Towards improved N2O budgets estimation from 10 site-years measurement and analysis of key drivers

<p>Agriculture represents 14% of global anthropogenic greenhous gases (GHG) emissions, 46% of this amount being due to N<sub>2</sub>O emissions from soils (UNEP, 2012). N<sub>2</sub>O is a powerful GHG (IPCC, 2013) and its emissions from agricultural soils are related to physical-chemical parameters which depend on climate (temperature, rain…), soil properties (Robertson et al., 1989) and farming practices (irrigation, tillage, fertilization…) (Tellez-Rio et al., 2015). The IPCC Tier 1 emission factor remains widely used to estimate annual N<sub>2</sub>O budgets from agricultural soils by taking into account the annual amount of N input only. However, not taking into account the environmental controlling factors may introduce high uncertainty in N<sub>2</sub>O budget estimation. Our study aims at highlighting the key drivers of N<sub>2</sub>O emissions from two agricultural sites in the South West of France and at proposing an improved, simple and accessible methodology to estimate N<sub>2</sub>O budget at crop plot and seasonal scale. For this purpose, we benefited from a unique long time series of daily N<sub>2</sub>O fluxes (from 2011 to 2016) measured with 6 closed automated chambers on two ICOS sites with contrasted agricultural management (FR-Lam and FR-Aur).</p><p>N<sub>2</sub>O annual budget vary from 1.04 to 7.96 kgN ha<sup>-1</sup> yr<sup>-1 </sup>for winter wheat and maize crop, respectively. The effects of fertilization, rain and irrigation, plant development, spring mineralization and deep tillage on N<sub>2</sub>O emissions were investigated. Significant correlations between rain combined with fertilization and plant development, deep tillage or spring mineralisation was found with R² of 0.91, 0.99 and 0.85, respectively.  We took advantage of these results to develop an empirical model, including N input quantity, residual N, leaf area index and water input in order to estimate seasonal and annual N<sub>2</sub>O budget. At the seasonal scale, the model output matched well with the observed budget, with a R² and a RMSE of 0.87 and 0.33 kgN ha<sup>-1</sup> at FR-Lam and of 0.92 and 0.12 kgN ha<sup>-1</sup> at FR-Aur, respectively.  It also gave good statistical scores at the crop year scale with a R² of 0.96 and a low RMSE of 0.43 kgN ha<sup>-1</sup> when binding data from both sites. Using the IPCC Tiers 1 methodology gave lower and more scattered results with a R² of 0.46 and a RMSE of 1.46 kgN ha<sup>-1</sup>. For sites where N<sub>2</sub>O fluxes are not monitored,  that new methodology may be an alternative and a more precise methodology than the IPCC Tiers 1 approach. It has also the advantage to require only few and accessible input variables.</p><p> </p><p>REFERENCES</p><p>IPCC, 2013. Climate Change 2013: The Physical Science Basis. Cambridge University Press, Cambridge.</p><p>Robertson et al., 1989. Aerobic denitrification in various heterotrophic nitrifiers. Antonie van Leeuwenhock., 56, 289-299.</p><p>Tellez-Rio et al., 2015. N2O and CH4 Emissions from a Fallow–wheat Rotation with Low N Input in Conservation and Conventional Tillage under a Mediterranean Agroecosystem. Sci. Total Environ., 508, 85–94.</p><p>UNEP, 2012. Growing greenhouse gas emissions due to meat production.</p>