Introduction
Secondary organic aerosol (SOA) forms in the atmosphere from oxidized
volatile organic compounds (VOCs) that are of low enough volatility to be
able to partition into the condensed phase. Aerosol directly affects Earth's
radiative balance and also contributes to cloud formation, both of which have
important climate forcing implications . Aerosol is responsible
for regional haze and has been shown to cause adverse cardiopulmonary health
effects . SOA constitutes a
large fraction of the total aerosol budget, but it is still poorly
constrained in global chemical transport models, which underpredict ambient
aerosol concentrations by 1 to 2 orders of magnitude . These models use laboratory-derived parameters, but
uncertainty in precursors, detailed mechanisms, and mechanistic differences
between chamber simulations and the real atmosphere result in the vast
discrepancies between models and observations .
Nearly 90 % of the non-methane VOCs emitted globally are biogenic in
origin, so it should follow that a large fraction of the uncertainty in model
predictions of the SOA budget comes from uncertainty in how biogenic VOCs
(BVOCs) form aerosol . Different plant
species emit different types and ratios of BVOCs, so the specific
distribution of BVOCs emitted to the atmosphere is dependent on unique
mixtures of vegetation and thus varies a great deal regionally. Monoterpenes
are one such class of BVOC that is both widely emitted and has been shown in
the laboratory to efficiently produce SOA . On average in the United
States, α-pinene is the most dominant monoterpene emission, but
β-pinene, Δ3-carene, and limonene
(Fig. ) are also prevalent and are emitted equally or
more than α-pinene in some regions .
Structures of monoterpenes used in this study.
While most VOCs are biogenic, the majority of atmospheric oxidants are
anthropogenically sourced, and thus human activity is highly influential on
SOA production . At
night, most VOC oxidation in the troposphere occurs by way of either
photolabile nitrate radical (NO3) or longer-lived ozone (O3), which is
photochemically produced but is not rapidly and completely consumed at
sundown as is the hydroxyl radical (OH). The formation of both of these
tropospheric oxidants requires NO2, nearly 90 % of which in the USA
(64 % globally) is estimated to come from anthropogenic sources
. Organonitrates have been observed in ambient
nighttime aerosol during multiple field studies , consistent with NO3 oxidation, and NO3
initiated production of aerosol organonitrates may even compete with
photolysis of NO3 during the day in some regions with high BVOC emissions
. These observations are consistent with several laboratory
studies that have found moderate to high aerosol yields from NO3 oxidation
, but this body of literature is comparatively small
relative to OH and O3 oxidation studies.
Most chamber studies of NO3-derived SOA generate NO3 through the
thermal dissociation of N2O5 in order to minimize the complexity caused
by introducing a second oxidant . Fewer studies have been done using the atmospherically more
relevant conditions of introducing both O3 and NO2 into the chamber to
mimic this full range of nighttime oxidation chemistry
.
and both studied the
effects of a range of NO2 concentrations on dark ozonolysis of
α-pinene, and both observed that increased [NO2] suppresses aerosol
formation. To our knowledge, NO2 effects on dark ozonolysis have not been
systematically assessed for any other monoterpenes. Ozonolysis of
α-pinene has been previously observed to have high (14–67 %)
aerosol yields but
strikingly low (0–16 %) SOA yields with NO3
. The observed
aerosol suppression in the O3 + NO2 system is consistent with the
increased contribution of NO3 at higher [NO2]. However, α-pinene
is the only monoterpene that has been observed to have such drastic SOA yield
discrepancies between the two oxidants , so it may not
be reasonable to assume NO2 has the same effect on other monoterpenes.
Here we focus on the four most prevalently emitted monoterpenes in the US:
α-pinene, β-pinene, Δ3-carene, and limonene.
Table shows rate constants for NO3 formation from
NO2 + O3 as well as each of the nighttime oxidants with the
monoterpenes used in this study. It is evident that the rates of O3 loss
to NO3 production and BVOC oxidation are comparable when [NO2] and
[BVOC] are similar. Even considering its smaller ambient concentrations,
NO3 oxidation is often much faster than O3 oxidation, so it follows
that NO3 oxidation should provide an important contribution to nighttime
aerosol formation in regions that are both biogenically and
anthropogenically influenced. This work seeks to characterize the role of
each competing nighttime oxidant over this broader range of monoterpenes and
the influence of each on SOA formation.
Rate constants at 298 K for NO2 + O3 and
for both O3 and NO3 with selected monoterpenes
.
k× 1017
kO3 × 1017
kNO3 × 1012
(cm3 molec-1 s-1)
(cm3 molec-1 s-1)
(cm3 molec-1 s-1)
NO2 + O3
3.2
–
–
α-Pinene
–
8.4
6.2
β-Pinene
–
1.5
2.51
Δ3-Carene
–
3.7
9.1
Limonene
–
21
12.2
Methods
Unseeded SOA formation experiments were performed in a darkened
∼ 400 L PFA film chamber, shown in Fig. , run in
flow-through mode with precursors added continuously, giving a residence time
of approximately 90 min. The set of experiments described in
Table measured the aerosol production from a single
monoterpene oxidized by O3 with varying concentrations of NO2 added. In
order to make comparisons across both the range of monoterpenes and the range
of [NO2], the monoterpene source and O3 source concentrations were kept
as constant as possible throughout the full study, allowing only the identity
of the BVOC and the concentration of NO2 to vary. While precursor
concentrations used in this study are all quite high and thus absolute
observed aerosol yields are likely not atmospherically relevant due to high-mass loadings and unrealistic radical fates, the ratios of [O3]:[NO2]
ranging from 1:0.5 to 1:4 are representative of ratios observable in the
atmosphere from relatively clean sites (O3 dominated) to heavily polluted
sites (NO2 dominated). Similarly, [NO2]:[BVOC] ranging from
approximately 1:1 to 2:1 is reasonable for relatively clean to relatively
polluted sites, making comparisons between these conditions informative to
aerosol formation in the real atmosphere.
Reed environmental chamber (REC) schematic for the experiments
described here.
O3 (and NO2, when applicable) were introduced into the chamber first
and allowed to reach steady state prior to initiation of SOA formation by
BVOC injection. O3 was generated by flowing zero air (Sabio Model 1001
compressed zero air generator) through a flask containing a Pen-Ray Hg lamp
(primary energy at 254 nm) and was continuously measured from the outlet of
the chamber using a Dasibi Model 1003-AH O3 monitor. NO2 was introduced
from a calibrated cylinder (Air Liquide, 0.3 % by volume in N2) and
monitored using a Thermo Model 17i chemiluminescence NOx/NH3 analyzer.
Chemiluminescence NOx analyzers are sensitive to any species that is
converted to NO in the 350 ∘C Mb converter responsible for
converting NO2 to NO . Some of these additional species include
N2O5, peroxy nitrates (PNs), and alkyl nitrates (ANs). At the high
concentrations used in this study, these NOy contributions were
significant. Kinetics modeling of the oxidant stabilization period (described
in the Supplement), corroborated by a characterization of oxidant
stabilization using chemiluminescence NOx analyzers and a cavity ring-down
spectrometer sensitive only to NO2, indicates that we detected N2O5
with approximately unit efficiency in the NO2 channel of the Thermo NOx
analyzer. The sensitivity of this NOx analyzer to PNs and ANs, which would
have formed following BVOC addition, was not calibrated, but is expected to
be near unity based on previous studies . Modeling only the oxidant stabilization period,
where NO2 and N2O5 were likely the only species detected in the
NO2 channel, provided the initial NO2 concentrations shown in
Table .
Conditions for each chamber experiment.
Experiment no.
Date
[BVOC]i*
[O3]i
[NO2]i*
RH
Temp
Notes
(ppb)
(ppb)
(ppb)
(%)
(K)
α-Pinene
1
12/19/12
780
485
–
33
294
a
2
1/5/13
680
490
–
20
295
f
3
1/16/13
590–715
480
510
24
294
a, c
4
1/18/13
780–960
480
840
22
295
a, d
5
1/14/13
∼ 300
480
1400
22
294
b, e
β-Pinene
6
1/7/13
370
485
–
40
295
a
7
1/23/13
470–680
480
530
23
295
a, c
8
1/25/13
650–1100
480
910
40
295
a, b, d
9
1/21/13
∼ 300
480
2000
20
295
b, e
Δ-Carene
10
1/9/13
220
470
–
30
294
a
11
3/9/13
250–340
470
290
27
295
a, c
12
3/13/13
400–650
470
590
38
295
a, d
13
2/6/13
∼ 300
470
900
33
295
b, e
Limonene
14
1/11/13
470
485
–
20
295
a
15
3/23/13
340–400
470
360
20
295
a, c
16
3/27/13
470–560
470
720
31
295
a, d
17
3/21/13
∼ 300
465
1000
26
295
a, b, e
* Values calculated using kinetics model. a SOA
filter sample collected and analyzed by HPLC-ESI-MS. b [BVOC]
estimated according to flow rate and temperature-dependent vapor pressure
within source flask. c Designated “low NO2.”
d Designated “medium NO2.” e Designated “high
NO2.” f Experiment included to show reproducibility of
chamber.
Once the oxidants stabilized, BVOC was introduced by flowing zero air over a
small, cooled liquid sample of the target BVOC ((1R)-(+)-alpha-Pinene, TCI
America, > 95.0 %; (-)-beta-Pinene, TCI America, > 94 %;
(+)-3-Carene, TCI America, > 90.0 %; (R)-(+)-Limonene, Aldrich,
> 97 %). The chiller temperature was held constant
(±0.3 ∘C) during a single experiment and ranged from -27 to
-21 ∘C for the different monoterpenes, based on the
temperature-dependent vapor pressure that is calculated to give a mixing
ratio of approximately 100 ppm in the source flask (Fig. S3 in the
Supplement) . Since vapor pressure data were unavailable for
Δ3-carene, it was estimated to reach the temperature-dependent
vapor pressure at -25 ∘C – between α-pinene and
β-pinene's target temperatures – due to structural similarities.
Online BVOC measurements were not available, but reacted BVOC was calculated
from the observed decay of the oxidant in the kinetics model for each
experiment. Methodology and uncertainties of this approach are described
further in Sect. and the Supplement.
Two methods were employed to measure the resulting aerosol loading and
composition. Particle size distributions between 20 and 800 nm were measured
at 85 s time resolution with a scanning electrical mobility sizer (SEMS; BMI
Model 2002) consisting of a differential mobility analyzer (BMI Model 2000C)
coupled to a water condensation particle counter (TSI Model 3781).
Size-dependent aerosol loss rates to the chamber walls were characterized and
used to correct size distributions to reflect the total aerosol number and
volume concentrations produced in each experiment
. This
methodology is described in further detail in the Supplement. Aerosol samples
from each experiment were collected onto filters (47 mm quartz fiber). Each
filter was extracted by sonication in 3:1 deionized
water : acetonitrile to minimize solvent reactions with analyte compounds
, and the resulting extract was analyzed offline
by high-performance liquid chromatography–electrospray ionization–mass
spectrometry (HPLC-ESI-MS).
Due to its relatively soft ionization source and thus minimal fragmentation
of analyte compounds, ESI-MS has been employed in several studies to probe
SOA composition . The HPLC-ESI-MS system used here consists of an
Agilent 1100 Series liquid chromatograph coupled to an Agilent LC/MCD TOF
G1969A time-of-flight mass spectrometer with an electrospray ionization
source. The chromatographic separation occurred on a Kinetex 100×3 mm C18 column with 2.6 µm particle size and a sample injection
volume of 50 µL at a flow rate of 0.5 mL min-1. The
electrospray ionization system had a nebulizer gas pressure of 50 psi and an
electrospray voltage of 3000 V. High mass resolution (m Δm-1
varies between 5000 at m/z 118 amu to 15 000 at m/z 1822 amu) and
chromatographic separation of the analytes allowed for straightforward
identification of product molecular formulae .
Between each experiment, the chamber was cleaned for at least 24 h by
flushing with zero air and O3 from the source used during experiments
until particle concentrations were at or below their typical background level
(< 1 µg m-3) and NO2 concentrations were below 5 ppb.
Particle formation was never observed while O3 and NO2 were stabilizing
for a new experiment, indicating that any traces of BVOC from the previous
experiment had been sufficiently removed from the chamber.
Results and discussion
Aerosol formation trends
Raw number and volume concentration time series are presented in
Fig. . These comparisons are not directly indicative of
relative yields due to differences in initial monoterpene concentrations
shown in Table (see Sect. for
further discussion of aerosol mass yields). However, these comparisons nicely
illustrate the vast diversity of the behavior of each monoterpene with
respect to systematically changing oxidant conditions, from O3 dominated
to NO3 dominated. α-Pinene exhibits a decrease in both the total
number of particles produced (Ntot) and total aerosol volume
produced (Vtot) with increasing NO2, consistent with the
findings of other studies .
β-Pinene and Δ3-carene both exhibit a similar decrease in
Ntot with addition of NO2 as α-pinene, but at early times
in the reaction, the addition of NO2 appears to enhance volume growth
relative to the O3-only experiment. Limonene exhibits enhancement in both
Ntot and Vtot with addition of NO2. While all three of
the monoalkene monoterpenes produce fewer particles at higher [NO2],
α-pinene is the only terpene for which the aerosol production seems to
be systematically depleted with the addition of NO2. β-Pinene and
Δ3-carene, in contrast, seem to level off at comparable
Ntot values for the intermediate range of [NO2]. All four
monoterpenes exhibit suppression of aerosol formation at the highest [NO2]
studied, which is likely the result of RO2+NO2 chemistry becoming
kinetically dominant at such high concentrations and producing metastable,
less condensable peroxy nitrate products .
SOA yields
While this study lacks direct BVOC measurements and thus is not optimized to
rigorously measure aerosol yields, the framework of aerosol mass yields can
still be used to compare aerosol formation trends between each experiment
while accounting for differing initial hydrocarbon concentrations as well as
differing aerosol mass loadings for each experiment. Unitless aerosol mass
yields (Y) are defined as the aerosol mass produced per hydrocarbon mass
consumed (Y=ΔM/ΔHC). Since the hydrocarbon was not measured
online during experiments, ΔHC values were determined using the
gas-phase kinetics model described in detail in the Supplement. The modeled
cumulative concentration of monoterpene reacted was converted to ΔHC
in µg m-3 using the molecular weight of monoterpenes
(136.23 g mol-1). In the model, ΔHC is calculated based on how
much of each oxidant reacts with the monoterpene. However, NO3 can also
react with subsequent RO2 radicals, thus depleting the concentration
available to react directly with BVOC. The rate constant used for RO2 +
NO3 (2×10-12 cm3 molec-1 s-1) is reasonably well
known and constant over a range of RO2 structures
(1.8±1.5×10-12 cm3 molec-1 s-1 for C2 - C6
RO2) . The rate constant for RO2 + RO2, the main
competing RO2 sink, is far more variable over RO2 structures, though,
so the “best estimate” employed in this study spans 3 orders of
magnitude (described further in Supplement). Therefore, kRO2+RO2
is the largest source of uncertainty in ΔHC, and aerosol yield ranges
are calculated spanning the minimum
(10-15 cm3 molec-1 s-1) and maximum
(10-12 cm3 molec-1 s-1) values used. Because O3 is
not expected to react with RO2 (whereas NO3 does), ΔHC from the
O3-only experiments does not vary in response to shifting
kRO2+RO2 values.
Raw total number concentrations (Ntot) and total volume
concentrations (Vtot) at each NO2 concentration for each
monoterpene studied, not corrected for wall losses.
ΔM was determined by converting the wall-loss-corrected aerosol total
volume data to mass, assuming a SOA density of 1.4 g mL-1
. Uncertainty in ΔM was estimated using
replicate measurements of α-pinene + O3 (experiments 1 and 2 in
Table ) as described in detail in the Supplement. The two
ΔM time series were interpolated onto the same ΔHC trace, and
time series of the average and standard deviation of ΔM were
calculated. The deviation between these two experiments was slightly variable
with time, so we conservatively chose the highest stable value -15 %
relative error – to use as the ΔM precision estimate. Using the
corresponding ΔM and ΔHC time series and respective
uncertainties, a time series of mass yields was attainable, as shown in
Fig. , plotted against aerosol mass produced (ΔM),
where ΔM and ΔHC are calculated relative to the beginning of
the experiment. In some cases, namely the β-pinene + O3 + NO2
experiments, the aerosol growth rapidly exceeded the size range of the SEMS
(20–800 nm). Aerosol data presented here are truncated as soon as the size
distribution begins to exceed the range of the SEMS instrument resulting in
these experiments “ending” at quite low mass loadings before the yield
curves have flattened.
Percentage of total BVOC reacted by each oxidant at 2 h into each
experiment. In the model, OH is produced from stabilized Criegee
intermediates from ozonolysis at the following ratios: α-pinene =
0.85; β-pinene = 0.35; Δ3-carene = 1.06; limonene =
0.86 . Values from NO2-containing experiments include
two values expressed as low/high where “low” denotes the lower RO2 +
RO2 rate constant limit (10-15 cm3 molec-1 s-1) and
“high” denotes the upper limit (10-12 cm3 molec-1 s-1)
as described in the Supplement.
[NO2]i (ppb)
% by NO3
% by O3
% by OH
α-Pinene
0
0
54
46
510
44(68)
34(21)
22(11)
840
58(78)
26(15)
16(7)
β-Pinene
0
0
74
26
530
77(94)
18(5)
5(1)
910
81 (95)
15 (4)
4 (1)
Δ3-Carene
0
0
49
51
290
62 (92)
21 (5)
17 (3)
590
63 (95)
20 (4)
17 (1)
Limonene
0
0
54
46
360
45 (74)
34 (18)
21 (8)
720
59 (85)
26 (11)
15 (4)
A variety of factors may contribute to the absolute numerical values of these
yields differing from yields reported in the literature. For example, vapor-phase wall losses were not accounted for , and the
chamber size, mixing, and conditioning of walls differ from other studies.
Since these experiments were conducted without seed particles, rather than
having a constant particle distribution for vapors to condense onto, size
distributions emerged as freshly nucleated particles that proceeded through
full growth curves until they exceeded the range of the SEMS and eventually
were removed through the constant outflow of the chamber. This combination of
growth and dilution led to an oscillatory behavior of periodic full growth
curves as the condensational sink was changing, thus preventing a true steady
state from ever being achieved. The yield curves shown in
Fig. highlight a single growth curve for each experiment,
but these yields may be more indicative of kinetically limited growth than
thermodynamic partitioning, causing them to differ from other studies.
Additionally, and perhaps most importantly, the chemistry itself (including
both first-generation oxidation and peroxy radical fate) is expected to
differ substantially in these mixed oxidant conditions compared to single
oxidant studies in the literature. With all of those factors in mind, the
precision reflected in the error ranges in Fig. gives us
confidence that the relative yield comparisons between individual experiments
in this study are robust.
Figure enables yield comparisons at comparable mass loadings
and also accounts for the fact that each experiment began with somewhat
variable BVOC concentrations. We still see similar trends as were observed in
the Vtot panels of Fig. . Figure
illustrates that increasing [NO2] substantially depletes aerosol formation
from α-pinene, whereas β-pinene and Δ3-carene have
comparable yields over the full range of oxidant conditions, and limonene
exhibits enhancement of aerosol formation at higher [NO2]. It should be
noted that yield calculations were only performed on the O3-only and
lowest two [NO2] studied for each monoterpene due to difficulties in
reliably reproducing ΔHC in the kinetics model for the highest
[NO2] experiments. The model is constrained using the observed O3
decay, but these high NO2 experiments react nearly all the BVOC by way of
NO3, leaving the O3 decay nearly unaffected. Furthermore, we expect the
full duration of these experiments to be kinetically dominated by the
RO2+ NO2 reservoir (peroxy nitrates), thus hindering SOA production. For these
reasons, the high NO2 experiments are not included in yield comparisons.
Individual oxidant contributions
Gas-phase kinetics modeling of the steady-state conditions in the chamber
yielded the time series of relative O3 and NO3 (and OH) contributions
to BVOC oxidation. Since each experiment starts with O3, NO2, NO3,
and N2O5 at their equilibrium concentrations, initial BVOC oxidation
will be dominated by NO3, which reacts orders of magnitude faster than
O3 (Table ). Eventually, as concentrations of
precursors change over time, rates to each oxidant change and O3 starts to
contribute. We assume OH is produced from stabilized Criegee intermediates
from ozonolysis according to the monoterpene-dependent yields found in
and described in the Supplement. The timing and
relative contribution of O3 depends on the relative rate constants of
O3 and NO3 with each monoterpene and thus the influence of each
oxidant varies for all conditions tested.
Yield vs. ΔM for each experiment. ΔM is corrected
for wall losses (described in Supplement). Uncertainty ranges on yields arise
from a constant 15 % relative error on ΔM calculated based on two
replicate experiments, propagated with modeled ΔHC values using the
range of 10-15 to 10-12 cm3 molec-1 s-1 for
kRO2+RO2 for the low and medium NO2 experiments for each
monoterpene. O3-only experiments do not have an analogous ΔHC
uncertainty range since all O3 was assumed to react with the monoterpene
directly, so uncertainty range on these traces is based exclusively on
ΔM.
This feature of staggered oxidant contributions is convenient to test the
hypothesis that observed yield differences between different oxidant
conditions applied to a single monoterpene can be attributed to distinct
contributions from NO3 and O3 oxidation. For β-pinene
(Fig. ), Δ3-carene (Fig. S8), and
limonene (Fig. S8), the fact that any aerosol mass is observed during the
beginning of the NO2 experiments when oxidation exclusively goes by way of
NO3 indicates that qualitative yield differences relative to the O3
experiment can be attributed at least in part to NO3 oxidation products.
In contrast, Fig. shows that neither of the
α-pinene experiments with NO2 produce any aerosol mass until O3
starts to contribute. This observation is consistent with the hypothesis that
the observed suppression of aerosol formation from α-pinene with
increasing concentrations of NO2 can be attributed to its (near) 0 %
yield with NO3 observed in other studies .
For β-pinene, Δ3-carene, and limonene, while it is clear that
aerosol mass forms from NO3 oxidation products in the NO2 experiments,
a time lag becomes apparent during which BVOC is reacting but no aerosol is
formed. As soon as aerosol formation is initiated, however, the mass rapidly
increases. The kinetics model used in this study assumes three options for
RO2 fate: reaction with RO2, NO3, or NO2. In
Sect. , we propose that high NO2 experiments yield
low mass concentrations due to the formation of less stable peroxy nitrates.
This explanation likely accounts for the lag time observed in each NO2
experiment before aerosol is able to form. Indeed, from the model we can
calculate a ratio of RO2+ NO2 products relative to the sum of
RO2+ RO2, RO2+ NO3, and RO2+ NO2 products present in the
chamber at each time in the experiment. When this ratio time series is
overlaid onto the plots in Fig. , a minimum in
RO2+ NO2 products appears at approximately the same time that aerosol
formation is initiated. This timing, shown in Fig.
and Fig. S8, indicates that even the low NO2 experiments have enough
NO2 present that formation of relatively volatile peroxy nitrates may
kinetically dominate experiments at early times until RO2+ RO2 and
RO2+ NO3 products start to compete.
The percentage of BVOC reacted by each of the three oxidants was modeled and
is shown in Table . Comparisons were made 2 h into
the reaction after the initial buildup of NO3 and N2O5 was depleted
and chemical production of NO3 more realistically competes with O3
oxidation of BVOCs. Even at this point in time, NO3 dominates the initial
oxidation pathway for all NO2 concentrations and all monoterpenes, further
indicating that if NO3 oxidation contributes to SOA mass, as is certainly
the case for β-pinene, Δ3-carene, and limonene, these NO3
oxidation products are plentiful enough throughout the full experiment to
contribute significantly to observed yield differences between those
experiments relative to the O3-only experiments.
Bulk SOA composition
Filter samples from experiments that yielded sufficient aerosol mass (all
experiments in Table except 1, 5, 9, 13) were collected and
analyzed offline by HPLC-ESI-MS at Colorado State University. Because
electrospray ionization is a soft ionization technique, this method has been
shown to be especially useful for detecting a wide range of m/z products –
including oligomer species that are likely to be significant SOA constituents
. Although quantitative
comparisons of products are not possible due to differences in mass loadings
and a lack of calibration standards, qualitative differences in product
distributions were readily apparent and consistent with observed aerosol
yield trends.
Introducing NO2 into ozonolysis of monoterpenes influences the composition
of resulting SOA in two different ways: first, by forming NO3 that can
either oxidize BVOC directly or react with NO3- or O3-initiated RO2,
or second, by directly reacting with RO2 or other products and reaction
intermediates as NO2. A visual comparison of the total ion chromatograms
from ozonolysis of β-pinene with no NO2 and the two lowest
concentrations of NO2 (Fig. ) shows that several
new products form once NO2 is added, and that in general increasing
[NO2] simply increases the intensity of those products rather than
changing product identities substantially. For ease of interpretation,
results from all of the NO2-containing experiments were combined into a
single product distribution from “NO3-influenced oxidation.” We can then
compare those product distributions to those of the O3-only experiments. A
complete list of compound formulae detected (> 1.5 % relative intensity,
see Supplement) in the O3 and NO3 dominated oxidation of each
monoterpene is compiled in Table S2.
Time series of wall-loss-corrected aerosol mass (right axis) and VOC
consumed by
each oxidant (left axis) for α-pinene and β-pinene at 0 (“O3-only”),
low, and medium NO2 concentrations, highlighting how much aerosol is produced at times
dominated by NO3 oxidation (shaded regions). ΔHC values shown are the
lower limits calculated using the lowest RO2+ RO2
rate constant (10-15 cm3 molec-1 s-1), which gives the low limit on how much NO3 reacts with VOC directly.
Dashed grey traces (inner left grey axis) represent the ratio of RO2+ NO2 products
that are present in the chamber (instantaneous concentration) relative to the sum of the instantaneous concentrations
of RO2+ RO2, RO2+ NO3, and RO2+ NO2 products. This ratio is a representation of the time dependence of peroxy nitrate formation in the chamber.
To best highlight qualitative differences in the identity of molecules that
make SOA for each set of precursors, every unique compound (distinct either
in mass, retention time, or both) was accounted for once, not normalized by
peak intensity. A variety of average bulk composition parameters were
calculated for each experiment, highlighted in Table ,
including average number of C, O, and N atoms per compound, molecular weight,
and total number of products. Some artifacts may remain in this data set, such
as impurities not captured by the background subtraction or product fragments
that do not reflect the original identity of the SOA product. The former
should affect all samples uniformly in this analysis and thus will not
influence qualitative comparisons, and the latter will either affect multiple
samples and thus be irrelevant in comparisons or only affect single samples
and thus still provide interesting qualitative differences.
A direct correlation between any of the average parameters (MWavg,
Cavg, Oavg, Navg) in
Table and absolute aerosol yields is not obvious.
α-Pinene ozonolysis, for example, produced the highest aerosol mass of
all the conditions tested, and while its average MW and number of C atoms are
higher than ozonolysis from all the other monoterpenes, those same values are
comparable to each of the NO3 experiments and substantially lower than
those values for limonene + NO3. However, the difference in average
values, defined as the difference in each average parameter between O3 and
NO3 dominated oxidation for each monoterpene (Δavg), are
consistent with O3 vs. NO3 yield comparisons. β-Pinene and
Δ3-carene have similar Δavg values for each
parameter (as well as similar absolute values for each oxidant condition),
suggesting that the addition of NO3 affects the product distribution of
these two monoterpenes similarly. The Δavg values for limonene
are much higher than any other monoterpene in this study, consistent with it
having the highest NO3 aerosol yields. Again, perhaps most notably, the
Δavg parameters hover near 0 for α-pinene,
suggesting that the aerosol composition does not differ much between the two
oxidants – consistent with all of α-pinene's aerosol production
coming exclusively from O3 oxidation.
Comparison of chromatograms from HPLC-ESI-MS samples of SOA derived
from β-pinene
ozonolysis with 0 (bottom), 530 (middle), and 910 ppb NO2 (top). Chromatograms
are annotated with speculative structures corresponding to the assigned molecular formulae
of the most intense peaks. Proposed structures are listed in Table S3 based on products observed in other studies.
Histograms of each O3 vs. NO3 (O3 + NO2)
regime for each monoterpene showing the number of compounds (left axis) in each 50 amu mass bin (bottom axis).
To illustrate some of the finer detail of these product distributions,
Fig. shows histograms where each observed product is
binned by compound mass in 50 amu intervals. Every experiment shows some
contribution from oligomer products (m/z > 246 according to
; > 300 according to ), but
this contribution is most pronounced from NO3 oxidation of β-pinene,
Δ3-carene, and limonene. In particular, we observe substantially
more distinct products > 400 amu from β-pinene,
Δ3-carene, and limonene with the O3 / NO2 / NO3
mixture than from O3 alone. In this region, the mass distributions for
α-pinene in both oxidant conditions are identical. Since mass is an
important contributing factor to volatility (e.g.,
), these high-mass products are likely important in
aerosol formation and growth and thus may be explanatory of the observed
yield differences from NO3 oxidation. If oligomerization is an important
pathway leading to SOA formation and growth from NO3-initiated chemistry,
α-pinene's lack of oligomer products with NO3 may be responsible
for its 0 % aerosol yield. In contrast, comparison of the four O3-only
histograms shows relatively small contributions of high MW oligomers for any
monoterpene, in spite of quite high aerosol yields in some cases, indicating
that aerosol formation by ozonolysis may not require oligomerization.
Recent studies of SOA nucleation and growth from ozonolysis of
α-pinene have shown that highly oxidized and/or oligomeric species are
likely important in nucleation and early growth, but that growth beginning
around 20 nm is dominated by lower MW products (140–380 amu)
. This latter MW range is consistent
with the ozonolysis products we observe for all four monoterpenes, indicating
that high MW products may dominate only early stages of growth and are thus
not detectable at the high-mass loadings in this study. NO3 oxidation,
however, seems to provide a weaker source of low volatility compounds
contributing to nucleation and early growth, as seen in the decrease of
Ntot with increasing [NO2] in Fig. (with the
exception of limonene), but produces oligomers throughout the full time
period of aerosol growth, leading to total aerosol mass concentrations that
rival ozonolysis (with the exception of α-pinene), as seen in
Fig. . Further supporting this observed difference in
products from ozonolysis compared to NO3 oxidation is the difference in
the reaction rate of each process. O3 + BVOC is much slower than NO3
+ BVOC, which means that RO2 is produced more slowly from ozonolysis and
thus the RO2 lifetime is much longer with respect to other radical
species. Longer RO2 lifetimes are more conducive to isomerization
processes like autoxidation , which
may be responsible for the initial high MW nucleating species observed in
other ozonolysis studies. In contrast, NO3 oxidation produces RO2 much
more rapidly, therefore increasing the likelihood of RO2 + RO2
oligomerization.
Average (± 1 standard deviation) molecular weight, number of C,
O, and N atoms, O / C, and total number of products identified by
HPLC-ESI-MS analysis of aerosol collected from O3 and NO3 (O3 +
NO2 + NO3) oxidation of each monoterpene studied. The difference in
average value for each parameter (Δavg) from each oxidation
scheme was also tabulated for each monoterpene.
α-Pinene
β-Pinene
O3
NO3
Δavg
O3
NO3
Δavg
MWavg
237.6 ± 86.9
233.9 ± 81.0
-3.7
212.0 ± 88.9
249.3 ± 104.3
37.3
Cavg
13.8 ± 5.4
13.2 ± 5.0
-0.6
12.0 ± 4.5
12.7 ± 4.7
0.7
Oavg
2.9 ± 1.6
3.1 ± 1.7
0.2
2.9 ± 2.1
4.2 ± 2.6
1.3
Navg
0.29 ± 0.53
0.40 ± 0.58
0.11
0.14 ± 0.36
0.74 ± 0.73
0.60
O / C
0.22 ± 0.11
0.25 ± 0.14
0.03
0.23 ± 0.12
0.32 ± 0.16
0.09
# ID'd
28
43
15
29
66
37
Δ-Carene
Limonene
MWavg
191.7 ± 56.9
232.1 ± 111.5
40.4
216.9 ± 81.2
306.5 ± 128.6
89.6
Cavg
11.0 ± 3.1
12.4 ± 4.7
1.4
12.3 ± 4.2
14.7 ± 4.8
2.4
Oavg
2.4 ± 1.2
3.6 ± 3.0
1.2
2.9 ± 1.8
5.9 ± 4.0
3.0
Navg
0.09 ± 0.30
0.41 ± 0.67
0.32
0.18 ± 0.46
0.94 ± 1.06
0.76
O / C
0.22 ± 0.11
0.27 ± 0.14
0.05
0.23 ± 0.13
0.39 ± 0.23
0.16
# ID'd
32
70
38
34
85
51
Mass spectra alone provide limited compositional information since they do
not distinguish between different functional groups. However, in this system,
one functional group that can be easily parsed out of the data is the nitrate
group. From the NO3 initiated oxidation chemistry, we expect that any
nitrogen present in a molecule is a part of a nitrate functional group. (Some
instances of -NO and -ONO have been found in the compound list, causing
relatively high Navg values for α-pinene + O3, for
example, where we expect any nitrogen is due to impurities.) The
Δavg values in Table for Navg
provide an approximate estimate of relative aerosol organic nitrate yield.
β-Pinene, Δ3-carene, and limonene all exhibit a substantial
increase in average number of N per molecule with the addition of NO2,
consistent with the relatively high organic nitrate yields observed from
NO3 oxidation of those species in other studies . α-Pinene produces comparatively fewer
nitrogen-containing SOA products in the presence of NO2. While the organic
nitrate products from α-pinene may be relatively volatile and thus not
partition appreciably into the aerosol phase, it is clear that this is not a
universal characteristic of C10 organic nitrates, as many do partition
into the aerosol phase for all three other monoterpenes studied – even those
with relatively low total aerosol mass loading.
Minimum [NO2] / [BVOC] value reported for each monoterpene
studied at which NO3 is expected to dominate nighttime oxidation.
BVOC
[NO2] / [BVOC]
α-Pinene
2.6
β-Pinene
0.47
Δ3-Carene
1.2
Limonene
6.6
Diurnal average NO2 and monoterpene concentrations (top panels)
are shown for two field
campaigns: BEACHON-RoMBAS 2011 (left panels) and SOAS 2013 (right panels) which both occurred at heavily
biogenically influenced sites. The bottom panels show the diurnally averaged [NO2] / [BVOC] ratios
for the speciated monoterpenes used in this study. The speciated monoterpenes for BEACHON-RoMBAS are
estimated as being 1:1:1 α-pinene : β-pinene : Δ3-carene; hence, each BVOC concentration
is assumed to be a third of total measured [BVOC]. Shaded regions indicate nighttime hours.
We note that the products observed here from ozonolysis vs. NO3 oxidation
are consistent with proposed mechanisms in the literature. Table S3 includes
proposed structures for several masses that have been observed in other
studies, including several monomeric carboxylic acids and aldehydes from
ozonolysis as well as
multi-functional monomeric nitrates from NO3 oxidation
, some of which have been
included in Fig. to highlight relative intensities
across different NO2 conditions. Several more speculative structures are
shown in the Supplement to indicate that observed oligomeric masses can be
reasonably achieved from dimers of first-generation oxidation products.
Implications: determination of dominant nighttime oxidant using NO2 to BVOC ratio
Using literature rate constant data (Table ), we can
approximate the NO2/ BVOC regime where NO3 will dominate nighttime
oxidation for each monoterpene. Since O3 contributes to both NO3
formation and BVOC oxidation, and for all monoterpenes NO3 oxidation is
much faster than O3 oxidation, we assume that once NO3 production
becomes faster than O3 oxidation of BVOC (Eq. ), NO3
becomes the dominant oxidant. The ratio of NO2 / BVOC at which this
crossover occurs, defined in Eq. (), is calculated for each
monoterpene and reported in Table .
k(O3+NO2)[O3][NO2]>k(O3+BVOC)[O3][BVOC],[NO2][BVOC]>k(O3+BVOC)k(O3+NO2).
This calculation leaves out factors like competing sinks for NO3 and is
thus a very crude approximation. Nevertheless, it is noteworthy how small the
magnitude of these ratios are. Figure shows diurnally
averaged NO2 and bulk monoterpene concentrations from two field campaigns:
BEACHON-RoMBAS in 2011, which took place in a remote montane forested
location in the Rocky Mountain front range , and SOAS
in 2013, which took place in a rural subtropical forest region in central
Alabama . Across both of these campaigns, NO2 and total
monoterpene diurnal concentrations were qualitatively and quantitatively
similar. For the BEACHON-RoMBAS campaign, we assume that the average
monoterpene distribution was 1:1:1
α-pinene : β-pinene : Δ3-carene
, whereas at SOAS we have explicit speciated
monoterpene measurements. For each campaign, we calculated the average
diurnal cycle of [NO2] / [BVOC] using speciated monoterpene
concentrations. The dashed lines indicate the minimum calculated threshold
from Table , above which NO3 oxidation is expected to
dominate over O3 oxidation. The shaded nighttime portions of
Fig. show measured average [NO2] / [BVOC] ratios
exceeding the minimum threshold at all times during the BEACHON-RoMBAS
campaign and at all times for β-pinene and limonene at SOAS as well as
part of the night for α-pinene at SOAS.
These ratios are expected to be even higher in regions with stronger
anthropogenic influences. This analysis suggests that NO3 is not only a
relevant contributor to nighttime oxidation chemistry, it may actually
dominate oxidation pathways in many regions. The consequence of this
NO3-dominant oxidation chemistry for SOA formation downwind of large
NOx point sources (coal-fired power plants) has been recently investigated
, showing spatial patterns of predicted SOA production that
depend substantially on the forest surrounding the point source. The present
study expands on this thinking to include further downwind regions where
O3 and NO3 begin to compete. If NO3 contributes significantly to
oxidation pathways in ambient air over a wide range of NO2 concentrations,
the fact that each monoterpene displays vastly different aerosol yields from
NO3 vs. O3 oxidation and that this difference differs among
monoterpenes becomes essential to accurately predicting aerosol formation in
different regions.
Conclusions
This work adds to the growing body of monoterpene aerosol yield comparison
literature suggesting that monoterpene oxidation has widely varying aerosol
yields depending on the specific monoterpene and oxidant combination
. We therefore conclude, first and foremost, that there is no
single “representative” monoterpene. Furthermore, the monoterpene most
often considered representative of BVOC oxidation, α-pinene, presents
here as the greatest anomaly with respect to aerosol formation, showing
higher ozonolysis aerosol mass yields than even limonene, and behaving in a
way consistent with 0 % aerosol yields from reaction with NO3.
We show that under the influence of NO3, α-pinene produces
comparatively few condensed-phase organic nitrates and oligomers with respect
to the other three monoterpenes studied. This finding is consistent with
α-pinene's negligible aerosol yield with NO3 and also suggests more
generally that oligomers and multifunctional organic nitrates are important
products leading to SOA formation from NO3. Additionally, the difference
in product distributions between O3 and NO3 oxidation for all
monoterpenes studied (except α-pinene) indicates that each oxidant
broadly employs a different mechanism toward condensable products – O3
likely nucleates and grows enough aerosol mass early in the reaction that
subsequent condensation is governed by comparatively small molecular weight
species, whereas NO3 produces less extremely low-volatility material early
but produces oligomers consistently throughout the period of condensation
such that they constitute an observable fraction of the bulk aerosol.
Careful treatment of the first-generation kinetics of this atmospherically
relevant nighttime oxidant mixture also served to contextualize the relative
importance of each observed aerosol precursor in different regions. We
propose using NO2/ BVOC ratios for each monoterpene to predict the
dominant nighttime oxidation pathway for each (Table ). For
example, for β-pinene at NO2/ BVOC ratios greater than 0.47,
NO3 oxidation will begin to out-compete O3 oxidation, suggesting that
β-pinene oxidation by O3 is likely to be minor at night in all but
the most pristine environments. β-Pinene displays a rather extreme
manifestation of this observation, but all four monoterpenes studied have
NO2 / BVOC ratios such that NO3 oxidation is likely to dominate
even in relatively remote regions.
The complexity shown by just these four BVOCs reacting with two different
oxidants suggests that bulk parameters in global and regional models need to
be very carefully considered if they are going to accurately match observed
ambient organic aerosol loadings. These models use one or two, typically
daytime, aerosol yield parameters for bulk monoterpenes – often considering
α-pinene or β-pinene yields to be representative (e.g.,
). To the knowledge of the authors, the
modeling approaches of and
are the only global-scale models that parameterize NO3 chemistry. Future
challenges in constraining the global aerosol budget will likely require
creating more nuanced approaches to modeling different regions with
ostensibly similar chemistry that has been shown to have diverse effects on
aerosol formation.