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Agricultural and Forest Meteorology 173 (2013) 85– 99

Contents lists available at SciVerse ScienceDirect

Agricultural and Forest Meteorology

jou rn al h om epa g e: www.elsev ier .com/ locate /agr formet

artitioning ozone fluxes between canopy and forest floor by measurements and multi-layer model

. Launiainena,b,∗, G.G. Katulc,d, T. Grönholmb, T. Vesalab

Finnish Forest Research Institute, Joensuu Research Unit, Yliopistonkatu 6, FI-80101 Joensuu, FinlandDepartment of Physics, P.O. Box 48, FI-00014 University of Helsinki, FinlandNicholas School of the Environment, Duke University, Durham, NC, USADepartment of Civil and Environmental Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA

r t i c l e i n f o

rticle history:eceived 31 July 2012ccepted 21 December 2012

eywords:anopy turbulenceulti-layer modelon-stomatal ozone removalzone uptaketomatal ozone uptake

a b s t r a c t

Ozone uptake by plant leaves is essential to studies investigating atmospheric air pollution and plantinjury. A major challenge to these investigations is the up-scaling of leaf-level stomatal processes to theecosystem level, the accounting for forest floor ozone removal mechanics, and resolving the numerouspathways responsible for non-stomatal ozone removal within the canopy sublayer. To progress on the firsttwo and offer constraints on the third, the O3 fluxes above and within a boreal Scots pine forest in SouthernFinland are explored using a combination of two-level eddy covariance fluxes and detailed within-canopyconcentration profiles. The interpretation of the results is aided by a multi-layer canopy model (MLM),which couples radiation attenuation and turbulent transport within the canopy volume with leaf-level gasexchange, photosynthesis, and stomatal conductance. Validation of the MLM against measured turbulentCO2 and H2O fluxes within and above the canopy, as well as their concomitant mean concentration profilessuggest that the stomatal pathway is reasonably quantified via the proposed MLM approach. The resultsshow that the stomatal pathway alone can explain some 80% of the daytime dry-canopy ecosystem uptakeof O3. The non-stomatal O3 uptake is largest during nighttime and early morning hours when betweenone third and half of it seems to originate from below the overstory canopy. During daytime, almostall the non-stomatal uptake occurs in the sub-canopy region. Sub-canopy and/or understory processescontribute between 25–30% (nighttime) and 35–45% (daytime) ecosystem O3 uptake. In sub-canopy,the non-stomatal component exceeds the stomatal by a factor of 2–4 during daytime. Finally, the MLMwas used to study some of the potential non-stomatal pathways, including cuticular and soil uptake,

forest floor uptake and disequilibrium between photochemical O3 production and a first-order kineticchemical destruction mechanism. The results indicate that the likely location of the non-stomatal sinkis in the lower trunk-space close the forest floor but the soil surface uptake is insignificant. Accordingto the results, a bulk gas-phase disequilibrium between O3 production (assumed to vary linearly withlight at a given level inside the canopy) and destruction (assumed to vary exponentially with mean airtemperature) is a plausible explanation for non-stomatal O3 removal inside the canopy.

. Introduction

Rapid improvements in fast response O3 gas analyzers havenabled direct turbulent O3 flux measurements by the eddy-ovariance (EC) method permitting estimates of total O3 removalates by ecosystems. However, linking this ecosystem EC flux to

otential plant injury requires, at minimum, estimates of the O3

dose’ experienced by the plant (Ashmore, 2005; Bassin et al., 2007;ares et al., 2010; Ferretti et al., 2007; Keller et al., 2007; Massman,

∗ Corresponding author at: Finnish Forest Research Institute, Joensuu Researchnit, Yliopistonkatu 6, FI-80101 Joensuu, Finland. Tel.: +358 408015323.

E-mail address: samuli.launiainen@metla.fi (S. Launiainen).

168-1923/$ – see front matter © 2013 Elsevier B.V. All rights reserved.ttp://dx.doi.org/10.1016/j.agrformet.2012.12.009

© 2013 Elsevier B.V. All rights reserved.

2004; Massman et al., 2000; Matyssek et al., 2007; Musselmanand Massman, 1999; Musselman et al., 2006; Tuovinen et al.,2009). Even when ideal conditions for EC measurements prevail (i.e.stationary, planar-homogeneous flow with no subsidence), threemajor scientific challenges must be confronted before employingEC flux measurements above the canopy as surrogate for O3 plantuptake.

The first is attributed to forest floor and understory O3 fluxesthat can be significant when compared to ecosystem O3 fluxes, aspredicted by a number of models (Bassin et al., 2004; Finkelstein

et al., 2004; Lamaud et al., 2009; Massman, 2004; Zhang et al.,2002) and some field experiments (Dorsey et al., 2004; Lamaudet al., 2002; Meyers and Baldocchi, 1993; Zhu et al., 2008). Thesecond is connected to the possible vertical variations in mean O3

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6 S. Launiainen et al. / Agricultural a

oncentration within the canopy air space, with some field exper-ments recording it to be as large as 10–30 ppb within forests andrasslands (Fontan et al., 1992; Jaggi et al., 2006; Joss and Graber,996; Utiyama et al., 2004). Any interpretation of direct ecosys-em scale O3 flux employing a ‘bulk’ or ‘big-leaf’ representationannot a priori ignore these vertical gradients of mean O3 con-entrations (Lamaud et al., 2002, 2009; Massman, 2004; Wesely,989; Wesely and Hicks, 2000; Zhang et al., 2002). The third isonnected to what is conventionally termed as ‘non-stomatal’ O3emoval pathways shown to be significant in numerous stud-es and across many ecosystem types and account for 30–70% ofcosystem O3 uptake (Altimir et al., 2006, 2004; Cieslik, 2004,009; Coe et al., 1995; Fares et al., 2010; Fowler et al., 2001;erosa et al., 2009; Goldstein et al., 2004; Grantz et al., 1995,997; Hogg et al., 2007; Lamaud et al., 2002, 2009; Weselynd Hicks, 2000; Wolfe et al., 2011a,b). The non-stomatal O3ux has been attributed mainly to physical and chemical O3epletion at the plant and soil surfaces through thermal decom-osition (Cape et al., 2009), aqueous reactions in the liquid waterlms (Altimir et al., 2004, 2006; Fuentes et al., 1992, 1994) and

ight-stimulated reactions (Coe et al., 1995). Recent studies have,owever, suggested that the gas-phase reactions of O3 with reac-ive biogenic volatile organic compounds (BVOC) and nitrous oxideNO) may form an important non-stomatal O3 removal path-ay in plant canopies (Fares et al., 2010; Goldstein et al., 2004;urpius and Goldstein, 2003; Wolfe and Thornton, 2011; Wolfet al., 2011b).

To overcome the first two limitations and contribute to resolv-ng the last, a multi-layer modeling (MLM) instead of ‘big-leaf’pproach is employed here. MLM schemes combine canopy radi-tion and eco-physiological principles with turbulent transportepresentation and enable predictions and independent verifica-ion of the stomatal pathway by which carbon dioxide (CO2) andater vapor (H2O) and other scalars are exchanged between the

eaves and the atmosphere across various levels within the canopyolume (Baldocchi and Meyers, 1998; Juang et al., 2008; Lai et al.,002; Launiainen et al., 2011; Meyers and Baldocchi, 1988; Meyerst al., 1998; Siqueira et al., 2002, 2006). Several MLM schemesave also been proposed for dry-canopy O3 uptake, emphasizingither the turbulent transport process, accounted through higher-rder closure schemes (Baldocchi and Meyers, 1998; Meyers andaldocchi, 1988; Meyers et al., 1998), or the detailed pathwaysy which chemical production and destruction of O3 occurs (Gaot al., 1993; Wolfe and Thornton, 2011; Wolfe et al., 2011a,b). Theagnitude of stomatal conductance is among the most important

ariables needed to explain O3 uptake into plants for assessinghyto-toxic effects of elevated O3 (Buker et al., 2007; Massman,004; Vitale et al., 2005). Leaf-level equations that combine bio-hemical demand for CO2, and models of stomatal conductancend Fickian diffusion of CO2 and H2O across the leaf, can be readilyncorporated into MLM. Especially well suited are the analyti-al results for leaf-level photosynthesis and stomatal conductanceerived from optimization theories that assume stomatal aperture

s autonomously regulated to maximize carbon gain for a given lossf water vapor (Berninger and Hari, 1993; Hari et al., 1986; Katult al., 2010a,b, 2009; Konrad et al., 2008). Predictions from theseodels and their up-scaling to a canopy scale via MLM can be inde-

endently verified with mean H2O and CO2 concentration and fluxrofiles within the canopy, which are now becoming widely avail-ble across various biomes and climatic regimes through FluxNetBaldocchi et al., 2001). After this evaluation, the MLM scheme cane used to predict (i) the efficiency of the stomatal pathway by

hich O3 is up-taken at each level within the canopy and (ii) the

esulting mean O3 concentration profile within the canopy that is inquilibrium with this stomatal sink. Anomalies between measurednd MLM predicted turbulent O3 fluxes and mean O3 concentration

est Meteorology 173 (2013) 85– 99

profiles can then be used to ‘fingerprint’ potential non-stomatalsinks inside the canopy.

In addition, the partitioning of O3 removal by the canopy andforest floor is further explored using O3 fluxes measured by EC bothabove and below a Scots pine forest located at the SMEAR II stationin Finland during the summer of 2010. The flux measurementswere accompanied with detailed mean concentration profiles ofwater vapor, CO2, and O3. As a starting point, measured O3 fluxesare analyzed using a two-layer big-leaf framework. Then, the MLM(Launiainen et al., 2011) is used to derive an independent predictionfor the stomatally regulated O3 fluxes and mean O3 concentrationprofiles within the canopy. The MML is also shown to reproducethe turbulent H2O and CO2 fluxes and their mean concentrationprofiles (including near the forest floor) thereby providing confi-dence in the multi-layer estimates of the O3 stomatal uptake andthe turbulent flow field responsible for the shape of the O3 meanconcentration profile. Based on these two independent measuresof the O3 uptake, the partitioning of O3 fluxes between the forestfloor and the canopy and the relative importance of stomatal andnon-stomatal components are discussed.

2. Materials and methods

2.1. The site

The experimental campaign was conducted at the SMEAR IIstation located in southern Finland (61◦51′N, 24◦17′E, 181 m abovesea level) during the summer of 2010. The site is a relativelyhomogenous Scots pine stand sown in 1962. In 2010, the forestwas characterized by the following attributes: a total leaf areaindex (LAI) of about 6.5 m2 m−2, a stand density of 1400 trees ha−1,a mean canopy height (h) of 15–16 m, and a mean diameter atbreast height of 0.16 m. The forest floor vegetation forms a con-tinuous cover over the soil surface. It consists of a shallow dwarfshrub layer (mean height is 0.2–0.3 m, LAI ∼ 0.5 m2 m−2) dominatedby lingonberry (Vaccinium vitis-idaea), blueberry (Vaccinium myr-tillus), and a dense moss layer underneath (LAI ∼ 1 m2 m−2) (Kolariet al., 2006; Kulmala et al., 2008).

2.2. Measurements

2.2.1. Mean concentration profilesThe mean concentration profiles and turbulent fluxes of CO2,

H2O and O3 within and above the forest were recorded during a fieldcampaign conducted in the summer of 2010 (July 1st–August 4th).The concentrations were measured at six heights at the scaffoldtower where the above-canopy EC setup was positioned. The high-est measurement height (16.8 m) was just above the treetops, threelayers were within the canopy foliage (14.3, 11.8, 9.8 m), one imme-diately below the crown (6.3 m) and the lowest at 0.5 m height,immediately above the understory vegetation. For each height, thesampling lines (PTFE Teflon, 12/10 mm diameter) were equally long(22 m), heated to minimize condensation and covered by plas-tic foam to eliminate potential chemical light reactions. Stainlesssteel filters (Swagelok pleated mesh element, pore size 7 �m) wereattached to the inlets to protect the sampling lines. All samplinglines were connected to a gas multiplexer from which a short 2.5 msample line (PTFE Teflon, 6/4 mm diameter) was attached to thegas analyzers. The air flow through the tubes was kept continu-ous; the bypass flow was ca 1.4 l min−1 and the sample flow was2.8 l min−1. The mean CO2 and H2O concentrations were measured

by a closed-path infra-red gas analyzer (LI-7000, Licor Inc., Lin-coln, NE, USA) at 1 Hz. The flow rate through the analyzer wasset to 2.0 l min−1. The mean O3 concentration was measured by aUV absorption gas analyzer (API-400E, Teledyne Technologies Inc.,

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S. Launiainen et al. / Agricultural a

an Diego, CA, USA). The response time (95%) of this analyzer isnder 20 s, and the lowest detectable limit is 0.6 ppb (RMS) accord-

ng to the manufacturer. The flow rate through the analyzer was.8 l min−1, controlled by a critical flow orifice. The API-400E wasperated at concentration range from 0 to 100 ppb and dwell timeetween reference and sample measurements was set to 2 s. Noime averaging of the concentration signal was performed by thenalyzer. The analog O3 concentration signal was introduced to theAC inputs of LI-7000 for synchronization and sampled by the com-uter controlling the multiplexer. Concentration at each height waseasured for 60 s providing a rotation cycle of 6 min. To eliminate

apid pressure changes that may disturb the O3 analyzer perfor-ance, the sampling line was opened 1 s before switching from

ypass flow. The first 8 s after and 8 s before a change in measure-ent level were discarded and 1 h averaged concentrations (mean

nd standard deviation) at each height were calculated to be usedn further analysis.

At SMEAR II, mean profiles of O3, CO2, and H2O concentrations,ind speed, air temperature (Ta) and relative humidity (RH) are

ontinuously measured at 4.2, 8.4, 16.8, 33.6, 67 m at a 72 m tallower (Hari and Kulmala, 2005; Rannik et al., 2004). This mainower is located ca. 35 m west from the scaffold tower wherehe detailed within-canopy O3 measurements were made. Above-anopy measurements from the SMEAR II tower were used as upperoundary conditions for the MLM calculations and when derivingulk canopy conductance.

.2.2. Turbulent fluxesFrom 1st June to 31st August 2010, the turbulent fluxes of

3, H2O and CO2 were measured simultaneously both above theanopy (22 m above the forest floor) and in trunk-space (3.5 mbove the forest floor) using the EC method, with all variables sam-led at 10 Hz. In essence, the two-level EC system here permitseparating the understory and forest floor contributions from theurbulent mass exchange of the entire ecosystem. The above canopyC measurements were made at the top of a scaffold tower using

setup consisting on an acoustic anemometer (Solent Research HS199, Gill Ltd., Lymington, Hampshire, England) to detect the windpeed fluctuations, a closed-path infra-red gas analyzer (LI-6262,icor Inc., Lincoln, NE, USA) to measure CO2 and H2O concen-rations and a chemiluminescence gas analyzer (LOZ-3 Ozonenalyzer, Unisearch Associates Inc., Concord, Ontario, Canada) toeasure O3 concentration. The O3 and CO2/H2O analyzers had

common sampling line (length 12 m, diameter 10/8 mm, PTFEeflon), which was heated to avoid condensation. A coarse filterith a mesh size range 5–10 �m was placed at the inlet to pro-

ect the sampling line from insects and coarse particulate matter.he total flow rate in the sampling line was 13.5 l min−1 of which.0 l min−1 and 7.0 l min−1 were then drawn through the LOZ-

and LI-6262 analyzers, respectively. The above-canopy O3 fluxeasurements and their post-processing are described elsewhere

Keronen et al., 2003). The trunk-space fluxes were measured atbout 20 m south-west from the main scaffold tower. The setuponsists of a Metek USA-1 acoustic anemometer (Metek GmbH,ermany) and a closed-path gas analyzer (LI-7000, Licor Inc., Lin-oln, NE, USA) for CO2/H2O concentrations. The sampling line wastainless steel (length 4.5 m, 3.6 mm inner diameter), flow rate6 l min−1 and heated to avoid condensation. The O3 concentrationas measured using a fast chemiluminescence analyzer (FOS, Sex-

ant Technology Ltd., Wellington, NZ). The air sample was drawnelow the anemometer through the sampling line (length 4 m,/4 mm diameter PTFE-Teflon) at flow rate 2.0 l min−1 to the ana-

yzer. A stainless steel filter with pore size 15 �m was also placed athe inlet to protect the sampling line. Reactant chemical (coumarin,H-chromen-2-one) target was replaced approximately every sec-nd week. The devise operated in AGC (automatic gain control)

est Meteorology 173 (2013) 85– 99 87

mode in which it automatically amplifies the digital signal basedon the measured voltage, which beyond the actual concentrationdepends on the state of the reactant chemical. The O3 concen-tration was measured at 10 Hz as the velocity components andCO2/H2O concentrations and all instruments were sampled by thesame computer for signal synchronization. Details on the trunk-space EC measurements of CO2 and H2O and their post-processingare provided elsewhere (Launiainen et al., 2005).

Turbulent fluxes were calculated according to conventionalmethods using a ½ h averaging time interval and using sign conven-tion where negative flux means downward transport (Aubinet et al.,2000). Time lags between scalar fluctuations and vertical velocitywere accounted for using the maximum cross-correlation method.Prior to the calculations, a 2D co-ordinate rotation was applied fortrunk-space and a 3D rotation for above-canopy wind velocity data.Previous analyses at the site have indicated that there are no sys-tematic differences in sub-canopy scalar fluxs between 2D or 3Drotations. The sensitivity (span) of fast chemiluminescence O3 ana-lyzers tends to vary with the state of reactant chemicals as wellas variations Ta and RH (Keronen et al., 2003; Muller et al., 2010).Therefore, each of the raw ½ h fluxes (FO3,raw) were corrected basedon the ratio between the mean ½ h O3 concentration measured bythe fast-response analyzer (Cm) and a reference concentration (Cref)measured by a slow response (but stable) O3 gas analyzer used inthe profile measurements. Hence, the final O3 fluxes (FO3 ) are givenas

FO3 = Cref

CmFO3,raw (1)

No co-spectral corrections of the high-frequency attenuationwere employed given its uncertainty for the trunk-space fluxes(Launiainen et al., 2005). Moreover, according to a previous study(Keronen et al., 2003), the co-spectral correction in unstable atmo-spheric conditions is less than 10% when wind speed at 22 m heightis below 4 m s−1. During the study period, the day-time medianwind speed at 22 m was ca. 1.8 m s−1 and 95% of the cases werebelow 3.5 m s−1. For this median wind speed, the magnitude of thehigh-frequency attenuation is less than 5%. According to anotherstudy at this site, the relative underestimation or CO2 and H2Ofluxes due to high-frequency attenuation is similar both above andbelow the canopy (Launiainen et al., 2005).

2.3. Analysis of flux measurements

The bulk ecosystem (GO3 , cm s−1) and forest floor (GO3,s) con-ductance for O3 were derived as a ratio of the flux and the drivingforce (concentration difference) assuming that leaf intercellular O3concentration is negligible (Laisk et al., 1989). Hence,

GO3 = − FO3

CO3

. (2)

Estimation of the ‘big-leaf’ stomatal conductance (Gst, cm s−1),which represents the stomatally regulated component of GO3 , wascarried out in two ways: The first assumes that the canopy is ‘well-coupled’ to the atmosphere (i.e. bulk canopy foliage temperatureTc ≈ Ta) so that the vapor pressure deficit (D) approximates the driv-ing force for transpiration. In this case, Gst was derived by invertinga version of the Penman–Monteith equation (Blanken and Black,2004) given as:

Gst = 0.66ga

[(εH − 1

)+ �cpD�

]−1

, (3)

Fw Fw

where H (W m−2) is the measured sensible and Fw (W m−2)the latent heat flux, ga = U/u2∗ (m s−1) the aerodynamic con-ductance, ε = s/� where s is the slope of saturation vapor

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8 S. Launiainen et al. / Agricultural a

ressure–temperature curve (Pa K−1) and � the psychometric con-tant (Pa K−1), � is the mean air density (kg m−3), cp the heatapacity of the air in constant pressure (J kg−1 K−1), 0.66 accountsor the different molecular diffusivities of O3 and H2O and D is innits of Pa. The second approach assumes the canopy is not entirelyell-coupled to the atmosphere and Gst∗ is

st∗ = 0.66Fw

es(Tc) − ea, (4)

ecessitating an estimate of the saturation vapor pressure es(Tc)t Tc. Since Tc was not directly measured in this experiment,t was inferred from measured upwelling long-wave radiations discussed in Appendix A. Roughly, the long-wave radiationeasurements suggest that the difference between skin and air

emperature measured near the canopy top, Tc − Ta(h), are below K during most of the daytime conditions. However, a small frac-ion of ½ h periods did experience differences up to 3 K.

For whole-ecosystem conductances, the driving forces wereetermined by linearly interpolating the concentrations at 16.8 mnd 33.6 m height to 22 m while the measured values at 4.2 meight were used for estimating forest floor conductances. Earliertudies at this site have shown that vertical advection of O3 cane significant in weakly turbulent conditions (Rannik et al., 2009).herefore, only measurements when the above-canopy frictionelocity (u*) exceeds 0.25 m s−1 were considered. Further separa-ion between dry- and wet canopy conditions was employed usingelative humidity (RH) threshold of 90% and checking that no rainccurred in the preceding 12 h period. Prior to computing con-uctance, the canopy surface wetness sensor was also checked tonsure no indication of dew. In total 65% of FO3 pass these criteria,hich simultaneously restrict the Gst to be representative of dry-

anopy ‘big-leaf’ stomatal conductance. The flux measurementsnd MLM results are analyzed in an ensemble sense and eitheredian and 25th and 75th percentiles (in case of big-leaf analysis)

r mean ± std (in case of MLM results and concentration profile)re used as measures of typical behavior and variability. Whenatios between forest floor and whole-stand values are considered,he ensemble averaging is performed using each 30-min computedatio.

.4. The multi-layer model (MLM) for O3 budget

To explore the interplay between vertical variations in theanopy microenvironment, photosynthesis, stomatal conductancend their impacts on stomatal O3 uptake, the MLM developed byauniainen et al. (2011) was extended to include an O3 budgetquation. Only the basic equations pertinent to O3 removal areresented here while the MLM equations not directly connectedo the O3 budget, such as the radiative transfer scheme and deriva-ion of the coupled photosynthesis – stomatal conductance modelre presented in Launiainen et al. (2011).

For a stationary, planar homogeneous flow in the absence of sub-idence and upon ignoring molecular diffusion relative to turbulentransport, the one-dimensional mean O3 continuity equation insidehe canopy reduces to

∂w′c′

∂z= Sc = Sst + Sns, (5)

here w′c′ is the vertical turbulent flux of O3. Overbar representsime and planar averaging (Finnigan, 2000; Raupach and Shaw,982), primed quantities represent excursions from space–timeverages, Sc is the mean destruction or removal of O3 due to

tomatal (Sst) and non-stomatal (Sns) mechanisms, and z is theeight from the forest floor surface. Hereafter, time-averaging

s applied over a period of ½ h and defines a single model run,hile ensemble-averaging is later applied over a collection of runs

est Meteorology 173 (2013) 85– 99

subjected to similar meteorological conditions and canopy state(e.g. dry canopy). Such ensemble averaging better approximatesthe space–time averaging employed in the conservation equationsthan the time averaging alone across an individual run (Katul et al.,2004a).

The simplest link between w′c′ and mean O3 concentration isvia first-order closure principles resulting in

w′c′(z) = −Kt(z)∂C(z)

∂z, (6)

where Kt is the turbulent diffusivity for O3, and C is the mean atmo-spheric O3 concentration. Invoking first-order closure principles formomentum transfer and using a mixing length hypothesis leads toan estimate of Kt given by

Kt(z) =(

1SN(z)

)(l(z))2

∣∣∣∣∂U(z)∂z

∣∣∣∣ , (7)

where SN is the turbulent Schmidt number defined as the ratio ofmomentum to scalar turbulent diffusivities and need not be unity,U is the mean horizontal velocity, and l is the effective mixinglength (see Appendix B). For simplicity, it is further assumed herethat SN ≈ 1 and some experimental evidence for this approximationabove the canopy is provided in Appendix B.

Because the intercellular O3 concentration is negligible rela-tive to the ambient (Laisk et al., 1989), the stomatal uptake canbe approximated as

Sst(z) ≈ −a(z)geff (z)C(z), (8)

where a(z) is the local leaf area density, and geff is defined as

geff = gst∗ gbl

gst∗ + gbl. (9)

Here, gbl is the leaf boundary-layer conductance, which varieswith U within the canopy and a characteristic leaf dimension asdiscussed in Appendix B. The gst* = gst + go is the effective stoma-tal conductance including stomatal conductance (gst), which isassumed to be autonomously regulated by the guard cells and resid-ual conductance (go). In typical dry-canopy daytime conditions,gst usually determines the outcome of Eq. (9) as shown elsewhere(Siqueira and Katul, 2010).

The gst model is based on stomatal optimization theories and theeconomics of leaf-gas exchange coupled together with a Farquhar-type photosynthesis model (Farquhar et al., 1980). These theoriesassume that the stomatal aperture is regulated so as to maximizecarbon gain at a given water vapor loss rate for a given set ofmicro-climatic conditions. For a linearlized biochemical demandfunction approximating the Farquhar photosynthesis model, thegst (Launiainen et al., 2011) is

gst = a1

a2 + sca

(−1 +

√ca − cp

ac�D

), (10)

where ac = 1.6 is the relative molecular diffusivity of water vaporwith respect to carbon dioxide, ca is the ambient CO2 con-centration, cp the CO2 compensation point and D the vaporpressure deficit between the leaf and the air. The a1 and a2are parameters of the photosynthesis model, selected depend-ing on whether the photosynthetic rate is restricted by electrontransport (light) or Ribulose bisphosphate carboxylase. Underlight-saturated conditions, a1 = Vc,max (maximum carboxylationcapacity) and a2 = Kc(1 + Coa/Ko), where Kc and Ko are the Michaelisconstants for CO2 fixation and oxygen inhibition and Coa is the oxy-

gen concentration in air. When light is limiting, as is the case formuch of the canopy layer, a1 = ˛pemQp and a2 = 2cp, where ˛p isthe leaf absorptivity of Qp, em is the quantum efficiency of leaves,and cp is the CO2 compensation point. Besides the photosynthetic

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arameters, the only parameters that require specification are �the marginal water use efficiency), and s, a constant that reflectshe long-term average ratio of the leaf intercellular and ambienttmospheric CO2 concentrations.

.4.1. The non-stomatal O3 sinkThe non-stomatal O3 removal in plant canopies has resisted

omplete theoretical treatment despite numerous studies suggest-ng different underlying mechanisms. The processes responsible forns are broadly connected to physical and chemical depletion of O3olecules on wet leaf (or litter) surfaces (Altimir et al., 2004, 2006;

uentes et al., 1992, 1994; Lamaud et al., 2002, 2009; Pleijel et al.,995) and to gas-phase reactions leading to chemical productionnd destruction of O3 (Fares et al., 2010; Goldstein et al., 2004;urpius and Goldstein, 2003; Utiyama et al., 2004). In dry-canopyaytime conditions, the latter have been suggested to dominatever surface processes (Wolfe and Thornton, 2011; Wolfe et al.,011b). The enhanced chemical destruction of O3 is likely to beelated to reactive BVOCs emitted from vegetation, supported fornstance by direct field measurements following a thinning of aoniferous forest (Goldstein et al., 2004). On the other hand, theresence of BVOCs have also been linked to increasing O3 produc-ion in upper canopy layers (Utiyama et al., 2004).

Based on the literature, three hypotheses for the non-stomatalink in dry-canopy conditions are explored via the MLM. The firstepresents the leaf and soil surfaces as additional sinks so that

ns,sur(z) = −gcut∗(z)a(z)C(z)︸ ︷︷ ︸leaf surface

− gsC(z1)︸ ︷︷ ︸soil

, (11)

here gcut* is the effective leaf (cuticular) surface conductance, gs

he soil conductance and C(z1) the concentration in the turbulentegime just above the ground surface. The gcut* and gs are defined asMeyers and Baldocchi, 1988; Baldocchi, 1988; Zhang et al., 2003)

cut∗ = gcutgbl

gcut + gbl

s = 1rsoil + rbs

. (12)

ere, gcut = 1/rcut is leaf cuticular conductance, rsoil the soil sur-ace resistance and rbs the soil boundary layer resistance given asBaldocchi, 1988; Nemitz et al., 2000):

bs = Sc − ln(ıo/z1)ku∗gz1

, (13)

here Sc is the Schmidt number for O3, k the von Kárman con-tant (∼0.41), u*g the near-ground friction velocity determined hererom the modeled shear stress within the canopy, ıo = DO3 /ku∗g theeight above ground at which molecular and turbulent transportqual, DO3 the molecular diffusivity of O3 in air and z1 the heightelow which the wind profile is assumed logarithmic.

The second is a non-stomatal sink in the understory and lowerrunk space given as

ns1(z) = −gns,1(z)C(z), (14)

here gns,1 is additional sink representing enhanced uptake of O3t and immediately above (below 1 m depth) the understory layer.he third is an imbalance between 1st order kinetic sink and pho-ochemical production of O3, which in the most reduced form, isiven by

ns,2(z) = − ksC(z)︸ ︷︷ ︸First−orderkinetic sink

+ kpQp(z)︸ ︷︷ ︸photo−chemical

production

, (15)

est Meteorology 173 (2013) 85– 99 89

where ks and kp describe the strengths of first-order kinetic sink,and the photochemical O3 production terms, respectively. It isassumed that ks is constant with depth but varies with Ta as ks =ks,10Q (Ta−10)/10

10 where Q10 is a priori set to 3 based on the chemi-cal O3 sink data from a coniferous forest in Kurpius and Goldstein(2003). The photochemical production of O3 is assumed to be a lin-ear function of shortwave radiation (here photosynthetically activeradiation, Qp) as in Utiyama et al. (2004). The values of gcut, gns,1, ks,10and kp were determined as an ‘inverse’ problem so that the mea-sured and modeled ecosystem scale O3 uptake equal in an ensemblesense.

2.4.2. Boundary conditions, parameterization and numericalimplementation

The MLM solves the (i) mean concentration profiles of CO2,H2O and O3, (ii) flux profiles of CO2, H2O, and O3 as well as theirconcomitant sources and sinks. The lower boundary conditionsimposed on MLM are flux-based. For CO2, the lower boundarycondition is the soil respiration rate directly measured by soil cham-bers (Pumpanen et al., 2001). For H2O, the soil and moss layerevaporation (lumped together) was assumed to occur at the equi-librium rate driven by radiation at the lowest grid point beneaththe understory, which was further decreased linearly whenevermeasured humus water content was below saturation. For O3 theflux at the soil surface is either assumed zero or modeled accord-ing to Eqs. (12) and (13). The upper boundary conditions are allbased on time series of reference mean concentrations (or meanvelocity) measured above the canopy at z/h = 1.55. These vari-ables include the ½ h time series of friction velocity u* (m s−1),ambient CO2 mixing ratio (ppm), O3 mixing ratio (Cref, ppm), atmo-spheric pressure (kPa), Ta (◦C), RH (%) and direct and diffuse Qp

(�mol m−2 s−1). During the model runs, Ta and ambient RH (and D)were assumed to be vertically uniform within the canopy therebyeliminating the need for modeling the leaf energy balance. Fromthe measured mean Ta and H2O concentration profiles, the verti-cal variability in D is about 0.05 kPa and hence does not exceed5% in typical conditions within the stand. The values of physio-logical parameters regulating shoot-scale photosynthesis (Table 1)were initially inferred from automatic shoot chamber measure-ments made in 2006 or derived from literature and presented indetail by Launiainen et al. (2011). To achieve an optimal fit betweenMLM-modeled and measured ecosystem Fw and CO2 flux (Fc) overthe period of the this study, these initial values were adjusted asfollows: Vc,max was increased and em decreased by 20% and � wasset to 1.65 × 10−3 mol(CO2) mol(H2O)−1 and s to 0.8. Regarding thephotosynthetic parameters, the adjustments are within the vari-ability range of individual needles and shoots at the site. The � valuecorresponds to the middle range of � measured in Launiainen et al.(2011) during well-watered conditions for the same site.

The MLM results were calculated as follows: The computationaldomain was first divided into 311 horizontally homogenous layers,of which 200 were below the treetops, and the radiation envi-ronment at each layer was solved. Second, initial estimations forthe combined assimilation – stomatal conductance – transpirationwere computed separately for sunlit and shaded leaves at eachlayer, assuming a vertically uniform ca and D with values set tothe measured ones above the canopy for each ½ h period. Then,the turbulent closure scheme was applied and the ca profile fol-lowing from the sink/source distribution was calculated and usedto refine estimates of assimilation, gst and transpiration iteratively.The iterations were continued until the maximum absolute differ-ence between two successive iterations was within 0.1% for all the

state variables and across all the layers of the canopy. Finally, the O3concentration profiles were solved based on Sst and the three dif-ferent formulations for Sns (Eqs. (11), (14) and (15)). The MLM wasapplied for a period commencing at 1st July to 4th August 2010 to

90 S. Launiainen et al. / Agricultural and Forest Meteorology 173 (2013) 85– 99

Table 1Parameters of leaf-scale photosynthesis and stomatal conductance model (Launiainen et al., 2011). All values are given per projected leaf area.

Abbreviation Variable Value Units

Vc,max25 Maximum carboxylation capacity at 25 ◦C 46 (pine)31 (understory)

�mol m−2 (leaf) s−1

� = ˛pem Quantum efficiency defined on incident light 0.035 (pine)0.055 (understory)

mol (CO2) mol (PAR)−1

rd25 Dark respiration at 25 ◦C rd,25 = 0.015Vc,max,25 �mol m−2(leaf) s−1

Kc Michaelis–Menten constant for CO2 fixation 460 ppmKo Michaelis–Menten constant for oxygen inhibition 330 000 ppmCoa Oxygen concentration in air 210 000 ppmcp CO2 compensation point cp = Coa[2 × 2.6 exp(− 0.056(T − T0))]−1 ppmgo Residual conductance for CO2 (Eq. (11)) 0.001 mol m−2(leaf) s−1

ambie

eao

3

stoflttctaa7

FS

� Marginal water use efficiency (cost parameter)

s Parameter resembling long-term mean ratio of internal to

ac Ratio of molecular diffusion coefficient of H2O to CO2

xplore the O3 removal by stomatal and non-stomatal pathwayslong with their signatures in the O3 mean concentration profilesn ensemble sense.

. Results and discussion

The section is organized as follows: First, the two-layer EC mea-urements are analyzed to provide a ‘big-leaf’ representation ofhe ecosystem and forest floor O3 uptake. Then, the comparisonf measured and modeled CO2 and H2O concentration profiles anduxes are shown to evaluate the MLM description of Sst. Finally,he relative importance of forest floor/understory O3 uptake andhe magnitude and possible location of Sns in dry-canopy daytimeonditions are discussed. During the field campaign, the mean air

emperature was 20.1 ◦C with typical diurnal amplitude of 10 ◦Cnd daytime maximum Qp ∼ 1300–1400 �mol m−2 s−1. The meanmbient O3 concentration above the canopy varied between 27 and0 ppb with diurnal amplitudes as large as 30 ppb (Fig. 1).

190 200 2100

500

1000

1500

PA

R (μ

mo

lm−2

s−1)

a)

Doy

190 200 2100

50

100

RH

(%

)

b)

Doy

190 200 2100

25

50

75

O3 (

pp

b)

Doy

c)

190 200 210

0.5

1

1.5

GO

3 (cm

s−1

)

Doy

d)

ig. 1. Time series of measured meteorological conditions, mean O3 concentration and tcots pine forest in summer 2010. (For interpretation of the references to color in this fig

0.0018 mol (CO2) mol (H2O)−1

nt CO2 mixing ratio 0.8 Dimensionless1.6 Dimensionless

3.1. Analysis of O3 deposition and its partitioning based on ECdata

The availability of two-level EC flux measurements for O3 andH2O permitted the evaluation and comparisons of GO3 and its stom-atally regulated component Gst both for the entire ecosystem andfor the understory and forest floor (lumped together). The ecosys-tem and forest floor ‘big-leaf’ O3 conductance GO3 exhibited a cleardiurnal cycle. The largest GO3 occurred in daytime conditions andranged between 0.5–1.0 cm s−1 (ecosystem) and 0.2–0.3 cm s−1

(forest floor) as shown in Fig. 1d. Fig. 2 presents the relationbetween measured GO3 and its stomatally regulated componentfor the whole ecosystem and forest floor in daytime dry-canopyconditions. Apart the variability, the measured ecosystem GO3 is

larger than would be predicted by Gst derived from measured watervapor flux. At the whole-ecosystem-scale, the results are in reason-able agreement with the long-term canopy and shoot-level datafrom the SMEAR II site (Altimir et al., 2006). Their data indicates

220 230 240

220 230 2400

20

40T

a (° C

)

220 230 240

220 230 240

he measured conductances (GO3 ) above (black) and in the sub-canopy (red) of theure legend, the reader is referred to the web version of the article.)

S. Launiainen et al. / Agricultural and Forest Meteorology 173 (2013) 85– 99 91

0 0. 5 1 1. 50

0.5

1

1.51:1a)

Ecosystem

GO

3 (cm

s−1

)

Gst (cm s−1)

0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 60

0.1

0.2

0.3

0.4

0.5

GO

3,s (

cm s

−1)

Gst,s

(cm s−1)

1:1b)

Understory and Forest Floor

Fig. 2. Comparison between measured big-leaf O3 conductance (GO3 ) and their ‘stomatally regulated’ component (Gst) derived from water vapor flux measurements indry-canopy daytime (08 AM–18 PM) conditions. (a) Ecosystem scale GO3 : the grey dots represent case when the canopy is assumed well-coupled to the atmosphere and theb ion eqf 65. No

twopat

m8odrtniasts3climin

(0l

lack circles the case when the “well-coupled” assumption is relaxed. Linear regressorest floor conductance GO3,s: linear regression equation is y = 0.08 + 0.887x, R2 = 0.

hat dry-canopy daytime GO3 scales approximately one-to-oneith Gst but has an intercept on the order of 5–15% of the maximum

bserved GO3 . In the sub-canopy, GO3,s exceeds the stomatal com-onent Gst,s and the shape of GO3,s–Gst – relation is non-linear. Anlmost identical relation was derived from EC measurements abovehe forest floor of a Maritime pine forest (Lamaud et al., 2002).

The ensemble-averaged diel cycles of both GO3 and Gst are asym-etric in time with the largest ecosystem GO3 occurring between

and 12 AM (Fig. 3a). The forest floor GO3,s peak is narrower andccurs earlier, between 8 and 10 AM. At both levels, the O3 con-uctance decreases in the early afternoon and evening, closelyesembling that of Gst inferred from Fw measurements (Fig. 3a). Athe forest floor, the diurnal cycle of GO3,s follows closely the diur-al cycle of Gst,s but is constantly larger even though here the Gst,s

s likely to be overestimated due to non-stomatal H2O sources suchs evaporation from the extensive moss layer and the underlyingoil. This finding is independent of whether Tc or Ta is employed inhe calculation of the driving force for forest floor evaporation (nothown). Based on the sub-canopy EC-data, it appears that below the.5 m height, the non-stomatal component (GO3,s − Gst,s) is ratheronstant, around 0.05 cm s−1 for most part of the day. A slightlyarger non-stomatal uptake (∼0.1 cm s−1) occurs in the early morn-ng. On relative terms, the non-stomatal components account at

inimum for 20–25% of forest floor (between 8 and 12 AM) whilets contribution is more than 50% in early morning and late after-oon.

At the ecosystem level, the daytime non-stomatal O3 uptakeGO3 − Gst) is largest, 30–50% of total GO3 (in absolute terms.15–0.2 cm s−1), in the morning. Non-stomatal uptake contributes

ess than 10% (∼0.05 cm s−1) in midday but increases again in the

uations are y = 0.21 + 0.62x, R2 = 0.26 and y = 0.19 + 0.74x, R2 = 0.20, respectively; (b)te the scale difference between the two panels.

late afternoon to 10–25% (∼0.1 cm s−1). The determination of thenon-stomatal contribution to ecosystem GO3 is, however, sensi-tive to the way the Gst is estimated since the two estimates differby ∼10% in morning and midday conditions. In turbulent condi-tions (u* > 0.2 m s−1), the nighttime (non-stomatal) ecosystem GO3was on average 0.15 cm s−1 and approximately one third of thatvalue can be attributed to processes occurring below 3.5 m height(Figs. 2 and 3). In daytime, however, the majority (if not all) non-stomatal uptake seems to occur in the sub-canopy layer.

The O3 deposition in the sub-canopy accounts for between25 and 45% of ecosystem O3 sink (Figs. 3b and 4). The sub-canopy/forest floor contribution is largest in the early morning(∼45%) but decreases in the afternoon in a manner resembling theratio of water fluxes (Fig. 3b). The different shapes of the diurnalcycles of ecosystem versus sub-canopy GO3 are thus responsiblefor some of the variation and non-linearity in the relation seen inFig. 4. The forest floor (or sub-canopy) contribution to O3 uptake ishigher than for other scalars at the SMEAR II site, where between15 and 30% of Fw, some 10% of sensible heat flux (Launiainen, 2010;Launiainen et al., 2005) and around 25% of aerosol particle drydeposition (Grönholm et al., 2009; Katul et al., 2010a,b) have beenfound to occur from/to the forest floor. The forest floor contribu-tion of O3 deposition here is comparable to Lamaud et al. (2002),who found that understory and forest floor GO3,s was 25% of night-time and 55% of daytime ecosystem GO3 in a Maritime pine stand.To the contrary, Meyers and Baldocchi (1993) measured an order

of magnitude lower GO3,s (0.3–0.4 mm s−1) above a deciduous for-est floor. Fuentes et al. (1992) report that O3 fluxes measured at10 m below treetops in a deciduous forest account for some 10%of ecosystem flux and slightly smaller forest floor contributions

92 S. Launiainen et al. / Agricultural and Forest Meteorology 173 (2013) 85– 99

0 4 8 12 16 20 240

0.1

0.2

0.3

0.4

0.5

time (h)

G (

cm s

−1 )

a)G

O3

GO3,s

Gst

Gst,s

Gst*

0 4 8 12 16 20 240

10

20

30

40

50

60

70

80

90

100

time (h)

un

der

sto

ry &

fo

rest

flo

or

con

trib

uti

on

(%

)

b)F

O3

Fw

Fig. 3. (a) Ensemble averaged (median) diurnal cycles of measured O3 conductances above (GO3 ) and in the sub-canopy (GO3,s). Also shown are estimates of their stomatallyregulated components, derived from measured water flux (Fw) when the well-coupled assumption is used (Gst) and relaxed (Gst*); b) contribution of understory and forestfloor to ecosystem scale O3 uptake (FO3 ) and Fw . The dashed lines are 25th/75th percentiles. The figure shows dry-canopy conditions when u* > 0.25 m s−1. Gst is derived onlyfor conditions when Fw exceeds 10 W m−2 at the ecosystem scale and 5 W m−2 at the sub-canopy.

0 0. 2 0. 4 0. 6 0. 8 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

GO3 (cm s−1 )

GO

3,s (

cm s

−1)

1:1daynight

Fig. 4. The relation between ½ h sub-canopy (GO3,s) and ecosystem (GO3 ) O3 conductance including both dry and wet conditions. Low radiation nighttime and morning/eveningcases (Qp <50 �mol m-2 s-1) are shown separately. The red line shows Gst,s (median and 25th/75th percentiles) in evenly spaced ecosystem GO3 -bins. The linear regressionequation is y = 0.04 + 0.23x, R2 = 0.15.

nd For

hec(∼omapo

3

uvcfltopoeaCmtFssva

Ft

S. Launiainen et al. / Agricultural a

ave been measured for a Douglas-fir (Dorsey et al., 2004; Duyzert al., 2004) and for a spruce forest (Zhu et al., 2008). The high sub-anopy O3 deposition found for the relatively sparse pine standsone-sided overstory LAI ∼ 2.1 m2 m−2 in Lamaud et al. (2002) and3 m2 m−2 at our site) compared to more closed-canopied decidu-us and spruce/fir forests could be due to more efficient turbulentixing within open-canopied forests. Part of the differences may

lso be attributed to different physiological characteristics such ashotosynthetic capacity and stomatal regulation strategies of theverstory and their impacts on stomatal O3 uptake.

.2. Analysis of O3 deposition and its partitioning by the MLM

While EC measurements provided a two-layer view of the O3ptake processes within and above the forest, an independent,ertically resolved picture can be derived by the MLM. Before dis-ussing the MLM results for O3 mean concentration and turbulentuxes, the MLM calculations for CO2 and H2O are briefly presentedo evaluate how well the MLM reproduces the vertical structuref the stomatal uptake for the study period. Fig. 5 presents com-arisons between measured and modeled ecosystem Fc and Fw

n a ½ h basis, in addition to their measured and MLM modelednsemble-averaged diurnal cycles. Fig. 6 shows the ensemble-veraged measured and MLM modeled daytime (10:00–16:00)O2 and H2O fluxes and mean concentration profiles. The agree-ent between measured and modeled mean concentration and

urbulent fluxes for these two scalars is satisfactory. The bias inc is due to systematic difference between chamber-measured

oil respiration (MLM boundary condition) and nocturnal EC mea-urements in the study period. The agreement suggests that theertical structure of the stomatal pathway is reasonably reproducednd provide the necessary confidence in the MLM computed geff

−20 −10 0 10−20

−15

−10

−5

0

5

10

Fc,

ML

M (μ

mo

lm−2

s−1)

Fc,EC

( μmolm−2 s−1 )

y=0.98x + 1.45

a)

F (

Wm

−2)

0 4 8 12 16 20 24

−15

−10

−5

0

5

Fc (μ

mo

lm−2

s−1)

time (h)

c)

F (

Wm

−2)

ig. 5. Top: Comparisons between EC measured and MLM computed ecosystem CO2 (Fc , ahe ensemble-averaged dry-canopy fluxes along time of day. For Fw , both whole ecosyste

est Meteorology 173 (2013) 85– 99 93

and its layer-wise up-scaling within the canopy via the leaf areadensity. Consequently, the predicted stomatal O3 uptake compo-nent (Sst) can be assumed to be reasonably well reproduced andanomalies between measured and MLM modeled FO3 (z) are nowused to provide clues about the magnitude and vertical location ofSns.

The ensemble-averaged modeled O3 sinks and sources (Sc),concentration-normalized fluxes FO3 (z)/C(z) and concomitantmodeled C(z) resulting from stomatal uptake Sc = Sst are shown inFig. 7. For comparison, the ensemble-averaged measured fluxesand mean concentration profiles are also given. The stomatal path-way alone clearly underestimates the O3 uptake measured by thetwo EC systems. The measured gradient in C(z) is small, in anensemble sense, and appears to be less than 4% indicative of thewell-mixed conditions inside the canopy during daytime condi-tions. However, the MLM predicted O3 mean concentrations areconsistently higher than the measured ones at virtually all levelswithin the canopy when only the stomatal pathway is accountedfor. Thus, comparisons of turbulent fluxes and mean concentrations(measured independently from each other) to the MLM predictionsindicate that non-stomatal O3 removal (estimated as the differencebetween modeled stomatal uptake and measured Vd) within thecanopy must be significant. In an ensemble sense, its magnitudeseems to be ∼0.1 cm s−1 and contributes some 25% of the “true”measured uptake. It also appears that all of the “missing” uptakeshould take place in the sub-canopy and/or at the forest floor wherethe stomatal component is slightly under 0.05 cm s−1. The differ-ence between the MLM-modeled (Fig. 7) and measured stomatal

uptake (Fig. 3) at the forest floor can, to a large extent, be attributedto the moss and forest floor evaporation, which are included in themeasured Fw but not considered as stomatal sources but includedas a boundary condition in MLM (Fig. 6).

0 100 200 300

0

50

100

150

200

250

300

w,M

LM

Fw,EC (Wm−2 )

y=0.88x + 14

b)

0 4 8 12 16 20 24

0

50

100

150

200

w

time (h)

d)

) and water (Fw , b) fluxes. Bottom: Same as above but the comparison is shown form and forest floor fluxes are shown (d).

94 S. Launiainen et al. / Agricultural and Forest Meteorology 173 (2013) 85– 99

−12 −8 −4 0 40

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Fc (μmolm−2 s−1 )

z/h

a)

0.995 1 1.005 1.010

0.2

0.4

0.6

0.8

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1.2

1.4

1.6

CO2/CO

2,ref (−)

z/h

b)

0 50 100 150 2000

0.2

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1.2

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(Wm−2 )

c)

0.98 1 1.02 1.04 1.060

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0.6

0.8

1

1.2

1.4

1.6

H2O/H

2O

ref (−)

d)

F ater

( aluesn

fi1GL2caCie

slT3lZenb

ig. 6. Ensemble averaged (n = 253) measured and MLM computed CO2 (Fc , a) and w10:00–16:00) conditions (c and d). The dots with horizontal bars show measured vot in scale) in the left panels.

At the ecosystem scale, the relative importance of Sns derivedrom the comparison between MLM results and measurements fallsn the middle range of other studies (Cieslik, 2004, 2009; Coe et al.,995; Fares et al., 2010; Fowler et al., 2001; Gerosa et al., 2009;oldstein et al., 2004; Grantz et al., 1995, 1997; Hogg et al., 2007;amaud et al., 2002, 2009; Wesely and Hicks, 2000; Wolfe et al.,011a,b). Supplementing the stomatal O3 uptake by non-stomatalomponent (Sns) may allow considering the plausible causes andpproximate shape of Sns by comparing measured and modeled(z). As discussed earlier, the net strength of the non-stomatal sink

s determined so as to match the MLM modeled and measurednsemble averaged whole-ecosystem FO3 .

The first non-stomatal pathway considered is the cuticular andoil surface uptake, in which case Sns was made proportional toocal a(z) and soil boundary layer characteristics (Sns,sur, Eq. (11)).he cuticular (rcut) and soil surface resistance (rs) were set to600 s m−1 and 100 s m−1, respectively, consistent with typical

iterature values (Baldocchi, 1988; Meyers and Baldocchi, 1988;

hang et al., 2003). This adjustment reproduces the measurednsemble averaged ecosystem FO3 , improves modeled C(z) but sig-ificantly underestimates FO3,s (Fig. 7). The results indicate thatelow such a tall canopy, soil boundary layer resistance is large so

(Fw , b) flux profiles and concomitant concentration profiles in dry-canopy daytime (mean ± std). The vertical leaf area distribution is superimposed (gray dashed line,

that soil conductance remains below 0.03 cm s−1, even when rs isreduced to zero (not shown). It thus seems that the soil surfaceO3 uptake is not significant in this site. Although the ecosystemO3 uptake is well recovered when stomatal component is sup-plemented by soil and cuticular surface uptake (Eq. (11)), poorcomparison of measured and modeled sub-canopy flux suggeststhat this may not be the correct O3 removal mechanism here.Second hypothesis considered a non-stomatal sink in the lowertrunk-space which was approached by setting all non-stomataluptake to occur within the lowest 1 m of the canopy (Sns,1, Eq.(14)). This treatment of the non-stomatal sink still yielded a slightunderestimate of FO3,s. However, the shape of the modeled C(z) isimproved but the modeled mean gradient is stronger than the mea-sured in the trunk-space. The C(z) is insensitive to the exact shapeof near-ground Sns,1 (not shown).

Finally, the addition of a ‘bulk’ gas-phase chemical sink and pho-tochemical O3 production (Sns,2, Eq. (15)) is explored. It appears thatthe shape of measured C(z) may be best (although not perfectly)

explained by the vertically varying imbalance between the photo-chemical source and the first-order chemical sink of O3 (Fig. 7). Inthis scenario, the MLM results indicate that there exists a net sourceof O3 above z/h ∼ 0.85 and it appears that the largest non-stomatal

S. Launiainen et al. / Agricultural and Forest Meteorology 173 (2013) 85– 99 95

−0.6 −0.4 −0.2 00

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

FO3 (z) / C(z) (cm s−1 )

z/h

a)

0.94 0.96 0.98 10

0.2

0.4

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1

1.2

1.4

1.6

O3(z)/O

3,ref (−)

z/h

b)S

st

Sst

+Sns,sur

Sst

+ Sns,1

Sst

+Sns,2

obs.

Fig. 7. Comparison between measured and the MLM computed ensemble-averaged (n = 253) dry-canopy daytime (10–16) O3 flux FO3 (z) normalized by local concentration(a) and concomitant concentration (C(z)) profiles (b). Negative values represent downward flux. The Sst represents run when only the stomatal uptake is accounted for. InSst + Sns,sur it is supplemented by cuticular and soil uptake (Eq. (11)), in Sst + Sns,1 by a depth-constant sink when z ≤ 0.07 z/h (Eq. (14)) and in Sst + Sns,2 by 1st order kinetic sinka ean ±(

nWnhdrlhbcktTtccpcb(

ic2swaaaFnn

nd photochemical O3 production (Eq. (15)). Throughout, horizontal bars indicate mgray dashed line, not in scale).

et sink is located in the lower part or below the canopy crown.ithin the MLM, the mechanism resulting in the apparently large

on-stomatal sink within the trunk-space is the reduced Qp(z) (andence reduced source of O3) compared to the above-canopy con-itions. The chemical sink term, assumed to follow a first-ordereaction with a temperature-dependent rate constant, remainsarge during daytime conditions. Since Sns,2 formulation (Eq. (15))as two free parameters (kp, ks,10), the same above-canopy Vd cane recovered by several parameter combinations. In Fig. 7, theombination that best approximates the GO3 in sub-canopy yieldsp ∼ 9.3 × 10−7 m2 mol−1 and ks,10 ∼ 4 × 10−3 mol m−3 s−1 (whenhe units of Sns,2 is in �mol m−3 s−1 and Qp(z) is in �mol m−2 s−1).he precise chemical pathways responsible for Sns,2 were not iden-ified or attempted in this study, but the inferred “lumped” rateonstants may potentially assist future identification of the pre-ise chemical pathways or their bulk aggregated effects. When thehotochemical production was set to zero and only for the depth-onstant chemical sinks of Eq. (15) were ‘activated’ in the MLM,oth the concentration gradient and FO3,s were underestimatednot shown).

This analysis does not provide a proof of whether the chem-cal gas-phase O3 removal pathways is significant inside plantanopies in dry-canopy daytime conditions (Kurpius and Goldstein,003; Goldstein et al., 2004; Wolfe et al., 2011b). The resultshould be interpreted within the limitations of the MLM, especiallyith regards to uncertainties in model parameters and canopy

ttributes, and the measurements. The comparison of measurednd modeled FO3 and C(z) profiles, however, indicate that such

hypothesis is plausible for the case of the studied pine forest.urther, the results suggest that the most likely location of theon-stomatal sink is the lower trunk-space or understory layer butot the soil surface.

std and the mean. The vertical leaf area distribution is superimposed in panel (a)

4. Conclusions

The O3 removal within a Scots pine forest were explored usinga combination of direct two-level eddy covariance fluxes anddetailed within-canopy concentration profiles assisted by a multi-layer modeling (MLM) approach. Between 25–30% (nighttime) and35–45% (daytime) of ecosystem O3 uptake occurs in the sub-canopyand/or at the forest floor. In this region, the non-stomatal pathwaysexceed their stomatal counterpart by factors of 2–4. At the ecosys-tem scale, the non-stomatal component is largest during nighttimeand early morning hours when one-third to one-half of it seems tooriginate below the overstory canopy. In dry-canopy daytime con-ditions, the non-stomatal component is 10–25% of ecosystem O3uptake, and almost completely attributed to sub-canopy and/or for-est floor processes. The agreement between the MLM predictionsand measurements for CO2 and H2O fluxes and mean concentra-tion profiles suggest that the stomatal uptake pathway of O3 andmean O3 profile can be well described by the model. Three poten-tial hypotheses for the dry-canopy daytime non-stomatal uptakewere addressed using the MLM. It was shown that the most likelylocation of the net non-stomatal sink is in the lower trunk-spacewhile the soil surface flux is of minor importance. The observed O3mean concentration profiles were best matched when the stoma-tal uptake was supplemented by a light-dependent photochemicalsource and a first-order kinetic sink term for O3 inside the canopy.

More broadly, the O3 mean concentration measurements andthe MLM results suggest that for relatively sparse stands, the ‘well-mixed’ condition inside the canopy is a reasonable assumption dur-

ing daytime and well-ventilated conditions. This finding is signifi-cant when assessing phyto-toxicity of stomatal O3 uptake by plants.The non-stomatal sink does not alter the O3 mean concentrationsignificantly here and this finding suggests that proper modeling

9 nd For

op

A

mfiOsLA1Pt(St6a3fF

Ac

Twtaat

Fuo

6 S. Launiainen et al. / Agricultural a

f the stomatal conductance remains the primary factor inhyto-toxic evaluation when dose or exposure measures are used.

cknowledgements

Erkki Siivola is acknowledged for the technical design of theeasurement system used for within-canopy concentration pro-

le, Petri Keronen and Sami Haapanala for the assistance with3 analyzers, Veijo Hiltunen for the maintenance of field mea-

urements and Ditte Mogensen for insights on O3 chemistry.auniainen, Grönholm and Vesala acknowledge support from thecademy of Finland Centre of Excellence program (Project No.118615) and from the project “Effects of Climate Change on Airollution Impacts and Response Strategies for European Ecosys-ems” (ÉCLAIRE), funded under the EC 7th Framework ProgrammeGrant Agreement No. 282910). Katul acknowledges the Nationalcience Foundation (NSF-AGS-1102227 and NSF-EAR-1013339),he United States Department of Agriculture (USDA Grant 2011-7003-30222), the Fulbright-Italy Distinguished Fellows program,nd the Department of Physics at University of Helsinki during his-month visit in 2009. The field measurements greatly benefitedrom the ICOS research infrastructure, funded by the Academy ofinland (Project No. 263149).

ppendix A. Estimation of skin temperature for canopyonductance calculations

The ‘big-leaf’ stomatal conductance was estimated in two ways.he first assumed the canopy is well coupled to the atmosphere,hile the second uses an estimate of the canopy skin tempera-

ure (Tc) and computes the driving forces as e*(Tc) − ea. The secondpproach can be viewed as a ‘correction’ to the well coupledssumption between the canopy and the atmosphere. Naturally,hese two estimates of the driving force for transpiration bound the

−200 0 200 400 600−0.5

0

0.5

1

1.5

2

2.5

3

Hs (W m−2 )

u* (

Tc −

Ta)

(m s

−1 K

)

ig. A.1. Left: Estimation of bulk surface emissivity (εs ≈ 0.99) from eddy-covariance mea* > 0.5 m s−1. The regression line is presented in solid. Right: Comparison between bulk cn u* > 0.5 m s−1. The Tc measurements were used to correct the driving force for water va

est Meteorology 173 (2013) 85– 99

possible values for canopy conductance for water vapor, with thesecond estimate providing lower canopy conductance values whencompared to the first given that Tc − Ta during daytime conditions.

While Tc was not directly measured here, it can be estimatedfrom the measured longwave radiation emitted from the surface(Rlr), which is given by

Rlt = εs�sf T4c , (A.1)

where εs is the surface emissivity (0.95–1.0) and �sf is theStefan–Boltzmann constant.

Since εs is not precisely known, its value was estimated by not-ing that at finite u* (>0.5 m s−1) and negligible sensible heat flux|Hs|, Tc ≈ Ta set at the canopy top. Using this approach, we esti-mated εs ≈ 0.99. Fig. A.1 shows the relationship between measuredHs and u*(Tc − Ta) as well as the comparison between Ts inferredfrom measured Rlr and measured Ta.

Using regression analysis on the data in Fig. A.1, the regressionequation is given by

Hs ≈ 157.4u∗(Tc − Ta), (A.2)

which for near-neutral conditions can be used to estimate zoh from

Hs = �Cpk

log[(h − d)/zoh]u∗[Tc − Ta(h)] (A.3)

resulting in

log[

h − doh

zoh

]≈ 3. (A.4)

Here doh and zoh are the zero-plane displacement height and theheat roughness length, respectively. In general, doh ≈ d ≈ 2/3h and

zoh

h≈ 1

3exp(−3) ≈ 0.0166, (A.5)

an order of magnitude smaller than the momentum rough-ness length (zo ∼ 0.1h), which is plausible for such canopies. This

0 10 20 30 405

10

15

20

25

30

35

Tc ( °C)

Ta (

° C)

surements of sensible heat flux (Hs) and u*(Tc − Ta) conditioned on friction velocityanopy temperature, Tc , and air temperature and the canopy top, Ta(h), conditionedpor flux when estimating the canopy conductance for water vapor.

nd For

ed

Adc

h

B

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Fp

S. Launiainen et al. / Agricultural a

stimate of Tc from measured Ta(h), Hs and u* was used to adjust theriving force e*(Tc) − ea for canopy scale conductance calculations.

ppendix B. Modeling the mean flow field, turbulentiffusivity, turbulent Schmidt number, and boundary layeronductance

Much of this material is presented in Launiainen et al. (2011);owever, the salient features are reviewed for completeness.

.1. Mean flow field and turbulent diffusivity

In a stationary and planar-homogeneous flow at high Reynoldsumber and with no subsidence and mean longitudinal pressure

radient, the mean momentum budget reduces to

∂u′w′

∂z= −Cda(z)U2, (B.1)

0 0. 5 1 0

0.01

0.02

0.03

0.04

0.05

PDF

KC

0.92a)

0 0. 5 1 0

0.00 5

0.01

0.01 5

0.02

0.02 5

0.03

0.03 5

0.04

PDF

KH

1.01b)

0 0. 5 1 0

0.00 5

0.01

0.01 5

0.02

0.02 5

0.03

0.03 5

PDF

KO

1.08c)

ig. B.1. The variations in turbulent Schmidt number (Ki/Km) above the canopy for CO2

ercentiles.

est Meteorology 173 (2013) 85– 99 97

where Cd is the foliage drag coefficient (here 0.15) usually between0.1 and 0.3 (Katul et al., 2004b). As with scalars, employing first-order closure principles results in

u′w′ = −Km∂U

∂z. (B.2)

Replacing Eq. (B.2) into Eq. (B.1) results in a homogeneoussecond-order nonlinear ordinary differential equation, given as

Km∂2U

∂z2+ ∂Km

∂z

∂U

∂z− Cda(z)U2 = 0, (B.3)

where the eddy diffusivity for momentum (K ) is

m

Km = l2∣∣∣∣∂U

∂z

∣∣∣∣ . (B.4)

1.5 2 2. 5 3

O2 / Km

1.5 2 2. 5 3

2O / Km

1.5 2 2. 5 3

3 / Km

, H2O, and O3. Solid line is the median and dashed lines represent the 25th/75th

9 nd For

l

wkpimaiozba

B

bnmwfi

w

wtlccd

B

bfb

g

wintiRras

R

A

A

A

A

8 S. Launiainen et al. / Agricultural a

The effective mixing length (l) is given as

=

⎧⎪⎨⎪⎩

kvz, z < (˛′h/kv)

˛′h, ˛′h/kv ≤ z < h

kv(z − d), z ≥ h

(B.5)

here d is the zero-plane displacement height (here set to 0.7 h),v = 0.4 is the von Karman constant and h is the canopy height. Thearameter ˛′ (here 9.0 m) ensures continuity (but not smoothness)

n the mixing length. It was determined empirically to match theodeled and measured CO2 concentration profiles when CO2 sinks

nd sources and boundary conditions were first independentlynferred. Eq. (B.3) can be solved when two boundary conditionsn the mean velocity are imposed. Because the canopy is dense, aero-turbulent shear stress at the ground was assumed as a loweroundary condition. The measured mean U at z/h ∼ 1.55 was useds upper boundary condition.

.2. Turbulent Schmidt number

As earlier noted, in the canopy sub-layer, SN = Km/Kt need note unity. In the near-neutral surface layer, neglecting the rough-ess sub-layer effects (or assuming them similar for both O3 andomentum as well as for CO2 and H2O), setting Km = kv(z − d)u∗,here u* is the friction velocity at the canopy top, and applying therst-order closure principles gives

′c′ = −Kt∂C

∂z= −ku∗

SN

∂C

∂ ln z, (B.6)

hich allows estimation of SN from direct flux and concen-ration gradient measurements made above the forest. Usingong-term mean concentration gradients and fluxes above theanopy (Keronen et al., 2003), we estimated SN for near-neutralonditions for all three scalars and found that the mode of theistributions of computed SN are close to unity as shown in Fig. B.1.

.3. Leaf boundary layer conductance

Because the mean wind field is modeled in the MLM scheme, theoundary layer conductance gbl for O3 can be readily accountedor in the numerical model. Using flat-plate theory for a laminaroundary layer, this conductance is given by

bl = 0.664��O3 Pr1/3Re1/2/lbl. (B.7)

here �O3 is the molecular diffusivity of O3 (=14.6 × 10−6 m2 s−1), �s the air density (=41.6 mol m−3), Pr = /�T is the molecular Prandtlumber defined as the ratio of air viscosity ( = 15.7 × 10−6 m s−1)o molecular diffusivity for heat (�T = 21.6 × 10−6 m s−1), Re = Ulb/s the Reynolds number assumed to be smaller than the criticaleynolds number for the transition from laminar to turbulent flowegime, which for a smooth flat plate is 5 × 105, and lbl is a char-cteristic leaf dimension, which for the conifer foliage, clumped inhoots, was set to 5 cm.

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