The Nitrogen Nutrition Index and nitrous oxide emissions: a probabilistic framework for monitoring agricultural emissions risk

Developing scalable frameworks to quantify cropland nitrous oxide (N 2 O) emission risk and incentivize mitigation is a global priority. The Nitrogen Nutrition Index (NNI) is a well-established agronomic indicator that expresses crop nitrogen (N) concentration relative to a critical value. However, its potential for assessing N 2 O emission risk has not been evaluated. Using a global dataset of 348 maize and wheat observations spanning 84 environments and 42 studies, we quantified relationships between cumulative N 2 O emissions and NNI using log-linear and probit models. NNI and N-balance (N fertilizer inputs minus crop N uptake) predicted N 2 O emissions with similar precision (p < 0.001; R 2 = 0.24–0.33), while combining these metrics improved model performance (p < 0.001; R 2 = 0.44–0.48). Compared to a log-linear approach, a probabilistic model accurately identified more total emissions by reducing false negatives and better distinguishing low- and high-risk observations. Fields with low probability (P ≤ 0.51) of exceeding background soil emissions (1.06 kg N ha −1 ) produced half the yield-scaled emissions (0.11–0.14 kg N 2 O-N Mg −1 ) of higher-risk observations (0.21–0.28 kg N 2 O-N Mg −1 ). Meanwhile, 28% of total emissions were concentrated within 14% of observations where P > 0.75. Estimating target exceedance probability is a novel emissions accounting approach that can be consistently derived even as underlying quantitative details evolve, enabling durable monitoring and bioeconomic frameworks. While further research must validate the relationship between remotely-sensed NNI and field-scale emissions, these results suggest NNI can effectively estimate N 2 O emissions risks in major cereal crops with prospects for near-term scalability.