Organic aerosol source apportionment in Zurich using an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF-MS) – Part 2: Biomass burning influences in winter
<p>Real-time, in situ molecular composition measurements of the organic fraction of fine particulate matter (PM<span class="inline-formula"><sub>2.5</sub></span>) remain challenging, hindering a full understanding of the climate impacts and health effects of P...
Main Authors: | , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2019-06-01
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Series: | Atmospheric Chemistry and Physics |
Online Access: | https://www.atmos-chem-phys.net/19/8037/2019/acp-19-8037-2019.pdf |
Summary: | <p>Real-time, in situ molecular composition measurements of the organic
fraction of fine particulate matter (PM<span class="inline-formula"><sub>2.5</sub></span>) remain challenging,
hindering a full understanding of the climate impacts and health effects of
PM<span class="inline-formula"><sub>2.5</sub></span>. In particular, the thermal decomposition and ionization-induced
fragmentation affecting current techniques has limited a detailed
investigation of secondary organic aerosol (SOA), which typically dominates
OA. Here we deploy a novel extractive electrospray ionization time-of-flight
mass spectrometer (EESI-TOF-MS) during winter 2017 in downtown Zurich,
Switzerland, which overcomes these limitations, together with an Aerodyne
high-resolution time-of-flight aerosol mass spectrometer (HR-TOF-AMS) and
supporting instrumentation. Positive matrix factorization (PMF) implemented
within the Multilinear Engine (ME-2) program was applied to the EESI-TOF-MS data to
quantify the primary and secondary contributions to OA. An 11-factor
solution was selected as the best representation of the data, including five primary and six secondary factors. Primary factors showed influence from
cooking, cigarette smoke, biomass burning (two factors) and a special local
unknown event occurred only during two nights. Secondary factors were
affected by biomass burning (three factors, distinguished by temperature and/or
wind direction), organonitrates, monoterpene oxidation, and undetermined
regional processing, in particular the contributions of wood combustion.
While the AMS attributed slightly over half the OA mass to SOA but did not
identify its source, the EESI-TOF-MS showed that most (<span class="inline-formula">>70</span> %) of
the SOA was derived from biomass burning. Together with significant
contributions from less aged biomass burning factors identified by both AMS
and EESI-TOF-MS, this firmly establishes biomass burning as the single most
important contributor to OA mass at this site during winter. High
correlation was obtained between EESI-TOF-MS and AMS PMF factors where specific
analogues existed, as well as between total signal and POA–SOA
apportionment. This suggests the EESI-TOF-MS apportionment in the current study
can be approximately taken at face value, despite ion-by-ion differences in
relative sensitivity. The apportionment of specific ions measured by the
EESI-TOF-MS (e.g., levoglucosan, nitrocatechol, and selected organic acids) and
utilization of a cluster analysis-based approach to identify key marker ions
for the EESI-TOF-MS factors are investigated. The interpretability of the
EESI-TOF-MS results and improved source separation relative to the AMS within
this pilot campaign validate the EESI-TOF-MS as a promising approach to source
apportionment and atmospheric composition research.</p> |
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ISSN: | 1680-7316 1680-7324 |