Methane emissions from typical paddy fields in Liaohe Plain and Sanjiang Plain, Northeast China

Liaohe Plain is situated in the southern tip of Northeast China (figure 1). Liaohe Plain Rice Field Station is located in the centre of Liaohe Plain (40°41'–41°27'N, 121°30'–122°41'E) with an area of cultivated land of 144 million ha. The annual, July and January average temperatures are 8.6, 24.4 and −9.8 °C, respectively. The frost-free period lasts 171 days, and the area has an accumulated temperature of 3509 °C and an average annual precipitation of 631 mm [17]. Sanjiang Plain is situated in the north-eastern tip of Northeast China. Sanjiang Plain Rice Field Station is located in the centre of Sanjiang Plain. Here, the altitude is 30.0–50.0 m, the average temperatures in July and January are 21–22 and −21 to −18 °C, respectively, the accumulated temperature is 2300 °C–2500 °C, the frost-free period is 140 d, and the average precipitation is 500–650 mm [18].

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The 2017 growth season on Liaohe Plain lasted from April 18th to September 27th, and that on Sanjiang Plain from April 15th to September 12th. The onset of the 2018 fertility period was close to that in 2017. However, the 2018 tillering periods for rice were delayed compared with those in 2017 (table 1). Irrigation at Liaohe Plain was in early May, later than that at Sanjiang Plain (late April). Drainage occurred between the end of the rice the milk maturity stages (August 23rd–27th). Harvest was in early October.

The soil in Liaohe Plain is characterised as a salinized paddy with an alkaline pH value. The tested rice variety was Yanfeng 47. The soil in Sanjiang Plain is characterised as black soil (Chernozem) and has a weakly acidic pH value (table 2). The typical redox value of the paddy field was in the range +300 to −200 mV [19]. The tested rice variety was LongJing 31. Sowing was carried out in the middle of April, but transplanting and reaching maturity in Liaohe Plain occurred later than in Sanjiang Plain.

The EC method calculates the flux of CH₄ and CO₂, LE, and H by measuring the scalar of both vertical wind speed and turbulent fluctuation, and then calculates the covariance between them [20].

EC observation systems were installed at Liaohe Plain (40°55'53''N, 121°57'66''E) and Sanjiang Plain (47°9'7''N, 131°56'19''E) (figure 1). The Kormann & Meixner (KM) footprint model was used to estimate the contribution to a regional measurement [21]. The KM model allowed the estimation of net fluxes for non-uniform wind directions. The main parameters driving the KM model include the observation time, friction wind speed (u*), Monin–Obukhov length and wind direction. Output parameters include the zero plane displacement. Rice was grown on 90% of the contribution area of the EC observation system.

The EC system consisted of a precision 3-axis sonic anemometer, an open-path CO₂/H₂O analyser (Li-7700, Licor, Lincoln, NE, USA) and a data collector (Li-7550, Licor). The sampling frequency was 10 Hz and the installation height was 4 m. The output data included horizontal wind speed (U_x, U_y), vertical wind speed (U_z), CO₂ absolute density, water vapour absolute density, ultrasonic virtual temperature (T_s), atmospheric pressure (pressure) and CSAT3 diagnostic value (diag_csat). The system calculates the flux in real time (every 30 min), and saved in 30-min intervals (every 30 min); and data was measured at 10 Hz and then averaged over 30 min periods (10 Hz; figure 2).

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The calibration of the LI-7700 open-path gas analyzer was checked at semiannual intervals, using a calibration cell provided by the manufacturer. The LI-7700 was calibrated span against a 5 ppm CH₄ standard gas and calibrated zero by 'zero gas'.

The CH₄ flux (F_C) was calculated as:

$$\begin{eqnarray}&&{F}_{C}=\overline{w^{\prime} {\rho }_{C}^{{\prime} }}\end{eqnarray} \tag{ 1 }$$

where $w^{\prime}$ is the instantaneous deviation between the vertical wind speed and the mean value, i.e., the disturbance value; ${\rho }_{c}^{{\prime} }$ is the instantaneous disturbance value of the CH₄ density; and $\overline{w^{\prime} {\rho }_{C}^{{\prime} }}$ is the covariance of the vertical wind speed and the CH₄ density (Baldocchi et al 1988) [20]. Raw data were manipulated using Eddypro 5.1.1(Licor) software to carry out coordinate rotation, spiking removal, time-delay removal and compensation of density fluctuations (WPL) corrections.

Quality assurance and quality control (QA/QC) was performed to remove outliers. The calculation of spectral correction factors was performed in different ways for 'small' and 'large' fluxes using the software's 'minimum' and 'unstable' values. During periods of precipitation, the observation error of the EC observation system was relatively large. Observational data collected during precipitation events were, therefore, excluded.

To accurately calculate the annual values of net ecosystem exchange (NEE) at the sites, gap-filling was required to account for missing data. A commonly used method for filling in small sections of missing data (1–3 points) is MS Excel's interpolation FORECAST function. For longer datasets, the mean diurnal variation is an interpolation technique where the missing NEE value for a certain time period (30 min) is replaced with the averaged value of the adjacent days at exactly that time of day. Windows of 7 and 14 days were chosen for averaging for daytime and night time missing data, respectively. Missing half-hourly data points (owing to, e.g., instrument and power failure) during the winter season were filled using the mean diurnal variation approach and a 14-day window [22]. Half-hourly data and the CH₄ mole-fraction were thus calculated and time series standard deviation analysis of the CH₄ flux was performed using MS Excel 2013.

An automatic weather observation system (A753 WS-X, Adcon, Vienna, Austria) was installed at 2.5 m. The soil temperature sensor (SM1) was installed at −5 cm. Photosynthetically active radiation (PAR) was observed by an PAR sensor (PAR1, Adcon). The main meteorological factors were monitored throughout the rice's growth period to establish relationships between meteorological factors and CH₄ emissions.

In 2017, the CH₄-release cycle ran from May 2nd (three-leaf stage) to September 12th (late-heading stage) for rice fields at the Sanjiang site. The CH₄ flux peaked at 0.52 g CH₄ m⁻²s⁻¹ on June 26th (rice tillering period; figure 2(A)). The rest of the time, CH₄ emissions were essentially zero. The annual CH₄ emission flux from paddy fields in Sanjiang Plain was 26.77 g CH₄ m⁻²year⁻¹, of which 79.57% was emitted in June and July.

The CH₄-release period at the Liaohe site was from April 18th (sowing date) to October 27th (the end of the growing season). Annual CH₄ emissions from paddy fields in Liaohe Plain were 16.17 g CH₄ m⁻²year⁻¹ (figure 2(A)), of which the highest CH₄ emissions occurred in July (34.78% of annual total). There was weak CH₄ absorption in winter. CH₄ emissions from Liaohe Plain were lower than those from Sanjiang Plain. Three peaks in the CH₄ flux were observed. These occurred during the early-transplanting stage, the jointing and booting stage and the mature stage. These peaks were in accordance with the results of Qingyu's 2013 study [23]. The maximum CH₄ flux appeared at the jointing stage, reaching 0.33 μmol CH₄ m⁻²s⁻¹. CH₄ emissions were low during the tillering stage. The lowest CH₄ emissions were observed during the regeneration stage; this was different to the lowest-emitting stage in Sanjiang Plain.

The net fluxes of CH₄ in 2018 were similar to those in 2017. In 2018, the CH₄ emission fluxes from paddy fields were 32.76 and 20.51 g CH₄ m⁻² year⁻¹ in Sanjiang Plain and Liaohe Plain, respectively.

To determine the diurnal variation of the CH₄ fluxes during the different stages of the growing season, the data were divided into five stages, corresponding with observed changes in CH₄ emission data (figure 2). Stage A represented the time until soil thawing occurred (1–76 days) (figure 3(A)). Stage B covered soil thawing to seeding (77–104 days) (figure 3(B)). Stage C started after sowing and continued to the green period (105–141 days) (figure 3(C)). Stage D ran from reviving to the onset of booting (141–190 days) (figure 3(D)). Stage E covered the period from booting to the onset of milk ripening (191–234 days) (figure 3(E)). Stage F started at milky ripening and ran until the end of growing season (235–273 days) (figure 3(F)). Stage G (274–365 days) represented the period from the end of the growing season until the end of the year (figure 3(G)). Data for each stage were grouped according to the time interval. The stage's half-hourly average was then calculated. The peak CH₄ fluxes (mean ± standard deviation) for each stage of the fallow period in Liaohe Plain were 0.12 ± 0.13, 0.17 ± 0.12 and 0.04 ± 0.07 μmol CH₄ m⁻² s⁻¹ (figure 3(G)) for stages A, B and G, respectively. During the growing season, the peak values were 0.15 ± 0.14, 0.19 ± 0.07 and 0.15 ± 0.24 μmol CH₄ m⁻² s⁻¹ for stages C, D and E, respectively. Different trends of diurnal (within day) variation of the CH₄ emissions flux from paddy fields were observed for different periods in 2017. Diurnal variations were obvious for Liaohe Plain for stages A–E (from the first day of measurements to the onset of milk ripening). Diurnal variations were very small during the fallow period (stages A, B and D). During this period, the CH₄ flux began increasing from 09:00, peaked at 13:00, and then fell back to a minimum around 15:00. Weak absorption of CH₄ during the night could offset daytime emissions in Liaohe Plain. In the growing season, the CH₄ flux began to increase at 08:00, peaked at 12:00–14:00, and fell to a minimum value by 17:00–18:00. There was little or no CH₄ emissions at night. The average CH₄ flux for the growing season was 0.065 μmol CH₄ m⁻² s⁻¹.

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There were obvious diurnal variations during the rice's growing period in Sanjiang Plain (figures 3(C)–(E)), but no diurnal variations were observed during the fallow period. The peak CH₄ flux was 0.07 ± 0.09, 0.43 ± 0.13 and 0.18 ± 0.11 μmol CH₄ m⁻² s⁻¹ (figure 3(E)) in stages C, D and E, respectively. The CH₄ flux began to increase at 08:00, peaked at 12:00–13:00, and decreased to a minimum value around 15:00–18:00. Night time emissions of CH₄ from the tillering to jointing stages were above 0.2 μmol CH₄ m⁻² s⁻¹, and were above 0.1 μmol CH₄ m⁻² s⁻¹ from the booting to the onset of milk ripening stages. The average CH₄ flux for the growing period was 0.127 μmol CH₄ m⁻² s⁻¹ in Sanjiang Plain. As shown in figure 4, methane emissions were higher in the afternoon (when the maximum temperature was observed) than in the morning.

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In 2017, the average air temperature at Sanjiang Plain Station was 3.43 °C, and the accumulated ≥10 °C temperature (figure 4(A)) was 2782 °C. The average air temperature at Liaohe Plain Station was 10.16 °C, and the accumulated ≥10 °C temperature was 3924 °C. These air temperatures were well suited to rice growth, with those in Sanjiang Plain more favourable than those in Liaohe Plain. The maximum air temperature of the two stations was observed from late June to July, corresponding to the peak in CH₄ emissions in Sanjiang Plain. The optimum air temperature for CH₄ production in the Northeast Plain was 25 °C–30 °C. The cumulative precipitation at Sanjiang Plain Station was 587.9 mm (figure 4(B)), which was higher than that at Liaohe Plain Station (521.7 mm). The frequency of precipitation was also higher at Sanjiang Plain Station than that at Liaohe Plain Station.

The PAR was 296.86 and 400.86 W · m⁻²year⁻¹ at Sanjiang Plain Station and at Liaohe Plain Station (figure 4(C)), respectively. The PAR peak was from late May to early June, which corresponds to the first peak in CH₄ emissions in Liaohe Plain but does not correspond to the first CH₄ emissions peak in Sanjiang Plain. There was a significant linear correlation between PAR and methane flux (figure 5). The average wind speed at Liaohe Plain Station was 12.23 m h⁻¹ , which was higher than that at Sanjiang Plain Station (11.64 m h⁻¹) (figure 4(D)). In the tillering and jointing stage, the average wind speed was lower than that in the other stages; CH₄ emitted from rice during this stage tended to accumulate nearer to the ground.

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The annual average temperature of the soil surface at Sanjiang Plain Station was 6.06 °C. The ground was frozen for 138 days, from January 1st to March 17th and from November 2nd to December 31st. The temperature was 4.53 °C lower than that at Liaohe Plain (10.59 °C) where the soil was frozen for less time (114 days); from January 1st to March 16th and from November 23rd to December 31st. Cold winter temperatures inhibit microbial activity across the large landmasses and very low CH₄ fluxes were observed from the paddy fields when the soil was frozen. CH₄ was absorbed at night.

The CH₄ emission flux was low or zero when the soil temperature was lower than 0 °C. The night-time temperature sensitivity in Sanjiang Plain was obviously greater than that during the daytime. The night-time temperature sensitivity followed an exponential relationship (figure 6). The temperature coefficient Q10 was calculated using the exponential equation. At night in stages C, D and E, the values of Q10 were 0.24, 0.17 and 0.09, respectively. Q10 was highest between the sowing and the green periods of the growing season (0 °C–20 °C). The CH₄ emission fluxes in Liaohe Plain were more sensitive to changes in temperature than those in Sanjiang Plain (figure 7). At night during these stages, the value of Q10 was 0.10. The emissions fluxes of CH₄ in stages C, D and E were generally below 0.2 μmol · CH₄ m⁻² s⁻¹ during the daytime and below 0.1 μmol CH₄ m⁻² s⁻¹ at night.

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