Introduction
Exposure to ambient particulate matter (PM) is associated with
adverse health effects (Atkinson et al., 2001; Li et al., 2003a; Lim et
al., 2012; Pope, 1995; Pope and Dockery, 2006). The mechanisms of PM toxicity
are complex and not completely understood. One view is that PM toxicity
occurs through inducement of oxidative stress (Delfino et al., 2005, 2013;
Nel, 2005): a state of biochemical imbalance in which the presence and
formation of reactive oxygen species (ROS) in the human body overwhelms
antioxidant defenses, eventually leading to various adverse health outcomes
(Delfino et al., 2011; Donaldson et al., 2001; Li et al., 2003a). ROS can be
either transported on inhaled particles to the air–lung interface or
generated in vivo by interaction between deposited PM and physiological
chemical components (Lakey et al., 2016). The ability of PM to generate ROS
is defined as the oxidative potential (OP) of PM. OP integrates various
biologically relevant properties of particles, including size, surface, and
chemical composition, which may better reflect the biological response to PM
exposure and consequently be more informative than PM mass, or specific PM
chemical species, when attempting to link aerosols to adverse health effects.
Various methods have been developed to assess PM OP (Ayres et al., 2008; Cho
et al., 2005; King and Weber, 2013; Mudway et al., 2004; Shi et al., 2003;
Wang et al., 2011). The dithiothreitol (DTT) assay is used in this study to
measure the OP of fine particles (i.e., OPDTT). DTT acts as a
surrogate of cellular reductants, such as NADH/NADPH. The goal is to mimic
interactions between physiological reductants and aerosol components through
a purely chemical analysis. Various aerosol components can react directly
with antioxidants (reducing agents) or transfer electrons from the
antioxidants to dissolved oxygen, leading to antioxidant depletion in the
first case and both antioxidant depletion and ROS generation in the second.
In the DTT assay, physiological reductants are represented by DTT. When this
reaction is monitored under conditions of excess DTT, the DTT consumption
over time is proportional to the concentration of PM redox-active species,
quantified as OPDTT. OPDTT per volume of air sampled
has been found to correlate with biological markers, such as cellular
heme oxygenase (HO-1) expression (Li et al., 2003b) and fractional exhaled
nitric oxide (FENO) in human subjects (Delfino et al., 2013;
Janssen et al., 2015). Epidemiological studies have linked OPDTT
to adverse health outcomes, such as asthma, rhinitis (Yang et al., 2016),
asthma or wheezing, and congestive heart failure (Bates et al., 2015; Fang et
al., 2016). Utilizing different measures of OP (e.g., ascorbic acid, AA;
glutathione, GSH; uric acid, UA), some other studies, however, have not found
links between OP and adverse health effects (Atkinson et al., 2016; Canova et
al., 2014).
OPDTT of water-soluble PM components (referred to as
OPWS-DTT) is the common focus of OP studies. Researchers
have identified DTT-active water-soluble PM components, including humic-like
substances (HULIS) (Lin and Yu, 2011; Verma et al., 2012, 2015b), oxygenated
quinones (a subset of HULIS) (Cho et al., 2005; Kumagai et al., 2002), and
transition metals (Charrier and Anastasio, 2012; Fang et al., 2016; Verma et
al., 2015a). Water-insoluble species can also be an important fraction of the
overall PM redox activity. Li et al. (2013) found that the solid particle
phase was a dominant factor in the DTT-based redox activity of soot
particles. Akhtar et al. (2010) found that redox-active substances could be
strongly bound to solid particles and not be easily extracted by water.
McWhinney et al. (2013) reported that 89–99 % of the redox activity of
diesel exhaust particles (DEPs) were water-insoluble and not extractable by
moderately polar (methanol) and nonpolar (dichloromethane) organic solvents.
Daher et al. (2011) reported the highest intrinsic OPDTT for
particle collection with a BioSampler, which was considered most efficient in
capturing both the soluble and insoluble PM species. Including the
contribution of water-insoluble species in the OP assessment would be closer
to actual PM exposure. A measure of both water-soluble and water-insoluble OP
would be useful to elucidate the relative risks of water-soluble versus
water-insoluble OP-induced health risks for specific health end points, such
as respiratory versus cardiovascular dysfunction.
Several PM extraction methods have been used to assess the OP of
water-insoluble PM. A common approach is to extract water-insoluble species
in organic solvents, such as methanol and dichloromethane. Verma et
al. (2012) found OPDTT (expressed per microgram of PM mass) of
filtered methanol extracts to be correlated with water-insoluble organic
carbon (OC) and elemental carbon (EC, N=8). The DTT assay response for the
methanol extracts was significantly higher than that for the water extracts,
with a methanol-to-water OPDTT ratio of 1.6±0.4. Yang et
al. (2014) compared OPDTT of ambient PM with two extraction
methods for Teflon filters: methanol extraction without filtering and water
extraction. They found that the methanol extracts were more DTT-reactive
(expressed per cubic meter of sampled volume) than the water extracts. In
this method, removal of organic solvent by evaporation was necessary prior to
the DTT assay, which can result in the loss of labile redox-active PM
species, such as semi-volatile organic compounds. Instead of attempting to
dissolve water-insoluble species in various solvents, other studies perform
the assay in the extraction liquid without filtration, retaining the
insoluble particles in the DTT reaction solution. McWhinney et al. (2013)
measured total redox activity of DEPs using particle suspensions that were
obtained by a water extraction procedure with the filter removed after
extraction. Whereas Charrier et al. (2016) performed the DTT assay on the
extraction liquid that still contained the filter. Daher et al. (2011)
collected particles directly into water with a BioSampler and performed the
DTT analysis without filtration.
In this study, we assess techniques for quantifying the overall oxidative
potential of ambient particles and determine the relative contribution from
water-soluble and water-insoluble components to PM OP by contrasting
measurements from different sites. This was accomplished by conducting the
DTT assay on samples extracted by three different methods. The goal was to
develop a system for measuring both soluble and total OPDTT
(insoluble OPDTT by difference) fractions to allow studies on the
health effects of soluble (Bates et al., 2015) versus insoluble PM OP.
Experimental methods
Sampling methods and locations
Measurements were made at two contrasting sampling sites: Georgia Tech (GT)
and roadside (RS). The GT site was situated on the rooftop of the Ford
ES&T building on the campus of Georgia Tech about 30 m above
ground level and approximately 420 m from the roadside site. (A map
of the sites is provided in Fig. S1 in Supplement.) The GT site is assumed to
be representative of the urban Atlanta environment. The RS site is adjacent
(within 3 m) to a heavily trafficked interstate freeway (I-85/75)
with an annual average daily traffic count of 382 000 vehicles in 2015
(GDOT, 2017; station ID 1215482). Heavy-duty trucks are restricted,
resulting in predominantly light-duty gasoline vehicle traffic
(non-heavy-duty truck traffic nominally 95 %; GDOT, 2013).
Measurements were undertaken during two different periods using different
particle filter collection systems. A high-volume (HiVol) sampler (Thermo
Anderson, nominal flow rate of 1.13 m3min-1, PM2.5 impactor)
was set up at each site to collect ambient fine particles simultaneously from
21 April to 30 May 2016. Fine particles were collected with prebaked 8×10 in. quartz filters (Pallflex Tissuquartz, Pall Life Sciences) for
23 h (11:00–10:00 LT the next day). The HiVol quartz filters were
wrapped in prebaked aluminum foil immediately after collection and stored at
-18 ∘C until analyses. The bias between the two HiVol samplers
was assessed by running them side by side at GT for 9 days. The measurements
were within 10 % for both water-soluble OPDTT
(OPWS-DTT) and total OPDTT
(OPTotal-DTT) (obtained by method 3, described below)
(Fig. S2). In Sect. 3.4, OP data from HiVol 1 were adjusted to match HiVol 2
based on the orthogonal linear regression from this comparison. The factors
used to convert OP from HiVol 1 to HiVol 2 were 1.00 and 1.10 for
OPWS-DTT and OPTotal-DTT, respectively.
Zefluor PTFE membrane filters (diameter 47 mm, 2 µm pore
size, Pall Life Sciences) were used as well for simultaneous PM2.5
sample collection from 26 July to 21 August 2016 using particle composition
monitors (PCMs, 16.7 Lmin-1, PM2.5 URG cyclone, undenuded).
Two PCMs were installed at each site to obtain two Teflon samples; one was
used for OPWS-DTT and the other for
OPTotal-DTT analysis. Similar to the HiVol filter
sampling, after 23 h collection, the PCM Teflon filters were placed into
Petri dishes and stored at -18 ∘C.
Measurements of PM oxidative potential
OP analyses were performed on both HiVol quartz and PCM Teflon filters. The
DTT assay followed the protocol developed by Cho et al. (2005). All OP
analyses on HiVol quartz filters were done immediately after collection; OP
measurements on Teflon filters were completed within 1 month after
collection.
OPWS-DTT analysis
One circular punch (diameter of 1 in.) from the HiVol quartz filter
was extracted in 4.9 mL of deionized water (DI,
> 18 MΩcm-1) in a sterile polypropylene centrifuge
tube (VWR International LLC, Suwanee, GA, USA) via 30 min sonication.
Considering the potential for radical formation during the sonication process
(Miljevic et al., 2014), experiments using sonication versus shaking were
done. Little difference observed in OP for sonication versus shaking
indicated negligible bias in OPWS-DTT measurement due to
sonication; see Fig. S3. The extract was then filtered through
0.45 µm PTFE syringe filters (Fisherbrand, Fisher Scientific) to
remove insoluble material. The filtered PM water extract was analyzed using a
semi-automated system (OPWS-DTT system) developed by Fang
et al. (2015) where all chemical reagents and reaction mixtures were mixed
and transferred by two programmable syringe pumps. Briefly, 3.5 mL water
extract is incubated with 0.5 mL of 1 mM DTT and 1 mL potassium
phosphate buffer (K-buffer; pH = 7.4) in a single incubation vial (IV) at
37 ∘C. At designated time points (0, 4, 13, 23, 32, 41 min), an
aliquot (100 µL) of this mixture is transferred to another vial
(reaction vial, RV) and mixed with trichloroacetic acid (TCA) to quench the
reaction. Tris buffer (pH = 8.9) and 5,5'-dithiobis-(2-nitrobenzoic acid)
(DTNB) are then added to form a colored product which absorbs light at
412 nm. The final mixture is pushed through a 10 cm path length
liquid waveguide capillary cell (LWCC), and the absorbance at 412 nm
is detected and recorded by an online UV–visible spectrophotometer. The DTT
concentration at each time point is quantified based on the absorbance
calibration curve, which had previously been determined from standard DTT
solutions also containing TCA, tris buffer, and DTNB. The DTT consumption
rates are then determined by applying linear regression to the observed DTT
concentration versus time. The final OP results are calculated by subtracting
a blank value from the sample and normalized by the volume of air that passed
through the filter (of 1 in. diameter punch size), expressed as nanomoles of
DTT per minute (nmolDTTmin-1) per sampled air volume
(OPWS-DTT m-3; if not explicitly stated,
OPWS-DTT is OPWS-DTT m-3) to
provide a measure of atmospheric levels of water-soluble aerosol OP. The DTT
consumption rates of multiple blanks for quartz filters (N=42) were
stable with a mean ±1σ of 0.33±0.07 nmolmin-1.
Since DTT is a relatively unstable compound, it can react with dissolved
oxygen in the liquid in the absence of particles (Kumagai et al., 2002),
resulting in OP response in blanks. The blank OP values are also due to trace
levels of contaminants on the filter, in the DI, and introduced during
sample preparation. 9,10-Phenanthrenequinone (PQN) is used as a positive
control throughout the analysis to evaluate the stability of the analytical
system.
Analytical scheme for three sample extraction methods to determine
total OP with the DTT assay (OPTotal-DTT).
Water extraction was also performed on the PCM Teflon filters. Each of the
two Teflon filters collected simultaneously at each site was cut in half. One
half of each filter was combined and immersed in 4.9 mL DI in a beaker and
sonicated for 30 min. The water extract was then filtered, and
OPWS-DTT determined using the automated system. DTT
analytical processing was exactly the same as that for quartz filters
described above. The other filter halves were stored in a freezer until
OPTotal-DTT analysis. This analysis approach removed any
potential biases associated with the separate filter collection systems at
each site. Sample flow rates were measured at the beginning and end of
sampling for each filter system, and the overall average was used to calculate
OPWS-DTT per cubic meter. Field blanks were also tested in the
same manner and had an average slope plus or minus standard deviation of
0.35±0.08 nmolmin-1 (mean ±1σ, N=18).
OPTotal-DTT analysis
Sample extraction and preparation
To assess methods for characterizing OPTotal-DTT, we used
three different methods of sample preparation using the HiVol quartz filters.
Sample preparation schemes are illustrated in Fig. 1. Multiple method
analysis was done only on HiVol filters since there was insufficient mass
collected to compare different methodologies using the PCM Teflon samples.
Method 1 consisted of two steps: water extraction and sequential
methanol extraction. A 1 in. circular punch taken from the HiVol quartz
filter was extracted in 4.9 mL DI via 30 min sonication. The water extract
was then filtered using a 0.45 µm PTFE syringe filter. This step
was the same as the measurement of OPWS-DTT. The
water-extracted filter punch was retained in the vial, dried in room air, and
re-extracted using methanol (HPLC grade) via 30 min sonication. The
methanol extract was also filtered through a syringe filter
(0.45 µm PTFE) and then concentrated to about 200 µL
using high-purity nitrogen gently blown into the vial above the liquid
surface. DI was added into the vial to reconstitute the small aliquot of
remaining methanol liquid to 4.9 mL of solution. The reconstituted
extract was stirred using a vortex mixer
(VWR® Analog Vortex Mixer,
300–3200 rpm) for 10 s to resuspend any particles deposited
on the walls of the vial during methanol blow-down. The purpose of the
sequential and filtered methanol extraction was to assess if water-insoluble
species could be dissolved by methanol as a way of quantifying the
water-insoluble OPDTT through a contrast to methods that retained
solid particles (discussed next). As methanol is less polar than water, it
may dissolve most of the water-insoluble organic species in addition to some
water-soluble compounds. However, since the solid-phase material in the
extract may have been removed by filtering the extract, this method will not
include DTT-active species that cannot be separated from a solid particle and
is therefore removed by the syringe filter. The determination of
OPDTT for both water extract (OPWS-DTT) and
sequential DI-reconstituted methanol extract (OPsM-DTT)
was conducted using the OPWS-DTT analytical system since
all extracts had been filtered, avoiding any plugging or contamination issues
in the analytical system by solid particles. The sum of
OPWS-DTT and OPsM-DTT is the total
redox activity obtained by method 1, which will be denoted as
OPTotal-DTT-1. Blank filters were also similarly
processed and analyzed for OPDTT, producing blank values of
0.33±0.07 nmolmin-1 (mean ±1σ, N=42) for
OPWS-DTT and 0.43±0.09 nmolmin-1
(mean ±1σ, N=18) for OPsM-DTT. This
method was used in the Southeastern Center for Air Pollution and Epidemiology
(SCAPE) study, so a substantial data set (N=198) exists on
OPsM-DTT.
Automated system setup for measuring OPDTT-Total.
The assay is performed in the vial containing the filter sample and
extraction water, which had been sonicated. The assay is filtered just prior
to analysis in the liquid wave guide capillary cell (LWCC).
Method 2 is similar to the methanol extraction by Yang et
al. (2014). The filter punch was extracted in methanol via 30 min
sonication. After extraction, the filter punch was removed from the vial. The
methanol extract was not filtered so that the methanol-insoluble components
were also retained and would possibly participate in the subsequent DTT
reaction. The methanol suspension was blown down to nominally
200 µL using nitrogen gas and reconstituted to 4.9 mL
with DI. The reconstituted extract was stirred for 10 s using a
vortex mixer in an attempt to resuspend particles deposited on vial walls.
Due to the presence of solid material in the extract, such as quartz filter
fibers released by sonication, the OPWS-DTT system could
not be utilized. Instead, a modified automated system was needed to measure
the OP of this aqueous suspension, discussed below. The OPDTT of
PM sample extracted in this manner is referred to as
OPTotal-DTT-2. The blank value for this method was
0.42±0.13 nmolmin-1 (mean ±1σ, N=18).
Method 3 is the easiest to perform among the three methods in terms
of sample preparation (Fig. 1). In this case the circular filter punch was
immersed in the mixture of 4.9 mL DI and 1.4 mL K-buffer in a sterile
polypropylene centrifuge tube, followed by 30 min sonication. The DTT assay
was then performed directly in the vial with the filter punch present using
the modified automated system discussed below. Some DTT-active species may be
strongly absorbed to the filter surface so that they are not extractable into
water. But in method 3, since the whole filter is suspended in DTT solution,
these DTT-active species may participate in the reaction with DTT. In the
study of Charrier et al. (2016), where DTT was also directly incubated with
the PM filter, an alcohol, 2,2,2-trifluoroethanol, was added to the
extraction solvent to facilitate removal of particles from the filter
substrate. We tested adding small amounts of methanol (up to 10 % of
total extraction volume) into the extraction solvent to investigate if
methanol would expose more solid aerosol for reaction with DTT, which would
be observed as an increase in DTT response. The test results are given in
Fig. S4 and show that the added methanol had negligible effects on the final
OPDTT measured; therefore, only DI was used for extraction in
this method. The OPDTT obtained in this way is referred to as
OPTotal-DTT-3. Sonication-versus-shaking tests were
also performed in method 3, and the results (Fig. S5) show little effect of
sonication on OPTotal-DTT-3 measurements. Only
method 3 was used for the OPTotal-DTT determination of
Teflon filters. Multiple blanks were processed similarly with DTT consumption
rates of 0.37±0.06 nmolmin-1 (mean ±1σ,
N=18) for quartz filters and 0.43±0.04 nmolmin-1
(mean ±1σ, N=18) for Teflon filters.
Automated system for OPTotal-DTT measurements
A modified automated analytical system for OPTotal-DTT was
developed by modifying the OPWS-DTT system of Fang et
al. (2015) for analysis of filters extracted using methods 2 and 3. A
schematic is shown in Fig. 2. In this approach the sample extraction vial
containing the suspension or suspension plus filter that had gone through
method 2 or 3 extraction is placed in the thermal mixer, prior to which
1.4 mL K-buffer had been loaded manually. In this case, each sample vial is
used as an incubation vial directly, continuously shaken, and maintained at
37 ∘C via a ThermoMixer (VWR® Cooling
Thermal Shake Touch; rotational frequency of 400 rpm, temperature of
(37±0.5) ∘C). Two PEEK tubes (PEEK Tubing Green 1/16 in.
OD × 0.030 in. ID), which are connected to a 14-port multi-position
valve (Valco Instrument Co. Inc. (VICI), USA), are inserted into each
incubation vial, with one tube having an in-line syringe filter
(0.45 µm polypropylene, filter media, Whatman) and the other
not. For each run, 0.7 mL DTT (1 mM) is loaded into the incubation
vial through the tubing without in-line filter via the programmable syringe
pump A (see Fig. 2). Air is then pumped into the incubation vial to
thoroughly mix. In the mixture, DTT is presumably oxidized with the catalytic
assistance of both water-soluble and water-insoluble DTT-active species
associated with the PM collected on the HiVol quartz or PCM Teflon filter.
After mixing, the multi-position valve is switched so that the syringe can
withdraw an aliquot of sample through the filter, at a low speed so as not to
form air bubbles by cavitation. At designated time intervals (13, 30, 48, 65,
82 min), the aliquot is withdrawn through the in-line filter,
transferred to the RV and mixed with TCA preloaded in the
vial by pump B. The DTT concentration is then determined following the same
steps as for the OPWS-DTT system (Fang et al., 2015).
A total of five data points of remaining DTT concentrations versus time are
generated and used for the final OPDTT determination. After
finishing the DTT analysis of each sample, the system is thoroughly cleaned
by flushing with DI to remove the residual liquid left in the various tubing,
reaction vial, pump syringes, and LWCC. Following the flushing, the 14-port
multi-position valve is switched to the next sample for analysis. Due to the
slow piston motions in liquid transfer from IV to RV, it generally takes
1.5 h for OPTotal-DTT system to analyze one
sample, compared with 1 h of analysis time of
OPWS-DTT. The OPTotal-DTT system, like
the OPWS-DTT system, can operate unattended and be
monitored remotely to analyze, at least, seven filters. (This is limited by
the 14 channels of the multi-position valve in Fig. 2.) To avoid
contamination from the insoluble material captured in the in-line syringe
filter, the syringe filter is replaced after each sample run. The automated
system is cleaned every 4 weeks of continued operation by flushing at least
three times with methanol, followed by four times with DI.
Other chemical analysis
A number of other aerosol components were analyzed on the HiVol quartz
filters to assess the various methods of measuring
OPTotal-DTT. Carbon analysis (EC and OC) was performed
on a 1.5 cm2 punch from the quartz filters using Interagency
Monitoring of Protected Visual Environments (IMPROVE) thermal optical
reflectance (TOR) protocol (Chow et al., 1993).
Total and water-soluble metals were determined by inductively coupled
plasma mass spectrometry (ICP-MS) (Agilent 7500a series, Agilent
Technologies, Inc., CA, USA) using EPA method 6020, again from sections of
the same HiVol quartz filters. The elements of interest included species that
possibly play a role in ROS generation (Fe, Mn, Cu; Schoonen et al., 2006)
and K, a marker of biomass burning (Artaxo et al., 1994). For the
determination of concentrations of total metals, acid digestion was carried
out on a 1.5 cm2 filter punch using nitro-hydrochloric acid
(HNO3 + 3HCl). The acid-digested sample was then diluted
in DI, filtered with a 0.45 µm PTFE syringe filter. No
digestion was required prior to the analysis of water-soluble metals. A
1.5 cm2 punch from the quartz filter was sonicated in DI for
30 min. After sonication, the extract was filtered using a
0.45 µm PTFE syringe filter and then acid-preserved by adding
concentrated nitric acid (70 %) to a final concentration of 2 %
(v/v). A set of mixed calibration standard solutions were prepared by
diluting the stock standard solutions and treated with the same procedures as
samples. Internal standards, including lithium (6Li) and scandium
(45Sc), were added to all calibration standards and samples to
monitor instrumental drift. DI blank and field blank which consist of the same
concentrations of acid and internal standards were used to monitor for
possible contamination resulting from the sample preparation procedures. This
was critical since in this case no special care was taken to pre-acid-wash
the quartz filters or syringe filters used in the water-soluble metal
analysis. The method detection limits are defined here as 3 times the
standard deviation of blanks, which for water-soluble metal method were
0.03 mgL-1 for K, 0.00007 mgL-1 for Mn,
0.009 mgL-1 for Fe, and 0.0002 mgL-1 for Cu; for
the total metal method they were 0.03 mgL-1 for K,
0.0002 mgL-1 for Mn, 0.02 mgL-1 for Fe, and
0.002 mgL-1 for Cu.
Data analysis
Linear regression was applied to the experimental data in order to assess
relationships between measurements. Since the data were normally distributed
(shown in Fig. S6), the Pearson correlation coefficients were calculated to
further demonstrate the strength and the direction of a linear relationship
between two measurements. A correlation coefficient greater than 0.7 with a
low p value (< 0.05) was generally described as strong.
The paired t tests were used to determine whether there was a significant
difference in OP measurements between two methods. Each
OPTotal-DTT was measured using three methods, resulting in
pairs of observations. The null hypothesis of the paired t test assumed
that the mean difference between the paired observations was zero. The p value
of the test gave the probability of observing the test results under the null
hypothesis; p values less than 0.05 rejected the null hypothesis at the
5 % significance level.
The F tests in one-way analysis of variance (ANOVA) were employed to
evaluate the impact of filter type (i.e., quartz versus Teflon filters) on
the PM OP measurements for a given site. The F statistic is the ratio of
between-group variability to within-group variability, which followed an
F distribution under the null hypothesis. In this paper, the null
hypothesis assumed that there was no significant OP difference between Teflon
and quartz filters. If the F calculated from the data were smaller than the
critical F value of the F distribution for significance level α=0.05, then the null hypothesis would be true with 95 % confidence.
The spatial variability of OP (Table S6 in Supplement) was assessed by the
coefficients of divergence (COD) (Pinto et al., 2004; Wilson et al., 2005):
COD=1N∑i=1Ncij-cikcij+cik2,
where cij and cik were OPWS-DTT or
OPTotal-DTT measured at site j and k, respectively,
and N was the number of observations. A COD close to 0 implied spatial
uniformity, while a value approaching unity indicated absolute heterogeneity.
Results and discussion
First we discuss the performance of the automated system for measuring
OPTotal-DTT where filters were extracted by method 3
(Fig. 1), and then we compare the results of the three differing methods for
measuring OPTotal-DTT at the two sampling sites. The
system performance was assessed by only method 3 since these samples were
easiest to prepare, and this is the final approach of the three methods tested
that was extensively utilized. Finally, we compare results from method 3
using quartz filters to a later study using Teflon filters. All
OPDTT results were blank-corrected.
Automated OPTotal-DTT system performance
The performance of the automated system was assessed in terms of the system
response, accuracy, and precision. PQN, a quinone
that has been identified to be DTT-active (Kumagai et al., 2002) and often
utilized as a positive control (Fang et al., 2015), was used to test the
system response. A highly linear relationship (R2=0.97) was found
between PQN concentration in the incubation vial and the DTT consumption rate
measured by the system (shown in Fig. 3). This linear relationship is
consistent with the results shown in Fang et al. (2015) and Charrier et
al. (2016).
The accuracy of measurements given by the OPTotal-DTT
system was further assessed by comparing the DTT consumption rate obtained by
the system to that following the manual DTT analysis approach of Cho et
al. (2005). Seven PQN solutions of various concentrations were tested by both
the automated system and manual approach. As shown in Fig. 4, a bivariate
linear regression was applied and yielded a slope near unity (0.99±0.06), intercept close to 0 (0.04±0.04), and correlation of
determination (R2) of 0.98. For further validation, five ambient samples,
which in this case would include insoluble species, were extracted by
method 3 and analyzed using both the automated and manual methods (see
Fig. S7). The ratio of automated to manual DTT consumption rate was 0.98±0.05. These tests illustrate the validity of the
OPTotal-DTT system as an alternative to the manual DTT
assay.
Blank-corrected DTT consumption rate as a function of PQN showing
linearity between PQN concentrations and DTT consumption rate for the total
analytical system (for PQN levels shown in the range above). Error bar
represents the standard deviation of three independent DTT measurements on
each concentration.
DTT consumption rate (blank-corrected) comparison of the automated
system for measuring OPTotal-DTT (shown in Fig. 2) to a
manual analysis using PQN (9,10-phenanthraquinone). Slope (±1 standard
deviation) and intercept (±1 standard deviation) are based on orthogonal
regression.
To assess the precision of the automated OPTotal-DTT
system, the DTT consumption rates of identical concentrations of several PQN
solutions were repeatedly measured. The OPTotal-DTT system
produced consistent results for the PQN replicates (blank-corrected DTT
consumption rate of 0.76±0.05 nmolmin-1 for
0.21 nmolmL-1 of PQN in the incubation vial; coefficient of
variation, CV = 6 %; N=7), suggesting good precision of the
system. We conclude that most variability in the analysis of samples will be
introduced in the extraction process and not the DTT analysis.
Comparison of OPDTT m-3 between extraction
methods 1 and 3 at (a) GT (N=35) and (b) RS
(N=31). Error bars denote 1 standard deviation in OPDTT
m-3 from repeated measurements and are propagated in calculating
OPTotal-DTT-1.
Precisions of various methods
To test the precision of the complete approach for measurement of
OPTotal-DTT (i.e., extraction and analysis), measurements
of OPTotal-DTT were repeated three times using three
separate punches from the same HiVol quartz filter. This was done for all
three OPTotal-DTT methods. The CV for replicates is used to assess the precision of each method. The
results are summarized in Table 1. CV ranged from 3 to 6 % for method 1,
which may result from the combined uncertainties of the two respective steps
(i.e., extraction and analysis). The range of CV for method 2 was from 5 to
12 %. The root of this variability may arise from the insoluble material
remaining in the reaction suspension that was difficult to reproduce from
run to run. In contrast, lower CV (1 % ∼ 5 %) was observed for
method 3, possibly because it involved the fewest steps in the filter
extraction.
Coefficient of variation (CV) of OPTotal-DTT for
three extraction methods.
Method 1
Method 2
Method 3
Coefficient of variation
3–6 %
5–12 %
1–5 %
(CV) from triplicate
N=10
N=7
N=12
N is the number of HiVol filters tested.
Comparison of OPDTT m-3 between methods 2 and 3 at
(a) GT (N=35) and (b) RS (N=31). Error bars
denote 1 standard deviation in OPDTT m-3 from
repeated measurements.
Comparison of methods for measuring total oxidative potential
(OPTotal-DTT)
Comparison of oxidative potential
In the following, OPDTT per cubic meter determined by the three methods
for simultaneously collected HiVol quartz filters at the GT and RS sites are
compared. Since no standard method is available for assessing the ability to
measure OPDTT per cubic meter, we simply compare the various methods
and assume that the highest measurement represents the most comprehensive
analytical method for measuring total oxidative potential. No HiVol
conversion factors were applied to the OP data as the three methods were all
performed on filters collected using the same HiVol sampler at each site.
Polar plots comparing Pearson correlation coefficients (r) between
various forms of OPDTT m-3 (a OPWS-DTT,
b OPWI-DTT and OPTotal-DTT;
red: OPTotal-DTT; blue:
OPWI-DTT(OPWI-DTT=OPTotal-DTT-OPWS-DTT for
methods 2 and 3)) and PM chemical components at GT (N=34) and RS
(N=29) sites. Correlations not statistically significant
(p value > 0.05) are not shown on the plots but can be found in
Table S2. The red line indicates r=0.7. Note: the scales for method 3 RS
are different from those for the other methods.
Figure 5 shows the OPDTT per cubic meter comparison between methods 1
and 3 at both GT and RS sites. In general, the response of the DTT assay of
method 3 was significantly higher than that of method 1 at the 95 %
confidence level (paired t test: p=0.028 at GT, N=35; p<0.001
at RS, N=31). The results are expected since in method 1 both the
water and methanol liquid extracts are filtered, potentially removing species
that could have been DTT-active but remained attached to solid particles. A
few observations where OPTotal-DTT-3 is less than
OPTotal-DTT-1 are likely due to propagation of
errors for the summation method (method 1) combined with variability in the
extraction process for each method. The mean
OPTotal-DTT-1-to-OPTotal-DTT-3 ratio at GT was close to 1
(ratio = 0.95) and also higher than that at RS (ratio = 0.85). The
lower OPTotal-DTT-1 may be due to liquid filtration
after water extraction. The ratios of OPsM-DTT to
OPWS-DTT are 0.34±0.14 (N=35) at GT and
0.37±0.12 (N=31) at RS, which are consistent with the ratios from
SCAPE data (0.27±0.08, N=198; unpublished data) and fall into the
typical range of ambient samples. The water-insoluble OP determined by the
difference in OPTotal-DTT-3 (which includes solid
particles) and the ratio of OPWS-DTT
(OPWI-DTT-3=OPTotal-DTT-3-OPWS-DTT) to OPWS-DTT, by
contrast, is 0.45±0.25 at GT (N=35) and 0.67±0.35 at RS
(N=31). There was very little correlation between the
OPWI-DTT-3 and OPWS-DTT, with Pearson
correlations of r= -0.23 and -0.51 at GT and RS sites, respectively
(see Table S1), which further indicates the importance of water-insoluble
compounds to a total OP measurement. Additionally,
OPWI-DTT-3 was weakly correlated with
OPsM-DTT (Pearson correlation: r=0.31 at GT, r=0.04 at RS). Based on these data, it is clear that there were species
associated with water-insoluble OPDTT not extracted by methanol
and that remain attached to solid particles. This analysis shows that
filtering the liquid extract, even if methanol solvent is used, will result
in a substantial underestimation of OPTotal-DTT.
Therefore, in terms of the OP response, method 3 is preferred to method 1.
Furthermore, the comparison between these two methods can provide insights
into the water-insoluble components that contribute to PM OP.
Figure 6 shows the comparison of OPDTT per cubic meter between methods 2
and 3 at both GT and RS sites. At the GT site, method 3 generally yielded
higher OP responses than method 2, with a mean
OPTotal-DTT-2-to-OPTotal-DTT-3 ratio of 0.90 (p<0.001 for a
paired t test, N=35). For the RS site, however, method 2 was able to
produce comparable (p=0.060 for a paired t test, N=31) or even
higher OP responses, at times, than method 3 with a
OPTotal-DTT-2-to-OPTotal-DTT-3 ratio of 0.94, which may imply that
method 2, in some cases, might be more efficient in extracting DTT-active
species from the unique RS sources such as vehicular emissions.
From the perspective of OP response, method 3 generally produced the highest
signals compared to the other two methods, in both the urban (GT) and
near-road (RS) sites.
Association between OPDTT and PM composition
A correlation analysis was performed between measured PM2.5 chemical
constituents and OPDTT determined by the three methods. Figure 7
shows the correlation results (detailed values are provided in Table S2). It
is seen that OPTotal-DTT-3 is better correlated
with the measured species than OPTotal-DTT-1 and
OPTotal-DTT-2. Compared with
OPWS-DTT, the stronger correlations between
OPTotal-DTT-1 and PM species suggest that
OPTotal-DTT-1 captures more chemical components
contributing to DTT than OPWS-DTT. In contrast,
OPTotal-DTT-2 is correlated with the fewest number
of measured PM species.
By subtracting OPWS-DTT from
OPTotal-DTT, OPWI-DTT is determined for
the three methods. In general, the correlations between
OPWI-DTT and PM species are mediocre for all three
methods, with a slightly better performance of method 1. The water-insoluble
OPDTT determined by method 1, i.e., OPsM-DTT,
has good correlation with OC at GT and OC, EC, and water-soluble Fe at RS.
Verma et al. (2012) also showed good correlations between OPDTT
of filtered methanol extracts and OC and EC, and attributed this association
to water-insoluble organic carbon species (WIOC) that dissolve in methanol.
Thus, OPsM-DTT in method 1 is likely attributed to some
fraction of the WIOC. OPWI-DTT obtained in method 1 is
determined from the direct measure of OPsM-DTT, whereas
OPWI-DTT is determined by the difference for methods 2 and 3,
which leads to larger uncertainty and more scatter associated with these
data.
The overall assessment of the three methods is summarized in Table 2. By
comparison, it is found that method 3 has better precision, more
comprehensive response (i.e., generally highest
OPTotal-DTT), stronger correlations with PM components,
and easiest filter preparation (extraction) process, all of which provide an
efficient way for OPTotal-DTT determination. The other two
methods have some value owing to their insights into the attributes of
water-insoluble OP contributors. In a subsequent study, discussed next, only
method 3 was utilized to measure OPTotal-DTT of PM for
Teflon filters.
Volume-normalized OPDTT of ambient PM2.5 particles
collected on quartz and Teflon filters at GT and RS sites for two different
sampling time periods. Red lines indicate volume-normalized
OPWS-DTT, and blue lines denote volume-normalized
OPTotal-DTT.
Comparison of methods for measuring OPTotal-DTT.
Method 1
Method 2
Method 3
Measured:
Measured:
Measured:
–
OPWS-DTT
–
OPTotal-DTT-2: OP of methanol-extractable
–
OPTotal-DTT-3: OP of water-soluble and
Description
–
OPWI-DTT-1(OPsM-DTT): OP of water-insoluble
species and some methanol-insoluble solids
water-insoluble species, solids.
but only methanol-extractable species
OPWI-DTT-2=OPTotal-DTT-2-OPWS-DTT
OPWI-DTT-3=OPTotal-DTT-3-OPWS-DTT
OPTotal-DTT-1=OPWS-DTT+OPsM-DTT
Ease of operation
Method 3 > method 2 > method 1
Precision
Method 3 > method 1 > method 2
Comparison
OP magnitude
At GT: method 3 > method 1 > method 2.
At RS: method 3 ≈ method 2 > method 1.
Correlations with
Number of correlations of OPTotal-DTT with various species: method 3 > method 1 > method 2.
PM components
OPWI-DTT: poor or mediocre correlations for all three methods.
OPWS-DTT and OPTotal-DTT measurements on quartz
versus Teflon filters and their spatial distributions
The time series of volume-normalized water-soluble and total
OPDTT via method 3 are shown in Fig. 8 for two different sample
time periods using HiVol samplers with quartz filters (21 April–30 May 2016;
HiVol conversion factors of 1.00 and 1.10 were applied to GT
OPWS-DTT and OPTotal-DTT data,
respectively) and PCMs with Teflon filters (26 July–21 August 2016). A
summary of the average OP data is given in Table S3. The ANOVA results
(Table S4) indicate negligible difference between types of filter (i.e.,
quartz versus Teflon) on OPDTT measurements.
Figure 8 shows that, as expected, OPTotal-DTT is always
higher than OPWS-DTT. The ratios of
OPWS-DTT to OPTotal-DTT were on average
65±10 % (insoluble accounts for 35±10 %) and 65±14 % at GT, compared to 62±12 % and 58±10 % at RS, for
quartz and Teflon PM samples, respectively. Thus,
OPTotal-DTT of PM2.5 contained on average
35–42 % insoluble species. The correlation coefficients between
OPWI-DTT and OPTotal-DTT were 0.87 and
0.84 for quartz filters at GT and RS, respectively (Table S1), which reflects
the contribution of insoluble species to total OP as well.
Comparison of simultaneous measurements at GT and RS sites based on
daily RS-to-GT concentration ratios. The bottom and top of the box are the
first (Q1) and third quartiles (Q3), and the band inside the box is the
median. The lowest and highest ends of whisker are (Q1–1.5IQR) and
(Q3 + 1.5IQR), where the interquartile range (IQR) = Q3–Q1.
Spatial distributions in OPDTT can also be investigated. As
discussed above, the water-soluble fraction of total OP
(OPWS-DTT-to-OPTotal-DTT ratio) was
fairly similar at the two sites, which means that the insoluble fraction was
not vastly different between the two sites. Figure 9 shows a summary of daily
concentration ratios between the sites. EC, a marker for incomplete
combustion and thus associated with vehicle emissions, was much higher at the
RS site; the ratio of RS to GT was 3.2 on average. OC was only slightly
elevated, as expected, since OC is largely secondary in Atlanta (Xu et
al., 2015) and so more spatially uniform (i.e., primary OC is a small
fraction of total OC, even at RS). Both OPWS-DTT and
OPTotal-DTT were spatially uniform with daily RS-to-GT OP
ratios close to 1. COD was also calculated to further assess the spatial
variability of OP (Table S6). The low COD values (COD < 0.08 for the
quartz filters and < 0.23 for the Teflon filters) between the RS and GT site
indicate spatial homogeneity of OP during the sampling periods. This was
found for both quartz and Teflon filters. The homogenous distributions of OP
are very similar to that of OC (COD = 0.18) and in contrast to EC
(COD = 0.52). Note that both OPWS-DTT and
OPTotal-DTT were slightly higher at the RS site, possibly
indicating a linkage to RS emissions. Uniformity of
OPWS-DTT is consistent with the results shown in the study
of Fang et al. (2015), but similar uniformity in
OPTotal-DTT may seem somewhat unexpected since
water-insoluble aerosol components are often associated with primary species.
These data show the importance of secondary atmospheric processes to
OPWI-DTT. The results are consistent with studies that
have found water-insoluble DTT-active constituents could be secondary
quinones from oxidized polycyclic aromatic hydrocarbons that remain bound to the surface of soot
particles associated with traffic emissions (Antinolo et al., 2015; Li et
al., 2013; Shiraiwa et al., 2012). This means that, although roadway emissions
are a source for components that contribute to OP, some form of processing is
needed to convert the roadway emissions to species with measurable oxidative
potential for both OPTotal-DTT and
OPWS-DTT. Size distributions of
OPWI-DTT (Fang et al., 2017) suggest that
OPWI-DTT is composed of different types of insoluble
species; that OP from oxidized aromatic species (e.g., quinones) may be mainly
associated with smaller-sized insoluble soot particles; and that, at the large end
of the PM2.5 size range, transition metal ions (i.e., water-soluble Cu)
associated with road and brake dust may be the main source.
Summary
An automated analytical system was developed for
quantifying total aerosol oxidative potential with the DTT assay
(OPTotal-DTT) from filter sample extracts. The method is
based on modifying an automated analytical system developed by Fang et
al. (2015) for measuring water-soluble oxidative potential
(OPWS-DTT). Three methods for including the contribution
of water-insoluble components to oxidative potential of PM
(OPWI-DTT) for a measurement of
OPTotal-DTT were tested: (1) extracting filter punches in
deionized water, filtering the extract, and measuring
OPWS-DTT; followed by methanol extraction on the same
filter, filtering the extract, and removing most methanol by evaporation; and then
reconstituting in water and summing with OPWS-DTT to
obtain OPTotal-DTT; (2) extracting filter punches in
methanol, reconstituting the unfiltered methanol extracts with DI after
evaporation of methanol, and performing the DTT assay on the DI-reconstituted
suspension; and (3) extracting filter punches in a vial with DI and then
performing the DTT assay in the vial containing the filter. Method 3
generally yielded higher DTT responses with higher precision (coefficient of
variation of 1∼5 %) and was highly correlated with more aerosol
species, including OC, EC, and various water-soluble and total elements.
Because this method requires no use of organic solvents that must be mostly
eliminated prior to DTT analysis, it is the easiest to automate. The
automated system for measuring OPWS-DTT (Fang et
al., 2015) was modified to follow method 3, and the system performance was
tested.
An ambient study was conducted to contrast measures of
OPTotal-DTT and OPWS-DTT for PM2.5
collected at a roadside (RS) site (highway with restricted heavy-duty diesel
access) and a site more representative of overall average urban Atlanta air
quality (GT). Simultaneous daily filter samples were collected during two
separate 1-month periods, and comparisons were made using quartz and Teflon
filters. At the representative urban site (GT), the ratio of
OPWS-DTT to OPTotal-DTT was 65 %
for both types of filters. At the roadside site (RS) the ratio was only
slightly lower: 62 % for quartz filters and 58 % for Teflon filters.
OPWS-DTT and OPTotal-DTT were
moderately correlated with Pearson product correlation coefficients between
0.56 (roadside) and 0.71 (urban). Simultaneous measures of
OPWS-DTT and OPTotal-DTT at the GT and
RS site showed only slightly higher levels of both at the RS site, indicating
both OPWS-DTT and OPTotal-DTT were
spatially homogeneous. The results are consistent with roadway emissions as
sources of OP but indicate that PM2.5 OP was largely secondary for both soluble
and insoluble aerosol components contributing to OP.