the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Jun 2022
NH3 spatio-temporal variability over Paris, Mexico and Toronto and its link to PM2.5 during pollution events
Abstract. Megacities can experience high levels of fine particulate matter (PM2.5) pollution linked to ammonia (NH3) mainly emitted from agricultural activities. Here, we investigate such pollution in the cities of Paris, Mexico and Toronto, each of which have distinct emission sources, agricultural regulations, and topography. Ten years of measurements from the Infrared Atmospheric Sounding Interferometer (IASI) are used to assess the spatio-temporal NH3 variability over and around the three cities.
In Europe and North America, we determine that temperature is associated with the increase in NH3 atmospheric concentrations with coefficient of determination (r2) of 0.8 over agricultural areas. The variety of the NH3 sources (industry and agricultural) and the weaker temperature seasonal cycle in southern North America induce a lower correlation factor (r2 = 0.5). The three regions are subject to long range transport of NH3, as shown using HYSPLIT cluster back-trajectories. The highest NH3 concentrations measured at the city scales are associated with air masses coming from the surrounding and north-northeast regions of Paris, the south-southwest areas of Toronto, and the southeast/southwest zones of Mexico City.
Using NH3 and PM2.5 measurements derived from IASI and surface observations from 2008 to 2017, annually frequent pollution events are identified in the 3 cities. Wind roses reveal statistical patterns during these pollution events with dominant northeast-southwest directions in Paris and Mexico cities, and the transboundary transport of pollutants from the United-States in Toronto. To check how well chemistry transport models perform during pollution events, we evaluate simulations made using the GEOS-Chem model for March 2011. In these simulations we find that NH3 concentrations are overall underestimated, though day-to-day variability is well represented. PM2.5 is generally underestimated over Paris and Mexico, but overestimated over Toronto.
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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
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Supplement
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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
(2252 KB) - Metadata XML
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Supplement
(2048 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-413', Anonymous Referee #1, 21 Jul 2022
General comments:
The manuscript of egusphere-2022-413 presented the result of a unique project of the AmmonAQ that targeted different three areas of Paris, Toronto, and Mexico City. Towards better air quality by mitigating NH3 emissions, the finding of this study will contribute to improving the atmospheric environment. I generally agree with this manuscript being published; however, some points are concerned. Especially, I am wondering about the uncertainty of the satellite NH3 measurement dataset analyzed in this study. Please address the following specific points.
Specific comments:
P3, L52: Please specify these five countries.
P3, L65: Are these increasing trends explained by the expansion of NH3 emissions, or meteorological variability (e.g., temperature)?
P3, L77: Does “the standard” indicate the standard in Mexico? Because this study conducted the comparison over three regions, it will be better to explicitly state it.
P5, L111 (Section 2.1): Because of the recent progress in satellite NH3 measurement, I would like to strongly suggest including the discussion of the uncertainty of satellite data, such as the detection limit (https://doi.org/10.5194/acp-19-12261-2019).
- What is the mottled pattern found over Canada during winter in Figure 3?
- Can all satellite measured NH3 close to zero be used in Figure 4?
- Is it available AK when comparing GEOS-Chem? The information on AK and how to calculate it in the comparison with the model is not described.
P5, L115: What is the actual gridded data (e.g., Figure 2) analyzed in this study?
P5, L130: Although we can find the reason to choose the model simulation period of 2011 in P12, L344-P13, L349, it is better to be shortly explained here.
P6, L178: Are these three panels shown with the same horizontal distance? If different, the scaler might be helpful.
P6, L152: Too coarse reanalysis resolution to investigate air mass trajectories on 50 km radius-circle at each city?
P7, L188: Same to Europe and southern North America, source information of “(Canada)” or “(U.S.A.)” can be useful in this Table 1.
P13, L358: Should the denominator be “observations” when comparing observation and model? Why model is referred to as a criterion?
P13, L359: Are these values positive? If model underestimation, are these negative?
P14, L379: From the spatial mapping over Europe, this seems to be simply led to model overestimation, and this is not consistent with the timeseries and relevant discussion in the main text. Please confirm this figure.
P15, L413-418: From this comparison on PM2.5 component, I am suspicious about the result in other cities of Paris and Mexico City. When we considered this poor performance for PM2.5 components, the result in Figure 9 and the relevant discussion seems to be meaningless. Is this performance for PM2.5 component useful (worse or better than other studies)? If not, I would like to request to reconsider this final section in P14, L391-P16, L425.
Technical corrections:
P10, L281: 4.71 “×” 1015?
P12, L324 and L325: “m.s-1”? Does it need the period?
Citation: https://doi.org/10.5194/egusphere-2022-413-RC1 - AC1: 'Reply on RC1', Camille Viatte, 02 Sep 2022
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RC2: 'Comment on egusphere-2022-413', Anonymous Referee #2, 22 Jul 2022
- AC2: 'Reply on RC2', Camille Viatte, 02 Sep 2022
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-413', Anonymous Referee #1, 21 Jul 2022
General comments:
The manuscript of egusphere-2022-413 presented the result of a unique project of the AmmonAQ that targeted different three areas of Paris, Toronto, and Mexico City. Towards better air quality by mitigating NH3 emissions, the finding of this study will contribute to improving the atmospheric environment. I generally agree with this manuscript being published; however, some points are concerned. Especially, I am wondering about the uncertainty of the satellite NH3 measurement dataset analyzed in this study. Please address the following specific points.
Specific comments:
P3, L52: Please specify these five countries.
P3, L65: Are these increasing trends explained by the expansion of NH3 emissions, or meteorological variability (e.g., temperature)?
P3, L77: Does “the standard” indicate the standard in Mexico? Because this study conducted the comparison over three regions, it will be better to explicitly state it.
P5, L111 (Section 2.1): Because of the recent progress in satellite NH3 measurement, I would like to strongly suggest including the discussion of the uncertainty of satellite data, such as the detection limit (https://doi.org/10.5194/acp-19-12261-2019).
- What is the mottled pattern found over Canada during winter in Figure 3?
- Can all satellite measured NH3 close to zero be used in Figure 4?
- Is it available AK when comparing GEOS-Chem? The information on AK and how to calculate it in the comparison with the model is not described.
P5, L115: What is the actual gridded data (e.g., Figure 2) analyzed in this study?
P5, L130: Although we can find the reason to choose the model simulation period of 2011 in P12, L344-P13, L349, it is better to be shortly explained here.
P6, L178: Are these three panels shown with the same horizontal distance? If different, the scaler might be helpful.
P6, L152: Too coarse reanalysis resolution to investigate air mass trajectories on 50 km radius-circle at each city?
P7, L188: Same to Europe and southern North America, source information of “(Canada)” or “(U.S.A.)” can be useful in this Table 1.
P13, L358: Should the denominator be “observations” when comparing observation and model? Why model is referred to as a criterion?
P13, L359: Are these values positive? If model underestimation, are these negative?
P14, L379: From the spatial mapping over Europe, this seems to be simply led to model overestimation, and this is not consistent with the timeseries and relevant discussion in the main text. Please confirm this figure.
P15, L413-418: From this comparison on PM2.5 component, I am suspicious about the result in other cities of Paris and Mexico City. When we considered this poor performance for PM2.5 components, the result in Figure 9 and the relevant discussion seems to be meaningless. Is this performance for PM2.5 component useful (worse or better than other studies)? If not, I would like to request to reconsider this final section in P14, L391-P16, L425.
Technical corrections:
P10, L281: 4.71 “×” 1015?
P12, L324 and L325: “m.s-1”? Does it need the period?
Citation: https://doi.org/10.5194/egusphere-2022-413-RC1 - AC1: 'Reply on RC1', Camille Viatte, 02 Sep 2022
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RC2: 'Comment on egusphere-2022-413', Anonymous Referee #2, 22 Jul 2022
- AC2: 'Reply on RC2', Camille Viatte, 02 Sep 2022
Peer review completion
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Camille Viatte
Rimal Abeed
Shoma Yamanouchi
William Porter
Sarah Safieddine
Martin Van Damme
Lieven Clarisse
Beatriz Herrera
Michel Grutter
Pierre-Francois Coheur
Kimberly Strong
Cathy Clerbaux
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2252 KB) - Metadata XML
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Supplement
(2048 KB) - BibTeX
- EndNote
- Final revised paper