supplement to the final revised paper
Preprint (discussion started on 22 May 2018)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review', Jocelyn Turnbull, 19 Jun 2018
- AC1: 'Response to Referee #1', A. A. Shusterman, 26 Jul 2018
RC2: 'Review of “Observing local CO2 sources using low-cost, near-surface CO2 monitors” by Shusterman et al.', Anonymous Referee #2, 18 Jul 2018
- AC2: 'Response to Referee #2', A. A. Shusterman, 26 Jul 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by A. A. Shusterman on behalf of the Authors (26 Jul 2018) Author's response Manuscript

ED: Publish subject to minor revisions (review by editor) (17 Aug 2018) by Andreas Engel

Thank you very much for your revised manuscript.

I have a few additional requests/suggestions which I would like you to consider. All page and line numbers are with respect to the track changed manuscript in the Authors response file.

I also noted that fuel efficiency is given in miles per gallon. Please use SI units for this. (e.g. l /100 km or km/liter). Similar comment with respect to temperature (e.g. ppm CO2 /K; not /°C.)

p.3. l. 26. I'm not convinced that this will satisfy the reader. Of course after longer averaging, the error of the mean reduces. I would however be very careful to call this an uncertainty. After loner averaging, the instrumental uncertainty decreases but the influence of atmospheric variability increases. This should in some way be mentioned/discussed and also I suggest to give a few examples of instrumental uncertainties after typical averaging times used in the manuscript (e.g. 5 min used in the correlation analysis). I also suggest to include a discussion of long-term drift as suggested by the reviewer. I find the answer in the reply to the reviewers rather vague. And it is one of those examples, where other papers need to be read to understand the procedure.

Reviewer comment on importance of other sources (and sinks): please include a statement on this in the manuscript, reflecting your reply.

Reviewer comment on the use of a single highway traffic count: please include a statement on this in the manuscript, reflecting your reply.

p.6. l. 24: please be more precise: in local CO2 mole fraction enhancements? Emissions?

Reviewer comment on intercept value of MLR: Please explain in more detail where the intercept is explained in the revised manuscript and what the physical meaning of this intercept is.

Reviewer comment regarding P7 L 4-4 (original manuscript): I'm not convinced that this answer satisfies the request of the reviewer to provide a robust explanation of how this value is derived (I guess it is derived by dividing the 11% slope uncertainty by 3.5 %/year expected increase in fuel efficiency?).

p.10. l. 5.: please specify what 1 ppm means: over which time period?

Hide

AR by A. A. Shusterman on behalf of the Authors (25 Aug 2018) Author's response Manuscript

ED: Publish as is (27 Aug 2018) by Andreas Engel

AR by A. A. Shusterman on behalf of the Authors (06 Sep 2018) Manuscript

Download

Article (5975 KB)
Full-text XML

Short summary

We describe the diversity and heterogeneity of urban CO₂ levels observed using the BErkeley Atmospheric CO₂ Observation Network, a distributed instrument of > 50 CO₂ sensors stationed every ~ 2 km across the San Francisco Bay Area. We demonstrate that relatively simple mathematical techniques, applied to these observations, can be used to detect the small changes in highway CO₂ emissions expected to result from upcoming fuel economy regulations, affirming the policy relevance of low-cost sensors.

Observing local CO2 sources using low-cost, near-surface urban monitors

Download

Interactive discussion

Peer-review completion

Observing local CO₂ sources using low-cost, near-surface urban monitors