the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Large Spatiotemporal Variability in Aerosol Properties over Central Argentina during the CACTI Field Campaign
Abstract. Few field campaigns with extensive aerosol measurements have been conducted over continental areas in the southern hemisphere. To address this data gap and better understand the interactions of convective clouds and the surrounding environment, extensive in situ and remote sensing measurements were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted between October 2018 and April 2019 over the Sierras de Córdoba range of central Argentina. This study describes measurements of aerosol number, size, composition, mixing state, and cloud condensation nuclei (CCN) collected at the ground and from a research aircraft during seven weeks of the campaign. Large spatial and multi-day variations in aerosol number, size, composition, and CCN were observed due to transport from upwind sources controlled by mesoscale to synoptic-scale meteorological conditions. Large vertical wind shears, back trajectories, single particle measurements, and chemical transport model predictions indicate that different types of emissions and source regions, including biogenic emissions and biomass burning from the Amazon and anthropogenic emissions from Chile and eastern Argentina, contribute to aerosols observed during CACTI. Repeated aircraft measurements near the boundary layer top reveal strong spatial and temporal variations in CCN and demonstrate that understanding the complex co-variability of aerosol properties and clouds is critical to quantify the impact of aerosol-cloud interactions. In addition to quantifying aerosol properties in this data-sparse region, these measurements will be valuable to evaluate predictions over the mid latitudes of South America and improve parameterized aerosol processes in local, regional, and global models.
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RC1: 'Comment on egusphere-2024-1349', Anonymous Referee #1, 22 May 2024
This manuscript provides a comprehensive description of data collected in Argentina during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in 2018 and 2019. The subject matter is appropriate for publication in ACP, and the manuscript is generally well written and fairly clear.
This manuscript is largely descriptive, lacking substantial findings that expand the field. However, this is a very undersampled region of the world, and it is appropriate to have a paper that relies primarily on displaying and categorizing the data. The key scientific finding is that the aerosol over the Sierras de Córdoba (SDC) mountain range is highly variable, and that co-variability of aerosols and clouds is especially important in evaluating aerosol-cloud interactions in this region. The aerosol is extremely complex and variable, and it's difficult to draw many broad conclusions based on the type of sampling that was done (a single ground-based site and relatively limited aircraft sampling).
While the text is mostly clear, I found the figures to be lacking. Specifically, the color scales and line color choices used in all figures are not consistent with Copernicus guidelines, which ask for authors to use colors that can be read by most people with color vision impairments. These requirements are detailed at https://www.atmospheric-chemistry-and-physics.net/submission.html#figurestables. All figures need to be reworked with appropriate color choices and/or symbols on lines. The figures that show the flight tracks on a map are especially hard to read; please make the flight track symbols wider so that the color scale can be seen against the background contour lines and wind vectors.
Additional comments:
Tables 1 and 2: What is "BEASD"? Is this what is described on Line 194?
Line 141: Excessive significant figures.
Line 179: What is the size range of the miniSPLAT? This is important in the context of the wide-ranging size distributions.
Fig. 2e. This panel and similar in other figures showing particle number concentration might best be shown on a logarithmic scale--the variability in the UHSAS is difficult to see on this linear scale.
Lines 253 and 254. How do you define when NPF occurs? Isn't is pretty synonymous with "days that produce large numbers of ultrafine particles"?
Line 262. You speculate that increasing PM1 concentrations suppress the formation and growth of UFP. Calculating and presenting condensation sink (or even surface area) would support this conjecture.
Line 265. Change to "Concentrations of CCN are a function . . . ."
Line 268. What are the slopes of these correlations? There should be close to a 1:1 relationship at the highest supersaturation, at least.
Line 294. Aren't there local emissions of rBC from motor vehicles, especially diesel?
Line 324. Are the differences in the concentrations of larger particles on the low- and high-UFP days statistically significant? It's hard to tell just from looking at the graph. How different are they?
Fig. 4 (and Fig.14). It is very difficult to intuit much from size distributions plotted on a logarithmic y-axis. Small features are expanded, and large features are suppressed. The human eye and mind try to integrate the area on the plot, but this doesn't make sense on a logarithmic plot. If plotted on a linear scale, the number size distribution will emphasize which particle contribute to number, and the volume plot will show the significance of the larger particles. I feel this would be clearer and more clearly show the importance of these ultrafine and fine size classes to number and mass, respectively.
Line 368. Do you have a reference for transport by the low level jet?
Paragraph beginning on line 378. The interquartile *range* is not varying as described in the text. The IQR is the difference between the 75th and 25th percentile. The magnitudes of the 75th and 25th percentiles are varying as described, not the IQR.
Line 397. Fires emit SO2 and about half the rate as CO? That's a *lot* of SO2! Please provide a reference.
Fig. 7d. There is a data point off scale.
Fig. 8. Replace "pyridinum" with "pyridinium" in the legend.
Fig. 9b (and 10b). It might be more useful to plot the number of samples on a log scale.
Fig. 13. You point out the range of CPC and CCN values from during legs 3 and 21 at the bottom of the profiles, but it took me a while to understand that these were from the AMF site. Please mention this in the figure caption.
Fig. 14. They grey line is very hard to see. (And linear y-axes, please.)
Line 685. What is meant by "low anthropogenic emission regions". Low altitude? Or low emissions?
Line 694. Schill et al. (Nature Geoscience, doi:10.1038/s41561-020-0586-1) found that about 1/4 of accumulation mode particles in remote areas had a signature of biomass burning. This seems relevant to the discussion here.
Line 718. Just as flow over the SDC moves PBL air into the FT, you may want to mention here that the trajectories suggest that you will see PBL air from upstream of the Andes lofted into the FT where you measured, helping explain some of the observed variability.
Line 812: "Around" misspelled as "arounc".
Fig. S10. If statistics support it, it would be more interesting to see the miniSPLAT particle types plotted averaged over altitude bins rather than plotted as a function of time, so we could see the difference between PBL and FT particle abundance. Alternately, plot altitude as a line graph on the right axis.
Citation: https://doi.org/10.5194/egusphere-2024-1349-RC1 -
RC2: 'Comment on egusphere-2024-1349', Anonymous Referee #2, 25 Jul 2024
General comments
The authors present the results of the CACTI campaign conducted in the Córdoba area (Argentina), in which a valuable amount of information on aerosols and meteorological variables was collected. The study area belongs to one of the typically “under-characterized” regions in relation to its air quality data, making the production of these data extremely useful for both local assessment and global science. However, since all of these data have been previously published (e.g., in “Deep Convection Initiation, Growth, and Environments in the Complex Terrain of Central Argentina during CACTI” by Feng et al 2022, published in a specific journal of the American Meteorological Society, RELAMPAGO-CACTI: High Impact Weather in Subtropical South America) their publication here does not add value to the manuscript. The value of this paper lies in the analysis of the spatio-temporal variations of aerosols and in the identification of the role of emission sources, suitable for publication in ACP with minor revisions, as detailed below.
Specific comments:
Interestingly, the evaluation presented with CAM-Chem of the episode that took place between November 11 and 13, where the transport of pollutants from the biomass burning in Amazonia to the monitoring site is detected due to the occurrence of a low-level jet, but, at the same time, this event is not distinguishable at the surface due to the recirculation on the western side of the plume. It would be interesting to understand if this is a specific circumstance of that day, or if it is related with the complex geography of the site. As expressed by the authors throughout the paper (e.g., in line 430) there were other circumstances where the site was influenced by biomass burning. What was the relationship in those cases between the pollutant levels at height and surface levels? Please expand on the assessment of the effect that low-level jets have on surface concentrations, which is a long-standing scientific question in the region.
The reason for choosing December 3 to show the spatial and temporal variability of aerosols is not clear. What happened on that day? In Figure S6 of the supplementary material, it is noted that for that day CO concentrations are particularly low, and in Figure S3 that it is a day with few clouds. Did these circumstances play a role? Since it is here that the large variation in aerosol properties is shown, more detailed explanation is needed to understand why the December 3 assessment is considered representative of the entire period (and location).
Technical corrections
- The authors present the evaluation of a sub-period of the CACTI campaign: the campaign took place between October 2018 and April 2019. On the other hand, in lines 153-154 they indicate that the G-1 aircraft collected data between 4 November and 8 December, to finally analyze data from 23 October to 16 December, as presented in Figure 2. Please clarify the rationale for evaluating a sub-period of the campaign, and clarify from where the data were taken at altitude after 8 December.
- In section 3.2 called “Sources of aerosols and trace gases observed on the ground”, in the first part the sources are evaluated with surface data (lines 354-391), but in the part where CAM-CHEM is used (lines 411-420) the data at altitude measured with the G-1 are evaluated. In section 3.2, called “Aircraft measurements, the vertical profiles are actually presented. It may be desirable to simply change the titles to be more in line with what is presented.
- Figure 2 is too small. It is where the surface results and those measured with aircraft are combined, and based on this figure some relevant conclusions are presented that could not be seen in this small representation:
1.1) The correlation between precipitation and low PM1 concentrations is not clearly seen.
1.2) What is stated in lines 258 and 259: “Since gas-phase aerosol precursors preferentially condense on larger particles, higher PM1 concentrations during period A suppress UFP formation and growth (Fig. S2g)” is not seen. For example, it appears that on October 28 there was rain and yet the CCN for supersaturations of 0.1% and 0.2% does not decay.
1.3) It also does not lead to visualize what is stated in lines 251-254 : “temporal variations in aerosol number distributions (Fig. 2d) and total aerosol number concentrations (Fig. 2e) reveal that new particle formation (NPF) events occur on many days producing large numbers of ultrafine particles (UFP, diameter < 50 nm)”.
- In Figure 9 the top headings are confusing: (1) the top of 9 (a) says “Particle concentrations” and refers to “particle number concentrations”; (2) the top of 9 (c) refers to the difference between ultrafine (> 3 nm) and fine (> 10 nm) condensation particle counters (CPCs). For some reason they put CPC with u subincident to those smaller than 3nm and CPC to those larger than 10 nm. Maybe putting 3um<CPC<10um would be enough.
- Line 423: confuses this evaluation with what is presented in Figure 2b, where for November 11 and 12 it is observed that there is practically no OM, coinciding with the fact that PM1 is very very low. However, line 523 indicates that 54% corresponds to OM. Perhaps this is an erroneous interpretation (line 423 refers to the average of the whole period?), please clarify.
- Figure 5 on the right shows a set of points in gray color that are not explained in the text, please clarify or modify the figure.
- Biogenic sources emit very little BC relative to total OM, but it is inaccurate to say that they do not emit BC (correct line 365).
- The authors evaluate the numerous observations to find clues that help to understand the process of aerosol formation and growth. For this purpose, they decide to divide the evaluation into periods called A, B and C. This decision is unclear because it masks the understanding of the impact of individual situations. Although the authors indicate that “rainy days divide the campaign into three periods” (line 741), this reviewer notes that in all three cases there were circumstances with and without rain. Please add a short paragraph clarifying the reasons why the selection of these 3 particular periods adds substantive information to the spatio-temporal assessment of the aerosols in the region.
Citation: https://doi.org/10.5194/egusphere-2024-1349-RC2
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