the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Oct 2024
The ZiCOS-M CO2 sensor network: measurement performance and CO2 variability across Zürich
Abstract. As a component of the ICOS Cities project, a "mid-cost'' NDIR (nondispersive infrared) CO2 sensor network was deployed across Zürich city (Switzerland), known as ZiCOS-M. The network was operational between July 2022 and July 2024 and consisted of 26 monitoring sites, 21 of which were located in or around Zürich city with five sites outside the urban area. Daily calibrations using two reference gas cylinders and corrections of the sensors' spectroscopic response to water vapour were performed to reach a high level of measurement accuracy. The hourly mean root mean squared error (RMSE) was 0.98 ppm (range of 0.46 and 1.5 ppm) while the mean bias was -0.09 ppm (range of -0.72 and 0.66 ppm) when undergoing parallel measurements with a high-precision reference gas analyser. CO2 concentrations (technically, dry air mole fractions), were highly variable with site means in Zürich ranging from 434 to 460 ppm and Zürich's mean urban CO2 dome was 15.4 ppm above the regional background. Some of the highest CO2 levels were found at two sites exposed to a combination of strong plant respiration and very confined nocturnal boundary layers. High CO2 episodes were detected outside Zürich's urban area demonstrating that processes acting on a variety of scales drove CO2 levels. The ZiCOS-M network offered significant insights at an order of magnitude lower cost compared to reference instruments and the observations generated by ZiCOS-M will be used in additional ICOS Cities activities to conduct CO2 emission inventory validation with inversion modelling systems.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(3614 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-2925', Anonymous Referee #1, 29 Oct 2024
This is an extremely careful, thorough description of the performance of an urban sensor network. It was a pleasure to read. I recommend publication.
I have two minor points that could be clarified.
· Line 228 – 230: It would be useful to confirm that a longer smoothing and diurnal variation in the calibration time has no effect on the analysis.
· Table 3: Does the lower data capture at a handful of sites (Beromunster, for example) mean the data from this site is not sampled across seasons with the same distribution as other sites?
Citation: https://doi.org/10.5194/egusphere-2024-2925-RC1 -
RC2: 'Comment on egusphere-2024-2925', Anonymous Referee #2, 10 Nov 2024
Review of “The ZiCOS-M CO2 sensor network: measurement performance and
CO2 variability across Zürich” by Grange et al.
This manuscript describes instrument performance and results from a network of nondispersive infrared CO2 sensors that are lower cost than the typical instruments used for studying urban greenhouse gas emissions. The advantages of a viable lower cost instrument are many – including enhancing the ability to spatially resolve emissions within a city. With increased spatial resolution we can also learn about the sectoral contributions to emissions and thus better advise policymakers as to the most effective means of mitigation. New instrumentation must be tested for compatibility and this manuscript does so for 26 sites (including three instrument types, but mostly Senseair HPP sensors). The research presented is well thought-out and the manuscript well-written. I recommend publication after minor revisions.
Minor
Abstract: I don’t think the mean bias being -0.09 ppm is relevant. The only thing we actually care about is that the range of biases for the instruments varied from -0.72 to +0.66 ppm. I suggest rewording. It would also be good to specify that these results came from co-locations of the instruments with a reference instrument of periods of two weeks or more. For a while I was thinking that the statistics came from co-locations of four mid-cost sensors at the four sites with reference instruments, in which case the statistics would not be nearly as representative.
Abstract: Consider adding the daytime mean gradient of 6.5 ppm (half of 13 ppm) to provide context for the attained compatibility.
Pg. 8 Section 2.3: This phrase is worrisome: "adjustment strategies to increase their agreement with observations generated by reference instrumentation" This procedure sounds odd, because it is the metric by which the instruments are evaluated. We need some details here.
It’s not until the results that we learn that there were parallel measurements at the Dubendorf site for at least two weeks for each of the instruments. This should be in the methods as well, and described more clearly in the abstract. (There is a single phrase indicating parallel measurements in section 2.3.1 but the idea that all instruments were tested for two weeks or more is important.)
Figure 4: The text indicates that the discontinued Senseair HPP sensor often performed more poorly than the other sensors. I think the most important statistic is the mean bias and the mean bias is better for the Senseair, overall (maybe too few of the others to really say).
Technical
Pg. 2, first full paragraph. I don’t know if I’d say that the monitoring of CO2 in urban areas has not been a priority. I understand the idea (there are more measurements of air pollutants), but there has been quite a lot of work on it!
Pg. 2, line 25: complementary instead of complimentary
General: I don’t know about British English but American English we’d say either in “Zurich” or in “the city”, but not in “Zurich city”.
Pg. 2, first full paragraph. Missing references for the US high precision network (e.g., LA, NorthEast Corridor, Indianapolis)
Pg.4, last paragraph: Please include manufacturers and part numbers. I’m particularly interested in the demand-flow regulator, but it’s good to have all the details documented.
Figure 1: The pump is upstream of the CO2 sensor and thus the measurements will be affected by leaks within the pump or connections. Please discuss this choice. Why are there RH/T sensors both upstream and downstream of the CO2 sensor?
Table 2: A column indicating the instrument type would be a nice addition to Table 2.
Table 3: How is near-ground difference from near-ground (kerbside)?
Pg. 18, line 365: What is the landcover surrounding Sottens (e.g., within 10 km)? Agriculture?
Citation: https://doi.org/10.5194/egusphere-2024-2925-RC2 - AC1: 'Comment on egusphere-2024-2925', Stuart Grange, 14 Dec 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-2925', Anonymous Referee #1, 29 Oct 2024
This is an extremely careful, thorough description of the performance of an urban sensor network. It was a pleasure to read. I recommend publication.
I have two minor points that could be clarified.
· Line 228 – 230: It would be useful to confirm that a longer smoothing and diurnal variation in the calibration time has no effect on the analysis.
· Table 3: Does the lower data capture at a handful of sites (Beromunster, for example) mean the data from this site is not sampled across seasons with the same distribution as other sites?
Citation: https://doi.org/10.5194/egusphere-2024-2925-RC1 -
RC2: 'Comment on egusphere-2024-2925', Anonymous Referee #2, 10 Nov 2024
Review of “The ZiCOS-M CO2 sensor network: measurement performance and
CO2 variability across Zürich” by Grange et al.
This manuscript describes instrument performance and results from a network of nondispersive infrared CO2 sensors that are lower cost than the typical instruments used for studying urban greenhouse gas emissions. The advantages of a viable lower cost instrument are many – including enhancing the ability to spatially resolve emissions within a city. With increased spatial resolution we can also learn about the sectoral contributions to emissions and thus better advise policymakers as to the most effective means of mitigation. New instrumentation must be tested for compatibility and this manuscript does so for 26 sites (including three instrument types, but mostly Senseair HPP sensors). The research presented is well thought-out and the manuscript well-written. I recommend publication after minor revisions.
Minor
Abstract: I don’t think the mean bias being -0.09 ppm is relevant. The only thing we actually care about is that the range of biases for the instruments varied from -0.72 to +0.66 ppm. I suggest rewording. It would also be good to specify that these results came from co-locations of the instruments with a reference instrument of periods of two weeks or more. For a while I was thinking that the statistics came from co-locations of four mid-cost sensors at the four sites with reference instruments, in which case the statistics would not be nearly as representative.
Abstract: Consider adding the daytime mean gradient of 6.5 ppm (half of 13 ppm) to provide context for the attained compatibility.
Pg. 8 Section 2.3: This phrase is worrisome: "adjustment strategies to increase their agreement with observations generated by reference instrumentation" This procedure sounds odd, because it is the metric by which the instruments are evaluated. We need some details here.
It’s not until the results that we learn that there were parallel measurements at the Dubendorf site for at least two weeks for each of the instruments. This should be in the methods as well, and described more clearly in the abstract. (There is a single phrase indicating parallel measurements in section 2.3.1 but the idea that all instruments were tested for two weeks or more is important.)
Figure 4: The text indicates that the discontinued Senseair HPP sensor often performed more poorly than the other sensors. I think the most important statistic is the mean bias and the mean bias is better for the Senseair, overall (maybe too few of the others to really say).
Technical
Pg. 2, first full paragraph. I don’t know if I’d say that the monitoring of CO2 in urban areas has not been a priority. I understand the idea (there are more measurements of air pollutants), but there has been quite a lot of work on it!
Pg. 2, line 25: complementary instead of complimentary
General: I don’t know about British English but American English we’d say either in “Zurich” or in “the city”, but not in “Zurich city”.
Pg. 2, first full paragraph. Missing references for the US high precision network (e.g., LA, NorthEast Corridor, Indianapolis)
Pg.4, last paragraph: Please include manufacturers and part numbers. I’m particularly interested in the demand-flow regulator, but it’s good to have all the details documented.
Figure 1: The pump is upstream of the CO2 sensor and thus the measurements will be affected by leaks within the pump or connections. Please discuss this choice. Why are there RH/T sensors both upstream and downstream of the CO2 sensor?
Table 2: A column indicating the instrument type would be a nice addition to Table 2.
Table 3: How is near-ground difference from near-ground (kerbside)?
Pg. 18, line 365: What is the landcover surrounding Sottens (e.g., within 10 km)? Agriculture?
Citation: https://doi.org/10.5194/egusphere-2024-2925-RC2 - AC1: 'Comment on egusphere-2024-2925', Stuart Grange, 14 Dec 2024
Peer review completion
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Pascal Rubli
Andrea Fischer
Dominik Brunner
Christoph Hueglin
Lukas Emmenegger
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(3614 KB) - Metadata XML