Modeling nitrous oxide emission from rivers: a global assessment

Abstract

Estimates of global riverine nitrous oxide (N₂O) emissions contain great uncertainity. We conducted a meta-analysis incorporating 169 observations from published literature to estimate global riverine N₂O emission rates and emission factors. Riverine N₂O flux was significantly correlated with NH₄, NO₃ and DIN (NH₄+NO₃) concentrations, loads and yields. The emission factors EF(a) (i.e., the ratio of N₂O emission rate and DIN load) and EF(b) (i.e., the ratio of N₂O and DIN concentrations) values were comparable and showed negative correlations with nitrogen concentration, load and yield and water discharge, but positive correlations with the dissolved organic carbon:DIN ratio. After individually evaluating 82 potential regression models based on EF(a) or EF(b) for global, temperate zone, and sub-tropical zone datasets, a power function of DIN yield multiplied by watershed area was determined to provide the best fit between modeled and observed riverine N₂O emission rates (EF(a): R²=0.92 for both global and climatic zone models, n=70; EF(b): R²=0.91 for global model and R²=0.90 for climatic zone models, n=70). Using recent estimates of DIN loads for 6400 rivers, models estimated global riverine N₂O emission rates of 29.6–35.3 (mean=32.2) Gg N₂O-N yr⁻¹ and emission factors of 0.16–0.19% (mean=0.17%). Global riverine N₂O emission rates are forecasted to increase by 35%, 25%, 18% and 3% in 2050 compared to the 2000s under the Millennium Ecosystem Assessment's Global Orchestration, Order from Strength, Technogarden, and Adapting Mosaic scenarios, respectively. Previous studies may overestimate global riverine N₂O emission rates (300–2100 Gg N₂O-N yr⁻¹) since they ignore declining emission factor values with increasing nitrogen levels and channel size, as well as neglect differences in emission factors corresponding to different nitrogen forms. Riverine N₂O emission estimates will be further enhanced through refining emission factor estimates, extending measurements longitudinally along entire river networks, and improving estimates of global riverine nitrogen loads.