the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Feb 2025
The influence of Amazonian anthropogenic emissions on new particle formation, aerosol, cloud and surface rain
Abstract. Anthropogenic emissions have been shown to affect new particle formation, aerosol concentrations, and clouds. Such effects vary with region, environmental conditions and cloud types. In the wet season of Amazonia, anthropogenic emissions emitted from Manaus, Brazil can significantly increase the cloud condensation nuclei (CCN) concentrations compared to the background of mainly natural aerosols. However, the regional response of cloud and rain to anthropogenic emissions in Amazonia remains very uncertain. Here we aim to quantify how new particle formation, aerosol concentration, cloud and rain respond to changes in anthropogenic emissions in the Manaus region and to understand the underlying mechanisms. We ran the atmosphere-only configuration of the HadGEM3 climate model with a nested regional domain that covers most of the rainforest region (720 km by 1200 km with 3 km resolution) under several regional emission scenarios. The 7-day simulations show that, in the areas that are affected by anthropogenic emissions, when aerosol and precursor gas emissions are doubled from the baseline emission inventories, aerosol number concentrations increase by 13 %. The nucleation rate that involves sulfuric acid generally increases with pollution levels. However, near the source of the pollution, nucleation is suppressed due to high primary aerosol emission, resulting in smaller nucleation and Aitken mode aerosol number concentrations. We also found that doubling the anthropogenic emission can increase the cloud droplet number concentrations (Nd) by 9 %, but cloud water mass and rain mass do not change significantly. Even very strong reductions in aerosol number concentrations by a factor of 4, which is an unrealistic condition, cause only 4 % increase in rain over the domain. If we assume our simulation has fine enough grid resolution and an accurate representation of the relevant atmospheric processes, the simulated weak response of cloud and rain would imply that the Amazonian convective environment is non-linear and resilient to the small changes in Nd that occur in response to localised anthropogenic aerosol emissions.
Competing interests: One of the authors is a member of the editorial board of Atmospheric Chemistry and Physics.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.- Preprint
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RC1: 'Comment on egusphere-2025-132', Anonymous Referee #2, 18 Mar 2025
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This manuscript presents a modelling investigation into the role of anthropogenic pollution from Manaus, Brazil, on CCN, clouds and precipitation downwind in Amazonia. They do this based on 5 days of simulations compared to measurement data collected from aircraft during the GoAmazon campaign in March 2014/15 (wet season). The setup includes a regional model embedded in a global model with horizontal resolution of 3 km, making it suitable for explicit representation of deep convection. They present sensitivity studies and their implications for particle number concentration, droplet and ice crystal concentrations and rainfall. Overall, they conclude that the impact of regional emissions from Manaus is moderate in terms of both aerosol number and cloud droplet number concentration and low for cloud water mass and rain. The paper is mostly well written, interesting and it is well within the scope of ACP.
I have two more general comments and then detailed comments below:
- Overall, the analysis in the paper focuses on high sulfur regions. I would expect NPF to have a larger impact in the regions where the plume is diluted somewhat into the cleaner surroundings and I am wondering why the research question is limited to the in-plume conditions? I am not suggesting that this needs to be changed, but rather that this could be discussed.
- This model description section (2.2.) doesn’t read very well in my opinion. There’s quite a bit of repetition and the information is not well structured. For the aerosol description specifically, I would suggest having a separate paragraph on BVOC oxidation products and yields, then introduce the different nucleation rates (is it correct that there is no sulfuric acid-water nucleation rate btw?), then say something about the overestimation in the models and where you turn off the nucleation rate.
The cloud microphysics scheme also deserves a bit more detail. How is rain initiated for example? Ice formation is mentioned in the discussion/results, but not in the description.
See detailed comments below.
L16: I think it would help if you specify what is meant by non-linear here.
L58-59: The meaning is somewhat unclear to me here. Consider rewording.
L105-107: The sentence does not flow well; the order of information seems slightly off. I suggest splitting it in two with the first containing information about the height and the second about the number concentrations.
L127: Is 3-km resolution enough to resolve all types of convection? What about shallow convection?
L136-137: This is a bit unclear: “i.e. collision and coalescence of aerosol-containing cloud droplets with some of the aerosol assumed to be deposited to the surface.”
L154: What does "that include vegetation" mean? Also, why are these not interactive? What about diurnal variability?
L155: Are all primary aerosols emitted at the same size?
L171-172: “The ability of biogenic vapour to nucleate depends on vapour volatility.” I feel like this should be followed by a statement about how the model treats the formation of ELVOCs/HOMs.
L173: “NPF in the UKCA model produces aerosol particles up to 3 nm in diameter.” Unclear what the implication is. Also, below you only mention parameterizations giving 1.7 nm particles. Do you mean that you parameterize growth up to 3 nm in diameter? Which parameterization do you use for this?
L175: Why below 100 m altitude? It’s only mentioned earlier that the model overestimates NPF in the free and upper troposphere?
L178: I don’t quite follow here. You find that even when you turn it off above 1 km and below 100 km, NPF is still the dominant source?
L181: This sentence seems a bit out of place. Move to earlier?
L184: The yields for HOM1 should be mentioned here?
L184: “Here, monoterpene is a type…” Everywhere, not just here :) monoterpene is a class of BVOCs, and I guess it is treated as one tracer by the model?
L195: “HOM2 is oxidized […]” maybe instead “HOM2 is the oxidation product of monoterpene by OH and O3.”
L195: “a steady-state approximation”. Please explain.
L197: Repetition.
L204-208: Do you mean that you include this in your survival probability calculation to the smallest nucleation mode? Do you use Kerminen and Kulmala (2002, https://linkinghub.elsevier.com/retrieve/pii/S002185020100194X) here? Maybe state explicitly.
L255-256: I would say maybe that for N100 the model mostly misses the rapid variability though? I.e. it only captures the large drops towards e.g. the end of the days some days.
L270: Same as above.
L272: I don’t think you describe the CTL-Bn simulations and H2SO4-H20 nucleation above in the description. It’s a bit unclear to me as well if H2SO4-H20 nucleation is only turned on in this simulation and if you have the same restrictions in the vertical (i.e. turned off above 1 km).
L285: I assume this is gas phase only? In the sentence before you write that these regions are defined “define according to the total sulfur species” which could be thought to be gas plus particle phase. I suggest clarifying this.
L336-339: I have a hard time following this. I suggest including an equation to make it clear.
L381-382: In addition to H2SO4 and nucleation rate going down, condensation sink goes down as well. I would have thought that the H2SO4 and nucleation rate went down due to high condensation sink, but this cannot be the explanation here?
L402-403: Why are the responses to the 0.25xaero and the 4xaero so symmetrical? Would you not expect some leveling off of the impact at high aerosol concentrations due to entering the updraft limited regime?
Fig. 8: The resolution of the arrows is quite bad.
L417-419: I suggest checking if these differences are significant and if not potentially removing this discussion.
Fig. 10: I suggest hatching insignificant areas here.
L438-440: How is rain initiated in the model? I think this is not covered in the model description?
L474: Is this out of the total or of the ones added regionally (i.e. CTL-offREG)?
L479: This sentence seems a bit unmotivated. Consider revising.
L498: Again, if this is the reason, why does also the condensation sink decrease then?
L510: Check this sentence, there’s repetition.
L516: Why would heterogeneous ice nucleation not being interactive weaken the “relationship” between ice and droplets? Is “interactively correlated” the right term here? I would say connected for example?
L527-528: Could you specify how a lack of prognostic supersaturation lead to a weaker effect?
L528-530: I don't understand these two sentences or what the implications are for your result. In the last sentence you seem to contradict yourself?
L531: Is this is just because your changes in emissions change the CCN concentration much much less than a factor of 4? Do you think it would be interesting to see the change in Nd plotted against the CCN concentration (or N100) in each of the simulations to see if it's completely linear?
L554: Again, I am not sure correlation is the right word here.
L557-558: “[…] of background aerosols even without anthropogenic emissions in the regional domain and the small perturbations of Nd as a result of small changes in aerosols.” The end of this sentence seems strange to me. Consider revising.
Citation: https://doi.org/10.5194/egusphere-2025-132-RC1
Data sets
Modelled data Xuemei Wang, Ken S. Carslaw, Daniel P. Grosvenor, and Hamish Gordon https://doi.org/10.5281/zenodo.7213371
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