Rapid deposition of oxidized biogenic compounds to
a temperate forest
Tran B. Nguyen
a,1,2
, John D. Crounse
a,1
, Alex P. Teng
a
, Jason M. St. Clair
a
, Fabien Paulot
b,c
, Glenn M. Wolfe
d,e
,
and Paul O. Wennberg
a,f,2
Divisions of
a
Geological and Planetary Sciences and
f
Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125;
b
Geophysical
Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration, Princeton, NJ 08540;
c
Atmospheric and Oceanic Sciences, Princeton University,
Princeton, NJ 08544;
d
Atmospheric Chemistry and Dynamics Lab, NASA Goddard Space Flight Center, Greenbelt, MD 20771; and
e
Joint Center for Earth
Systems Technology, University of Maryland Baltimore County, Baltimore, MD 21250
Edited by Mark H. Thiemens, University of California, San Diego, La Jolla, CA, and approved December 22, 2014 (received for review September 28, 2014)
We report fluxes and dry deposition velocities for 16 atmospheric
compounds above a southeastern United States forest, including:
hydrogen peroxide (H
2
O
2
), nitric acid (HNO
3
), hydrogen cyanide
(HCN), hydroxymethyl hydroperoxide, peroxyacetic acid, organic
hydroxy nitrates, and other multifunctional species derived from
the oxidation of isoprene and monoterpenes. The data suggest
that dry deposition is the dominant daytime sink for small, satu-
rated oxygenates. Greater than 6 wt %C emitted as isoprene by
the forest was returned by dry deposition of its oxidized products.
Peroxides account for a large fraction of the oxidant flux, possibly
eclipsing ozone in more pristine regions. The measured organic
nitrates comprise a sizable portion (15%) of the oxidized nitrogen
input into the canopy, with HNO
3
making up the balance. We ob-
serve that water-soluble compounds (e.g., strong acids and hydro-
peroxides) deposit with low surface resistance whereas compounds
with moderate solubility (e.g., organic nitrates and hydroxycarbon-
yls) or poor solubility (e.g., HCN) exhibited reduced uptake at the
surface of plants. To first order, the relative deposition velocities of
water-soluble compounds are constrained by their molecular diffu-
sivity. From resistance modeling, we infer a substantial emission flux
of formic acid at the canopy level (
∼
1nmolm
−
2
·
s
−
1
). GEOS
−
Chem,
a widely used atmospheric chemical t
ransport model, currently under-
estimates dry deposition for most molecules studied in this work.
Reconciling GEOS
−
Chem deposition velocities with observations
resulted in up to a 45% decrease in the simulated surface con-
centration of trace gases.
biosphere
−
atmosphere exchange
|
isoprene
|
dry deposition
|
OVOCs
|
fluxes
F
orests are major sources of volatile organic compounds (VOCs),
contributing approximately half of the reactive carbon emissions
worldwide (1). Emissions of a single compound, isoprene (C
5
H
8
),
contribute approximately a third of the global VOC flux (2). The
emitted carbon is transformed in the atmosphere by photolysis
and oxidation reactions with the hydroxyl radical (OH), ozone
(O
3
), or the nitrate radical (NO
3
), generating highly oxidized and
often multifunctional compounds that are termed oxidized volatile
organic compounds (OVOCs). Atmospheric OVOCs can be lost
through further photooxidation (ultimately leading to CO
2
or
small organic acids), condensation onto aerosol particles (forming
secondary organic aerosols), or deposition to surfaces.
Due to its high emission and fast reactivity, the atmospheric
oxidation of isoprene significantly impacts air quality and climate
by altering the regional and global budgets of organic aerosols (2)
and oxidants [e.g., ozone (3) and HO
x
=
OH
+
HO
2
(4)]. Fig. 1
illustrates the typical atmospheric reaction pathways for isoprene
and the related monoterpenes, occurring both in the day and night.
Representations of VOC oxidatio
n and organic aerosol production
in air quality and climate models ha
ve significantly improved in the
last decade (3, 5) as a result of renewed focus on the isoprene
chemical mechanism. This has followed from improved analytical
methods that have enabled ambient and laboratory studies of the
chemistry and oxidative fate of OVOCs such as isoprene hydroxy
nitrates (ISOPN) and isoprene epoxydiols (IEPOX). However,
little progress on understanding the dry deposition of OVOCs
has been made, despite the suggested importance of this loss
pathway (6, 7).
Direct and speciated measurements of trace gas exchange have
been performed for inorganic compounds (e.g., O
3
,SO
2
,NO
x
,
N
2
O, NH
3
,HNO
3
,H
2
O
2
), biogenic VOCs, and simple oxygenates
[e.g., peroxyacetylnitrate (PAN), methanol, formic acid, acetone]
(8, 9). Recent flux observations above a California orange grove
provide evidence for large depositional fluxes of OVOCs (10),
although the speciated fluxes were not measured. Indeed, the
surface exchange behavior for the multifunctional OVOCs that
comprise the majority of isoprene and monoterpene oxidation
products remains poorly constrained because few ambient mea-
surements have been performed with sufficient temporal resolu-
tion or chemical specificity. It has been postulated that dry
deposition may be a significant sink for many key OVOCs within
the boundary layer and thus may be a controlling factor for their
atmospheric lifetimes and mixing ratios at Earth
’
s surface. Fur-
thermore, atmospheric model evaluations suggest that disregard-
ing dry deposition of OVOCs may lead to a large overestimate in
the formation rate of secondary organic aerosol (up to 50%) (11,
12), a larger error than that due to ignoring wet deposition (13).
Due to the scarcity of ambient chemically specific dry de-
position data, model representation of atmosphere
−
biosphere
Significance
Dry deposition is an important removal mechanism for oxidized
atmospheric compounds. This process remains, however, poorly
understood due to the scarcity of direct flux observations for all
but small, inorganic molecules in the atmosphere. The chemically
speciated fluxes presented here comprise a unique and novel
dataset that quantifies the dry deposition velocities for a variety
of trace gases in a typical forested ecosystem. The data illustrate
the key role of molecular diffusion in the atmosphere
−
biosphere
exchange of water-soluble species. Furthermore, this work en-
abled evaluation of the dry deposition parameterization in a
global chemical transport model. The results aid in resolving key
discrepancies within the global m
odel, resulting in more-accurate
predictions of trace gas lifetimes
and surface concentrations.
Author contributions: P.O.W. designed research; T.B.N., J.D.C., A.P.T., J.M.S.C., F.P., and
G.M.W. performed research; J.D.C. contributed new reagents/analytic tools; T.B.N. ana-
lyzed data; and T.B.N. and P.O.W. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Freely available online through the PNAS open access option.
1
T.B.N. and J.D.C. contributed equally to this work.
2
To whom correspondence may be addressed. Email: wennberg@caltech.edu or tbn@
caltech.edu.
This article contains supporting information online at
www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1418702112/-/DCSupplemental
.
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PNAS
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Published online January 20, 2015
www.pnas.org/cgi/doi/10.1073/pnas.1418702112
exchange behavior of OVOCs rely on parameterizations that
have been optimized for O
3
and SO
2
(14). The higher water sol-
ubility of oxygenates compared with hydrocarbons increases their
propensity to deposit to the surface by interacting with surface
water layers; thus, it is unclear if the parameterization developed
for less soluble species is sufficient to describe the flux behavior of
water-soluble compounds. Direct measurements of dry deposition
for key VOC oxidation products are clearly needed to complete
the understanding of their atmospheric fates.
As the biosphere exchange of chemical species within the
boundary layer is driven by turbulence, surface fluxes can be es-
timated with micrometeorological methods such as eddy co-
variance (EC). Calculations using the EC method require mixing
ratio measurements performed fast enough to capture the high-
frequency timescale of turbulent eddies; e.g., measurements should
exceed 1 Hz sampling frequency at this site (
SI Appendix
,Fig.S7
).
The recent development of fast mass spectrometry-based detectors
facilitates EC flux measurements for a wide variety of species, in-
cluding complex OVOCs (15). The EC flux of the desired species
x
(
F
x
) above a surface, such as a forest canopy, can be expressed as
the correlation of the mixing ratio of
x
with the vertical wind
component (
w
),
F
x
=
w
′
x
′
[1]
where primes denote deviation from the mean value, and overbars
denote an average over a typical flux period (
∼
30 min). Important
underlying assumptions in Eq.
1
are that (
i
) the measurement is
stationary (i.e., no significant variations in the turbulent statistics
in time or in the point of measurement relative to meteorological
events), (
ii
) the surface is homogeneous so that the horizontal
wind components are unimportant, and (
iii
) the scale of chemical
change is slow in relation to flux variation (16). In this work, we
focus on the downward exchange of trace gases, where the de-
position velocity (
V
d
,cm
·
s
−
1
) is defined in relation to the flux and
the mean mixing ratio of
x
,
V
d
=
−
F
x
x
:
[2]
This velocity determines the deposition lifetime of compound
x
in the tropospheric boundary layer (
τ
dep
≈
h
/
V
d
, where
h
is the
boundary layer height in centimeters). We report EC flux obser-
vations for 16 biogenic trace gases and energy balance closure
above a southeast US temperate mixed forest in the summer. The
organic and inorganic species studied here were chemically re-
solved with time-of-flight chemical ionization mass spectrometry
using CF
3
O
−
reagent anions (CIMS), a soft-ionization method
specific for the detection of hyd
roperoxides, acids, multifunc-
tional nitrates, and multifun
ctional oxygen
ated compounds
(17). The mixing ratios of compounds, meteorology, and three-
dimensional wind (
u, v,
and
w
) were measured atop a 20-m walk-
up tower in the Talladega National Forest in June 2013 as part of
the Southern Oxidant and Aerosol Study (SOAS) campaign
(
SI Appendix
,section1
).
Results and Discussion
Fluxes are calculated from the fast measurements of chemical
mixing ratios (10 Hz), virtual temperature (8 Hz), and vertical
winds (8 Hz). Details of the site, measurement methods, cali-
bration (
SI Appendix
, Table S1
), and quality assessment/quality
control of flux data can be found in
Materials and Methods
and
SI
Appendix
. The site location and tower sampling platform pre-
sented challenges to the flux measurements due to inconsistencies
in fetch to the south and perturbations of wind trajectory in this
direction due to shadowing by the instrument. Accurate flux
measurements were possible on several days, however, when the
wind direction was ideal to sample air from the forest to the
north. The measurement of solar radiation, externally calibrated
and converted to net radiation (18), was used as one verification
of flux quality (16). The closure condition requires that the ob-
served net radiation downward (
R
n
), less the storage heat flux (
S
)
(19), is equivalent to the observed sensible heat flux upward (
SH
,
heat that can be measured) plus latent heat flux upward (LE,
heat that is used to evaporate water). The quality constraints (
SI
Appendix
, section 4
) were met for only a subset of measurements
(
∼
16%). We restrict our analysis to these periods.
Our observations demonstrate that dry deposition is a signifi-
cant atmospheric sink for many OVOCs formed in the dark
chemical and photochemical reactions of isoprene and mono-
terpenes. Gas-phase inorganic compounds are also observed to
deposit, often quite rapidly. Fig. 2 and
SI Appendix
, Fig. S17
,
show downward exchanges of relevant OVOCs and inorganic
species and upward exchanges of heat and water for the days in
Fig. 1.
Formation pathways for the oxidation products of isoprene and
monoterpenes included in this study. Thick arrows indicate primary emission.
Representative isomers and reaction pathways are shown. Flux data are
reported for compounds shown in solid boxes. In HO
2
-rich environments, the
OH-initiated reaction of isoprene generates ISOPOOH, which are sub-
sequently oxidized to epoxydiols (IEPOX) in an OH-conserving mechanism
with almost quantitative yields (88). The photooxidation of IEPOX produces
C
4
dihydroxy carbonyls (DHC
4
), C
4
hydroxy dicarbonyls (HDC
4
), HAC, formic
acid, and other products (42, 89). In NO-rich environments, the minor route
of the OH-initiated reaction of isoprene produces ISOPN, which are sub-
sequently oxidized to HAC, hydroxy nitrates with backbones of MACN
and MVKN, and other products (54, 90, 91). The major route of the NO-
dominated OH-initiated reaction (not shown) produces carbonyls such
as methacrolein, methyl vinyl ketone, and HAC, among other products.
PROPNN is formed primarily from the oxidation-induced fragmentation of
larger nitrates. A temperature-dependent isomerization of the isoprene RO
2
generates the HPALD (56, 92). The O
3
-initated oxidation of isoprene or other
exocyclic compounds forms the C
1
stabilized Criegee intermediate (SCI),
among other products, which reacts with water to produce HMHP and for-
mic acid (43). NO
3
-initated oxidation of isoprene and monoterpenes, fol-
lowed by the HO
2
reaction, produces INP and MTNP, respectively (93). PAA is
thought to predominantly form through the HO
2
reaction with acetylperoxy
radical [CH
3
C(O)OO], which has several anthropogenic and biogenic sources
(94). The main source of HCN is biomass burning (52). Formic acid has many
sources, including direct emission from canopies, photooxidation at surfaces
and in the gas phase, ozonolysis, and secondary chemistry (6).
Nguyen et al.
PNAS
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Published online January 20, 2015
|
E393
EARTH, ATMOSPHERIC,
AND PLANETARY SCIENCES
PNAS PLUS
this study. LE comprised the majority of the total upward energy
flux at this site, which is typical for forested environments. Fluxes
of hydrogen peroxide (H
2
O
2
) are among the largest observed
during the campaign, reaching 2 nmol
·
m
−
2
·
s
−
1
, in good agreement
with other accounts in forested settings (20). Observed fluxes had
a daytime diurnal pattern, driven by the combined effect of light
and temperature on turbulence, stomatal conductance, and gas-
phase photochemical production.
The biosphere
−
atmosphere exchange behaviors for several
species studied here are currently unknown or have only been
speculated in the past. These chemical compounds include hy-
drogen cyanide (HCN), hydroxymethyl hydroperoxide (HMHP),
peroxyacetic acid (PAA), the sum of isoprene hydroxy hydro-
peroxides and epoxydiols (ISOPOOH
+
IEPOX), isoprene
hydroperoxy aldehydes (HPALD), ISOPN, the sum of hydroxy
nitrates with carbon backbones of methacrolein and methyl-
vinylketone (MACN
+
MVKN), propanone nitrate or propanal
nitrate (PROPNN), hydroxyacetone (HAC), the C
4
hydroxy
dicarbonyl from IEPOX oxidation (HDC
4
), the C
4
dihydroxy
carbonyl from IEPOX oxidation (DHC
4
), isoprene nitrooxy
hydroperoxide (INP), and monoterpene nitrooxy hydroperoxide
(MTNP). The structures of the compounds measured in this work
are shown in Fig. 1.
Fig. 3 shows the observed mean deposition velocities (
V
d
) for
each compound binned into hourly periods. Daytime
V
d
values
(Fig. 3 legend) were averaged for local hours 1000
–
1500 across
all measurement days. In most cases, the deposition velocities are
more rapid than that of O
3
(21). Diurnal patterns of deposition
velocities largely mirrored tho
se for flux. However, the diurnal
patterns for some compounds are asymmetric (peaking before
noon), which may indicate that their biosphere exchange is con-
trolled in part by stomatal con
ductance and/or surface water
availability. Although daytime
V
d
may depend to some extent
on environmental conditions and canopy characteristics at each
site, it is instructive to compare the values measured here with
available data on dry deposition over forests. For example, in this
work, the observed
V
d
for H
2
O
2
(5.2
±
1.1 cm
·
s
−
1
) is in excellent
agreement with other direct measurement accounts (
V
d
;
H
2
O
2
=
5
±
2cm
·
s
−
1
(22
–
24). Measured fluxes of formic acid have been
reported to be bidirectional, with an effective range of
V
d
;
Formic
=
0.17
–
1.0 cm
·
s
−
1
(25, 26) that is in reasonable agreement with our
determination (1.0
±
0.4 cm
·
s
−
1
). Measurements of nitric acid
(HNO
3
) dry deposition encompass the largest range in the
literature [
V
d
;
HNO
3
=
−
1
–
8cm
·
s
−
1
(27
–
30)]. HNO
3
is a chal-
lenging compound to measure because of its interactions with
instrument surfaces. The CIMS measurement of HNO
3
was
affected by an instrumental delay and was corrected with
a time response perturbation function (
SI Appendix
,section
5
). Our determination for nitri
c acid deposition velocity
(
V
d
;
HNO
3
=
3.8
±
1.3 cm
·
s
−
1
) is within range of other reports
and is consistent with results from resistance modeling per-
formed in this work. Other speciated
V
d
we observe compare
well, although indirectly, to previously reported data available
as averaged measurements within the class of organic hydro-
peroxides [
V
d
;
ROOH
=
1.1
–
2.5 cm
·
s
−
1
(22, 23)] or organic nitrates
[
V
d
;
RONO
2
(gas
+
particles)
≈
2.0 cm
·
s
−
1
(29, 30)].
Resistance Model of Deposition.
Here we seek to evaluate the
physical factors that control dry deposition within the framework
of resistance modeling. Deposition velocity is usually parame-
terized as a series of resistances in the transport from the at-
mosphere to a surface
—
in this case, a canopy that is represented
as a theoretical large leaf (31). The downward trajectory of a
chemical species can be hindered by the step-wise resistances to
aerodynamic transfer (
R
a
), molecular diffusion through the quasi-
laminar boundary layer of the leaf (
R
b
), and uptake at the surface
of the leaf (
R
c
),
V
d
=
1
R
a
+
R
b
+
R
c
[3]
SI Appendix
, section 6
, describes the resistance model in detail.
We used
R
a
and
R
b
parameterization as suggested (32
–
34).
R
a
is
dependent only on the atmospheric stability (i.e., turbulence).
R
b
is inversely dependent on the turbulence, the molecular diffusiv-
ity of compound
x
in air [
D
x
(m
2
·
s
−
1
)], and canopy characteristics
such as the observed leaf area index (LAI) of the canopy at the
measurement site (LAI
=
4.7; see
SI Appendix
).
R
c
is parameter-
ized according to a revised Weseley scheme (35), which, to first
order, considers the combined resistances from stomata (
r
s
),
mesophyll (
r
m
), and cuticles (
r
cut
) of plants. The surface uptake of
Fig. 2.
The balance of latent heat (LE) and sensible heat (SH) fluxes com-
pared with net radiation (R
n
) minus heat storage (S), virtual temperature and
absolute water vapor, and fluxes and mean mixing ratios for select chemical
species.
SI Appendix
, Fig. S17
, shows the remaining fluxes and mean mixing
ratios measured in this work.
Fig. 3.
Measured deposition velocities (centimeters per second) for species
included in this work. The daytime (h
=
1000
–
1500) mean (centimeters
per second) and SD (1
σ
)are(
A
)formicacid[1.0
±
0.4], (
B
)nitricacid[3.8
±
1.3], (
C
)HCN[0.3
±
0.1], (
D
)H
2
O
2
[5.2
±
1.1], (
E
)HMHP[4.1
±
1.1], (
F
)PAA
[2.7
±
0.7], (
G
)ISOPOOH
+
IEPOX (IP
+
IE, isomeric) [2.5
±
0.6], (
H
)HPALD
[2.4
±
0.6], (
I
) ISOPN [1.5
±
0.6], (
J
) MACN
+
MVKN [1.5
±
0.5], (
K
),
PROPNN [1.7
±
0.6], (
L
) HAC [1.4
±
0.5], (
M
) HDC
4
[1.1
±
0.5], (
N
) DHC
4
[1.0
±
0.4], (
O
) INP [1.3
±
0.6], and (
P
) MTNP [0.8
±
0.4]. Solid curve is data
smoothed by a moving average algorithm.
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Nguyen et al.
a particular compound is represented as functions of
D
x
, water
solubility (
H
, Henry
’
s Law coefficient), and a reactivity coeffi-
cient (
f
0
, range 0
–
1 where 1 is as reactive as ozone),
R
c
∼
1
ð
r
s
ð
D
x
Þ
+
r
m
ð
H
;
f
0
ÞÞ
+
1
r
cut
ð
H
;
f
0
Þ
−
1
:
[4]
The original Weseley parameterization overestimates
R
c
for
compounds like H
2
O
2
(20), which should be close to zero (22),
despite the fact that water solubility of H
2
O
2
is not significantly
variable below pH
=
8 and
f
0
is set to maximum. With empirical
results at hand, we optimized the parameters in the Weseley
R
c
scheme to minimize discrepancies between calculated and ob-
served
V
d
. We adjusted coefficients only in the
r
m
and
r
cut
terms
(
SI Appendix
, Eqs.
14
–
16
) to be more sensitive to water solubil-
ity. Furthermore, we use the simple Henry
’
s Law coefficients (
H
)
that describe physical solvation in pure water, instead of effective
Henry
’
s Law coefficients (
H
*). We find that
H
satisfactorily repro-
duces empirical
R
c
. Furthermore,
H
is a more practical parameter
as the knowledge of ionic activity (36, 37) and pH at surface
aqueous layers is not readily available to estimate
H
* for the
species where solubility enhancements are important (e.g., alde-
hydes, acids, and bases). We neglect pH dependence for solubility
because pH inside plant mesophyll (38) and leaf surface (39) tend
to be buffered near neutral.
H
was estimated based on chemical
proxies for the larger multifunctional compounds (
SI Appendix
,
Table S2
) where measured values were unavailable (40).
Fig. 4 shows that results from the revised resistance model are
in excellent agreement with ambient observations for the ma-
jority of the compounds studied in this work. The poorer model
agreement for the mean of ISOPOOH
+
IEPOX is likely due to
error in flux measurement and not modeling. Deposition velocity
for IEPOX may be slightly underrepresented in our work be-
cause the expected time response delay in sampling IEPOX was
uncorrected (
SI Appendix
,section5
). Surface resistances are small
for the water-soluble and more reactive species (e.g., strong acids,
hydroperoxides, and peroxyacids) but become important for other
compounds. The parameterization captures observed
V
d
success-
fully on both ends of the water-solubility spectrum, e.g., for poorly
water-soluble compounds like HCN [
H
≈
10 M
·
atm
−
1
(40)] and for
highly water-soluble compounds like HMHP (
H
∼
10
6
M
·
atm
−
1
).
The exception is formic acid, where
V
d
predicted by the re-
sistance model is approximately twice the observed value.
The behavior of formic acid cannot be explained by the physical
characteristics of this molecule. With the assumption that the re-
sistance model results are robust, poor model agreement implies
that error may exist in the formic acid measurement, solubility
estimations, or the assumption that formic acid has no emission
source. A time response test suggests that
>
98% of the formic acid
flux was captured by the measurement (
SI Appendix
,Fig.S11
)and
H
is not expected to be overestimated for formic acid. More likely,
we believe that a significant portion of the observed formic acid in
a forested setting is produced by secondary, possibly heteroge-
neous, reactions (6, 41). These secondary emission pathways are
additional to the proposed primary emission of formic acid from
biogenic, anthropogenic, and pyrogenic sources. The discrepancy
between modeled and observed
V
d
of formic acid requires a large
emission flux
—
on the order of 1 nmol
·
m
−
2
·
s
−
1
in the daytime.
One possible route to secondary formic acid formation may
include water-mediated degradation of larger OVOCs that are
deposited on canopy surfaces or on aerosol surfaces, e.g., the oxi-
dation of IEPOX (42) and decomposition of HMHP (43). The
deposition of HMHP and IEPOX is likely independent of surface
chemistry at this site because surface uptake is not a limiting process
for these compounds (Fig. 4,
Lower
). Thus, their in-canopy chem-
istry is not expected to lead to model/measurement disagreement,
within the error of the measurement, by significantly enhancing
deposition. HMHP decomposition (downward flux of
∼
0.2
nmol
·
m
−
2
·
s
−
1
) may produce formic acid via thermal, photochem-
ical, or dark decomposition pathways. The lifetime of HMHP with
respect to hydrolysis at neutral pH has been measured to be
roughly 17 min (44), on the timescale of mixing within the can-
opy. The formation yield of formic acid from IEPOX oxidation is
significant in the gas phase (10
–
30%) (42), although the lifetime
of IEPOX in the gas phase is long (
>
10 h). We speculate the
yields are higher in the aqueous phase; however, more work is
needed before the contribution of IEPOX to the formic acid flux
can be estimated.
Another possible formic acid source is the rapid in-canopy
ozonolysis of monoterpenes and other biogenic VOCs (45, 46),
which may occur primarily within stomata (47) and is enhanced
under humid conditions (43). For example, the in-canopy ozo-
nolysis of sesquiterpenes (
τ
≈
1
–
2 min) has been estimated to con-
sume 0.6
–
1.5 nmol
·
m
−
2
·
s
−
1
(7
–
28%) of the downward ozone flux
and 46
–
61% of the sesquiterpenes mass in Amazonia (48). Ap-
proximately 6% of the ozone flux at this site is required to ac-
count for the entire formic acid flux. Although the kinetics and
yields of the myriad formic acid formation routes are not well
understood, a 1 nmol
·
m
−
2
·
s
−
1
secondary source of formic acid
from these combined pathways appears plausible.
The calculated resistances shed light on a remarkable empirical
relationship of highly depositing compounds
—
their observed day-
time deposition scale with inverse molecular mass
ð
ffiffiffiffi
m
p
Þ
−
1
(Fig. 5).
These trends suggest that molecular diffusivity through the leaf
boundary layer and, for larger molecules, from the leaf surface itself
act as a constraint on dry deposition at a specific turbulent condi-
tion. According to the resistance model, diffusivity restrictions arise
from the terms describing transport to the quasi-laminar layer of the
leaf surface (
R
b
) or through stomata (
r
s
component of
R
c
). We find
two
“
diffusion-limited
”
upper bounds: when there is no resistance at
the surface of the leaf (
R
total
=
R
a
+
R
b
,Fig.5,dashedline)and
when there is a stomata-controlled resistance at the surface of the
leaf [
R
total
=
R
a
+
R
b
+
R
c
(
r
s
), Fig. 5, solid line]. The two limits
converge for smaller compounds (
<
80 Da) with high diffusivity
such that
r
s
is minimal. As expected, the observed daytime
V
d
for
HNO
3
(the prototypical molecule for rapid deposition) is at
maximum for its size. It appears that bulkier compounds such as
MTNP cannot achieve surface resistance-free deposition because
they are hindered by subsequent transport through the stomata.
Fig. 4.
(
Upper
) Daytime mean deposition velocities (centimeters per sec-
ond) that were measured vs. calculated by a tuned resistance model. (
Lower
)
Modeled contributions to the total deposition resistance from aerodynamic
transfer (R
a
), molecular diffusion (R
b
), and canopy uptake (R
c
). Model inputs
and results are shown in
SI Appendix
, Table S2
.
Nguyen et al.
PNAS
|
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|
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EARTH, ATMOSPHERIC,
AND PLANETARY SCIENCES
PNAS PLUS
Efficiently-depositing compounds approaching the stomata-
controlled diffusion limit generally belong to the chemical classes
of simple or multifunctional hydroperoxides and strong acids
with high water solubility (threshold
H
in this model
≈
3
×
10
4
M
·
atm
−
1
). The model sensitivity to various parameters is dis-
cussed in
SI Appendix
, section 6
, and shown in
SI Appendix
, Fig.
S16
, for
H
. Organic nitrates and peroxyacids are close to the
upper bound. Most of the major outliers in Fig. 5, e.g., HCN and
ketones, have poor solubility in water or low reactivity at the leaf
surface, which produces a substantial nonstomatal
R
c
term. In
particular, uptake of HCN from the surface comprise
>
90% of
its total resistance. Formic acid is also an outlier on this plot,
likely due to the aforementioned emission. In addition to diffu-
sion restrictions, the absolute deposition velocities for a specific
compound remain highly dependent on atmospheric stability.
The aerodynamic resistance (
R
a
) can be significant when the
atmospheric stability is high; however, this term is identical for
all compounds, so it will materialize as a vertical offset in Fig. 5.
Under exceptionally high turbulent mixing conditions (
R
a
→
0),
we estimate that
V
d
for HNO
3
and H
2
O
2
can reach
∼
6cm
·
s
−
1
and 8 cm
·
s
−
1
, respectively, in this forest setting.
The empirical relationship between mass and deposition velocity
for soluble species serves as a useful paradigm for understanding
previous and future measurements performed under differing
conditions. That a single physical
characteristic of atmospheric
trace gases constrains their deposition velocities in relation to
each other has not yet been fully realized. Current sensitivity
simulations of atmospheric loss often exceed these
“
diffusion-
limited maxima
”
when modeling dry deposition of OVOCs. For
example, HNO
3
is typically modeled to have the highest relative
deposition velocity, and sensitivity studies tend to equate
V
d
of
other compounds that may also deposit quickly (e.g., ISOPN)
to
V
d
of HNO
3
(7, 49). These data suggest that it may be more
appropriate to scale
V
d
of highly depositing species in sensitivity
simulations with respect to H
2
O
2
or HNO
3
based on molecular
mass. Furthermore, it appears that H
2
O
2
will always deposit
faster than HNO
3
at any given turbulent condition.
Impact on Regional and Global Budgets of Trace Gases.
Global at-
mospheric transport models used to assess chemistry and climate
feedbacks often overpredict surface volume mixing ratios for trace
gases such as H
2
O
2
(50, 51), HCN (52), and ISOPN (5). Depending
on the molecule, such model discrepancies can affect the entire
troposphere or only the boundary layer. These overestimations have
motivated hypotheses about unknown atmospheric sinks for these
compounds or their precursors, e.g., enhanced aerosol uptake of
HO
2
due to Fenton chemistry that does not produce H
2
O
2
in the
gas phase (51) or an ocean sink for HCN (52).
We performed regional and global simulations using GEOS
−
Chem v9.2 (53), a global 3D chemical transport model, to as-
sess the importance of dry deposition in model simulations of
surface mixing ratios. GEOS
−
Chem simulations were driven by
GEOS-FP (forward processing) meteorology with hourly reso-
lution (
SI Appendix
, section 7
). Compound-specific surface
mixing ratio and vertical profile impacts in response to modeled
changes in dry deposition are a nonlinear result of chemistry,
land use, and meteorology; thus, they are not possible to predict
a priori. In one case study, we performed a 1-mo simulation at
a fine-grid horizontal resolution of 0.25°
×
0.33° to facilitate
comparisons with hourly observations of deposition velocities
and meteorology at the measurement site. Two year-long global
simulations at a coarser resolution (2°
×
2.5°) were also per-
formed for a
“
base
”
case and
“
sensitivity
”
case. In the base
simulation, we use the default GEOS
−
Chem dry deposition ve-
locities, while in the sensitivity simulation, we adjust the average
daytime
V
d
of several compounds to match measurements. We
use the most recent version of GEOS
−
Chem chemical mech-
anism with a few updates (
SI Appendix
,TableS3
)toreflect
revised knowledge of OVOC reactions published very recently,
such as updated ISOPN
+
OH and ISOPN
+
O
3
rate coefficients
(54). Model results for HCN and several other species of interest
are not available because these com
pounds are either not included
in GEOS
−
Chem (HMHP, HCN, HPALDs, HDC
4
,DHC
4
,INP,
and MTNP) or because their dry deposition was neglected in the
model (PAA). Among the compounds not included in the sim-
ulations, HMHP (55) and HPALDs (56) may have the more
significant impact on model predictions because of their high
deposition velocities and large abundance in forested settings
and in biomass burning plumes.
Fig. 6 shows the meteorological conditions and energy fluxes
generated by GEOS-FP and deposition velocities calculated by
the fine-grid GEOS
−
Chem simulation for June 2013 at the coor-
dinates of measurement site (CTR)
. Excellent agreement in both
the mean magnitudes and diurnal pattern was obtained for the
comparison of friction velocity (turbulence, Fig. 6
A
), sensible
heat flux (Fig. 6
B
), and latent heat flux (Fig. 6
C
) between the
model (averaged for 30 d) and measurements (averaged for 5 d).
This suggests that the meteorological and surface exchange
conditions during the select days used in this work are repre-
sentative of the site during June. Furthermore, these simulations
suggest that flux observations during the SOAS campaign are not
atypical for the eastern US region or for the year 2013 (
SI Ap-
pendix
, Figs. S18 and S19
, respectively).
The deposition velocities for compounds of interest showed
poorer agreement in the fine-grid simulations (Fig. 6
D
–
F
, black
lines). As meteorology and land surface processes are reasonably
well represented in the atmospheric model, the discrepancy likely
resides in the parameterization of surface uptake resistance (
R
c
)
by the canopy. The GEOS
−
Chem model uses the Weseley scheme
(Eq.
4
) to calculate surface resistance for chemical species. As
noted earlier (20),
R
c
for H
2
O
2
and certain OVOCs are over-
estimated compared with observations, leading to low values of
V
d
simulated by the model. For the sensitivity study, we arbi-
trarily increased the effective solubility inputs for compounds of
interest (
SI Appendix
, Table S4
) until the calculated
V
d
matched
observed values (Fig. 6
D
–
F
, blue lines, when an applicable
change is made). In some cases, the required solubility adjust-
ments are clearly too large compared with uncertainties and
suggest that a change to the parameterization, such as was done in
Resistance Model of Deposition
, should be implemented to improve
the model description of dry deposition in future work. This
method, however, is a reasonable temporary solution that can be
Fig. 5.
The dependence of deposition velocities on inverse molecular mass
ð
ffiffiffiffiffi
m
p
Þ
−
1
, a representation of molecular diffusivity, for various chemical clas-
ses. The dashed line is the upper limit for deposition without surface re-
sistance (
V
d
=
1/[
R
a
+
R
b
]). The solid line is the upper limit for deposition that
experiences only stomatal resistance at the surface (
V
d
=
1/[
R
a
+
R
b
+
R
c
(
r
s
)]).
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www.pnas.org/cgi/doi/10.1073/pnas.1418702112
Nguyen et al.
immediately implemented in atmospheric models while an upda-
ted parameterization is under development.
Table 1 shows simulation results extracted for June 2013 from
the base and sensitivity studies in the grid box that encompasses
the coordinates of the measurement site. Changes in
V
d
signifi-
cantly impact predictions of surfac
e concentration for the depositing
species, but secondary chemistry, e.g., ozone production or SO
2
oxidation, are not considerably affected. The surface mixing ratios
for compounds with adjusted
V
d
decreased
∼
10
–
50%. Although the
observed changes in modeled mixing ratios were not found to affect
O
3
and HO
x
(OH
+
HO
2
) at this site, season, and altitude (
<
1km),
effects on O
3
and HO
x
due to the photochemistry of isoprene
nitrates and H
2
O
2
, respectively, may be more significant for other
regions of the globe and times of the year (51, 57). The adjustment
in
V
d
for H
2
O
2
was the largest (a factor of 7 increase), and its
surface mixing ratio was correspondingly reduced by the greatest
amount (45%). Higher H
2
O
2
dry deposition significantly affected
simulation results of its surface concentration for much of the
forested areas of the globe (Fig. 7), e.g., Canadian and European
boreal forests, the Amazon basin, and the Congo basin. Mea-
surements at these sites are not available for model comparison;
however, the results suggest that underrepresentation of dry de-
position for H
2
O
2
is likely responsible for much of past over-
estimations of its mixing ratios in GEOS
−
Chem simulations (51).
The sensitivity of H
2
O
2
boundary layer mixing ratio to dry
deposition may be expected because this compound has a long
lifetime with respect to oxidation and photolysis in the lower
atmosphere. To estimate dry, midday sinks, we use measured
daytime deposition velocities (Fig. 3), simulated [OH]
≈
2.6
×
10
6
·
cm
−
3
(twice the 24-h value in Table 1), simulated photolysis
under tropical noon with 300 Dobson units ozone (58), and
a boundary layer height of 1.5 km. The deposition lifetime of
H
2
O
2
(
τ
dep
≈
8 h) accounts for
>
70% of its total atmospheric
loss under dry conditions [
τ
hv
≈
1.4 d;
τ
OH
≈
2.6 d (59)]. Re-
action with ozone, usually several orders of magnitude slower
for unsaturated compounds and unimportant for saturated
compounds, was
neglected as a loss process. Dry deposition of
other saturated compounds can be expected to dominate their
atmospheric removal in a manner similar to H
2
O
2
because their
reactive lifetimes in the atmosphere are long and their water
solubilities are high. For example, HMHP (
∼
4cm
·
s
−
1
) has a de-
position lifetime of 10 h, accounting for
∼
55% of its atmospheric
removal [
τ
hv
≈
4d,
τ
OH
≈
14 h (estimated based on methylhy-
droperoxide
+
OH rate coefficient) (60)]. Similarly, dry deposition
may comprise
∼
60% of the atmospheric loss for PAA (59, 61) and
∼
45% of the atmospheric loss for IEPOX (42). IEPOX is also
removed by reactive uptake to aerosols. Using data from a recent
Fig. 6.
Base GEOS
−
Chem (run at 0.25° lat
×
0.33° lon) simulations (black
lines) and observations (colored points) for June 2013 at the Brent, AL CTR
site. The modeled (
A
) friction velocity, (
B
) sensible heat flux, and (
C
) latent
heat flux data are derived from GEOS-FP hourly-resolved meteorology. De-
position velocities (
D
–
F
) were calculated from GEOS
−
Chem without mod-
ifications (black lines) or with adjustments to the Henry
’
s coefficient of these
compounds (blue lines, if applicable) for a sensitivity study (see text). Simu-
lations were performed for all 30 d in June 2013, and observed data were
measured for the 5 d included in this study. Error bars represent 1 SD from
mean values.
Table 1. GEOS
−
Chem base and sensitivity (sens.) simulation for the grid box representing the
Brent, AL, field site, 2°
×
2.5° resolution
Tracer name
Base V
d
,* cm
·
s
−
1
Sens. V
d
,* cm
·
s
−
1
Base conc. (70 m) Sens. conc. (70 m)
Δ
%
OH
––
1.32
×
10
6
1.30
×
10
6
−
2
HO
2
––
3.84
×
10
8
3.77
×
10
8
−
2
NO
––
0.12
0.12
0
NO
2
––
0.98
0.98
0
O
3
––
50.97
50.63
−
1
PAN
––
0.38
0.37
−
2
HNO
3
3.02
3.02
0.46
0.45
−
1
H
2
O
2
0.37
2.66
2.83
1.55
−
45
PPN
––
0.019
0.018
−
2
HCHO
––
3.64
3.60
−
1
MHP
––
1.18
1.15
−
2
SO
2
––
1.20
1.21
1
SO
4
––
0.53
0.52
−
2
ISOPN
0.30
0.82
0.081
0.073
−
10
MACN
+
MVKN
0.30
0.81
0.075
0.069
−
9
PROPNN
0.30
0.48
0.055
0.047
−
14
HAC
0.30
0.71
1.48
1.25
−
15
ISOPOOH
0.76
0.76
0.38
0.38
0
IEPOX
2.86
2.73
0.58
0.59
1
Concentrations (conc.) are reported in parts per billion by volume, except OH and HO
2
, where units are in
molecules per cubic centimeter. Percent change is defined with respect to the base simulation.
*The 24-h average (approximately half of daytime value).
Nguyen et al.
PNAS
|
Published online January 20, 2015
|
E397
EARTH, ATMOSPHERIC,
AND PLANETARY SCIENCES
PNAS PLUS
laboratory study of IEPOX particle uptake probabilities (62), we
estimate that the dry deposition fate of IEPOX is significantly
affected only in the presence of very acidic inorganic sulfate par-
ticles at pH
<
1 (reduced to
∼
20%) and is relatively unaffected if
the particles have more moderate acidities (pH
>
3).
For unsaturated compounds like ISOPN, deposition may
comprise a smaller fraction (
<
10%) of the daytime sink because
its reaction with OH is fast (54). Thus, errors in representation of
ISOPN dry deposition will have a much smaller effect on simu-
lated ISOPN surface concentrations. In general, while dry de-
position is less important for organic nitrates than peroxides,
changes in their mixing ratios obtained from the sensitivity study
were significant for both classes of compounds. Mixing ratios for
organic nitrates from isoprene were reduced by 9
–
14% in the
sensitivity study. The carbonyl nitrates (in particular MACN)
may be reasonably photolabile (63), further diminishing the
importance of dry deposition. Smaller multifunctional carbonyls
like HAC are longer-lived in the atmosphere. Correspondingly,
their surface concentration reductions (15%) in the sensitivity
study are larger than for ISOPN.
The differences in H
2
O
2
and other trace gas mixing ratios in
the troposphere between the base and sensitivity studies were
most significant within the boundary layer (
<
3 km). Importantly,
the concentration gradient is larger near the surface when
V
d
is
higher (
SI Appendix
, Fig. S20
), leading to more pronounced
differences between the base and sensitivity studies at the mea-
surement height of
∼
20 m. As the lowest vertical layer in GEOS
−
Chem corresponds to an average height of 70 m, we linearly
extrapolated the surface gradient to the tower height for com-
pounds of interest to compare with measurements. Compared
with mixing ratios measured at SOAS [24-h mean
≈
0.5 (
±
30%)
parts per billion by volume (ppbv) on campaign days without
significant precipitation], H
2
O
2
mixing ratios are overpredicted
by more than 300% in the base simulation and are much closer
in the sensitivity simulations, but still overpredicted by
∼
85%.
Daytime values for other trace gases are still overestimated by
30
–
300% in the model for the CTR measurement site; however,
all mixing ratios in the sensitivity study are substantially closer to
measured values at SOAS when extrapolated to the measure-
ment height. The errors in overestimations are reduced by fac-
tors of 1.5
–
4.
The most dramatic overestimation occurred with IEPOX,
where 24-h mean values at SOAS are measured to be
∼
0.09 ppb
with tandem mass spectrometry and simulated to be
∼
0.35 ppb
(extrapolated to 20 m). Unlike H
2
O
2
, this result is not attributed
to underestimation of dry deposition. In fact, the simulated
V
d
in
GEOS
−
Chem for IEPOX is
∼
70% higher than results from the
adjusted resistance model we used in this work. Interestingly,
V
d
simulated in GEOS
−
Chem for ISOPOOH is
∼
50% lower than
our estimates. IEPOX deposition velocity should be limited by
molecular diffusion due to its high water solubility (Fig. 5), which
suggests a lower daytime
V
d
than that simulated by GEOS
−
Chem (
∼
5.5 cm
·
s
−
1
). The average
V
d
for these isobaric species
was not adjusted in our sensitivity simulations because their
mean simulated
V
d
is similar to the observed value due to the
negating errors. More likely, the low observed mixing ratios of
IEPOX at SOAS may be due to error in its production rate or
because heterogeneous loss reactions, such as conversion to or-
ganic aerosols in anthropogenically impacted particle liquid
water (64), were not accounted for in the model. IEPOX uptake
clearly involves hydronium-catalyzed ring opening in aerosol
liquid water (62, 65, 66). However, field results suggest that more
factors than acid catalysis govern the chemistry (67). Laboratory
results indicate that hydrated ammonium sulfate particles (but
not sodium or magnesium sulfate) produce a similar magnitude
of organic aerosol mass due to IEPOX uptake regardless of
whether acid was added (68, 69). More work is needed to
elucidate field observations and update atmospheric model
mechanisms.
Results from this sensitivity simulation suggest that improved
representations of dry deposition in GEOS
−
Chem, and likely
other models, would partially resolve model overestimations for
certain species within the boundary layer. Additionally, an ex-
perimentally constrained OVOC dry deposition scheme is likely
to have a substantial effect on the organic aerosol budget, as
suggested previously (11). The impact on aerosols, however, was
not determined in this work. Enhanced accuracy of model sim-
ulations of biogenic trace gas surface concentrations and life-
times may be gained by updating the model to include OVOCs
that are not yet in the mechanism and by improving vertical
mixing schemes for volatile compounds (70), especially near the
canopy (71).
Impact on Ecosystems.
The field observations suggest that a sig-
nificant portion of VOC emitted by the biosphere is returned to
the ecosystem via dry deposition of OVOCs. Fig. 8,
Left
, shows
the net mean deposition of C, N, and O atomic mass, obtained
from the speciated contributions of 16 molecular formulas ob-
served, averaged across multiple days. As our measurements
encompass only a subset of organic species present in the tro-
posphere, all estimations of combined fluxes are lower limits. We
observed that at least 6% of the reactive carbon mass that was
emitted as isoprene in an AL forest [
∼
4 mgC
·
m
−
2
·
h
−
1
daytime
(72), integrated over 24 h] were removed by the canopy via dry
deposition of isoprene
’
s oxidation products. Our analysis does
Fig. 7.
GEOS
−
Chem sensitivity study (2° lat
×
2.5° lon) for H
2
O
2
during June
2013: 24-h mean deposition velocities in the (
A
) base and (
B
) sensitivity
simulations and surface mixing ratios in the (
C
) base and (
D
) sensitivity
simulations.
Fig. 8.
(
Left
) Net carbon, oxygen, and nitrogen downward flux by mass, cal-
culated from molecular formulas for compounds shown in
SI Appendix
,Table
S1
, and averaged over the dates in the study. (
Right
) Percent contribution of
organic nitrates and nitric acid to the measured oxidized nitrogen flux.
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www.pnas.org/cgi/doi/10.1073/pnas.1418702112
Nguyen et al.
not include HCN and MTNP. This estimate of the contribution
of dry deposition removal of isoprene carbon may be larger if the
many isoprene-derived OVOCs that are expected to deposit are
included in the analysis, e.g., ethanal nitrate, various acylperox-
ynitrates (APNs), acetic acid, glycolaldehyde, formaldehyde,
glyoxal, methylglyoxal, acetaldehyde, and other OVOCs.
Oxygenated compounds contribute most of the mass flux due
to the combined effect of their larger molecular weight from the
incorporation of oxygen during oxidation (73), and the pro-
pensity for less-volatile and more-water-soluble compounds to
deposit. The oxidant deposition observed by our instrument is
attributed to hydroperoxides (
−
OOH), although we are missing
the likely minor contribution of methyl hydroperoxide (MHP).
Organic hydroperoxides can be formed primarily from the RO
2
reaction with HO
2
, more prevalent in pristine environments, or
from humid ozonolysis, more prevalent in urban-influenced
environments (Fig. 1). Thus, oxidant deposition is highly de-
pendent on geographical location and time of day. However,
ozone has been considered as the predominant oxidant in
modeling dry deposition or in estimating oxidant-induced plant
damage. The apparent effects of ozone on forest ecosystems are
well documented, but they may not be directly attributable to
ozone. Ozone concentration rapidly declines after stomatal up-
take, and damaging effects in plants are often linked to the
production of secondary stressors that are dependent on ozone
dose (74). These secondary stressors were suggested to be, in
part, H
2
O
2
, HMHP, and other hydroperoxides that are produced
as part of alkene ozonolysis (46). It should be noted that both
H
2
O
2
and O
3
may elicit beneficial defense reactions in plants
below their relative phytotoxic limits (75, 76), and the physio-
logical effects are tightly coupled. Thus, it may be useful to
consider the total activated oxygen flux as the sum of ozone
and peroxides.
We estimate that the daytime molar peroxide flux at this
southeast US site (2.4 nmol OOH
·
m
−
2
·
s
−
1
) is 15% of the ozone
flux on average [
∼
16 nmol
·
m
−
2
·
s
−
1
using [O
3
]
=
50 ppbv and
V
d
;
O
3
=
0.8 cm
·
s
−
1
(77)]. However, in more pristine areas like the
Amazon rainforest, the concentration of total peroxides is higher
and ozone is lower than the southeast United States. The esti-
mated daytime peroxide flux of 5.7 nmol
·
m
−
2
·
s
−
1
in Amazonia
[using [H
2
O
2
] and [ROOH] observed by Lelieveld et al. (4) and
V
d
;
H
2
O
2
=
5cm
·
s
−
1
and
V
d
;
ROOH
=
2cm
·
s
−
1
] can be 50
–
120% of
observed daytime O
3
fluxes during the dry season (78). These
results suggest that, across varying degrees of urban influence,
peroxides can comprise a significant to dominant fraction of the
daytime oxidant flux in forest ecosystems.
Exogenous H
2
O
2
(millimolar equivalent) has been shown to
inhibit stomatal opening by signaling the production of NO in
guard cells (79, 80). Furthermore, as peroxides are potent oxi-
dizers and generators of reactive oxygen species (ROS) like the
hydroxyl radical (OH) and the superoxide (O
2
.
−
) in water, their
large deposition flux motivates inquiries into their fates at the
surface of plants. Deposited peroxides likely participate in
aqueous or heterogeneous chemistry, e.g., the oxidation of de-
posited SO
2
to sulfuric acid (81) or the production of ROS like
OH, HO
2
, and O
2
.
−
through direct photochemistry and catalytic
reaction with trace metals (Fe) (82). During the SOAS cam-
paign, we measured plumes of SO
2
in the range of 1
–
9 ppb (
SI
Appendix
, Fig. S21
). The peroxide-mediated production of strong
acids and oxidants may play a role in plant damage during these
episodes. Additionally, this chemistry may contribute to the
aforementioned inferred emission flux of formic acid through
heterogeneous oxidation of OVOCs. Whether the observed de-
position flux of peroxides can impact atmospheric chemistry via
heterogeneous pathways or affect plant function under typical
atmospheric conditions remains to be further explored.
The mean daytime dry deposition flux from HNO
3
,HCN,
and speciated organic nitrates was measured to be 27 (
±
15)
μ
gN
·
m
−
2
·
h
−
1
. To estimate the ecosystem input of nitrogen, the
dry flux of N-containing species that were not measured in this
work (NH
3
,NH
4
+
, etc.) were simulated with GEOS
−
Chem.
The wet-deposited N data for 2013 (measured as NH
4
+
and
NO
3
−
) was provided by the National Atmospheric Deposition
Program at the AL03 site corresponding to CTR (
nadp.sws.uiuc.
edu/
). We estimate that dry deposition supplied
∼
52% of the
total wet and dry input of nitrogen to the canopy by mass. This
result is consistent with average estimates (
∼
46%) at 10 North
American forests (83).
HNO
3
is commonly assumed to dominate the oxidized nitro-
gen dry deposition flux; however, our data indicate that organic
nitrates (RONO
2
) measured by our instrument can constitute
a sizable portion (15%) of the dry flux of oxidized nitrogen ob-
served at this site (Fig. 8,
Right
), with nitric acid making up the
balance. This is a lower limit of the organic nitrogen input into
the canopy. Zhang et al. (49) assumed a deposition velocity of
isoprene nitrates to be
∼
5.5 cm
·
s
−
1
in the daytime (greater than
a factor of 3 larger than our observations) and arrived at a similar
conclusion. If we include an estimation for acylperoxy nitrates
from data obtained in Northern California (84), the resulting
organic nitrogen contribution would be a bit higher (
∼
25%).
HCN was, at most, 3% of the N flux observed in this work.
However, the main source of HCN is biomass burning and, thus,
its flux will vary significantly depending on location and time of
year. The minor impact from NO
2
deposition (21) was neglected.
The data demonstrate that organic nitrogen is an important
fraction of the oxidized nitrogen dry deposition flux, similar to
wet deposition (85). The organic nitrogen may be taken up by
foliage (86, 87) and incorporated into the synthesis of leaf
nutrients. As the effects of organic nitrogen on carbon seques-
tration are inadequately represented in most ecological models,
these data motivate further inquiry into the ecosystem ram-
ifications of OVOC deposition.
Materials and Methods
Site and Sampling.
This work was performed as part of the SOAS Campaign
(
soas2013.rutgers.edu/
) at the CTR Southeastern Aerosol Research and
Characterization Study (SEARCH) site operated by the Electric Power Re-
search Institute (Brent, AL, Lat 32.90289 Lon
−
87.24968) for the US Envi-
ronmental Protection Agency. The metal walk-up sampling tower was
∼
20 m
in height (measurement height
∼
22 m) and the mean canopy height was
∼
10 m. The CIMS was situated on the topmost platform, facing north toward
the forest. The temperatures inside the instrument enclosure and CIMS flow
region were controlled, and the instrument was shielded from the elements
by an insulated enclosure. An ultrasonic anemometer extending off the
tower on the north side, longitudinally separated from the inlet
∼
0.8 m,
measured the 3D wind components and the converted virtual temperature.
A weather station comprised of several sensors monitored the relative hu-
midity (RH, percent), air temperature (
T
, degrees Centigrade), barometric
pressure (
P
, millibars), solar radiation (watts per square meter), wind speed
(meters per second), and wind direction (0
–
360°).
CIMS Mixing Ratios.
The ionization mechanism and details about calibration
for each species are presented in
SI Appendix
. Briefly, compounds were mea-
sured through a high-flow fluoropolymer-coated glass inlet (
∼
40 cm long,
3.1 cm ID,
∼
2,000 L
·
min
−
1
). The analytical method, using reagent ion CF
3
O
−
,
is specific toward the detection of acids, hydroperoxides, multifunctional
nitrates, and other multifunctional species. The ionization mechanism is
fluoride transfer for acidic analytes and cluster formation for other analytes.
The absolute sensitivity and water vapor dependence of the ionization were
calibrated for each species in the laboratory by quantitative techniques
(spectroscopy, gravimetry, liquid chromatography, etc.), when calibration
standards are available commercially or can be synthesized and purified (11
out of 16 compounds). The sensitivities were calculated by ab initio methods
otherwise. High-frequency CIMS measurement of water vapor was cali-
brated by 1-Hz weather station measurements of RH,
T
,and
P
after ap-
plication of a temperature correction to the ion signal. In-field calibrations
were performed every 2 h with commerc
ially available standards, and in-
field zero backgrounds were measured every half hour, under dry and
ambient RH conditions.
Nguyen et al.
PNAS
|
Published online January 20, 2015
|
E399
EARTH, ATMOSPHERIC,
AND PLANETARY SCIENCES
PNAS PLUS
Flux Calculations.
Data processing protocols, flux quality assessment and
criteria, standard corrections, and CIMS-specific corrections are documented
in detail in
SI Appendix
. We limit the fluxes presented here to a few ideal
days from the campaign period, characterized by the following conditions:
The turbulence (measured by the momentum flux) is well established, the
data reproducibility is high, the spectral analysis shows expected behavior
for sampling in the inertial subrange, and the energy balance closure at the
surface (Fig. 2) is adequately met. Acceptable data generally correspond to
measurement periods for which winds were northerly, with exclusively forest
fetch. Mixing ratios and the vertical wind were measured at 8 Hz or faster. A
time response correction was applied for HNO
3
(factor of 1.62) as described in
SI Appendix
,section5
, due the measured flux dampening caused by the time
delayofthiscompoundfrominteractionswithinstrumentsurfaces.Mea-
surement uncertainties (
±
1
σ
) are largest for species with lower mean con-
centrations during the daytime, such as MTNP, which has a dominant
nighttime source. A short period of atypical nighttime convection was re-
moved from the data for Julian day 165 due to the flux criteria discussed in
SI Appendix
,section4
. EC fluxes of other species commonly detected by CIMS
(notably, SO
2
, glycolaldehyde, and methyl hydroperoxide) were not calculated
in this work because mixing ratios at this site were either too rapidly changing
(SO
2
plumes) or contain interfering species when measured with the time-of-
flight mass detector.
ACKNOWLEDGMENTS.
We thank the organizers and committee members of
the SOAS campaign: A. G. Carlton, A. H. Goldstein, J. L. Jimenez, R. W. Pinder,
J. de Gouw, B. J. Turpin, and A. B. Guenther. We acknowledge C. J. Groff at
Purdue University for his help with leaf area index measurements and tree
surveys. We thank D. J. Jacob and the Atmospheric Chemistry Modeling Group
at Harvard University for making GEOS
−
Chem available for this work. Mete-
orological data used in the GEOS
−
Chem simulations were provided by the
Global Modeling and Assimilation Office at NASA Goddard Space Flight Cen-
ter. We acknowledge funding from the National Science Foundation (NSF)
under Grant AGS-1240604 and NSF Postdoctoral Research Fellowship program
Award AGS-1331360. Financial and logistical support for SOAS was provided
by the NSF, the Earth Observing Laboratory at the National Center for Atmo-
spheric Research (operated by NSF), the personnel at Atmospheric Research
and Analysis, and the Electric Power Research Institute.
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PNAS
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Published online January 20, 2015
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E401
EARTH, ATMOSPHERIC,
AND PLANETARY SCIENCES
PNAS PLUS