Arable soils are a large source of nitrous oxide (N2O) emission and several factors may affect the processes responsible for its production (nitrification and denitrification). In particular, forage crop systems for dairy farming are among the cropping systems with highest N input, mainly because they are based on high yielding forage grasses such as maize. A number of options have been explored to decrease the emissions but they remain site specific and are related to climatic, soil and local availability of management options. Moreover, guidelines for estimating N2O emission from agricultural soils does not take into account different crops, soils, climate and management, all of which are known to affect nitrification-denitrification and N2O production and emission. Process-based models represent a promising route to capture the spatial and temporal variability of N2O emissions, along with the effects of crop management. Nevertheless, the testing and comparison of these models have been limited to only a few works, with studies mainly based on biogeochemical models rather than process-based crop models. Furthermore, a multi-model ensemble analysis, which proved to be the best option for crop system analysis, has not been done extensively for the simulation of N2O emissions to addressing the various options for mitigations practices related to maize crop fertilization systems. Our objective is to evaluate the performance of several process-based models in simulating N2O emission under different type, amount, rate of N fertilizer, i) quantify N2O emission, as a function of nitrogen inputs, across a wide range of soil types and environmental contexts; ii) assess the uncertainty in simulating N2O emission, and iii) identify efficient mitigation of N-fertilized maize systems.

Modelling nitrous oxide emissions of high input maize crop systems / Bassu S., Acutis M., Amaducci S., Argenti G., Baranowski P., Berti A., Bertora C., Bindi M., Bonari E. 8, Bosco S., Brilli L., Cammarano D., Doro L., Ferrise R., Gayler S., Grignani C., Harrison M.T. 14, Iocola I. 1, Krzyszczak J., Lai R., Morari F., Mula L., Nendel C., Oygarden L., Perego A., Priesack E., Pulina A., Stella T., Volpi I., Wu L., Zubik M., Roggero, P.P.. - STAMPA. - (2017), pp. 70-70. (Intervento presentato al convegno MACSUR Science Conference 2017 tenutosi a Berlin nel 2017, 22–24 May).

Modelling nitrous oxide emissions of high input maize crop systems

Argenti G.;Bindi M.;BRILLI, LORENZO;Ferrise R.;
2017

Abstract

Arable soils are a large source of nitrous oxide (N2O) emission and several factors may affect the processes responsible for its production (nitrification and denitrification). In particular, forage crop systems for dairy farming are among the cropping systems with highest N input, mainly because they are based on high yielding forage grasses such as maize. A number of options have been explored to decrease the emissions but they remain site specific and are related to climatic, soil and local availability of management options. Moreover, guidelines for estimating N2O emission from agricultural soils does not take into account different crops, soils, climate and management, all of which are known to affect nitrification-denitrification and N2O production and emission. Process-based models represent a promising route to capture the spatial and temporal variability of N2O emissions, along with the effects of crop management. Nevertheless, the testing and comparison of these models have been limited to only a few works, with studies mainly based on biogeochemical models rather than process-based crop models. Furthermore, a multi-model ensemble analysis, which proved to be the best option for crop system analysis, has not been done extensively for the simulation of N2O emissions to addressing the various options for mitigations practices related to maize crop fertilization systems. Our objective is to evaluate the performance of several process-based models in simulating N2O emission under different type, amount, rate of N fertilizer, i) quantify N2O emission, as a function of nitrogen inputs, across a wide range of soil types and environmental contexts; ii) assess the uncertainty in simulating N2O emission, and iii) identify efficient mitigation of N-fertilized maize systems.
2017
Book of Abstracts MACSUR Science Conference 2017
MACSUR Science Conference 2017
Berlin
Bassu S., Acutis M., Amaducci S., Argenti G., Baranowski P., Berti A., Bertora C., Bindi M., Bonari E. 8, Bosco S., Brilli L., Cammarano D., Doro L., Ferrise R., Gayler S., Grignani C., Harrison M.T. 14, Iocola I. 1, Krzyszczak J., Lai R., Morari F., Mula L., Nendel C., Oygarden L., Perego A., Priesack E., Pulina A., Stella T., Volpi I., Wu L., Zubik M., Roggero, P.P.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1132307
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