8.4.2 Mitigation technologies and practices: per-area estimates of potential

Notes:

The estimates represent average change in soil carbon stocks (CO2) or emissions of N2O and CH4 on a per hectare basis. Positive values represent CO2 uptake which increases the soil carbon stock, or a reduction in emissions of N2O and CH4.

Estimates of soil carbon storage (CO2 mitigation) for all practices except management of organic soils were derived from about 200 studies (see IPCC, 2006, Grassland and Cropland Chapters of Volume IV, Annexes 5A and 6A) using a linear mixed-effect modelling approach, which is a standard linear regression technique with the inclusion of random effects due to dependencies in data from the same country, site and time series (Ogle et al., 2004, 2005; IPCC, 2006; Smith et al., 2007b). The studies were conducted in regions throughout the world, but temperate studies were more prevalent leading to smaller uncertainties than for estimates for warm tropical climates. Estimates represent annual soil carbon change rate for a 20-year time horizon in the top 30 cm of the soil. Soils under bio-energy crops and agro-forestry were assumed to derive their mitigation potential mainly from cessation of soil disturbance, and given the same estimates as no-till. Management of organic soils was based on emissions under drained conditions from IPCC guidelines (IPCC, 1997). Soil CH4 and N2O emission reduction potentials were derived as follows:

a) for organic soils, N2O emissions were based on the median, low and high nutrient status organic soil N2O emission factors from the IPCC GPG LULUCF (IPCC, 2003) and CH4 emissions were based on low, high and median values from Le Mer and Roger (2001);

b) N2O figures for nutrient management were derived using the DAYCENT simulation model, and include both direct emissions from nitrification/denitrification at the site, as well as indirect N2O emissions associated with volatilization and leaching/runoff of N that is converted into N2O following atmospheric deposition or in waterways, respectively (US-EPA, 2006b; assuming a N reduction to 80% of current application);

c) N2O figures for tillage and residue management were derived using DAYCENT (US-EPA, 2006b; figures for no till);

d) Rice figures were taken directly from US-EPA (2006b) so are not shown here. Low and high values represent the range of a 95% confidence interval. Table 8.4 has mean and uncertainty for change in soil C, N2O and CH4 emissions at the climate region scale, and are not intended for use in assessments at finer scales such as individual farms.

Notes:

a The proportional reduction due to application of each practice was estimated from reports in the scientific literature (see footnotes below). These estimates were adjusted for:

(i) proportion of the animal’s life where the practice was applicable;

(ii) technical adoption feasibility in a region, such as whether farmers have the necessary knowledge, equipment, extension services, etc. to apply the practice (average dairy cow milk production in each region over the period 2000-2004 was used as an index of the level of technical efficiency in the region, and was used to score a region’s technical adoption feasibility);

(iii) proportion of animals in a region that the measure can be applied (i.e. if the measure is already being applied to some animals as in the case of bST use in North America, it is considered to be only applicable to the proportion of animals not currently receiving the product;

(iv) Non-additivity of simultaneous application of multiple measures.

There is evidence in the literature that some measures are not additive when applied simultaneously, such as the use of dietary oils and ionophores, but this is probably not the case with most measures. However, the model used (as described in Smith et al., 2007a) did account for the fact that once one measure is applied, the emissions base for the second measure is reduced, and so on, and a further 20% reduction in mitigation potential was incorporated to account for unknown non-additivity effects. Only measures considered feasible for a region were applied in that region (e.g., bST was not considered for European regions due to the ban on its use in the EU). It was assumed that total production of milk or meat was not affected by application of the practices, so that if a measure increased animal productivity, animal numbers were reduced in order to keep production constant.

b Includes replacing roughage with concentrate (Blaxter & Claperton, 1965; Moe & Tyrrell, 1979; Johnson & Johnson, 1995; Yan et al., 2000; Mills et al., 2003; Beauchemin & McGinn, 2005; Lovett et al., 2006), improving forages/inclusion of legumes (Leng, 1991; McCrabb et al., 1998; Woodward et al., 2001; Waghorn et al., 2002; Pinares-Patiño et al., 2003; Alcock & Hegarty, 2006) and feeding extra dietary oil (Machmüller et al., 2000; Dohme et al., 2001; Machmüller et al., 2003, Lovett et al., 2003; McGinn et al., 2004; Beauchemin & McGinn, 2005; Jordan et al., 2006a; Jordan et al., 2006b; Jordan et al., 2006c).

c Includes bST (Johnson et al., 1991; Bauman, 1992), growth hormones (McCrabb, 2001), ionophores (Benz & Johnson, 1982; Rumpler et al., 1986; Van Nevel & Demeyer, 1996; McGinn et al., 2004), propionate precursors (McGinn et al., 2004; Beauchemin & McGinn, 2005; Newbold et al., 2005; Wallace et al., 2006).

d Includes lifetime management of beef cattle (Johnson et al., 2002; Lovett & O’Mara, 2002) and improved productivity through animal breeding (Ferris et al., 1999; Hansen, 2000; Robertson and Waghorn, 2002; Miglior et al., 2005).

Source: adapted from Smith et al., 2007a.