Carbon Sequestration and Contribution of CO2, CH4 and N2O Fluxes to Global Warming Potential from Paddy-Fallow Fields on Mineral Soil Beneath Peat in Central Hokkaido, Japan

Since each greenhouse gas (GHG) has its own radiative capacity, all three gasses (CO2, CH4 and N2O) must be accounted for by calculating the net global warming potential (GWP) in a crop production system. To compare the impact of GHG fluxes from the rice growing and the fallow season on the annual gas fluxes, and their contribution to the GWP and carbon sequestration (CS) were evaluated. From May to April in Bibai (43°18′ N, 141°44′ E), in central Hokkaido, Japan, three rice paddy fields under actual management conditions were investigated to determine CS and the contribution of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) fluxes to GWP. Methane and N2O fluxes were measured by placing the chamber over the rice plants covering four hills and CO2 fluxes from rice plants root free space in paddy fields were taken as an indicator of soil microbial respiration (Rm) using the closed chamber method. Soil CS was calculated as the difference between net primary production (NPP) and loss of carbon (C) through Rm, emission of CH4 and harvest of crop C. Annual cumulative Rm ranged from 422 to 519 g C m−2 yr−1; which accounted for 54.7 to 55.5% of the rice growing season in particular. Annual cumulative CH4 emissions ranged from 75.5 to 116 g C m−2 yr−1 and this contribution occurred entirely during the rice growing period. Total cumulative N2O emissions ranged from 0.091 to 0.154 g N m−2 yr−1 and from 73.5 to 81.3% of the total N2O emissions recorded during the winter-fallow season. The CS ranged from −305 to −365 g C m−2 yr−1, suggesting that C input by NPP may not be compensate for the loss of soil C. The loss of C in the winter-fallow season was much higher (62 to 66%) than in the growing season. The annual net GWP from the investigated paddy fields ranged from 3823 to 5016 g CO2 equivalent m−2 yr−1. Annual GWPCH4 accounted for 71.9 to 86.1% of the annual net GWP predominantly from the rice growing period. These results indicate that CH4 dominated the net GWP of the rice paddy.

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Effects of Green Manure Application and Prolonging Mid-Season Drainage on Greenhouse Gas Emission from Paddy Fields in Ehime, Southwestern Japan

Agriculture ◽

10.3390/agriculture9020029 ◽

2019 ◽

Vol 9 (2) ◽

pp. 29 ◽

Cited By ~ 4

Author(s):

Yo Toma ◽

Nukhak Nufita Sari ◽

Koh Akamatsu ◽

Shingo Oomori ◽

Osamu Nagata ◽

...

Keyword(s):

Greenhouse Gas ◽

Green Manure ◽

Greenhouse Gas Emission ◽

Rice Paddy ◽

Paddy Fields ◽

N2o Emissions ◽

Gas Emission ◽

Manure Application ◽

Ch4 And N2o ◽

Rice Paddy Fields

Green manure application helps maintain soil fertility, reduce chemical fertilizer use, and carbon sequestration in the soil. Nevertheless, the application of organic matter in paddy fields induces CH4 and N2O emissions. Prolonging mid-season drainage reduces CH4 emissions in paddy fields. Therefore, the combined effects of green manure application and mid-season drainage prolongation on net greenhouse gas emission (NGHGE) were investigated. Four experimental treatments were set up over a 2-year period: conventional mid-season drainage with (CMG) and without (CM) green manure and prolonged (4 or 7 days) mid-season drainage with (PMG) and without (PM) green manure. Astragalus sinicus L. seeds were sown in autumn and incorporated before rice cultivation. No significant difference in annual CH4 and N2O emissions, heterotrophic respiration, and NGHGE between treatments were observed, indicating that green manure application and mid-season drainage prolongation did not influence NGHGE. CH4 flux decreased drastically in PM and PMG during mid-season drainage under the hot and dry weather conditions. However, increasing applied carbon increases NGHGE because of increased CH4 and Rh. Consequently, combination practice of mid-season drainage prolongation and green manure utilization can be acceptable without changing NGHGE while maintaining grain yield in rice paddy fields under organically managed rice paddy fields.

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Comparison of Soil Greenhouse Gas Fluxes during the Spring Freeze–Thaw Period and the Growing Season in a Temperate Broadleaved Korean Pine Forest, Changbai Mountains, China

Forests ◽

10.3390/f11111135 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1135

Author(s):

Chuying Guo ◽

Leiming Zhang ◽

Shenggong Li ◽

Qingkang Li ◽

Guanhua Dai

Keyword(s):

Global Warming ◽

Greenhouse Gas ◽

Global Warming Potential ◽

Growing Season ◽

Korean Pine ◽

Soil Co2 ◽

Freeze Thaw ◽

N2o Fluxes ◽

Ch4 And N2o ◽

Ghg Fluxes

Soils in mid-high latitudes are under the great impact of freeze–thaw cycling. However, insufficient research on soil CO2, CH4, and N2O fluxes during the spring freeze–thaw (SFT) period has led to great uncertainties in estimating soil greenhouse gas (GHG) fluxes. The present study was conducted in a temperate broad-leaved Korean pine mixed forest in Northeastern China, where soils experience an apparent freeze–thaw effect in spring. The temporal variations and impact factors of soil GHG fluxes were measured during the SFT period and growing season (GS) using the static-chamber method. The results show that the soil acted as a source of atmospheric CO2 and N2O and a sink of atmospheric CH4 during the whole observation period. Soil CO2 emission and CH4 uptake were lower during the SFT period than those during the GS, whereas N2O emissions were more than six times higher during the SFT period than that during the GS. The responses of soil GHG fluxes to soil temperature (Ts) and soil moisture during the SFT and GS periods differed. During the SFT period, soil CO2 and CH4 fluxes were mainly affected by the volumetric water content (VWC) and Ts, respectively, whereas soil N2O flux was influenced jointly by Ts and VWC. The dominant controlling factor for CO2 was Ts during the GS, whereas CH4 and N2O were mainly regulated by VWC. Soil CO2 and N2O fluxes accounted for 97.3% and 3.1% of the total 100-year global warming potential (GWP100) respectively, with CH4 flux offsetting 0.4% of the total GWP100. The results highlight the importance of environmental variations to soil N2O pulse during the SFT period and the difference of soil GHG fluxes between the SFT and GS periods, which contribute to predicting the forest soil GHG fluxes and their global warming potential under global climate change.

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Effect of organic, inorganic and slow-release urea fertilisers on CH4 and N2O emissions from rice paddy fields

Paddy and Water Environment ◽

10.1007/s10333-016-0551-1 ◽

2016 ◽

Vol 15 (2) ◽

pp. 317-330 ◽

Cited By ~ 9

Author(s):

Mai Van Trinh ◽

Mehreteab Tesfai ◽

Andrew Borrell ◽

Udaya Sekhar Nagothu ◽

Thi Phuong Loan Bui ◽

...

Keyword(s):

Slow Release ◽

Rice Paddy ◽

Paddy Fields ◽

N2o Emissions ◽

Ch4 And N2o ◽

Slow Release Urea ◽

Rice Paddy Fields

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Soil CH4 and N2O Emissions from Rice Paddy Fields in Southern Brazil as Affected by Crop Management Levels: a Three-Year Field Study

Revista Brasileira de Ciência do Solo ◽

10.1590/18069657rbcs20170306 ◽

2018 ◽

Vol 42 (0) ◽

Cited By ~ 2

Author(s):

Tiago Zschornack ◽

Carla Machado da Rosa ◽

Cecília Estima Sacramento dos Reis ◽

Gabriel Munhoz Pedroso ◽

Estefânia Silva Camargo ◽

...

Keyword(s):

Field Study ◽

Crop Management ◽

Rice Paddy ◽

Paddy Fields ◽

N2o Emissions ◽

Southern Brazil ◽

Ch4 And N2o ◽

Rice Paddy Fields

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Options for mitigating global warming potential of a double-rice field in China

10.5194/acp-2016-227 ◽

2016 ◽

Author(s):

Guangbin Zhang ◽

Haiyang Yu ◽

Xianfang Fan ◽

Yuting Yang ◽

Jing Ma ◽

...

Keyword(s):

Global Warming ◽

Rice Field ◽

N2o Emission ◽

Rice Fields ◽

N2o Emissions ◽

Ch4 Emission ◽

Double Rice ◽

Ch4 And N2o ◽

Late Rice ◽

Winter Fallow

Abstract. Traditional land managements (neither drainage nor tillage, NTND) in winter fallow season result in substantial CH4 and N2O emissions from the double-rice fields in China. For investigating the effects of drainage and tillage in winter fallow season on global warming potentials (GWPs) of CH4 and N2O emissions and developing mitigation options, a field experiment with four treatments: NTND, drainage but non-tillage (NTD), tillage but non-drainage (TND), and both drainage and tillage (TD) were carried out from 2010 to 2014 in a Chinese double-rice field. In winter fallow season total precipitation and mean daily temperature had important effects on CH4 emission, and significant correlations were observed between them and CH4 emission. Compared with NTND, drainage and tillage reduced CH4 emission in early- and late-rice seasons and decreased annual emission by 54 and 33 kg CH4 ha−1 yr−1, respectively. Drainage and tillage increased N2O emission in winter fallow season while reduced it in early- and late-rice seasons, causing annual N2O emission unaffected. Accordingly, the GWPs were decreased by 1.49 and 0.92 t CO2-eq ha−1 yr−1, respectively, and they were far more reduced by combining drainage with tillage, with a mitigation potential of 1.96 t CO2-eq ha−1 yr−1. Low total C content and high C/N ratio in rice residues revealed that tillage in winter fallow season reduced CH4 and N2O emissions in early- and late-rice seasons. Moreover, drainage and tillage significantly decreased the abundance of methanogens in paddy soil, which was a possible reason for the decrease of CH4 emission. Greenhouse gas intensity was significantly decreased by drainage and tillage, and it was much more reduced by combining drainage with tillage, with a reduction of 0.17 t CO2-eq t−1 yield yr−1. The results indicate that soil drainage combined with tillage in winter fallow season is an effective mitigating strategy in double-rice fields.

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Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs)

Water ◽

10.3390/w11102169 ◽

2019 ◽

Vol 11 (10) ◽

pp. 2169 ◽

Cited By ~ 4

Author(s):

Tabassum Abbasi ◽

Tasneem Abbasi ◽

Chirchom Luithui ◽

Shahid Abbas Abbasi

Keyword(s):

Nitrous Oxide ◽

Paddy Fields ◽

Anthropogenic Sources ◽

Nitrous Oxide Emissions ◽

Soil Conditions ◽

N2o Emissions ◽

Ch4 Emissions ◽

Artificial Neural ◽

Ch4 And N2o

Paddy fields, which are shallow man-made wetlands, are estimated to be responsible for ~11% of the total methane emissions attributed to anthropogenic sources. The role of water use in driving these emissions, and the apportioning of the emissions to individual countries engaged in paddy cultivation, are aspects that have been mired in controversy and disagreement. This is largely due to the fact that methane (CH4) emissions not only change with the cultivar type but also regions, climate, soil type, soil conditions, manner of irrigation, type and quantity of fertilizer added—to name a few. The factors which can influence these aspects also encompass a wide range, and have origins in causes which can be physical, chemical, biological, and combinations of these. Exceedingly complex feedback mechanisms, exerting different magnitudes and types of influences on CH4 emissions under different conditions, are operative. Similar is the case of nitrous oxide (N2O); indeed, the present level of understanding of the factors which influence the quantum of its emission is still more patchy. This makes it difficult to even understand precisely the role of the myriad factors, less so model them. The challenge is made even more daunting by the fact that accurate and precise data on most of these aspects is lacking. This makes it nearly impossible to develop analytical models linking causes with effects vis a vis CH4 and N2O emissions from paddy fields. For situations like this the bioinspired artificial intelligence technique of artificial neural network (ANN), which can model a phenomenon on the basis of past data and without the explicit understanding of the mechanism phenomena, may prove useful. However, no such model for CH4 or N2O has been developed so far. Hence the present work was undertaken. It describes ANN-based models developed by us to predict CH4 and N2O emissions using soil characteristics, fertilizer inputs, and rice cultivar yield as inputs. Upon testing the predictive ability of the models with sets of data not used in model development, it was seen that there was excellent agreement between model forecasts and experimental findings, leading to correlations coefficients of 0.991 and 0.96, and root mean square error (RMSE) of 11.17 and 261.3, respectively, for CH4 and N2O emissions. Thus, the models can be used to estimate CH4 and N2O emissions from all those continuously flooded paddy wetlands for which data on total organic carbon, soil electrical conductivity, applied nitrogen, phosphorous and potassium, NPK, and grain yield is available.

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