Abstract / Description of output
Reliable quantification of nitrous oxide emission is a key to assessing efficiency of use and environmental impacts of N fertilizers in crop production. In this study, N2O emission and yield were quantified with a database of 853 field measurements in 104 reported studies and a regression model was fitted to the associated environmental attributes and management practices from China’s croplands. The fitted emission model explained 48% of the variance in N2O emissions as a function of fertilizer rate, crop type, temperature, soil clay content, and the interaction between N rate and fertilizer type. With all other variables fixed, N2O emissions were lower with rice than with legumes and then other upland crops, lower with organic fertilizers than with mineral fertilizers. We used the subset of the dataset for rice - covering a full range of different typical water regimes, and estimated emissions from China’s rice cultivation to be 31.1 Gg N2O-N per year. The fitted yield model explained 35% of the variance in crop yield as a function of fertilizer rate, temperature, crop type, and soil clay content. Finally, the empirical models for N2O emission and crop yield were coupled to explore the optimum N rates (N rate with minimum N2O emission per unit yield) for combinations of crop and fertilizer types. Consequently, the optimum N application rate ranged between 100 kg N ha-1 and 190 kg N ha-1 respectively with organic and mineral fertilizers, and different crop types. This study therefore improved on existing empirical methods to estimate N2O emissions from China’s croplands and suggests how N rate may be optimized for different crops, fertilizers and site conditions.
Original language | English |
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Pages (from-to) | 70-78 |
Number of pages | 9 |
Journal | Agriculture, Ecosystems & Environment |
Volume | 268 |
DOIs | |
Publication status | Published - 14 Sept 2018 |
Keywords / Materials (for Non-textual outputs)
- Nitrous oxide
- Croplands
- Nitrogen fertilizers
- Greenhouse gas emission
- Regression model
- Data synthesis
- China’s agriculture
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Jonathan Hillier
- Royal (Dick) School of Veterinary Studies - Chair of Mathematical Modelling and Global Food Systems
- Global Academy of Agriculture and Food Systems
Person: Academic: Research Active