|DEBASISH, SAHA - PENNSYLVANIA STATE UNIVERSITY|
|KEMANIAN, ARMEN - PENNSYLVANIA STATE UNIVERSITY|
|MONTES, FELIPE - PENNSYLVANIA STATE UNIVERSITY|
Submitted to: Journal of Geophysical Research-Biogeosciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/20/2017
Publication Date: 1/4/2018
Citation: Debasish, S., Kemanian, A.R., Montes, F., Adler, P.R., Rau, B.M. 2018. Lorenz curve and Gini coefficient reveal hot spots and hot moments for nitrous oxide emissions. Journal of Geophysical Research-Biogeosciences. https://doi.org/10.1002/2017JG004041.
Interpretive Summary: Although nitrous oxide is the largest source of greenhouse gas emissions associated with crop production, most N2O comes from small areas in the landscape over short time periods. We evaluated an approach to characterize where in the landscape N2O emissions will most likely occur. We found that we were able to predict these source areas of N2O emissions which would allow targeted mitigation to be more effective and economical. Adoption of this approach could increase opportunities to incorporate targeted mitigation strategies for nitrous oxide mitigation strategies into policy frameworks.
Technical Abstract: Identifying hot spots and hot moments of N2O emissions in the landscape is critical for monitoring and mitigating the emission of this powerful greenhouse gas. We propose a novel use of the Lorenz curve and Gini coefficient (G) to quantify the heterogeneous distribution of N2O emissions from a landscape planted with a biomass crop. 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 (mean 127 g N ha-1 d-1), which caused a highly heterogeneous spatial distribution of N2O emissions (G = 0.65) to emerge; in contrast, CO2 emissions remained more spatially uniform (G = 0.36). Greater frequency of soil aeration below 0.03 m3 m-3 in the lower landscape positions created the N2O hot spots, with a high spatial inequality (G = 0.75) during the growing season. In contrast, well-drained shoulder positions were cool spots, with lower spatial inequality (G = 0.44) of low N2O emissions through the growing season. Event-based evolution of N2O temporal inequality mirrored the hydrologic inequality, given that biogeochemical equality prevailed in the landscape. The Lorenz curve and G were used to "quantify" the hot spots and hot moments of N2O emissions better than any other indicator. These two inequality indicators can help guide landscape-scale monitoring and mitigation strategies to reduce N2O emissions, and provide a means to standardize the spatial and temporal variation of these emissions across diverse landscapes and management scenarios.