Presented at the 3rd ICOS Science Conference in Prague, Czech Republic, 11-13 Sep 2018.

1. Ozone deposition effects on carbon assimilation in
Mediterranean forests
ICOS Conference, Prague, 11-14 September 2018
Silvano Fares
Council for Agricultural Research and Economics (CREA), Rome, Italy.
http://www.icos-italy.it/

2. 1. Stomatal sink. Stomatal opening regulate leaf ozone uptake and largely contribute to ozone
removal in the atmosphere. Main reason for damage to leaves. Stomatal conductance to ozone
is a suitable metrik for ozone-risk assessment.
O3 uptake
2. Surface deposition on cuticles and soil. Adsorption processes
O3
O3
O3
3. Chemistry in the gas phase. Reactions between BVOC, NO and ozone
O3 O3
O3
Ozone budget in plant ecosystems
4. Ozone is photochemically produced
under high VOC and NOx concentration!

3. Ozone in low troposphere: an increasing
threat for plants
Ozone is an oxidant molecule that causes serious
damage to plants. It is at high concentration
mainly in and downwinde of urban and
industrialised areas and its concentration becomes
a risk at doses higher than 40 ppb
In the United States alone, ozone is
responsible for an estimated $500 million in
reduced crop production each year! (EPA,
2010).

4. • Scientific consensus is that flux estimates are more
accurate because they include analysis of plant
physiology and different environmental parameters
that control the uptake of ozone (not just the
exposure)
Regulations to assess ozone risk to plants
Stomatal
conductance
Tropospheric O3
concentration
Fares et al. J. Exp. Bot. 2010

5. 5
Fluxes are measured from the eddy covariance (EC) between vertical wind speed and
gas concentration (O3, VOC, CO2, H2O), with observations 10 times per second
Water flux: Stomatal conductance is calculated from measured transpiration by inversion
of Monteith equation, therefore an estimate of stomatal ozone fluxes is possible
Continuous Eddy Covariance flux measurements

6. 2012 2013 2014 2015
Canfora et al. Environ Monit Assess.
• About 600 g CO2 m-2 per year removed by
the forest
• Tot. GPP in 2013: 1566 g (C) m-2 (894 mm
precip.)
• Tot. GPP in 2014: 1768 g (C) m-2 (1100 mm
precip.)
Long term measurements of carbon fluxes in a Holm oak
forest

7. The Hom Oak is a relevant ozone sink
O3
2012 2013 2014
Fares et al. 2014. Agr. For Met.
Atmospheric O3 concentration gradient
from the soil to above the canopy
Ozone fluxes are higher during late spring, when stomatal conductance is high.
Up to 8 g O3 m-2 are sequestrated every year!

8. Ways of O3 sink partitoning: using EC data
• Evaporative/resi
sitve method for
the stomatal
component:
𝑂3sto = 𝑂3 canopy ∙ 0.61 ∙ 𝐺𝑠𝑡𝑜,𝐻2𝑂
• Soil sink:
• Cuticoles:
(Zhang et al., 2002)
(Zhang et al., 2002)
 
)(
)()( 0
stoba
msp
RRR
zeTec
E






Up to 60% of total O3 sink is stomatal

9. Cumulative ozone fluxes do not
correlate well with high ozone
concentrations especially under high
VPD
Duker et al. Biogeoscie. 2018

10. GPP is negatively affected by exposure
to high ozone doses
Case studies on Pinus ponderosa forest, an Orange orchard, and a
Holm oak forest

11. Stomatal ozone fluxes (L2) always correlate better than total
ozone fluxes (L1) with GPP (EC data, years 2012 to 2016)
Fares et al. Env. Scie. Poll. Res. 2018
Carbon assimilation and
ozone sequestration ar
correlated.
The key issue is: how to
discriminate between all the
covarying factors affecting
carbon assimilation?

12. At increasing ground levels of ozone, the slope between GPP and
stomatal ozone deposition decreases in Mediterranean ecosystems
Blodget,
Pine
forest
Lindcove,
Citrus
orchard
Photosynthesis uncoupling from stomatal conductance ay high levels of O3
concentrations
Fares et al. Glob. Ch. Poll. 2013

13. Temporal correlation between GPP (residuals), ozone concentration and stomatal ozone
flux exists
The highest covariance between GPP and stomatal ozone deposition does not occur at
the highest GPP values
The FREQUENCY domain: Usage of Wavelet coherence analysis to
highlight regions of significant temporal correlations in a pine forest
High correlation at daily scale (period ~ 1) was observed
Correlations between stomatal ozone deposition and GPP
Correlations between ozone concentration and GPP
Fares et al. Glob. Ch. Poll. 2013

14. Case 1
Predictors beta multiple R2
F total beta multiple R2
F total beta multiple R2
F total
PAR (umolm-2
s-1
) -0.722 0.489 46407.180 PAR (umolm-2
s-1
) -0.431 0.098 470.028 Soil moisture (%) -0.414 0.115 176.796
VPD (kpa) 0.457 0.492 210.360 VPD (kpa) 0.493 0.156 299.663 PAR (umolm-2
s-1
) -0.438 0.209 159.452
Ta ( o
C) -0.350 0.499 680.680 Ta ( o
C) -0.236 0.162 29.010 VPD (kpa) 0.089 0.215 10.667
Soil moisture (%) 0.087 0.502 320.310 Soil moisture (%) -0.035 0.163 6.161 Ta ( o
C) 0.081 0.217 3.257
R-square 0.5 0.17 0.22
slope 0.86 0.74 0.77
df 48399 4338 1351
F 12198 211 94
Case 2
ET (mmolm-2
s-1
) -0.469 0.483 27355.570 PAR (umolm-2
s-1
) -0.253 0.098 470.028 Soil moisture (%) -0.331 0.115 176.796
PAR (umolm-2
s-1
) -0.308 0.542 3771.650 VPD (kpa) 0.352 0.156 299.663 ET (mmolm-2
s-1
) -0.239 0.214 169.705
Soil moisture (%) 0.072 0.546 213.980 ET (mmolm-2
s-1
) -0.438 0.234 440.230 PAR (umolm-2
s-1
) -0.323 0.233 32.896
VPD (kpa) 0.375 0.547 71.590 Ta ( o
C) 0.115 0.235 5.738 VPD (kpa) 0.126 0.245 21.623
Ta ( o
C) -0.352 0.551 312.320 Soil moisture (%) 0.032 0.236 5.394 Ta ( o
C) 0.121 0.249 7.515
R-square 0.55 0.24 0.25
slope 0.88 0.76 0.78
df 29254 4338 1356
F 7192 267 89.52
Case 3
ET (mmolm-2
s-1
) -0.469 0.483 27355.570 PAR (umolm-2
s-1
) -0.254 0.098 471.990 Soil moisture (%) -0.331 0.115 176.796
PAR (umolm-2
s-1
) -0.308 0.542 3771.650 VPD (kpa) 0.277 0.156 298.684 ET (mmolm-2
s-1
) -0.239 0.214 169.705
Soil moisture (%) 0.072 0.546 213.980 ET (mmolm-2
s-1
) -0.453 0.234 441.996 PAR (umolm-2
s-1
) -0.323 0.233 32.896
VPD (kpa) 0.375 0.547 71.590 [O3 ] (ppb) 0.106 0.237 14.196 VPD(kpa) 0.126 0.245 21.623
Ta ( o
C) -0.352 0.551 312.320 Ta ( o
C) 0.103 0.238 4.598 Ta ( o
C) 0.121 0.249 7.515
[O3 ] (ppb) n.s. n.s. n.s. Soil moisture (%) 0.026002 0.238265 3.5346 [O3 ] (ppb) n.s. n.s. n.s.
R-square 0.55 0.24 0.25
slope 0.88 0.76 0.78
df 29254 4332 1350
F 7192 225.84 90
Case 4
ET (mmolm-2
s-1
) -0.730 0.473 21686.430 G O3 (m s-1
) 0.053 0.085 272.181 G O3 (m s-1
) -0.347 0.240 422.360
G O3 (m s-1
) 0.271 0.525 2639.770 PAR (umolm-2
s-1
) -0.203 0.152 235.276 Soil moisture (%) -0.258 0.293 100.616
PAR (umolm-2
s-1
) -0.242 0.540 813.270 VPD (kpa) 0.385 0.180 99.428 PAR (umolm-2
s-1
) -0.199 0.308 28.848
VPD (kpa) 0.252 0.548 446.420 ET (mmolm-2
s-1
) -0.461 0.225 168.336 Ta ( o
C) 0.134 0.314 10.790
Soil moisture (%) 0.062 0.551 131.650 Ta ( o
C) 0.048 0.226 6.805 ET (mmolm-2
s-1
) -0.056 0.315 2.796
Ta ( o
C) -0.082 0.551065 12.11 Soil moisture (%) 0.143966 0.227684 4.8459 VPD (kpa) n.s. n.s n.s
R-square 0.55 0.23 0.315
slope 0.89 0.79 0.79
df 24184 2937 1332
F 4947 144 153
Blodgett Lindcove Castelporziano
Can we predict GPP using multiple regression linear and non-linear
models? Is ozone a significant predictor?
Multiple regression
linear model: (GPP = b1P
+ b2Q + b3R…+bnN)
Negative sign of
predictor: negative
effect on carbon
assimilation
4 case
studies
Stomatal
ozone
deposition
explains
better than
ozone
concentration
GPP decrease
Ozone
responsible for
up to 19%
reduction in
GPP
Random Forest Analysis of the effects on GPP at three Mediterranean-type ecosystems: Pinus
ponderosa, Citrus sinensis, Quercus ilex

15. Dose–response relationships to
estimate ozone damage based on CEO
via synthetic ozone flux estimation
(FLUXNET data)
CUO = CEO3 ×gs × 1.67 ×3600×10−6, CEO3 is the cumulative O3 exposure
Using dose–response relationships between CUO and biomass reduction, O3 reduces
biomass production and carbon uptake by 4 %–29%, depending on the site and plant
type
Duker et al. Biogeoscie. 2018
View of the OTC facility in Curno, Italy

16. Radiative transfers:
Leaf temperature and
solar irradiation
Photosynthesis &
stomatal conductances
BVOC emission
Air pollutants deposition,
carbon fluxes and
ecosystem services
Proximally sensed data, in situ
gradient measurement
Measurements on site
Literature
Pollutant
concentrations,
meteorological
parameters,
vegetation type
Photosynthetic parameters, e-g- Vcmax, Basal
Emission Factors for BVOC, LAI
Canopy
profile
CO2
H2O R a
R bR cut R stom
R g
Soil processes
Turbulent transport
Leaf
profile
CO2
H2O
Could multi-layer canopy models help to estimate ozone damage?
Validation with EC data

17. GPP
• Unrealistic predictions when
soil water content is not
included among the
parameters driving stomatal
regulation
Performances of photosynthetic apparatus are the most sensitive
parameters of the canopy model
Soil porosity
Velocity of carboxilation changing
over the vegetative season
Optimization routines by Gauss-Marquardt-Levenberg
algorithm (Doherty, 2016).
Aggregated Interpretation of the Energy balance and water
dynamics for Ecosystem services assessment (AIRTREE)

18. The Ball-Berry empirical model (Ball et al., 1987) describes the behaviour of gs as a function of environmental conditions
and net photosynthetic rate as:
𝑔𝑠 = 𝑔0 + 𝑚
𝐴 ∗ 𝑅𝐻
𝐶𝑠
Where g0 is the stomatal conductance at the light compensation point, m is a fitting parameter representing the slope of
the equation, A is photosynthesis (mol m-2 s-1), RH is Relative Humidity (%) and Cs is the molar fraction of CO2 at the leaf
surface (ppm).
Two correction factors are applied to A and gs of the Ball-Berry model. (eq.2). These correction factors are derived
accordingly to Lombardozzi et al (2013 and 2015) on the results reported in Alonso et al., (2013), and in Vitale et al. (2007)
on Q.ilex rensponses to different cumulated ozone dose.
𝐹𝑝𝑂3
= 𝑎 𝑝 ∗ 𝐶𝑈𝑂 + 𝑏 𝑝 𝐹𝑐𝑂3
= 𝑎 𝑐 ∗ 𝐶𝑈𝑂 + 𝑏𝑐
Ozone correction based on dose-response relationship
Stomatal conductance estimation
Where a and b are slope and intercept constants for gs and A with the Cumulative Uptake of O3 (CUO) obtained in controlled experiments.
CUO = CEO3 ×gs × 1.67 ×3600×10−6, CEO3 is the cumulative O3 concentrations.
The core of MLM: stomatal conductance & photosynthesis
View of the OTC facility in Curno, Italy

19. MLM predicts up to 5% GPP reduction due to ozone exposure
Stomatal conductance
correlates better with
EC derived condutance
after correcting for
ozone effect

20. NEE
Solar Radiation
SWC
VPD
G sto
O3 stomatal uptake
The Weight Approach
(Olden et al., 2004 Eco Mod)
Neural network analysis
confirm reductions in
NEE by ozone exposure
Long-term measurements may support the
training and application of NN
Savi et al. In prep.

21. NEP response to stomatal ozone flux in the ECLAIRE network
Neural network analysis shows
very small decrease of NEP in
response to ozone (up to 2 %)
Ozone impact on NEP during the day
changes depending on sites and climate

22. Conclusions
• Direct measurement of ozone fluxes and an accurate partitioning is the way to
determine O3 sinks in the soil-plat-atmosphere continuum
• A large time series is necessary to achieve
statistical significance. More long-term flux
measurements for different ecosystems are
needed, possibly next to manipulative
sites.
• ozone concentration and in particular stomatal ozone fluxes are tightly
correlated at hourly basis with GPP
• Stomatal ozone flux negatively affects carbon assimilation. To which extent? Percent
reduction need to converge between different estimates

23. ICOS (Integrated Carbon Observation System) is
a European Research Infrastructure (ESFRI)
for quantifying and understanding the
greenhouse gas balance of the European
continent
Map of proposed ICOS sites
• The ICOS candidate sites must
obey rigorous quality protocols.
• Advanced Eddy Covariance
systems are set up for long-term
measurements of Greenhouse
gas fluxes.
• The running costs of each
ecosystem station per year may
exceed 70keuro.
• O3 is actually not included in the
protocols, while it could be
measured a very limited costs
(7keuro purchase of a sensor…)

24. Thank you for the attention!
Silvano Fares
Skype: silva_802000
email: silvano.fares@crea.gov.it
Funding Projects:
EXPLO3RVOC (FP7-PEOPLE-2012-CIG, proposal n. 321711)
ECLAIRE (FP7-ENV-2011)
TREECITY (PRIN 2010/2011) CASTEL4, Life MOTTLES
Staff at the Biomet lab at CREA
Alessandro Alivernini, Adriano Conte, Flavia Savi, Tiziano
Sorgi, Valerio Moretti, Filippo Ilardi, Luca Salvati