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Title: Partitioning N2O emissions within the US Corn Belt using an inverse modeling approach

Author
item CHEN, Z - University Of Minnesota
item GRIFFIS, TIMOTHY - University Of Minnesota
item MILLET, D - University Of Minnesota
item WOOD, J - University Of Minnesota
item LEE, X - Yale University
item Baker, John
item XIAO, K - University Of Minnesota
item TURNER, P - University Of Minnesota

Submitted to: Global Biogeochemical Cycles
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/29/2016
Publication Date: 8/24/2016
Citation: Chen, Z., Griffis, T.J., Millet, D.B., Wood, J.D., Lee, X., Baker, J.M., Xiao, K., Turner, P.A. 2016. Partitioning N2O emissions within the US Corn Belt using an inverse modeling approach. Global Biogeochemical Cycles. 30(8):1192-1205. doi:10.1002/2015GB005313.

Interpretive Summary: Nitrous oxide (N2O) is an important atmospheric pollutant that is a potent greenhouse gas, and also contributes to depletion of stratospheric ozone. Recent research has suggested that nitrous oxide emissions from the U.S. Corn Belt are much larger than previous estimates that were based on empirical emission factors developed by the Intergovenmental Panel on Climate Change (IPCC). We have used two years of continuous measurements of N2O from the top of a 185 m radio tower in Minnesota as input to an inverse statistical model to simultaneously place bounds on direct emissions (those that come from farm fields) and indirect emissions (those that occur after N has left a field, for instance by runoff or leaching). The results indicated that while both sources of N2O had previsously been underestimated, the underestimate was much smaller for the direct emission (42-58%) than for the indirect emissions (200-525%). Furthermore, they indicated that indirect emissions account for 41-58% of total agricultural emissions. On the basis of these results, we conclude that the emission factor for indirect emissions should be substantially increased.

Technical Abstract: Nitrous oxide (N2O) emissions within the US Corn Belt have been estimated to be 2- to 9-11 fold larger than predictions from emission inventories, implying that one or more source 12 categories in bottom-up approaches are underestimated. Here we interpret hourly N2O 13 mixing ratios measured during 2010 and 2011 at a tall tower located within the US Corn 14 Belt using a time-inverted transport model and a scale factor Bayesian inverse method to 15 simultaneously constrain direct and indirect agricultual emissions. The optimization 16 revealed that both agricultural souce categories were underestimated by bottom-up 17 inventories; however, the magnitude of the discrepancies differed substantially, being 42-18 58% and 200-525% for direct and indirect components, respectively. Optimized 19 agricultural N2O budgets for the Corn Belt were 319+-184 (total),188+-66 (direct), and 20 131+-118 Gg N yr-1 (indirect),in 2010, versus 47+-326, 198+-80, and 273+-246 Gg-N yr-1 in 21 2011. We attribute the between-year differences to varying moisture conditions, with 22 increased precipitation in 2011 amplifying emissions. A significant finding was that indirect 23 sources represented 41-58% of the agricultural budgets, which differs from bottom-up 24 inventories for which the indirect component is ~25-30%. These findings confirm the 25 hypothesis that indirect emissions are presently underestimated in bottom-up inventories. 26 Based on our results, we suggest an indirect emission factor for runoff and leaching 27 ranging from 0.018 to 0.038 for the US Corn Belt, which represents an upward adjustment 28 of 3.6 to 7.7 times relative to the Intergovernmental Panel on Climate Change and is in 29 agreement with recent bottom-up field studies.