Literature DB >> 18637360

[Modeling the ammonia volatilization from common urea and controlled releasing urea fertilizers in paddy soil of Taihui region of China by Jayaweera-Mikkelsen model].

Hui-lin Li1, Yong Han, Zu-cong Cai.   

Abstract

The ammonia volatilization on the Typic Gleyi-stagnic Anthrosol with application of common urea and controlled release urea (LP-S100) fertilizers in the rice seasons in paddy soil of Taihui region of China was modeled by Jayaweera-Mikkelsen model. Results showed great difference of ammonia volatilization from two type fertilizers was detected with lysimeter experiment in the rice season. Nitrogen loss via ammonia volatilization after common urea application with conventional ways was 29%-35%, while only 5% of controlled release urea-N was volatilized. The Jayaweera-Mikkelsen model was over estimated the total amount of ammonia volatilization in the whole season, and great deviation from the measured data was obvious for the higher volatilization from common urea fertilizer. The estimated data were 2.95-4.19 times of the measures one for common urea treatments, while they were 1.19-1.40 times of those measured for LP-S100 treatments. The order of magnitude quotient was one of the indicators to evaluate the model estimation. The value of it was 0.8, which indicated the estimation of the model need improvement. Though sensitive analysis for the five parameters in the model was tested and amended the parameter of the concentration of NH4+ -N, a limited term was inducted in the model operation. The amended model got better results as the ratio of estimation to measured data was decreased to 1.12-1.28. The alga activity in the paddy field influenced ammonia volatilization and might make the failure of the model estimation of the original model.

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Year:  2008        PMID: 18637360

Source DB:  PubMed          Journal:  Huan Jing Ke Xue        ISSN: 0250-3301


  1 in total

1.  Improved Jayaweera-Mikkelsen model to quantify ammonia volatilization from rice paddy fields in China.

Authors:  Xiaoying Zhan; Chuan Chen; Qihui Wang; Feng Zhou; Kentaro Hayashi; Xiaotang Ju; Shu Kee Lam; Yonghua Wang; Yali Wu; Jin Fu; Luping Zhang; Shuoshuo Gao; Xikang Hou; Yan Bo; Dan Zhang; Kaiwen Liu; Qixia Wu; Rongrui Su; Jianqiang Zhu; Changliang Yang; Chaomeng Dai; Hongbin Liu
Journal:  Environ Sci Pollut Res Int       Date:  2019-01-28       Impact factor: 4.223

  1 in total

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