Application of Bayesian statistics to estimate nitrous oxide emission factors of three nitrogen fertilisers on UK grasslands

A - Papers appearing in refereed journals

Cowan, N., Levy, P., Drewer, J., Carswell, A. M., Shaw, R., Simmons, I., Bache, C., Marinheiro, J., Brichet, J., Sanchez-Rodriguez, A. R., Cotton, J., Hill, P.W., Chadwick, D. R., Jones, D. L., Misselbrook, T. H. and Skiba, U. 2019. Application of Bayesian statistics to estimate nitrous oxide emission factors of three nitrogen fertilisers on UK grasslands. Environment International. 128, pp. 362-370.

AuthorsCowan, N., Levy, P., Drewer, J., Carswell, A. M., Shaw, R., Simmons, I., Bache, C., Marinheiro, J., Brichet, J., Sanchez-Rodriguez, A. R., Cotton, J., Hill, P.W., Chadwick, D. R., Jones, D. L., Misselbrook, T. H. and Skiba, U.
Abstract

Trapezoidal integration by linear interpolation of data points is by far the most commonly used method of cumulative flux calculations of nitrous oxide (N2O) in studies that use flux chambers; however, this method is incapable of providing accurate uncertainty estimates. A Bayesian approach was used to calculate N2O emission factors (EFs) and their associated uncertainties from flux chamber measurements made after the application of nitrogen fertilisers, in the form of ammonium nitrate (AN), urea (Ur) and urea treated with Agrotain® urease inhibitor (UI) at four grassland sites in the UK. The comparison between the cumulative fluxes estimated using the Bayesian and linear interpolation methods were broadly similar (R2 = 0.79); however, the Bayesian method was capable of providing realistic uncertainties when a limited number of data points is available. The study reports mean EF values (and 95% confidence intervals) of 0.60 ± 0.63, 0.29 ± 0.22 and 0.26 ± 0.17% of applied N emitted as N2O for the AN, Ur and UI treatments, respectively. There was no significant difference between N2O emissions from the Ur and UI treatments. In the case of the automatic chamber data collected at one site in this study, the data did not fit the log-normal model, implying that more complex models may be needed, particularly for measurement data with high temporal resolution

KeywordsAgriculture; N2O; Urease inhibitor; Urea; Uncertainty
Year of Publication2019
JournalEnvironment International
Journal citation128, pp. 362-370
Digital Object Identifier (DOI)doi:10.1016/j.envint.2019.04.054
Web address (URL)https://www.sciencedirect.com/science/article/pii/S0160412019302648?via%3Dihub#!
Open accessPublished as ‘gold’ (paid) open access
Funder project or codeUK - China Virtual Joint Centre for Improved Nitrogen Agronomy (CINAG)
FunderBBSRC Newton funding
Biotechnology and Biological Sciences Research Council
Publisher's version1-s2.0-S0160412019302648-main.pdf
Output statusPublished
Publication dates
Online08 May 2019
Publication process dates
Accepted24 Apr 2019
Copyright licenseCC BY
PublisherElsevier
ISSN0160-4120

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