Improving N2O emission estimates with the global N2O database

Christopher D. Dorich* (Corresponding Author), Richard T. Conant, Fabrizio Albanito, Klaus Butterbach-Bahl, Peter Grace, Clemens Scheer, Val O. Snow, Iris Vogeler, Tony J. van der Weerden

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Climate change will have dire consequences and collaborative efforts are required to quickly develop and assess mitigation solutions. Agriculture is the primary source of the powerful greenhouse gas (GHG) nitrous oxide (N2O) and an important source of GHG emissions. Due to sampling limitations, N2O measurements have traditionally been sparse; approximately 75% of sites we reviewed sampled for fewer than 50 days within a year. Nitrous oxide emissions are highly variable and short-lived peak emission periods may contribute more than 50% to annual emissions. Gap filling around these peaks, if measured at all, can result in poor estimations under the standard practice using area under the curve. Improved gap filling methods that reflect covariate data will likely reduce uncertainty and improve annual N2O estimates. The Global N2O Database was created to serve as a repository for these datasets as well as become a resource for publicly available data and analytical advances.
Original languageEnglish
Pages (from-to)13-20
Number of pages8
JournalCurrent Opinion in Environmental Sustainability
Volume47
Early online date11 Jun 2020
DOIs
Publication statusPublished - Dec 2020

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