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Re-estimating methane emissions from Chinese paddy fields based on a regional empirical model and high-spatial-resolution data

文献类型： 外文期刊

作者： Sun, Jianfei 1 ; Wang, Minghui 1 ; Xu, Xiangrui 1 ; Cheng, Kun 1 ; Yue, Qian 3 ; Pan, Genxing 1 ;

作者机构： 1.Nanjing Agr Univ, Inst Resource Ecosyst & Environm Agr, 1 Weigang, Nanjing 210095, Jiangsu, Peoples R China

2.Nanjing Agr Univ, Jiangsu Collaborat Innovat Ctr Solid Organ Waste, 1 Weigang, Nanjing 210095, Jiangsu, Peoples R China

3.Jiangsu Acad Agr Sci, Key Lab Crop & Anim Integrated Farming, Minist Agr & Rural Affairs, Recycling Agr Res Ctr, Nanjing 210014, Peoples R China

关键词： CH4; Rice paddy; Model simulation; Uncertainty; Greenhouse gas; Climate change

期刊名称：ENVIRONMENTAL POLLUTION （ 影响因子：8.071； 五年影响因子：8.35 ）

ISSN： 0269-7491

年卷期： 2020 年 265 卷

页码：

收录情况： SCI

摘要： Quantifying methane (CH4) emissions from paddy fields is essential for evaluating the environmental risks of the paddy rice production system, and improving the accuracy of CH4 modeling is a key issue that needs to be addressed. Based on a database containing 835 field measurements, both single national and region-specific models were established to estimate CH4 emissions from paddy fields considering different environmental factors and management patterns using 70% of the measurements. The remaining 30% of the measurements were then used for model evaluation. The performance of the region-specific model was better than that of the single national model. The region-specific model could simulate CH4 emissions in an unbiased manner with R-2 values of 0.15-0.70 and efficiency values of 11-60%. The paddy rice type, water regime, organic amendment, latitude, and soil characteristics (pH and bulk density) were identified as the main drivers in the models. By inputting the high-resolution spatial data of these drivers into the established model, the CH4 emissions from China's paddy fields were estimated to be 4.75 Tg in 2015, with a 95% confidence interval of 4.19-5.61 Tg. The results indicated that establishing and driving a region-specific model with high-resolution data can improve the estimation accuracy of CH4 emissions from paddy fields. (C) 2020 Elsevier Ltd. All rights reserved.

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