globalchange  > 气候变化事实与影响
DOI: 10.1002/2014GB005046
Scopus记录号: 2-s2.0-84947126787
论文题名:
New model for capturing the variations of fertilizer-induced emission factors of N2O
作者: Zhou F; , Shang Z; , Zeng Z; , Piao S; , Ciais P; , Raymond P; A; , Wang X; , Wang R; , Chen M; , Yang C; , Tao S; , Zhao Y; , Meng Q; , Gao S; , Mao Q
刊名: Global Biogeochemical Cycles
ISSN: 8866236
出版年: 2015
卷: 29, 期:6
起始页码: 885
结束页码: 897
语种: 英语
英文关键词: agricultural soils ; Bayesian inference ; data mining ; emission factor ; nitrous oxide ; nonlinear response
英文摘要: Accumulating evidence indicates that N2O emission factors (EFs) vary with nitrogen additions and environmental variations. Yet the impact of the latter was often ignored by previous EF determinations. We developed piecewise statistical models (PMs) to explain how the N2O EFs in agricultural soils depend upon various predictors such as climate, soil attributes, and agricultural management. The PMs are derived from a new Bayesian Recursive Regression Tree algorithm. The PMs were applied to the case of EFs from agricultural soils in China, a country where large EF spatial gradients prevail. The results indicate substantial improvements of the PMs compared with other EF determinations. First, PMs are able to reproduce a larger fraction of the variability of observed EFs for upland grain crops (84%, n = 381) and paddy rice (91%, n = 161) as well as the ratio of EFs to nitrogen application rates (73%, n = 96). The superior predictive accuracy of PMs is further confirmed by evaluating their predictions against independent EF measurements (n = 285) from outside China. Results show that the PMs calibrated using Chinese data can explain 75% of the variance. Hence, the PMs could be reliable for upscaling of N2O EFs and fluxes for regions that have a phase space of predictors similar to China. Results from the validated models also suggest that climatic factors regulate the heterogeneity of EFs in China, explaining 69% and 85% of their variations for upland grain crops and paddy rice, respectively. The corresponding N2O EFs in 2008 are 0.84 ± 0.18% (as N2O-N emissions divided by the total N input) for upland grain crops and 0.65 ± 0.14% for paddy rice, the latter being twice as large as the Intergovernmental Panel on Climate Change Tier 1 defaults. Based upon these new estimates of EFs, we infer that only 22% of current arable land could achieve a potential reduction of N2O emission of 50%. © 2015. The Authors.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78018
Appears in Collections:气候变化事实与影响

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作者单位: Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China; Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, Gif-sur-Yvette, France; Yale School of Forestry and Environmental Studies, Yale University, New Haven, CT, United States; Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, China; Research Institute of Engineering Technology, Yunnan University, Kunming, China; Department of Water Environmental Planning, Chinese Academy for Environmental Planning, Beijing, China; Department of Statistics, University of Connecticut, Storrs, CT, United States

Recommended Citation:
Zhou F,, Shang Z,, Zeng Z,et al. New model for capturing the variations of fertilizer-induced emission factors of N2O[J]. Global Biogeochemical Cycles,2015-01-01,29(6)
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