Lorenz Curve and Gini Coefficient Reveal Hot Spots and Hot Moments for Nitrous Oxide Emissions. Issue 1 (24th January 2018)

• Record Type: Journal Article
• Authors: Saha, Debasish; Kemanian, Armen R.; Montes, Felipe; Gall, Heather; Adler, Paul R.; Rau, Benjamin M.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 1(2018)
• Page Start: 193
• Page End: 206
• Publication Date: 2018-01-24
• Subjects: nitrous oxide -- hot spots -- hot moments -- inequality -- Lorenz curve -- Gini coefficient; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1002/2017JG004041
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: Identifying hot spots and hot moments of nitrous oxide (N2 O) 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 N2 O emissions from a bioenergy landscape. The analyses indicate that the G was better correlated ( R 2 = 0.72, P < 0.001) with daily N2 O emissions than the coefficient of variation and skewness. A hot moment for N2 O emissions occurred after a storm event, with a heterogeneous spatial distribution of N2 O 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 m 3 m −3 occurred more frequently in the wetter footslope positions and created N2 O 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 N2 O emissions (G = 0.44). The spatial N2 O 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 N2 O 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 N2 O emissions and guide landscape‐scale monitoring and mitigation strategies to reduce N2 O emissions. Key Points: We used the Lorenz curve and Gini coefficient to assess hot spots and hot moments contribution to N2 O flux in the landscape Footslope positions had the greatest spatial and temporal inequality due to spring and summer rain activating N2 O emission hot spots The Gini coefficient related well to N2 O emission magnitudes and could guide monitoring and mitigation practices