acp-16-9349-2016.pdf

Atmos. Chem. Phys., 16, 9349–9359, 2016

www.atmos-chem-phys.net/16/9349/2016/

doi:10.5194/acp-16-9349-2016

Speciation of OH reactivity above the canopy of an

isoprene-dominated forest

J. Kaiser

1,a

, K. M. Skog

, K. Baumann

, S. B. Bertman

, S. B. Brown

4,5

, W. H. Brune

, J. D. Crounse

J. A. de Gouw

4,5,8

, E. S. Edgerton

, P. A. Feiner

, A. H. Goldstein

9,10

, A. Koss

4,8

, P. K. Misztal

, T. B. Nguyen

K. F. Olson

, J. M. St. Clair

7,b,c

, A. P. Teng

, S. Toma

, P. O. Wennberg

7,11

, R. J. Wild

4,8

, L. Zhang

, and

F. N. Keutsch

Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA

Atmospheric Research & Analysis Inc, Cary, NC, USA

Department of Chemistry, Western Michigan University, Kalamazoo, MI, USA

Chemical Sciences Division, NOAA Earth System Research Laboratory, Boulder, CO, USA

Department of Chemistry, University of Colorado, Boulder, CO, USA

Department of Meteorology, Pennsylvania State University, University Park, PA, USA

Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA

Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA

Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA

Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA

Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA

School of Engineering and Applied Sciences and Department of Chemistry and Chemical Biology, Harvard University,

Cambridge, MA, USA

now at: School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

now at: Joint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, MD, USA

now at: Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA

Correspondence to:

J. Kaiser (jkaiser@seas.harvard.edu)

Received: 11 December 2015 – Published in Atmos. Chem. Phys. Discuss.: 18 January 2016

Revised: 12 July 2016 – Accepted: 12 July 2016 – Published: 28 July 2016

Abstract.

Measurements of OH reactivity, the inverse life-

time of the OH radical, can provide a top–down estimate

of the total amount of reactive carbon in an air mass. Us-

ing a comprehensive measurement suite, we examine the

measured and modeled OH reactivity above an isoprene-

dominated forest in the southeast United States during the

2013 Southern Oxidant and Aerosol Study (SOAS) field

campaign. Measured and modeled species account for the

vast majority of average daytime reactivity (80–95 %) and

a smaller portion of nighttime and early morning reactivity

(68–80 %). The largest contribution to total reactivity con-

sistently comes from primary biogenic emissions, with iso-

prene contributing

∼

60 % in the afternoon, and

∼

30–40 %

at night and monoterpenes contributing

∼

15–25 % at night.

By comparing total reactivity to the reactivity stemming from

isoprene alone, we find that

∼

20 % of the discrepancy is

temporally related to isoprene reactivity, and an additional

constant

∼

1 s

−

offset accounts for the remaining portion.

The model typically overestimates measured OVOC concen-

trations, indicating that unmeasured oxidation products are

unlikely to influence measured OH reactivity. Instead, we

suggest that unmeasured primary emissions may influence

the OH reactivity at this site.

1 Introduction

Biogenic emissions of volatile organic compounds (VOCs)

constitute the largest source of reactive carbon in the atmo-

sphere (Guenther et al., 2012). During the daytime, oxida-

Published by Copernicus Publications on behalf of the European Geosciences Union.

9350

J. Kaiser et al.: Speciation of OH reactivity above the canopy

tion of VOCs by the OH radical can drive the formation of

secondary pollutants. Under high NO

(NO

)

condi-

tions, peroxy radicals (RO

)

generated from VOC oxidation

convert NO to NO

, which ultimately photolyzes to form

ozone. Additionally, oxidized VOCs (OVOCs) are typically

less volatile than their precursors and can contribute to the

formation of secondary organic aerosol (SOA). Therefore, it

is important to understand the total VOC

OH reaction rate

and the fate of the resultant OVOC to understand the forma-

tion of tropospheric ozone and SOA.

While measuring every VOC and oxidation product is not

feasible, measurement of OH reactivity (the loss rate of the

OH radical divided by the OH concentration) provides an al-

ternative to the bottom–up molecular approach (Kovacs and

Brune, 2001). The absolute value of OH reactivity can be

used to estimate the total amount of reactive carbon in an air

mass or the RO

production rate. The speciation of the reac-

tivity carries air-quality-relevant implications as SOA yield

is directly tied to molecular properties such as volatility, hy-

groscopicity, viscosity, and condensed-phase reactivity.

One half of the annual non-methane VOC emissions is in

the form of isoprene (C

)

, making it the dominant bio-

genic VOC globally (Guenther et al., 2012). Due to iso-

prene’s abundance and high reactivity, the chemistry of iso-

prene and its resulting oxidation products have been the focus

of numerous field studies. OH reactivity has been examined

in four isoprene-dominated forests, with some studies sug-

gesting missing primary emissions or missing OVOCs and

others finding good agreement between measurements and

calculations.

In a deciduous forest in Northern Michigan, DiCarlo et

al. (2004) could account for only 50 % of the OH reactiv-

ity measured above the canopy in the summer of 2000. As

OVOCs calculated by a model did not significantly increase

calculated OH reactivity and as the missing reactivity fit a

terpenoid-like emission profile, unmeasured terpene emis-

sions were cited as a large source of reactive carbon in this

environment. However, later measurements of monoterpenes

and sesquiterpenes at this site suggested that only

∼

20 % of

the missing reactivity could be attributed to these primary

VOCs (Kim et al., 2009). Additionally, Kim et al. (2011)

found that measurements and calculations of OH reactivity in

branch enclosures of isoprene-emitting trees at the same site

were in good agreement. Using measurements taken at this

site during 2009, Hansen et al. (2014) found that isoprene ac-

counted for 60–70 % of afternoon OH reactivity both within

and above the forest canopy. Because in-canopy OH reac-

tivity calculations and measurements were in good agree-

ment, the authors concluded that there are unlikely to be un-

measured primary VOCs at this site. However, above-canopy

comparisons show a large missing fraction of reactivity, sug-

gesting that unmeasured oxidation products may contribute

at longer processing times.

In a downy oaks forest in the Mediterranean southeast of

France, Zannoni et al. (2016) examined OH reactivity both

within and above the canopy. Measured and calculated OH

reactivity were in good agreement at both heights during the

daytime, with isoprene contributing 83 % within the canopy

and 74 % above the canopy. However, more than 50 % of

nighttime reactivity was missing on a subset of days. The au-

thors conclude that unmeasured, higher-generation isoprene

oxidation products account for part of the nighttime dis-

crepancy, alongside unmeasured OVOCs produced from the

ozonolysis of large, non-isoprene biogenic VOCs.

In a tropical rainforest in Borneo, unmeasured isoprene-

derived OVOCs were a more dominant contribution to the

observed reactivity than isoprene itself, at nearly 50 % (Ed-

wards et al., 2013). OH reactivity measured from a clearing

atop a hill surrounded by forest was significantly underesti-

mated by a model (

∼

60 % at noon). The authors concluded

missing that primary emissions were unlikely to contribute

significantly to OH reactivity, and an underrepresentation of

secondary multifunctional OVOCs is a likely source of dis-

crepancies.

Finally, in the tropical rainforest of Suriname, in-canopy

OH reactivity measured could not be reached by summing

the contributions from measured isoprene, methyl-vinyl ke-

tone, methacrolein, acetone, and acetaldehyde. The authors

called for a more comprehensive measurement suite to in-

vestigate the large discrepancy (65%) (Sinha et al., 2008).

Each forest examined in these studies is composed of a

unique mixture of tree species, potentially leading to differ-

ent relative contributions of non-isoprene primary emissions.

Furthermore, different meteorological conditions and canopy

structures may lead to different processing times and resul-

tant contributions of isoprene-derived OVOCs. While these

differences may make the above studies difficult to gener-

alize, they all address an underlying question: are isoprene-

derived OVOCs a substantial source of missing reactive car-

bon? If so, after what degree of processing?

To assess the contribution of unmeasured oxidation prod-

ucts, ideally, one would explicitly model all isoprene OVOCs

and include modeled species in the summation. Additionally,

several OVOC measurements would be available to test the

reliability of model concentrations. This sort of analysis has

been performed in a chamber study of the oxidation of iso-

prene (Nölscher et al., 2014), but as initial concentrations of

reactants were orders of magnitude greater than those found

in the atmosphere, and as physical processes such as depo-

sition onto plant surfaces are not captured in chamber stud-

ies, chamber experiments may not capture the behavior of

OH reactivity observed in a forest. Of the above field studies,

several rely only on the concentration of measured species in

the calculation of OH reactivity (Sinha et al., 2008; Hansen

et al., 2014 (part 2 will include a modeling study); Zannoni

et al., 2016). While studies that employ model OVOC con-

centrations have a more complete representation of oxidation

products (DiCarlo et al., 2004; Edwards et al., 2013), neither

of these studies compare measured and modeled OVOC mix-

ing ratios. Additionally, as isoprene hydroxyl hydroperox-

Atmos. Chem. Phys., 16, 9349–9359, 2016

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J. Kaiser et al.: Speciation of OH reactivity above the canopy

9351

ide (ISOPOOH) and isoprene hydroxy nitrate (ISOPN) stan-

dards have only recently become available (Rivera-Rios et

al., 2014; Lee et al., 2014), first-generation oxidation prod-

uct measurements are often incomplete.

With high isoprene emissions, the southeast United States

is an ideal location to reassess questions of missing OH re-

activity and speciation of observed reactivity. In addition

to measurements of OH reactivity, the 2013 Southern Oxi-

dant and Aerosol Study (SOAS) field campaign provides a

comprehensive suite of VOC and OVOC measurements, en-

abling a more constrained analysis of the contribution from

isoprene-derived OVOCs than previously available. This in-

cludes first-generation isoprene oxidation products for both

low-NO and high-NO oxidation, such as ISOPOOH, ISOPN,

isoprene hydroperoxy aldehydes (HPALD), and the sum of

methyl-vinyl ketone (MVK) and methacrolein (MACR), as

well as several smaller oxidation products. Furthermore, dry-

deposition rates of isoprene’s OVOCs are measured and pa-

rameterized for this site (Nguyen et al., 2015), enabling us

to reduce some of the uncertainty related to physical losses

of carbon. Speciated and total monoterpene measurements

provide additional insight into reactive carbon not stemming

from isoprene.

Using a 0-D box model, we investigate the sources of

reactive carbon and compare the summation of calculated

species with measured OH reactivity. We then discuss our

findings in the context of previous studies and briefly dis-

cuss the air-quality-relevant implications. Further discussion

on the isoprene oxidation mechanism and product formation

can be found in Su et al. (2016) and Xiong et al. (2015), and

modeled OH and HO

are discussed more fully in Feiner et

al. (2016).

2 Methods

2.1 SOAS measurements

Measurements were performed from 1 June to 15 July at

the SouthEastern Aerosol Research and CHaracterization

(SEARCH) Centreville (CTR) site near Brent, Alabama,

as part of the 2013 SOAS field campaign (http://soas2013.

rutgers.edu/). CTR is a rural site surrounded by mixed

deciduous-evergreen forests, at times experiencing urban in-

fluence from Birmingham, Montgomery, or Tuscaloosa, AL.

The long-term and regional chemical tends observed at this

site have been discussed in detail elsewhere (Blanchard et

al., 2013; Hidy et al., 2014). We restrict our analysis to

the time frame of good instrumental overlap (11 June to

16 July 2013). All observations shown here are binned to

30 min time intervals. A discussion of missing data interpo-

lation can be found in the Supplement.

Table 1 summarizes the chemical measurements used in

this analysis and their related uncertainties. Most chemi-

cal measurements and solar radiation were acquired from a

walk-up tower with a height of

∼

20 m, approximately 10 m

above the forest canopy. CO, gas chromatograph–electron

capture detector (GC-ECD) measurements, and meteorologi-

cal parameters (relative humidity, temperature, pressure, and

boundary layer height) were acquired from a nearby trailer.

Key measurements to this analysis are OH reactivity,

VOCs, and OVOCs. OH reactivity was measured by adding

OH to an airstream using a moveable wand and monitoring

the decay of the OH radical by laser-induced fluorescence

(Mao et al., 2009). The instrument zero (4.3 s

−

)

is deter-

mined by measuring the wall loss of the OH radical while us-

ing a clean carrier gas. The uncertainty in the zero is 0.5 s

−

with 2

confidence. The recycling of OH from HO

was corrected by taking into account measured HO

decays.

The accuracy of the instrument was verified using gasses

with well-known reaction rate coefficients (C

in the field,

and CO, propane, propene, and isoprene in the lab). Further

details about the operating procedures for the OH reactivity

instrument are described in Mao et al. (2009).

Most VOCs were measured by gas chromatography-mass

spectrometry (GC-MS), which provided 5 min samples ev-

ery 30 min (Gilman et al., 2010). Due to possible line losses

for oxygenated species in GC-MS measurements, proton-

transfer reaction time-of-flight mass spectrometry (PTR-

TOFMS, Ionicon Analytik model PTR-TOF 8000) measure-

ments are used for the sum of MVK and MACR (Jordan et

al., 2009). The PTR-TOFMS also provided measurements of

the total monoterpene mixing ratio. Unspeciated monoter-

penes are defined as the difference between the PTR-TOFMS

measurement of total monoterpenes and the sum of individ-

ual species measured by the GC-MS (

-pinene,

limonene, myrcene, and camphene).

Glycolaldehyde, ISOPOOH, and isoprene dihydroxy

epoxides (IEPOX) were measured by CF

−

triple

quadrupole chemical ionization mass spectrometry (Paulot et

al., 2009; St. Clair et al., 2010, 2014). ISOPN, HPALD, the

sum of MVK and MACR nitrates (MACNO

MVKNO

)

hydroxyacetone, and peroxyacetic acid were measured

by chemical ionization time-of-flight mass spectrometry

(Crounse et al., 2006; Lee et al., 2014). Formaldehyde

(HCHO) was measured by fiber-laser-induced fluorescence

(Hottle et al., 2008; DiGangi et al., 2011), and glyoxal was

measured by laser-induced phosphorescence (Huisman et al.,

2008). Additional speciated organic nitrates were measured

by a gas chromatography–electron-capture detector (Roberts

et al., 2002).

2.2 Model simulations

A 0-D box model analysis was performed using the Univer-

sity of Washington Chemical Box Model (UWCM) (Wolfe

and Thornton, 2011), incorporating the Master Chemical

Mechanism, MCM v3.2 (Jenkin et al., 1997; Saunders et

al., 2003; website: http://mcm.leeds.ac.uk/MCM), updated

to include the isoprene alkyl radical-O

adduct equilibria

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Atmos. Chem. Phys., 16, 9349–9359, 2016

9352

J. Kaiser et al.: Speciation of OH reactivity above the canopy

Table 1.

SOAS measurements used in this study.

Instrument

Parameters

uncertainty

Reference or model number

OH laser-induced fluorescence

16 % (30 min)

Mao et al. (2009)

OH reactivity

10 % (30 s)

Tropospheric Airborne Chromato-

graph for Oxy-hydrocarbons

VOCs

20 % (30 min)

Gilman et al. (2010)

Proton-transfer-reaction time-of

flight mass spectrometer

Total monoterpenes

20 % (1 min)

Jordan et al. (2009)

MVK

MACR

40 % (1 min)

−

triple quadrupole chemical

ionization mass spectrometry

ISOPOOH, IEPOX,

Glycolaldehyde

100 ppt

70 %

(0.5 s)

St. Clair et al. (2010)

Fiber-laser-induced fluorescence

HCHO

15 % (1 s)

Hottle et al. (2008); DiGangi et

al. (2011)

Madison laser-induced-

phosphorescence

Glyoxal

9 % (1 s)

Huisman et al. (2008)

Gas chromatograph–electron cap-

ture detector

PAN

, PPN

, MPAN

20 % (20 min)

Roberts et al. (2002)

−

compact

time-of-flight

mass spectrometer

HCOOH

, H

, HNO

ISOPN, Hydroxyacetone,

Peroxyacetic acid, HPALD,

MACNO

MVKNO

100 ppt

30–50 %

(5 s)

Crounse et al. (2006)

Absorption of IR with gas filter cor-

relation

7.4 % (5 min)

Thermo Scientific Model 48i-

TLE

Nitrogen oxides by cavity ring

down

3 % (1 min)

Fuchs et al. (2009); Wild et al.

(2014)

8 % (1 min)

3 % (1 min)

All species listed are constrained when calculating OH reactivity.

Denotes species constrained when calculating both OH reactivity and OVOC mixing ratios.

Peroxyacetyl nitrate.

Peroxypropionyl nitrate.

Methacryloyl peroxynitrate.

(Peeters and Müller, 2010), isoprene peroxy radical isomer-

izations (Crounse et al., 2011; da Silva et al., 2010), re-

vised ISOPOOH

OH rate constant (St. Clair et al., 2015),

and HPALD photolysis and OH reaction rates (Wolfe et al.,

2012). Monoterpene reactions for species not included in the

MCM (i.e., myrcene, camphene, and unspeciated monoter-

penes) are described in Wolfe et al. (2011). At each time step,

photolysis rates are scaled according to the ratio of measured

radiation and the maximum observed radiation at that time of

day.

Dry deposition is included for H

, organic hydroper-

oxides, nitrates, and the isoprene-derived epoxides (IEPOX).

Measured deposition velocities are used for H

IEPOX,

and ISOPN. For other hydroperoxides and organic nitrates,

noontime deposition velocities are calculated according to

the relationship with mass shown by Nguyen et al. (2015).

Diurnal variability of deposition velocities are scaled ac-

cording to the measured variation for representative species

(ISOPOOH for peroxides, methacrolein nitrate for nitrates).

Dilution is assumed to occur with air with a concentration

of zero for all species. This dilution represents entrainment

with free tropospheric air and any decrease in concentrations

related to unrepresented deposition or advection processes.

A constant, empirically determined rate of 4 day

−

is used

in all analysis presented here, giving a 6 h lifetime with re-

spect to dilution. A sensitivity analysis of this dilution rate

is provided in Sect. 3.2. The model is initiated with a 2-day

spin-up period using diurnal averages of measured species to

account for the buildup of unmeasured intermediate species.

Two separate model configurations are used to examine

OH reactivity and OVOC concentrations. In all discussions

of modeled OH reactivity, OVOC concentrations are con-

strained to their measurements to ensure the most com-

plete representation of measured OH reaction partners. This

includes constraining ISOPN, ISOPOOH, MVK

MACR,

MVKNO

MACNO

, HPALD, and IEPOX by apply-

ing modeled isomeric distributions to measured concen-

trations. Due to the partial conversion of ISOPOOH to

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J. Kaiser et al.: Speciation of OH reactivity above the canopy

9353

Figure 1.

Comparison of measured and modeled OH reactivity col-

ored by measured

-pinene concentrations. The solid line repre-

sents 1 : 1 agreement, and the dashed line (

36) rep-

resents the linear least squares fit weighted by uncertainty (York et

al., 2004; Thirumalai et al., 2011). The gray shaded area represents

the region with 28 % uncertainty of 1 : 1 agreement.

MVK

MACR in the PTR-TOFMS inlet (Rivera et al.,

2014), this represents an upper limit on MVK and MACR

measurements. However, because daytime ISOPOOH con-

centrations are a factor of

5 lower than MVK

MACR

and because the sensitivity to ISOPOOH is only

∼

30 %

of that of MVK

MACR, the effect of ISOPOOH on

the MVK

MACR signal is expected to be negligible. It

should be noted that all species that react with OH are

included in the calculated reactivity, whereas species that

immediately regenerate OH as a reaction product (such as

ISOPOOH

→

IEPOX

OH) would not contribute to

measured OH reactivity. The average total contribution from

such species to calculated reactivity is small (0.6

0.3 s

−

)

The scenario for comparing modeled and measured OVOCs

is identical, except that OVOCs are not constrained. Because

OVOC concentrations are calculated in a separate model

scenario, any discrepancy between measured and modeled

OVOC concentrations does not translate to a discrepancy in

calculated reactivity.

In both model configurations, OH, NO, NO

, CO, O

, HNO

, and all primary VOCs are constrained to their

measurements. Primary VOCs are defined as any species that

are likely to have a significant contribution from direct emis-

sions. This includes alkanes, alkenes, aromatic compounds,

and some oxygenated species (methanol, ethanol, acetone,

methyl-ethyl-ketone, acetaldehyde, biacetyl, propanal, hy-

droxyacetone, and formic acid). Table 1 provides a listing

of constraints for each model scenario.

Figure S5 in the Supplement provides model results for

(HO

OH), OH reactivity, and two first-generation

OVOCs given a variety of possible constraints on HO

and

OVOCs. The result essential to this analysis is that model

is in good agreement with measurements and has a min-

imal impact on calculated OH reactivity and model OVOC

concentrations. Our results are in agreement with Feiner et

Figure 2.

Diurnal profile of the discrepancy between measured and

modeled OH reactivity. Error bars represent 1

standard deviation

of diurnal variability. Points in the gray shaded area are within the

range of agreement considering combined measurement and model

uncertainty (

28 %).

al. (2016), which also employs a 0-D box model and the

MCM isoprene oxidation mechanism. Feiner et al. (2016)

provide a detailed discussion of the observed and modeled

radical budget, which is beyond the scope of this manuscript.

3 Results

3.1 Measured and modeled OH reactivity

Figure 1 shows a comparison between measured and mod-

eled OH reactivity for the constrained-OVOC scenario. Mod-

eled and measured values are well correlated (

85),

with a slope of 0.80

0.02. The average missing reactiv-

ity for all measurement points is 16

18 %. An uncertainty

of 20 % is assigned to model reactivity based on the uncer-

tainty in isoprene, which comprises the majority of modeled

reactivity. Propagating measurement uncertainty (20 %) and

model uncertainty (20 %) yields at least 28 % uncertainty in

the missing fraction of OH reactivity. As both the slope and

average discrepancy agree with measurement within 28 %,

on average, we find no significant discrepancy between mod-

eled and measured OH reactivity. A subset of points that cor-

respond to high

-pinene concentrations fall outside of this

range. Most of these points occur early in the measurement

period, from 11 to 17 June. To investigate the sources of these

discrepancies, we examine both the diurnal variability and

composition of OH reactivity.

Figure 2 shows the diurnal variability of the missing por-

tion of reactivity. In the afternoon, the model typically cap-

tures

90 % of OH reactivity. At night, the model typically

captures

∼

80 % of measured reactivity. Early morning dis-

crepancies show the largest average discrepancies, reaching

an average of 32 % missing reactivity at 07:00 LT.

The average diurnal speciation of observed reactivity is

shown in Fig. 3. Primary biogenic VOCs make up the largest

fraction of modeled OH reactivity throughout the entire day,

with isoprene contributing

∼

60% in the afternoon and

∼

30–

40 % at night and monoterpenes contributing

∼

15–25 % at

night. Oxygen-containing VOCs contribute less significantly

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Atmos. Chem. Phys., 16, 9349–9359, 2016

9354

J. Kaiser et al.: Speciation of OH reactivity above the canopy

Figure 3.

Diurnal profile of measured and modeled OH reactivity.

Error bars represent 1

standard deviation of diurnal variability.

at all time points (

∼

20–28 %), and the largest individual con-

tributors are measured species such as HCHO (

∼

3–4 %),

MVK, and MACR (

∼

2–4 %). Unmeasured oxidation prod-

ucts contribute

∼

6–10 % of total modeled reactivity and are

most prominent at night.

As discussed in Edwards et al. (2013), the increase in to-

tal reactivity with increase in isoprene is another useful pa-

rameter when considering OH reactivity speciation. In a plot

of total OH reactivity plotted against the contribution from

isoprene alone, the slope is related to the contribution from

short-lived isoprene-derived OVOCs and VOCs co-emitted

with isoprene. Figure 4 shows this relationship for measured

and modeled OH reactivity, still referring to the OVOC-

constrained scenario. Both observed and modeled OH reac-

tivity are tightly correlated with OH reactivity from isoprene

(

≥

81). The difference between model (1.22

0.02) and

observed (1.44

0.02) slope is small but significant. This

amounts to 15 % of reactivity correlated with isoprene re-

activity not captured by measured species or modeled un-

measured oxidation products. The

intercept from measure-

ments (6.4

0.1 s

−

)

and model (5.4

0.1) also shows a

small but significant difference. This indicates a missing re-

activity of

∼

1 s

−

that is temporally distinct from isoprene

reactivity.

3.2 Measured and modeled OVOCs

By investigating the model’s ability to capture measured

OVOC concentrations, we can assess the likely accuracy of

model predictions of unmeasured species. As the model is

constrained to measured OVOC concentrations when calcu-

lating model OH reactivity, the contribution of unmeasured

species to total reactivity will be different in these two sce-

narios. However, the evaluation of model performance can

be extended to the constrained-OVOC scenario.

Figure 5 shows the model’s prediction of several mea-

sured OVOC concentrations. Isoprene’s first-generation ox-

idation products MVK

MACR, ISOPOOH, ISOPN, and

HPALD are overpredicted in the afternoon. Though the un-

certainties in each of these measurements is large (40–70 %),

all model concentrations are much higher than measure-

ments. The model overestimates daytime HPALD observa-

tions by a factor of

∼

6, ISOPOOH by a factor of

∼

Figure 4.

Total measured and modeled OH reactivity as a function

of the OH reactivity calculated from isoprene alone. Lines repre-

sent least square linear fits weighted by uncertainty (York et al.,

2004; Thirumalai et al., 2011) for measured (solid) and model (red

dashed) OH reactivity.

and ISOPN by a factor of

∼

3. This translates to an over-

prediction of IEPOX and MACNO

MVKNO

, which are

formed in the oxidation of ISOPOOH and ISOPN, respec-

tively. For MVK

MACR, the daytime overprediction is ap-

proximately a factor of 2. Daytime agreement for MPAN,

which is formed from MACR, is comparatively good. In

general, smaller oxidation products (i.e., glyoxal, glycolalde-

hyde, and HCHO) are less susceptible to overprediction.

In an investigation of isoprene photochemistry and turbu-

lent mixing during this campaign, the mixed layer chem-

ical model (MXLCH) predicts similarly high values for

ISOPOOH (1.5 ppb), MVK

MACR (3.0 ppb), and ISOPN

(80 ppt) in the convective mixed boundary layer (Su et al.,

2016). The MXLCH MVK

MACR mixing ratios are sub-

stantially higher than ground-based measurements but com-

parable to measurements from the Long-EZ research plane

flying at altitudes of 100–1000 m a.g.l.

Model OVOC concentrations are highly sensitive to the

assumed dilution scheme. This sensitivity is examined us-

ing three dilution scenarios: (1) applying an entrainment rate

(

)

calculated from measurements of boundary layer height

(BLH), (2) applying a dilution constant that scales accord-

ing to the ratio of observed BLH and maximum BLH, and

(3) using a constant dilution rate of either 2, 4, or 40 day

−

Calculated dilution rates are derived in the supplement and

shown in Fig. S1, and model results are shown in Figs. S2–

S3. As in the base scenario, measured VOCs are constrained

when calculating OH reactivity. The dilution rate of 4 day

−

used in the base scenarios is chosen based on the resultant

agreement with several measured species including HCHO,

glyoxal, glycolaldehyde, and PAN (Fig. S3). Further support

of this is the good agreement between measured and model

IEPOX when ISOPOOH is constrained using this rate con-

stant (Fig. S4).

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J. Kaiser et al.: Speciation of OH reactivity above the canopy

9355

Figure 5.

Average measured and modeled diurnal profiles of isoprene,

-pinene, and several measured oxidation products. Error bars and

shaded area represent 1

standard deviation of diurnal variability. For each species, model results are not included for points where measure-

ments are missing.

In order for dilution alone to account for the low con-

centrations of first-generation oxidation products, extremely

high dilution rates would need to be incorporated. For

ISOPOOH, a constant rate of 40 day

−

, (roughly 5 times the

photochemical loss rate) would be needed. Most importantly,

when OVOCs are constrained, the assumed dilution scheme

has very little effect on the model OH reactivity (Fig. S2), as

measured species dominate total reactivity.

4 Discussion

While on average the model largely captures the absolute

value of OH reactivity at SOAS (Fig. 1), there are small but

significant differences (15 %) in the increase in total reac-

tivity and reactivity from isoprene alone (slope of Fig. 4).

While most measured species have uncertainties

15 %, it

is unlikely that all measured species are systematically low,

suggesting this discrepancy is likely the result of unmeasured

species. When given a constrained precursor, the model ei-

ther reproduces or overpredicts the resulting oxidation prod-

ucts (Figs. 5, S4). As isoprene and its oxidation products are

heavily constrained, we conclude that unmeasured primary

species co-emitted with isoprene (and those species’ oxida-

tion products) are the likely source of this small discrepancy.

As observed daytime isoprene concentrations increase

with temperature, the difference in slope also represents a

temperature-dependent daytime missing reactivity. The tem-

perature dependence observed at SOAS is greater than that

observed by DiCarlo et al. (2004) and the dependence of

monoterpene emissions, though it is important to note the

different range of temperatures included in each set of ob-

servations (Fig. 6). Emissions which depend both on tem-

perature and light are likely to have stronger net temperature

dependence, as temperature increases with increasing solar

radiation. Therefore, a portion of the total missing emissions

could likely be characterized by both a light and temperature

dependence.

Furthermore, the model is missing

∼

1 s

−

reactivity that

is temporally unrelated to the oxidation of isoprene and co-

emitted species (intercept of Fig. 4). This is consistent with

the diurnal variability of missing reactivity, with larger por-

tions occurring at night and in the early morning (Fig. 2).

Likely, missing nighttime reactivity is composed of a mix-

ture of unmeasured primary emissions, unmeasured oxida-

tion products, and long-lived unmeasured species mixed in

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Atmos. Chem. Phys., 16, 9349–9359, 2016

9356

J. Kaiser et al.: Speciation of OH reactivity above the canopy

Figure 6.

Daytime (10:00–16:00 LT) missing reactivity as a func-

tion of temperature and isoprene. Black squares represent 2

◦

aver-

ages and standard deviations. All daytime points are fit according to

the function

exp

(β(x

−

293

))

. The temperature dependence

observed at SOAS (

30) is greater than that observed by Di-

Carlo et al. (2004) and the dependence of monoterpene emissions

(

11).

from the residual layer. Xiong et al. (2015) show that 27 %

of the early morning increase in ISOPN results from down-

ward mixing from the residual layer during this campaign.

Similarly, there may be unmeasured OH reaction partners

stored in the nocturnal boundary layer that lead to an in-

crease in OH reactivity upon breakup of the inversion. Like

-pinene, anthropogenic VOCs such as toluene and benzene

are highest at night. However, these species were not unusu-

ally high during the 11–16 June period, which demonstrated

the highest missing reactivity, and therefore unmeasured an-

thropogenic VOCs are unlikely the major source of discrep-

ancy. Sesquiterpenes (C

)

are another class of VOC

which typically follow the emission patterns of monoter-

penes. The total sesquiterpene emission rate from broadleaf

trees is estimated to be

∼

67 % of the emission rate of to-

tal monoterpenes in terms of total mass (Sakulyanontvit-

taya et al., 2008). Assuming a reaction rate with OH of

caryophyllene,

∼

200 ppt of sesquiterpenes would provide

the 1 s

−

offset in reactivity temporally separated from iso-

prene.

Much like the previous work of Zannoni et al. (2016), we

find good daytime agreement between measured and mod-

eled reactivity above the forest canopy and that the majority

of reactivity can be attributed to primary emissions. Using

measurements of first- and later-generation OVOCs as a con-

straint on the amount of total unmeasured oxidation prod-

ucts, we find no evidence of substantial contributions of un-

measured OVOCs to above-canopy OH reactivity. This is in

contrast to studies of Edwards et al. (2013) and Hansen et

al. (2014), who showed that these species may contribute sig-

nificantly to OH reactivity directly above the forest canopy.

Varying amounts of intra-canopy oxidation are likely to re-

sult in these different conclusions, as secondary compounds

will quickly become more important than the primary iso-

prene emissions at higher altitudes or farther downwind of

the forest.

Based on measured OH concentrations, the measured con-

centrations of OVOCs suggest surprisingly little intra-canopy

oxidation of primary VOCs at this site. Furthermore, advec-

tion does not appear to bring in processed isoprene emis-

sions. Despite measuring

∼

10 m above the forest canopy

in a relatively homogeneous area, OH reactivity is primarily

composed of measured primary species. Our model overpre-

dicts concentrations of isoprene’s first-generation oxidation

products by at least a factor of 2. If these species and other

OVOCs were not constrained by measurements, these over-

predictions would lead to problematic conclusions about the

speciation of reactivity. In the relationship of reactivity from

isoprene to total reactivity, the modeled slope (1.22

0.02)

and measured slope (1.44

0.02) would show no discrep-

ancy. While the true observed missing contribution is small,

it highlights the contribution from primary species whose ox-

idation may be important downwind.

5 Conclusions

In summary, when VOCs and their oxidation products are

constrained to measured values, the discrepancies in the ab-

solute value of measured and modeled OH reactivity are

rarely significant at this site. Assuming that the RO

pro-

duction rate can be represented by the VOC portion of OH

reactivity (i.e., VOC

−

)

, this suggests that the

production rate from VOC oxidation is well captured by

both measured OH reactivity and measured OVOCs/VOCs.

Therefore, together with measurements of NO, both OH re-

activity measurements and speciated OVOC/VOC measure-

ments are well suited to characterize O

production rates at

this site.

Small but significant discrepancies in the observed and

calculated trend in OH reactivity with increasing isoprene

suggest missing sources of reactive carbon. The model fails

to capture a portion of reactivity that is temporally related

to isoprene, as well as a portion unrelated to local iso-

prene oxidation. As isoprene oxidation products are heav-

ily constrained and the model does not typically underesti-

mate OVOCs, we propose that missing primary emissions

and their oxidation products are likely candidates for both

sources of reactive carbon. While these missing emissions do

not lead to significant inconsistencies between measured and

modeled OH reactivity, at larger total emissions, the trend-

ing discrepancy may lead to larger missing fractions of OH

reactivity.

The speciation of this missing carbon source has air-

quality-relevant implications. For example, though monoter-

penes are much less abundant than isoprene, they can sub-

stantially effect SOA formation. Ayres et al. (2015) found

that organic nitrate aerosol from NO

monoterpenes is

a substantial contribution to observed particulate matter at

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www.atmos-chem-phys.net/16/9349/2016/

J. Kaiser et al.: Speciation of OH reactivity above the canopy

9357

this site, with an SOA molar yield of 23–44 %. In con-

trast, the comparable isoprene nitrate is primarily a gas-phase

product. Through positive matrix factorization analysis of

aerosol mass spectrometer measurements, Xu et al. (2015)

found that monoterpene

chemistry contributes 50 %

to total nighttime organic aerosol formation at this site,

whereas IEPOX-derived SOA constitutes 19–34 % total or-

ganic aerosol. Additionally, Su et al. (2016) cite aerosol up-

take and condensed-phase reactivity as a possible explana-

tion for the large discrepancy between observed and mod-

eled ISOPOOH at this site, which implies a large loss of

total carbon to the aerosol phase. While the magnitude of

OH reactivity is well captured, continued efforts in speciated

OVOC and VOC measurements are vital to fully understand

the SOA contribution from various primary emissions.

6 Data availability

The SOAS research data used in this publication are avail-

able at http://esrl.noaa.gov/csd/field.html (2013, Southeast

Nexus, SOAS Centreville Site).

The Supplement related to this article is available online

at doi:10.5194/acp-16-9349-2016-supplement.

Acknowledgements.

The authors would like to acknowledge

contribution from all members of the SOAS science team. Funding

was provided by US EPA “Science to Achieve Results (STAR)

program” Grant 83540601. A. H. Goldstein and P. K. Misztal

acknowledge support from EPA STAR Grant R835407. This

research has not been subjected to any EPA review and therefore

does not necessarily reflect the views of the Agency, and no official

endorsement should be inferred. Additional funding was provided

by NSF-grant AGS-1247421 and 1628530. J. Kaiser acknowledges

support from NASA Headquarters under the NASA Earth and

Space Science Fellowship Program – Grant NNX14AK97H.

Edited by: N. L. Ng

Reviewed by: two anonymous referees

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