Seasonal variations in stable carbon and ... - AGU Publications

GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 16, NO. 4, 1094, doi:10.1029/2001GB001428, 2002

Seasonal variations in stable carbon and hydrogen isotope ratios in methane from rice fields Thomas Marik and Horst Fischer Max Planck Institute for Chemistry, Mainz, Germany

Franz Conen and Keith Smith Institute of Ecology and Resource Management, University of Edinburgh, Edinburgh, UK Received 16 April 2001; revised 22 May 2002; accepted 24 June 2002; published 20 November 2002.

[1] During two successive growing seasons, methane emissions from rice fields in Italy

were measured. High-precision measurements of the methane 13C/12C and D/H ratios were carried out by mass spectrometry and tunable diode laser absorption spectrometry. Significant seasonal variations were found for both d13C and dD. The results confirm earlier observations by Bergamaschi [1997] in finding a seasonal cycle with isotopically depleted methane in the main growing season and higher values at the beginning and the end of the season during drainage of the field. The measured d13C diurnal cycles showed a strong correlation with the methane emission rate. The isotopic composition of methane, which depended on the season, can be explained by variations of the different pathways for methane production, oxidation, and release into the atmosphere. A model based on these parameters was able to reproduce the field measurements and indicate the principal causes of observed fluctuations in the isotopic INDEX TERMS: 0315 Atmospheric Composition and Structure: Biosphere/ methane composition. atmosphere interactions; 0322 Atmospheric Composition and Structure: Constituent sources and sinks; 0365 Atmospheric Composition and Structure: Troposphere—composition and chemistry; 1615 Global Change: Biogeochemical processes (4805); KEYWORDS: methane, isotopes, rice paddies, TDLAS Citation: Marik, T., H. Fischer, F. Conen, and K. Smith, Seasonal variations in stable carbon and hydrogen isotope ratios in methane from rice fields, Global Biogeochem. Cycles, 16(4), 1094, doi:10.1029/2001GB001428, 2002.

1. Introduction [2] Atmospheric methane, one of the most important anthropogenically emitted greenhouse gases, has more than doubled in the past 150 years [Etheridge et al., 1998]. Rice paddies are among the major anthropogenic sources of atmospheric methane. In the flooded fields, anaerobic bacteria convert organic material partially into methane. This material, mainly straw, organic fertilizer, and plant exudates, is degraded by a chain of anaerobic bacteria, which enzymatically consume cellulose and other longchain organic compounds. The resulting compounds, such as fatty acids, are degraded in turn by other bacteria, ending up as acetate or compounds containing one carbon atom, for example CO2 or methanol. At the end of this degradation chain methanogenic bacteria reduce these compounds to methane. Many methanogenic bacteria can use either major pathway i.e., via acetate or via CO2, to methane, switching from one to the other depending on substrate availability. [3] The release of methane from the anaerobic soil occurs mainly via the aerenchyma (air-filled intercellular spaces) of the rice plants [Cicerone and Shetter, 1981]. The rice plant, Copyright 2002 by the American Geophysical Union. 0886-6236/02/2001GB001428

adapted to flooded conditions, provides oxygen for the use of its roots via the aerenchyma [Dacey and Klug, 1979; Holzapfel-Pschorn et al., 1985; Chanton and Dacey, 1991], through which methane is also transported from the soil to the atmosphere. This methane transport occurs by molecular diffusion [Beckett et al., 1988], which depends on the concentration difference between soil and atmosphere, rather than by bulk flow, which occurs in other plant groups with active ventilation. The oxygen transported to the roots is also responsible for a small aerobic zone around the roots, the rhizosphere, in which aerobic bacteria are able to oxidize methane and reduce the total emissions of rice paddies. Earlier work has reported the oxidation of up to 80% of the methane produced [Sass et al., 1991; Frenzel et al., 1992; Tyler et al., 1997], but the recent use of difluoromethane as a selective inhibitor of methane oxidation suggests that this fraction is 40% or less, depending on the stage of the growing season [Kru¨ger et al., 2001]. In the literature, values between 20 and 150 Tg yr1 for the total emission of methane by rice paddies can be found [Houghton et al., 1995]. The current best estimate is 50 ± 20 Tg yr1 [Neue, 1997]. [4] To increase the understanding of the processes that are involved in the emission of methane by rice paddies, the fluxes and the isotopic composition of the emitted methane

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MARIK ET AL.: SEASONAL VARIATIONS IN CH4 ISOTOPE RATIOS FROM RICE

Table 1. Overview of Available Isotope Measurements on Methane From Rice Paddiesa Location California Kenya Louisiana Italy Japan NA Japan Louisiana China Texas Texas Italy a

d13C 68 63 66 68 68 65 71 72 66 61 56 71 71 58 62 67 65

to to to to to to to to to to to to to to to to to

dD

66 57 60 63 48 61 56 58 61 57 50 52 58 53 48 47 53

NA NA NA 339 NA 310 NA NA NA 325 NA 352 358 338 331 356 354

Seasonal Coverage

to 319 to 290

3 weeks before harvest days 44, 72, 100, 128, 156 after harvest May – June days 85 – 88 after flooding throughout the season NA days 22, 51, 71, 93, 107 (1990) days 38, 72, 100 (1991) after flooding days 84 – 89 after seeding

to 300 to to to to to to

311 343 315 313 320 315

throughout the season throughout throughout throughout throughout

the the the the

season season season 1998 season 1999

Sampling Method/ Sample Type

Reference

nocturnal inversion static chamber NA static chamber gas bubbles NA static chamber

Stevens and Engelkemeier [1998] Tyler et al. [1988] Wahlen et al. [1989] Bergamaschi [1990] Uzaki et al. [1991] Wahlen [1993] Tyler et al. [1994]

CO2 controlled chamber gas bubbles lacunal static chamber gas bubbles static chamber static chamber CO2 and T controlled chamber

Chanton et al. [1997] Bergamaschi [1997] Tyler et al. [1997] Bilek et al. [1999] this work

Adapted from the study of Bergamaschi [1997].

and of the methane in the soil were measured during two successive growing seasons in Italy. The measurement of the isotopic compositions in sources and the atmosphere can help reduce the uncertainties in the atmospheric methane budget and, also, help understand the processes involved. Therefore, several other studies have been made to measure the isotopic composition of methane from rice paddies (see Table 1). The measurements of the isotopic composition of methane may also help define the input parameters for a process-based model to estimate the methane emissions of rice areas by measuring environmental parameters. [5] Isotopic ratios are given in the delta notation [Hut, 1987; Coplen, 1994] d¼

RSample 1 1000½% RStandard

ð1Þ

where RSample is the ratio of 13C/12C or D/H in the sample methane and RStandard is the ratio of 13C/12C or D/H in the standard methane. As standards we use the V-PDB scale for d13C and V-SMOW for dD. The processes involved in the methane release by plants have different influences on the isotopic composition of the methane. The ratios of the reaction rates for the isotopomers in the different processes are the parameters that quantify this influence. a13 ¼

k12 d13 CH4 þ 1000% ¼ 13 k13 d CSubstrate þ 1000%

ð2Þ

kH dCH3 D þ 1000% ¼ aD ¼ kD dDSubtrate þ 1000%

[6] Using this definition for the fractionation factor a leads to a > 1 for a depletion of methane relative to the substrate. The production pathways (aceticlastic versus CO2/H2) have different signatures, mainly in the d13C of the produced methane. It was found by Sugimoto and Wada [1993] that the fermentation process of acetotrophic bacteria has only a small fractionation effect on the 13C/12C ratio, which means that the d13C of the methane is only 11% lower than that of the methyl group of acetate. In natural conditions the d13C of the acetate is in the range of that of

the original organic matter, which is for C3 plants, such as rice, 28%. An intermolecular difference was found between the d13C of the methyl group and that of the carboxyl group in anaerobic environments [Kryzycki et al., 1987; Sugimoto and Wada, 1993]. Methane from CO2 reduction is much more depleted in d13C. Here a fractionation factor range from a = 1.030 to 1.060 was found [Blair et al., 1993, and references therein]. Starting with CO2 at 10%, a value, which can be found under strict anaerobic soil conditions, a d13C for methane of 68% is obtained. If CO2 and carbonates are mainly formed in aerobic conditions and transported into the anaerobic soil layer, increasingly negative values, the d13C of CO2 down to the original d13C of the substrate, can also be reached, which results in even more negative values for d13C of CH4. For D/H, methane values from 330 to 360% were found, depending on the isotopic signature of water. [7] Both molecular diffusion and methane oxidation result in an enrichment of the remaining methane in both 13 C and D. The fractionation factor for d13C is 1.019 for diffusion and for oxidation it ranges from 1.003 from field studies by Happell et al. [1994] to 1.025 from laboratory studies by Coleman et al. [1981]. dD has the same factor as 13 C for diffusion, and for oxidation it ranges from 1.044 from field studies by Bergamaschi and Harris [1995] to 1.325 from laboratory studies by Coleman et al. [1981]. In previous publications it was reported that the isotopic composition of the methane emitted from rice fields changed during the growing season [Tyler et al., 1994; Bergamaschi, 1997].

2. Methods and Measurements 2.1. Field Site and Management [8] The rice paddies studied are situated in the Po valley near Vercelli, Italy, at the research station of the Istituto Sperimentale per la Cerealicoltura (ISC). The soil was a sandy loam (62% sand, 26% silt, 12% clay), with an organic carbon content of 2.5%. The management for rice production followed the normal practice of the region. The pH at


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the start of the growing season was 6.0, increasing during the flooded period to 7.2. Details of the crop variety and the field operations relevant to CH4 emissions are given in Table 2. Measurements covered two full cropping seasons (1998 and 1999). 2.2. CH4 Sampling and Analysis System [9] Four automated flux chambers were placed in each of two adjacent 1 ha fields immediately after sowing (Figure 1). Access to each chamber was along the earth bund (1.2 m wide, 1 m high) that divided the fields, and then via wooden walkways extending perpendicularly out to each side at distances of 10, 18, 26, and 34 m along the bund. The chambers were placed alternately either 4 or 8 m into the field. They were 0.8 m by 0.8 m in area and 1.0 m high, except at the beginning of the 1998 season, when the height was reduced to 0.5 m to increase the methane-mixing ratio at low fluxes. The design was similar to that described by Butterbach-Bahl [1993]. Each structure consisted of a painted metal frame, holding together 4 mm clear methacrylate (Perspex) sheets, and a pneumatically operated Perspex lid. Joints were made with commercial plastic profiles and sealed with silicone gel. Foam rubber draught excluder was used as a gas seal between the lid and the top frame. Two chambers (nos. 3 and 4) were equipped with a cooling and CO2 control system similar to that described by Chanton et al. [1997] to permit closure periods of 13 hours in order to achieve a sufficient CH4 mixing ratio for isotopic analysis, while minimizing the impact on the growth of the rice. The CO2 levels in the chambers and outside were measured with a Licor nondispersive infrared monitor (Type 6262, Li-COR Inc., USA) by adding pure CO2 (Messer Griesheim CO2 4.6) with a flow controller (MKS 10 ml s1 max. flow). The temperature was measured with NiCrNi elements and the temperature inside the chambers was kept at outside air temperature by a purpose-built water-cooling system driven by a commercial water cooler. The control system was automated using an embedded microcontroller system based on a V25 processor (MPI Mainz). The cold water from the cooler was also used to dry the measurement air for the Licor and the airconditioning for the box in which the measurement instruTable 2. Timing of Field Operations Relevant to CH4 Emissions Year Operation Cultivation: ploughing in of straw and stubble after application of 26 kg N ha1 as Ca cyanamide Fertilization (in kg ha1): N, 98 (as urea); P2O5, 34; K2O, 156 Harrowing Flooding of fields (floodwater level 5 – 10 cm) Sowing (Oriza sativa, japonica type, cv. Koral) First drainage (followed by herbicide application) Reflooding Tillering Second drainage (for 3 days) Fertilization (98 kg N ha1 as urea) Flowering Final drainage (water level 0 cm) Harvest

1998

1999

Early April Early April 12 May

23 Apr

14 May 15 May 19 May 1 June 12 June 18 June N/A 22 July 11 Aug 30 Aug 10 Oct

30 Apr 3 May 5 May 21 May 1 June 14 June 16 June 13 July 10 Aug 7 Sep 30 Sep

Figure 1. Location of flux chambers in rice fields at Vercelli (not to scale). ments were situated. The control of the CO2 mixing ratio was improved by adding the current signal of a solar cell into the regulator algorithm; the maximal deviation between outside and inside air CO2 mixing ratio was smaller than 10 ppm. In the field it was found that the cooling performance was too weak to maintain the outside temperature inside the chambers at midday but still sufficient to prevent water condensing at the walls of the chambers; the inside temperature did not exceed the outside air temperature by more than 3C. The gas sampling system is shown schematically in Figure 2. Gas samples were pumped from each chamber in turn, via a manifold and a 160 m long Rilsan1, 2 mm i.d. tube, to a gas chromatograph (Hewlett Packard, Model 5890 series II) equipped with a 1.8 mm 6 mm Porapak Q column, a flame ionization detector, and an external integrator (Hewlett Packard, Model 3395) in the Institute laboratory. Loading and injection have been described by Arah et al. [1994]. The flow paths during flushing of the sampling line and filling of the sample loop are shown in Figure 2. GC calibration was carried out with 5 and 50 ppm CH4 standards. The entire sampling and injection procedure took 7 min per sample, and chamber closure (routinely for 31 min) was also initiated at 7 min intervals, giving an 87 min-sequence for a full sampling cycle of all eight chambers. Between two and eight complete closure/sampling sequences were carried out per day. When only two sequences were carried out, they were timed to cover the times of the lowest and the highest points of the diurnal fluctuation in emission rate. The entire system was initially controlled by a computer-driven unit constructed by Spectra Elettronica, Milan, Model RS422, but after frequent breakdowns during thunderstorms this was replaced by a system with a fiber-optics link to the field, built at the Max Planck Institute for Chemistry in Mainz. 2.3. Isotopic Measurements [10] Once a week, samples were taken from chambers 3 and 4 (Figure 1) for isotope ratio measurement. At the end of a 1– 3 hours closure period, 10– 20 l of chamber air was pumped into a polyethylene-coated aluminum bag. In addition, bubble samples from the root zone in the soil were

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Figure 2. Schematic of gas sampling and GC injection system for methane flux measurement (not to scale). Solid lines indicate gas flows; (a) filling sample loop; (b) sample injection. collected with an inverted funnel. Two crossed wires were fixed to the mouth of the funnel and the apparatus was used to shake the soil surface, to free the bubbles that were trapped in the rhizosphere. Another inverted funnel system was used for passive collection (i.e., without soil disturbance) of bubbles naturally emanating from the soil. [11] The methane-mixing ratio in the air from the flux chambers was measured on a gas chromatograph (Shimadzu GC-7) equipped with a 3 ft 1/8 in. (1 m 3.16 mm) column filled with Porapak-Q (Alltech) and a flame ionization detector. The reproducibility of these measurements was ±1% and they were in good agreement with the GC analyses carried out at Vercelli with the Hewlett Packard instrument (data not shown). Subsequently the air was pumped through a preparation line in which CO2 and water were removed by liquid nitrogen traps, and the methane was adsorbed on 20-g activated charcoal at liquid nitrogen temperature. This enrichment was performed at a pressure of 150 hPa. The methane was then transferred from the charcoal by warming it to 305 K and back-flushing with nitrogen gas into a 300 ml glass vessel. The sample was split into two. One half was used to determine the D/H ratio in a tunable laser diode spectrometer [Bergamaschi et al., 1994], and the other half was combusted to CO2 and water and the 13C/12C ratio of the CO2 was measured on a MAT-252 mass spectrometer. The reproducibility of this procedure depended on the size of the sample, due to con-

tamination effects in the 13C/12C measurement and stability problems in the D/H measurement. The overall accuracy was ±1 and ±0.05% for D/H and 13C/12C, respectively, for a sample containing 60 mmol methane and ±2% for D/H and ±0.4% for 13C/12C for a 15 mmol sample.

3. Results 3.1. Spatial Variability in Methane Emissions [12] During the first part of the 1998 season, the range of fluxes between the eight chambers was about 2.5-fold. After a small relocation of the chambers in early July, the range was somewhat less. In 1999, seven of the eight chambers showed a similar variability to that experienced in 1998, but the remaining chamber yielded about four times the emission of the chamber with the lowest flux, and more than twice that of the chamber showing the second largest flux values (seasonal average). At the end of the experiment, it was found that the high-flux chamber, unlike the others, had been located above a dense mat of straw, about 4 cm thick, buried at about 19 cm depth. 3.2. Seasonal Flux Trends [13] The average methane fluxes for the chambers in the east and west fields, respectively, during the 1998 and 1999 growing seasons are shown in Figures 3a and 3b, with the


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able to show a significant correlation ( p = 0.056) between temperature and CH4 flux. However, the power of the regression analysis performed was weak (for a = 0.05, b = 0.48). Therefore, the hypothesis that CH4 fluxes were also temperature-dependent in 1999 cannot be rejected. [15] When the flux data were compared with the fluxes obtained from the weekly samplings for isotopic analysis (Figures 4a and 4b), no significant systematic difference was found, indicating that the methane collected for the isotopic work was generally representative of the methane being emitted from the site.

Figure 3. Daily and 15-day running means of methane fluxes during the rice-growing season, as determined by automated chamber measurements in (a) 1998 and (b) 1999. West field: data from four chambers in each season; east field: data from four chambers in 1998 and three (chamber 1 excluded) in 1999 (see text). The thick lines along the time axis show the drainage intervals. exclusion of the data from the high-flux chamber (chamber 1) for 1999. Emissions began in both years shortly after flooding of the fields. Early-season and final drainage led to brief increases in flux values, followed by a rapid decrease, probably after CH4 stored in the soil had been released. This feature was more pronounced in 1998 (Figure 3a) than in 1999 (Figure 3b). There were marked differences in flux between the two seasons. In 1998, average daily emissions were 21.5 mg CH4 m2 h1 (standard deviation = 10.1) and total seasonal emissions reached 58 g CH4 m2 (SE = 6.3 g). In 1999, average daily emission values were smaller (17.9 mg CH4 m2 h1, standard deviation = 4.0), and total seasonal emissions were 50.1 g CH4 m2 (SE = 11.6). [14] In 1998, temperature decreases, usually during periods of heavy rain, were reflected in decreased CH4 flux, especially at the beginning of June and the beginning of August. There was a significant linear correlation between average daily air temperature and average daily CH4 flux ( p < 0.01), with the flux increasing by 2.6 mg CH4 m2 h1 with each 1C increase in air temperature. In 1999, the second half of June was on average about 4C cooler than the year before, and the methane flux was only about half of that observed during the corresponding period in the previous year. Rain and associated temperature decreases in the middle of August and beginning of September were again mirrored by decreases in the methane flux. While the total range of air temperatures at the time of flux measurements was very similar in both years (15– 27C), the total range of CH4 flux values observed was only about half as wide in 1999 as in 1998. This might be a reason why the dataset for 1999 was not

3.3. Isotopic Analysis [16] The dD measurements showed a seasonal cycle throughout the season. Starting with high values at the beginning of the season a reduction over 3 week to low values could be seen (Figure 5). The ratio increased slowly after reaching a minimum 60 days after flooding. Very high values were found at the end of the season during drainage of the field. A similar trend could be seen for d13C (Figure 5). At the beginning of the season methane showed a relatively high 13C/12C ratio for a biogenic source, which decreased as dD decreased over 3 weeks to 64%. A further slow decrease was found during the rest of the time the fields were flooded. Only during drainage did the d13C increase again to relatively high values. Comparing the two chambers, a nearly constant difference of 2% of the d13C values was found in the first year. In the second season of this project the two chambers agreed well. d13C and dD showed no significant systematic difference. [17] During the middle of the 1998 growing season, the measurement rate was increased for 3 days, from one

Figure 4. Methane fluxes during the rice growing season determined by weekly sampling for isotopic measurements from chambers 3 and 4, in combination with a 15-day running-mean from the automated measurements for the same chambers in (a) 1998 and (b) 1999.

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Figure 5. (a – d) Isotopic data of methane emissions in chambers 3 (diamonds) and 4 (triangles) during the rice-growing season in 1998 (left) and 1999 (right): 13CH4/12CH4 ratio d13C (top figures) and CH3D/ CH4 (dD, bottom figures). Results from bubble samples are shown by crosses. The thick lines along the time axis show the drainage intervals.

sample per week to one sample every 6 hours, to derive the diurnal changes in the methane isotope ratios. The measurements from the two chamber sites showed little difference over the period (Figure 6). d13C showed a clear correlation (R2 = 0.78) with the flux for both sites. Slopes of 0.52 ± 0.09% mg CH4 m2 h1 for chamber 3 and 0.24 ± 0.05% mg CH4 m2 h1 for chamber 4 were found (Figure 7a). No dependence of dD on flux was observed. 3.4. Bubble Samples [18] The proportion of the methane emission occurring as bubbles, averaged over tillering and flowering stages and both seasons, was significantly larger (25%) during the afternoon than during the morning (14%) (Difference: p < 0.05). During both growth stages in 1999, the proportion occurring as bubbles was only about half of what it had been in 1998 ( p < 0.05). Methane concentrations in those gas bubbles reaching the water surface were found to be significantly higher during the flowering stage (11%) than during tillering (6.7%) ( p < 0.01). The isotopic measurements on the bubble samples are shown in Figure 5a. Most of the bubble samples were depleted in dD relative to that of the emitted methane and enriched in d13C. The greatest differences in dD were found at the beginning and the end of the growing season, whereas the enrichment in d13C showed no significant changes through the season. Both isotope

ratios showed a slight negative slope of about 10% from the beginning to the end of the season.

4. Modeling and Interpretation [19] To interpret the data a simple box model was developed. It was adapted from the study of Chanton et al. [1997] and included the separation of the different pathways for methane production. The box model consists of two reservoirs: one in which the production of methane occurs and one in which the oxidation process occurs (Figure 8 and Appendix A). The reservoirs are connected via transport between them and to the atmosphere. Transport takes place by molecular diffusion (e.g., in the aerenchyma) or convective flow without isotopic fractionation (e.g., bubbles). We assume fractionation factors constant in time for the different processes (Table 3), which are within the range of those in the publications cited above, and variable reaction rates to simulate the data found here. These factors were included in the model. To understand the influence of the oxidation in combination with diffusion separate model runs were made, in which only the oxidation rate was varied with two scenarios of diffusion, one a low proportion of bulk flow versus molecular diffusion and the other with a high proportion of molecular diffusion (Figures 9a and 9b). The influence of this combination is remarkable. With a low proportion of molecular diffusion, oxidation leads to an


Figure 6. (a – c) Flow, d13C, and dD, versus time in chambers 3 (diamonds) and 4 (triangles) during the highfrequency measurement campaign 15– 17 July 1998 (62 –64 days after flooding). enrichment of the emitted methane in both isotope ratios, d13C and dD. With a high proportion of molecular diffusion (as opposed to bulk flow), which is to be expected for the main growing season, when the major part of the transport occurs via the aerenchyma of the rice plants, d13C only shows a weak change with increasing fraction of oxidation, whereas D/H still becomes enriched. Diffusion itself without oxidation has only a minor effect on the emitted methane because the system very quickly reaches steadystate, in which the emitted methane equals the produced methane, and the methane stored in the anaerobic layer is enriched in the heavier isotopomers (13CH4, CH3D) by the diffusion fractionation. Methane oxidation bacteria are therefore supplied with a higher proportion of these isotopomers and, therefore, the absolute loss of these isotopomers relative to 12 CH 4 is higher than what the fractionation factor due to oxidation may lead one to expect. Depending on the respective fractionation factors due to oxidation and diffusion, the 13C/12C fractionation of the emitted methane may be much smaller than the oxidation fractionation, and if the diffusion fractionation is larger than that due to oxidation it could lead to an inverse isotope effect: the emitted methane being depleted by oxidation. For the D/H ratio, the oxidation fractionation is in all cases

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Figure 7. (a and b) d13C and dD versus flux in chambers 3 (diamonds) and 4 (triangles) during the high-frequency measurement campaign 15– 17 July 1998 (62 – 64 days after flooding). much larger than that of molecular diffusion. Here, the net effect of oxidation and diffusive processes is in all cases a net enrichment of CH3D in the emitted methane. [20] The effect of diffusive fractionation can be seen in the d13C of the bubble samples. During the whole season the

Figure 8. Schematic of the box model.

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Table 3. Model Parameters Constant in Time Parameter

Description 2

P0 = 25 mg CH4 m

1

v0,transport = 0.04 h

1

h

normalization factor for the methane production in the anaerobic layer inverse of residence time in the soil layers in the two boxes that represent the diffusivity (including bubbles) from the anaerobic to the aerobic zone and from the aerobic into the atmosphere

2

m

d13C

dD

d CCH4 ðAcÞ ¼ 39%0 d13 CCH4 ðAcÞ ¼ 80%0 aoxi(12C/13C) = 1.018 adiff(12C/13C) = 1.019

dDCH4 ¼ 339%0 dDCH4 ¼ 370%0 aoxi(H/D) = 1.240 adiff(H/D) = 1.019

13

methane in the bubbles was enriched compared with the methane emitted into the chambers. For dD the large fractionation caused by oxidation of methane hides this effect. Oxidation leads to an enrichment of the emitted methane, which passes through the aerobic layer around the roots and the soil-water interface and therefore masks the depletion effect of molecular diffusion. During the diurnal cycle measurements of the methane isotopic composition (Figure 6), dD was nearly the same for the bubble samples as for the emitted methane, whereas d13C was still enriched in the bubble samples (Figure 5). The dependence of d13C on the flux can be interpreted as a diurnal variation in bubble emission. Higher fluxes can be explained in terms of higher emissions by bubbles, which is a nonfractionating transport of soil methane into the atmosphere that temporarily leads to higher d13C values. At the end of the season, as the fields dried out, the emission peak was found to be combined with high isotopic ratios in both isotopomers. This can be explained by a fast release of this storage pool. The enrichment of both isotopomers in the soil layer was also found in the bubble sample collected during this period. [21] As an example of an application of this model, the model parameters were varied to simulate the 1999 measured values for chamber 4. The parameters that were used to fit the measurements are the methane production (P), partitioning of the production processes (rAc: acetate fermentation versus CO2 reduction), oxidation fraction (Foxidation), and partitioning between methane diffusion through plants versus bubble transport (rDiff) (see Figure 10). The fractionation factors and isotopic signatures of the production pathways are constant in time. The fitting procedure was performed manually by varying the time-dependent factors to minimize the differences between measurements and model results. First, the oxidation fraction foxidation is set. It influences mainly the D/H ratio, because of the large isotopic fractionation factor, but also directly affects the emitted methane. In the next step, the production p is changed to fit the measured methane fluxes. In the last step the production pathways are changed, which mainly affects the 13C/12C ratio but also D/H. The whole procedure is then repeated. After three iterations the deviations between sample data and model are between the error bars of the measurements (see Figure 11). [22] It had been observed in this work (and reported earlier by Butterbach-Bahl et al. [1997]) that the proportion of total emissions via bubbles decreased as the plants

Description isotopic isotopic isotopic isotopic

signature of methane from acetate signature of methane fromCO2 reduction fractionation of methane oxidation fractionation of methane diffusion

develop. Therefore, the proportion of methane released via bubbles and aerenchyma, the parameter rdiffaerobic, was set to start at 0.1 and increase linearly to 0.95 at the end of the season. The partitioning between acetate fermentation and CO2 reduction mainly determines the d13C value of the emitted methane. rAc starts from 0.7, which is equal to 70% methane production via acetate fermentation, and is reduced linearly to 0.42 after 56 days of flooding. Then the decline of rAc slowed down so that it reached a value of 0.38, or 38% acetate fermentation 100 days after flooding, followed by a small increase to 0.40 by the end of the season. Oxidation plays only a minor role at this site. The highest proportion of oxidation is reached near the beginning (21

Figure 9. Influence of oxidation on the isotope ratios 13 CH4/12CH4 (continuous line) and CH3D/CH4 (dashed line) with (a) 10% diffusive gas transport and (b) 90% diffusive gas transport.


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was 66% at the beginning and in the middle of the season for both years. A dD of 50% was found for a sample from 3 September 1999, about 15% higher than before. According to the findings of Sugimoto and Wada [1995] this effect will change the acetate fermentation signature by 6% and CO2/H2 by 10%, which would lead to a change of about 8% for the produced methane assuming 60% production via acetate. A shift of 20% was found in the measurements from the middle and the end of the season. There is no positive trend visible in the bubble samples, which should show the same trend if the production signature changed.

5. Conclusions [23] The isotopic measurements of the emitted methane show a seasonal cycle with higher ratios of 13C/12C and D/H at the beginning of the season and the end and relatively low ratios in the middle of the season. The model simulation indicates a low oxidation rate in the middle of the season, related to the minimum in the D/H ratio at this time. The fraction of oxidation in d13C is masked by diffusion patterns and changes in the ratio between the production pathways. [24] The model simulation shows that the ratio of 13CH4 to 12 CH4 is not a good indicator for the fraction of oxidation;

Figure 10. (a and b) Time-dependent parameters p(t) (solid line, top figure), Foxidation(t) (dashed line, top figure), rAc(t) (solid line, bottom figure), and rdiffaerobic(t) (dashed line, bottom figure) that fit the model simulation with the measurements in chamber 4 in 1999. days after flooding), with a maximum of Foxidation = 0.40, at the end of the season; around 0.10 in the middle of the season. The quantification of this parameter sensitively depends on the effective fractionation factor for CH3D versus CH4 discussed above and the dD signatures of the two production pathways, because Foxidation is mainly determined by the dD signature of the methane emitted. If the effective fractionation factor is smaller then the factor inserted in the model and the signatures of the production pathways are lower, the calculated fraction of methane oxidation will be higher. From measurements of this partitioning, using inhibitors for methane oxidation, a value of 40% is obtained [Kru¨ger et al., 2001] at the beginning of the season, which declines to almost zero in the middle and at the end of the season. This supports the model results for the beginning and the middle of the season. The simulated high oxidation pattern was not found for the end of the season by Kru¨ger et al. [2001]. One reason may be that their measurements were made at the opposite side of the west field (ca. 100 m away from our chambers); another reason could be a change in the water signature at the end. Measurement of the HDO/H2O ratio of water from this field shows that dD

Figure 11. (a – c). Model simulation for the methane measurements of chamber 4 in 1999 shown in comparison with the data for flux (open triangles, top figure), d13C (open diamonds, middle figure), and dD (circles, bottom figure) for this chamber and period.

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however, it can be used to show changes in the production of methane. Laboratory experiments show that the reduction of CO2 leads to strongly depleted methane compared with that produced by acetate fermentation. Direct measurements of the ratio between CO2 reduction and acetate fermentation in the same field and same season agree well with the findings made here [Kru¨ger et al., 2001]. The differences in the isotopic ratios between bubble samples and the emitted methane support the finding of the model simulation that the proportion of methane released by plants relative to that released by bubbles increased throughout the season. These results must be treated with care because only a few bubble measurements were performed, and for these samples it is not clear if they are representative of the soil methane pool. Nevertheless, comparison of the isotopic data with other published seasonal measurements of isotopic ratios from rice paddies indicates that a seasonal cycle with a minimum in the middle of the season is a common phenomenon and should be taken into consideration when modeling the global methane budget using isotope ratios.

Appendix A:

Model Equations

[25] All calculations are based on the equation

~ Þðt Þ ¼ Q ~ð t Þ ~ ðM S ðt Þ:

where vdiff (vbulk) is the loss rate by the diffusive (bulk) transport process, and the sign stands for the outer product of two vectors, in which the resulting vector consists of the product of each vector component: 0

1 a1 b1 ~ c ¼~ a ~ b ¼ @ a2 b2 A: a3 b3

This can be transformed similarly to the production pathways by separating v into time-dependent and isotope ratio-dependent parts. A2. Aerobic Box [28] In equation

~aerobic ~ ~aerobic ¼ Q M S aerobic

the source is equal to the sink of the anaerobic box: ~aerobic ¼ ~ S anaerobic Q

and the sink is made up of the loss by oxidation of methane and the loss by diffusive and bulk flow into the atmosphere: ~ ~ aerobic ~ ~ aerobic ~ voxidation þ M vdiffaerobic S aerobic ¼ M ~ aerobic ~ þM vbulkaerobic ~ aerobic ðt Þ v0;oxidation foxidation ðtÞ~ ¼M k oxidation

M is the amount of methane in the box, Q is the source, and ~ S oxidation S is the sink for methane.Each vector comprises these ~ aerobic ðtÞ v0;transport ftransport ðtÞ amounts for the isotopomers 12CH4, 13CH4, and CH3D.The ~ S oxidation ¼ M model consists of two boxes, which represent the anaerobic

ðrdiffaerobic ðtÞ~ k diff þ ð1 rdiffaerobic ðt ÞÞ~ k bulk Þ; and aerobic zones, respectively. A1. Anaerobic Box [26] In the anaerobic box ~ anaerobic ¼ ~ M Qanaerobic ~ S anaerobic

the sources of methane are the two production pathways and the sink is the loss of methane into the aerobic zone: ~anaerobic ¼ PAc þ PCO Q 2 ¼ P0 pðt Þ rAc ðt Þ~ k Ac þ ð1 rAc ðt ÞÞ~ k CO2 ;

where PAc is the amount of methane produced by acetogenic (CO2-reducing) bacteria. Both production pathways can be mathematically transformed by adding a normalization P0, which is a time-independent production amount, and dimensionless time-dependent parameter p(t), which describes the time evolution of the total production. The ratio of acetogenic to CO2-reducing methane production is parameterized by rAc = PAc(t)/PCO2(t). The k vectors contain ~anaerobic ¼ P0 pðt Þ rAc ðt Þ~ k Ac þ the isotopic information: Q ½1 rAc ðt Þ~ k CO2 g: [27] The sink for this box is made up of losses by diffusive processes and bulk flow. ~ ~ anaerobic ~ ~ vn vbulk S anaerobic ¼ M diff þ M anaerobic ~ o ~ ~ ¼ M anaerobic ðtÞv rdiff ðt Þk diff þ ½1 rdiff ðtÞ~ k bulk ;

where voxidation (vbulkaerobic, vdiffaerobic) is the time-dependent oxidation (transport) rate, which is separated in a similar way as above into a time-independent normalization factor and a fraction f of this factor, which is time dependent. The value of v0 is chosen to be the maximal rate to keep f in the range 0 –1. The emitted methane is equal to the sink of the aerobic box. From this the oxidation rate Foxidation, which is the ratio of the oxidized methane to the produced methane, which is the sum of oxidized methane and emitted methane, can be calculated by Foxidation ðt Þ ¼

v0;oxidation foxidation ðtÞ : v0;transport ftransport ðt Þ þ v0;oxidation foxidation ðt Þ

If the normalization factors v0 for oxidation are set equal to that for transport, the equation for Foxidation can be simplified to Foxidation ðt Þ ¼

foxidation ðtÞ : ftransport ðt Þ þ foxidation ðtÞ

[29] Acknowledgments. We acknowledge the financial support for this work from the European Union, through the ‘‘Riceotopes’’ project, Contract ENV4-CT97-0408, and the contributions of Carl Brenningkmeijer, MPI Mainz, who provided the mass spectrometer facilities and the methane combustion line, and Salvatore Russo, Director of the Istituto Sperimentale per la Cerealicoltura (ISC) in Vercelli, who provided weather data and general logistical support and hospitality.


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F. Conen and K. Smith, Institute of Ecology and Resource Management, University of Edinburgh, Mayfield Rd., Edinburgh EH9 3JU, U.K. H. Fischer and T. Marik, Max Planck Institute for Chemistry, P.O. Box 3060, D-55020 Mainz, Germany. ([email protected])