Indirect nitrous oxide emissions from streams within the US Corn Belt scale with stream order

• Published in: Proceedings of the National Academy of Sciences - PNAS 2015-08, Vol.112 (32), p.9839-9843
• Main Authors: Turner, Peter A., Griffis, Timothy J., Lee, Xuhui, Baker, John M., Venterea, Rodney T., Wood, Jeffrey D.
• Format: Article
• Language: English
• Subjects: Agriculture; Biological Sciences; Emissions control; Environmental impact; Environmental regulations; Greenhouse gases; Nitrous oxide
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1503598112

N₂O is an important greenhouse gas and the primary stratospheric ozone depleting substance. Its deleterious effects on the environment have prompted appeals to regulate emissions from agriculture, which represents the primary anthropogenic source in the global N₂O budget. Successful implementation of mitigation strategies requires robust bottom-up inventories that are based on emission factors (EFs), simulation models, or a combination of the two. Top-down emission estimates, based on tall-tower and aircraft observations, indicate that bottom-up inventories severely underestimate regional and continental scale N₂O emissions, implying that EFs may be biased low. Here, we measured N₂O emissions from streams within the US Corn Belt using a chamber-based approach and analyzed the data as a function of Strahler stream order (S). N₂O fluxes from headwater streams often exceeded 29 nmol N₂O-N m⁻²·s⁻¹ and decreased exponentially as a function of S. This relation was used to scale up riverine emissions and to assess the differences between bottom-up and top-down emission inventories at the local to regional scale. We found that the Intergovernmental Panel on Climate Change (IPCC) indirect EF for rivers (EF5r) is underestimated up to ninefold in southern Minnesota, which translates to a total tier 1 agricultural underestimation of N₂O emissions by 40%. We show that accounting for zero-order streams as potential N₂O hotspots can more than double the agricultural budget. Applying the same analysis to the US Corn Belt demonstrates that the IPCC EF5runderestimation explains the large differences observed between top-down and bottom-up emission estimates.