Topdown estimates

Nitrous oxide and crop production

Using a global top-down approach, Crutzen et al (2008) estimated that at the global scale 3-5 per cent of all new reactive N input into terrestrial systems is converted to N2O. This N2O conversion range was based on data compiled by Prather et al (2001) and Galloway et al (2004). New N input includes the N that is produced by chemical, biological and atmospheric processes (i.e. fertilizer nitrogen produced by the Haber-Bosch process, N oxides produced by fossil fuel combustion, and biological N fixation). The pre-industrial, natural N2O sink and source at an atmospheric mixing ratio of 270ppb was calculated to be equal to 10.2Tg N2O-N yr-1 (Prather et al, 2001), which includes marine emissions. By the start of the present century, when the atmospheric volume mixing ratio was 315ppb, the stratospheric photochemical sink of N2O was about 11.9Tg N2O-N yr-1. The total N2O source at that time was equal to the photochemical sink (11.9Tg N2O-N yr-1) plus the atmospheric growth rate (3.9Tg N2O-N yr-1), together totalling 15.8Tg N2O-N yr-1 (Prather et al, 2001). The anthropogenic N2O source is the difference between the total source strength, 15.8Tg N2O-Nr yr-1, and the current natural source, which is equal to the pre-industrial source of 10.2Tg N2O-N yr-1 minus an uncertain 0-0.9Tg N2O-N, with the last number taking into account a decreased natural N2O source due to 30 per cent global deforestation (Klein Goldewijk, 2001). Thus an anthropogenic N2O source of 5.6-6.5Tg N2O-N yr-1 was derived. To obtain the agricultural contribution, the estimated industrial source of 0.7-

1.3Tg N2O-N yr"1 (Prather et al, 2001) was subtracted, giving a range of 4.3-5.8Tg N2O-N yr"1. This is 3.8-5.1 per cent of the anthropogenic 'new' reactive nitrogen input of 114Tg N yr"1 for the early 1990s. This input value is derived from the 100Tg of N fixed by the Haber-Bosch process, plus 24Tg of reactive N released by fossil fuel combustion and a 3.5Tg N increase through biological nitrogen fixation (BNF), between current and pre-industrial times (Galloway et al, 2004), minus the 14Tg of Haber-Bosch N not used as fertilizer (Smeets et al, 2007). In comparison, the N2O-N emission estimated by Prather et al (2001) is 2.9-6.3Tg N2O-N yr"1, or 3.4-6.8Tg N2O-N yr"1 if we also include biomass and biofuel burning (which we consider an agricultural source), leading to N2O-N yields of 2.6-5.5 per cent or 3.0-6.0 per cent, respectively.

The global source and sink of N2O in pre-industrial, natural conditions was 10.2Tg N2O-N yr"1 (see above). Of that, 6.2-7.2Tg N2O-N yr"1 came from the land and coastal zones (Prather et al, 2001), and was derived from an estimated fresh reactive N input of 141Tg N yr"1 (Galloway et al, 2004). This gives an N2O-N yield of 4.4-5.1 per cent. Thus, both for the pre-Haber-Bosch natural terrestrial emissions and the agricultural emissions in the Haber-Bosch era, we find that the N2O output (or emission factor, EF) is 3-5 per cent of the fresh reactive N input. This is a parametric relationship, based on the global budgets of N2O and reactive N input, and on atmospheric concentrations and known lifetime of N2O, and thus is not dependent on detailed knowledge of the terrestrial N cycle. When the relationship was applied to the fertilizer-N input to biofuel crop production - for example, production of maize for ethanol and rapeseed oil for biodiesel - the global warming impact of the resulting N2O emissions was found to match or even exceed the corresponding 'cooling' achieved by replacement of fossil fuels by the biofuels (Crutzen et al, 2008). Subsequent work in which the global EF was introduced into existing life-cycle analysis models gave broadly similar outcomes (Mosier et al, 2009).

We make the assumption here that this top-down approach for estimating the impact of Nr on N2O emissions is applicable to all crop production and is not limited solely to biofuel crop production, and in the next section we elaborate on how the underlying concepts compare with those that are the basis for bottom-up estimation procedures, and compare the results given by the different procedures.

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