the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Nov 2024
Advances in characterization of black carbon particles and their associated coatings using the soot particle aerosol mass spectrometer in Singapore, a complex city environment
Abstract. Atmospheric black carbon can act as a short-lived climate forcer and carrier of toxics. This work aims to utilize aerosol compositions detected by a soot-particle aerosol mass spectrometer to advance our understanding of emission and atmospheric processing of refractory BC (rBC) in Singapore. Positive matrix factorization analysis of rBC and organic aerosols (OA) (PMFbase) identified two local traffic factors with large differences in rBC content and coating thickness, and two secondary OA (SOA) factors impacted by local chemistry and/or regional transport (less-oxidized oxygenated OA (LO-OOA) and more-oxidized OA (MO-OOA)). Including metals in the PMF (PMFmetal) improved the quality of source apportionment significantly. An industrial and shipping influenced OA separated from traffic emissions was strongly associated with heavy metals (e.g., V+ and Ni+) that might pose higher potential risks to human health. Two biomass burning-influenced OA (BBOA) factors with different degree of oxygenation were also identified. Although the aged-BBOA component was highly oxidized, its strong association with K3SO4+ differentiated itself from other background SOA. Integration of both metals and inorganic aerosols (IA) into the PMF (PMFall) was found to provide further insight into the origin of SOA coatings and their chemical processing. PMFall identified an additional aged-BBOA component that was associated with nighttime IA and organo-nitrate formation. Furthermore, PMFall revealed concurrent LO-OOA and nitrate formation during daytime, whereas photochemical production of MO-OOA was linked to acidic sulfate formation, indicating the importance of investigating interaction between SOA and IA formation and their mixing state in complex city environments.
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RC1: 'Comment on egusphere-2024-3240', Anonymous Referee #1, 20 Dec 2024
This manuscript describes analysis of soot particle aerosol mass spectrometer (SP-AMS) measurements conducted in Singapore during a ~2-month period. The manuscript systematically explores and demonstrates the application of PMF to the SP-AMS data. The analysis starts with a more traditional approach of using organic aerosol (and refractory BC, rBC) signals and then sequentially adds in metal signals and then inorganic signals, all from the SP-AMS spectrum. With the traditional approach, 4 meaningful source factors are resolved. With the addition of the metals, another 3 factors are resolved, an aged biomass burning and a fresher primary biomass burning factor, as well as an industrial and shipping related factor. Addition of the inorganic signals yield one more factor, a biomass burning-influenced OA factor associated with different inorganic fragments. Various additional formulations are used to provide support for the meaningfulness and robustness of the PMF separations, e.g. size diurnal cycles, size distributions, wind and back trajectory analyses, as is typically required for testing PMF results. Apportionment of the rBC among the factors and the contributions of the factors to overall composition are reported. The manuscript is primarily a methods demonstration, with a few relatively generalized observations of aerosol chemical and source processes.
The paper is well-organized and clearly written. It will make a valuable contribution to the body of literature of aerosol composition analytical methods. I liked the way the expansion/exploration of the additional PMF chemical inputs were discussed sequentially, building on the previous results. I also particularly found Fig 12 to be a valuable in putting these new and previous BBOA factor separations in context. I recommend publication in EGUsphere with a few minor suggested changes.
A few general comments. While I understand that the primary focus of this work is methods demonstration, it would seem useful to provide more of a general presentation of previous aerosol measurements conducted in this region for context. There are a few statements and references that are sprinkled in at points in the manuscript to compare to relevant observations. However, it was difficult as a reader not familiar with this region to get a sense of what is known about aerosol concentration, composition, and sources in this region. Also, during particularly the 1st half of the manuscript, there were a number of instances where the discussions and interpretations were a bit overreaching or protracted discussion of details that may not add any additional information. Those probably at unnecessarily length to an already fairly long manuscript and water down the more interesting and insightful information in this manuscript. See for example the detailed comments below on nitrate composition (P16, L25), diurnal cycles of O/C (P15, L8-11), and ions fragment size distributions (P17, L25-30). I encourage the authors to review the paper and trim any unnecessary text and discussions along those lines.
Detailed Comments:
P7, L8-9. Incomplete sentence
P8, L20-21. Would be useful to explain the methodological reasoning for downweighting K+ and upweighting Rb+, V+, and Ni+. I.e. how does this improved separation, what happens if you keep them at their native S/N? Of if this was explored more systematically in the papers referenced, perhaps briefly state how it can help. These types of details/discussions could be quite useful for others conducting “combined” PMF” as indeed this manuscript is in large part a methods demonstration.
P8, L25-26. “Sulfate fragments were downweighed by a factor of 3 due to their relative strong intensities.” For PMF, it’s the S/N, not the signal that controls the influence on the factorization. I.e. if intensity (signal) is high but so is the uncertainty, it’s not necessarily going to have a strong influence. This is a useful paper, that I think future practitioners will read, so import to be precise with language.
P8, L29. “FPEAK” not “F peak”
Fig. 2e pie chart. In the time series it appears that Cl is on average greater than SO4, however it is not visible in the pie chart, while SO4 is?
P11, L10-11: Here quantitatively comparing SP-AMS rBC to aethalometer. It would seem key to discuss the absorption coefficients applied to the AE33 data (to convert optical absorption to mass) for comparison to be most meaningful.
P15, L8-11: O/C values of 0.38-0.39 on average during the morning and evening rush hours is a lot higher than typically HOA O/C ratios (typically <0.1), at least for standard vaporizer AMS. Authors should reconsider this statement or provide context for differences for the SP-AMS (perhaps discussed in more detail later, but this would seem to stand out as written here as a dubious statement for most readers with some familiarity of AMS OA analyses).
Similarly, in P15, L17-19 the higher evening O/C (~0.43) are interpreted as “suggests that the OA coatings were largely contributed by oxidized organic species”. Together these statements suggest that a shift from 0.38-0.39 to 0.43 indicates a shift from mostly HOA to mostly OOA coatings. That seems like a big exaggeration of what appears to be a fairly subtle shift between degrees of moderately oxidized composition. Or perhaps I’m misunderstanding the intention, in which case consider making the point more precisely.
P16, L1-7. The authors reference to the Cubison et al background value (0.3%) determined for a standard vaporizer AMS, but then discuss enhancement factors for oxygenated OA and levoglucason, as well as point to the f values in this data (Fig. 6). What are those enhancement factors referenced to? Cubison 0.3% or some revised LV-SP-AMS background? Can the authors report the typical background fC2H4O2+ for non-BB OA for the LV-SP-AMS, assuming that’s what the factors are being reference to? Adding a horizontal line in Fig. 6d for background f’s for LV SP-AMS might be useful as well.
P16, L25. “NO3- and Cl- have elevated levels over midnight…” Does Fig. 6d really support elevated NO3? Nightime NO3 doesn’t seem higher than the average values and any diurnal cycles in the average look quite subtle. And given the variably/range (shown in swaths), those features barely seem significant. This appears to be another example of where the authors are reaching to draw conclusions/speculations from very subtle features.
P17, L25-30: speculation on the m/z 43, 55, 57 peaks being CxHy+ or CxHyOz+ peaks. Those peaks can be separated peaks using the HR PToF, assuming the .p files were saved. Otherwise, in this section, discussion of those ions doesn’t seem to add any additional information. E.g. the distribution of m/z 44 and laboratory measurements are used to speculate what the composition of the m/z 43 is? So then, what does showing/discussing the measured m/z 43 distribution add?
Sect 3.3.1 POA from fossil fuel combustion. This is interesting. Can the authors discuss why they think the rBC-rich and HOA factors were separated with PMF (case base-4) and what information that separation can provide? It is noted that both factor sources presumably come from combustion, and the diurnal cycles, NWR and PSCF plots are very similar. But clearly, there must be some significant difference in the time series from some changes in atmospheric sources/processes, instrumental drifts, etc.
Fig. 8: should “Cother” be “C Other” in MO-OOA legend?
Figure S6. “The NWR plots of factors identified by PMFbase-4.” Would be helpful to point out the differences for these vs the plots in Fig. 8 (different WS resolutions, etc) in the caption.
Fig 11: Yellow metals bar color missing from legend
P29, L6: Should be Fig 9, not Fig 7
P34, L4: Need “an” before “aged” or make “component” and verb made plural.
P34, L13: hands shouldn’t be plural
Citation: https://doi.org/10.5194/egusphere-2024-3240-RC1 -
RC2: 'Comment on egusphere-2024-3240', Anonymous Referee #2, 22 Dec 2024
This study investigates the emission sources and atmospheric processing of refractory black carbon (rBC) in Singapore using a soot-particle aerosol mass spectrometer. By applying multiple positive matrix factorization (PMF) approaches, the analysis identified distinct sources of rBC. Incorporating metals in PMF distinguished industrial and shipping emissions linked to heavy metals, while integrating inorganic aerosols revealed aged biomass burning aerosols and interactions between secondary organic aerosols (SOA) and inorganic aerosol formation. These findings highlight the effectiveness of diverse PMF approaches in resolving complex urban aerosol sources and processes.
The paper is well-organized and makes a valuable contribution to the field of aerosol source and property investigations. Additionally, it offers significant insights into the potential of expanding the PMF method by incorporating metals to better explore and detail aerosol sources. These strengths make the paper suitable for publication in EGUsphere. However, there are several areas that require improvement for greater clarity. Therefore, I recommend the paper for publication pending major revisions.
General cooments :
This paper provides valuable information on the properties of BC-coated aerosols. However, it is unclear whether the discussed properties represent typical features of BC-coated aerosols or are specific to aerosols in this region. For instance, the ion balance among inorganic components is significantly lower than 1, which the authors use to infer aerosol acidity. However, the provided values show limited variability and are much lower compared to NR-PM1. Is this discrepancy due to the specific location, the characteristics of BC-coated aerosols, or another factor? Other discussions on aerosol properties should address this issue to provide more clarity.Since the authors use ACSM to measure non-BC PM1, it would be beneficial to utilize that data to offer a broader perspective on the general characteristics of PM. Additionally, comparing ACSM data could help quantify the proportions of BC-coated versus non-coated aerosols, at least for non-refractory compounds. Such comparisons would enhance the readers’ understanding of the results.
Moreover, regarding the PMF results, the significance of the sources could be better contextualized by providing the proportion of BC-containing particles relative to the total aerosol population. Without these additional details, the paper appears overly focused on methodology, making it challenging to translate the findings into meaningful air quality applications.
When performing PMF with different methods, the authors downweight or multiply several inputs. It is important to clarify how these adjustments affect the results and how those compounds are treated in the final analysis.
Regarding the inclusion of metals in PMF, although the authors use Hz signals rather than mass conversion, are there possibilities that different metal compounds evaporate at varying rates? Are all metals fully evaporated? While calibration may not have been necessary since the authors do not report metal masses, understanding the collection efficiency or ionization efficiency (IE) of metals is crucial to provide accurate ratios for certain sources.
The rBC mass fraction from SP-AMS is reported to be overestimated by 30%. Calibration for BC quantification is essential. Why does this overestimation occur, and is it consistent across other studies using SP-AMS measurements?
The authors mention that BBOA carries organonitrate, inferred from the NO/NO2 ratio. Does this mean the reported nitrate concentration is not entirely inorganic? Or has the organonitrate portion been separated out? If so, it is necessary to explain how inorganic nitrate and sulfate concentrations were derived, the potential for organonitrate inclusion, and, ultimately, how much organonitrate is present.
In several places, the authors discuss coating thickness without addressing size distribution. For instance, on Page 15, Lines 10–12, and in Section 3.3.1 on Lines 20, 24, and 27, comparisons are made to rBC, but it is unclear whether smaller or larger amounts of material compared to rBC explain the thin or thick coatings.
Regarding size, in Section 3.2.4, the authors state that BC size increases with aging. However, generally, BC size does not increase; rather, coatings around BC grow with aging. The dual BC size distribution observed might suggest different sources. Alternatively, could the rBC signal include organic material, potentially explaining the observed aging effect?
Related to the above questions, are there any possibilities that rBC measurements contain organic contributions? Addressing this would help clarify the findings and improve the overall interpretation of the results in this manuscript.
Detail comments.
Section 3.1 page11: Presenting the ion balance of NR-PMcoating measured by SP-AMS alongside the ion balance of bulk OA measured by ToF-ACSM could provide a clearer understanding of the differences in chemical composition.
Section 3.1 page12: The observation that sulfate is the second most abundant component after BC in NR-PMcoating and it is supported by previous literature. However, this finding could be further substantiated by including the time series and a pie chart of bulk OA composition, which would provide additional context and strengthen the interpretation of the results.
Section 3.2.2 page15: To explain the low values of Org/BC, O:C, and OSc observed during 8:00–9:00 LT and 20:00–21:00 LT as being caused by POA, it would be necessary to also analyze the diurnal patterns of vehicle emissions or SOA based on PMF results. While, previous studies reported that POA (particularly from traffic) tends to increase during these time periods, this cannot definitively confirm that the observed values are due to POA in this study. Still the interpretation remains uncertain. Therefore, it is recommended to present the explanation related to POA as a possibility or to integrate it into the discussion of PMF results at Section 3.3.2, which provide a more comprehensive context for such interpretations.
Section 3.2.2 page16: To interpret the increase in fC2H4O2+ between 2:00 and 8:00 LT as being influenced by oxidized biomass burning emissions, it is important to consider previous studies that suggest the fC2H4O2+ signal decreases as aging progresses. This suggests that biomass burning was active during this period and, separately, secondary production and aging of other OA components may have contributed to the observed increase in OSc.
Section 3.4.1 page25: The use of the V+/Ni+ ratio as evidence for shipping emissions is reasonable and aligns with previous studies. However, the classification of the industrial-related factor as IOA requires additional supporting data. Specifically, further analysis of other metal ratios could provide stronger evidence to validate its association with industrial emissions. Including these ratios would enhance the reliability of the interpretation and clearly differentiate industrial contributions from other sources.
Citation: https://doi.org/10.5194/egusphere-2024-3240-RC2
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