The effect of the averaging period for PMF analysis of aerosol mass spectrometer measurements during offline applications
<p>Offline aerosol mass spectrometer (AMS) measurements can provide valuable information about ambient organic aerosols in areas and periods in which online AMS measurements are not available. However, these offline measurements have a low temporal resolution, as they are based on filter sampl...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-11-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/15/6419/2022/amt-15-6419-2022.pdf |
| Summary: | <p>Offline aerosol mass spectrometer (AMS) measurements can
provide valuable information about ambient organic aerosols in areas and
periods in which online AMS measurements are not available. However, these
offline measurements have a low temporal resolution, as they are based on
filter samples usually collected over 24 h. In this study, we examine
whether and how this low time resolution affects source apportionment
results. We used a five-month period (November 2016–March 2017) of online
measurements in Athens, Greece, and performed positive matrix factorization (PMF)
analysis to both the original dataset, which consists of 30 min
measurements, and to time averages from 1 up to 24 h. The 30 min results
indicated that five factors were able to represent the ambient organic
aerosol (OA): a biomass burning organic aerosol factor (BBOA), which contributed
16 % of the total OA; hydrocarbon-like OA (HOA) (29 %); cooking OA (COA) (20 %); more-oxygenated OA (MO-OOA) (18 %); and less-oxygenated OA (LO-OOA) (17 %). Use of the daily averages resulted in estimated average contributions that were within 8 % of the total OA compared with the high-resolution analysis for the five-month period. The most important difference was for the BBOA contribution, which was overestimated (25 % for low resolution versus 17 % for high resolution) when daily averages were used. The estimated secondary OA varied from 35 % to 28 % when the averaging
interval varied between 30 min and 24 h. The high-resolution results are
expected to be more accurate, both because they are based on much larger
datasets and because they are based on additional information about the
temporal source variability. The error for the low-resolution analysis was
much higher for individual days, and its results for high-concentration days in particular are quite uncertain. The low-resolution analysis
introduces errors in the determined AMS profiles for the BBOA and LO-OOA
factors but determines the rest relatively accurately (theta angle around
10<span class="inline-formula"><sup>∘</sup></span> or less).</p> |
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| ISSN: | 1867-1381 1867-8548 |