Model-based evaluation of methane emissions from paddy fields in East Asia
Model-based evaluation of methane emissions from paddy fields in East Asia
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DOI：
10.2480/agrmet.d-21-00037
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发表时间：
2022-04-01
影响因子：
1.3
通讯作者：
Inatomi, Motoko
中科院分区：
文献类型：
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作者：
Ito, Akihiko;Inoue, Shimpei;Inatomi, Motoko
甲烷（CH 4）是一种强烈的温室气体，也是一种短暂的气候强迫因子，评估其区域收支是未来气候管理的一项重要任务。本研究采用基于气候和土地利用数据的陆地生态地球化学过程模型，估算了东亚稻田CH 4排放量。为了捕捉估计不确定性的范围，本研究使用了两个CH 4排放方案，四个稻田地图，和两个季节性淹没方法，共16个模拟。2000-2015年期间的平均甲烷排放率估计为5.7 Tg CH 4 yr（-1），这与统计清单和其他估计值相似。然而，模拟之间的大标准差（+/- 3.2 Tg CH 4 yr（-1））意味着严重的估计不确定性仍然存在。三个因素-甲烷排放计划，稻田地图，和洪水季节性-负责的估计差异。由于缺乏历史管理数据，模型模拟没有显示出农业CH 4排放量的下降趋势。对温度的敏感性分析表明，温度上升1-2摄氏度（缓解设想情景中的典型升温）将大大增加甲烷排放量。然而，对水管理的敏感性分析表明，较低的地下水位深度将在很大程度上缓解排放量的增加。仍然需要进一步研究，以改善农业数据集和模型，以更好地管理稻田。
Evaluating regional budgets of methane (CH4), a potent greenhouse gas and short-lived climate forcer, is an important task for future climate management. This study estimated historical CH4 emissions from paddy fields in East Asia by using a process-based terrestrial biogeochemical model driven by climate and land-use data. To capture the range of estimation uncertainty, this study used two CH4 emission schemes, four paddy field maps, and two seasonal inundation methods for a total of 16 simulations. The mean CH4 emission rate during 2000-2015 was estimated to be 5.7 Tg CH4 yr(-1), which is similar to statistical inventories and other estimates. However, the large standard deviation ( +/- 3.2 Tg CH4 yr(-1)) among the simulations implies that serious estimation uncertainties remain. Three factors - CH4 emission scheme, paddy field map, and inundation seasonality - were responsible for the disparity of the estimates. Because of the lack of historical management data, the model simulation did not show a decreasing trend in the agricultural CH4 emissions. A sensitivity analysis for temperature indicated that a 1-2 degrees C temperature rise (typical warming in mitigation-oriented scenarios) would substantially enhance CH4 emissions. However, a sensitivity analysis for water management indicated that a lower water-table depth would largely mitigate the emission increase. Additional studies to improve agricultural datasets and models for better paddy field management are still needed.