Agriculture Reference
In-Depth Information
Standards
(Guinée
et al
., 2002). Readers inter-
ested specifically in using LCA for estimating
GHG emissions are referred to the specifica-
tion of the British Standards Institute (BSI,
2011a, b), which builds on the ISO standards
to provide a method for assessing the life cycle
GHG emissions of goods and services.
There are four phases of a LCA:
Functional Unit
The Functional unit (FU) is the measure of out-
put from the system and provides a reference
point for expressing the environmental impacts.
For animal production systems, the FU is typi-
cally a kilogram of weight (either live weight
leaving the farm, shrunk weight at the abattoir,
or carcass weight) for beef and sheep, and a kilo-
gram of milk for dairy production. Milk is usually
normalized as energy corrected milk (ECM) or fat
and protein corrected milk (FPCM) to account for
differences in milk components (note, ECM and
FPCM are virtually interchangeable, differing by
1%) (Tyrrell and Reid, 1965). The International
Dairy Federation (IDF, 2010) recently published
guidelines for conducting LCA for the dairy
industry and recommended the use of FPCM as
the FU, with fat corrected to 4% and protein cor-
rected to 3.3%. It should be noted that the IDF
(2010) equation predicts slightly lower FPCM at
a given milk composition compared with most
other equations (Tyrrell and Reid, 1965).
When the goal is to determine efficient
use of land resources, a more appropriate FU
may be land use area (e.g. Beukes
et al
., 2010;
Foley
et al
., 2011). In this approach, land use
area includes the amount of land used directly
by the farming operation as well as the amount
of land required to produce any feed inputs.
Land use can be a particularly relevant FU for
assessing the impact of grazing management
systems, such as stocking rate. In addition, land
use has been used as a means of comparing
resource usage across the various livestock com-
modities. For example, de Vries and de Boer
(2010) compared 16 LCA studies from OECD
countries using a FU of land use per amount of
average daily intake of animal product. The daily
consumption of beef (60 g day
−1
) in OECD coun-
tries had the highest land use (1.65-2.96 m
2
,
followed by consumption (545 g day
−1
) of milk
(0.62-1.1 m
2
), pork (82 g day
−1
, 0.73-0.99 m
2
)
and chicken (74 g day
−1
, 0.60-0.73 m
2
), which
were relatively similar, and then consumption of
eggs (36 g day
−1
) with the lowest land use value
(0.16-0.22 m
2
). The large amount of land
required for beef production can be attributed to
a low efficiency of converting ingested energy
into edible meat coupled with the relatively small
number of progeny produced per cow annually.
However, it must also be stressed that beef cattle
1.
Goal and scope
: The goal and intended use of
the LCA set the depth and breadth needed in the
study. These considerations will affect the sys-
tem boundary (what elements are to be included)
and the level of detail needed.
2.
Inventory analysis
: The inventory phase
includes the collection of relevant input and
output data.
3.
Impact assessment
: The impact assessment
provides an understanding of the environmen-
tal significance of the results. This is done using
indicators to reflect the environmental issue or
impact category of interest (e.g. kg CO
2
equiva-
lent (CO
2
e) for GHG emissions).
4.
Interpretation
: The final stage leads to conclu-
sions and recommendations based on the origi-
nal goal of the LCA.
Types of Life Cycle Assessment
There are two basic types of LCA - attributional
and consequential. An attributional LCA analyses
the environmentally relevant flows to and from the
system, whereas a consequential LCA describes
how the environmental flows within a system
might change in response to a change in product
output (Finnveden
et al
., 2009). For example, an
attributional LCA might quantify the environmen-
tal impact of a dairy production system, while a
consequential LCA might assess the future envi-
ronmental burden of that same dairy system
assuming higher milk production (Thomassen
et al
., 2008a). To date, most LCAs in animal pro-
duction have been attributional mainly because
consequential LCAs are conceptually complex and
are required to be dynamic. Consequential LCAs
rely heavily on assumptions that directly affect the
outcome and often there is a lack of basic informa-
tion available. However, as LCAs are increasingly
used to direct agricultural policy, there is a growing
need for consequential LCAs to examine animal
production under future scenarios.
