ALBERT

Description: Reductions in N2O emissions from nitrification inhibitors (NI) are substantial but remain uncertain because measurements of N2O emissions are highly variable and discontinuous. Mathematical modelling may offer an opportunity to estimate these reductions if the processes causing variability in N2O emissions can be accurately simulated. In this study, the effect of NI was simulated with a simple, time-dependent algorithm to slow NH4+ oxidation in the ecosystem model ecosys. Slower nitrification modelled with NI caused increases in soil NH4+ concentrations and reductions in soil NO3- concentrations and in N2O fluxes that were consistent with those measured following fall and spring applications of slurry over 2 years from 2014 to 2016. The model was then used to estimate direct and indirect effects of NI on seasonal and annual emissions. After spring slurry applications, NI reduced N2O emissions modelled and measured during the drier spring of 2015 (35 % and 45 %) less than during the wetter spring of 2016 (53 % and 72 %). After fall slurry applications, NI reduced modelled N2O emissions by 58 % and 56 % during late fall in 2014 and 2015 and by 8 % and 33 % during subsequent spring thaw in 2015 and 2016. Modelled reductions were consistent with those from meta-analyses of other NI studies. Simulated NI activity declined over time so that reductions in N2O emissions modelled with NI at an annual timescale were relatively smaller than those during emission events. These reductions were accompanied by increases in NH3 emissions and reductions in NO3- losses with NI that caused changes in indirect N2O emissions. With further parameter evaluation, the addition of this algorithm for NI to ecosys may allow emission factors for different NI products to be derived from annual N2O emissions modelled under diverse site, soil, land use and weather.

Description: Reductions in N2O emissions from nitrification inhibitors (NI) are substantial, but remain uncertain because measurements of N2O emissions are highly variable and discontinuous. Mathematical modelling may offer an opportunity to estimate these reductions if the processes causing variability in N2O emissions can be accurately simulated. In this study, the effect of NI was simulated with a simple, time-dependent algorithm to slow NH4+ oxidation in the ecosystem model ecosys. Slower nitrification modelled with NI caused increases in soil NH4+ concentrations and reductions in soil NO3− concentrations and in N2O fluxes that were consistent with those measured following fall and spring applications of slurry over two years from 2014 to 2016. The model was then used to estimate direct and indirect effects of NI on seasonal and annual emissions. After spring slurry applications, NI reduced N2O emissions modelled and measured during the drier spring of 2015 (35 % and 45%) less than during the wetter spring of 2016 (53 % and 72 %). After fall slurry applications, NI reduced modelled N2O emissions by 58 % and 56 % during late fall in 2014 and 2015, and by 8 % and 33 % during subsequent spring thaw in 2015 and 2016. Modelled reductions were consistent with those from meta-analyses of other NI studies. Simulated NI activity declined over time, so that reductions in N2O emissions modelled with NI at an annual time scale were relatively smaller than those during emission events. These reductions were accompanied by increases in NH3 emissions and reductions in NO3− losses with NI that caused changes in indirect N2O emissions. With further parameter evaluation, the addition of this algorithm for NI to ecosys may allow emission factors for different NI products to be derived from annual N2O emissions modelled under diverse site, soil, land use and weather.