Dataset for: 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 (N2O), a
powerful greenhouse gas. Estimating global riverine N2O emissions
is critical for the assessment of anthropogenic N2O emission
inventories. The indirect N2O emission factor (EF5r) model, one
of the bottom-up approaches, adopts a fixed EF5r value to
estimate riverine N2O emissions based on IPCC methodology.
However, the estimates have considerable uncertainty due to the large
spatiotemporal variations in EF5r values. Factors regulating
EF5r 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 EF5r values. Our
results show that the EF5r values in China and other regions with
high N loads are lower than those for regions with lower N loads. Although
the global mean EF5r value is comparable to the IPCC default
value, the global EF5r values are highly skewed with large
variations, indicating that adopting region-specific EF5r values
rather than revising the fixed default value is more appropriate for the
estimation of regional and global riverine N2O emissions. The
ratio of dissolved organic carbon to nitrate (DOC/NO3-) and
NO3- concentration are identified as the dominant predictors of
region-specific EF5r values at both regional and global scales
because stoichiometry and nutrients strictly regulate denitrification and
N2O production efficiency in rivers. A multiple linear regression
model using DOC/NO3- and NO3- is proposed to predict
region-specific EF5r 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 EF5r values at the global scale and provides a
pathway to estimate global riverine N2O emissions more accurately
based on IPCC methodology. This dataset is a global integrated N2O dataset
including data from 4-year (2017-2020) in situ measurements of six large
rivers in China, 3-year (2018-2020) in situ measurements of urban river
networks in Beijing of China, and 825 measurements from 70
published papers over six continents. The data includes dissolved N2O
concentration, biogeochemical (DOC, NO3-, NH4+, temperature, and
DO), climatological (climate zones), and geographic (region, location, and
land cover) information.