Diurnal and seasonal variation of monoterpene emission rates for two typical Mediterranean species (Pinus pinea and Quercus ilex) from field measurements—relationship with temperature and PAR

Atmospheric Environment 35 (2001) 4419–4431

Diurnal and seasonal variation of monoterpene emission rates for two typical Mediterranean species (Pinus pinea and Quercus ilex) from field measurementsFrelationship with temperature and PAR ! La! zaro V. Cremades* Danelia Sabillon, " Department de Projectes d’Enginyeria, Universitat Politecnica de Catalunya, ETSEIB, Av. Diagonal, 647 planta 10, 08028 Barcelona, Spain Received 5 July 2000; received in revised form 16 April 2001; accepted 26 April 2001

Abstract Two of the most typical Mediterranean tree species (Pinus pinea [Pp] and Quercus ilex [Qi]) were screened for emissions of monoterpenes during the period of June 1997–July 1998 in the field at a semi-rural location near Terrassa (Barcelona, Spain) using a bag-enclosure sampling method followed by gas chromatography analysis with mass selective detection (GC/MSD). A mean of about eight samples per day were measured. A periodical sampling throughout 1 yr allowed to examine data for long-term influences. The main compounds emitted from Pp were linalool, limonene, trans-ocimene and 1,8-cineole (80% on average). Eighty percent of total emissions in Qi were b-pinene, apinene, myrcene and sabinene, followed by limonene, b-phellandrene, g-terpinene and trans-ocimene (20%). On average, the standard monoterpene emission rate from Qi was approximately three times higher than from Pp. Diurnal and seasonal emission variations were characterized with regard to temperature and PAR. For both species a statistically significant variation in monoterpene emissions was observed between seasons for 1 yr period. For Pp, the seasonal variability not accounted for by PAR and temperature is also estimated and compared with existing models in the literature. r 2001 Elsevier Science Ltd. All rights reserved. Keywords: Monoterpene emission; Modeling; Environmental variables; Seasonal variation; Mediterranean biogenic emissions; Field measurements

1. Introduction In the past years the importance of volatile organic compounds (VOC) emitted by natural sources from the photochemical formation of ozone has been considered (Chameides et al., 1988). Biogenic emissions have been estimated to equal or exceed anthropogenic emissions (Guenther et al., 1995). Monoterpenes are natural VOCs that play a key role in photochemical reactions. Their rapid reaction with atmospheric constituents such as OH radicals affects the lifetime of tropospheric gases. Monoterpenes are in*Corresponding author. E-mail address: [email protected] (L.V. Cremades).

volved in the global carbon budget and in the regional formation of ozone in the troposphere (Fehsenfeld et al., 1992). Apart from being species-specific, emissions of monoterpenes are regulated by many environmental variables such as temperature, light, and humidity, which are the most important (Owen et al., 1997), and seasonal variations, making temporal predictions a process fraught with uncertainties. In Europe, one of the most important sources of tropospheric ozone is the Mediterranean region (Bertin et al., 1997; Staudt et al., 1997; Versino, 1997). However, present knowledge of monoterpene emissions from vegetal species in this area is rather scarce. The Biogenic Emissions in the Mediterranean Area (BEMA) project

1352-2310/01/$ - see front matter r 2001 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 2 - 2 3 1 0 ( 0 1 ) 0 0 2 5 5 - 2

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! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon,

(1993–1997) aimed at quantifying biogenic emissions and evaluating the role of monoterpenes as producers of tropospheric ozone, although only the short term responses to light and temperature of isoprene and monoterpenes emissions were evaluated. So, the complete annual variation of monoterpene field emissions has not been completely studied in the Mediterranean region. Up to date, emission inventories take only these light and temperature influences into account to simulate the temporal variations of emissions over the year (Staudt et al., 2000). There is, however, increasing evidence that a great part of emission variations is due to long term responses to plant phenological processes (Hakola et al., 1998), modifications of growth conditions (Sharkey and Loreto, 1993) or water availability (Bertin and Staudt, 1996). Recently, models have been developed to simulate the seasonal variations of isoprene emissions from Quercus species: Pier and McDuffie (1997) studied emissions from a chambered mature Quercus alba L. throughout the growing season; and Schnitzler et al. (1997) proposed a seasonal variation model from the enzyme activity in Quercus robur L. leaves. For conifers, Staudt et al. (2000) proposed a seasonal monoterpene emission model from potted saplings of Pinus pinea. These above mentioned emission studies were performed in the laboratory under controlled environmental conditions. In the present work, the monoterpene emissions of two typical Mediterranean tree species are studied: Pinus pinea (Pp) and Quercus ilex (Qi). Measurements were performed under ambient conditions in the field on mature plants of natural stands. Bi-weekly or monthly measurements were carried out during years 1997 and 1998. Pinus halepensis was also studied but measurements did not span a complete year, and therefore are not presented. The main goals of this study are (1) to characterize the diurnal and seasonal monoterpene emission cycles for Pp and Qi with regard to temperature and photosynthetically active radiation (PAR) in ambient conditions, and (2) to quantify the seasonal variability not accounted for by PAR and temperature. By measuring monoterpene emissions from the two plant species at periodic intervals throughout an annual cycle, it was possible to observe the magnitude of emission rate variability not accounted for by temperature and PAR alone.

2. Experimental 2.1. Site description The study site is located 20 km from the Mediterranean sea shore (Terrassa, Spain) at 270 m above sea

level. The test area is rather flat and spreads over 4.5 ha. Experimental field measurements were carried out at the border of a small forest close to our research center. This proximity allowed us to make frequent field campaigns and hence cover both daily and annual cycles. Pinus pinea is the dominant tree species followed by Pinus halepensis, Quercus ilex, Populus nigra and Ulmus minor. The forest was selected because its vegetation is quite representative of that growing in the Mediterranean region and, in particular, of Catalonia. The three first species mentioned above (two coniferous and one oak) represent approximately 50% of the present vegetal land cover (Boada, 1997). Land–sea breezes, moderate climate and a small influence of anthropogenic emissions from the surrounding urban areas (the most important anthropogenic emissions come from a road with a vehicle flux of 14000 vehicles/day located 600 m away from the test area) are also the characteristics of this semi-rural site.

2.2. Measurement program Measurements were made at the forest site during the periods of June 1997–June 1998 for Pinus pinea and July 1997–July 1998 for Quercus ilex. Details are presented in Table 1. For both species Pp and Qi measurements were made during daytime between 10:00 and 20:00 h LT (local time), with irregular frequency and at variable hours of the day. A total of 19 days (Julian days) with a mean of eight samples per day were screened for Pp, and 16 days (Julian days) with a mean of seven samples per day for Qi. The number of measuring days per month ranged between 1 and 2. Field measurements were carried out in different branches of the same individual tree at ambient conditions. Environmental variables continuously measured in this work were: temperature (inside and outside the enclosure), relative humidity (inside and outside), wind velocity and PAR. A single branch was used for each sampling day, and was cut at the end of each day in order to weigh its leaves after being dried.

2.3. Sampling and analytical techniques The sampling system is based mainly on personal communications with BEMA project participants. A dynamic flow-through enclosure system (‘‘cuvette’’) was built to measure emission rates at the branch scale. The system was continuously flushed with ambient air and the trace gas emission rates are calculated from the differences in the mixing ratios between the in and outflowing air (Parusel et al., 1993; Seufert et al., 1997).

! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon, Table 1 Sampling dates, number of measurements and mean temperature and PAR conditions for each sampled branch of Pinus pinea (20 yr old) and Quercus ilex (30 yr old) during the whole campaign period of June 1997–July 1998 Date (dd/mm/yy)

Julian day

na

Temperature (1C)

PAR (mmol m
2 s
1)

Pinus pinea 02/06/97 06/06/97 09/06/97 30/06/97 16/07/97 21/07/97 07/08/97 08/08/97 04/09/97 15/10/97 10/11/97 01/12/97 22/12/97 19/01/98 13/02/98 18/02/98 13/03/98 24/04/98 01/06/98

153 157 160 181 197 202 219 220 247 288 314 335 356 19 44 49 72 114 152

11 8 2 5 11 12 9 9 8 8 7 7 6 7 6 6 7 7 9

25.474.3 31.175.0 35.071.5 31.971.6 35.375.2 33.073.8 33.575.9 34.475.3 31.673.2 20.173.4 22.275.0 19.275.5 15.673.5 20.273.7 19.974.2 24.171.2 17.273.9 23.573.4 29.773.9

340.27204.3 324.07252.7 1478.07585.2 1760.87331.9 957.57591.9 944.67463.7 775.17704.4 600.97491.6 884.27747.5 475.97381.3 685.77481.5 714.97462.9 329.27225.7 871.77557.5 1083.17557.6 944.47406.3 1099.37686.9 1119.07659.1 1241.07605.3

Quercus ilex 22/07/97 23/07/97 21/08/97 22/08/97 05/09/97 17/10/97 12/11/97 12/12/97 15/12/97 09/01/98 11/02/98 16/03/98 17/04/98 27/04/98 25/06/98 16/07/98

203 204 233 234 248 290 316 346 349 9 42 75 107 117 176 197

9 8 9 6 8 7 6 6 6 7 6 7 7 8 7 8

30.573.6 31.074.4 31.473.8 31.472.8 31.673.2 22.171.1 19.473.8 12.470.6 11.273.7 17.174.5 18.173.7 23.473.5 17.671.8 19.373.7 28.372.9 30.871.4

1014.57713.4 1045.27779.3 604.17504.9 752.17551.3 880.47743.2 320.27195.4 805.77402.0 52.2721.8 260.57216.9 406.87285.7 730.47535.7 720.87690.1 526.27556.5 732.87685.9 333.17293.4 467.57718.8

a

n=number of measurements.

2.3.1. Dynamic sampling Our cuvette consisted of a frame and a circular plate, both made of transparent polycarbonate, which supported a cylindrical Teflon FEP bag of approximately 60 l volume (40 cm i.d. and 47 cm length). A branch of the vegetal species under study was enclosed within the FEP bag. The cuvette was flushed with non-filtered ambient air, coming from a Teflon PTFE-lined diaphragm pump (KNF Neuberger Model 726 FTE) at a flowrate of 12 l min
1. The approximate

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residence time within the cuvette was 5 min. Chemical lifetimes of most of the monoterpenes are usually longer than this residence time (Kesselmeier and Staudt, 1999). Besides, some works have shown that monoterpene emissions exposed to atmospheric ozone concentrations are not significantly influenced (Juuti et al., 1990; Steinbrecher et al., 1994; Kesselmeier et al., 1996). Inlet and outlet air samples were collected simultaneously by passing air through Teflon tubing (1/400 o.d.) at 0.1 l min
1 during 30 min. Two low-volume sampling pumps (ELF Escort) were placed downstream the stainless-steel sorbent tubes (Perkin-Elmer; 6.1 mm o.d. and 90 mm length), which had previously been loaded with 200 mg Tenax TA (Perkin-Elmer; 60–80 mesh). When duplicate outlet air sampling was required (at least once each sampling day for each species) a dual-tube adapter (Gemini Twin-port, MSA) with independent flow adjustment was used. The flow rates were calibrated with a digital flowmeter (Jour Digital). Temperature and relative humidity inside the enclosure were monitored automatically by means of a combined probe (Vaisala, 50Y) placed inside the cuvette and protected from solar radiation. Photosynthetic active radiation (PAR) was measured also automatically with a standard sensor (Skye Instruments, SKP 215). All measurements were recorded as 5 min averages on a data-logger (Campbell, CR10). Ambient meteorological conditions were measured with a portable meteorological tower (Davis, Weather monitor II). 2.3.2. Analytical method Desorption and analysis of monoterpenes were carried out using a Perkin-Elmer automated thermal desorption unit (ATD 400) connected via a transfer line (2001C) to an HP 5890 II GC equipped with an HP 5971 mass selective detector. Trapped compounds were desorbed at 2801C for 8 min at a carrier gas (He) pressure of 11.5 psi approximately, with prefocussing of the sample by means of a cold trap packed with Tenax TA at
301C. Separation of compounds was achieved using an HP-1 column (25 m  0.2 mm i.d.  0.25 mm) and He as the carrier gas at approximately 0.5 ml min
1. The initial oven temperature of 401C was maintained for 1 min, then increased to 651C at 201C min
1 and maintained for 5 min, increased again to 1151C at 41C min
1 and finally raised to 2001C at 301C min
1 (for 5 additional minutes). Detector temperature was set at 2801C. Blank tests were regularly performed for sample tubes and cuvette prior to and after field sampling. No terpenes were detected in any of the test tubes which were kept close to sample tubes in both the field and the laboratory during sampling and desorption, respectively, to account for cross contamination and sample integrity and stability during transport and storage.

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! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon,

Quantification was achieved by comparing the mass spectra of monoterpenes detected by GC-MS with those of the solutions of commercial chemicals of 95–99% purity. Furthermore, bromo-chlorobenzene (BCB) added in each sample tube was used as internal standard and the relative response factors (RRFs) were calculated. Detection limits ranged from 0.3 mg m
3 for apinene to 6.3 mg m
3 for linalool in air for a 3 l sample. 2.4. Emission rates and uncertainties Monoterpene emission rates were calculated as the difference between the outflowing and inflowing air from the enclosure   m2 m1 Q ; ð1Þ
E¼ q2 q1 Mt where E is the emission rate expressed as mg (of compound) g (dry leaf weight)
1 h
1; m2 and m1 are the mass of compound in the outlet and inlet samples (mg), respectively; q2 and q1 are sample outlet and inlet flow rates (l min
1); Q is the enclosure inflow rate (l min
1); M is the dry weight (d.w.) of leaf biomass of the sampled branch in grams (g d.w.), and t is the sample time (h). The overall measurement uncertainty associated with emission rates in Eq. (1) is approximately 25%, excluding the uncertainty linked to the enclosure itself. 2.5. Standardization of emission rates In order to compare field measured emission rates with literature values, standard emission rates (Es ) were estimated. For Pp Es values were obtained according to Tingey et al. (1980) (T80), where emission rates are described as a function of temperature only Es ¼ E exp ½bðTs
TÞ;

ð2Þ

where Es represents the emission rate at the standard leaf temperature Ts (303 K), E is the experimental emission factor described above, measured at the leaf temperature TðKÞ; and b is an empirical coefficient which Guenther et al. (1993) suggest to be equal to 0.09 K
1. Because leaf temperature was not measured in this work, the temperature of the air inside the enclosure was used to compute the standard emission rates. Some laboratory works suggest that the difference between leaf temperature and enclosure air temperature is rarely higher than 11C (Owen et al., 1997). For Qi, due to the assumed temperature and PAR dependency of Qi emissions (Staudt and Seufert, 1995; Loreto et al., 1996; Bertin et al., 1997; Street et al., 1997), the isoprene emissions model described by Guenther et al. (1993) (G93) was used to standardize

field emissions of monoterpenes Es ¼

E ; CL CT

ð3Þ

where Es is the emission rate at the standard leaf temperature Ts (303 K) and PAR (1000 mmol m
2 s
1) and CL and CT are functions of PAR and temperature, respectively. Although originally proposed for isoprene emissions, this model is also used by some authors (among others, Loreto et al., 1996; Kesselmeier et al., 1996; Bertin et al., 1997; Street et al., 1997; Simpson and Winiwarter, 1998) to standardize light-and-temperature dependent monoterpene emission rates.

3. Results and discussion 3.1. Composition of monoterpene emissions 3.1.1. Pinus pinea Fifteen monoterpene compounds were identified in the emission of a 20 yr-old Pinus pinea tree during the study period. Table 2 lists the standard emission rates with respect to temperature according to Eq. (2), in order to minimize the temperature effects, the high variability of emissions, and to compare them with literature values. Linalool, limonene, trans-ocimene and 1,8-cineole appeared to be the most frequently and abundantly emitted compounds from Pp. These four compounds represented on average 80% of the total measured period emissions. Street et al. (1997) found that 75–86% of the total monoterpene emissions from Pp could be assigned to these three first compounds. Daytime relative proportions of the four main compounds are shown in Fig. 1A. Limonene and linalool were present during the whole measurement period; both compounds were the most emitted and their maximum emissions occurred in June 1997 (Julian days: 160 and 157, respectively). On the other hand, trans-ocimene and 1,8-cineole were detected only in summer (Julian days: 160, 197, 202, 219, 220, 247) under warm and sunny conditions (see Table 1), and were absent during the rest of the year. The rest of the detected compounds (20% of the total emissions) were identified in only a few samples. Significant changes in relative proportions were observed throughout the measurement period (see Fig. 1A), especially in some days like on 15th October 1997 (Julian day: 288) in which only two compounds were detected (limonene 59% and a-pinene 41%) and with very low concentrations. Table 3 shows the diurnal emission development of the four main compounds from Pp during a single day. Relative emission values changed strongly during the day. For instance, linalool emissions were almost stable

! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon, Table 2 Standard monoterpene emission rates (ES) and contribution as a percentage related to the sum of mean individual monoterpene emissions of Pinus pinea (June 1997–June 1998) and Quercus ilex (July 1997
July 1998) Compound

na

Mean emission7s.d.b (mg [g d.w.]
1 h
1 )

% Emission

Pinus pinea Linalool Limonene t-Ocimene 1,8-Cineole b-Phellandrene Myrcene a-Pinene a-Terpineol b-Pinene c-Linalool oxide Sabinene t-Linalool oxide a-Terpinene g-Terpinene a-Thujene a-Phellandrene Camphene Terpinolene c-Ocimene Mean of total summed monoterpene emissions

128 131 69 41 37 72 91 79 9 70 27 26 3 3 F F F F 2 135

2.8472.13 1.7572.57 1.5670.93 1.7970.85 0.5770.44 0.2970.19 0.2870.24 0.2070.11 0.2270.10 0.1570.11 0.1270.05 0.0770.04 0.0370.02 0.0270.001 F F F F 0.0670.015 6.575.4

28.5 17.6 15.7 17.9 5.7 2.9 2.8 2.0 2.2 1.5 1.2 0.7 0.3 0.2 F F F F 0.6

19 69 9 F 24 71 93 23 84 F 74 F 29 30 20 20 27 26 F

0.2170.12 0.9870.85 0.6270.46 F 1.0870.40 4.573.9 7.375.7 0.1870.10 7.175.9 F 3.172.7 F 0.4570.25 0.6170.27 0.2970.09 0.2770.10 0.1870.07 0.1370.05 F 21.1719.8

0.8 3.6 2.3 F 4.0 16.7 27.0 0.7 26.3 F 11.5 F 1.7 2.2 1.0 1.0 0.7 0.5 F 94

Quercus ilex Linalool Limonene t-Ocimene 1,8-Cineole b-Phellandrene Myrcene a-Pinene a-Terpineol b-Pinene c-Linalool oxide Sabinene t-Linalool oxide a-Terpinene g-Terpinene a-Thujene a-Phellandrene Camphene Terpinolene c-Ocimene Mean of total summed monoterpene emissions a b

n=number of data. s.d.=standard deviation.

(30–40%) but increased considerably at the end of the day (50–70%; 18:00–20:00 h LT); on the contrary, transocimene and 1,8-cineole emissions increased during the day with the warmest and sunniest conditions but decreased with decreasing temperature and PAR values. Peak emissions of single compounds did not occur simultaneously.

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The sum of monoterpene emissions had a mean standard emission rate of 6.4875.44 mg [g d.w.]
1 h
1, which is very close to Street et al. (1997)’s value who found for Pp in June 1993 a standard mean total summed rate of 7.3874.9 mg [g d.w.]
1 h
1. A maximum value of 39.75 mg [g d.w.]
1 h
1 for the sum of monoterpene emissions was recorded on 9th June 1997 at 13:00 h LT (T ¼ 37:51C; PAR=480 mmol m
2 s
1). 3.1.2. Quercus ilex For Qi, a species that is generally considered a strong emitter of monoterpenes (Staudt and Seufert, 1995; Kesselmeier et al., 1996; Bertin et al., 1997; Staudt et al., 1997), 15 monoterpene emissions were identified during the study period (July 1997–July 1998) from a 30 yr-old tree. Table 2 shows the identified emitted compounds and their standard emission rates. a-pinene, b-pinene, myrcene and sabinene, arranged in decreasing order of importance, where the main compounds detected accounted for 80% of the total emissions. These compounds were detected during the whole measurement period (see Fig. 1B). Somewhat lower emission rates were found for a-thujene, a-phellandrene, camphene, a-terpineol and terpinolene. In contrast to some other studies (e.g., Owen et al., 1997; Street et al., 1997), 1,8-cineole was not detected at all from Qi. The diurnal emissions of the four main compounds from Qi during a single day are shown in Table 3. Relative emission values remain stable during daytime (11:00–16:00 h LT), and decrease at night. Unlike Pp, peak emissions of single compounds occurred simultaneously at midday (13:00 h LT). Fig. 1B shows daytime relative emissions of the four main compounds detected; no significant changes in ratios were observed throughout the measurement period. However, in December 1997 (Julian days: 346 and 349) only a-pinene and b-pinene emissions were detected, maybe due to the low values of temperature and PAR. The total summed monoterpene emissions had a mean standard emission rate of 21.1719.8 mg [g d.w.]
1 h
1. (Street et al. (1997) found 20.0712.7 in June 1993 and 27.1717.2 mg [g d.w.]
1 h
1 in May 1994 in sun forest). Maximum values were measured on 21st August 1997 at 14:30 h LT (T ¼ 35:41C; PAR=1047 mmol m
2 s
1) with a total summed emission rate of 131.6 mg [g d.w.]
1 h
1. 3.2. Dependency of monoterpene emissions on environmental variables Several authors have found that monoterpene emissions depend on temperature alone (Tingey et al., 1980; Lamb et al., 1987; Juuti et al., 1990; Guenther et al., 1991, 1993, 1995), and some others establish an influence

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! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon,

Fig. 1. Relative proportions (% of total monoterpene emission) of the main four compound emissions from Pinus pinea (A) and Quercus ilex (B) during different Julian sampling days. Total=15 monoterpenes.

of both temperature and light (Janson, 1993; Monson et al., 1995; Staudt and Seufert, 1995). The short-term response to both variables have been extensively studied for many plants and compounds, and described in several mathematical models (e.g., Tingey et al., 1980; Guenther et al., 1991; Schuh et al., 1997; Staudt and Bertin, 1998). Dependency of the emission rates with related environmental variables (temperature and PAR) was analyzed and compared with literature data. For Pp, results concerning the short-term relationship between daytime emission rates and temperature are listed in Table 4, where the b-values correspond to the slope of the linear regression line fitted between ln (total

emission rate) and temperature (K). Only the b values for daytime emission (Julian day) with reasonably good relationships (r2 X0:5) are shown. Values ranged between 0.09 and 0.42 K
1; the best fit obtained (b795%confidence intervals) was 0.2570.08 K
1 (r2 ¼ 0:94; n ¼ 7) for March 1998 (Julian day=72). A value of 0.1870.02 K
1 (r2 ¼ 0:65; n ¼ 135) was obtained for the total emission throughout the measuring period. Guenther et al. (1993) report b-values ranging from 0.057 to 0.144 K
1, with a mean value of 0.0970.08 K
1 obtained from studies using non-Mediterranean species. Short-term relationships between individual monoterpene emission rates and temperature were good for linalool and limonene during the Julian days: 153, 197,

20:00 24.6 87.5 2.9 (67) 0.5 (12) 0.6 (14) 0 4.3 (51) (7) (24) (10)

(42) (31) (11) (11)

20:00 24.7 70.6 0.6 (60) 0.4 (40) 0 0 1.0 (38) (31) (11) (15)

19:00 26.3 122.3 1.1 0.8 0.3 0.3 2.6 (31) (29) (10) (19)

17:30 27.9 237.8 3.0 2.4 0.9 1.2 7.8 (30) (28) (10) (19)

16:00 30 1366.1 10.4 9.6 3.3 6.4 33.3 (30) (28) (10) (20)

14:00 31.3 1868.0 20.4 18.9 6.5 13.0 66.8 (33) (29) (9) (18)

13:00 31.9 1836.6 22.1 20.8 7.6 14.8 73.5 10:00 34.7 1057.6 16.2 15.9 6.7 9.3 53.7 Quercus ilex Time Temperature PAR a-Pinene b-Pinene Sabinene Myrcene Total

(30) (30) (12) (17)

(47) (9) (29) (8) (41) (9) (38) (7) (37) (13) (30) (12) (36) (13) (28) (14) 11:00 35.4 1199.5 5.5 2.3 3.6 2.9 15.7

(35) (15) (23) (18)

11:30 33.4 1513.8 22.8 20.1 6.5 12.7 69.8

(49) (11) (25) (11)

19:00 30.6 356.8 6.1 0.9 2.9 1.2 12.0 18:00 31.6 265.9 3.5 0.8 1.8 0.8 7.1 17:00 32.7 364.1 5.6 1.1 3.5 1.0 11.9 16:00 35.5 880.3 7.9 1.7 7.3 1.4 19.3 15:00 41.2 1610.3 7.1 (36) 3.1 (16) 8.5 (43) 0 19.8 14:00 41.6 1669.4 6.8 (36) 3.4 (18) 7.3 (39) 0 18.7 13:00 40.5 1538.5 9.0 3.1 7.3 2.8 24.0 12:00 39.3 1360.7 7.9 2.9 6.1 3.1 21.7

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Table 4 Temperature dependence of total (15 monoterpenes) monoterpene emission from Pinus pinea: b ðK
1 Þ is the slope of ln (emission) versus temperature (K), s=standard deviation (95% confidence interval), r2 =correlation coefficient, and n=number of data

Pinus pinea Time Temperature PAR Linalool Limonene trans-Ocimene 1,8-Cineole Total

Table 3 Diurnal emission rates (mg [g d.w.]
1 h
1) of main monoterpenes and percentage (%) of total emission (in parenthesis) from a branch of Pinus pinea (16 July, 1997) and Quercus ilex (22 July, 1997). Time is local time and total emission is the sum of 15 monoterpenes (=100%). Maxima are in bold and minima are in italics

! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon,

Date (dd/mm/yy)

Julian day

n

b7s

r2

02/06/97 06/06/97 16/07/97 21/07/97 04/09/97 10/11/97 01/12/97 13/03/98 24/04/98 01/06/98 Total campaign period

153 157 197 202 247 314 335 72 114 152

11 8 11 12 8 7 7 7 7 9 135

0.2070.07 0.1470.08 0.0970.03 0.1370.06 0.3170.25 0.2070.09 0.2170.10 0.2570.08 0.4270.30 0.1270.08 0.1870.02

0.83 0.73 0.80 0.65 0.54 0.88 0.81 0.94 0.74 0.58 0.65

314, 72. For linalool, b-values ranged between 0.05 and 0.25 K
1 (r2 ¼ 0:65 and r2 ¼ 0:98; respectively), limonene, 0.12–0.19 K
1 (r2 ¼ 0:91 and r2 ¼ 0:80); transocimene, 0.14–0.21 K
1(r2 ¼ 0:83 and r2 ¼ 0:65). Staudt et al. (1997) reported b-values between 0.06 and 0.20 K
1 for limonene and 0.17–0.43 K
1 for ocimene throughout 1 yr. Long-term relationships (all data for the 1-yr period) between emission rates and temperature were poor (r2 o0:5) for most of the individual monoterpenes with the exception of linalool (b ¼ 0:1670:02 K
1; r2 ¼ 0:65; n ¼ 135). In order to test the suitability of the monoterpene model T80 [Tingey et al., 1980; Eq. (2)] and the isoprene model G93 [Guenther et al., 1993; Eq. (3)], to predict the short-term variations of emissions, the data of one day (21 July, 1997) were standardized by T80 and G93, and then divided by the experimental value of Es measured in the field close (T ¼ 31:81C and PAR= 1023.7 mmol m
2 s
1) to standard conditions. Results of the comparison between measurements and simulations are given in Table 5. Excluding trans-ocimene, the performance obtained by both models was generally poor, especially for linalool and cineole. The above results suggested that a temperature function is not enough to describe the short-term variations of Pp monoterpene emissions, except for trans-ocimene. This is contrary to Staudt et al. (1997) who found that trans-ocimene data fitted better with G93 model, while T80 was more appropriate for limonene data. It is well known that Qi emissions are light-andtemperature-dependent, and the influence of these ambient variables in the short-term control of monoterpene emissions have been revealed by laboratory and

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Table 5 Performance of the monoterpene (T80) and isoprene (G93) models (with parameters given by Guenther et al., 1993) to predict the short-term emissions for the main monoterpene emissions from Pinus pinea and Quercus ilex, during one campaign day Pinus pinea (21 July 1997) Model Limonene r2 (n ¼ 12Þ 0.50 T80a G93b 0.64

1,8-Cineole r2 (n ¼ 12) o0.5 0.51

trans-Ocimene r2 (n ¼ 12) 0.85 0.88

Linalool r2 (n ¼ 12) o0.5 0.5

Quercus ilex (22 July 1997) Model a-Pinene r2 (n ¼ 9) T80a 0.66 G93b 0.81

b-Pinene r2 (n ¼ 9) 0.70 0.84

Sabinene r2 (n ¼ 9) 0.73 0.90

Myrcene r2 (n ¼ 9) 0.54 0.73

a b

Tingey et al. (1980). Guenther et al. (1993).

field experiments (Staudt and Seufert, 1995; Loreto et al., 1996; Kesselmeier et al., 1996; Bertin et al., 1997). Good correlation coefficients (r2 X0:7) between measured and simulated emission with G93 model were obtained for the main monoterpene emissions (a-pinene, b-pinene, limonene, myrcene and sabinene). The diurnal pattern of these emissions was simulated in a satisfying way (see Table 5) by the isoprene model (G93) for one day (22 July, 1997) whose T and PAR observed values were close to the standard conditions. 3.3. Seasonal variation of monoterpene emissions Fig. 2 (A and B) shows the seasonal variation of standard emission rates (Es ), [i.e., T ¼ 301C; Eq. (2) or T ¼ 301C and PAR=1000 mmol m
2 s
1 Eq. (3)] of the four main compounds emitted by Pinus pinea and Quercus ilex. 3.3.1. Pinus pinea The highest emission rates for Pp were observed in spring 1997 period (Julian days: 153, 157 and 160) obtaining 11.575.7 mg [g d.w.]
1 h
1 as average (n ¼ 21; min–max: 3.1–24.8). As can be seen in Fig. 2A emissions during this period showed a strong increasing trend, but decreased in summer 1997 (Julian days: 181, 197, 202, 219, 220 and 247) with a mean of 7.373.7 mg [g d.w.]
1 h
1 (n ¼ 54; min–max: 0.5–16.5). Emissions decreased even more in autumn 1997 (Julian days: 288, 314, 335 and 356) down to 2.971.8 mg [g d.w.]
1 h
1 (n ¼ 20; min–max: 0.39–6.4) and a minimum was reached during winter 1998 (Julian days: 19, 44, 49 and 72) with 1.671.5 mg [g d.w.]
1 h
1 (n ¼ 24; min– max: 0.3–5.2). Year-to-year variability can be only evaluated by comparing one measured day of each year (2 June 1997 and 1 June 1998). Fig. 2A shows that emission rates differed as much as 50% on average: 9.0474.9 mg [g d.w.]
1 h
1; n ¼ 11 and 4.371.5 mg [g d.w.]
1 h
1; n ¼ 9: Because only these days were measured we could not

appreciate whether this difference was maintained during the spring 1998 period. This degree of variation is not unexpected if we take into account that samples were taken in different branches, different days, besides the temporary occurrence of 1,8-cineole and trans-ocimene emissions. This difference was also observed by Staudt et al. (2000) in other field campaigns. These authors found a reduction in monoterpene emissions during spring/summer 1994 compared to those in the previous year, mainly due to lower trans-ocimene emissions. They suggested that the seasonal occurrence of these compound emissions is related, on one hand, to high temperature events, and on the other, to the period of foliar biomass growth, since it may be a by-product of isoprenoid synthesis in the developing foliage. In the case of the above mentioned difference in emissions, the decrease in the number of new shoots from 1993 to 1994 was approximately one half. Fig. 3A shows a pronounced seasonal variation of Es (standardized by T80 model) for the total monoterpene emission rates, similar to that in the original data (Eo ). Standardization does not decrease emission variation, that is to say, emissions measured (Eo ) in spring 1997 (Julian days: 153, 157 and 160) compared to those in autumn 1997 (Julian days: 288, 314, 335 and 356) differ 88% on average whereas the difference in Es between the same periods is very similar (73% on average). For both cases, the differences are statistically significant (p ¼ 0:05; t-test). Then, in order to assess the suitability of the existing models T80 and G93 to predict the seasonal (long-term) variations of total monoterpene emissions, the data were standardized by T80 and G93 and then divided by the experimental value of Es measured in the field close to standard conditions obtaining a mean value of 8.8476.71 mg [g d.w.]
1 h
1 (T ¼ 31:071:181C; PAR= 1054.2770.1 mmol m
2 s
1; n ¼ 4). The overall performance obtained from the comparison between measured and predicted emissions was not satisfactory (r2 ¼ 0:5; n ¼ 135 applying T80 and r2 ¼ 0:56; n ¼ 135 applying G93). Like other authors (Staudt et al., 1997; Bertin

! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon,

4427

Fig. 2. Seasonal variation of daily mean standard (Es ) emissions rates (expressed as mg [g d.w.]
1 h
1) for the main four monoterpene emissions from Pinus pinea (A) and Quercus ilex (B). Emissions were normalized with T80 model (Pp) and G93 model (Qi).

et al., 1997) we also estimated our proper model parameters by following best linear (Eq. 2) and nonlinear (Eq. 3) fit procedures, which did not improve the model performance. Poor performance of the models could be caused by the inaccuracy of Es estimation, as underlined by Guenther et al. (1993), that was measured in the field in conditions close to standard ones and by the data scattering (i.e. experimental errors, accuracy of trace gas emissions measurements). Another reason might be the inadequacy of these models to explain the diurnal variations, as expressed by other authors (Street et al., 1997; Staudt et al., 1997). This high variation in long-term emissions seems to involve other environmental and/or phenological fac-

tors, fairly denoting the need to consider a time variation of emission rates. Es values display a pattern similar to that found by Staudt et al. (2000) for saplings of Pinus pinea during a measurement period of 15 months (bell-shaped). The empirical time-based model proposed by Staudt et al. (2000), which accounts for seasonal influences on emissions in addition to the short-term effect of temperature and light, is as follows: EðT;L;DÞ ¼ ESmax CT;L CD ;

ð4Þ

where EðT;L;DÞ is the emission rate at a given temperature T; radiation L and month D of the year, Esmax is the maximum standard emission rate in the year, CT;L is the dimensionless correction factor for the instantaneous

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! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon,

Fig. 3. Seasonal variation of daily mean of measured (Eo ) and standard (Es ) emissions (expressed as mg [g d.w.]
1 h
1) to the total sum of monoterpene emissions for Pinus pinea (A) and Quercus ilex (B) emissions. Rates were set to standard conditions with ‘‘G93’’ parameters.

influences of temperature and light [Eq. (3)] proposed by Guenther et al. (1993), and CD is the dimensionless correction factor accounting for Es variation during the year. We have found that a fair fitting of the mean daily sum of emissions was obtained if CD is expressed by following this Gaussian equation CD ¼ exp ½
ðD
D0 Þ2 =s2 ;

ð5Þ

where D is the sampling date (Julian day) and D0 ¼ 176:1 and s ¼ 31:8 are empirical parameters. The overall performance applying this model to the total sum of emissions was r2 ¼ 0:64 (n ¼ 19 Julian days). 3.3.2. Quercus ilex Unlike Pinus pinea, in Quercus ilex the relative proportion of a-pinene and b-pinene emissions were rather stable all through the year (Fig. 1B). The highest mean standard emission rates were obtained for the four main compounds, a-pinene, b-pinene, sabinene and myrcene, in summer 1997 period (Julian days: 203, 204, 233 and 234) with 32.1717.0 mg [g d.w.]
1 h
1 (n ¼ 39; min–max: 7.2–73.5) as mean monoterpene emission. Emissions decreased in autumn 1997 (Julian

days: 290, 316, 346 and 349) down to 16.4717.2 mg [g d.w.]
1 h
1 (n ¼ 20; min–max: 2.2–60.1). In winter 1998 (Julian days: 9, 42 and 75) emissions even decreased down to 50%7mg [g d.w.]
1 h
1; (n ¼ 14; min–max: 1.3–17.3)]. As for Pp, the variation of emission rates from 1 yr to the next can be only evaluated by comparing one measured day of each year (22 July 1997 and 16 July 1998). As can be seen in Fig. 2B the difference between emissions for these days is approximately 83% on average: 30.9715.8 mg [g d.w.]
1 h
1, n=9, and 5.17 3.2 mg [g d.w.]
1, n ¼ 8; respectively. However, it cannot be asserted that this sporadic result is determinant of a typical emission behaviour. Street et al. (1997) observed that total mean emission rates from forest appeared to vary considerably from 1 yr to the next (29.8720.0 and 9.178.2 mg [g d.w.]
1 h
1 in June 1993 and May 1994, respectively), but after normalizing to T ¼ 301C and PAR=1000 mmol m
2 s
1, the mean emission rates were comparable (20.0712.7 and 27.17 17.2 mg [g d.w.]
1 h
1 in June 1993 and May 1994, respectively). This was related by the latter authors to differences in soil and xylem water potential resulting from cooler and wetter weather conditions preceding the

! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon,

field measurements in May 1994 or may also be caused by physiological changes in the early part of the growing season. In our case, water stress may be also be one of the main causes for the decrease in monoterpene emissions, as rainfall noticeably decreased since 1997 until 1998 (653 mm and 78 precipitation days in 1997 against 453 mm and 67 precipitation days in 1998). Fig. 3B shows the seasonal variation of daily (Julian date) standard emission rates (Es ) (standardized with G93) throughout the whole campaign period. Standardization produces a light decrease in emission variation between seasons compared with measured emissions (Eo ). For instance, measured emissions (Eo ) in summer 1997 were 94% higher as average than those in winter 1998, whereas the difference between standard emissions (Es ) in the same periods is 76% as average. In both cases emissions were significantly different from each other (p ¼ 0:05; t-test). Since temperature and PAR are positively correlated with monoterpene emissions from this species, we considered only the isoprene model (G93) to predict the seasonal (long-term) variations of total monoterpene emissions. The data were standardized and then divided by the experimental value of Es measured in the field close to standard conditions obtaining a mean value of 8.8476.71 mg [g d.w.]
1 h
1 (T ¼ 31:374:01C; PAR=1014.57160.1 mmol m
2 s
1; n ¼ 5). A good overall performance (r2 ¼ 0:74; n ¼ 94) was obtained from the comparison between measured and predicted emissions. In a second step, model parameters from Eq. (3) were estimated by a best non-linear fit procedure on 94 data. Both versions of the model (‘‘fitted’’ and ‘‘G93’’) were applied to obtain standard emissions (Es ) throughout the whole measurement period. Differences between Es obtained with ‘‘fitted’’ and ‘‘G93’’ parameters were not significantly different (p ¼ 0:05; t-test). Then, G93’s model parameters are suitable to predict the long-term variations for the total summed monoterpene emissions.

4429

and the values were in the range of those previously reported in the literature. Relative proportions of the main compounds emitted by Pp noticeably varied throughout the campaign period, especially as far as the seasonal occurrence of trans-ocimene and 1,8-cineole emissions was concerned. On the contrary, relative proportions of the main compound emissions from Qi (a-pinene, b-pinene, sabinene and myrcene) were rather stable over the measured period. Model performances (T80 and G93) for daily emissions (short-term) in a single day were assessed. For Pp, excluding trans-ocimene, the performance obtained by both models was poor, which suggests that other internal or external factors could be involved in the emission control. Better correlations with temperature (b-values) were obtained for short-term emissions of individual monoterpenes than for their annual emissions. For both species a statistically significant variation in monoterpene emissions was observed between seasons for 1-yr period. Standardization using the T80 and G93 models (poor performances were obtained) did not decrease the high variability over the whole measurement period observed for daily mean standard emission rates (Es ). On the contrary, model application revealed significant seasonal differences in the standard emission factors. The seasonal variation for Pp was evaluated applying the empirical time-based model proposed by Staudt et al. (2000). A slight modification of the model allowed us to improve the correlation coefficient a little between measured and predicted values. On the other hand, the diurnal and seasonal emission patterns from Qi were simulated in a satisfying way by the G93 model. Finally, the findings in this study emphasize that future research should be focused in measuring longterm emissions under non-environmental controlled conditions in the field.

Acknowledgements 4. Conclusions The measurement period spanned a complete year for both species (Pp and Qi), from which up to 15 monoterpenes were identified. The main burden of emitted compounds accounted to Pp can be linked to linalool, limonene, trans-ocimene and 1,8-cineole (80% on average). Eighty percent of total emissions in Qi were b-pinene, a-pinene, myrcene and sabinene, followed by limonene, b-phellandrene, gterpinene and trans-ocimene (20%). On average, the standard monoterpene emission rate from Qi was on average approximately three times higher than from Pp

The authors wish to express their gratitude to Ms S. Ribes for her help in the early stages of this work, to Dr. G. Seufert and Mr. D. Droste (JRC-Ispra, Italy) for their helpful advice in designing the dynamic enclosure developed and for providing the FEP film, and to Dr. J. Cid for his comments and help in the analytical methodology. Dr. Kotzias (JRC-Ispra, Italy) is thanked for allowing our participation in a later phase of the BEMA project. The authors also wish to thank the ! Interministerial de Ciencia y Tecnolog!ıa Comision (Madrid, Spain) for funding this work through * Contract AMB95-0417, and the Agencia Espanola de

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! L.V. Cremades / Atmospheric Environment 35 (2001) 4419–4431 D. Sabillon,

! Internacional (AECI) for providing a Cooperacion ! grant to one of us (D. Sabillon).

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