History effect of light and temperature on monoterpenoid emissions from Fagus sylvatica L.

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History effect of light and temperature on monoterpenoid emissions
from Fagus sylvatica L.
M. Demarckea, J.-F. Müllera, N. Schoona, H. Van Langenhoveb, J. Dewulfb, E. Joób, K. Steppec,
M.?Simpragac, B. Heineschd, M. Aubinetd, C. Amelyncka,*
aBelgian Institute for Space Aeronomy, Ringlaan 3, B-1180 Brussels, Belgium
bResearch Group Environmental Organic Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
cLaboratory of Plant Ecology, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
dUnité de Physique des Biosystèmes, Gembloux Agro-Bio Tech, Université de Liège, Gembloux, Belgium
a r t i c l e i n f o
Article history:
Received 8 April 2010
Received in revised form
27 May 2010
Accepted 28 May 2010
Keywords:
Monoterpene
Monoterpenoid
Fagus sylvatica L.
Emission algorithm
MEGAN
PTR-MS
a b s t r a c t
Monoterpenoid emissions from Fagus sylvatica L. trees have been measured at light- and temperature-
controlled conditions in a growth chamber, using Proton Transfer Reaction Mass Spectrometry (PTR-MS)
and the dynamic branch enclosure technique.
De novo synthesized monoterpenoid Standard Emission Factors, obtained by applying the G97 algo-
rithm (Guenther, 1997), varied between 2 and 32 mg gDW
and September, probably due to senescence.
The response of monoterpenoid emissions to temperature variations at a constant daily light pattern
could be well reproduced with a modified version of the MEGAN algorithm (Guenther et al., 2006), with
a typical dependence on the average temperature over the past five days.
The diurnal emissions at constant temperature showed a typical hysteretic behaviour, which could also
be adequately described with the modified MEGAN algorithm by taking into account a dependence on
the average light levels experienced by the trees during the past 10e13 h.
The impact of the past light and temperature conditions on the monoterpenoid emissions from
F. sylvatica L. was found to be much stronger than assumed in previous algorithms.
Since our experiments were conducted under low light intensity, future studies should aim at con-
firming and completing the proposed algorithm updates in sunny conditions and natural environments.
?1h?1and showed a strong decline in late August
? 2010 Elsevier Ltd. All rights reserved.
1. Introduction
Vegetation plays an important role in eartheatmosphere inter-
actions due to its importance for the carbon cycle but also as
a source of a variety of reactive volatile organic compounds. The
global annual flux of non methane volatile organic compounds
(NMVOC) emitted from vegetation is estimated to be 1150 Tg C y?1
(Guenther et al.,1995). With respective estimates between 454 and
601 Tg C y?1and between 32 and 127 Tg C y?1, isoprene and
monoterpenes represent a large part of the NMVOC flux (Arneth
et al., 2008). The large variability of these estimates, especially for
monoterpenes, reflects a lack of observations for constraining the
emission models. Whereas on a global scale monoterpene emission
rates are only w15% of isoprene emission rates, a recent NMVOC
inventory predicts equal isoprene and monoterpene emission rates
in Europe (Karl et al., 2009), showing the relative importance of the
latter species in Europe.
Accurate estimates of these emissions are needed, because
atmospheric oxidation of these compounds has an important
impact on the budget of oxidants, in particular ozone (O3) and the
hydroxyl radical (OH) (Seinfeld and Pandis, 1998). Furthermore,
isoprenoids represent a large source of Secondary Organic Aerosol
(SOA) due to the gas-to-particle conversion of low-volatility
oxidation products (Kulmala et al., 2004), and the large variability
on global monoterpene emission rates results in very high uncer-
tainties on bottom-up estimates of global biogenic SOA fluxes
(Hallquist et al., 2009).
Many plant species (e.g. most conifers) store monoterpenes in
special storage tissues or organs and the diffusion of monoterpenes
out of these structures is driven by temperature (Kesselmeier and
Staudt, 1999). However, several plant species, which lack these
storage compartments, are known to emit de novo biosynthesized
* Corresponding author. Tel.: þ32 2 373 03 90; fax: þ32 2 374 84 23.
E-mail address: crist.amelynck@aeronomie.be (C. Amelynck).
Contents lists available at ScienceDirect
Atmospheric Environment
journal homepage: www.elsevier.com/locate/atmosenv
1352-2310/$ e see front matter ? 2010 Elsevier Ltd. All rights reserved.
doi:10.1016/j.atmosenv.2010.05.054
Atmospheric Environment 44 (2010) 3261e3268

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monoterpenes. These emissions are driven by light and tempera-
ture in a similar way as for isoprene emissions (Staudt and Seufert,
1995). Moreover, they appear also to depend on light and temper-
ature levels experienced by the plant in the previous hours, days or
even weeks. The dependence on temperature during previous days
or weeks has been observed in the case of isoprene (Monson et al.,
1994; Sharkeyet al.,1999; Pétronet al., 2001; Rapparini et al., 2004)
and 2-methyl-3-buten-2-ol (MBO) (Gray et al., 2003, 2006). This
dependence is apparently due to changes in the concentration of
enzymes responsible for the production of these compounds
(Schnitzler et al., 1997) and is consistent with their hypothesized
role as thermal protectant (Sharkey et al., 2008). Since non-
oxygenated monoterpenes might contribute to heat stress resis-
tance (Copolovici et al., 2005), temperature history effects as
observed for isoprene can be expected for monoterpenes as well.
Indeed, dependence on past temperature and light levels has been
reported for (de novo synthesized) monoterpene emissions from
Quercus ilex L. (Staudt et al., 2003). The acclimatization time was
observed to vary from a few days to several weeks, and down-
regulation of the emission capacity was found to be slower than
upregulation. In addition, monoterpene emissions are expected to
depend on past environmental conditions during the previous
minutes or hours, due to the existence of transient storage pools, as
suggested for instance by the observed temporal dynamics of13C
incorporation into newly synthesized monoterpenoid emissions
(Noe et al., 2006, 2010). The time-lag between monoterpene
production and emission is compound-specific and depends on
the Henry’s law constant and the octanol/water partitioning
coefficient.
Dependence of emissions on past radiation levels is suggested
from the observed hysteretic behaviour of monoterpene emissions
from Fagus sylvatica L. reported by Dindorf et al. (2005) in natural
environmental conditions, with higher emissions in the afternoon
than in the morning at constant light and temperature levels. Note
that dependence on past radiation levels could be (at least partly)
due to leaf heating (Gray et al., 2006).
The history effects observed for isoprene emissions have been
parameterized in the algorithm of Guenther et al. (1999, 2006).
However, the shape of the response curve to past weather condi-
tions is highly uncertain, despite its demonstrated importance in
the simulation of seasonal variations of isoprene emissions.
Furthermore, its applicability to the emissions of other NMVOCs is
questionable.
Due to the strong co-variation of temperature and light in
natural conditions, it is often difficult to separate the effects of both
parameters on BVOC emissions. Therefore the present study
focuses on the light and temperature dependence of monoterpene
emissions by F. sylvatica L., a common European tree species,
measured under controlled light and temperature conditions in
a growth chamber.
2. Experimental set-up and methods
Experiments were carried out successively on two three-year
old beech (F. sylvatica L.) trees. Both trees were grown in outdoor
conditions and were allowed to acclimate to the growth chamber
conditions for at least one month prior to the start of the
measurements. VOC emissions were obtained by putting a single
branch of each tree in a dynamic enclosure system and contin-
uously monitoring the emitted species with a Proton Transfer
Reaction MassSpectrometer
measurements were occasionally complemented by enclosure
air sampling, followed by off-line analysis by Thermal Desorp-
tion Gas Chromatography Mass Spectrometry (TD-GC-MS) for
VOC speciation.
(PTR-MS). These continuous
2.1. Controlled environment
In the growth chamber (2 ?1.5 ? 2 m; height ? width ? length)
the trees were subjected to a controlled light and temperature
regime. The daily light pattern was simulated by varying the light
intensity in eight steps by means of a set of 40 fluorescent lamps
(type PHILIPS Master TL-D fluorescent lamps 36W/830 warm
white, super 80). The maximum photosynthetic photon flux
density (PPFD) thatwasobtained
150 mmol m?2s?1. The incident PPFD was monitored by a quantum
sensor (LI-190SA, LI-COR, USA), positioned next to the branch
enclosures at the same height of the leaves of the enclosed branch.
The daily PPFD pattern imposed on the enclosed branch of the
second tree is shown in the upper graph of Fig. 2 and is similar to
the one imposed on the enclosed branch of the first tree.
For the second tree, a horizontal Teflonated grid was used to
gently flatten the leaves and to avoid leaf overlap with the aim to
ensure a homogeneous light distribution over the leaves enclosed.
The total leaf area and total leaf dry weight were 0.181 m2and
0.89 g for the enclosed branch of the first tree and 0.0120 m2and
0.59 g for the enclosed branch of the second tree.
The temperature in the growth chamber was controlled by
means of an air conditioning system. During the experiments with
the first tree, daily averaged leaf temperatures of the enclosed
branch were 21 (13e16/07),19.5 (17e18/07) and 18?C (20e22/07).
Measurements taken during temperature transition periods were
excluded from the analysis. During the experiments with the
second tree, the leaf temperature for the enclosed branch varied
between 17 and 27?C, as shown in Fig. 3 (upper graph). The air
temperature outside and inside the enclosures was monitored by
thermistors (type 10k, NTC, Omega, NL). Leaf temperature was
measured byan infrared thermocouple (type IRt/c.1X, Exergen, MA,
USA), mounted in a Teflon housing and installed in the cuvette
about 5 mm under the surface of a single beech leaf. Relative
humidity sensors were installed in the outlet line of each cuvette
(type HIH-3610, Honeywell, NJ, USA) and in the growth chamber
itself (type RHa, Rotronic, CH).
atbranchlevelwas
2.2. Branch enclosure system and incoming air supply system
The dynamic branch enclosure system consists of a trans-
parent cylindrical box with a volume of 12.2 L and is shown in
Fig. 1. Dynamic enclosure system containing a branch of a Fagus sylvatica L. tree
(second tree).
M. Demarcke et al. / Atmospheric Environment 44 (2010) 3261e3268
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Fig. 1. The external frame is made of a transparent poly-
methylmethacrylate (PMMA) base plate, three PMMA rings and
three aluminum bars, which hold a cylindrical 50 mm thick per-
fluoroalkoxy Teflon (PFA) envelope (Norton, Saint-Gobain Perfor-
mance Plastics, NJ, USA) with a solar transmission of 96%. The
base plate contains two PFA gas feedthroughs (bulkheads) for
incoming and exiting air, as well as a Teflon feedthrough for
electrical connections inside the cuvette. The emitted biogenic
volatile organic compounds (BVOCs) and the incoming air are
efficiently homogenized by means of a Teflon ventilator, which is
Fig. 2. Hourly averaged PPFD values (upper graph) and monoterpenoid emission rates for the second tree (lower graph), with (circles) and without (diamonds) correction for
nighttime emissions. The values represent averages over the entire experimental period.
Fig. 3. Temporal evolution of leaf temperature and monoterpenoid emission rates (mg m?2h?1) for the enclosed branch of the second beech tree.
M. Demarcke et al. / Atmospheric Environment 44 (2010) 3261e3268
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mounted on the base plate. The air exit opening of the cuvette is
sufficiently large to avoid overpressure in the cuvette. While
enclosing the branch in the cuvette, extreme care was taken not
to bend the branch too much and not to injure any leaves, in
order to avoid unwanted stress-induced BVOC emissions.
Ambient air from above the roof of the building was pumped by
a diaphragm pump (MD4, Pfeiffer Vacuum, Germany) and purified
bya dust filter (2 mm pore size Zefluor? PTFE Membrane Filter, Pall,
MI, USA) and an ozone filter, consisting of a set of 12 MnO2-coated
copper nets (type ETO341FC004, Ansyco, Germany) housed in an
aluminum filter holder. The air was subsequently sent through a set
of two active coal filters (Airpel 10, Organosorb 10-CO, Desotec,
Belgium), the combination of which resulted in an optimal pore
size distribution for absorption of VOCs. To prevent carry-over of
carbon powder a second dust filter was placed downstream the
activecoal filters. The purified air was then distributedtothree flow
meters (5860S (0e30 L min?1), BROOKS Instrument, PA, USA), all
followed by manual ball valves (type SS-43S4, Swagelok, OH, USA).
By adjusting the valve settings, all cuvettes were provided with
identical dust-, O3- and VOC-free air flows of typically 5 L min?1
(at standard conditions of pressure (1013.25 hPa) and temperature
(293 K)). Ozone levels in the incoming air were regularlychecked at
the cuvette inlet with an ECC Ozonesonde (EN-SCI, Inc., Boulder,
USA) and were found to be below 2 ppbv at all times.
Part of the BVOC-enriched air flow exiting each of the cuvettes
was continuously pumped through PFA tubes towards a PFA gas
multiplexer. The rest of the outgoing cuvette air was sent into the
growth chamber.
2.3. BVOC analysis
A small part (about 20 mL min?1) of the 1 L min?1BVOC-
enriched air flow which was sampled from the cuvettes was
introduced in a high sensitivity Proton Transfer Reaction Mass
Spectrometer (hs-PTR-MS, Ionicon Analytik GmbH, Austria). This
sensitive and fast on-line VOC analyzer is based on the soft
chemical ionization of analyte molecules by proton transfer reac-
tions with hydronium (H3Oþ) ions. Detailed information on the
technique can be found in a number of extensive review articles
(de Gouw and Warneke, 2007; Blake et al., 2009). In the present
experiments, the PTR-MS was operated at a drift tube pressure of
2.2 mbar and an E/N value of 140 Td (1 Td ¼ 10?17V cm2). The
temperature of the capillary inlet line and the drift tube reactor
were kept at 333 K.
The PTR-MS ion signal at m/z 137 (protonated monoterpene,
C10H17
terpene calibration was performed regularly by using a gravimet-
rically prepared mixture of a-pinene (0.47 ppmv) and sabinene
(0.41 ppmv) in nitrogen (Apel-Riemer Inc., Denver, CO, USA), with
a certified accuracy of 5%.
Cuvette air samples were taken occasionally and analyzed off-
line by TD-GC-MS (Joó et al., 2010) to determine the monoterpene
emission pattern. These analyses revealed the presence of linalool
which also contributes to the ion signal at m/z 137 and therefore
interferes with monoterpene detection. Consequently, the BVOC
emissions that were inferred from the PTR-MS ion signal at m/z 137
included both monoterpenes and linalool and will be called mon-
oterpenoid emissions hereafter. A fraction of the ion signal at m/z
137 can also be due to the emission of a-farnesene, a sesquiterpene
which was also observed by TD-GC-MS (Joó et al., 2010). However,
this fraction was estimated to be at most 3e5% and was therefore
neglected in the further analysis.
The procedure to determine accurate monoterpenoid emission
rates, taking into account the experimentally determined mono-
terpene calibration factor, the ratio of the detection sensitivity of
þ) was used to monitor the sum of monoterpenes. Mono-
monoterpenes (mainly sabinene) to the one of linalool at m/z 137,
as well as the fractional contribution of both species to the sum of
monoterpenoids (as determined by TD-GC-MS), has been described
in detail in by Joó et al. (2010).
2.4. Emission algorithms
Monoterpene emissions by F. sylvatica L. are known to be
temperature and light dependent. Since, however, small nighttime
emissions have been observed, probably due to a temperature-
dependent release from non-specific storage pools (Schuh et al.,
1997), we write the emission (E in mg m?2h?1) of monoterpenoids
by F. sylvatica L. as
E ¼ Ensþ Ep
where Ensis the newly synthesized emission component and Ep
represents the release from storage pools. The light and tempera-
ture-dependent part, Ens, has been often described by the emission
algorithm of Guenther (1997) originally developed for isoprene:
(1)
Ens;G97¼ 3G97$gT;G97$gP;G97
where 3G97[mg m?2h?1] is a standard emission factor (SEF), i.e. the
emissionrateatstandardizedconditions(30?C,1000mmolm?2s?1),
typical for the tree considered; gT,G97 and gP,G97 describe the
dependence of the emissions on temperature and photosyntheti-
cally active radiation, respectively. In the formulation of Guenther
(1997), 3G97is constant; however, the SEF for Fagus sylvatica L. is
known to show a significant decrease between spring and autumn
probably associated with the phenological development (i.e. the
age) of the leaves (Schuh et al., 1997; König et al., 1995). We adopt
therefore the more general expression:
(2)
Ens ¼ 3$gage$gT$gP
where gageaccounts for these variations due to phenology. Several
choices are possible for the response functions gT and gP: (1)
Guenther (1997) (G97), (2) Schuh et al. (1997) (S97), (3) Guenther
et al. (2006) (G06), (4) Gray et al. (2006) (Gray), and (5) a modi-
fied form of the G06 algorithm (G06a), with parameters fitted using
the measurements presented in the next Section.
The G97 and G06 models were originally developed for isoprene
emissions using experimental emission rate data from several tree
species; the S97 algorithm was developed using sunflower as
a model plant and beech to confirm its applicability for other plant
species; the Gray algorithm was developed to parameterize the
impact of both instantaneous and past temperatures for methyl-
butenol (MBO) emissions from needles of ponderosa pine trees.
The response function gTin the G97 algorithm (Guenther,1997)
is given by:
?CT1$ðT?TSÞ
CT3þ exp
CT1¼ 95 000 J mol?1, CT2¼ 230 000 J mol?1and CT3¼ 0.961 are
empirical coefficients, R ¼ 8.314 J K?1mol?1is the universal gas
constant, T is leaf temperature [K], TM¼ 314 K, and TS¼ 303 K. The
corresponding light response function is given by:
(3)
gT;G97¼
exp
R$T$TS
?CT2$ðT?TMÞ
?
R$T$TS
?
(4)
gP;G97¼ CL;G97$
aG97$L
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1 þ a2
G97$L2
q
(5)
where L is the photosynthetic photon flux density (PPFD) in
mmol m?2s?1, whereas aG97 ¼ 0.0027 and CL,G97 ¼ 1.066 are
empirical coefficients.
M. Demarcke et al. / Atmospheric Environment 44 (2010) 3261e3268
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Whereas the temperature dependence of the emissions
according to Schuh et al. (1997) is very similar to the response
function gT,G97, the light dependence of the S97 algorithm is
a sigmoidal curve expressed as:
gP;S97¼ CL;S97$
0
@
B
aS97$L
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1 þ a2
S97$L2
q
1
A
C
2
(6)
where aS97and CL,S97are equal to aG97and CL,G97, respectively.
The temperature response function in Gray et al. (2006) which
achieves the best agreement with their MBO flux measurements
involves a correction factor to the G97 algorithm:
?
gT;Gray¼ gT;G97$
0:822$T ? T0
30
þ 0:805$T7d? T0
30
? 0:601
?
(7)
where T0¼ 273 K and T7dis the average daily maximum temper-
ature for the previous 7 days.
The isoprene emissionalgorithm in MEGAN(Model of Emissions
of Gases and Aerosols from Nature) (Guenther et al., 2006) incor-
porates a dependence of the emissions on leaf age and soil mois-
ture, as well as updated temperature and light response functions
accounting for the observed role of past meteorological conditions.
Both MEGAN (G06) and a generalized form of the MEGAN algo-
rithm (G06a) will be tested against our measurements. The
temperature response function of G06 is:
?
with
?
R
gT;G06¼ Eopt;G06$
CT2$expðCT1$xÞ
CT2? CT1$ð1 ? expðCT2$xÞÞ
?
(8)
x ¼
where R, CT1and CT2are as in Eq. (4); Eopt,G06ais the maximum
normalized emission capacity, and Topt,G06ais the temperature at
which Eopt,G06aoccurs. These quantities depend on the average leaf
temperature over the past 24 h (T24 h) and the past m days (Tmd) and
are given by:
T?1
opt;G06? T?1?
(9)
Topt;G06a¼ 313 þ 0:6$ðTmd? 297Þ
(10)
Eopt;G06a¼ 2:038$expða1$ðT24h? 297Þ þ a2$ðTmd? 297ÞÞ
(11)
where m, a1and a2are adjustable parameters (note that m ¼ 10,
a1¼ a2¼ 0.05 in MEGAN).
The light response function in G06a is expressed as:
gP;G06a¼ CL;G06a$
aG06a$L
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1 þ a2
G06a$L2
q
(12)
with
aG06a¼ a3$ð0:004 ? 0:0005$lnðP10dÞÞ
(13)
CL;G06a¼ 0:0468$expða4$ðPnh? P0ÞÞ$P0:6
where Pnhand P10d[mmol m?2s?1] are the PPFD averages over the
last
n
hours and10days,
200 mmol m?2s?1for sunlit leaves and 50 mmol m?2s?1for shaded
leaves, respectively. a3and a4are adjustable parameters (n ¼ 24,
a3¼ 1 and a4¼ 0.0005 in MEGAN). Due to the constant diurnal
10d
(14)
respectively,
P0
isequalto
PPFD pattern in our experiments, P10dand P24 hare constant and
both equal to 50 mmol m?2h?1.
3. Results and discussion
The first part of this section deals with small nighttime ion
signals that were observed at m/z 137, and how these were
accounted for in the derivation of standard emission factors for the
newly synthesized monoterpenoids. Subsequently, the perfor-
mance of the different emission algorithms in describing the
experimental results will be assessed and the effect of previous
temperature and light conditions on the emissions will be
quantified.
3.1. Nighttime emissions and standard emission factors
The temporal evolution of the monoterpenoid emission rate
from a branch of the second F. sylvatica L. tree is shown in Fig. 3,
along with the variation in leaf temperature, fromAugust 24th until
October 15th.
Gaps in the data are mainly due to instrumental problems and
power failures. Monoterpenoid emissions clearly followed the daily
imposed PPFD profile (Fig. 2) and responded to a large extent to leaf
temperature variations. However, in late September and early
October this reponse was masked by a general decline of the
emissions, which was observed over the entire period and which is
discussed in more detail in Section 3.2.
This light and temperature dependence of monoterpene emis-
sions by F. sylvatica L., with emissions close to zero at darkness, is in
agreement with what has been reported previously by several
authors (Schuh et al., 1997; Spirig et al., 2005; Holzke et al., 2006;
Moukhtar et al., 2005; Dindorf et al., 2006). In the beginning and
at the end of the experimental period the emission rate at zero
PPFD was found to be negligible. Between August 28th and
September 4th and between September 9th and September 18th,
small PTR-MS ion signals at m/z 137 appeared in dark conditions,
amounting to at most 12% of the maximum daytime emission rate,
with the exception of one day at which a value of 20% was reached
(September 2nd). Schuh et al. (1997) previously reported small
emissions of a-pinene at zero light flux in growth chamber exper-
iments on F. sylvatica L., indicating the presence of non-specific
storage pools. The monoterpenoid emission pattern in our experi-
ments, however, contained no a-pinene but was mainly composed
of sabinene, linalool, ocimene and an unidentified monoterpene, as
determined by GCeMS analysis of sampled air from the branch
enclosure (Joó et al., 2010). Sabinene was the predominant C10H16
compound and linalool was always present in non-negligible
amounts.
Although the nighttime emission rates calculated from the
PTR-MS ion signal at m/z 137 are considered to be monoterpenoid
emission rates, it cannot be excluded that other BVOCs (e.g.
sesquiterpenes for which temperature-dependent dark emissions
can be expected) also contributed to this ion signal to some
extent.
In order to separate this limited light independent contribution
from the major light dependent contribution to the monoterpenoid
emission rates, linearly interpolated dark emission rates were
subtracted from the hourly averaged daytime emission rates.
Emission rates obtained at 11 PM of the day of the measurement
and 11 PM of the previous day were used for this interpolation. The
influence of this correction on the hourly averaged emissions over
the entire experimental period is shown in Fig. 2. In the following
discussion, the corrected, daytime emission data are compared
with literature data and tested against existing emission algorithms
for newly synthesized monoterpenoids.
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The values of the daily standard emission factors (3G97, see
Eq. (2)) inferred from the measured monoterpenoid emission rates
of the second tree are found to vary between 100 and
1550 mg m?2h?1or 2 and 32 mg gDW
literature data reported for F. sylvatica L. in recent years (Schuh
et al., 1997; Kahl et al., 1999; Spirig et al., 2005; Moukhtar et al.,
2005; Dindorf et al., 2006), which have been recently compiled in
Table 3 of Dindorf et al. (2006), and with the values adopted in the
two most recent European plant-specific BVOC inventories,
22.1 mg gDW
et al., 2009).
?1h?1, in good agreement with
?1h?1(Karl et al., 2009) and 10.0 mg gDW
?1h?1(Schurgers
3.2. Response of monoterpene emissions to temperature
variations at constant daily PPFD pattern
The temporal variation of the standard emission factors 3G97for
the second tree is shown in Fig. 4.
The SEFs are normalized by their value on August 24
(1020 mg m?2h?1). Two features are prominent: a general decrease
of the SEF during the course of the experimental period, very
probably related to senescence, and a large peak around September
1st. The effect of senescence is crudely parameterized by an
exponential decrease of the leaf age activity factor (Eq. (3)) with
time:
gage¼ expð ? ðt ? t0ÞÞ=ts
where ts (¼18 days) is a characteristic time for the effect of
senescence, fitted fromthe measurements, and t0is August 24th. As
seen in Fig. 4, gagedecreased by almost an order of magnitude in
less than 6 weeks. Although such a fast decline might be partly due
to the unusual environment of the growth chamber, it is qualita-
tively consistent with the seasonal decline of the SEFs reported e.g.
by Schuh et al. (1997).
The maximum SEF on September 1st (w50% above the initial
SEF on August 24th) occurred at the end of a 5-day period with
warmer temperatures (up to 26?C, see Fig. 2). Taking the effect of
senescence (i.e. gage) into account, the emission capacity approxi-
mately doubled in response to the 5?C warming imposed on the
tree in this period. In the following days, the decrease in temper-
ature was immediately followed by an abrupt decrease in SEF
amounting to a factor of 5 in only one week. The dependence of SEF
on temperature history suggested by this pattern is much stronger
(15)
than in existing emission algorithms accounting for temperature
history effects, such as MEGAN and the algorithm developed by
Grayet al. (2006) (green and yellowcurves on Fig. 4). It is, however,
similar in magnitude to the acclimation of isoprene emission
capacity by Quercus macrocarpa to changes in growth temperature
observed by Pétron et al. (2001): a 5?C warming was found to
double the emission capacity of Q. macrocarpa, while a subsequent
cooling led to a strong reduction in SEF, bya factor up to 4 on a time
scale of several days. The monoterpene emission capacity of Q. ilex
has been observed by Staudt et al. (2003) to respond even more
drastically to the temperature regime: in so-called shaded condi-
tions (PPFD ? 300 mmol m?2s?1), the emission capacity increased
by almost an order of magnitude in less than one week when the
growth temperature was increased by 10?C.
The observed temporal evolution of the daily SEF values was
used to constrain the temperature dependence of the algorithm
G06a, by minimizing the root mean square deviation between
modeled and observed daily SEFs. The best match was found when
including a strong dependence on the average temperature over
the last 5 days (m ¼ 5), with a2¼ 0.21 in Eq. (11). Dependence on
the average temperature over the last day was weak (a1¼ 0.03).
The temporal evolution of the SEF for the first tree (Fig. 5)
provides some confirmation of the parameterized influence of past
temperature on the emissions.
The reasons for the small increase during the first days (before
16/07) are unclear, since temperature remained constant during
that period. Afterwards, the SEF steadily declined in response to
a decrease in temperature, in agreement with the G06a algorithm
constrained by data from the second tree, and in reasonable
agreement with the algorithm of Gray et al. (2006). The effect of
senescence was assumed to be unimportant during that period.
3.3. Response of monoterpenoid emissions
to PPFD variations at fixed temperatures
Fig. 6 illustrates the response of monoterpenoid emissions to
PPFD during selected days for the second tree. Temperature was
constant during each series of days (21?C on 24e26/08, 18?C on
5e6/09, 24?C on 30/09e01/10).
The emissions were found to be consistently and significantly
lower in the morning compared to the afternoon at the same PPFD
level, which resulted in a genuine hysteretic behaviour. Note that
Fig. 4. Daily standard emission factor 3G97derived from the measurements with the
second tree, and normalized by its value on 24/08 (stars), and comparison with
modeled values based on three algorithms for the temperature response: MEGAN
(green), Gray et al. (yellow) and the adjusted algorithm G06a (red). The assumed
senescence factor (gage) used in the calculations and inferred from the data is also
shown.
Fig. 5. Standard emission factor 3G97derived from the measurements with the first
tree, and normalized by its value on 13/07 (stars), and comparison with modeled
values based on MEGAN (green), Gray et al. (yellow) and the algorithm G06a adjusted
using the measurements obtained with the second tree shown in Fig. 4 (red).
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the maximal difference between morning and afternoon emissions
is found to be much larger than the statistical error on the emis-
sions. A similar behaviour was also observed for the first tree, for
which the emissions were measured in July 2007 (data not shown).
The hysteresis phenomenon was previously reported in the litera-
ture but has not been accounted for in existing BVOC emission
algorithms. Dindorf et al. (2005) reported a significant delay in
monoterpene emission from a F. sylvatica L. tree in the early
morning, which could be better reproduced by the algorithm of
Schuh et al. (1997) (S97, Eq. (6)) than by the the G97 algorithm.
However, S97 was found to underestimate emission rates in the
early evening in their study. The hysteretic behaviour has been
described for other monoterpene emitting broadleaf tree species as
well, e.g. the evergreen Q. ilex (Ciccioli et al., 1997).
The hysteresis might reflect the existence of monoterpenoid
storage pools (Noe et al., 2010) and/or an acclimation to environ-
mental conditions. In any case, it suggests a dependence of the
emission rates on past PPFD levels. The S97 algorithm clearly failed
to reproduce the diurnal cycle observed in this study, with large
underestimations found at low PPFD levels (Fig. 6a). Although the
MEGAN model includes a dependence on PPFD history, it also failed
to reproduce the observed hysteresis (Fig. 6a). This was due to the
choice of the averaging periods in G06, the past PPFD averages P10d
and P24 hbeing initially constant in our experimental set-up.
The observed diurnal cycle of emissions can be reproduced only
when assuming a dependence of the emissions on past PPFD fluxes
averaged over a shorter period (n ¼ 10e13 h, see Fig. 6). The
averaging period n and the parameters a3and a4of the adjustable
algorithm, G06a, have been obtained by minimizing the root mean
squared deviation between modeled and measured emission rates.
The values obtained for a4(0.0025e0.0038) are 5e8 times larger
than in MEGAN, reflecting the significance of the PPFD history
effect suggested by the measurements. The values for a3(1.9 at the
startof the experimental period, 5e10 at laterstages) are also larger
than in MEGAN (a3¼ 1), indicating that emission saturation occurs
at lower PPFD values compared to MEGAN, as clearly seen on
Fig. 6bec. The increase of a3during the course of the experimental
period is presumably related to senescence and acclimation to low
light levels and the associated decrease in emission capacity, as
discussed in the previous subsection.
4. Conclusion
The response of monoterpenoid emissions of two young
F. sylvatica L. trees to changes in light intensity and temperature
has been investigated in controlled growth chamber conditions.
The observations show a clear dependence of the emissions on the
past light and temperature levels experienced by the trees. In
addition, a strong decline of the emission capacity was observed
in late August and September, with an e-folding time of 18 days,
most probably related to leaf senescence.
The response of the monoterpenoid emission capacities to
temperature variations at a constant daily PPFD pattern could be
fairly well described bya modified version of the MEGAN algorithm
(Guenther et al., 2006) originally developed for isoprene emissions.
The results of our study suggest a much stronger dependence of the
emission rates on the past temperature conditions than in previous
algorithms (Guenther et al., 2006; Gray et al., 2006), and a typical
dependence on the average temperature of the past five days.
The observed diurnal cycle of the emissions confirms the
hysteretic behaviour which has been previously described, with
lower emissions in the morning than in the afternoon at the same
PPFD values. This effect can be parameterized with a modified
version of the MEGAN algorithm, through a dependence of the
emissions to the average PPFD over the past 10e13 h. In addition,
emission saturation is observed to occur at lower PPFD values
compared to MEGAN.
Since the experiments were performed on young trees and at
PPFD levels which are typical for shaded conditions, additional
enclosuremeasurementsinnaturaloutdoorconditionsarerequired
to confirm the strong dependence on past temperature and light
observed in this study, and to further refine the adapted version
of the MEGAN algorithm developed from our measurements. In
particular, the seasonal evolution of the model parameters in
response to phenological development will require further inves-
tigation. Finally, the applicability of the modified MEGAN algorithm
Fig. 6. Measured monoterpenoid emission rates (mg m?2h?1) as a function of PPFD
(mmol m?2s?1) on (a) August 24e26, (b) September 5e6 and (c) September 30-
October 1, and comparison with different algorithms: G97 or G06 (in blue), S97 (in
green), and the adjustable algorithm G06a (in red). The values of the fitted parameters
n, a3and a4(see Eqs. (12)e(14)) are indicated for each period.
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toBVOC emissions byother plant species will clearlyrequire a more
systematicinvestigationontheenvironmentaldependenceof these
emissions.
Acknowledgements
The authors would like to thank the Belgian Science Policy Office
(BELSPO) (contract number SD/TE/03A) for funding the IMPECVOC
(Impact of Phenology and Environmental Conditions on BVOC
Emissions from Forest Ecosystems) research project. Support
from the Research Foundation e Flanders (FWO) (contract numbers
B/07659/02 and G/0031/07) is also gratefully acknowledged. We
also wish to thank Philip Deman, technician of the Laboratory of
Plant Ecology, and the technical personnel of the Belgian Institute
for Space Aeronomy for their outstanding support.
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