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应用生态学报 ›› 1995, Vol. 6 ›› Issue (4): 378-382.

• 研究论文 • 上一篇    下一篇

稻田CH4和N2O的排放及养萍和施肥的影响

陈冠雄1, 黄国宏1, 黄斌1, 吴杰1, 于克伟1, 徐慧1, 薛晓华1, 王正平2   

  1. 1. 中国科学院沈阳应用生态研究所陆地生态系统痕量物质生态过程开放实验室, 沈阳 110015;
    2. 美国路易斯安娜州立大学湿地生物地球化学研究所, LA70803
  • 收稿日期:1995-02-22 修回日期:1995-05-24 出版日期:1995-10-25 发布日期:1995-10-25
  • 基金资助:

    国家攀登计划;中国科学院陆地生态系统痕量物质土态过程开放实验室基金

CH4 and N2O emission from a rice field and effect of Azolla and fertilitaion on them

Chen Guanxiong1, Huang Guohong1, Huang Bin1, Wu Jie1, Yu Kewei1, Xu Hui1, Xue Xiaohua1, Wang Zhengping2   

  1. 1. Laboratory of Ecological Process of Trace Substance in Terrestrial Ecosystem, Institute of Applied Ecology, Academia Sinica, Shenyang 110015;
    2. Wetland Biogeochemistry Institute, Louisiana State University, Raton Rouge, LA70803, USA
  • Received:1995-02-22 Revised:1995-05-24 Online:1995-10-25 Published:1995-10-25

摘要: 用箱法对我国东北稻田CH4和N2O排放进行观测研究表明,东北稻田的CH4排放通量比南方稻田小,平均日排放通量和生长季节排放总量分别为0.07和7.4g·m-2.稻田淹水期几乎没有N2O的净排放,但在非淹水期内却有大量N2O排放(平均通量59μgN2O·m-2·h-1).稻田养萍和施肥明显促进CH4和N2O排放。稻田CH4和N2O排放之间存在消长关系。制定稻田温室气体减排技术措施时应充分注意这一关系。

关键词: 稻田, CH4和N2O排放, 养萍, 施肥, 景观空间格局, 景观指数, 太湖流域, CLUE-S模型, 动态转移

Abstract: CH4 and N2O emission from a rice field in northeast China are monitored simultaneously and systematically by using chamber technique to estimate their fluxes from rice fields and to understand the relationship between these two gases emissions.The results show that CH4 emission from rice field in northeast China is much lower than that in south China, with a daily average emission of 0.079·m-2 and total seasonal emission of 7.4g·m-2.Rice fields almost do not emit or deposit N2O during flooding period, but substantially emit it (average flux 59 μgN2O.m-2·h-1) during non-flooding period.CH4 and N2O emissions are greatly enhanced by Azolla and fertilization.Atrade-off between CH4 and N2O emissions is observed, which should be considered when mitigation options for reducing greenhouse gas emission are proposed.

Key words: Rice field CH4 and N2O emission, Azolla, Fertilization, dynamic transfer, CLUE-S model, Taihu Lake basin, landscape spatial pattern, landscape index