Agriculture Reference
In-Depth Information
Table 14.2. Example impact categories that could be considered in life cycle assessment of livestock
production (compiled from Haas et al ., 2001; Guinée et al ., 2002; Cederberg and Stadig, 2003).
Potential characterization
method
Impact category
Description
Indicator unit
Global warming
potential
Production of greenhouse gases
Estimation of CH 4 , N 2 O
and CO 2 using IPCC
(2006) guidelines
kg CO 2 e
Land competition
Loss of land as a resource due
to land use
Aggregation of land use
m 2 year −1
Landscape image Subjective assessment of the
aesthetic value of the landscape
Visual assessment
index (1-5)
Biodiversity
Effects on biodiversity resulting
from harvesting biotic resources
or alteration of land
Based on a statistical
measure of plant
and animal species
density
Species per ha 2
(in development)
Loss of life
support
function
Resulting from interventions such
as harvesting biotic resources or
destruction of land
Based on net primary
production
in development
Desiccation
Caused by water shortage
due to groundwater extraction or
manipulation of the water table
Not well developed
in development
Acidification
Emissions of the acidifying pollutants
SO 2 , NO x and NH x to the air
AP of each emission
kg SO 2 e
Eutrophication
Emissions of N and P to air,
water and soil
EP of each emission
kg PO 4 e or kg NO 3 e
Odour
Odorous substances
Based on odour
threshold values
m 3 (air)
Non-renewable
energy
Exhaustion of energy supplies
due to direct and indirect energy
use in farming
Based on energy used
directly, and imported
fertilizers
MJ
Water Use
Depletion of water resources
Based on water used
for irrigation of feed
crops and for drinking
by livestock
production
litres
AP, acidification potential; EP, eutrophication potential.
in GHG emissions arising from the prospective
mitigation practice. Sometimes reducing GHG
emissions in one part of a farming system can lead
to an increase in emissions in another part of the
system, which can only be detected using a whole
farm approach (Janzen et al ., 2006). The total
quantity of GHG emissions associated with a
product is sometimes referred to as its GHG inten-
sity (Henderson et al ., 2011) or C-footprint (Kitzes
and Wackernagel, 2009), which is expressed as
kg CO 2 e per kg of product. A measure of GHG
intensity avoids favouring practices that reduce
emissions at the expense of animal productivity.
While GHG intensities of beef and dairy produc-
tion are reported as a value rather than a range,
it should be noted that there is considerable
uncertainty associated with these estimates due
to the uncertainty in the emissions factors used to
estimate CH 4 and N 2 O emissions (Flysjö et al ., 2011b).
Whole farm systems models can be used in
LCA to estimate the total GHG emissions (CH 4 ,
N 2 O and CO 2 ) from producing meat, milk and
eggs (Crosson et al ., 2011). The various GHG
are expressed as CO 2 e to account for the global
warming potential of the respective gases
(International Panel on Climate Change (IPCC),
2007; 100-year timeframe): CH 4 , 25; N 2 O, 298;
and CO 2 , 1. A number of models and software
tools have been developed to estimate GHG emis-
sions from farming systems, or their compo-
nents (e.g. animals, crops, soils), with some of
these listed in Table 14.3.
Most GHG models are based to some extent
on IPCC (2006) methodology, which provides
 
Search WWH ::




Custom Search