the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Oct 2024
The evolution of aerosols mixing state derived from a field campaign in Beijing: implications to the particles aging time scale in urban atmosphere
Abstract. The mixing states and aging time scale of aerosol particles play a vital role in evaluating their climate effects. Here, we identified four different real-time mixing patterns of size-resolved particles using the field measurement by a humidity tandem differential mobility analyzer (H-TDMA) in the urban Beijing. We show that the particles with external, transitional and internal mixing state during the campaign account for 20–48 %, 17–24 % and 27–56 % respectively and the fraction highly depends on particles size. The diurnal variation of the mixing states of particles in all sizes investigated (40, 80, 110, 150 and 200 nm) present an apparent aging process from external to internal mixing state, typically spanning a duration of approximately 5–8 hours from 8:00–10:00 to 15:00–17:00. Additionally, the results illustrate that high ambient temperature during daytime or more humid atmosphere accelerates the aging process of aerosol particles, leading to the particles from external to internal mixing on both clear and cloudy days. Also, with the evolution of particulate pollution, the aerosol particles become more internally-mixed. Our result implies that those fine aerosol particles experience aging through both the photochemical process and aqueous growth in the polluted atmosphere of urban Beijing. Furthermore, through a comprehensive review of the aging timescale of particles adopted in current models and derived from observations, we show the great discrepancy between observations and models, highlighting the importance to parameterize their aging time scale based on more field campaigns.
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RC1: 'Comment on egusphere-2024-2999', Anonymous Referee #1, 13 Nov 2024
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This study uses H-TDMA to identify in real-time the four mixing states of aerosols across different particle sizes, proposing changes in the transition from external to internal mixing under various conditions. Additionally, the study explains the possible causes and diurnal variations of the aging process associated with the transition of aerosol mixing states. The study finds significant differences between observations and models regarding aerosol aging timescales, suggesting that the models need improvements. This research offers innovative insights, providing valuable observational evidence for understanding the evolution of aerosols in the atmosphere. The study also reviews a large amount of observational and simulation results, which are highly useful for further research in this field.
When considering the mixing states of different particle sizes, how can we distinguish the impact of aging from smaller aerosols on the internal mixing fraction of larger particles, as well as the influence of primary emissions? Clarifying the relationship between these two factors will help better explain the causes of mixing state changes across different particle sizes.
The paper presents many interesting results; however, most of the results only present phenomena or conclusions without providing reasonable explanations or sufficient interpretation of the data, which may lead readers to question whether the results are justified.
L137: You explain that σ cannot represent the mixing state of Beijing aerosols due to the influence of significant anthropogenic emissions. It would be helpful to provide a more detailed explanation of the relationship between anthropogenic emissions and mixing state, and the specific effects on σ and κ. You claim that σ alone is insufficient to characterize the mixing state of Beijing aerosols, but the relationship between the particle size distribution of the σ value and the vegetation-covered areas is not fully explained. Shouldn't you check whether the differences are due to methodological variations or regional characteristics?
L148: The sources of 150 nm and 200 nm aerosols mentioned here—are they primary emissions from traffic and biomass burning, or secondary aerosols? If they are from primary emissions, they should be similar to the 40 nm aerosols. Moreover, 80 and 110 nm aerosols should continue aging and form 150 and 200 nm aerosols. The aging of this group of aerosols should be more advanced—why is the influence of this aged aerosol group on the internal mixing fraction not reflected?
L176: While the conclusion that the standard deviation of κ-PDF alone is insufficient to characterize the mixing state in polluted regions may be correct, could you further explain why the relationship between κ and σ exhibits contrasting characteristics for different particle sizes?
L185: Earlier, you mentioned that larger particles may be related to traffic and biomass emissions, but here you claim that the peak for 40 nm particles is related to traffic emissions, which seems inconsistent with previous statements.
L190: If the large amount of external mixing in the early morning is due to fresh emissions, what is the source of the external mixing aerosols at night?
L214: Is the proportion of internal mixing state reduced with increasing humidity? Does this suggest that aerosols undergo less aging in high humidity conditions? This appears to contradict the conclusion in line 217.
L245: There is insufficient reliable evidence to support that this is a new particle formation process. I recommend not using this as a basis to explain the size characteristics of the mixing state.
L256: Clearly, the aging times of aerosols in different cities vary greatly. Given such large differences, how representative is your study?
L280: You point out that the observed aging time is similar to the aging times used in current models. Does this contradict the general conclusion that the aging timescale in models is inaccurately represented? Furthermore, do simulation results show variations in aging timescales under different environmental and pollution conditions? Can these results be directly compared to observations? You may also consider including a range for the simulated aging times, as this comparison would be more scientifically rigorous.
Citation: https://doi.org/10.5194/egusphere-2024-2999-RC1 -
RC2: 'Comment on egusphere-2024-2999', Anonymous Referee #2, 17 Dec 2024
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In this manuscript, the authors show an analysis of of H-TDMA measurements of aerosol in Beijing, and they attempt to identify the aging timescale of the transition of freshly emitted low-hygroscopicity aerosol to high-hygroscopicity aerosol and some factors that affect this aging timescale. The authors correctly identify this transition as a pertinent area of study, and they show some good insights, including that the standard deviation of the hygroscopicity yields different information that counting the number of hygroscopicity modes. However, there are some issues in the authors’ analysis of the effects of temperature and relative humidity, their calculation of the aging timescale, and their comparison with other studies that require improvement before I can recommend this manuscript for publication. I will go into more detail on these issues below.
There is unfortunately an existing ambiguity in the literature regarding the terms “externally mixed”, “internally mixed”, and “aging” or “aged”. This has led to confusion, with different authors using different definitions and making comparisons across studies of different physical processes without identifying these differences. I therefore request that the authors make clear in the abstract and the conclusions that the aging timescales refer to hygroscopic aging. I also suggest that the authors adopt the terminology suggested by Riemer et al. (2019) regarding internal mixing and external mixing: these are properties of aerosol populations, rather than of individual aerosol particles. I strongly believe that the paper will be clearer and easier to understand if the authors are precise in their use of terms, and that the current terms leave an ambiguity that can result in reader confusion.
This is most notable in the naming of the “LH External Mixing” category: by the Riemer et al. (2019) nomenclature, the term “externally mixed” implies a population of aerosol particles with different chemical compositions. However, the hygroscopicity PDF shown in the leftmost panel of Fig. 1 is fairly uniformly non-hygroscopic. If the aerosol is assumed to consist of black carbon and low-hygroscopicity organic material, then the population may very well be internally mixed: each particle has the same composition of low-hygroscopicity material, consisting of black carbon partially or completely coated by low-hygroscopicity organic material. For the population to be externally-mixed, there need to be additional set(s) of aerosol particles with a different chemical composition. If the κ‐PDF is to be the evidence of this, then there must be at least two peaks with different hygroscopicities. The “LH External Mixing” mode can certainly be described as low-hygroscopicity, but not as externally-mixed. Given the authors’ measurement location, the smaller particles in this mode can likely be described as “LH freshly-emitted”, although it is not difficult for me to think of processes (coagulation with other low-hygroscopicity particles, condensation/evaporation of low-hygroscopicity organic material) that could alter the particles without greatly increasing their hygroscopicity. To use this term, the authors may need to justify that the larger particles in this mode are not from long-range transport of biomass-burning aerosol or desert dust. Alternatively, it would be more precise but less evocative to term this “LH unimodal”.
The ambiguity in the literature as to what constitutes “fresh” aerosol, “aged” aerosol, and what transition is being described by the “aging” timescale is especially pertinent for the comparison with the literature values of the aging timescale. In many of the models cited in Table S1 and Fig. 8, there is a convolution of the change in radiative properties (i.e. the absorption enhancement on thickly-coated black carbon vs. bare black carbon) and the change in the hygroscopic properties (low-hygroscopicity black carbon, primary organic aerosol, and dust becoming partially or completely coated in hydrophilic material) (Stevens and Dastoor, 2019). These two processes frequently are not represented independently, in part due to constraints on computational resources. However, the optical and hygroscopic properties do not necessarily co-vary; it is possible e.g. for black carbon to be thickly coated by low-hygroscopicity organic material, especially as this primary organic aerosol is frequently emitted by the same sources as black carbon. This ambiguity in “aging” exists in observational and experimental studies as well. I think that the authors are clear in referring exclusively to hygroscopic aging timescales for the modelling studies (despite the convolution I just described), and I appreciate the authors noting the measurement method for the experimental and observational studies mentioned in Table S1 and Fig. 8. However, I would also like them to make explicit what was the definition of “aged” used by each of the experimental or observational studies, especially regarding whether it was based on hygroscopicity, CCN activation, radiative properties, or black carbon mass fraction. These different definitions will yield different aging timescales.
There are additional problems in comparing the aging timescale derived in this study with those used in models and other studies: the authors are examining changes in hygroscopicity of a single size range, when the processes that would age the “LH External Mixing” mode from low-hygroscopicity to high-hygroscopicity, being coagulation and condensation, would also increase the size of the particles, potentially moving them from one size range to the next. Fresh nucleation and growth of ammonium-sulphate-nitrate-organic aerosol will create a mode of highly-hygroscopic aerosol; if the number of these freshly-nucleated particles greatly exceeds the number of “LH External Mixing” particles (possibly aided by the low-hygroscopicity particles growing out of this size range), then it will appear that the low-hygroscopicity particles have aged into a highly-hygroscopic particles, when few of these particles contain any low-hygroscopicity material. It appears to me in Fig. 5 and Fig. 7 that the peak in the fraction of internal mixing is later for the 110 and 150 nm particles than for the 40 and 80 nm particles, which may support growth of the internally-mixed mode. There is also an issue of deriving lagrangian properties from single-location measurements: if the aerosol required e.g. six hours to become internally-mixed, then the “internally mixed” aerosol would have been emitted six hours prior to measurement. For an example wind speed of 10 km / hour, the “internally-mixed” aerosol would therefore have been emitted 60 km away, possibly with a different source profile than the “LH externally mixed” mode which is assumed to be freshly and locally-emitted. Additionally, the authors’ method restricts the derived aging timescale to be less than 24 hours at maximum. The authors should at least discuss these difficulties in the interpretation of their aging timescale.
Given the strong association between temperature and time of day, it is difficult to tell if there are any independent associations between temperature and the mixing state or hygroscopic properties that are not best explained by diurnal cycles in emissions and the downward shortwave radiation that drives photochemistry. Aerosol nucleation and condensation processes that drive hygroscopic aging can proceed more quickly under colder temperatures, not warmer temperatures, assuming that the actinic flux is constant. This criticism also applies to the analysis vs. relative humidity which also has a clear diurnal cycle. The authors therefore cannot draw any conclusions on the relationships between aging processes and temperature or relative humidity based on their current analysis. The authors should correct for this either by performing daily averages before analysing the data in this way or by removing the diurnal cycle before performing this analysis.
Specific comments:
lines 97-99: The authors mention that the instrument was described previously. Was this particular measurement campaign described previously? Even if it was, the authors should still state where in Beijing the measurements were taken. On the roof of one of the authors’ institutes? Co-located with an existing air pollution measurement site? Briefly, what is the source of the other measurements presented in this study (T, RH, PM1, chemical composition)? Were they measured by the authors or provided by another source? Additionally, can the presence of desert dust, especially in the larger size ranges, be excluded based on the chemical composition measurements? Or might long-range transport of dust be a significant contributor to the low-hygroscopicity particles?
line 25: “with the evolution of particle pollution…” It is not clear what the authors mean with this sentence. Are they merely saying that particles evolve from being externally-mixed to being internally-mixed with time?
lines 76-79: “aerosols containing two or more components may also exhibit external mixing” Since external mixing is defined as different aerosol particles having different chemical compositions, the aerosol population must have two or more components for external mixing to occur.
lines 107-109: Should I understand the authors to mean that there must be two hygroscopicity modes, and one of the mode peaks must be at κ < 0.1 and the other mode peak at κ > 0.1? Does it matter which of the two peaks is greater? This was not clear to me.
lines 109-110: Is it required that one of the modes in the trimodal category have κ < 0.1? Further, if there are 2 or 3 modes where all of the peaks have κ > 0.1, how would this be classified? Were there measurements that did not fit into any of the four categories?
line 122: I assume that the authors mean “in each of the five particle sizes”. The sentence as written could also be interpreted as “between the five particle sizes”.
lines 129-133: Do the authors have any thoughts as to a physical explanation for the different σ-κ relationships between different size ranges?
lines 131-133: It’s not clear to me what the authors are trying to communicate with the second half of this sentence. Are you simply trying to highlight that “internally-mixed” cluster for particles >100 nm in size has high hygroscopicity and low standard deviation in hygroscopicity?
lines 146-149: My reading of Ren et al. (2023) is that they associated transportation sources (traffic, in their words) with small particles (<100 nm), which is consistent with my previous understanding that vehicular emissions yield primary particles that are <100 nm. I don’t recall Ren et al. (2023) discussing biomass burning at all. Do the authors have the correct reference here?
lines 212-219: Looking at Fig. S4, 15 C temperatures seem to be rarely sampled, and possibly only during 3-6 am on clear days. Is it possible that all of the associations with 15 C temperatures are due to a sampling artifact, a small number of cases with coincidentally high numbers of hydrophilic aerosol and low temperatures? I note also that relative humidities > 60% seem only to occur during hours when temperatures are particularly low. Could a sampling bias also be affecting the relationships shown with relative humidity?
line 239: While the enhancement is less for cloudy days, it is certainly notable. For particles larger than 40 nm, the enhancement on cloudy days is nearly as large as for clear days.
lines 239-242: The first part of this sentence is confusingly written. I would suggest phrasing as “The proportion of particles with internal mixing state usually increased by less than 50 percentage points between the period before 9:00 and during 12:00–17:00 ”.
lines 331-332: This is an incomplete sentence.
Fig. 7: “The start time [...] of particle aging process was selected when the proportion of particles with internal mixing state is closest after sunrise”. I am not sure what the authors mean by this. Do the authors mean the hour when the proportion in the “internally mixed” state is most similar between the cloudy and clear cases? If so, then I don’t understand why this was the criterion chose, as opposed to e.g. using the minimum between sunrise and noon, or using the maximum in this time range of the “LH externally mixed” state.
Riemer, N., Ault, A. P., West, M., Craig, R. L., and Curtis, J. H.: Aerosol Mixing State: Measurements, Modeling, and Impacts, Rev Geophys, 57, 187–249, https://doi.org/10.1029/2018RG000615, 2019.
Stevens, Robin, and Ashu Dastoor. ‘A Review of the Representation of Aerosol Mixing State in Atmospheric Models’. Atmosphere, vol. 10, no. 4, Mar. 2019, p. 168, https://doi.org/10.3390/atmos10040168.
Citation: https://doi.org/10.5194/egusphere-2024-2999-RC2
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