Estimating the secondary organic aerosol contribution to PM2.5 using the EC tracer
method.
Juan C. Cabada and Spyros N. Pandis, Department of Chemical Engineering, Carnegie
Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213
Ramachandran Subramanian and Allen L. Robinson, Department of Mechanical
Engineering, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213
Andrea Polidori and Barbara Turpin, Department of Environmental Sciences, Rutgers
University, 14 College Farm Road, New Brunswick, NJ 08901
Abstract
The EC tracer method is applied to a series of measurements by different
carbonaceous aerosol samplers in the Pittsburgh Air Quality Study (PAQS) in order to
estimate the concentration of secondary organic aerosol. High-resolution measurements
(2-6 hrs) and daily averaged concentrations were collected during the summer 2001
intensive (July 1 to August 4, 2001) and are used for the analysis. The various samplers
used during PAQS show differences in the measured concentrations of OC and EC due to
the different sampling artifacts and sampling periods.
A systematic approach for the separation of periods where SOA contributes
significantly to the ambient OC levels from the periods where organic and elemental
carbon concentrations are dominated by primary emissions is proposed. Ozone is used as
indicator of photochemical activity to identify periods of probable secondary organic
aerosol production in the area. Gaseous tracers of combustion sources (CO, NO, and
NOx) are used to identify periods where most of the OC is primary. Periods dominated by
primary emissions are used to establish the relationship between primary OC and EC, a
tracer for primary combustion-generated carbon for the different sets of measurements
for July 2001. Around 35% of the organic carbon concentration in Western Pennsylvania
during July of 2001 is estimated to be secondary in origin.
1
1. Introduction
Carbonaceous aerosol is an important constituent of the PM2.5 (particulate matter with
aerodynamic diameters less than 2.5 microns) mass in most of the U.S. Between 10 to
65% of the fine particulate mass has been identified as carbonaceous material for various
regions of the country (Gray et al., 1986; Turpin et al., 1991; Seinfeld and Pandis, 1998;
Tolocka et al., 2001; Lim and Turpin, 2002). Aerosol carbon is commonly classified as
organic (OC) and elemental carbon (EC). OC can be directly emitted to the atmosphere in
the particulate form (primary) or can be produced by gas to particle conversion processes
(secondary). EC is emitted from combustion sources. Since primary OC and EC are
mostly emitted from the same sources, EC can be used as a tracer for primary
combustion-generated OC (Gray, 1986; Turpin and Huntzicker, 1995; Strader et al.,
1999). The formation of secondary organic aerosol (SOA) increases the ambient
concentration of OC and the ambient OC/EC ratio. OC to EC ratios exceeding the
expected primary emission ratio are an indication of SOA formation. For Southern and
Central California between 30 to 80% of the total OC has been identified as secondary in
summer (Gray et al., 1986; Pandis et al., 1992; Hildemann et al., 1993; Turpin and
Huntzicker, 1995; Schauer et al., 1996).
The relationship between primary OC and EC depends also on the sampling and
analyses techniques used to determine the ambient OC and EC concentrations. Sample
collection (i.e. use or not of denuders, filter face velocities, etc.) and different analysis
techniques (i.e. Thermal Optical Transmittance vs. Thermal Optical Reflectance) affect
the reported concentrations for OC and EC (Countess, 1990; Birch, 1998; Chow et al.,
2001; Schmid et al., 2001). Sampling carbonaceous particulate matter from the
2
atmosphere is challenging because of interferences from gaseous material that is
adsorbed on the filters or evaporation of the collected organic material during sampling
(Turpin et al., 1994; Fitz, 1990; Hering et al., 1990). Different sampling arrangements
(e.g., using backup quartz filters, placing denuders upstream of the filter to remove
organic gases, etc.) have been proposed in order to reduce and/or measure and correct for
the positive and negative artifacts that affect the measured carbonaceous concentrations
(Turpin et al., 2000).
Primary ratios of OC to EC vary from source to source and show temporal and
diurnal patterns (Gray, 1986; Cabada et al. 2002) but since EC is only emitted by
combustion sources, gaseous tracers of combustion (CO, NO, NOx) can be used to
determine periods dominated by primary aerosol emissions. Ozone is an indicator of
photochemical activity and it also can be used as a tracer for periods where secondary
organic aerosol production is expected. In this case, increases in the OC to EC ratio
correlated to ozone episodes are indicative of SOA production.
In this work a relationship between primary OC and EC is established for each of
the different types of measurements and artifact estimation approaches. An algorithm is
proposed for the determination of the primary OC/EC ratio and secondary organic aerosol
concentrations are estimated. SOA results based on high-resolution and the dailyaveraged samples are compared. The effect of sampling frequency on the estimates of the
primary ratios is also discussed.
2. Experimental Methods and Equipment
The Pittsburgh Air Quality Study (PAQS) main site was located in Schenley park
on the top of a hill just outside of Carnegie Mellon University campus, around three miles
3
to the east of downtown Pittsburgh. The Pittsburgh supersite operated three different
samplers for collecting carbonaceous aerosol (one undenuded and two denuded
samplers). The undenuded sampler and a denuded in-situ analyzer collected samples
every 2-6 hr, while the denuder-based sampler collected daily samples, during the 2001
summer intensive (July 1 to August 4, 2001).
Quartz fiber filters (47 mm Pallflex, QAOT), Teflon filters (2 m pore, Whatman
7592-104) and carbon-impregnated filters (Schleicher and Schuell, GF-3649) were used
to sample carbonaceous material in three different samplers. Quartz fiber filters were
baked at 550°C for more than 12 hours and stored in previously cleaned glass jars until
sampling and analysis. Carbon-impregnated filters were baked at 370˚C for more than 3
hours in a nitrogen atmosphere.
Undenuded sampler
PM2.5 carbonaceous aerosol samples were collected on quartz fiber filters using filter
packs in a non-denuded line. This sampler consisted of two parallel lines, the first line
holding a quartz fiber filter followed by a backup quartz filter and the second line having
of a Teflon filter followed by a backup quartz fiber filter (Figure 1). The two backup
quartz fiber filters are used to estimate the positive and negative artifact (Turpin, 2000).
Five samples a day, with sampling times between 4 and 6 hrs, were collected during the
summer intensive. Samples were collected during 0-6, 6-10, 10-14, 14-18 and 18-24 hrs
(all in EST). The filter configuration allows two different estimates of the adsorption
artifacts on the front quartz fiber filter. The first correction is done subtracting the OC
collected in the backup quartz fiber filter behind the front quartz (QB,F) from the OC
collected by the front quartz (QF). This approach assumes that the front quartz filter (QF)
4
collects 100% of the carbonaceous particulate matter (no evaporation) and that both the
front and the backup filter adsorb organic gases and reach equilibrium with them during
the sampling period. The second correction approach subtracts the OC collected in the
backup quartz filter behind the Teflon filter (QB,T) from the OC in the front quartz filter
(QF). This approach assumes that the Teflon filter collects all the particles from the
sampled flow with 100% efficiency and the backup quartz from this line adsorbs the
same quantity of gases as the front quartz fiber filter. The EC concentration reported by
the front quartz filter (QF) is used for all datasets from the undenuded sampler.
Denuded sampler
Filter packs holding a quartz filter in front of a carbon-impregnated filter (CIF) were used
to collect carbonaceous material from a denuded sampling line (Figure 1). A carbon
annular denuder (Novacarb monolith synthetic carbon, Mast Carbon Ltd. Guilford, UK)
was used to remove organic gases and minimize the positive artifact in the quartz filter.
The CIF organic carbon concentration was intended to correct for evaporation of semivolatile material from the quartz filter (negative artifact). Sampling frequency for this
unit was 24 hrs, from midnight to midnight (EST).
Semi-continuous denuded in-situ analyzer
An in-situ semi continuous carbon analyzer (Sunset Labs, Carbon Aerosol Analysis Field
Instrument), similar in design to that described by Turpin et al. (1990), was used to
collect and analyze carbonaceous aerosol with sampling periods of 2 to 4 hours (100 to
220 minutes sampling time plus 20 minutes for analysis). Instrument performance and
PAQS protocols are described in detail by Lim et al. (2002) and Polidori et al. (2002). A
parallel plate diffusion denuder (CIF; Schleicher Schuell, Keene, NH) was placed
5
upstream of a quartz filter, which is mounted inside the analyzer (Figure 1). Cycles of
sampling and analysis were alternated in order to determine the ambient concentrations of
OC and EC (Lim et al., 2002).
Quartz filters from the filter pack-based samplers were analyzed using a
Thermal/Optical transmittance carbon analyzer (Sunset Laboratory Inc., OC-EC Aerosol
Carbon Analyzer Model-3) using the temperature steps of the NIOSH protocol (Birch,
1996; NIOSH, 1999) for the determination of OC and EC. Table 1 shows the
experimental parameters for the analysis of the quartz and carbon impregnated filter
during PAQS. The time length of the different temperatures steps in the method was
modified to get a better split between OC and EC (Yu et al., 2002). Carbon impregnated
filters were analyzed using a temperature ramp up to 340°C, during 25 minutes under a
helium atmosphere. All concentrations of OC and EC were corrected for field blanks.
Concentrations reported from the in-situ carbon analyzer were corrected for dynamic
blanks generated by sampling with a Teflon filter upstream of the denuder (Polidori et al.,
2002).
3. Carbonaceous aerosol measurements
Differences exist among the measured concentrations of organic and elemental carbon
collected by the different samplers. For example, adsorption of organic gases on the front
quartz filter of the undenuded lines (positive artifact) is evident as the OC measured by
this line is higher than that of the denuded samplers. The magnitudes of the positive and
negative artifacts depend not only on the sampling method and the atmospheric
composition but also on the length of the sampling period. A detailed discussion of the
artifacts using these datasets is presented by Subramanian et al. (2002).
6
Figure 2 shows time resolved concentrations for the different samplers during a 6-day
period. Overall samplers indicate similar patterns of OC and EC concentrations, but the
OC and EC concentrations from the undenuded line are almost always higher than that of
the other two samplers.
The summer intensive averaged concentrations of OC and EC for all types of
samplers and all artifact correction approaches at the Pittsburgh supersite is shown in
figure 3. Subtracting the measured OC concentration on the backup quartz filters (QB,F,
and QB,T) from the front quartz (QF) reduces the OC concentrations by 20% on average
for the summer intensive. Subtracting the OC concentration of the backup quartz filter
behind the Teflon filter in the parallel line of the undenuded sampler results in an average
correction of around 50% on average for the summer intensive. The reported OC
concentrations of the two denuded samplers agree within 10%, and give particulate OC
concentrations between the QF,B and QB,T corrected undenuded sampler concentrations.
However the reported average EC concentrations differ by 50%. EC concentrations
reported by the undenuded and denuded in-situ analyzer agree within 10%. A detailed
discussion of the potential reasons for these differences is provided by Subramanian et al.
(2002).
In this work we examine the effect of the difference in sampler configuration and
sampling periods of OC and EC measurements on the SOA estimates applying the EC
tracer method.
4. The EC tracer method
The ratio of the ambient concentrations of particulate OC to EC includes information
about the extent of secondary OC formation. Ambient OC/EC ratios greater than those
7
characteristic of the primary emissions for a specific area are an indication of secondary
aerosol formation. The EC tracer method takes advantage of the fact that primary OC and
EC are mostly emitted by the same combustion sources. Primary ratios of OC to EC can
be determined form a subset of ambient measurements if a large data set is available and
conditions to produce SOA are unlikely (Turpin and Huntzicker, 1995; Strader et al.,
1999) or by developing an emissions inventory of the principal sources for an area of
interest (Gray, 1986; Cabada et al., 2002).
Assuming that OC primary can be defined by,
OCp   OC   EC   b
 EC  p
(1)
the contribution of secondary OC can be estimated as
OCS  OC  OCp
(2)
where [OC]p is the primary organic aerosol concentration, [OC/EC]p is the ratio of OC to
EC for the primary sources affecting the site of interest and b is the non-combustion
contribution to the primary OC (Turpin and Huntzicker, 1995; Strader et al., 1999), [EC]
is the measured EC concentration, [OC]S is the secondary organic aerosol contribution to
the total OC and [OC] is the measured OC concentration. All of these parameters are time
dependent because of the temporal variations in anthropogenic emissions and in
meteorology. The application of this method requires measurements of [OC], [EC] and
the determination of the [OC/EC]p ratio and the non-combustion primary OC contribution
(b) for the area and period of interest (Turpin and Huntzicker, 1995).
4.1 Calculation of the primary OC/EC ratio and intercept
8
Diurnal variations of the ambient OC to EC ratio were observed for all the highresolution measurements taken during the summer intensive of 2001 at PAQS.
Photochemical activity, meteorology and primary emissions all contribute to these
variations. Ozone concentration can be used as an indicator of photochemical activity.
Carbon monoxide (CO) and nitrogen oxides (NO and NOx) can be used as tracers of
combustion-related primary emissions. The primary ratio and intercept are determined
from a dataset by identifying the periods where the ambient concentrations are dominated
by primary emissions.
The first step in the determination of the primary OC/EC ratio is the subtraction from the
original dataset of the points where rain and the corresponding storms cause significant
changes to the OC/EC ratio (Figure 4a). These changes have a variety of causes (removal
of aged particles and increased importance of the locally produced ones, preferential
removal of secondary OC, etc.). These periods are excluded from the analysis to avoid
unnecessary complications.
The second step consists in identifying the OC and EC concentrations where there is high
probability of SOA production. The OC to EC ratio usually showed a strong correlation
with ozone but a lag time between the ozone peak and the actual OC to EC ratio was
observed. In an effort to account for those events, the “history” of the ozone peak was
taken into account, and the peak ozone concentration for the period preceding the sample
was compared to the OC to EC ratio to evaluate its influence. For example, Figure 4b
shows the measured OC/EC ratio and O3 concentrations during a 4-day period in July.
Periods of significant photochemical activity are evident during the afternoon of each
day. The corresponding afternoon OC and EC measurements are “deleted” from the
9
dataset because they probably include some SOA contribution. This does not mean that
the other periods have only primary OC. Secondary aerosol can be produced elsewhere,
maybe even during the previous day and transported into the site.
Figure 4c and 4d show periods were combustion related sources were dominating over
the area. The last step in this methodology consists in identify these periods. As the NOx,
NO and CO concentrations peaked during the night and early morning of July 3 and
August 1, the OC to EC ratios decreased indicating the influence of primary sources over
the area of analysis. The corresponding samples during these periods are kept in the
dataset and are used to estimate the primary OC/EC ratio for the period of analysis.
Figure 5 shows the sequence of how the OC vs. EC plot is evolving during the
different steps of the analysis. Once all the points that are dominated by primary OC are
determined (those influenced by combustion sources as described by the algorithm), a
linear regression by least squares minimization is fitted to the “primary” concentrations.
The slope of the fit represents the OC to EC primary ratio and the intercept represents the
“non-combustion organic carbon” contribution to the primary OC concentration (see
equations 1 and 2).
Table 2 shows the classification of concentrations between primary and secondary
influenced for a two day period during the summer intensive, using the undenuded front
quartz data (QF). Most of the OC during the first morning (6:00-10:00) appears to be
primary as the area was heavily influenced by primary emissions, showing higher values
of NOx and CO. OC to EC ratios increased rapidly during the day as the ozone
concentration increased, suggesting that formation of SOA was probably taking place. A
period where SOA material is probably transported into the area can be observed during
10
the late hours of August 1 and the first hours of August 2. These periods are characterized
by relatively high ozone and NOx, leading to the classification of this period as SOA
dominated. Periods when most of the OC is primary are characterized by average
concentrations of 25 ppb of NOx, 8 ppb of NO, 0.3 ppm of CO, and 30 ppb of ozone. The
remaining periods where there may be significant amounts of SOA present have average
concentrations of 17 ppb of NOx, 2 ppb of NO, 0.2 ppm of CO, and 50 ppb of ozone.
For the analysis of the daily samples (or daily averaged concentrations) the above
algorithm needs to be modified. Daily averages of the O3, CO and NOx concentrations are
used to determine the periods when the OC concentrations are influenced by primary
sources. Primary dominated concentrations, for the daily averaged concentrations, show
an average concentration of 17 ppb of NOx, 4 ppb of NO, 0.2 ppm of CO, and 30 ppb of
ozone. Secondary dominated concentrations show and average concentration of 20 ppb of
NOx, 4 ppb of NO, 0.2 ppm of CO, and 45 ppb of ozone.
4.2 Estimated [OC/EC]p and b
Figure 6, summarizes the classification of points between primary and secondary
influenced for all high-resolution datasets. The estimated primary ratio of OC to EC
([OC/EC]p) and the intercept “b” vary depending on the dataset analyzed and the
averaging period used (Table 3). A consistent set of concentrations of OC and EC should
be used in order to estimate the SOA concentration using the approach proposed in the
previous sections. Estimates of the primary ratio vary from 0.9 to 3.1 and the intercept, b,
varies from 0.3 to 1.2 g C/m3. Variations in the estimated parameters for the different
sets of measurements are due to the different characteristics of the samplers
(Subramanian et al., 2002). In general primary ratios and intercepts from the fitting of the
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daily-average concentrations influenced by primary emissions are higher than those
calculated from the high-time resolution measurements (Figure 7). This can be explained
by the fact that high-resolution measurements have the ability to more accurately identify
and separate periods of secondary organic aerosol formation from those dominated by
primary emissions. Higher correlations coefficients are achieved for the daily samples
because the datasets show less variability among the points considered to be influenced
by primary emissions (Table 3). The effect of the sampling artifacts can also be seen in
the estimated primary ratios for the different datasets. Those datasets with corrections of
the artifact (using the backup quartz filters in the undenuded sampler) or having a
denuded line have lower primary ratios. The exception to this rule is the denuded
sampler, but this is due to issues related to the EC measurement by this sampler
(Subramanian et al., 2002).
Higher contributions from the non-combustion primary OC are calculated for the
undenuded front quartz datasets. This is due to the addition of the adsorbed organic gases
to the actual primary non-combustion OC and the calculated values (1.2-1.4 g C/m3) are
probably overestimates. Lower intercepts are calculated for the undenuded datasets where
corrections are done for the front quartz artifact and these values are probably closer to
the true concentrations (Table 3).
5. SOA Concentrations
Once the primary ratio and the non-combustion primary OC contribution are calculated
for each of the different datasets of carbonaceous measurements, the primary and
secondary components of the Pittsburgh organic aerosol can be determined applying
equations 1 and 2.
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5.1 SOA based on high time resolution measurements.
The calculated SOA concentrations for the different high-resolution measurements are in
a qualitative agreement (Figure 8), predicting the same periods of SOA production for the
summer intensive. For example, from July 15 to July 25 a high pressure system
dominated the area allowing high production of SOA. The effect of two other highpressure systems can be seen from July 8 to July 11 and in the beginning of August.
Production of SOA can be observed during the mid afternoon of each of those days and
significant transport of secondary material into the area occasionally occurs during the
nighttime. The first days of July were characterized by a strong contribution of SOA
during the daylight hours.
Ozone and solar radiation (UV) are triggers of secondary organic aerosol production.
Estimated SOA concentrations show the same behavior as the ozone and UV radiation
during the day (Figure 9). This qualitative agreement provides some additional
confidence on the estimated concentrations. The first hours of August 2 show a period of
pollution transport to the area. SOA concentration increases and a peak in the ozone
concentration are observed during the middle of the night. The effect of ambient
temperature can also be observed as the temperature increases more SOA is produced in
the area (Figure 9c). Temperature increases are associated with high-pressure systems
over the Pittsburgh area. In general these periods provide the ideal conditions for the
production of SOA, like stagnant air masses and high photochemical activity. Little
correlation exists between relative humidity and SOA production. For the summer
intensive 2001, in Pittsburgh, low relative humidity periods are associated with high
13
temperatures at the middle of the day and high relative humidity periods correspond to
fronts entering the area and lowering the SOA production.
Figure 10 shows the average daily concentrations of the estimated SOA and primary OC
for all high-resolution datasets analyzed. In order to make comparisons between the
datasets, average concentrations for each are normalized to the daily average primary OC
and SOA for the period. The diurnal variation of primary OC is relatively small because
during the summer intensive 2001 the majority of the OC is transported to the region
from elsewhere (Cabada et al., 2002). SOA patterns (Figure 10) show some differences
among the datasets used. Overall all samplers show a minimum concentration of SOA in
the early morning hours (0600-0900 hrs) and a SOA increase as the photochemical
activity increases during the day. The SOA production peak varies depending on the
dataset analyzed, but it follows the ozone average daily peak occurring around 15:00 EST
(Figure 10). All datasets suggest that a significant amount of SOA is due to long-range
transport, during the late afternoon and night hours. Minimum production of SOA
coincides with periods where the ozone concentration is at its minimum (between 4:00
and 8:00 EST).
The daily averaged SOA concentrations for all high-resolution datasets show high
episodes of SOA formation in the middle of July and at the beginning on August (Figure
11). Practically all days during the summer intensive show some contribution of SOA
material to the total OC concentrations.
Figure 12 summarizes the monthly averaged SOA contribution for all the high-resolution
measurements. Estimates of SOA vary from 30% for the denuded in-situ analyzer to a
high of 45% for the undenuded sampler doing the correction to the front quartz artifact
14
with the backup filter behind the Teflon filter. Error bars are estimated from the
uncertainties in the linear fit (95% confidence level) from the point influenced by primary
emissions determined for each dataset. Taking into account these uncertainties all
methods agree in the average contribution of SOA around 35%.
5.2 SOA based on daily results, summer intensive 2001.
Figure 13 shows the estimated organic carbon composition (primary and
secondary) for all different carbonaceous concentrations datasets, using daily
concentrations averages to estimate the primary ratio and the primary OC intercept. The
SOA concentration variation during the period is qualitatively similar to that estimated
using the high-resolution measurements (Figure 11). Periods of high SOA production are
evident in the middle of July and the beginning of August. Unlike the estimates of SOA
from the high-resolution measurements, primary ratios and intercepts calculated with the
daily averaged concentrations show a number of days when no SOA is produced. SOA is
probably present in all days but the estimated primary ratio and intercept is probably too
high for this dataset, so these results can be viewed as a lower bound for the SOA
concentrations. On average from all the methods, 22% of the total OC concentrations are
estimated to be SOA (Figure 14). All estimates agree within 5% from each other. The
higher estimate is given from the denuded sampler dataset, where SOA contributes with
25%. The lower estimate is 18% from the undenuded front quartz dataset. Error bars are
calculated from the uncertainties in the linear fitting of the point identified as influenced
by primary emissions for each dataset.
Figure 15 shows a scatter plot of the daily fraction of the different samplers for
both high-resolution and daily averaged samplers. For both cases all samplers agree
15
within 20% on the estimated SOA fraction for each day. Higher differences are shown at
the lower fractions. The reason for this could be that the lower fractions correspond to
lower concentrations of OC, magnifying small variations over the SOA estimations.
6. Conclusions and Discussion
Application of the EC tracer method analysis to the different types of highresolution measurements, suggest an average of 35% SOA contribution to the monthly
average OC concentration during the summer intensive of 2001. Overall estimates range
from a low of 20% to a high of 50%. A preliminary study trying to identify the sources of
carbonaceous aerosol for western Pennsylvania, estimated a SOA contribution from 30%
to 50% to the total OC concentration during the summer of 1995 (Cabada et al., 2002).
These previous results are in good agreement with the estimates that are obtained
applying this new method, giving some confidence about the results.
Higher time resolutions measurements result in the highest estimation of SOA.
Events that trigger SOA production have a strong diurnal dependence (i.e. ozone and
sunlight daily cycles), so high-resolution measurements are more likely to identify
periods of primary or secondary production dominance. The use of daily averaged
measurements probably tends to under-predict the SOA concentration, especially for
relatively small datasets because it may be impossible to find days without any SOA
present. On average the SOA concentrations are around 5 to 10% higher if highresolution measurements are used compared to the daily averaged concentrations.
The EC tracer method is a simple approach for the determination of contribution
of SOA to the total OC concentration measured in a sampling site. It relies in
simultaneous measurements of gaseous pollutants that could be indicators of primary
16
emissions or secondary aerosol production. The major weakness of the method is its
reliance on the assumption of a constant primary OC/EC and constant “b” during the
analysis period (the whole month, or the few hours of the measurement period).
Variations of sources strengths, meteorology, etc, are expected to change the (OC/EC)p
even for the same four-hour period from day to day. This variability introduces
significant uncertainties (see Figures 12 and 14).
Acknowledgments
This research was conducted as part of the Pittsburgh Air Quality Study
that was supported by US Environmental Protection Agency under contract
R82806101 and the US Department of Energy National Energy Technology
Laboratory under contract DE-FC26-01NT41017. This paper has not been subject to
EPA's required peer and policy review, and therefore does not necessarily reflect
the views of the Agency. No official endorsement should be inferred.
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Seinfeld, J.H., Pandis, S.N. (1998) In Atmospheric chemistry and physics: from air
pollution to global change. John Wiley and Sons Inc. New York.
Strader, R., Lurmann, F.; Pandis, S. (1999).Evaluation of Secondary Organic Aerosol
Formation in Winter. Atmospheric Environment. 33, 4849-4863.
Subramanian, R., Khlystov, A., Cabada, J.C., Robinson, A.L. (2002). Measurement of
Positive and Negative Artifacts with Denuded and Undenuded Sampler Configurations.
Aerosol Science and Technology. In press.
18
Tolocka, M.P., Solomon, P.A., Mitchel, W., Norris, G.A., Gemmill, D.B., Weiner, R.W.,
Vanderpool, R.W., Homolya, J.B., Rice, J. (2001). East versus West in the US: Chemical
Characteristics of PM2.5 during the winter of 1999. Aerosol Science and Technology. 34,
88-96.
Turpin, B.J., and Huntzicker, J.J. (1994). Investigation of Organic Aerosol Sampling
Artifacts in the Los Angeles Basin. Atmospheric Environment. 28, 3061-3071.
Turpin, B.J., and Huntzicker, J.J. (1995). Identification of Secondary Organic Aerosol
Episodes and Quantitation of Primary and Secondary Organic Aerosol Concentrations
During SCAQS. Atmospheric Environment. 29, 3527-3544.
Turpin, B.J., Cary, R.A., Huntzicker, J.J. (1990). An In Situ, Time Resolved Analyzer for
Aerosol Organic and Elemental Carbon. Aerosol Science and Technology. 12: 161-171.
Turpin, B.J., Huntzicker, J.J., Larson, S.M., Cass, G.R. (1991). Los Angeles Summer
Midday Particulate Carbon: Primary and Secondary Aerosol. Environmental Science and
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Turpin, B.J., Saxena P., Andrews, E. (2000). Measuring and Simulating Particle Organics
in the Atmosphere: Problems and Prospects. Atmospheric Environment. 34: 2983-3013.
Yu, J.Z., Xu, J., Yang, H. (2002). Charring Characteristics of Atmospheric Organic
Particulate Matter in Thermal Analysis. Environmental Science and Technology. 36, 754761.
19
Table 1. Temperature programs used by the Thermal/Optical Transmittance methods for
the analysis of carbonaceous material during PAQS.
PAQS Analysis Method
Carrier
gas
He
He
He
He
He/O2
He/O2
He/O2
He/O2
He/O2
Filter pack-based
samplers
340ºC, 120 sec
500 ºC, 120 sec
615 ºC, 120 sec
870 ºC, 180 sec
575 ºC, 45 sec
650 ºC, 45 sec
725 ºC, 45 sec
800 ºC, 45 sec
910 ºC, 100 sec
In-situ carbon analyzer
340ºC, 60 sec
500 ºC, 60 sec
615 ºC, 60 sec
870 ºC, 90 sec
575 ºC, 45 sec
650 ºC, 45 sec
725 ºC, 45 sec
800 ºC, 45 sec
910 ºC, 100 sec
Carbon impregnated
filters
20 ºC/min up to 330 ºC
330 ºC, 300 sec
20
Table 2. Selection criteria for OC and EC concentrations (undenuded Q F dataset)
influenced by primary emissions or SOA formation.
Date
8/1/01
6:00-10:00
8/1/01
10:00-14:00
8/1/01
14:00-18:00
8/1/01
18:00-24:00
8/2/01
0:00-6:00
8/2/01
6:00-10:00
8/2/01
10:00-14:00
8/2/01
14:00-18:00
8/2/01
18:00-24:00
EC
g/m3
OC
g C/m3
OC/EC
Ratio
O3 avg.
(ppb)
O3
peak
(ppb)
O3
peak
(i-1)*
(ppb)
CO
(ppm)
NO
(ppb)
NOx
(ppb)
Source
Influence
1.5
5.4
3.5
18
29
34
0.7
12
40
Primary
1.1
6.7
6.3
75
97
29
0.2
3
20
Secondary
0.8
5.0
6.3
92
98
97
0.1
1
13
Secondary
1.1
5.4
4.9
49
80
98
0.2
2
31
Secondary
1.1
5.6
5.0
13
29
80
0.3
5
38
Secondary
1.1
4.6
4.4
21
35
29
0.2
4
25
Primary
0.9
6.4
7.5
86
107
35
0.1
1
12
Secondary
0.6
4.9
8.4
104
105
107
0.1
0.2
8
Secondary
0.9
4.6
5.3
69
90
105
0.2
0.1
15
Secondary
* i-1, corresponds to the average concentration of ozone during the previous sampling
interval of carbonaceous material.
21
Table 3. Estimated parameters for the linear fit of the “primary” OC and EC
concentrations. High-resolution data (2-6 hrs) and daily averages and low-resolution
measurements (24 hrs) from the July 2001 summer intensive at Pittsburgh Air Quality
Study.
[OC/EC]p
Non-combustion
primary OC, b (g/m3)
Correlation
coefficient (R2)
Undenuded (QF 4-6 hrs samples)
2.3 ± 0.4
1.2 ± 0.4
0.60
Undenuded (QF– QB,Q 4-6 hrs samples)
2.6 ± 0.4
0.3 ± 0.4
0.76
Denuded in-situ analyzer (2-4 hrs samples)
1.7 ± 0.2
0.9 ± 0.2
0.78
Undenuded (QF-QB,T 4-6 hrs samples)
0.9 ± 0.2
0.6 ± 0.2
0.53
Denuded sampler (24 hrs samples)
3.1 ± 0.8
1.0 ± 0.4
0.80
Undenuded (QF 24 hrs averages)
2.7 ± 0.5
1.3 ± 0.4
0.90
Undenuded (QF– QB,Q 24 hrs averages)
2.3 ± 0.5
1.2 ± 0.3
0.88
Undenuded (QF– QB,T 24 hrs averages)
1.6 ± 0.5
0.5 ± 0.4
0.62
Denuded In-situ analyzer (24 hrs averages)
1.9 ± 0.5
0.7 ± 0.4
0.80
Measurement Type
22
PM2.5
Cyclone
PM2.5
Cyclone
Denuded In-situ
Sampler-Analyzer
PM2.5
Cyclone
Denuder
Denuded
Sampler
Denuder
Undenuded
Sampler
Sunset Labs
Instrument
TF
QB,T
16.7 lpm
16.7 lpm
QF
QFden
QB,Q
CIFB,Qden
16.7 lpm
QFsitu
8.2 lpm
Figure 1. Schematic of the Pittsburgh Air Quality Study carbonaceous aerosol samplers.
Subscript “F” denotes the front filter in the samplers. Backup filters are indicated as a
subscript “B” followed by the type of filter they are after (T =Teflon, Q= quartz).
23
OC (g C/m3)
10
OC
8
Denuded OC
Undenuded OC
(QF)
6
4
2
Denuded In-situ OC
0
EC (g/m3)
4 22
23
24
25
26
27
Denuded In-situ EC
28
EC
3
Denuded EC
2
Undenuded EC
(QF)
1
0
22
23
24
25
26
27
28
July
Figure 2. Time-resolved concentrations for the different organic samplers at the
Pittsburgh supersite project. The filter based undenuded samples and the denuded in-situ
analyzer samples were collected in high resolution time periods (2-6 hrs). The filter based
denuded samples were collected in 24 hrs periods.
24
OC
EC
4
3
2
(QF)
(QF – QB,F)
Undenuded
Sampler
(QF – QB,T)
Denuded
In-Situ
Analyzer
Denuded
Sampler
Undenuded
Sampler
Denuded
In-situ
Analyzer
Undenuded
Sampler
Undenuded
Sampler
(front
quartzbackup
quartz)
0
Undenuded
Sampler
(front
quartzteflon
quartz)
1
Undenuded
Sampler
(front
quartz)
OC and EC (g C/m3)
5
Denuded
Sampler
(QFden + CIFB,Fden)
Figure 3. Monthly averaged OC and EC concentrations for the summer intensive 2001 at
PAQS. The undenuded sampler OC concentrations are corrected by subtracting the OC
collected in the backup quartz filter behind the front quartz or by subtracting the OC
collected in the backup quartz filter behind the Teflon filter from the parallel sampling
line.
25
Rainfall
3
10
2
5
1
0
0
8
9
10
15
10
5
0
15
11
16
July
120
100
80
60
40
20
0
NOx
15
NO
10
5
0
2
3
July
4
20
OC/EC Ratio
OC/EC Ratio
(c)
17
18
19
July
NO, NOx (ppb)
20
120
100
80
60
40
20
0
Ozone
3
(d)
15
CO
2
10
1
5
0
CO (ppm)
7
(b)
O3 (ppb)
4
15
20
OC/EC Ratio
5
(a)
Rainfall (mm)
OC/EC Ratio
20
0
31
1
July
2
August
Figure 4. Time series of OC/EC ratio (undenuded QF) and gaseous tracers of
photochemical activity and primary emissions for different periods in July 2001, during
the summer intensive at the Pittsburgh Supersite. (a) Ozone and OC/EC ratio. (b) OC/EC
ratio affected by rain. (c) Nitrogen oxides and OC/EC ratio. (d) OC/EC ratio and carbon
monoxide.
26
10
(a)
8
OC (g C/m3)
OC (g C/m3)
10
6
4
2
0
(b)
8
6
4
2
0
0
1
2
3
4
5
0
1
EC (g/m3)
3
4
5
EC (g/m3)
10
10
(c)
8
OC (g C/m3)
OC (g C/m3)
2
6
4
2
(d)
8
6
4
2
0
0
0
1
2
3
EC (g/m3)
4
5
0
1
2
3
4
5
EC (g/m3)
Figure 5. Scatter plot of OC vs. EC for all samples collected during the period (summer
intensive 2001). Concentrations shown are form the undenuded sampler, front quartz
data. Hollow circles represent concentrations that have not been classified according to
the criteria used. (a) OC vs. EC for all samples collected during the period of analysis. (b)
Concentrations eliminated from the dataset because they are affected by rain (solid
rhombus). (c) Concentrations strongly influenced by photochemical activity are deleted
from the dataset (solid squares). (d) Final set of concentrations influenced by primary
emissions (hollow triangles). OC/EC primary ratio and intercept, b, are estimated by a
linear fit of these data.
27
(a)
8
6
4
2
OC=2.3*EC+1.2
10
Undenuded OC
QF – QB,F (g C/m3)
Undenuded OC
QF (g C/m3)
10
0
6
4
2
OC=2.6*EC+0.3
0
1
2
3
Undenuded EC, QF
4
5
10
8
6
4
OC=0.9*EC+0.6
0
0
1
2
3
4
Undenuded EC, QF (g/m3)
1
2
3
Undenuded EC, QF
(c)
2
0
(g/m3)
5
Denuded In-situ analyzer
OC (g C/m3)
0
Undenuded OC
QF – QB,T (g C/m3)
(b)
8
10
4
5
(g/m3)
(d)
8
6
4
2
OC=1.7*EC+0.9
0
0
1
2
3
4
5
Denuded In-situ analyzer EC (g/m3)
Figure 6. Estimated carbonaceous concentrations influenced by primary emissions and
SOA production for high-time resolution measurements (2-6 hrs samples) during the
summer intensive at PAQS. Solid squares correspond to SOA influenced concentrations
and hollow triangles to primary dominated concentrations. (a) Front quartz OC (QF) and
EC concentrations. (b) Correcting the OC measurement with the backup quartz filter
behind the front quartz (QF-QB,F). (c) Correcting the OC concentrations with the backup
quartz filter behind the Teflon filter in the parallel undenuded line (QF-QB,T).(d) Denuded
in-situ analyzer.
28
10
(a)
8
Undenuded OC
QF – QB,F (g C/m3)
Undenuded OC
QF (g C/m3)
10
6
4
2
OC=2.7*EC+1.3
0
(b)
8
6
4
2
OC=2.3*EC+1.2
0
0
1
2
3
4
5
0
Undenuded EC, QF (g/m3)
Denuded In-situ analyzer
OC (g C/m3)
Undenuded OC
QF – QB,T (g C/m3)
5
10
10
(c)
8
6
4
2
OC=1.6*EC+0.5
0
0
1
2
3
4
5
3
Undenuded EC, QF (g/m )
10
Denuded sampler
OC (g C/m3)
1
2
3
4
Undenuded EC, QF (g/m3)
(d)
8
6
4
2
OC=1.9*EC+0.7
0
0
1
2
3
4
5
3
Denuded In-situ analyzer EC (g/m )
(e)
8
6
4
2
OC=3.1*EC+1.0
0
0
1
2
3
4
5
Denuded sampler EC (g/m3)
Figure 7. Estimated carbonaceous concentrations influenced by primary emissions and
SOA production for daily averaged and 24 hrs measurements during the summer
intensive at PAQS. Solid squares correspond to SOA influenced concentrations and
hollow triangles to primary influenced concentrations. (a) Front quartz OC (Q F) and EC
concentrations. (b) Correcting the OC measurement with the backup quartz filter behind
the front quartz (QF-QB,F). (c) Correcting the OC concentrations with the backup quartz
filter behind the Teflon filter in the parallel undenuded line (QF-QB,T).(d) Denuded in-situ
analyzer. (e) Denuded sampler.
29
6
(a)
4
2
0
SOA (g C/m3)
6 1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031 1 2 3 4
(b)
4
2
0
6 1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031 1 2 3 4
(c)
4
2
0
6 1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031 1 2 3 4
(d)
4
2
0
11 13 15 17 19 21 23 25 27 29 311 2 23 4
11 2 3 34 55 6 77 8 9910111213141516171819202122232425262728293031
July
August
Figure 8. Estimated SOA concentrations based on the higher resolution measurements of
OC and EC. (a) Undenuded sampler, QF. (b) Undenuded sampler, QF-QB,F. (c)
Undenuded sampler, QF-QB,T. (d) Concentrations from the denuded in-situ analyzer.
30
0
31
July
SOA (g/m3)
8
1
2
2
10
0
0
30
3
Temperature
35
30
25
4
20
2
15
0
10
July
31
1
July
6
21 22 23 24 25 26 27 28
20
4
August
(c)
30
6
10
SOA (g/m3)
30
40
Solar Radiation
Solar radiation
2
8
(b)
2
3
August
RH
8
(d)
100
80
6
60
4
2
40
0
20
RH (%)
4
SOA (g/m3)
6
10
10
O3 (ppb)
8
120
100
80
60
40
20
0
(a)
Ozone
Temperature (C)
SOA (g/m3)
10
21 22 23 24 25 26 27 28
July
Figure 9. Hourly SOA production patterns for various periods during the summer
intensive 2001 at PAQS. SOA concentrations calculated from the undenuded front quartz
dataset (QF). (a) Ozone concentration and SOA production. (b) Solar radiation (UV) and
SOA production. (c) Relative humidity has a minor role on the production of SOA. (d)
Ambient temperature influences over the SOA production in Pittsburgh.
31
undenuded
QF –QB,T
undenuded
QF and QF –QB,F
(a)
Denuded
in-situ
SOA/Avg. SOA
OC pri/Avg. OC pri
1.6
1.4
1.2
1.0
0.8
0.6
0.4
1.6
1.4
1.2
1.0
0.8
0.6
0.4
00123456789
3 6 91011112
15
21
2131415
1617118
8192021
2223
undenuded
QF –QB,T
undenuded
QF and QF –QB,F
Time of Day (EST)
40
NOx
20
10
0
0
3
6
9 12 15 18 21
Time of Day (EST)
0.5
CO
0.4
(d)
30
20
0
CO (ppm)
40
NOx (ppb)
O3 (ppb)
(c)
Ozone
60
Denuded
in-situ
00123456789
3 6 91011112
15
21
2131415
1617118
8192021
2223
Time of Day (EST)
80
(b)
0
3
6
9 12 15 18 21
Time of Day (EST)
(e)
0.3
0.2
0.1
0.0
0
3
6
9 12 15 18 21
Time of Day (EST)
Figure 10. Average daily pattern of SOA and primary OC concentrations (normalized)
during the summer intensive at PAQS, plotted along with daily averaged concentrations
of various atmospheric variables. (a) Daily pattern primary OC estimated from highresolution samplers. (b) Daily pattern SOA estimated from high-resolution samplers (c)
Ozone average daily concentrations. (d) NOx average daily concentrations. (e) CO
averaged daily concentrations.
32
10
SOA
8
(a)
Primary OC
6
4
2
0
10 1
3
5
7
9
11 13
15
17 19
21
23 25
27 29
31
2
(b)
8
OC (g C/m3)
6
4
2
0
10 1
3
5
7
9
11
13 15
17
19 21
23
25
27 29
31
2
(c)
8
6
4
2
0
10
1
3
5
7
9
11 13 15 17 19 21 23 25 27 29 31 2
(d)
8
6
4
2
0
1
3
5
7
9
11
13
July
15
17 19
21
23
25 27
29
31
2
August
Figure 11. Daily averaged SOA and primary OC concentrations during the summer
intensive, estimated from the high-resolution measurements. (a) Undenuded sampler, QF.
(b) Undenuded sampler, QF-QB,F. (c) Undenuded sampler, QF-QB,T. (d) Concentrations
from the denuded in-situ analyzer.
33
Denuded
DenuderIn-situ
in-situ
analyzer
(2-4
hr)
Analyzer(2-6 hrs)
Undenuded,
Q-Q
Undenuded,
QF-QB,F
(4-6hrs)
hr)
correction
(4-6
Undenuded,
Q-TQ
Undenuded,
QF-QB,T
(4-6hrs)
hr)
correction
(4-6
Undenuded
front
Undenuded,
Q
(4-6
hr)
quartz
(4-6 hrs)
F
0%
20%
40%
60%
80%
100%
% Secondary OC
Figure 12. Summer intensive average SOA fraction of the Pittsburgh organic aerosol for
all high-resolution datasets (2-6 hrs sampling times). From all the datasets, in average 30
to 50% contribution of SOA is calculated.
34
10
SOA
8
(a)
Primary OC
6
4
2
0
10 1
3
5
7
9
11 13
15
17 19
21
23 25
27 29
31
2
(b)
8
6
4
2
OC (g C/m3)
0
10
1
3
5
7
9
11 13 15 17 19 21 23 25 27 29 31 2
8
(c)
6
4
2
0
10
1
3
5
7
9
11
13 15
17
19 21
23
25
27 29
31
8
2
(d)
6
4
2
0
10
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
8
2
(e)
6
4
2
0
1
3
5
7
9
11
13
July
15
17
19
21
23
25
27
29
31
2
August
Figure 13. Daily averaged SOA and primary OC concentrations during the summer
intensive, estimated from the daily averaged concentrations (24 hrs averages). (a)
Undenuded sampler, QF. (b) Undenuded sampler, QF-QB,F. (c) Undenuded sampler, QFQB,T. (d) Concentrations from the denuded in-situ analyzer. (e) Concentrations from the
denuder sampler.
35
Denuder
Sampler
Denuded
sampler
(24
(24 hrs)
hr)
Denuded
In-situ
Denuder in-situ
analyzer (24
(24 hr)
Analyzer
hrs)
Undenuded,
Undenuded,Q-Q
QF-QB,F (24
correction
(24hr)
hrs)
Undenuded,
Q-TQ
Undenuded,
Q
-Q
(24
correction
hrs)
F
B,T (24hr)
Undenuded
Undenuded, front
Qquartz
(24 hrs)
F (24 hr)
0%
20%
40%
60%
80%
100%
% Secondary OC
Figure 14. Summer intensive average SOA fraction of the Pittsburgh organic aerosol for
all datasets (24 hrs averaged concentrations). From all the datasets, in average 18 to 25%
contribution of SOA is calculated.
36
80%
(a)
60%
40%
20%
0%
0%
20%
40%
60%
80%
100%
SOA, all other samplers (g C/m3)
SOA, all other samplers (g C/m3)
100%
100%
(b)
80%
60%
40%
20%
0%
0%
Undenuded SOA, QF (g C/m3)
+ % SOA, Undenuded Sampler (QF-QB,F)
% SOA, Undenuded Sampler (QF-QB,T)
20%
40%
60%
80% 100%
Undenuded SOA, QF (g C/m3)
x
% SOA, Denuded in-situ analyzer
% SOA, Denuded sampler
Figure 15. Correlation of daily percentage SOA contribution to the total OC for the
different samplers for the summer intensive at PAQS for all datasets. Solid line represents
the 1:1 fit and dashed lines are 20% error lines. (a) % SOA contributions from highresolution measurements. (b) % SOA contributions from daily averaged measurements.
37