Identifying hot spots and hot moments of nitrous oxide (N2O) emissions in the landscape is critical for monitoring and mitigating the emission of this potent greenhouse gas. We propose a novel use of the Lorenz curve and Gini coefficient (G) to improve the estimation of the mean as well as the spatial and temporal variation of N2O emissions from a bioenergy landscape. The analyses indicate that the G was better correlated (R2 = 0.72, P < 0.001) with daily N2O emissions than the coefficient of variation and skewness. A hot moment for N2O emissions occurred after a storm event, with a heterogeneous spatial distribution of N2O emissions (G = 0.65); in contrast, CO2 emissions remained spatially uniform throughout the same period (G = 0.36). Volumetric soil air content below 0.03 m3 m−3 occurred more frequently in the wetter footslope positions and created N2O hot spots, with a high temporal inequality during the growing season (G = 0.75). In contrast, well-drained shoulder positions were cold spots, with uniformly distributed and low N2O emissions (G = 0.44). The spatial N2O inequality mirrored the landscape wetness generated by rain events, while biogeochemical equality prevailed in the landscape. The Lorenz curve and G are tools to standardize the spatial and temporal variation of N2O emissions across diverse landscapes and management scenarios. These two inequality indicators, in association with spatial maps, can help delineate the critical spatial mosaics and temporal windows of N2O emissions and guide landscape-scale monitoring and mitigation strategies to reduce N2O emissions.
All Science Journal Classification (ASJC) codes
- Soil Science
- Water Science and Technology
- Atmospheric Science
- Aquatic Science