Approaches to estimating direct and indirect nitrous oxide emissions

The estimation of N2O emissions is still highly uncertain, due to their large variability in time and space. Large variability is caused by the variable rates at which the processes of nitrification and denitrification occur. These processes, in turn, are controlled by biophysical and chemical conditions in soil micro-sites, which often show strong non-linear relationships with emissions of N2O. This non-linearity makes upscaling difficult. In order to estimate direct N2O emissions from the plot scale to the global scale, various methodologies have been developed, ranging from factorial approaches and statistical models to process-based simulation models. All approaches are trying to find relationships between controlling factors and N2O emissions, on different scales, and apply them to estimate N2O emissions using information on the controlling factors as input parameters.

The emission factor approaches such as those used by Bouwman (1996) are based on increasing N2O emissions following an increase in fertilizer-N input (Kaiser and Ruser, 2000; McSwiney and Robertson, 2005). IPCC (2006) estimated the proportion of N fertilizer applied that is emitted as N2O to be 1 per cent, i.e. an EF of 0.01 (or 1 per cent). This EF is used as a 'default factor' and reflects 'direct emissions' (Table 5.1). Recently, Crutzen et al (2008) proposed that instead of using a bottom-up approach for estimating the EF in agricultural systems, a top-down approach would give a more realistic estimate of N2O emissions in agriculture. The top-down approach includes secondary N2O emissions within agricultural systems, for example via livestock feed and manure, and indirect emissions of N2O from N leached from agricultural fields

Table 5.1 Default emission factors to calculate the anthropogenic N2O emission for arable land, including direct and indirect emissions

Type Code Default value Range Description

Table 5.1 Default emission factors to calculate the anthropogenic N2O emission for arable land, including direct and indirect emissions

Type Code Default value Range Description

Direct emission

EF1

0.01

0.003-0.03

Emission from N input of fertilizer, manure, crop residues, mineralization

Indirect emission

EF4

0.01

0.002-0.05

Emission from N input from volatilization and re-deposition

Indirect emission

EF5

0.0075

0.0005-0.025

Emission from nitrate leaching and N runoff

Source: IPCC (2006)

Source: IPCC (2006)

into streams and open waters. Nitrogen newly fixed by biological N2 fixation is also included. By following the top-down avenue, Crutzen et al (2008) calculated that between 3 and 5 per cent of newly fixed N is emitted as N2O.

Statistical methods have identified factors that control annual N2O emissions at the field scale, and form the basis of the default emission factor adopted by IPCC to estimate direct N2O emissions (Bouwman et al, 2002b; Freibauer and Kaltschmitt, 2003; Stehfest and Bouwman, 2006) (Figure 5.1). The most important controlling factors in these statistical approaches are the rates of N-fertilizer application, crop type, fertilizer type, soil organic C content, soil pH and texture, and climate. As these relationships are identified at a larger temporal and spatial scale by statistical methods, no causal relationships can be derived from these correlations. In general, it cannot be determined whether the emissions occur via nitrification or denitrification.

In contrast, mechanistic models make use of (sub-)daily measurements of N2O emissions at the plot scale and the results of laboratory experiments to identify the controlling factors for N2O emissions from nitrification and denitrification. One of the first conceptual mechanistic N2O emissions models is the 'hole-in-the-pipe' model (Firestone and Davidson, 1989), which relates N2O emissions to the total amount of N flowing through the soils system (the pipe), and to factors controlling the loss of N2O during this flow (the hole). More detailed process-based models such as DNDC ('denitrification/-decomposition') (Li and Aber, 2000) and DAYCENT (Parton et al, 1996, 2001; Del Grosso et al, 2000) describe the processes of nitrification and denitrification with separate N2O emissions (Figure 5.2). In both models, the soil water content and aeration status of the soils are key controlling factors. The DNDC model also explicitly includes gas diffusion through the soil profile.

An overview of the controlling factors for N2O emissions from nitrification and denitrification is provided elsewhere (Farquharson and Baldock, 2008). Although DNDC and DAYCENT are the most well-known process-based

AMF. grass, temp A MF grass, trop

0 50 100 150 200 250 300

N application fate (kg N ha ')

0 50 100 150 200 250 300

N application fate (kg N ha ')

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