文献类型：期刊文献

英文题名：Integrating major agricultural practices into the TRIPLEX-GHG model v2.0 for simulating global cropland nitrous oxide emissions: Development, sensitivity analysis and site evaluation

作者：Song, Hanxiong[1] Peng, Changhui[1,2,5] Zhang, Kerou[3] Zhu, Qiuan[4]

第一作者：Song, Hanxiong

通信作者：Peng, CH[1]

机构：[1]Univ Quebec Montreal, Inst Sci Environm, Case Postale 8888 Succ Ctr Ville, Montreal, PQ H3C 3P8, Canada;[2]Hunan Normal Univ, Sch Geog Sci, Changsha 410081, Peoples R China;[3]Chinese Acad Forestry, Inst Wetland Res, Beijing 100091, Peoples R China;[4]Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210024, Peoples R China;[5]Univ Quebec Montreal UQAM, succursale Ctr Ville, Case postale 8888, Montreal, PQ H3C 3P8, Canada

年份：2022

卷号：843

外文期刊名：SCIENCE OF THE TOTAL ENVIRONMENT

收录：;EI(收录号：20222712313798);Scopus(收录号：2-s2.0-85133200176);WOS:【SCI-EXPANDED(收录号:WOS:000826504500004)】；

基金：This study was funded by the Natural Sciences and Engineering Research Council of Canada Discovery Grant, the National Key R &D Program of China (2016YFC0500203) and the Merit Scholarship Program for Foreign Students provided by China Scholarship Council (CSC) and the Ministre de l'ducation et de l'Enseignement Suprieur (MEES) . We thank LetPub ( www.letpub.com ) for its linguistic assistance during the preparation of this manuscript.

语种：英文

外文关键词：Nitrous oxide; Process-based model; Croplands; Denitrification; Fertilization

摘要：Nitrous oxide (N2O) emissions from croplands are one of the most important greenhouse gas sources while the estimation of which remains large uncertainties globally. To simulate N2O emissions from global croplands, the process-based TRIPLEX-GHG model v2.0 was improved by coupling the major agricultural activities. Sensitivity experiment was used to measure the impact of the integrated processes to modeled N2O emission found chemical N fertilization have the highest relative effect sizes. While the coefficient of the NO(3)(- )consumption rate for denitrification (COEdNO3), controlling the first step of the denitrification process was identified to be the most sensitive parameter based on sensitivity analysis of model parameters. The model performed well when simulating the magnitude of the daily N2O emissions for 39 calibration sites and the continental mean of the parameters were used to producing reasonable estimations for the means of the measured daily N2O fluxes (R-2 = 0.87, slope = 1.07) and emission factors (EFs, R-2 = 0.70, slope = 0.72) during the experiment periods. The model reliability was further confirmed by model validation. General trend of modeled daily N2O emissions were reasonably consistent with the observations of selected validated sites. In addition, high correlations between the results of modeled and observed mean N2O emissions (R-2 = 0.86, slope = 0.82) and EFs (R-2 = 0.66, slope = 0.83) from 68 validation sites were obtained. Further improvement on more detailed estimations for the variation of the environmental factors, management effects as well as accurate model input model driving data are required to reduce the uncertainties of model simulations. Consequently, our simulation results demonstrate that the TRIPLEX-GHG model v2.0 can reliably estimate N2O emissions from various croplands at the global scale, which contributes to closing global N2O budget and sustainable development of agriculture.