Predicting in situ soil N₂O emission using NOE algorithm and soil database

Abstract

This paper presents a new algorithm, Nitrous Oxide Emission (NOE) for simulating the emission of the greenhouse gas N 2 O from agricultural soils. N 2 O fluxes are calculated as the result of production through denitrification and nitrification and reduction through the last step of denitrification. Actual denitrification and nitrification rates are calculated from biological parameters and soil water-filled pore space, temperature and mineral nitrogen contents. New suggestions in NOE consisted in introducing (1) biological sitespecific parameters of soil N 2 O reduction and (2) reduction of the N 2 O produced through nitrification to N 2 through denitrification. This paper includes a database of 64 N 2 O fluxes measured on the field scale with corresponding environmental parameters collected from five agricultural situations in France. This database was used to test the validity of this algorithm. Site per site comparison of simulated N 2 O fluxes against observed data leads to mixed results. For 80% of the tested points, measured and simulated fluxes are in accordance whereas the others resulted in an important discrepancy. The origin of this discrepancy is discussed. On the other hand, mean annual fluxes measured on each site were strongly correlated to mean simulated annual fluxes. The biological site-specific parameter of soil N 2 O reduction introduced into NOE appeared particularly useful to discriminate the general level of N 2 O emissions from site to site. Furthermore, the relevance of NOE was confirmed by comparing measured and simulated N 2 O fluxes using some data from the US TRAGNET database. We suggest the use of NOE on a regional scale in order to predict mean annual N 2 O emissions.

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“…Process oriented models which account for management practices can be used, instead of emission factors. The Denitrification-Decomposition (DNDC) model [13] and the Nitrous Oxide Emission (NOE) model [12] have been tested in European conditions with promising results [12,14]. However, while the seasonal simulated values agree rather well with measurements, there are many discrepancies in daily emissions.…”

“…This emission factor is 1% with an uncertainty range of 0.3% to 3%. Such a large uncertainty is due to factors affecting N 2 O emissions, which are biological soil parameters, soil water-filled pore space and temperature [12]. The use of such an emission factor for a given field is inaccurate and cannot allow the test of different management scenarios such as no-till, cover crop or change in N fertilizer timing.…”

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“…Despite our efforts, CERES-EGC still underestimated emissions in [2008][2009] due to several combined factors (Bessou et al 2010b). Other sources also showed a marginal error of roughly 20% with CERES-EGC (Hénault et al 2005;Gabrielle et al 2011). This error remains lower than the uncertainty associated with IPCC factors.…”

“…This process-based model simulates crop growth by considering the type of soil, climate conditions, plant variety, and management practices at the field scale. It also predicts substance losses outside the ecosystem such as nitrate leaching, ammonium volatilization (Génermont and Cellier 1997), and nitrous oxide emissions through nitrification and denitrification which are predicted with the NOE sub-model (Hénault et al 2005). In order to improve its accuracy, we implemented the NOE2 submodel (Bessou et al 2010b) in CERES-EGC and proceeded to a Bayesian calibration of the 22 parameters of NOE2.…”

Nitrification rates and associated nitrous oxide emissions from agricultural soils – a synopsis

“…Most agro-ecological models (e.g. DayCent, APSIM, DNDC, WNMM, NOE) explicitly deal with each of these processes with varying degrees of process understanding and empiricism (Li et al 1992;Parton et al 1998;Hénault et al 2005;Li et al 2007; Thorburn et al 2010). By necessity, these processes are often simplistically modelled using potential process rates that then are modified by drivers such as substrate availability, water content, pH and temperature ( Fig.…”