Modeling Impacts of Alternative Practices on Net Global Warming Potential and Greenhouse Gas Intensity from Rice–Wheat Annual Rotation in China

Wang, Jinyang; Zhang, Xiaolin; Liu, Yinglie; Pan, Xuebiao; Liu, Pingli; Chen, Zhaozhi; Huang, Taiqing; Xiong, Zhengqin

doi:10.1371/journal.pone.0045668

Cited by 10 publications

(3 citation statements)

References 51 publications

(77 reference statements)

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“…The pattern of CH 4 emission fluxes did not change under shading treatments; the characteristic of the CH 4 emission fluxes of this study were consistent with those of other experiments (Fig. ) . Initially, relatively lower CH 4 emission fluxes were caused by minimal methanogenesis as well as weak gas transport ability.…”

Section: Discussionsupporting

confidence: 91%

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Estimation of methane emissions based on crop yield and remote sensing data in a paddy field

Shi

Zhang

et al. 2020

Greenhouse Gases

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Quantifying agricultural greenhouse gas (GHG) emissions is important for addressing global warming. In this regard, empirical models were constructed to evaluate the feasibility of using rice yield and canopy spectral properties for estimating paddy cumulative methane (CH4) emissions (CCE). A field experiment with shading treatments was conducted in 2017. A static chamber‐gas chromatography was used to measure CH4 fluxes during the growing season. Canopy hyperspectral reflectance was measured and then used to calculate the multispectral normalized difference vegetation index (NDVI), the ratio vegetation index (RVI), and the enhanced vegetation index (EVI). The results show that CH4 emissions were positively correlated to rice yield and biomass, indicating that higher biomass provided more substrates for CH4 generation. O2 availability maybe a main factor in the CCE differences under shading treatments. RVI and EVI showed a stronger positive relationship to CH4 emissions than NDVI. The empirical model including yield and EVI‐JS (EVI of jointing‐booting stage) as input variables performed better (adj‐R2 = 0.85, root mean square error [RMSE] = 12.26 kg ha−1) than the model that included only yield (adj‐R2 = 0.5, RMSE = 22.5 kg ha−1). This study suggests that it is feasible to apply remote sensing in paddy CH4 estimation, providing a referable attempt for future regional agricultural GHG emissions quantification. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

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Section: Discussionsupporting

confidence: 91%

“…1). 40,41 Initially, relatively lower CH 4 emission fluxes were caused by minimal methanogenesis as well as weak gas transport ability.…”

Section: Emissionsmentioning

confidence: 99%

Estimation of methane emissions based on crop yield and remote sensing data in a paddy field

Shi

Zhang

et al. 2020

Greenhouse Gases

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“…Increased methane emissions in organic systems were associated to the incorporation of rice straw and manures. As shown in other studies, C sequestration promoted by these inputs could not overcome the increase in methane emissions in terms of global warming potential (Wang et al 2012). Straw and manure have a high content of easily decomposable C, which is associated to methane emissions in rice paddies and therefore to a high scaling factor according to IPCC (2006) methodology.…”

Section: Ricementioning

confidence: 92%

Greenhouse gas emissions from conventional and organic cropping systems in Spain. I. Herbaceous crops

Aguilera

Guzmán

Alonso

2014

Agron. Sustain. Dev.

111

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Agriculture is a major driver of climate change, particularly when all indirect emission sources are accounted for. Mitigation options targeted on one process are often proposed, ignoring their secondary effects on the overall greenhouse gas balance. Integrative methodologies such as life cycle assessment (LCA) are often applied without adjusting emission factors to specific site characteristics. Here, we used LCA to calculate the global warming potential of 38 pairs of organic and conventional herbaceous cropping systems and products in Spain. Crop products included rainfed cereals and pulses, rice, open-air vegetables, and greenhouse vegetables. We used data from farmer interviews and published conversion factors. Our results show that the emission balances were dominated by fossil fuel use rather than by direct field emissions. Organic management reduced crop emissions by 36-65 %, with the exception of rice showing an increase of 8 % due to methane generation. Productbased emissions of organic crops were also lower by 30 % on average, except for rice.

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Estimation and mitigation of greenhouse gases in typical paddy‐upland rotation systems in the middle and lower reaches of the Yangtze River, China

Shi

Wang

et al. 2020

Greenhouse Gases

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Agricultural greenhouse gas (GHG) has a significant effect on climate change. The ability to quantify agricultural GHG and implement practices to mitigate its emissions is of great significance. Optimal GHG mitigation practices in the middle and lower reaches of the Yangtze River, China, have not been well documented. In this study, historical (2000–2014) and projected (2015–2049) methane (CH4) and nitrous oxide (N2O) emissions from paddy‐upland crop rotations were simulated at a county scale using the denitrification–decomposition model. The results demonstrated (1) historical mean emissions of CH4, N2O, and global warming potential (GWP) were 158.6 kg‐C ha−1 year−1, 0.75 kg‐N ha−1 year−1, and 22.15 Tg CO2‐eq year−1 in the study area (1 Tg = 1012 g); (2) CH4 emission rates significantly increased, while there was no significant change in N2O under projected RCP4.5 and RCP8.5 climate scenarios, and RCP8.5 induced 10% more CH4 than RCP4.5; (3) marginal flooding coupled with reduced‐tillage practice was the optimal strategy to mitigate GHG emissions due to its lowest GWP. This study would provide insight into the agricultural GHG emissions, as well as the impact on climate change. Also, a theoretical basis for policymaking would be provided by this study. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

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Modeling Impacts of Alternative Practices on Net Global Warming Potential and Greenhouse Gas Intensity from Rice–Wheat Annual Rotation in China

Cited by 10 publications

References 51 publications

Estimation of methane emissions based on crop yield and remote sensing data in a paddy field

Estimation of methane emissions based on crop yield and remote sensing data in a paddy field

Greenhouse gas emissions from conventional and organic cropping systems in Spain. I. Herbaceous crops

Estimation and mitigation of greenhouse gases in typical paddy‐upland rotation systems in the middle and lower reaches of the Yangtze River, China

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