Atmospheric Environment 55 (2012) 271e278

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Atmospheric Environment
journal homepage: www.elsevier.com/locate/atmosenv

Parameterization of Zelkova serrata stomatal conductance model to estimate
stomatal ozone uptake in Japan
Yasutomo Hoshika a,1, Elena Paoletti b, Kenji Omasa a, *ab

Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
Institute of Plant Protection, National Council of Research, Via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italya r t i c l e i n f o

a b s t r a c t

Article history:
Received 14 October 2011
Received in revised form
23 February 2012
Accepted 24 February 2012

To parameterize stomatal conductance or ozone uptake modeling in the Eastern Asian tree species
Zelkova serrata, measurements of stomatal conductance were carried out in several Japanese sites acrossthe growing season. The new parameterization improved the stomatal conductance model performance
relative to a previously proposed model. The results were used to compare the spatial distribution of
AOT40 and Z. serrata stomatal ozone uptake in Japan. Including a soil moisture function improved themodel in the short periods with low precipitation. In addition, elevated vapor pressure deﬁcit and soil
moisture deﬁcit due to high temperature, and high ozone exposure induced stomatal closure. The
consequent decoupling of stomatal ozone uptake from high ozone exposure suggests caution in using
AOT40 as a standard for Z. serrata protection in Japan.
Ó 2012 Elsevier Ltd. All rights reserved.

Keywords:
Zelkova serrata
Ozone uptake
Stomatal conductance modeling
Japan
Ozone

1. Introduction
Tropospheric ozone (O3) is an important phytotoxic air pollutant
and is also recognized as a signiﬁcant greenhouse gas (Bytnerowicz
et al., 2007; Serengil et al., 2011). Surface O3 concentrations are
increasing in East Asia because of rapid increases in emission of themain O3 precursors, Nitrogen oxides and volatile organic compounds(Naja and Akimoto, 2004). Ohara and Sakata (2003) reported thatannual average concentrations of photochemical oxidant, mainly O3,
increased at high rate (0.33 ppb year1) from 1985 to 1999 in Japan.
Phytotoxic nature of O3 has been well known for decades (e.g.,
NIES, 1980, 1984; Omasa et al., 2002; Paoletti, 2007). The concentration based approach for O3 effects on plants (e.g., AOT40: accumulated exposure over a threshold of 40 ppb) has the advantage ofbeing simple and needs only atmospheric O3 concentrations, i.e.,external O3 exposure, without considering internal O3 uptake ina leaf. In Japan, Kohno et al. (2005) recommended 8e15 ppm h
AOT40 from April to September for sensitive forest species asa critical level, i.e., able to induce a 10% growth reduction. In Europe,
the critical level is 5 ppm h AOT40 for forests (Mills et al., 2010) or* Corresponding author. Tel.: þ81 3 5841 5340; fax: þ81 3 5841 8175.
E-mail addresses: ahoshika@for.agr.hokudai.ac.jp (Y. Hoshika), e.paoletti@
ipp.cnr.it (E. Paoletti), aomasa@mail.ecc.u-tokyo.ac.jp (K. Omasa).
1
Present address: Silviculture and Forest Ecological Studies, Hokkaido University,
Sapporo 060-8589, Japan.
1352-2310/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved.
doi:10.1016/j.atmosenv.2012.02.083

9 ppm h AOT40 for any kind of vegetation (European Commission,2008). However, several studies suggest that AOT40 is not adequate
for O3 risk assessment to plants (Kobayashi, 1999; Matyssek andInnes, 1999; Matyssek et al., 2007). Stomatal O3 uptake or ﬂux ismore closely related to O3 impacts (Omasa et al., 2002; Paoletti and
Manning, 2007; Karlsson et al., 2007). In Europe, critical levels forO3 risk based on stomatal O3 uptake have been suggested for
potato, tomato, wheat and several tree species (Mills et al., 2010).
Although the stomatal ﬂux-based approach is expected toprovide a better assessment of O3 impacts to plants in East Asia
(Watanabe and Yamaguchi, 2011), AOT40 has been recommended
for assessments of O3 impacts in Japan (e.g., Kohno et al., 2005).
This is because much precipitation and limited water stress in Japanmight be favorable climate for stomatal opening, i.e., not limiting
stomatal O3 uptake. In Japan, however, maximum hourly air
temperature exceeding 35  C often occurred in summer since the90s (JMA, 2002), which thus may induce high vapor pressure deﬁcit(VPD) and enhance evapotranspiration resulting in soil moisturedeﬁcit. Enhanced VPD and soil moisture deﬁcit may limit stomatal
O3 uptake. Ozone is also known to directly induce stomatal closure
as a result of the inhibition of photosynthesis (Wittig et al., 2007).
Therefore, stomatal O3 uptake may be limited under current
climate conditions and air quality in East Asia.
Japanese zelkova (Zelkova serrata) is one of the typical deciduous
broadleaved tree species in Japan, Korea, eastern China, and Taiwan.
It is often grown as an ornamental tree in warm temperate climates.

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Y. Hoshika et al. / Atmospheric Environment 55 (2012) 271e278

This species is known as a highly O3-sensitive species (Kohno et al.,2005). A short-term (2-day) previous investigation provided model
parameters of stomatal conductance for Z. serrata in western Japan(Kadaira and Yoshida, 2006), but the results were not validated bycomparison with data measured over a seasonal course. The model
developed in that study is here referred to as “literature-based
stomatal conductance model”.
Our main objective was to develop a parameterization of thestomatal conductance model for Z. serrata, and to use it for O3 uptake
modeling in Japan. The re-parameterized model was applied tomeasured data throughout the growing season and compared withthe literature-based model. Because no measured data of soil watercontent were obtained, the model function of soil water content wastested by using model estimates. Results from the literature-basedmodel and the re-parameterized model were used to map
stomatal O3 uptake, compared with AOT40 maps, and used to
discuss whether current climate and O3 pollution may limit stomatal
O3 uptake in East Asia.
2. Materials and methods

2.2. Literature-based stomatal conductance model

2.1. Estimation of AOT40 and stomatal ozone uptake
AOT40 was estimated by using hourly mean O3 concentrations
during daylight hours from April to September in 2007 (Kohno
et al., 2005; Mills et al., 2010), i.e., the growing season of
Z. serrata in Japan:

AOT40 ¼X

(1)where [O3] is hourly mean O3 concentration (ppb).
Stomatal O3 uptake (Fst; nmol O3 m2 s1) was calculated as:

Fst ¼ ½O3 $f1=ðrb þ rc Þg$fðgsw =1:65Þ=ðgsw =1:65 þ gext Þg
1

(2)

2

where rb is the leaf boundary layer resistance (mol m s), rc is theleaf surface resistance (¼1/(gsw/1.65 þ gext); s m1), gsw is thestomatal conductance for water vapor (mmol H2O m2 Projected
Leaf Area (PLA) s1) and 1.65 accounts for the difference in diffusivity of water in air compared with O3. gext is the external leaf
conductance (s m1) that indicates negligible or slight adsorptionof O3 on leaf surface (Omasa et al., 2002). gext was set to
0.0004 m s1 (Mills et al., 2010).
Leaf boundary layer resistance (rb) was calculated from the windspeed, u (s m1), and the mean leaf length, Ld (0.06 m for Z. serrata
obtained from Hosoi and Omasa, 2007) (Mills et al., 2010):

rb ¼ 1:3$150$ðLd =uÞ0:5(3)

where the factor 1.3 accounts for differences in diffusivity between
heat and O3.
In Europe, phytotoxic O3 dose above a ﬂux threshold of Y (PODY)
was recommended to assess O3 risk for forest species (Mills et al.,2010). It is given by:X

A stomatal conductance model for Z. serrata was previously
provided by measurements carried out in western Japan (35 010 N,
135 460 E) (Kadaira and Yoshida, 2006) over two days in August andOctober. The model was based on the multiplicative algorithm
described by Jarvis (1976):

gsw ¼ gmax $flight $ftemp $fVPD

maxð40  ½O3 ; 0Þ

if global radiation>50 W m2

PODY ¼

applied for this species in Japan, we did not set a threshold for theFst value (POD0) in the present study.
Climate (air temperature, precipitation, air humidity, solar
radiation and wind speed) and O3 concentration data for the year
2007 (Takigawa et al., 2007) were input into our model. The valuesof the main climate parameters are shown in Table 1. These data
were provided by the regional air quality forecasting system(Takigawa et al., 2007). This system consists of global and regional
chemistry transport model (CTM). The regional CTM is based on the
WRF/Chem model (Grell et al., 2005) provided at 1-h temporal
resolution and 15  15 km spatial resolution in East Asia (25 e45N, 120 e150 E). Boundary condition in the regional CTM wasprovided by the global CTM based on CHASER (Sudo et al., 2002).
The model successfully captured the horizontal distribution of theobserved surface O3 concentrations (Takigawa et al., 2007). Distribution of Z. serrata was obtained from the spatial map of tree
species in Japan (Horikawa, 1976). These data allowed to provide anestimation of the leaf-level stomatal O3 uptake for Z. serrata in eachgrid square (15  15 km) with 1-h time steps.

maxðFst  Y; 0Þ

(4)where Y is a species-speciﬁc threshold of stomatal O3 uptake(nmol O3 m2 s1). As it was not clear which threshold Y can be

(5)

where
gmax
is
the
maximum
stomatal
conductance(610 mmol H2O m2 PLA s1). The other functions are limiting factorsof gmax and are scaled from 0 to 1. flight, ftemp, and fVPD are a function ofphotosynthetically photon ﬂux density at the leaf surface (PPFD,
mmol photons m2 s1), temperature (T,  C), and VPD (kPa),
respectively.
These functions are expressed as follows:

flight ¼

PPFDðPPFD þ kÞftemp ¼

T  TminTopt  Tmin

(6)
8
>
>
<


9
>
 Tmax  Topt >=Tmax  T
Topt  Tmin
> Tmax  Topt
>
>
>
:
;

1

fVPD ¼ 
1 þ ðVPD=D0:5 Þa

(7)

(8)

where k is a constant, and Topt, Tmin, and Tmax represent the
optimum, minimum, and maximum temperatures for gsw, respectively. D0.5 and a are constants.
2.3. Reparameterization of the stomatal conductance model
Measurements of gsw were conducted in the three regions near
Tokyo listed in Table 2 (central Tokyo: 35 430 N, 139 450 E; southeastern Tokyo: 35 370 N, 139 420 E; western Tokyo: 35 440 N,
139 320 E). The three regions were chosen as representatives ofTable 1Main climate data (SD) as an input data (AprileSeptember 2007) estimated by Takigawa et al. (2007) to estimate stomatal O3 uptake in Japan.
Grid number

Air temperature ( C)

Precipitation (mm)Solar radiation (W m2)

VPD (kPa)

O3 concentration (ppb)

1598

18.8 (3.9)

939 (313)

249.4 (15.5)

0.72 (0.29)

37.2 (3.6)

Y. Hoshika et al. / Atmospheric Environment 55 (2012) 271e278

273

Table 2Range of main meteorological parameters during gs measurements (value in brackets indicates mean), and AOT40 in the measurement sites.
Site

Year

PPFD (mmol m2 s1)

Air temperature ( C)

VPD (kPa)

AOT40a (ppm h)Central Tokyo
South eastern Tokyo

2009
2008

0e1970 (638)60e1660 (491)12.5e33.4 (25.4)
25.2e32.8 (29.2)

0.8e2.5 (1.6)
1.3e2.4 (1.7)

6.1
16.6

Western Tokyo

2008
2009
2010

100e1910 (583)90e1990 (918)60e1950 (1051)

15.1e35.8 (25.7)
18.9e34.4 (27.6)
19.8e36.9 (29.6)

0.9e2.4 (1.6)
0.8e3.2 (1.8)
0.9e2.8 (1.7)

28.0
27.7
31.0

a
Ozone concentration data was obtained from monitoring stations near the measurement sites (distance between the stations and measurement sites <1.5 km). AOT40 was
calculated over AprileSeptember.

different polluted area in order to parameterize O3 effects on gsw.
Western Tokyo (Tanashi) is a high-polluted area where AOT40 was
nearly equaled to 30 ppm h. gsw was measured using a cycling
diffusive porometer (Model AP4, Delta-T devices, Cambridge, UK).
Measurements were carried out on southward sunlit leaves in >10year-old tree in all sites and on fully sun-exposed healthy leaves at
top of the canopy of 10-year-old saplings at western Tokyo (Table 3).
Diurnal courses of gsw were measured during different stages of thegrowing seasons of three consecutive years (central Tokyo:
AprileAugust in 2009; south eastern Tokyo: July and September in
2008; western Tokyo (Tanashi park): MayeAugust in 2009, and thenearby University of Tokyo Tanashi forest, MayeNovember in 2008,
AprileAugust in 2009, and MayeSeptember in 2010). All pooleddata of 2532 measurements were divided into two subsets, i.e., datafor validation and parameterization. A subset for validation (20% of
all pooled data, 510 measurements) was extracted by random
sampling using Microsoft Excel software. The extracted data
included following measurements: 10 June 2009 in central Tokyo,
17 July 2008 in south eastern Tokyo, 13 July 2009 in Tanashi park
(western Tokyo), and 11 July 2008, 30 April and 28 August 2009, and
11 June, 2 July and 5 August 2010 in University of Tokyo Tanashi
forest (western Tokyo). The rest of data set was used to reparameterize the stomatal conductance model.
The model was based on the multiplicative algorithm describedby Jarvis (1976) and modiﬁed by Emberson et al. (2000a):where DOY is the day of year. SGS and EGS is a date of start and endof growing season, respectively. The parameters fphen_a and fphen_b
denote the maximum fraction of gmax at the start and end of thegrowing season. fphen_c and fphen_d are the parameters representing
the number of days for fphen to reach its maximum and the numberof days during the decline of fphen for the minimum value.
The response of gsw to PPFD, i.e., flight, is described as:

flight ¼ 1  expða$PPFDÞ

where a is a species-speciﬁc parameter deﬁning the shape of thehyperbolic relationship.
The function of T ( C) is expressed as:

fVPD ¼(12)

ð1  fmin Þ$ðVPDmin  VPDÞþ fmin
VPDmin  VPDmax(13)

where VPDmin and VPDmax represent the threshold of VPD to reachminimum and full stomatal opening, respectively. If VPD exceeds
VPDmin, fVPD is set to fmin. If VPD is lower than VPDmax, fVPD is 1.
The function of O3 is given as follows, according to Pleijel et al.
(2002):

where fmin is the minimum stomatal conductance. fphen and fO3 are
the variation in gsw with leaf age and premature senescenceinduced by O3, respectively. fSWP is a function of volumetric soil
water potential (MPa).
The response of gsw to phenology (fphen) is described as follows:
When SGS  DOY < (SGS þ fphen_c)1
fO3 ¼ 1 þ ðAOT0=bÞc

(14)

where AOT0 is the accumulated exposure over a threshold of 0 ppb
during daylight hours (ppm h). b and c are constants.
Parameterization was carried out using a boundary line analysis.
First, the gsw data were divided into classes with the following stepwise increases for each variable: 200 mmol photons m2 s1 for PPFD
(when PPFD values were less than 200 mmol photons m2 s1, PPFD
classes at 50 mmol photons m2 s1 steps were adopted), 2  C for T,
0.2 kPa for VPD and 20 ppm h for AOT0. A function was ﬁtted against
each model variable based on 98th percentile values per each class ofenvironmental factors except for fSWP. Because no measurements ofsoil water content were available, the effect of soil water availability
on stomatal O3 uptake was accounted for by using model estimates 1  fphen a $ ðDOY  SGSÞ=fphen c þ fphen a

When (SGS þ fphen_c)  DOY  (EGS  fphen_d)fphen ¼ 1
When (EGS  fphen_d) < DOY  EGS 
1  fphen b $ ðEGS  DOYÞ=fphen d þ fphen b9> Tmax  Topt >=Tmax  T
Topt  Tmin>>
T
 Topt
>
>
;
: max

8
>
>
<

where Topt, Tmin, and Tmax represent the optimum, minimum, andmaximum temperature for gsw, respectively.
The response of gsw to VPD (kPa) is given by:(9)fphen ¼

T  TminTopt  Tmin

ftemp ¼ongsw ¼ gmax $min fphen ; fO3 $flight $max fmin ; ftemp $fVPD $fSWP

fphen ¼

(11)

(10)

Table 3
Summary of target trees in the measurement sites.
Measured leaf position

Site

Year

Number of trees

Number of leaves of each tree

Tree height (m)Southward sunlit leaves(3 m, >10-year-old tree)

Central Tokyo (Bunkyo-ku)
South eastern Tokyo (Meguro-ku)
Western Tokyo (Tanashi park)

2009
2008
2009

1
1
1

10
10
10

15
15
10

Leaves at top of the canopy(5 m, 10-year-old saplings)

Western Tokyo Univ. Tokyo Tanashi forest)

2008e2010

3

3e5

5

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Y. Hoshika et al. / Atmospheric Environment 55 (2012) 271e278

of soil water content (see Section 2.4). Meteorological parameterssuch as PPFD, T and VPD were derived from the porometry
measurements to estimate the parameters of stomatal conductancemodel. O3 concentration data was obtained from monitoring
stations near the measurement sites (distance between the stations
and measurement sites <1.5 km).

I ¼

12
X


i; i ¼

1Tm
5

1:514; imin ¼ 0

 
 


d ¼ 6:75  107 I 3  7:71  105 I 2 þ 1:79  102 Iþ 0:492(19)

2.4. Testing a model function of soil water content
The function of root-zone plant available water (fPAW) has beensuggested as a better proxy of soil moisture effects on stomata andcan be used instead of the function of soil water potential (fSWP)(Mills et al., 2010). Root-zone plant available water (PAW) is theamount of water in the soil, which is available to the plants. PAW(fraction) is expressed as follows:

PAW ¼

q  qWPqFC  qWP

(15)

where q is the current soil water content (mm), qFC is soil watercontent at ﬁeld capacity (mm) and qWP is soil water content at
wilting point (mm).
The fPAW is given by the following equations:
When PAWt < PAW

fPAW ¼ 1

where Ta is daily mean air temperature ( C), Tm is monthly mean air
temperature ( C), h is length of daylight hours (h), I is the annual
heat index (no dimension), d is an empirical coefﬁcient (nodimension). To calculate Ep, Ta and P for each site were obtained
from nearby monitoring stations of the Japanese climate agency.
fPAW was ﬁtted using boundary line analysis based on 98th
percentile values per each of PAW, i.e., splitting up the data set into
PAW class at 0.1 steps. The stomatal conductance model including
fPAW was validated by comparison with measurements of gsw.
2.5. Data analysis
Simple regression analysis was used to test the relationships
between measured and estimated gsw. The analysis was performed
using SPSS software (SPSS, Chicago, USA).
Spatial maps of both indices were provided in order to compare
AOT40 and POD0. The mapping was achieved using Arc GIS software (ESRI, USA).

when 0 < PAW < PAWt

fPAW ¼q  qWP
PAWt

3. Results(16)

where PAWt is the threshold of PAW (fraction), above which gsw is
at a maximum.
Root-zone moisture (RM ¼ q  qWP, mm) was estimated by using
the simple water budget model (e.g., Lhomme and Katerji, 1991;
Mintz and Walker, 1993):

RM ¼ RM1 þ ðP  El Þ  ðEt þ Es Þ

(17)where RM1 is the root-zone moisture at the end of the precedingday (mm), P is the daily precipitation (mm), El is the daily intercepted canopy evaporation (water evaporated from the wet surfaceof the vegetation and wet surface of the soil, during and following
precipitation ,mm), Et is the daily transpiration (mm), and Es is thedaily soil evaporation (mm). Any excess precipitation was assumed
to be lost to run-off. Soil water storage capacity (qFC  qWP) was set
to 200 mm (soil type: clay loam; soil depth: 1 m) (Fujieda, 2007).
PAW was assumed to be 0.9 at the beginning of the year (De Marcoet al., 2010).
Et, Es and El was estimated by Thornthwaite’s method(Thornthwaite and Mather, 1955; Mintz and Walker, 1993):


El ¼ min P; EpEt þ Es ¼ Ep  El $PAW

(18)

where Ep is the daily potential evapotranspiration (mm), and given by:8>>> 0; Ta < 0 C
>
>



>
>
<
10$Ta d h
; 0 < Ta < 26:5  C
0:533$
Ep ¼
12
I
>
>
>
>

 h
>
>
>
; Ta >26:5  C:  13:86 þ 1:075$Ta  0:0144$Ta2
12

3.1. Reparameterization of the stomatal conductance model
The gmax value was set to 465 mmol H2O m2 PLA s1 as 98th
percentile of gsw measurements at all 4 sites (Fig. 1A; Table 4). The
fmin value was set to 0.1 (fraction) corresponding to the 5th
percentile values of gsw recorded throughout the measurements.
The limiting functions of gsw (fphen, flight, ftemp, fVPD, fPAW and fO3)
were deﬁned by boundary line analysis (Fig. 1BeG; Table 4). The
main differences between the literature-based model and therevised model were in fphen, ftemp, fPAW and fO3 (Fig. 1B, D, F, G). In
the literature-based model, functions of phenology, soil water andTable 4
Summary of gsw parameters in re-parameterized model and literature-based modelfor Zelkova serrata.
Parameter

Re-parameterized model

Literature-basedmodel

gmax (mmol H2O m2 PLA s1)465
SD ¼ 64.5

610

fmin (fraction)

0.1

fphen SGS (day of year)
EGS (day of year)
fphen_a (fraction)fphen_b (fraction)fphen_c (days)
fphen_d (days)

105
320
0.2
0.5
56
60

flight a (constant)0.0084k (constant)

94

ftemp Topt ( C)
Tmin ( C)
Tmax ( C)

27
11
45

Topt ( C)
Tmin ( C)
Tmax ( C)

43.9
5
45

fVPD VPDmax (kPa)
VPDmin (kPa)

1.1
4.9

a (constant)

D0.5 (kPa)

3.5
2.3

fPAW PAWt (fraction)

0.58

fO3 b (constant)c (constant)

141
3.4

Y. Hoshika et al. / Atmospheric Environment 55 (2012) 271e278

275

Fig. 1. Parameterization of stomatal conductance model for Zelkova serrata (A: gmax; B: fphen; C: flight; D: ftemp; E: fVPD; F: fPAW; G: fO3). fphen, flight, ftemp, fVPD, fPAW and fO3 are functionsof phenology, photosynthetically photon ﬂux density at the leaf surface (PPFD, mmol photons m2 s1), temperature (T,  C), vapor pressure deﬁcit (VPD, kPa), root-zone plant
available water (fraction) and AOT0 (ppm h), respectively. Relative gsw was calculated as gsw divided by gmax in each site. Thick and dashed lines are the plots of each function in reparameterized model and literature-based model, respectively. Larger symbols show 98th percentile values per each class of environmental factors (PPFD:
200 mmol photons m2 s1, except for values less than 200 mmol photons m2 s1 where 50 mmol photons m2 s1 class was chosen; T: 2  C; VPD: 0.2 kPa; root-zone plant available
water: 0.1; AOT0: 20 ppm h).

276

Y. Hoshika et al. / Atmospheric Environment 55 (2012) 271e278

Table 5Results of the regression analysis between measured and estimated gsw using
literature-based model and re-parameterized model.
Model

fPAW

fO3

Literature-based modelR2 ¼ 0.17
RMSE ¼ 111.4

Re-parameterized modelR2 ¼ 0.48
RMSE ¼ 114.9

Re-parameterized modelþR2 ¼ 0.54
RMSE ¼ 98.0

Re-parameterized modelþR2 ¼ 0.48
RMSE ¼ 110.5

Re-parameterized modelþþR2 ¼ 0.53
RMSE ¼ 95.5

þ: including the function; : not including the function.

O3 were not included, i.e., fphen, fPAW and fO3 ¼ 1 throughout thegrowing season.
The reparameterization presented in this study provided
a better ﬁt with the measurements for validation than theliterature-based model presented by Kadaira and Yoshida (2006)(R2 ¼ 0.53 vs. 0.17) (Table 5). Including fO3 improved the model
performance (Table 5). Testing a function of soil water showed nochange of model performance because fPAW was 1 in most of thegrowing seasons, i.e., no limitation to gsw. However, when the reparameterized model was applied in summer 2010 with low
precipitation (27 mm as monthly precipitation in August), fPAW
improved the daily course of estimated gsw (Fig. 2).
3.2. Comparison of POD0 and AOT40 maps
Fig. 3A shows a map of the AOT40 values from April to
September 2007 in Japan. There was a strong gradient in the AOT40
values from central Japan to northern and western Japan. The
highest AOT40 value of 30 ppm h could be found in Kanto region(around 35 N, 140 E). In contrast, the AOT40 values were relatively
low (0e9 ppm h) in Hokkaido region (42 e45 N, 140 e145 E).
POD0 presented in this study was 46e50 mmol m2 in thecentral part of Japan (Fig. 3B). In Kanto region (around 35 N, 140E), POD0 was relatively low (28e34 mmol m2) although thehighest AOT40 was recorded here. Fig. 4A and B shows averaged
fVPD and fPAW values in summer (JulyeAugust), respectively. In
Kanto region, the averaged fVPD values were <0.8 because of hightemperature in summer. fPAW values were also <0.8 in this region
because high temperature increased evapotranspiration andinduced soil moisture deﬁcit. Therefore, relatively low POD0 was
estimated in this area by the re-parameterized model. The spatial
distribution of POD0 by the re-parameterized model differed fromestimates based on the literature-based model (Fig. 3B, C). In
particular, in Kanto region (around 35 N, 140 E), POD0 was

43e52 mmol m2 and 28e34 mmol m2 when estimated by theliterature-based model and the re-parameterized model, respectively. According to the new model, the highest value of POD0
(50 mmol m2) was recorded in central Japan (Fig. 3B).
4. Discussion
The new model of gsw showed a better performance than theliterature-based model when compared with the measurements(Table 5). The main discrepancies in model parameters between theliterature-based model and the revised model were gmax, fphen,
ftemp, fPAW and fO3 (Fig. 1).
The gmax (610 mmol H2O m2 PLA s1) in the literature-basedmodel was higher than gmax obtained in this study(465 mmol H2O m2 PLA s1). Literature values support gmax presented in this study. Saito et al. (2003) showed a diurnal course of
stomatal conductance of 6-year-old Z. serrata saplings and reported
around 400e500 mmol H2O m2 PLA s1 as maximum values undersaturated light and low VPD conditions. Previous studies havehighlighted the importance of gmax in determining the predictive
capabilities of the model (e.g. Emberson et al., 2000b; Tuovinen
et al., 2007). gmax depends not only on tree and leaf age andcanopy position, but also on population and environmental conditions such as nutrient availability and pollution climate (Wieser
et al., 2000). Collecting data of gmax is important for identifying
the representative value on a regional scale. Although further work
is needed, gmax presented in this study was based on a larger data
set of measurements than previous exercises and is thus recommended for estimating stomatal O3 uptake of Z. serrata in Japan.
The response of gsw to phenology was added to the stomatal
conductance model according to the Emberson et al. (2000a)
approach. fphen increased from mid-April to May, and gradually
decreased from the beginning of September (Fig. 1B). The parameter of fphen improved the model performance at early spring andlate autumn (data not shown). Seasonal course of fphen differeddepending on the sites (Fig. 1B). In western Tokyo, 98th percentile
of measured gsw was 50e70% of gmax from mid-August to
September in 2008 to 2010. Western Tokyo is a highly polluted area
where AOT40 was 31.7 ppm h (Table 1). Ozone-induced reductions
in stomatal conductance have been widely reported (Wittig et al.,2007). The function of O3, fO3, reduced the error of estimated gsw
in the re-parameterized model (Table 5). In summer 2010, low
precipitation in Tokyo induced soil moisture deﬁcit resulting in
reduction of gsw (Fig. 2). Including the soil moisture function (fPAW)
improved the model performance in summer 2010 (Fig. 2). In most
seasons, fPAW was not a limiting factor to stomatal conductance. In
Japan, annual precipitation is elevated and ranges from 1100 mm to2300 mm. Sirisampan et al. (2003) reported that soil water content
had no effect on gsw of six tree species in central Japan. However,the present study suggests that soil moisture deﬁcit may be
a limiting factor in estimating POD0 during short periods of highFig. 2. Examples of the daily trend of measured gsw (C) and estimated gsw by the re-parameterized model (,) and re-parameterized model with the soil moisture function () at
western Tokyo (Univ. Tokyo Tanashi forest) in August 2010. Measured data are mean values  SD, n ¼ 15 (5 leaves  3 trees).

Y. Hoshika et al. / Atmospheric Environment 55 (2012) 271e278

277

Fig. 4. Spatial distribution of averaged fVPD values (A) and fPAW values (B) of reparameterized model during summer (JulyeAugust) in 2007. fVPD and fPAW show the
response of stomatal conductance to vapor pressure deﬁcit and root-zone plant
available water, respectively (scaled from 0 to 1).

Fig. 3. Maps of estimated AOT40 (accumulated exposure over a threshold of 40 ppb) (A),estimated POD0 (phytotoxic ozone dose above a ﬂux threshold of 0 nmol m2 s1) for Zelkova
serrata by the re-parameterized model (B) and the literature-based model (C) in 2007.

soil moisture deﬁcit due to lack of rainfall and/or high temperatures
as experienced in August 2010 (Fig. 2). The parameterization of fPAW
developed in this study thus improves the calculation of stomatal
O3 uptake for Japan.
The function of air temperature, ftemp, was also signiﬁcantly
changed relative to the literature-based model (Fig. 1D), where theTopt was set to more than 40  C. High Topt may cause strong
temperature dependency of POD0 (data not shown). High VPD often
occurs in the afternoon together with high air temperature. Highambient O3 concentrations are often associated with occurrence ofhigh VPD leading to stomatal closure (e.g., Grünhage and Jäger,1994). In general, Topt ranges from 20 to 30  C for temperate
deciduous forest trees (Larcher, 2001). Adequate settings of Topt in
the re-parameterized model reﬂected such interactions between
atmosphere and stomatal responses.
The highest AOT40 value was 30 ppm h found in Kanto region(around 35 N, 140 E) (Fig. 3A). In contrast, POD0 provided by reparameterized model in the same region was relatively low(23e34 mmol m2) (Fig. 3B), because stomatal closure induced by
VPD and soil moisture deﬁcit led to limited stomatal O3 uptake(Fig. 4A, B).

In Japan, air temperature increased by 1.0  C during the past 100
years (JMA, 2002), which is higher than the world average (0.7  C)
(IPCC, 2007). Although an increase in air temperature can be clearlyfound in Japan, no change of annual precipitation was recorded
during the past 100 years (JMA, 2002). Air temperature is expected
to increase more than 2  C in 2081e2100 (Kurihara et al., 2005).
This perspective suggests higher frequency of elevated temperatureand high VPD conditions in a future climate. Stomatal O3 uptake
may be further limited under an expected warming climate.
Risk assessments based on AOT40 and O3 ﬂux may not signiﬁcantly differ under non-limiting conditions for gsw (Schaub et al.,2007). Although annual precipitations are usually very high inJapan, VPD and soil moisture deﬁcit induced by high temperature,
and O3 exposure limited stomatal O3 uptake under high ambient O3
levels. As a result, the comparison between POD0 and AOT40 maps
revealed that the spatial patterns of POD0 differed from those of
AOT40. Therefore, current climate conditions and O3 pollution may
limit stomatal O3 uptake and decoupled it from high O3 levels inJapan.
5. Conclusion
There are only a few reports of gsw modeling to develop thestomatal ﬂux-based approach in East Asia such as Japan (rice: Oueet al., 2008; wheat: Oue et al., 2009; several tree species: Hoshika
et al., 2011a,b). Our results contribute to develop the stomatal
ﬂux-based approach in East Asia. A new parameterization of gsw forZ. serrata was developed on the basis of measured data andimproved the performance of the model relative to a previous
model (Kadaira and Yoshida, 2006). We demonstrated thatstomatal closure induced by VPD, soil moisture deﬁcit and O3
exposure can limit stomatal O3 uptake under high ambient O3
levels. Caution is thus recommended in using AOT40 as a standard
for Z. serrata protection in Japan. Response data in the ﬁeld or free-278

Y. Hoshika et al. / Atmospheric Environment 55 (2012) 271e278

air experiments are insufﬁcient in East Asia. Monitoring of O3 injury
and biomass reduction may help to validate the spatial maps of O3
risks in East Asia and develop the assessment approach in future.
Acknowledgments
This work was supported by JSPS Fellowships for Young Scientists. We thank the staff of the experimental station at University ofTokyo Tanashi Forest. Dr. Masayuki Takigawa is acknowledged forproviding ozone and climate data in Japan. We also thank Dr.
Makoto Watanabe and Dr. Alessandra De Marco for valuable
discussion and kind advice.
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