Haoyu Qian, Zhengqi Yuan, Xiangcheng Zhu, Yuanfa Huang, Min Li, Jiarui Li, Yukun Ren, Jinfei Feng, Shan Huang, Wenjun Dong, Feng Jin, Jiping Gao, Qiang Xu, Ting Peng, Bing Zhang, Tao Yang, Ming Zhang, Xiaoning Hang, Wanjun Ren, Ziyin Shang, Jinyang Wang, Jianwen Zou, Songhan Wang, Zhenghui Liu, Ganghua Li, Qi Zhao, Fengbo Li, Weijian Zhang, Yanfeng Ding, Kees Jan van Groenigen, Yu Jiang
ABSTRACT Nitrogen (N) management is critical for ensuring food security and mitigating greenhouse gas (GHG) emissions. In rice paddies, the effectiveness of N management in maximizing yields and minimizing N losses is highly dependent on local environmental conditions and thus varies widely across regions. However, the influence of optimized, site‐specific N management on methane (CH 4 ) emissions remains poorly quantified and is not reflected in current IPCC Tier 1 methodologies. Here, we synthesize data from multiregional field experiments and conduct a meta‐analysis to show that locally optimized N management practices—such as delayed fertilizer application, reduced N input, and deep placement—reduce CH 4 emissions from rice paddies by 16%–21%. The experiments further show that these practices suppress CH 4 emissions by lowering soil N availability and organic matter decomposition, thereby limiting substrates for methanogenesis. Combining survey data from 155 counties with machine learning models, we estimate that implementing optimized N strategies across China's rice‐growing regions could reduce CH 4 emissions by 16% while simultaneously increasing rice yields by 7%. These findings underscore the dual benefits of locally optimized N management for agricultural productivity and climate change mitigation, and provide a foundation for improving CH 4 emission estimates under diverse management regimes.