Development and Evaluation of an Improved Off-Line Aerosol Mass Spectrometry Technique
Abstract. The off-line Aerosol Mass Spectrometry (AMS) technique is a useful tool for the source apportionment of organic aerosol (OA) in areas and periods during which an AMS is not available. However, the technique is based on the extraction of aerosol samples in water, while several atmospheric OA components are partially or fully insoluble in water. In this work an improved off-line technique was developed and evaluated in an effort to capture most of the partially soluble and insoluble organic aerosol material, reducing significantly the uncertainty of the corresponding source apportionment. A major advantage of the proposed approach is that no corrections are needed for the off-line analysis to account for the limited water solubility of some OA components. The improved off-line AMS analysis was tested in three campaigns: two during winter and one during summer. Collocated on-line AMS measurements were performed for the evaluation of the off-line method. Source apportionment analysis was performed separately for the on-line and the off-line measurements using Positive Matrix Factorization (PMF). The PMF results showed that the fractional contribution of each factor to the total OA differed between the on-line and the off-line PMF results by less than 15 %. The differences in the AMS spectra of the factors of the two approaches could be significant suggesting that the use of factor profiles from the literature in the off-line analysis may lead to complications. Part of the good agreement between the on-line and the off-line PMF results is due to the ability of the improved off-line AMS technique to capture a bigger part of the OA, including insoluble organic material. This was evident by the significant fraction of submicrometer suspended insoluble particles present in the water extract, and by the reduced insoluble material on the filters after the extraction process. More than half of the elemental carbon (EC) was on average missing from the filters after the water extraction. Significant EC concentrations were measured in the produced aerosol that was used as input to the AMS during the off-line analysis.
Christina N. Vasilakopoulou et al.
Status: open (until 01 Apr 2023)
RC1: 'Comment on amt-2023-16', Anonymous Referee #1, 10 Mar 2023
- AC1: 'Response to Referee #1', Spyros Pandis, 17 Mar 2023 reply
- RC2: 'Comment on amt-2023-16', Anonymous Referee #2, 19 Mar 2023 reply
- RC3: 'Comment on amt-2023-16', Anonymous Referee #3, 19 Mar 2023 reply
Christina N. Vasilakopoulou et al.
Christina N. Vasilakopoulou et al.
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This manuscript describes a method modification to off-line extraction of filter-based particle collections with re-suspension and analysis by high resolution AMS. Importantly, the method has been compared to on-line AMS (and ACSM) measurements from 3 different field studies. One limitation of the work presented here is that the off-line analysis is non-quantitative under the current method. However, the relative amount of contributing PMF components/factors shows reasonable agreement between the on-line analysis and off-line analysis.
Comments and recommended edits:
Line 31: not quite “automatically”, processing is needed. Please remove or revise.
Line 34: change “various sources” to “various sources or atmospheric transformations”
Line 34: already defined OA in line 29
Line 41: Regarding, “Its weight and size”, add “Its weight, size, and power consumption”
Line 74: include sample volume here (flow rate and sample time)
Section 2.1: does the quartz filter survive sonication? Or do they break apart? I’d imagine they break apart, in which case are there not issues with quartz fibers interfering with the atomizer stability if you don’t filter the water?
For blank measurements, has that water gone over a clean filter?
Line 93: change “variables related to CO2 “ to “variables related to CO2 and CO2-based corrections“
Line 96: used the name Thissio campaign here, but previously just referred to it as Athens campaign. Define this as Thissio earlier if that it the name you will use in the document.
Section 3: Is there any supporting information that could be provided here. Temperatures during each campaign? Maps of sample sites within the cities/regions? Plots of wind directions/speeds? Something to give the reader a better sense of each study.
Line 157: Any ideas on what is driving this difference between BBOA types?
Figure 2: this timeseries appears in low resolution on the file I accessed. Also, are the highest concentrations being cut off at the max 10 ug/m3 y-axis scale?
Also, would be helpful to see a stacked plot timeseries of the MO-OOA, LO-OOA, and HOA components here. And if showing them in this plot, the MO- and LO- categories should be described in the document when figure first introduced.
Figure 3: same points as fig. 2, except the resolution does look better for this figure in the file I have. Specify in figure description that these are results from PMF of on-line AMS. Also revise how it is stated in Figure 2. It is not on-line PMF. It is PMF of on-line AMS data.
Figure 4: Legend does not indicate which is on-line and which is off-line.
Section 4.1.2.: it would be important to make these online/offline comparisons in terms of mass concentrations, not just percentages of total. It’s my understanding that a calibrant was not used for offline samples however.
Line 183: avoid statements such as “The only minor weakness”. The truth is it could go either way, maybe it is a weakness, maybe it is a strength, unclear without quantification. Just call it a “difference”
Line 189: Regarding bootstrapping comparison amongst factors: again, would be better to see this as mass concentrations
Figure S5: This could match better on a mass basis as opposed to a % of total, had a calibrant been used.
Line 213: I could imagine a third reason. With high time resolution online AMS, there are more time periods where individual components/factors dominate over the others, producing a more defined factor profile. The offline method always has a higher contribution from all factors due to the daily integration.
It seems there are some major contributions in the offline method from m/z’s < 20 relative to the online method. You may get better matches overall if you excluded m/z <20 from your comparison. And in doing so, consider why these may be higher in the offline method (residue from water?)
Line 217: Yes, here you accounted for the difference at m/z <20….why not go back and do the same for factors in previous paragraph (shown in fig S6)
Figure S18: not OOAI and OOAII according to previous figures, MO- and LO-
Line 296: fig. S19 not S20
Line 300: fig. S20 not S21….I think this is off going forward in figures, please fix
Line 303: how did authors get O:C from online ACSM? Did it have a ToF-MS?
Line 335: What do authors mean by “filtration phase”? It was explained that the water extracts were not filtered in their process.
Line 342: Were the blanks extracted from clean/unused filters, or just looking at the water? There could be suspended particles released from a clean filter.