Whole farm systems analysis of

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Whole farm systems analysis of
greenhouse gas emission abatement
strategies for dairy farms.

UT12945


F
inal
report
to Dairy Australia
on the


investigation and analysis into greenhouse gas
abatement strategies, modelling and decision tools

for
the
Austral
ian
dairy industry
.


Prepared by:

Karen Christie,
Dr
Richard Rawnsley, and
Dr
Danny Donaghy
(
Tasmanian Institute of Agricultural Research
,

University of Tasmania
)


August 2008













ii


Contents


Executive summary

................................
................................
..........................

1


Review of propo
sed project outputs

................................
..............................

3


1.

Project objectives

................................
................................
........................

4


2.

Project activities

................................
................................
..........................

7

2.1.

Collate and synthesise existing information relevant to greenhouse gas

abatement strategies for dairy farming systems

................................
............................

7

2.2.

Identify key abatement strategies for differing dai
ry farm systems

......................

13

2.3.

Quantifying the pre
-
farm embedded greenhouse gas emissions

.........................

17

2.4.

Modelling analysis to quantify the gr
eenhouse gas emissions of differing

dairy farm systems

................................
................................
................................
.....

20

2.5.

Selection of key abatement strategies for each differing farming systems

..........

35

2.6

Modelling analysis of each abatement strategy

................................
...................

39

2.7

Costs, benefits and synergies of adopting abatement strategies in a whole

farm systems context
................................
................................
................................
..

44

2.8

Evaluation of tools and processes to monitor greenhouse gas emissions

...........

47

2.9

Development of a spreadsheet model that enables a whol
e of system

comparison between indicative systems and changes in imports and

management practices.

................................
................................
..............................

50


3.

Way forward for the Australian dairy industry

................................
........

53

3.1.

Educate and promote best management practices

................................
.............

53

3.2.

On
-
going research requirements

................................
................................
........

55


4.

Conclusion

................................
................................
................................
.

57


5.

References

................................
................................
................................
.

58


6.

Appendices

................................
................................
................................

62



iii


List of tables

Table 1. Annual non
-
carbon dioxide greenhouse gas emissions for the dairy,

beef, sheep and pigs and poultry industries .
................................
................................
.

12

Table 2. Embedded greenho
use gas emissions from key farm inputs.

..........................

18

Table 3.
Description of the low supplementary feeding farm system.

............................

23

Table 4.
Descri
ption of the high supplementary feeding 1 farm system.

........................

25

Table 5.
Description of the high supplementary feeding 2 farm system.

........................

27

Table 6. Description of the total mixed ration 1 farm system.

................................
.........

29

Table 7. Description of the total mixed ration 2 farm system.

................................
.........

31

Table 8. A comparison of the total farm and intensity of greenhouse gas emission

and the percentage of emissions from each source
for

the five baseline farming

systems.

................................
................................
................................
........................

33

Table 9.

A comparison of the results of the baseline farm system and the three

most effective abatement strategies in reducing greenhouse gas emissions per

tonne milksolids, in terms of total farm and the carbon pollution reduction scheme
liability.

................................
................................
................................
..........................

40

Table 10. Ease of implementation and/or relevance of each abatement strategy

for a low supplementary feeding system, a high supplementary feeding system

and a total mi
xed ration feeding system.

................................
................................
.......

45

Table 11.
A comparison of the capacities of five greenhouse gas calculator models

.....

48



iv


List of figures

Figure 1. Australian total and percentage of total greenhouse gas emissions from

various industry sectors.

................................
................................
................................

10

Figure 2. Australian total greenhouse gas emissions

across the various agricultural
sectors.

................................
................................
................................
.........................

11

Figure 3. Estimates of potential reduction in enteric methane and nitrous oxide

with the ad
option of abatement strategies
.

................................
................................
...

15

Figure 4. The intensity of greenhouse gas emissions from the low supplementary

feeding farm system .

................................
................................
................................
....

24

Figure 5. The intensity of green
house gas emissions from the high supplementary
feeding 1 farm system.

................................
................................
................................
..

26

Figure 6. The intensity of greenhouse gas emissions from the high supplementary
feeding 2 farm system .

................................
................................
................................
.

28

Figure 7. The intensity of greenhouse gas emissions from the total mixed ration 1

farm system
................................
................................
................................
...................

30

Figure 8. The intensity of greenhouse

gas emissions from the total mixed ration 2

farm system
................................
................................
................................
...................

32

Figure 9. Total farm greenhouse gas emissions for each of the five farming

systems.

................................
................................
................................
........................

33

Figure 10. Total on
-
farm methane and nitrous oxide emissions for the baseline

farm system and three selected abatement strategies

................................
..................

42

Figure 11. A copy

of the results page from the Dairy Greenhouse gas Abatement
Strategies calculator.

................................
................................
................................
.....

52






v


List of
common
abbreviations


CH
4
-

methane

CO
2
-

carbon dioxide

CO
2
-
e
-

carbon dioxide equivalents

CP
-

crude protein

CPRS
-

carbon pollu
tion reduction scheme

DGAS
-

Dairy Greenhouse gas Abatement Strategies

calculator

DMD
-

dry matter digestibility

DM
-

dry matter

DMI
-

dry matter intake

GHG
-

greenhouse gas

ha
-

hectare

HSF
-

high supplementary feeding

kg
-

kilogram

kWh
-

kilowatt hour


L
-

litre

L
SF
-

low supplementary feeding

ME
-

metabolisable energy

MJ
-

megajoule

MS
-

milksolids

N
-

nitrogen

N
2
O
-

nitrous oxide

t
-

tonne

TMR
-

total mixed ration





vi


Acknowledgements


The assistance from the following people and organisations has been gratefully
received
:




Department of Agriculture, Fisheries and Forestry for project funding



Dairy Australia for project funding



Dr Richard Eckard and Cathy Phelps (project steering committee)



Colin and Erina Thompson (TMR dairy farmers),
Brian Crockart (CRC
Agrisolutions),
J
ess Coad (TIAR), Dr Cameron Gourley (Victorian DPI), Will
English (Victorian DPI)

and
Neil Lane (Interlact) for farm data



Dr Chris Grainger (Victorian DPI), Dr Deli Chen and Dr Helen Suter (University of
Melbourne) for abatement strategy information



Tim Gr
ant (Life Cycle Strategies) for farm input life cycle assessments



Dr Bill Slattery
and
Rob Waterworth (Australian Department of Climate Change)

for
NCAT

model

information



Robert Kildare for
DGAS
model development





1


Executive summary


The Australian dairy

industry is a diverse and complex industry, in terms of location,
climatic variability and management systems. While there is diversity within the industry,
farms can be categorised into

one of three farming systems
. This report has ex
am
ined
the greenho
use gas emissions
(GHG)
of
these three
farm
ing

systems found throughout
the industry, namely a low supplementary feeding system (LSF), a high supplementary
feeding system (HSF) and a total mixed ration feeding system (TMR).


Greenhouse gas emissions for th
ese three farming systems were determined in terms of
total farm GHG emissions, as the sum of the pre
-
farm embedded emissions associated
with farm inputs

and the on
-
farm carbon dioxide, methane and nitrous oxide emissions.
To
compare
between farming syste
ms, the total farm GHG emissions were divided by
farm milk production
and
reported as tonnes of
GHG emissions per tonne of
milksolids
(t
CO
2
-
e/t MS)
. Greenhouse gas emissions
were

12.2

and
12.
8
t CO
2
-
e/t MS for the
two
modelled
TMR system
s
,
were

14.0
and
15.3 t CO
2
-
e/t MS for the
two modelled
HSF
farm system
s
, and
w
as

17.5 t CO
2
-
e/t MS for the
modelled
LSF farm system.


Farm GHG emissions were also calculated in terms of emissions directly associated with
the farm (i.e. only on
-
farm methane and nitrous oxi
de

emissions
). Under an emission
trading scheme, farmers
c
ould
potentially
become liable for any on
-
farm
source of
emissions so a second series of figures were calculated and termed CPRS liability.
Greenhouse gas emissions under a CPRS liability ranged f
rom 9.5
and
9.8 t CO
2
-
e/t MS
for the TMR farm system
s
, were 10.6
and

11.3 t CO
2
-
e/t MS for the HSF farm system
s

and
was 1
4.0 t C
O
2
-
e/t MS for the LSF farm system.


These figures
highlighted that
as farm intensity
increase
s

(greater per cow milk
production,

greater feed intakes etc),
the intensity of GHG
emissions

(t CO
2
-
e/t MS)
decrease
s
.

This concept contradicts the edict that farm profitability for the
Australian
dairy industry has traditionally been associated with predominantly grass based diets
with l
ow to medium grain inputs.
Detailed farm e
conomic
analysis
is required

to highlight
which farm system will result in reducing farm GHG emissions without jeopardising milk
production and
farm business
profitability.


Previous research has highlighted that
adopting abatement strategies could reduce GHG
emissions on d
ai
ry farms by 20
-
30%.
However,
a review of the impacts and outcomes
of different abatement strategies, at a whole dairy system level,
h
as not been
undertaken
previously
. This report has explore
d the impact of abatement strategies on the whole


2


farm system.

W
e
have
modelled the effect of adopting either sing
le

strategies
or
an
all
-
inclusive abatement strateg
y
, in reducing GHG emission
s
.
Each strategy
can be
classified
into one of three categorie
s
-

namely
herd, feed and soil.


For each of the three farming systems, the greatest reduction in GHG emissions/t MS
occurred with
the

all
-
inclusive abatement strategy of increas
ed

herd weight,

feed
intakes
and milk production while feeding additives to
reduce emissions and applying fertilisers
coated with a nitrification inhibitor. This strategy reduce
d

GHG emissions by up to a
maximum of 22% for the LSF farm system, with lower reductions for the other two farm
systems. When assessing
a potential
CPRS
liability emission
,
the
reductions achievable
were up to a maximum of 25.5%. While there were
several
strategies available to farms
operating as either LSF or HSF farm systems, there
wa
s very little scope for TMR farm
systems to reduce their GHG emissions
.


When viewing this report, it must be remembered that this is a desktop analysis of
GHG
emissions. We have

highlighted some of the issues with adopting some strategies
. For
example
increas
ing

milk production

per cow to
very high levels
could
possibly
r
esult in
deceasing reproductive performance
, resulting in the
need to raise more replacement
stock

therefore increasing
farm
GHG emissions
.
In addition
, we have not
taken into
consideration the full implications of adopting any strategies in terms of
farm

economics,
changes to labour inputs

and skill base and/or
changes to farm infrastructure
, due to
difficulty in quantifying these changes in a simulated study.

Many of the abatement
strategies
discussed
are also time dependant. It would take many years o
f selective
breeding

within the farm system

to increase feed conversion efficiency, herd weight
and
/or
milk production

to reduce
the intensity of
GHG emissions
.


The current models available to
audit

farm GHG emissions are based on inventory type
algorit
hms
. None are
dynamic mechanistic models that
calculate
the impact of a feeding
abatement strategy on animal performance and

GHG emissions
. They are also
dependant on Australian emission factors based on limited field experimental data. For
example, nit
rous oxide emissions
losses from irrigated pastures

are
based on flood
irrigation
results from
inland V
ictoria
. W
hat
losses could we expect to have u
nder other
forms of irrigation, under different soil types

and/or
formulations of

N fertiliser
?

Better
un
derstandings of regional specific emission factors are critical if individual farms are
made accountable for their GHG emissions. To facilitate this, f
urther research
needs to
continue to build upon our current knowledge of minimising GHG emissions, in te
rms of
reducing GHG emissions from the dairy herd and from

nitrogen
fertiliser
management.




3


Review of proposed project out
puts


1.

Report quantifying the whole of system implications, including ‘opportunity costs’
and ‘benefits’ of adopting key GHG abatement

strategies across a range of dairy
farming systems.


This outcome has been achieved. The following report details the GHG
emissions associated with differing dairy farming systems and reviews potential
GHG abatement strategies for each system.


2.

Discussio
n paper evaluating tools and processes to monitor GHG emissions at a
farming systems level.


This outcome has been
achieved
. A discussion paper detailing the approach
es
used

to assess GHG emission
s

from

dairy farm systems and a
n
evaluation

of
available GH
G
tools

is given in Appendix
1
.
The discussion paper is essentially a
summarised version of this final report
.


3.

Develop a s
preadsheet

model
that farmers and industry can use to quantify
changes in GHG emissions at a farming systems level in response to ch
anges in
imports and management practices
.


This outcome has been exceeded. The project has de
veloped
a spread sheet
model

which contains 1
3


worksheets


and
four “userforms”

a
s

its core and is
viewed using Visual Basic for Applications. A CD copy of the m
odel is provided
and
a
user manual of the
model is given in Appendix
2
. The m
odels allows for th
e
qua
ntification of GHG emission from differing dairy

fa
rm

systems

which include
emission
sources

from imports (pre
-
farm) and on farm
sources

(
carbon dioxide,
m
ethane and nitrous oxide)
. The model allows for compa
rison

between system
s

where differing
abatement

strategies

can be
assessed
.
The model has been
designed with the flexibility to allow future comparisons to be explored as they
become available
.




4


1.

Projec
t
o
bjectives

Previous research undertaken in Australia had highlighted numerous strategies which
could result in reducing GHG emissions in the order of 20 to 30% from dairy farms.
However, the assessment of the impact of adopting abatement strategies has
generally
not taken into consideration the whole of farm systems implications or the potential GHG
emissions associated with key farm inputs such as fertilisers, grain and other feed
sources. Th
e

current
project

aimed to quantify the

potential reduction i
n GHG emissions
for selected abatement strategies from a farming systems viewpoint

and cons
isted

of
four major objectives:



Quantify the
greenhouse gas (GHG)

emissions (including embedded
emissions in key
farm
inputs) from three typical dairy farming system
s
:



A
system based p
redominantly on
pasture, with low levels of
supplementation

(
15% of to
tal diet supplementary feeding),



A
system
based

on high levels of supplementary feed
(40
-
50% of the total
diet from supplementary feeding),



A t
otal mixed ration
system

(zero grazing with all feed supplied in an
enclosed area);



Quantify the impacts on those systems (GHG, costs, benefits and synergies)
of a range of GHG abatement strategies in a whole farm systems context;



Identify likely methods of validating GHG abateme
nt and associated costs;




Evaluate the usefulness of science based modelling, including ex
isting tools
such as OVERSEER and WFSAT (Whole Farm Systems Analysis Tools), to
estimate changes in GHG emissions resulting from changes in management
practices, and
to provide a possible monitoring and reporting strategy.


Greenhouse gas emissions have been reported in two ways. The first
method
was total
farm GHG emissions (t CO
2
-
e/farm), as the sum of four sources: pre
-
farm embedded
GHG emissions from imported prod
ucts, on
-
farm carbon dioxide, on
-
farm methane and
on
-
farm nitrous oxide. In addition, a GHG emission intensity figure was calculated by
dividing total farm GHG emission by tonnes of milksolids produced (t CO
2
-
e/t MS).



The second method involved assessi
ng the GHG emissions that
potentially c
ould be a
direct liability under an emissions trading scheme. The
Australian
F
ederal
G
overnment
is

in the process of introducing an
emissions trading scheme

titled
the Carbon Pollution


5


Reduction Scheme (CPRS). This
CPRS will come into effect in 2010, with agriculture
potentially liable for their on
-
farm methane and nitrous oxide emissions from 2015
onwards. Similarly to the total farm GHG emissions, two figures have been reported
-

CPRS farm GHG emissions (total meth
ane and nitrous oxide; t CO
2
-
e) and CPRS
emissions

intensity

(t CO
2
-
e/t MS).


A series of project activities have been undertaken to meet the four key project
objectives and are described in details in each of the following

sections:


Objective 1
-

Quantify

the greenhouse gas (GHG) emissions (including embedded
emissions in key inputs) from three typical dairy farming systems

The following activities were undertaken to meet this objective.



A
collation and synthesise of existing information relevant to GHG
a
batement
strategies for
dair
y farm systems,



A review of the potential abatement
strategies
for differing da
i
ry farm
systems
,



A quantification of the embedded
GHG
emissions in d
ai
ry farm imports
,



An assessment of the GHG
emission
s

from

differing

dairy
farmi
ng systems.


Objective 2
-

Quantify the impacts differing dairy systems for a range of GHG abatement
strategies in a whole farm systems context

The following activities were undertaken to meet this objective:



Selection

of the key abatement strategies for ea
ch of the differing farming
system
,



A
whole farm system
modelling analysis
for each abatement strategy for each
farming system
.


Objective 3
-

Identify

likely methods of validating GHG abatement and associated costs

The following activit
y was

undertaken to
meet this objective:



A
review of the potential

opportunity costs,

benefits and synergies of differing
GHG abatement stra
tegies at
a
farming system
s
level.






6


Objective 4
-

Evaluate the usefulness of science based modelling, including existing tools
such as
OVERSEER and WFSAT (Whole Farm Systems
and
Analysis Tools), to
estimate changes in GHG emissions resulting from changes in management practices,
and to provide a possible monitoring and reporting strategy

The following activities were undertaken to meet th
is objective:



An evaluation of tools and process to monitor greenhouse gas emissions
,



Development of a spreadsheet model that enables a
whole of system

comparison between indicative systems and changes in imports and
management practices
.



























7


2.

Project activities

2.1.

Collate and synthesise existing information relevant to
greenhouse
gas

abatement strategies for dairy farming systems

Sources of greenhouse gases

It is widely accepted that since the beginning of the 20
th

century, human activity
has
resulted in global warming due to the increase in greenhouse gas (GHG) emissions into
the atmosphere (Dalal
et al.

2003b). The three major
gases

that are widely accepted as
contributing to global warming are
carbon dioxide (CO
2
), methane (CH
4
) and nit
rous
oxide (N
2
O). Molecule for molecule,
carbon dioxide

is a weak
gas

in terms of its global
warming potential. Compared to
carbon dioxide
, on a 100
-
year timescale, the
global
warming potential

of
methane

and
nitrous oxide

are 21 and 310 times greater,
r
espectively

(IPCC 2001).

Multiplying the GHG by its
global warming potential

converts
all three gases to a carbon dioxide equivalent (CO
2
-
e) to allow for easier comparisons
between gas sources.



A global annual
carbon dioxide

emission rate of approxima
tely 23.9 gigatonnes has been
estimated by the Carbon Dioxide Information and Analysis Centre (Marland
et al.

2005).
Methane emissions amounted to ~
7.6 gigatonnes of CO
2
-
e/annum
while
nitrous oxide

emissions
have been estimated to be within the range of
3.1 to 5.4

gigatonnes of CO
2
-
e/annum
(Marland
et al.

2005).


Carbon dioxide

Carbon dioxide is a heavy
gas and is

approximately 380 parts per million (ppm) of the
atmosphere
. Carbon dioxide emissions have

risen by approximately 100

ppm since
1750 (startin
g date considered to be practically uninfluenced by human activity such as
increasing specialised agriculture, land clearing and the combustion of fossil fuels;
Blasing and Smith (2006)).


Carbon dioxide is released into our atmosphere when carbon
-
based

fossil fuels such as
oil, natural gas and coal are burned. Increased global burning of fossil fuels has
contributed to an increasing amount of
carbon dioxide

in the atmosphere. Carbon
dioxide is also produced by all animals, plants, fungi and micro
-
organi
sms during
respiration and organic decomposition. Carbon dioxide is used by plants during


8


photosynthesis to make sugars which can either be
used for plant growth or be
consumed in the process of plant respiration.


While electricity usage
does not result
in carbon dioxide emission
at a farm level
, there is
an embedded carbon dioxide emission associated with its production. There is also an
emission associated with the production and consumption of fuel
s

such as diesel. When
analysing the
dairy
whole farm

system, the emission from the production and
consumption of energy
have been
grouped together as CO
2
-

energy. While these
emissions have been accounted for at a whole farm system analysis, they are unlikely to
be accounted for at a farm systems level in
any future
CPRS
.



Methane

Methane is a colourless, odourless gas with a wide distribution in nature. It is the
principal component of natural gas and is derived from the anaerobic breakdown of
organic matter. A recent figure of the abundance of
methane

in the Earth’s atmosphere
from the northern hemisphere was 1847 parts per billion (ppb) with a southern
hemisphere figure of 1730 ppb. These figures are
2.5 times greater than
pre
-
1750
figur
es
(Blasing and Smith 2006).


Methane is an important greenhouse

gas with a
global warming potential

of 21

times
greater than that of carbon dioxide

over a 100 year period (UNFCCC 1995).
However,
the global warming potential o
f
methane
,

over a 20 year time period is markedly greate
r

at up to
72
, due to
methane
having a
n estimated

half life
between
7
and

10 years

(IPCC
2007). There are six different sources of atmospheric
methane
;
wetlands, fossil fuels,
landfills, ruminant animals, rice paddies and biomass combustion.


In ruminant animals
,

methane

originates from the a
naerobic microbial fermentation
process in the gastrointestinal tract. As feed is ingested by ruminants, the proteins,
starch and plant cell
-
wall polymers of the feed is hydrolysed into amino acids and simple
sugars by the bacteria, protozoa and fungi tha
t reside in the rumen. Primary and
secondary digestive micro
-
organisms further ferment the amino acids and sugars into
volatile fatty acids, hydrogen,
carbon dioxide

and other end products. Methanogen
micro
-
organisms then reduce the
carbon dioxide to met
hane

so as to prevent the
accumulation of hydrogen in the rumen (McAllister
et al.
1996).



9


The
emission of methane from livestock represents a direct loss of energy to the
ruminant, as
between 4

and 10
% of
all ingested energy is excreted as methane
(
Johns
on
et al.

1997
).
T
his represents a significant loss of energy from the production
system that could be redirected to produce more milk (Eckard 2006).

A small amount of
methane is also emitted with the excretion and decomposition of manure.


Enteric
meth
ane

emissions from dairy farm systems can be reduced by improving the
digestibility of the diet, reducing the number of unproductive animals and/or modifying
the rumen outputs by feeding additives such as fats, condensed tannins and ionophores.


Nitrous ox
ide

Nitrous oxide
,
commonly known as laughing gas
,
is a colourless non
-
flammable gas that
is released naturally from a wide range of biological sources in soils and the oceans. It is
a

by
-
product of the aerobic nitrification process when am
monium is oxidis
ed into nitrate.

Nitrous oxide can also be a result of the anaerobic denitrification process when
nitrate

is
microbially converted into either di
-
nitrogen or
nitrous oxide
. This process is maximised
in warm, anaerobic soil conditions when there is large
amounts of
nitrate

and available
carbon present (de Klein and Eckard 2008).


The atmospheric concentration of nitrous oxide has increased from 270 ppb pre
-
1750 to
a current value of ~319 ppb and continues to increase (Blasing and Smith 2006). Nitrous
oxid
e concentrations are increasing
due to
land
-
use changes, burning of vegetation,
industr
ial emissions and fertiliser usage
. Agriculture is the main source of human
-
induced

nitrous oxide

emissions
. Nitrous oxide is lost from agricultural soils as a result o
f
cultivation, legumes, nitrogen fertilisers and animal excreta (Eckard 2006).


Nitrous oxide emissions
from a dairy farm system
can be reduced by balancing the
animals’ diet to minimise excess nitrogen in their urine and dung. Emissions can also be
red
uced by minimising anaerobic soil conditions, reducing soil compaction and/or
improving fertiliser management practices through the use of
current best management
practices and in using various products such as
nitrification inhibitors.






10


A
ustralia’s
gree
nhouse gas

emissions

Australia’s net GHG emissions across all sectors totalled
576

million tonnes of carbon
dioxide equivalents (Mt CO
2


e) in 200
6
. The stationary energy sector contributed
287.4

Mt CO
2


e or approximately half of these emissions, with ag
riculture the second largest
contributor, with
90
.
1

Mt CO
2

-
e or approximately 15.
6
% of the nation’s
GHG

emissions

(
Australian Department of Climate Change 2008a
;
Figure 1).


0
50
100
150
200
250
300
350
Stationary
Energy
Agriculture
Transport
Land Use,
Land Use
Change and
Forestry
Fugitive
Emissions
Industrial
Processes
Waste
Mt CO
2
-e
50%
16%
14%
7%
6%
5%
3%

Figure
1
.
Australian total and percentage of tot
al greenhouse gas emissions from various
industry sectors for 200
6

(
Australian Department of Climate Change 2008
a
).


Australia committed itself to playing a major role in addressing its contribution to the
global issue of climate change by ratifying the Ky
oto Protocol in late 2007. This
ratification has committed Australia to limiting
the growth of
its GHG emissions to 108%
of its 1990 baseline by 2012
.
While the
major focus
in reducing GHG emissions
has
been placed on the stationary energy, industrial an
d transport sectors
, t
he agricultural

sector
will also
be required to implement their own series of measures to tackle the issue
of GHG emissions and climate change.



Australia’s agriculture
greenhouse gas emissions

Within agriculture, there are six
broa
d
sources of
GHG
emissions. Based on 200
6

figures, enteric fermentation
wa
s the
most significant
at
59.3

Mt CO
2


e or ~6
6
% of the
total agricultural emissions. Agricultural soils contribute
d

15.2

Mt CO
2


e, followed by
the prescribed burning of savannas
at
11.5

Mt CO
2


e, manure management at
3.6

Mt
CO
2


e,
with
the field burning of agricultural residues
and rice cultivation both totalling


11


0.3

Mt CO
2


e
(F
igure 2). Agriculture
wa
s the dominant source of
methane and nitrous
oxide
emissions
,
accounting for

59% and
84
% of the nations’ total
methane and nitrous
oxide
gas emissions, respectively

(
Australian Department of Climate Change

2008
a
).

0
10
20
30
40
50
60
70
Enteric
fermentation
Agricultural soils
Burning
savannahs
Manure
management
Rice cultivation
Burning crop
residuals
Mt CO
2
-e
65.7%
16.9%
12.7%
4.0%
0.3%
0.3%

Figure
2
.
Australian total greenhouse gas emissions across the various agricultural
secto
rs for 200
6

(
Australian Department of Climate Change 2008
a
).


Australia’s livestock
greenhouse gas emissions

Within the agricultural sector, livestock was the biggest contributor of emissions at 62.8
Mt
which was

69.7% of agricultural emissions or approxim
ately 11% of the nations


total
emissions (Australian Department of Climate Change 2008a
).
The production of
methane

from
livestock
enteric fermentation
wa
s the biggest source of GHG
emissions
for Australian agriculture
.
Table 1 shows the GHG emission rat
es from
methane and
nitrous oxide

f
or

the dairy, beef, sheep, pigs and poultry industry in 200
6

(
Australian
Department of Climate Change 2008
a
).












12


Table
1
.

Annual non
-
carbon
dioxide
greenhouse gas emissions
, expressed as kilo
tonnes
of carbon dioxide equivalents,
for the dairy, beef, sheep and pigs and poultry industries in
200
6

(A
ustralian Department of Climate Change 2008
a)
.


Dairy
cattle

Beef
Cattle

Sheep

Pigs &
Poultry

Methane from enteric

fermentation

(kt CO
2
-
e)

6,802

3
8,653

15,570

81

Methane from manure
management

(kt CO
2
-
e)

5
24

1,129

4

1,889

Nitrous oxide from animal excretion
directly onto pastures/rangelands

(kt CO
2
-
e)


656

2,036

1,390

neg

Nitrous oxide from animal waste
stored and applied to soils


(kt CO
2
-
e)

83

351

neg

266


The extensive agricultural industries of beef and sheep farming are major contributors to
the nation’s emissions, primarily due to the significantly larger number of animals within
each industry (
2005 figures of
~ 24 and 100 million beef cat
tle and sheep
, respectively
,

compared to 3.2 million dairy cattle (inc. 2 million milking cows
)
; ABARE 2007a, b & c
)
.
Implementing abatement strategies to reduce their contribution to GHG emissions could
result in substantial reductions in GHG emissions.

However, the very nature of these
industries could
add a degree of difficulty in
implement
ing
abatement strategies.


Beef and sheep f
arms are generally reliant on low to medium digestibility pasture to
supply the majority of the herd or flocks diet, wi
th supplementary feeding generally
restricted to times of drought and when finishing off stock for slaughter. Contact with the
herd or flock can
be highly varied, from
daily to weekly contact on smaller farms, through
to annual contact on some of the larg
e (million plus hectare
s
) northern Australian cattle
properties. The reduction in stock contact, together with low to medium pasture
digestibility and extensive grazing constrain the opport
unities to reduce
GHG
emissions
for

the Australian beef and sheep
industries.




13


Dairy farming, on the other hand, involves daily contact with the milking herd, and
coupled with medium to high quality pastures
,

allows for a variety of abatement
strategies to be implemented. Therefore
,

there is a more practical pathway av
ailable to
dairy farmers to implement abatement strategies on farm to reduce GHG emissions.


A
ustralia’s dairy industry

greenhouse gas emissions

Methane

from enteric fermentation
was

the biggest source of GHG for the dairy industry,
with an estimated
6
,802

kt CO
2
-
e emissions in 200
6

(Table 1). The second biggest
source
wa
s
nitrous oxide

from urine and faeces
deposition
while stock
grazed

pastures
,
at
656

kt CO
2
-
e. Approximately
500

kt CO
2
-
e
of this
was from urine
and

the balance
from faeces. Methane
produced from
a
nimal manures was
the third biggest at
524

kt
CO
2
-
e
,

with 79% of this from

manure
s

deposited into
anaerobic ponds. There was also
a small amount of
nitrous oxide

emitted from the application of manures onto soils at ~
83

kt CO
2
-
e. No figur
es were presented in terms of
nitrous oxide

emissions from the
application of nitrogenous fertilisers onto dairy pastures. Assuming that
all

synthetic
fertilisers applied to irrigated and dryland pastures could be attributed to the dairy

industry

(RJ Ecka
rd pers comm.), it could be assumed that the d
ai
ry industry contribute
d

an additional
797

kt CO
2
-
e (
Australian Department of Climate Change 2008
a
).

Therefore
, in 2006,
the Australian dairy industry contributed approximately 2% or 8,870
kt CO
2
-
e towards th
e nations’ GHG emissions.



2.2.

Identify key abatement strategies

for differing dairy farm systems

There have been many reviews of potential abatement strategies to reducing non
-
carbon
dioxide

emissions from agricultural and/or livestock practices (Dalal
et a
l.
2003a; O’Hara
et al.
2003; Tamminga
et al.

2007; Beauchemin
et al.

2008; de Klein and Eckard 2008).
A
review

of

key abatement strategies
t
hat
are

both currently available and relatively
easily adoptable by farmers
was undertaken in milestone 3
(
refer t
o
Appendix 3 for

details)
.


The impacts of abatement strategies from these research review papers have been
reported in several ways. Methane emissions has been reported as a total (e.g. 135 g
CH
4
/cow.day
), in terms of a percentage of gross energy intake

(e.g. 5.5% GEI) or in
terms of the amount of emissions per kg of dry matter intake (e.g. 20g CH
4
/ kg DMI).
Nitrous oxides emissions have been reported as a total (eg. 22.3 Mt CO
2
-
e/year), as


14


nitrous oxide

emissions per unit area (eg. 11 kg N
2
O
-
N/ha) or as

a fractional loss per unit
application (eg 1.5% N
2
O
-
N/kg N applied).



A summary of the potential reduction in GHG emissions from the adoption of abatement
strategies can be seen in
Figure
3
. However, it must be noted that the adoption of one
or more of

these strategies may result in a lower reduction than reported here,
depending on which of the three broad farming systems the strategy is applied to. For
example, a TMR diet is
generally formulated by animal nutritionalists and is balanced in
terms of s
upplying the correct amounts of energy, protein and fibre concentration.
Therefore there is very little scope in improving the quality of the TMR diet. Total mixed
rations also frequently contain sources of fats such as whole cottonseed and as such,
ther
e is also less scope to increase the fat con
tent

of the diet to assist in reducing
methane

production. Therefore, while feeding fats and oils could potentially reduce
methane

production by 10
-
25%, for a TMR farm, this abatement strategy is either
unlikely

to be adopted or if adopted, would result in a significantly lower GHG emission
reduction than
reported.





15



Figure
3
.
Estimates of potential reduction in enteric methane and nitrous oxide with the
adopt
ion of abatement strategies (Adapted from pers. comm. Eckard & Grainger 2007,
refer to Appendix 3 for more details).


We have not focussed on abatement strategies that are currently
un
available f
or

farmers
to adopt. For example,
while
CSIRO have been
deve
lop
ing and testing various
vaccine
s

to reduce
methane

production
,
the
se vaccines
have
not been
commercially
released and
therefore
are

not currently available for use
. In a press release Dr Rob Kelly

predicted
“we expect that the commercial vaccine will b
e able to reduce methane emissions by
about 20%” (Science
Daily
, 11
th

June, 2001
).

Once this vaccine is available, we will be
able to incorporate it as an abatement strategy into the new
Dairy Greenhouse gas
Abatement Strategies (DGAS)

calculator.



GHG emissions

Enteric Methane

Nitrous oxide

Extended lactations

Reduced herd size

Extended longevity in
the herd


Higher feed c
onversion efficiency

Feeding fats & oils

oioioioils

Feeding fats & oils


Feeding condensed tannins

Feeding ionophores

Condensed tannins

Nitrification inhibitors in urine

Higher feed conversion efficiency

Balance crude protein in the diet

Herd based strategies

10
-
50
% po
tential

reduction in
urinary nitrogen

Soil based strategies

10
-
20
% potential

Nitrification inhibitors

Improved drainage

Stand
-
off pads during winter

Fertiliser management
-


rate/ timing/ formulation

Improved irrigation management

Herd based str
ategies

10
-
20
% potential

Feed based strategies

10
-
20
% potential

Maximise diet digestibility



16


In u
ndertaking this project
,
we have
reviewed

three
strategies
which
are not currently
available but have the potential to

significant
ly

reduce
GHG emissions.
Researchers
only beg
a
n to
genome seq
uence
the
methanogen

micro
-
organisms responsible for
methane

pro
duction

in the 1990’s.
According to Attwood and McSweeney

(2008)
, there
are several methanogenesis pathways present in the rumen
. R
esearch
is
required to
develop a better understanding of
the complex process

in which methanogens produce
methane
, especial
ly under the grazing conditions prevalent in the Australian dairy
industry

(Jarvis
et al.
2000).
This

will hopefully lead to future options for
methane

mitigation
.
E
xample
s

of such mitigation
are

the enhancement of r
umen micro
-
organisms
that combine
carbo
n dioxide

and
hydrogen

to form acetate
instead of
methane

or
to
promote organisms that
divert excess hydrogen away from
methane

production into
pr
opionate
.


Researchers in the USA and other countries are developing new lucerne
(
Medicago
sativa
)
and other
forage cultivar
s
that contain adequate levels of condensed tannins to
assist in improving protein absorption (Grabber
et al.
2002). Recent research on the
benefits of feeding
condensed tannins
to dairy cows in Victoria
,

administered as an
extract of
t
he B
lack Wattle tree

(
Acacia mearnsii
)
in a water
-
diluted drench twice daily
,
found
that
methane

emissions were reduced by 10 to 22% on a DMI basis

(Grainger
et
al.
2008)
.

However, t
his
method of administering a source of
condensed tannin

would
be very tediou
s and time consuming
in the context of a
commercial
ly operated

dairy
farm
.


B
reeding
tannins

back into forages
would have several additional benefits beyond being
a delivery mechanism for the tannin.
Lucerne is an accepted source of forage, unlike
other

condensed tannin
-
rich
forages such as birdsfoot trefoil

(
Lotus corniculatus
)

and
sulla

(
Hedysarum coronarium
)
.

Therefore
farmers
w
ould

be
more
supportive of
growing
and feeding
lucerne t
o their herd
, compared to these other species
. Lucerne
is
a legume

forage
that synthesises its own N fertiliser to maintain growth
,
therefore reducing any
manufacturing and
fertiliser
-
related
nitrous oxide

emissions
. Lucerne will

generally
supply
adequate
energy and protein require
ments

for milk production and it is grow
n
widely
throughout

dairying regions of Australia.




17


It has long been recognised that there is variation in
methane

production both within and
between animals (Blaxter and Clapperton 1965).
Animals with greater feed conversion
efficiency will
result in red
ucing
methane
produ
ction per kg DMI,
as research by Hegarty
et al.
(2007) demonstrated that residual feed intake could partly explain the variation in
high and low
methane

producing beef cattle.
We believe that
research into identifying
and isolating the s
equence of DNA responsible for feed conversion efficiency
could

provide a
significant
strategy
in

reducing
methane

emissions. In the same way that
farmers currently select semen from bulls that will lead to improvements in milk quality,
temperament or bon
e structure, they may in the future be able to also select
semen from
a line of bulls
that’s

offspring will have greater feed conversion efficiency

and reduced
enteric
methane

emission
s

per unit of intake
.


Further

research into establish
ing

a greater und
erstanding

of the r
umen microflora,
in
breeding
forages
than could assist in supplying condensed tannins directly to the animal
rather than as a feed additive
and
/or
breeding
animals
that exhibit greater feed
conversion efficiency, therefore requiring less

forage to produce the same level of
milk
production,
will
all
result in significant improvements in reducing on
-
farm GHG
emissions. However,
the
implementations of the outcomes from th
ese areas of
research
are

still many years away.



2.3.

Quantifying

the

pre
-
farm embedded greenhouse gas emissions

The GHG emissions generated with the production of farm inputs such as fertilisers,
feeds and pasture chemicals was calculated by Tim Grant from Life Cycle Strategies Pty
Ltd, using Simapro software. An emission

factor (EF; kg CO
2
-
e/kg product) for a range
of i
nputs can be seen
in Table
2
.

To calculate the GHG emissions generated with the
production of each farm input product, the amount of product was multiplied by the EF to
convert into t CO
2
-
e. For example, g
rain has an EF of 0.302 so for every tonne of grain
that is imported onto farm; there is an associated pre
-
farm embedded GHG emission of
0.302 t CO
2
-
e. We grouped similar farm inputs together to calculate a pre
-
farm GHG
emission for grain, other feed sour
ces (hay, silage, grass seed etc), fertilisers and
herbicides. Once pre
-
farm embedded GHG emissions were calculated, the
y were added
to on
-
farm GHG emissions to determine the total farm GHG emissions. Details of
the life
cycle assessment of
each of the e
mbedded calculations are
given

in
Appendix
4
.



18


Table
2
.

Embedded
greenhouse gas
emissions from key farm inputs
.


Farm input (kg product)

Total

(kg CO
2
-
e)

CO
2

(kg CO
2
-
e)

CH
4

(kg CO
2
-
e)

N
2
O

(kg CO
2
-
e)

Sequestration
(kg CO
2
-
e)

Other

(
kg CO
2
-
e)

Source of data

Wheat

0.302

0.190

0.007

0.104

0.000

1.09E
-
06

Australian inventory data
-

based on average wheat crop
1.3 t/ha yield

Lupins

0.204

0.107

-
0.001

0.098

0.000

1.67E
-
06

Model from typical data in
NSW cropping

Grass silage
1

0.25

0.075

0.000

0.146

0.000

2.22E
-
05

Ecoinvent data

Grass hay
1

0.25

0.091

0.000

0.132

0.000

4.69E
-
05

Ecoinvent data

Maize silage

0.371

0.142

0.004

0.225

0.000

2.99E
-
06

From maize study in Griffith

Urea

0.891

0.839

0.050

0.002

0.000

1.99E
-
05

Adapted from ecoinven
t data

Ammonium sulphate, as
N

2.534

2.522

0.000

0.010

0.000

2.05E
-
03

Adapted from ecoinvent data

Single superphosphate,
as P
2
O
5


2.602

2.573

0.001

0.023

0.003

1.17E
-
03

Adapted from ecoinvent data

Triple superphosphate

0.834

0.816

0.015

0.003

0.000

1
.03E
-
04

Adapted from ecoinvent data

Diammonium
phosphate, as N

2.737

2.722

0.000

0.013

0.000

1.187E
-
3

Adapted from ecoinvent data

Monoammonium
phosphate, as P
2
O
5


1.592

1.580

0.001

0.008

0.000

5.64E
-
4

Adapted from ecoinvent data

1
Calculated
figure

base
d on European farming

conditions
, so
total GHG emissions were
adjusted to reflect Australian conditions



19


Table 2 cont. Embedded GHG emissions from key farm inputs
.


Farm input (kg product)

Total

(kg CO
2
-
e)

CO
2

(kg CO
2
-
e)

CH
4

(kg CO
2
-
e)

N
2
O

(kg CO
2
-
e)

Seques
tration
(kg CO
2
-
e)

Other

(kg CO
2
-
e)

Source of data

Potassium chloride

0.131

0.128

0.002

0.001

0.000

1.91E
-
05

Adapted from ecoinvent data

Limestone

0.019

0.019

0.000

0.000

0.000

1.80E
-
05

Australian inventory data

Pesticide unspecified

7.017

6.956

0.001

0
.058

0.000

2.57E
-
03

Adapted from ecoinvent data

Canola meal

0.308

0.256

0.006

0.045

0.000

5.82E
-
06

Based on data from study
done for AGO and Caltex

Soybean meal

0.485

0.373

0.009

0.102

0.000

4.25E
-
05

Based on data from study
done for AGO and Caltex

Palm

kernel oil

2.723

0.615

0.000

0.502

1.605

1.97E
-
04

Ecoinvent data

Palm kernel meal

0.186

0.042

0.000

0.034

0.109

1.34E
-
05

Ecoinvent data

Maize seed

1.923

1.000

0.000

0.922

0.000

3.95E
-
04

Ecoinvent data

Grass seed

3.367

1.093

0.000

2.272

0.000

4.69E
-
04

E
coinvent data

Clover seed

0.291

0.108

0.004

0.179

0.000

1.83E
-
06

From maize study in Griffith

Glyphosate (41.5%)

8.945

8.708

0.210

0.027

0.000

1.37E
-
04

Adapted from ecoinvent data

MCPA

4.000

3.968

0.001

0.030

0.000

9.39E
-
04

Ecoinvent data

Diuron

6.574

6.518

0.002

0.052

0.000

2.09E
-
03

Ecoinvent data

Diesel

0.719

0.671

0.046

0.002

0.000

1.38E
-
05

Australian inventory data




20


2.4.

Modelling analysis to quantify the
greenhouse gas

emissions of
differing dairy farm systems

Methodology to determine on
-
farm
greenho
use gas emissions

To model the on
-
farm GHG emissions, we used the Dairy Greenhouse Framework
calculator (refer
red to

as the GHG calculator) which was developed by Dr Richard
Eckard, Dr Roger Hegarty and Mr Geoff Thomas (Dairy Australia funded UM10778
proje
ct). The GHG calculator was developed using
Intergovernmental Panel on Climate
Change (
IPCC) and Australian
-
specific
algorithms

and emission factors to determine
carbon dioxide, methane and nitrous oxide

emissions that conform to international
guidelines
developed by the United Nations Framework Convention on Climate Change.


Methane

emission
s

from enteric fermentation is
calculated

based on Australian
methodologies, as the IPCC approach uses a fixed
methane

conversion rate for each
livestock category
. This IPCC method was deemed
unsuitable for the Australian dairy
industry due to
the industries

vast difference
s

in terms of
location and types of feeds
used. Methane production from manure management uses a combination of IPCC and
Australian
-
specific m
ethodologies, as research measuring
methane

production from
dairy cattle manure under field conditions found that the IPCC conversion f
actor of 1.5%
was too high for Australian
conditions, resulting in a reduction of the factor to 1
.0
%.


Nitrous oxide emis
sions
from manure management is based on
algorithms

developed in
Australia
from the Australian Standing Committee on Agriculture (1990) and
by
Freer
et
al.

(1997)
,

rather than
applying
IPCC default values
.
The methodology for determining
GHG emissions fro
m N fertiliser is based on Australian
-
specific emission factors
was
reduced to
0.3 and 0.4% for crops and pastures, respectively
, as the IPCC default factor
of 1.25% across all classes of crops and pastures was shown to be too high for
Australian condition
s.


Since the development of the GHG calculator, based on the 2003
national
methodology
inventory
report, there have been two significant changes. Communications with Dr
Mick Meyer from CSIRO has confirmed that
nitrous oxide

loss from soil disturbance ha
s
been removed

from the inventory
. A
t the same time a

nitrous oxide

emission
from
indirect sources

has been added. The indirect sources are from the
ammonia


21


volatilisation and the
leaching
/runoff
of N fertilisers and animal waste. Modelling in this
repo
rt
reflects these inventory changes
.


Modelling the three dairy farming systems

The first objective of this project was to quantify the GHG emissions from three typical
dairy farming systems. These
we
re
defined as a low supplementary feeding system
(LSF)

where a
pproximately 10
-
15% of the total diet to the milking herd
wa
s from
concentrates/grain, with the balance (85
-
90%) from pasture. The second system
wa
s

defined as a high supplementary feeding system (HSF)
where approximately 50
-
60
% of
the herd’s feed

intake
wa
s derived from pastures with the
balance (
40
-
50%
)

of the diet
derived from grain

and

other supplementary feeds. The third system
wa
s defined as a
total mixed ration feeding system (TMR)
where the milking herd
wa
s
maintained in an
enclosed area y
ear round and
their diet
wa
s either a cut and carry system from home
grown forages or sourced
from
off
-
farm

feeds
.


The process adopted to
model the
LSF and HSF

farm systems

was to model a farm
system where annual milk production totalled 2 million litre
s

or 150 t MS and was
located

in Victoria
.
For the LSF
farm
system,
this was achieved by milking 445 cows
, with
each
cow
producing 4,500L/lactation

and the diet consisting of 89% pasture and 11% grain
.
From here on this farm system is referred to as LSF
.


For the
HSF
farm system, the milk production target

was achieved by one of two
methods:




A pasture and grain system where 310 cows produced 6,500L/lactation and
the diet consisted of 56% pasture and 44% grain. From here on this farm
system is referre
d to as HSF 1;



A

pasture, grain and maize silage
system where 333 cows produced
6,000L/lactation and the diet consisted of 56% pasture, 26% grain and 18%
maize silage from an off
-
farm source. From here on this farm system
i
s
referred to as HSF 2.





22


Two
TM
R

dairy systems were modelled based on farm data from commercially operated
TMR dairies

both located in New South Wales
. The two systems were:





A traditional TMR farm, with cows housed in a large freestall system
with

the
diet consist
ing

of 42%
forage, c
onserved both on and off farm
, 30% grain and
28%
by
-
products (waste from Manildra Mills, cottonseed meal, molasses and
whole cottonseed).
This farm produced 3.8 million litres or 285 t MS per
annum.
From here on this farm system is
refer
r
ed

to as TMR 1;



A farming system which has converted from a traditional pasture grazing
system to a cropping system due to reduced water allocations,
with

the diet
consist
ing
of 43% on
-
farm conserved forage, 36% grain and 21% ‘waste’
products (canola meal, soybean meal, d
ried distillers grain and cottonseed
meal).
This farm produced 6.4 million litres or 487 t MS per annum.
From
here on this farm system is referred to as TMR 2.


To allow easier comparison of the total farm GHG emissions between the farming
systems, the tw
o TMR systems were scaled down to replicate farms that produced 150t
MS/annum (
the
same as the LSF and HSF systems), by dividing their baseline total farm
GHG emissions by their total MS production and then multiplying by 150.
Only these
scaled downs figu
res are shown in this report.


In addition, the TMR 1 farm agist their replacement stock off farm, thus reducing their
on
-
farm
GHG emissions. Reintroducing the replacement stock on farm allowed for all farm
systems to be comparative in terms of herd str
ucture.


It is generally accepted that daily feed intake can be determined from bodyweight. Daily
DMI is generally 3
.0 to
3.5% of a cows bodyweight so for every 100kg of body weight, a
cow can consume 3

to
3.5 kg DM
/day
. For the LSF baseline system we as
sumed that
the cows were consuming 3% of their bodyweight or 15kg DM/
day
, increasing to 16.5 kg
DM
/day

when the
weight was increased to
550kg.

This resulted in a feed conversion
efficiency of 1L milk/kg DMI, which according to Buckley
et al.
(2007), is on

the lower
scale

of the feed conversion efficiency scale.

For the HSF baseline system, we
assumed that the cows could consume 3.25% of their bodyweight or 18 kg DM/day,
increasing to 19.5 kg DM/day when
the
weight was increased to 600kg.

We assumed


23


that
for the HSF 1 system,
every kg DMI resulted in 1.2L milk to achieve 6,500L from 5.4

t
DMI
, while the lower quality diet of the HSF 2 farm system
resulted in 1.1L milk from
every kg of feed to achieve 6,000L from 5.4 t DMI.


Low supplementary feeding system

The LSF farm system consists of 445 milkers
, each
producing 4,500L/cow.lacation from
a predominantly pasture based diet (Table
3
).


Table
3
.

D
escription
of the
low supplementary feeding
farm
system
.


Description

Baseline

Cow numbe
rs

445

milkers

Cow weight

500 kg

Milk production

4,500L/cow or
15.0

L/day

Heifer replacement rate

20% or 90 heifers/year

Farm size
-

milking area

300 ha at 1.5 cows/ha with 20% irrigated

Farm size
-

heifer area

120 ha at 1.5 heifers/ha

Total farm
size

420 ha

Annual diet for milkers

1

4.0 t pasture & 0.5 t grain

Diet of 4.5 t DM, 71.1% DMD,

ME 10.4 MJ/kg DM & CP 19.
1
%


Diet for heifers

70% DMD, ME 10.2 MJ/kg DM & CP 16%

Total N fertiliser applied
2

72
.0 t

Grain imported

223 t

DM

Diesel

15,00
0 L

Electricity
3


12
0
,000 kWh

1

see Appendix
5

for diet quality calculation
; DMD
-
dry matter digestibility, ME
-

metabolisable
energy, MJ
-
megajoules & CP
-
crude protein


2
N fertiliser based on 150kg N/ha
.annum

for dryland pastures, 300 kg N/ha
.annum

for i
rrigated
pastures

3
Electricity based on dairy consuming 0.67 kWh/cow for 365 days

and
irrigators consuming 8
kWh/ha.day for 150 days on a 6 day rotation


Total farm
GHG
emissions for the LSF system w
as

2,623

t CO
2
-
e/farm or
17.5

t CO
2
-
e/t
MS, with enteri
c
methane

production equating to 9.3 t CO
2
-
e/t MS or ~
53
% of the total
farm emissions. As a percentage of the total farm GHG emissions, pre
-
farm,
on
-
farm


24


carbon dioxide
,
on
-
farm
methane

and on
-
farm
nitrous oxide

emissions were
11.
4
,
8.
3
,
54.5

and
25.7
%,
respectively
(Figure
4
).

Assessment of the on
-
farm liability GHG
emissions showed that
CPRS

farm GHG emissions was 2,105
t CO
2
-
e/farm or
14.0

t
CO
2
-
e/t MS, with enteric
methane

~
67
% of the
on
-

farm
CPRS

emissions.



Figure
4
.

The intensity of greenhouse gas emissions from the low supplementary feeding
farm system calculated as
pre
-
farm (

),

on
-
farm carbon dioxide (

)
,
on
-
farm methane (

)

and on
-
farm nitrous oxide emissions (

)
, total farm (

; t CO
2
-
e
/t MS)

and that liable under a
carbon pollution reduction scheme
(

; t CO
2
-
e/t MS
)
.

The percentage of total farm
emissions from
each source shown as the
enclosed pie chart
.



High supplementary feeding system

For the HSF system we have modelled two contra
sting farm systems. The first was a
high grain based di
et, where the cows received ~ 56
% of their diet from pasture and the
balance of their diet from grain

(HSF 1)
. The second system replicated many of the
aspects of the first system with the major diff
erence being that this diet consisted of ~
5
6
% of the diet f
rom pasture, 26% from grain and 1
8
% from maize
silage sourced off
-
farm
(
HSF 2
)
.
Feeding silage
was estimated to
increase the diesel usage on farm from
15,000L/annum to 20,000 L/annum.


The HSF
1

f
arming

system
consists of 310 milkers,
with
each
cow
producing
6,500L/cow.lactation from a diet that
was

5
6
% pasture and 4
4
% grain (Table
4
).





0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
20.0
Fertiliser
Herbicide
Grain
Other feed sources
CO2 -Energy
CH4 - Enteric
CH4 - Effluent ponds
N2O - Effluent
N2O - N Fertiliser
N2O - Dung & urine
N2O - Indirect
Tree plantings
Total farm
CPRS liability
GHG emissions (t CO
2
-e/t MS)


25


Table
4
.
D
escription
of
the high supplementary feeding 1 farm system
.


Description

Ba
seline

Cow numbers

310

milkers

Cow weight

550
kg

Milk production

6
,500L/cow or
21.7

L/day

Heifer replacement rate

25% or 78 heifers/year

Farm size
-

milking area

125 ha at 2.5 cows/ha with 40% irrigated

Farm size
-

heifer area

100 ha at 1.5 heifer
s/ha

Total farm size

225 ha

Annual diet for milkers

1

3.0

t pasture &
2.4

t grain

Diet of
5.4

t DM,
74.4
% DMD,

ME 10.
9

MJ/kg DM & CP
16.4
%



Diet for
replacement stock

70% DMD, ME 10.2 MJ/kg DM & CP 16%

Total N fertiliser applied
2

41
.3 t

Grain im
ported

745 t DM

Diesel

15,000

L

Electricity
3


8
5
,000

kWh

1

see Appendix
5

for diet quality calculation


2
N fertiliser based on 150kg N/ha
.annum

for dryland pastures, 300 kg N/ha
.annum

for irrigated
pastures
;

3
Electricity based on dairy consuming 0.
67 kWh/cow for 365 days and irrigators consuming 8
kWh/ha.day for 150 days on a 6 day rotation


Total farm GHG emissions for the HSF

1

system was
2,118

t CO
2
-
e/farm or
14.0

t CO
2
-
e/t MS, with enteric
methane

production equating to
7.
5

t CO
2
-
e/t MS or ~
54
% of the
total farm emissions. As a percentage of the total farm GHG emissions, pre
-
farm, on
-
farm
carbon dioxide
, on
-
farm
methane

and on
-
farm
nitrous oxide

emissions were
16.7
,
7.
9
, 54.9 and 20.5
%, respectively

(Figure
5
)
. Assessment of the on
-
farm liabi
lity GHG
emissions showed that
CPRS

farm GHG emissions was 1,596
t CO
2
-
e/farm or
10.6

t
CO
2
-
e/t MS, with enteric
methane

~
71
% of the
on
-

farm
CPRS

emissions
.



26



Figure
5
.
The intensity of greenhouse gas e
missions from the high supplementary feeding
1 farm system calculated as
pre
-
farm (

),

on
-
farm carbon dioxide (

)
,
on
-
farm methane (

)

and on
-
farm nitrous oxide emissions (

)
, total farm (

; t CO
2
-
e/t MS)

and that liable under a
carbon pollution reduction scheme
(

; t CO
2
-
e/t MS
)
.

The percentage of total farm
emissions from
each source s
hown as the
enclosed pie chart
.


The HSF

2 farm

system consist
ed

of 3
33

milkers,
with
each

cow

producing
6,
0
00L/cow.lactation from a diet that was ~ 5
6
% pasture, 26% grain and 1
8
% maize
silage. As the overal
l diet quality was lower for this

diet compared
to the
HSF

1 diet
,
this
equated to a reduction in
milk
production

from 6,500 to 6,000L/cow.lactation. To
maintain a total farm milk production of 2 million litres, we increase
d

her
d size to 333
milkers (Table
5
).













0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
Fertiliser
Herbicide
Grain
Other feed sources
CO2 -Energy
CH4 - Enteric
CH4 - Effluent ponds
N2O - Effluent ponds
N2O - N Fertiliser
N2O - Dung & urine
N2O - Indirect
Tree plantings
Total farm
CPRS liability
GHG emissions (t CO
2
-e/t MS)


27


Table
5
.
D
escription
of

the
high supplementary feeding 2 farm system
.

Description

Baseline

Cow numbers

3
33

milkers

Cow weight

550 kg

Milk production

6,
00
0L/cow or
20.0

L/day

Heifer replacement rate

25% or
83

heifers/year

Farm size
-

milking area

125 ha
at 2.
67

cows/ha with 40% irrigated

Farm size
-

heifer area

100 ha at 1.
67

heifers/ha

Total farm size

225 ha

Annual diet for milkers

1

3.0 t pasture
, 1.4 t grain and 1.0 t maize silage


Diet of 5.4 t DM,
71.7
% DMD,


ME
10.5

MJ/kg DM & CP
16.8
%

Diet for

replacement stock

70% DMD, ME 10.2 MJ/kg DM & CP 16%

Total N fertiliser applied
2

41
.3 t

Grain and silage imported

466 & 365 t DM

Diesel

20
,000 L

Electricity
3


91
,000 kWh

1
see Appendix
5

for diet quality calculat
ion


2

N fertiliser based on 150kg
N/ha
.annum

for dryland pastures, 300 kg N/ha
.annum

for irrigated
pastures
;

3

Electricity based on dairy consuming 0.67 kWh/cow for 365 days and irrigators consuming 8
kWh/ha.day for 150 days on a 6 day rotation


Total

farm GHG emissions for the HSF

2 far
m

system was
2,290

t CO
2
-
e/farm or
15.3

t
CO
2
-
e/t MS, with enteric
methane

production equating to
8.0

t CO
2
-
e/t MS or ~
53
% of
the total farm emissions. As a percentage of the total farm GHG emissions, pre
-
farm,
on
-
farm
carbon dioxide
, on
-
farm
methane

and

on
-
farm
nitrous oxide

emissions were
17.7
, 8.
5
, 53.8 and 20.0
%, respectively

(Figure
6
)
. Assessment of the on
-
farm liability
GHG emissions showed that
CPRS

farm GHG emissions was 1,690
t CO
2
-
e/farm or
11.3

t CO
2
-
e/t MS, with enteric
methane

~
71
% of the
on
-

farm
CPRS

emissions
.




28



Figure
6
.
The intensity of greenhouse gas emissions from the high supplementary feeding
2 farm system calculated as
pre
-
farm (

),

on
-
farm carbon dioxide (

)
,
on
-
farm methane (

)

and on
-
farm nitrous oxide emissions (

)
, total farm (

; t CO
2
-
e/t MS)

and that liable under a
carbon pollution reduction scheme
(

; t CO
2
-
e/t MS
)
.

The percentage of total farm
emissions from
each source shown as the
enclosed pie chart
.



Total mixed rati
on feeding system

While the number of dairy farms in Australia that would be classed as a TMR farming
system is small, there is a very strong likelihood that as irrigation water becomes
increasingly more difficult to a
c
quire and forage production becomes i
ncreasingly more
expensive due to increasing fertili
se
r and other costs, farmers will try to achieve as much

milk
production as possible out of their forages and purchased feeds. While th
e dairy
industry will never progress

down the path of fully housed f
ree
-
stall stanchion style farms
found in

North America and Europe, we will start to see more farms consolidate their
herd into a small area around the dairy facilities and cut and carry most
and/
or all of the
on
-
farm grown forages to the
milking
herd.


T
his is evident from the two commercial farms that we have modelled in this report. The
first farm
(TMR 1)

was established when
the dairy

business
relocated from the south
coast of NSW to the central west of NSW, with funds from the
Dairy Structural
Adjust
ment Scheme deregulation payments.

They constructed

an
enclosed
free
-
stall
feeding
system to feed their milking herd
year round, with access to loafing paddocks
when not feeding or milking.

0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
Fertiliser
Herbicide
Grain
Other feed sources
CO2 -Energy
CH4 - Enteric
CH4 - Effluent ponds
N2O - Effluent ponds
N2O - N Fertiliser
N2O - Dung & urine
N2O - Indirect
Tree plantings
Total farm
CPRS liability
GHG emissions (t CO
2
-e/t MS)


29


The TMR 1

farm
systems consisted of year round milking of
300
c
ows
, with ~ 50 dry
cows

maintained on
-
farm while
the
replacement stock
were

agisted off
-
farm from
weaning age to just prior to calving.
This farm
produce
d

the bulk of their forage on a
second
property

3 km from the home farm
. However, the
biggest proport
ion of the
milking herds’ diet
wa
s
supplied from off
-
farm sources.
To assist in comparing farm
systems, we re
-
introduced the replacement stock on
-
farm.
Farm details are shown in
Table
6.


Table
6
.
D
escription of the total mixed ra
tion 1 farm

system
.

Description

Baseline

Cow numbers
-

milkers

300 milkers

Cow weight

700

kg

Milk production

11,500
L/cow or
38.3
L/day

Dry cows


50


Heifer replacement rate

33
% or
110
-
120

heifers/year

Farm size
-

pasture/cropping

area

100

ha

at 3.0

cows/ha

with 50
% irrigated

Farm size
-

dry cow area

50

ha

Total farm size

1

220

ha

Annual diet for milkers

2

2.85 t DM ryegrass & sorghum silage,
2.25 t DM

grain, 2.1 t DM
by
-
products

&
0.3 t DM cereal hay

Diet of
7.5

t DM, 7
2.0
% DMD,


ME 10.5 MJ/kg DM
& CP 16.
0
%

Diet for dries

65
% DMD, ME
9.4

MJ/kg DM & CP 1
4
%

Diet for replacement stock

70% DMD, ME 10.2 MJ/kg DM & CP 16%

Total N fertiliser applied

52

t

Grain, silage and hay imported

800, 300 and 200 t DM

Diesel