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Where nitrogen input from fertilizer application exceeds plant demands, hotspots of microbially produced nitrous oxide (N2O) can exhibit disproportionately high rates of emissions relative to longer periods of time, known as hot moments. Hotspots and hot moments of N2O are sensitive to changes in agricultural management and weather, making it difficult to accurately quantify N2O emissions. This study investigates the spatial and temporal variability of N2O emissions using both static chambers (CH) and eddy covariance (EC) techniques, measured at a grassland site subject to four fertilizer applications of calcium ammonium nitrate (CAN) in 2019. Daily mean CH emissions were calculated using the arithmetic method and Bayesian statistics to explicitly account for the log-normal distribution of the dataset. N2O fluxes measured by CH and EC were most comparable when flux measurements were > 115 N2O-N µg m − 2 hr −1, and EC and CH measurements showed spatial and temporal alignment when CH n ≥ 15. Where n ≤ 5, the Bayesian method produced large uncertainties due to the difficulty of fitting an arithmetic mean from a log-normally distributed data set with few flux measurements. Annual EC fluxes, gap-filled using a multi-variate linear model, showed a strong correlation with measured flux values (R 2 = 0.92). Annual cumulative fluxes by EC were higher (3.35 [± 0.5] kg N ha−1) than CH using the arithmetic (2.98 [± 0.17] kg N ha−1) and Bayesian method (3.13 [± 0.24] kg N ha−1), which quantified emission factors of 1.46%, 1.30% and 1.36%, respectively. This study implies that a large sample size and frequent CH flux measurements are necessary for comparison with EC fluxes and that Bayesian statistics are an appropriate method for estimating realistic means and ranges of uncertainty for CH flux data sets.

Where nitrogen input from fertilizer application exceeds plant demands, hotspots of microbially produced nitrous oxide (N2O) can exhibit disproportionately high rates of emissions relative to longer periods of time, known as hot moments. Hotspots and hot moments of N2O are sensitive to changes in agricultural management and weather, making it difficult to accurately quantify N2O emissions. This study investigates the spatial and temporal variability of N2O emissions using both static chambers (CH) and eddy covariance (EC) techniques, measured at a grassland site subject to four fertilizer applications of calcium ammonium nitrate (CAN) in 2019. Daily mean CH emissions were calculated using the arithmetic method and Bayesian statistics to explicitly account for the log-normal distribution of the dataset. N2O fluxes measured by CH and EC were most comparable when flux measurements were > 115 N2O-N µg m − 2 hr −1, and EC and CH measurements showed spatial and temporal alignment when CH n ≥ 15. Where n ≤ 5, the Bayesian method produced large uncertainties due to the difficulty of fitting an arithmetic mean from a log-normally distributed data set with few flux measurements. Annual EC fluxes, gap-filled using a multi-variate linear model, showed a strong correlation with measured flux values (R 2 = 0.92). Annual cumulative fluxes by EC were higher (3.35 [± 0.5] kg N ha−1) than CH using the arithmetic (2.98 [± 0.17] kg N ha−1) and Bayesian method (3.13 [± 0.24] kg N ha−1), which quantified emission factors of 1.46%, 1.30% and 1.36%, respectively. This study implies that a large sample size and frequent CH flux measurements are necessary for comparison with EC fluxes and that Bayesian statistics are an appropriate method for estimating realistic means and ranges of uncertainty for CH flux data sets.

Cattle excreta deposited on grazed pastures are responsible for one fifth of the global anthropogenic nitrous oxide (N2O) emissions. One of the key nitrogen (N) sources is urine deposited from grazing animals, which contributes to very large N loadings within small areas. The main objective of this plot study was to establish whether the application of N fertiliser and urine deposit from dairy cows synergistically interacts and thereby increases N2O emissions, and how such interaction is influenced by the timing of application. The combined application of fertiliser (calcium ammonium nitrate) and urine significantly increased the cumulative N2O emissions as well as the N2O emission factor (EF) from 0.35 to 0.74 % in spring and from 0.26 to 0.52 % in summer. By contrast, EFs were lower when only fertiliser (0.31 % in spring, 0.07 % in summer) or urine was applied (0.33 % in spring, 0.28 % in summer). In autumn, N2O emissions were larger than in other seasons and the emissions from the combined application were not statistically different to those from either the separately applied urine or N fertiliser (EF ranging from 0.72 to 0.83, p-value < 0.05). The absence of significant synergistic effect could be explained by weather conditions, particularly rainfall during the three days prior to and after application in autumn. This study implies that the interactive effects of N fertilisation and urine deposit, as well as the timing of the application on N2O emission need to be taken into account in greenhouse gas emission inventories.

Cattle excreta deposited on grazed pastures are responsible for one fifth of the global anthropogenic nitrous oxide (N2O) emissions. One of the key nitrogen (N) sources is urine deposited from grazing animals, which contributes to very large N loadings within small areas. The main objective of this plot study was to establish whether the application of N fertiliser and urine deposit from dairy cows synergistically interacts and thereby increases N2O emissions, and how such interaction is influenced by the timing of application. The combined application of fertiliser (calcium ammonium nitrate) and urine significantly increased the cumulative N2O emissions as well as the N2O emission factor (EF) from 0.35 to 0.74 % in spring and from 0.26 to 0.52 % in summer. By contrast, EFs were lower when only fertiliser (0.31 % in spring, 0.07 % in summer) or urine was applied (0.33 % in spring, 0.28 % in summer). In autumn, N2O emissions were larger than in other seasons and the emissions from the combined application were not statistically different to those from either the separately applied urine or N fertiliser (EF ranging from 0.72 to 0.83, p-value < 0.05). The absence of significant synergistic effect could be explained by weather conditions, particularly rainfall during the three days prior to and after application in autumn. This study implies that the interactive effects of N fertilisation and urine deposit, as well as the timing of the application on N2O emission need to be taken into account in greenhouse gas emission inventories.