source apportionment of ambient particle number concentrations in central los angeles using positive matrix factorization (pmf)
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2016
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Abstract
In this study, the positive matrix factorization (PMF) receptor model
(version 5.0) was used to identify and quantify major sources contributing
to particulate matter (PM) number concentrations, using PM number size
distributions in the range of 13 nm to 10 µm combined with several
auxiliary variables, including black carbon (BC), elemental and organic
carbon (EC/OC), PM mass concentrations, gaseous pollutants, meteorological,
and traffic counts data, collected for about 9 months between August 2014
and 2015 in central Los Angeles, CA. Several parameters, including particle
number and volume size distribution profiles, profiles of auxiliary
variables, contributions of different factors in different seasons to the
total number concentrations, diurnal variations of each of the resolved
factors in the cold and warm phases, weekday/weekend analysis for each of
the resolved factors, and correlation between auxiliary variables and the
relative contribution of each of the resolved factors, were used to identify
PM sources. A six-factor solution was identified as the optimum for the
aforementioned input data. The resolved factors comprised nucleation,
traffic 1, traffic 2 (with a larger mode diameter than traffic 1 factor),
urban background aerosol, secondary aerosol, and soil/road dust. Traffic
sources (1 and 2) were the major contributor to PM number concentrations,
collectively making up to above 60 % (60.8–68.4 %) of the total number
concentrations during the study period. Their contribution was also
significantly higher in the cold phase compared to the warm phase.
Nucleation was another major factor significantly contributing to the total
number concentrations (an overall contribution of 17 %, ranging from
11.7 to 24 %), with a larger contribution during the warm phase than
in the cold phase. The other identified factors were urban background
aerosol, secondary aerosol, and soil/road dust, with relative contributions
of approximately 12 % (7.4–17.1), 2.1 % (1.5–2.5 %), and 1.1 %
(0.2–6.3 %), respectively, overall accounting for about 15 %
(15.2–19.8 %) of PM number concentrations. As expected, PM number
concentrations were dominated by factors with smaller mode diameters, such
as traffic and nucleation. On the other hand, PM volume and mass
concentrations in the study area were mostly affected by sources with
larger mode diameters, including secondary aerosols and soil/road dust.
Results from the present study can be used as input parameters in future
epidemiological studies to link PM sources to adverse health effects as well
as by policymakers to set targeted and more protective emission standards
for PM.
| Reference Key |
sowlat2016atmosphericsource
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|---|---|
| Authors | ;M. H. Sowlat;S. Hasheminassab;C. Sioutas |
| Journal | Journal of agricultural and food chemistry |
| Year | 2016 |
| DOI |
10.5194/acp-16-4849-2016
|
| URL | |
| Keywords |
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