the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Nov 2023
Measurement Report: Potential of MAX-DOAS and AERONET ground based measurements in Montevideo, Uruguay for the detection of distant biomass burning
Abstract. Biomass burning releases large amounts of aerosols and chemical species into the atmosphere, which represents a major source of air pollutants. Emissions and by-products can be transported over long distances, presenting challenges in quantification. This is mainly done using satellites, which offer global coverage and data acquisition for places that are difficult to access. In this study, ground-based observations play an important role in assessing the abundance of trace gases and aerosols. On November 24, 2020, a significant increase in formaldehyde was observed, with a MAX-DOAS instrument located in Montevideo (Uruguay). Vertical column densities reached values of 2.4x1016 molec. cm-2, more than twice the values observed during the previous days. This was accompanied by an increase in the aerosol levels measured by an AERONET photometer located at the same site. For example, the AOD at 440 nm reached values close to 1, one order of magnitude larger than typical values in Montevideo.
Our findings indicate that the cause of the increase was associated with the passage of a plume originating from distant biomass burning. This conclusion is supported using TROPOMI satellite observations as well as HYSPLIT trajectory simulations. The profiles of the gases and aerosols retrieved from the MAX-DOAS observations are consistent with the HYSPLIT analysis, showing the passage of a plume over Montevideo on November 24 located at a height of ∼1.5 km. This corroborates that biomass burning events that occur about 800 km north of Montevideo can affect the local atmosphere due to long-distance transport of emissions. This study underscores the potential of ground-based atmospheric monitoring as a tool for detection of such events. Furthermore, it demonstrates the greater sensitivity compared to satellite when it comes to detection of relatively small amounts of carbonyls like glyoxal and formaldehyde.
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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
(9466 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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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2390', Anonymous Referee #1, 11 Jan 2024
General comment:
The manuscript investigates with, ground based and satellite measurements, the effects on the air composition over the Montevideo region during a long range transport due to a biomass burning event. Investigations of air quality and the consequent effects a wildfire can cause on the environment are very important to properly address. Detecting these events and following their trajectories are the initial steps in building a scientific understanding of these processes. The authors showed good results in demonstrating the gases/particles contributions from the wildfire event. My major concern is with the following investigation the authors could have done with the elements showed in the paper. For example, the vegetation damage aspects or the fire aging plume characteristics and its chemical/physic composition and interaction with the radiation could have been explored.
Specific comments:
The authors should improve the investigation by analyzing the amount of O3 produced due to the fire event and how it might cause damage to the atmosphere and environment, for example vegetation damage.
Another aspect that could be further explored is the spatial distribution of he fire plume effect. Depending on the fire plume age, what are the secondary organic aerosol, Black carbon, AOD, CO, O3, NOx, HCHO values? And how are they impacted by the solar radiation for example, in the formation processes of O3 and SOA?
It is important to know during a fire event, how strong is the correspondence between atmospheric oxidants, such as, characterized O3 and NO2 and the SOA concentration.
The authors could be using the Hysplit model to define forward trajectories by calculating it starting from a cluster of points at varying heights above sea level. For example, defining a cylinder of initial staring points with a radius of ~5km centered on the fire plume’s initial location, the average gas and aerosol concentrations could be calculated within the volume defined in latitude and longitude by the points as they are time evolved by HYSPLIT, rather than just examine point values. The authors could also define an altitude range to track the fire plume.
It is important to have a numerical experiment with an atmospheric model with a gas-phase chemistry, and aerosol model to better understand the plume trajectory. Specifically when no ground or satellite data are available.
I recommend the authors to better emphasize the main scientific question approached in the paper. The contribution in this paper needs to be solid and be part of the knowledge’s support used for future science.
Citation: https://doi.org/10.5194/egusphere-2023-2390-RC1 - AC1: 'Reply on RC1', Matias Osorio, 07 Apr 2024
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RC2: 'Comment on egusphere-2023-2390', Anonymous Referee #2, 23 Feb 2024
Review of
Measurement Report: Potential of MAX-DOAS and AERONET ground based measurements in Montevideo, Uruguay for the detection of distant biomass burning
by Matías Osorio et al
https://doi.org/10.5194/egusphere-2023-2390
Summary: This study reports observations during an episode of long range transport of smoke using a MAX-DOAS instrument located in Montevideo, Uruguay. The observations reported are complemented with ancillary standard information available such as Aeronet aerosol products, HYSPLIT model runs to trace back the source regions and satellite products from the TROPomi sensor. The novelty of this study is the first-time description of a smoke event in this region of the world with a combination of instrumentation that has become standard in the northern hemisphere but are notoriously lacking in the southern hemisphere. Studies like this one are very much welcomed. I view this study as a reference work where future research focusing on smoke transport in South America can compare with. This fact makes this study worthy of publication and I recommend to it. I do have general comments about writing style, and suggestions for figure improvement and clarifications. Not addressing them should not be a reason to prevent the publication however, it would make a more enjoyable reading and useful information for future studies as I detail below.
Detail:
1) While this is a measurement report and there is no expectation of new discovery reporting or lengthy discussions and speculation, the general tone of the paper is too tentative in the sense that it is written as if the observations must demonstrate that what it is been observed by the MAX-DOAS is smoke. I think the emphasis should be changed to a different tone where established techniques are used to track a smoke event. The goal is to report how these observations and analysis perform in a region/environment where there hasn’t been many application of such techniques. In other words, it is not a matter to prove that smoke was arriving at Montevideo but the goal is to report how a smoke event is observed in Montevideo with these commonly used techniques in the northern Hemisphere but not in this region. For example expressions like:
lines 204-205: "The main interest in this analysis is to assess the effectiveness of formaldehyde and glyoxal as plume tracers from biomass burning events and their detection in Montevideo."
Unless there is an alternative reason to suspect that formaldehyde and glyoxal are coming from somewhere else and given that it already been seen in smoke events elsewhere, it is not necessary to be so tentative to prove the smoke is coming from where the satellite images and model clearly show. This tone pervades the paper and it distracts from the real novelty which is to highlight how such event is seen by a tool that is not common in the South America. So, I highly advice to do some style editing.
2) With regards to readability the paper is perfectly understandable and fine. However, there are some mistakes particularly regarding the use of prepositions. I will not detail those because it is too tedious, but I advise to have it check by a native speaker.
3) Figures: overall I found the figures clear and appropriate, except for couple of cases I mention below
4) line 225. Can you clarify how those percentiles are computed? they are not explained in the satellite section and as far as I know, there are not part of the standard satellite products.
5) line 228-230 , figure 8b is a scattering plot for which there is linear fit plotted. It is not a correlation plot. Please correct.
6) Paragraph starting 236 , Not clear to what plot or figure this explanation is referring to , so it is difficult to verify.
7) full text in page 15 (starting line 248). This is a difficult description to follow because the data for Nov24 shown in figure 7 is too cramped. I think it would be more illustrative to add a figure displaying a time series of hourly observations for 22 and 24/Nov to illustrate this paragraph.
8) incidentally, I do not think that figure 9 is very useful because there is little independent information to verify the profiles. I think that replacing it with the above suggested new figure would be more useful.
Citation: https://doi.org/10.5194/egusphere-2023-2390-RC2 - AC2: 'Reply on RC2', Matias Osorio, 07 Apr 2024
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RC3: 'Review comment on egusphere-2023-2390', Anonymous Referee #3, 26 Feb 2024
Review of manuscript ‘Measurement Report: Potential of MAX-DOAS and AERONET
ground based measurements in Montevideo, Uruguay for the detection of distant biomass burning’
by Osorio et al, submitted for publication in Egusphere.
General review
The paper describes the detection of a biomass burning generated plume, consisting of a mixture
of aerosol particles and gaseous components, using ground-based observations of UV-VIS
scattered radiation by a ground-based multi-axis differential optical absorption spectrometer
(MAX-DOAS) in Montevideo, Uruguay during November 2020. The authors made use of collocated
AERONET observations on total column aerosol optical depth, particle size distribution, and
aerosol single scattering albedo in the inversion MAX-DOAS spectroscopic observations to derive
the vertical distributions of formaldehyde (HCHO), glyoxal (CHOCHO), nitrogen dioxide (NO2),
oxygen collision complex (O4), and aerosols.
The obtained results show that the combined use of MAX-DOAS and AERONET observation can be
advantageously used to derive the vertical distribution of transported carbon-containing aerosols
generated by biomass burning. Although the authors make a convincing description of their
results, a few, mostly minor, modifications are needed before the manuscript is acceptable for
publication.
Specific comments
Title: The current title does not adequately convey the main contribution of this work. I suggest
slightly modifying the tittle to: ‘Combined use of MAX-DOAS and AERONET ground-based
observations in Montevideo, Uruguay, for retrieving the vertical distribution of biomass burning
generated aerosols.’
Abstract: Since the abstract is a standalone description of the paper, all acronyms therein must be
resolved.
Line 5 Resolve MAX-DOAS acronym
Line 7 Resolve AERONET acronym
Line 8 Resolve AOD acronym
Line 11 Resolve TROPOMI and HYSPLIT acronyms
All acronyms must be resolved again in the main body of the manuscript.
Line 29 Resolve BB acronym
Line 38 Provide a reference for the statement on air quality in Uruguay.
Line 40 Suggest using ‘sunphotometer’ to be consistent with AERONET’s terminology.
Line 54-57 The statement on the variability of AERONET AOD and other parameters, and apparent
consistency with the detection of ‘this plume’ should be supported with observations. Likewise,
conclusions on satellite data analysis and trajectory simulations do not belong in the introduction
section. At this point in the paper, these statements read like unsupported speculations.
Line 73. What is the resulting vertical resolution?
Line 85. Add a reference on AERONET current version and aerosol data products.
Line 90. Resolve UV-VIS-NIR-SWIR acronyms.
Line 94 Resolve CCD acronym.
Line 100 Resolve VOC acronym
Line 106 Resolve TM5-MP and SCD acronyms.
Line 125. Add references on retrievability of aerosol vertical distribution by this technique.
Line 126. List specific AERONET aerosol retrieval results extrapolated to the matching windows and
discuss the extrapolation method.
-Which AERONET wavelengths were used in the calculation of Angstrom Exponent?
- For this application, AERONET shortest wavelengths (340 and 380 nm) should have been used.
- AERONET does not retrieve single scattering albedo at wavelengths shorter than 440 nm. How
was aerosol absorption accounted for in the UV region?
Line 160. CALIPSO or icesat-2 lidar data may have been available on this day. If so, how does it
compare?
Line 173. Can these results be confirmed with CALIPSO or icesat2 lidar observations? CALIPSO
data may be affected by the South Atlantic Anomaly. Icesat2, however, reports observations over
the analysis period in this paper at https://icesat-2.gsfc.nasa.gov/atmo-data.
Line 175. Discuss the expected lifetimes of the retrieved species. It may be relevant in this
analysis.
Line 182. Resolve QDOAS acronym.
Line 182. Discuss Tables 1 and 2 separately. They provide different information. Describe each
column of Table 1 in detail. No absorption cross-section data is shown in Table 2.
Line 189 The description of Figure 5 is incomplete. Only the top row is discussed. There is not an
adequate discussion of the bottom three rows. The figure caption should accurately describe what
is shown in each of the nine panels of the figure. If some of the data shown in this figure is not
relevant to the analysis, then remove it.
Line 193. Describe in some detail the mentioned color index classification algorithm. How is the
comparison of intensities used to discern clear from cloudy or partly cloudy conditions?
Line 198. Change the x-axis time representation in Figure 6 to the commonly used month-day
nomenclature. The figure caption should clearly indicate what is shown on each row from top to
bottom, and on each column from left to right.
Line 219. Sentinel 5 (S5P) is just the satellite name. The sensor’s name should also be included- AC3: 'Reply on RC3', Matias Osorio, 07 Apr 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2390', Anonymous Referee #1, 11 Jan 2024
General comment:
The manuscript investigates with, ground based and satellite measurements, the effects on the air composition over the Montevideo region during a long range transport due to a biomass burning event. Investigations of air quality and the consequent effects a wildfire can cause on the environment are very important to properly address. Detecting these events and following their trajectories are the initial steps in building a scientific understanding of these processes. The authors showed good results in demonstrating the gases/particles contributions from the wildfire event. My major concern is with the following investigation the authors could have done with the elements showed in the paper. For example, the vegetation damage aspects or the fire aging plume characteristics and its chemical/physic composition and interaction with the radiation could have been explored.
Specific comments:
The authors should improve the investigation by analyzing the amount of O3 produced due to the fire event and how it might cause damage to the atmosphere and environment, for example vegetation damage.
Another aspect that could be further explored is the spatial distribution of he fire plume effect. Depending on the fire plume age, what are the secondary organic aerosol, Black carbon, AOD, CO, O3, NOx, HCHO values? And how are they impacted by the solar radiation for example, in the formation processes of O3 and SOA?
It is important to know during a fire event, how strong is the correspondence between atmospheric oxidants, such as, characterized O3 and NO2 and the SOA concentration.
The authors could be using the Hysplit model to define forward trajectories by calculating it starting from a cluster of points at varying heights above sea level. For example, defining a cylinder of initial staring points with a radius of ~5km centered on the fire plume’s initial location, the average gas and aerosol concentrations could be calculated within the volume defined in latitude and longitude by the points as they are time evolved by HYSPLIT, rather than just examine point values. The authors could also define an altitude range to track the fire plume.
It is important to have a numerical experiment with an atmospheric model with a gas-phase chemistry, and aerosol model to better understand the plume trajectory. Specifically when no ground or satellite data are available.
I recommend the authors to better emphasize the main scientific question approached in the paper. The contribution in this paper needs to be solid and be part of the knowledge’s support used for future science.
Citation: https://doi.org/10.5194/egusphere-2023-2390-RC1 - AC1: 'Reply on RC1', Matias Osorio, 07 Apr 2024
-
RC2: 'Comment on egusphere-2023-2390', Anonymous Referee #2, 23 Feb 2024
Review of
Measurement Report: Potential of MAX-DOAS and AERONET ground based measurements in Montevideo, Uruguay for the detection of distant biomass burning
by Matías Osorio et al
https://doi.org/10.5194/egusphere-2023-2390
Summary: This study reports observations during an episode of long range transport of smoke using a MAX-DOAS instrument located in Montevideo, Uruguay. The observations reported are complemented with ancillary standard information available such as Aeronet aerosol products, HYSPLIT model runs to trace back the source regions and satellite products from the TROPomi sensor. The novelty of this study is the first-time description of a smoke event in this region of the world with a combination of instrumentation that has become standard in the northern hemisphere but are notoriously lacking in the southern hemisphere. Studies like this one are very much welcomed. I view this study as a reference work where future research focusing on smoke transport in South America can compare with. This fact makes this study worthy of publication and I recommend to it. I do have general comments about writing style, and suggestions for figure improvement and clarifications. Not addressing them should not be a reason to prevent the publication however, it would make a more enjoyable reading and useful information for future studies as I detail below.
Detail:
1) While this is a measurement report and there is no expectation of new discovery reporting or lengthy discussions and speculation, the general tone of the paper is too tentative in the sense that it is written as if the observations must demonstrate that what it is been observed by the MAX-DOAS is smoke. I think the emphasis should be changed to a different tone where established techniques are used to track a smoke event. The goal is to report how these observations and analysis perform in a region/environment where there hasn’t been many application of such techniques. In other words, it is not a matter to prove that smoke was arriving at Montevideo but the goal is to report how a smoke event is observed in Montevideo with these commonly used techniques in the northern Hemisphere but not in this region. For example expressions like:
lines 204-205: "The main interest in this analysis is to assess the effectiveness of formaldehyde and glyoxal as plume tracers from biomass burning events and their detection in Montevideo."
Unless there is an alternative reason to suspect that formaldehyde and glyoxal are coming from somewhere else and given that it already been seen in smoke events elsewhere, it is not necessary to be so tentative to prove the smoke is coming from where the satellite images and model clearly show. This tone pervades the paper and it distracts from the real novelty which is to highlight how such event is seen by a tool that is not common in the South America. So, I highly advice to do some style editing.
2) With regards to readability the paper is perfectly understandable and fine. However, there are some mistakes particularly regarding the use of prepositions. I will not detail those because it is too tedious, but I advise to have it check by a native speaker.
3) Figures: overall I found the figures clear and appropriate, except for couple of cases I mention below
4) line 225. Can you clarify how those percentiles are computed? they are not explained in the satellite section and as far as I know, there are not part of the standard satellite products.
5) line 228-230 , figure 8b is a scattering plot for which there is linear fit plotted. It is not a correlation plot. Please correct.
6) Paragraph starting 236 , Not clear to what plot or figure this explanation is referring to , so it is difficult to verify.
7) full text in page 15 (starting line 248). This is a difficult description to follow because the data for Nov24 shown in figure 7 is too cramped. I think it would be more illustrative to add a figure displaying a time series of hourly observations for 22 and 24/Nov to illustrate this paragraph.
8) incidentally, I do not think that figure 9 is very useful because there is little independent information to verify the profiles. I think that replacing it with the above suggested new figure would be more useful.
Citation: https://doi.org/10.5194/egusphere-2023-2390-RC2 - AC2: 'Reply on RC2', Matias Osorio, 07 Apr 2024
-
RC3: 'Review comment on egusphere-2023-2390', Anonymous Referee #3, 26 Feb 2024
Review of manuscript ‘Measurement Report: Potential of MAX-DOAS and AERONET
ground based measurements in Montevideo, Uruguay for the detection of distant biomass burning’
by Osorio et al, submitted for publication in Egusphere.
General review
The paper describes the detection of a biomass burning generated plume, consisting of a mixture
of aerosol particles and gaseous components, using ground-based observations of UV-VIS
scattered radiation by a ground-based multi-axis differential optical absorption spectrometer
(MAX-DOAS) in Montevideo, Uruguay during November 2020. The authors made use of collocated
AERONET observations on total column aerosol optical depth, particle size distribution, and
aerosol single scattering albedo in the inversion MAX-DOAS spectroscopic observations to derive
the vertical distributions of formaldehyde (HCHO), glyoxal (CHOCHO), nitrogen dioxide (NO2),
oxygen collision complex (O4), and aerosols.
The obtained results show that the combined use of MAX-DOAS and AERONET observation can be
advantageously used to derive the vertical distribution of transported carbon-containing aerosols
generated by biomass burning. Although the authors make a convincing description of their
results, a few, mostly minor, modifications are needed before the manuscript is acceptable for
publication.
Specific comments
Title: The current title does not adequately convey the main contribution of this work. I suggest
slightly modifying the tittle to: ‘Combined use of MAX-DOAS and AERONET ground-based
observations in Montevideo, Uruguay, for retrieving the vertical distribution of biomass burning
generated aerosols.’
Abstract: Since the abstract is a standalone description of the paper, all acronyms therein must be
resolved.
Line 5 Resolve MAX-DOAS acronym
Line 7 Resolve AERONET acronym
Line 8 Resolve AOD acronym
Line 11 Resolve TROPOMI and HYSPLIT acronyms
All acronyms must be resolved again in the main body of the manuscript.
Line 29 Resolve BB acronym
Line 38 Provide a reference for the statement on air quality in Uruguay.
Line 40 Suggest using ‘sunphotometer’ to be consistent with AERONET’s terminology.
Line 54-57 The statement on the variability of AERONET AOD and other parameters, and apparent
consistency with the detection of ‘this plume’ should be supported with observations. Likewise,
conclusions on satellite data analysis and trajectory simulations do not belong in the introduction
section. At this point in the paper, these statements read like unsupported speculations.
Line 73. What is the resulting vertical resolution?
Line 85. Add a reference on AERONET current version and aerosol data products.
Line 90. Resolve UV-VIS-NIR-SWIR acronyms.
Line 94 Resolve CCD acronym.
Line 100 Resolve VOC acronym
Line 106 Resolve TM5-MP and SCD acronyms.
Line 125. Add references on retrievability of aerosol vertical distribution by this technique.
Line 126. List specific AERONET aerosol retrieval results extrapolated to the matching windows and
discuss the extrapolation method.
-Which AERONET wavelengths were used in the calculation of Angstrom Exponent?
- For this application, AERONET shortest wavelengths (340 and 380 nm) should have been used.
- AERONET does not retrieve single scattering albedo at wavelengths shorter than 440 nm. How
was aerosol absorption accounted for in the UV region?
Line 160. CALIPSO or icesat-2 lidar data may have been available on this day. If so, how does it
compare?
Line 173. Can these results be confirmed with CALIPSO or icesat2 lidar observations? CALIPSO
data may be affected by the South Atlantic Anomaly. Icesat2, however, reports observations over
the analysis period in this paper at https://icesat-2.gsfc.nasa.gov/atmo-data.
Line 175. Discuss the expected lifetimes of the retrieved species. It may be relevant in this
analysis.
Line 182. Resolve QDOAS acronym.
Line 182. Discuss Tables 1 and 2 separately. They provide different information. Describe each
column of Table 1 in detail. No absorption cross-section data is shown in Table 2.
Line 189 The description of Figure 5 is incomplete. Only the top row is discussed. There is not an
adequate discussion of the bottom three rows. The figure caption should accurately describe what
is shown in each of the nine panels of the figure. If some of the data shown in this figure is not
relevant to the analysis, then remove it.
Line 193. Describe in some detail the mentioned color index classification algorithm. How is the
comparison of intensities used to discern clear from cloudy or partly cloudy conditions?
Line 198. Change the x-axis time representation in Figure 6 to the commonly used month-day
nomenclature. The figure caption should clearly indicate what is shown on each row from top to
bottom, and on each column from left to right.
Line 219. Sentinel 5 (S5P) is just the satellite name. The sensor’s name should also be included- AC3: 'Reply on RC3', Matias Osorio, 07 Apr 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
Biomass Burning detection data from MAX-DOAS inversion - dataset N. Casaballe https://www.fing.edu.uy/if/grupos/optica_aplicada/assets/
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Matías Osorio
Alejandro Agesta
Tim Bösch
Nicolás Casaballe
Andreas Richter
Leonardo Alvarado
Erna Frins
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(9466 KB) - Metadata XML