Authors
Minpeng Hu, Zhongjie Yu, Timothy J Griffis, Kelly Aho, Yucang Wang, Jie Yang, Wendy H Yang, Carl J Bernacchi, Justin M McGrath, Randy A Dahlgren, Hanqin Tian, John M Baker
Published in
Proceedings of the National Academy of Sciences of the United States of America. Volume 123. Issue 26. Pages e2524113123. Jun 30, 2026. Epub Jun 22, 2026.
Abstract
Riverine nitrous oxide (N2O) emissions constitute a significant yet uncertain component of global greenhouse gas budgets. Integrating approximately 3,600 observations across the contiguous United States (CONUS), we present a monthly resolved, national-scale estimate of riverine N2O emissions (60.7 Gg N2O-N y-1; 95% CI: 41.9 to 71.2) using a machine-learning framework. Our analysis reveals that enhanced hydrologic connectivity strongly regulates nitrogen and N2O delivery to streams, driving emission hot moments during high-flow periods, especially in nutrient-rich low-order streams. The Midwest Corn Belt is identified as a major emission hot spot, where seasonal increases in connectivity (e.g., late-winter thaws and postharvest rainfall) amplify riverine emissions relative to direct soil emissions. Our watershed-specific EF5r (0.0005 to 0.029) exceeds the IPCC default (0.0026) by more than twofold on average and up to 10-fold in intensively managed watersheds. These findings highlight the importance of incorporating hydrologic connectivity and nitrogen transport into climate models and watershed nitrogen management strategies.
PMID:
42330281
Bibliographic data and abstract were imported from PubMed on 23 Jun 2026.
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