Indirect nitrous oxide emission factors of fluvial networks can be predicted by dissolved organic carbon and nitrate from local to global scales.

Streams and rivers are important sources of nitrous oxide (N O), a powerful greenhouse gas. Estimating global riverine N O emissions is critical for the assessment of anthropogenic N O emission inventories. The indirect N O emission factor (EF ) model, one of the bottom-up approaches, adopts a fixed EF value to estimate riverine N O emissions based on IPCC methodology. However, the estimates have considerable uncertainty due to the large spatiotemporal variations in EF values. Factors regulating EF are poorly understood at the global scale. Here, we combine 4-year in situ observations across rivers of different land use types in China, with a global meta-analysis over six continents, to explore the spatiotemporal variations and controls on EF values. Our results show that the EF values in China and other regions with high N loads are lower than those for regions with lower N loads. Although the global mean EF value is comparable to the IPCC default value, the global EF values are highly skewed with large variations, indicating that adopting region-specific EF values rather than revising the fixed default value is more appropriate for the estimation of regional and global riverine N O emissions. The ratio of dissolved organic carbon to nitrate (DOC/NO ) and NO concentration are identified as the dominant predictors of region-specific EF values at both regional and global scales because stoichiometry and nutrients strictly regulate denitrification and N O production efficiency in rivers. A multiple linear regression model using DOC/NO and NO is proposed to predict region-specific EF values. The good fit of the model associated with easily obtained water quality variables allows its widespread application. This study fills a key knowledge gap in predicting region-specific EF values at the global scale and provides a pathway to estimate global riverine N O emissions more accurately based on IPCC methodology.