Agriculture Reference
In-Depth Information
Table 14.3. A partial list of models used to predict greenhouse gas emissions from livestock production.
Whole farm beef GHG emissions model used in Ireland,
Excel based
Foley et al . (2011)
Software tool for estimating GHG emissions and carbon footprint
of dairy production systems in the USA. Includes all major sources
and sinks of CH 4 , N 2 O and CO 2 . Http://
Rotz et al . (2010)
Empirical model for estimating GHG from dairy farms, accounts
for livestock and feed management, land and crop management;
GHG calculated according to the Dutch inventory methodology
Schils et al . (2007)
Models of C and N flows and GHG on dairy farms in Denmark.
Quantifies all direct and indirect emissions of CO 2 , CH 4 and N 2 O;
includes imports, exports and flows of all products through the farm
Olesen et al . (2004)
Software tool for estimating the GHG emissions from farms in
Canada. All major sources and sinks of CH 4 , N 2 O and CO 2 and all
major livestock and cropping systems considered. Http://www.agr.
Little et al . (2008)
Software tool to develop nutrient budgets for farms in New Zealand.
GHG estimates are based on New Zealand's national inventory
Beukes et al . (2010)
Excel-based spreadsheet model from France to estimate direct
and indirect GHG linked to farm activities using IPCC tier 2
Bochu (2002)
Farm-scale model for use on dairy farms in the UK; accounts for
GHG, nutrient loss, farm profitability and attributes of biodiversity,
milk quality, soil quality and animal welfare
Del Prado et al .
guidelines for quantifying emission sources and
sinks from agriculture. Although the IPCC
(2006) methodology is designed for national
GHG inventory, it can be applied at an industry-
wide scale, or at a regional- or farm-scale for use
in LCA. The IPCC uses a three-tiered approach
with each successive tier having an increased
level of detail and accuracy. This tiered approach
recognizes the considerable variation in data
availability, technical expertise and inventory
capacity across countries. Tier 1 is a simple
approach that uses yearly default emission
factors by animal category. Tier 2 is similar to
tier 1, but uses country-specific detail for ani-
mals, diets and emission factors as determined
by peer-reviewed scientific research. Tier 3 esti-
mates are based on process-oriented models that
simulate emissions in high detailed spatial and
temporal resolution, based on the input of cli-
matic driving factors and recorded agricultural
management. An example of how IPCC method-
ology might be used in farm-based GHG model-
ling is Holos, a model developed by Agriculture
and Agri-Food Canada (
holos-ghg) to estimate whole-farm GHG emissions.
Holos is based broadly on IPCC methodologies,
with the algorithms and emission factors modi-
fied to reflect Canadian conditions and farming
practices. The model considers all significant
emissions and removals on the farm, as shown
in Fig. 14.2. The model estimates whole-farm
GHG emissions, including emissions of enteric
CH 4 from ruminants, manure-derived CH 4 and
N 2 O, soil-derived N 2 O, CO 2 from on-farm energy
use and the manufacturing of fertilizer and her-
bicide, and CO 2 emission/removal from manage-
ment-induced changes in soil C stocks. This
whole systems approach can be used to estimate
the impact of changes in management practices
on whole-farm emissions and has been used in
LCA of beef (Beauchemin et al ., 2010, 2011)
and dairy production (McGeough et al ., 2012).
Methane is the predominant GHG emission in
ruminant livestock systems (Beauchemin et al .,
2010; McGeough et al ., 2012) and enteric fer-
mentation within the rumen contributes the
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