Life cycle assessment (LCA) of Dairy and beef cattles

Student: Mohamed Sarhan
Agris Mundus [Academic Year 2013-2014]

Supervisor: Prof. MOULIN Charles-Henri
Montpellier, SupAgro

Table of Contents
1 Introduction…………………………………………….….……..1
2 Whole farm GHGs emissions models…….…….………3
*

GHG EMISSIONS FROM BIG
AND SMALL RUMINANT DAIRY
AND BEEF PRODUCTION
SYSTEMS IN A LIFE CYCLE
ASSESSMENT (LCA) STUDIES
Supervised by: Prof.MOULIN
Charles-Henri

2.1 Using models for scientific research………………..3
2.2 Choice of Functional unit…….………………..…….….4
2.3 Standardization of Methodology…….……...........4
2.4 Comparison of LCA Studies…….….………..………...5
2.5 Animal Performance for combined beef and
……….milk production systems…………………….…..….….6
3 The effect of production intensification……………..7
3.1 …...Beef production systems……….…………………...7
3.1.1… Pasture and feedlot based …………….………….7
3.1.1.1 System Performance Assessment..…..…….…7
3.1.1.2 Environmental impact of farming system….9
3.1.2 …Pasture, Mixed and zero-grazing based…….10
3.1.2.1 System Performance Assessment..…..….…..10
3.1.2.2 Environmental Performance Assessment…10
3.1…….Conclusion………………………………..………………11
3.2 .……Milk production systems………….…..………..12
3.2.1.… Organic vs. conventional farming..…..….…..12
3.2.1.1..Environmental impact assessment…………..13
3.2.2.....Intensive vs. extensive farming………………..14
3.2.3.....Mitigation strategies………………………………..15
4 Conclusion…………………………………………..……………..16
5 Appendix …………………………………………..……………..17
5.1. Assembled LCA investigated studies………………17
5.2. Total GHGs CO2-eq of milk results…………….……20
5.3. Total GHGs CO2-eq of meat results…………..……21
5.4. A Whole farm GHGs models…….…………..……….22
6 References …………………………………………..…….…….25

*

http://www.econlife.com/climate-change-livestock emissions

Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems

Global Greenhouse gas Emissions in animal production: towards an
Integrated life cycle sustainability assessment from Ruminant Farming Systems

Abstract
The objectives of this review were to evaluate the environmental impacts of the greenhouse gas (GHG)
emissions and emissions intensity (Ei) for the small ruminants, Dairy and beef cattle livestock production
systems using the life-cycle assessment (LCA) method with a system boundaries from “Cradle-to- farmgate” and to promote the other capability of this internationally accepted approach nowadays in the
agriculture world to determine weaknesses and robustness and/or the performance of the livestock
production system adapted in any regions or areas of examination. This aim was illustrated using results
from LCAs in the literature and from a pilot study of different production systems. The emissions were
estimated using a whole farm GHGs models, based on the Intergovernmental Panel on Climate Change
(IPCC) methodology with a yearly time-step. By recognizing different farming systems for ruminant
species (i.e. pasture, mixed, and zero grazing). with specific reference to recent published models,
outline general conclusions from application of these published models, and describe some
limitations and risks associated with these approaches. Certain models were adapted (i.e. an economic
optimization model, an environmental assessment model) in which it considers all significant CH4, N2O,
and CO2 emissions and removals on the farm and off-farm emissions of N2O derived from nitrogen applied
on the farm. This review however, shows that LCAs of different case studies currently cannot be compared
directly. Such a comparison requires further international standardization of the LCA method. Nonetheless
a recent collective global LCA estimated the GHG intensity of ruminant supply chains to produce 5.7
gigatonnes CO2-eq per annum representing about 80% of the livestock sector emissions. Enteric Methane
CH4 was the largest contributing source of GHG accounting for 47%. N2O from soil and deposited manure
accounted for a further 24%, while LUC is estimated to contribute 9% of the sector’s overall GHG
emissions. However, LCAs should be performed at a large number of practical farms for each production
system of interest. Application of LCA on practical farms, however, requires in-depth research to
understand underlying processes, and to predict, or measure, variation in emissions realized in practice.
Keywords: life cycle assessment, ruminant, greenhouse gases, livestock, climate change, enteric methane,
Whole farm modelling, IPCC, Beef production systems, Dairy production systems, Systems analysis
1. Introduction
The global livestock industry is charged with providing sufficient animal-source foods while improving
the environmental sustainability of animal production (1). The livestock sector represents a significant
source of greenhouse gas (GHGs, Fig.1) emissions worldwide, generating carbon dioxide (CO2) which
is released from combustion of fossil fuels to power machinery, from burning of biomass, and from
microbial decay related to, for example, changes in land use or in crop management and can be sequestered
by transforming arable land into permanent grassland (7), methane (CH4; i.e., enteric CH4) is produced
when organic matter decomposes in oxygen deprived conditions, for example, during enteric fermentation
(especially in ruminants) and storage of manure (8) and nitrous oxide (N2O) is released during microbial
transformation of nitrogen in the soil or in manure (i.e. Nitrification of NH4+ into NO3-, and incomplete
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DE nitrification of NO3- into N2) as
well as during nitrate fertilizer
production (9). The sector faces the
difficult challenge of having to reduce
its GHG emissions while responding
to a significant demand growth for
livestock products which will be
particularly strong as it appears meat
and milk in 2050 is projected to grow
by 73 and 58 percent, respectively,
from their levels in 2010 to supply the
global population which will grow
from 7.2 billion today to 9.6 billion in
2050 With emissions estimated at 7.1
gigatonnes CO2-eq per annum,
representing 18% of human-induced
Figure 1.Main emission pathways of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) GHG emissions (3). Current decisions
related to livestock production (Boer et al., 2011)
on GHG mitigation in animal
production, therefore, are hindered by the complexity and uncertainty of the combined effect of
GHG mitigation options on climate change and their relation with other aspects of sustainability
(5).Using a life cycle assessment (LCA) approach and accounting for land-use change (LUC), (6) it is
estimated that the livestock sector contributes about 18% of the total global anthropogenic GHG emissions
in which Feed production and processing, and enteric fermentation from ruminants are the two main
sources of emissions, representing 45 and 39 percent of sector emissions, respectively. Manure storage
and processing represent 10 percent in which Beef and cattle milk production account for the majority of
emissions, respectively contributing 41 and 20 percent of the sector’s emissions (13).
Such a LCA enfolds the entire farming system, accounting for all changes in GHG emissions arising
from a prospective mitigation practice. Often, reducing, GHG emissions in one part of a farming system
can lead to an increase in emissions from another sector; a whole-systems approach avoids potentially illadvised practices based on preoccupation with a single GHG (17). However, LCA also presents significant
challenges, particularly when applied to agriculture. First, the data-intensive nature of the method often
requires simplification of the inherent complexity of food supply chains (21). A second difficulty lies in
the fact that variation in methods and assumptions such as the choice of system boundary, functional units,
and allocation techniques can affect results (4). Still The major advantage of conducting a farm-level LCA
is the ability to evaluate the impact of changes in farm management in terms of the GHG intensity of meat
and milk production and A major disadvantage of conducting an LCA focused only on GHG is that the
analysis does not consider other potential benefits of maintaining ruminants on grasslands (15).
This paper makes a global comparison of the consequences of different production systems practices
adapted while pointing out their environmental footprint. However, it shows that LCAs of these different
case studies currently cannot be compared directly as mentioned previously due to different
characteristics, assumptions, approaches, functional unit, and algorithms used in calculations. This
discrepancy among the different analyses is a major problem because one of the main applications of
the LCA is benchmarking and also because one of the main steps of an LCA analysis is a comparison
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with the results obtained by other authors. However, this is only possible if there is a common method or,
at least, a common approach to their interpretation. Nonetheless, the comparison we can make is between
Beef, meat, and dairy production. In this way, it will determine the comparison of beef production systems
(pasture, feedlot) and (pasture, mixed crop-livestock, zero-grazing) for lamb meat. Besides milk
production systems (organic, conventional) and (intensive, extensive) farming. Finally it gives some
spotlights of the mitigation strategies that could be implemented to reduce Ei and overall GHGs emissions.
2. Whole farm GHGs emissions models
Whole farm GHG emissions models (Fig.2) may be categorized
as systems analysis models or LCA models not only to facilitate
investigation of implications of alternative production strategies
on GHG emissions for the farming systems (24) and, developing
and assessing mitigation policies to reduce GHG emissions from
livestock system (27a). But also it ensures possible interactions with
other GHGs are taken into account (34). Whole-farm models are often
developed through the combination of existing sub models, which Figure 2.Basic elements of modelling GHGs in a
whole-farm approach (Schils et al., 2007)
may have different underlying simulation methodologies with respect
to GHG, emissions can be calculated with emission factors, comparable to the IPCC1 methodology, or
simulated with mechanistic (sub) models (24). While the objective of the IPCC guidelines is to model
national level emissions and not to determine emissions or assess strategies to reduce emissions on a
lower scale such as at the farm level (35) and, as such, variations that arise due to differences in
farming systems and regions are not considered. However, these guidelines developed and published
by IPCC will continue to be the primary methodology for reporting national emissions, noted that
whole farm modelling approaches should not be seen as a replacement for the IPCC methodology
(22). In fact a whole farm GHG emission model provide the most robust and comprehensive approach
to developing and implementing effective strategies and to overcome limitations with respect to this
national and sectorial approach and enables all emissions associated with production of livestock
products to be calculated (27a). And, typically, this involves a cradle-to-farm gate approach (Figure.3).
2.1 Using models for scientific research
Studies reviewed confirms that numerous GHGs models have been successfully developed in a way
that differs according to the objectives of the raised research question. Anyhow they could be vary from
a so-called ” Virtual farm conceptualization” model (e.g. HOLOS) (36) in which its strength lies in linking
farm characterization and activities to algorithms (e.g. IPCC Tier 2 emission factors) besides enfolding
different animal production systems (e.g. reproduction  initial growth feedlot) . In addition they could
be a “whole farm economic simulation” model (e.g. Moorepark Dairy System Model or MDSM) (37) to
calculate profitability of dairy farms.in which it mainly operates by selecting GHG emission factors data
obtained from the results of experiments of studies completed in relevant temperate grassland dairy
systems conducted in Moorepark to be integrated using the GHG model and this approach is hereafter
referred to as LCA-refined. Eventually whole-farm GHG models was designed to quantify the internal
flows of carbon (C) and nitrogen (N) on dairy farms and provides assessments of emissions from both the
production unit and the pre-chains (e.g. Farm GHG) (12). These internal flows are represented as flows
1

The Intergovernmental Panel on Climate Change (IPCC) (33).

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between compartments in the farm system. The model also explicitly includes all C and N losses except
for soil respiration and N2 emissions from soils. The energy use is calculated for each compartment and is
converted to pre-chain emissions of CO2 and other GHGs. The pre-chain emissions are the emissions
associated with imports of production goods to the farm. While the presented framework for a whole farm
approach contributes to a transparent evaluation of the effectiveness and efficiency of mitigation strategies
(38). Continuous development of models will allow researchers to explore feedbacks within systems that
most research cannot investigate due to limitations in measurement equipment, time, and workforce (36).
2.2. Choice of functional unit
In most LCAs of agricultural products, the functional unit (FU) has been initially developed to assess
environmental impact defined as the mass of the product leaving the farm gate (24). Scientists working
on the Carbon footprint (CF) and GHG from livestock production systems studies agree on the importance
of choosing a (FU) of GHG emissions evaluations per unit of meat or milk produced for a given period of
time rather than per animal unit, regardless of the quantity of product produced or the time required to
produce that product (41). Because of its consequences for results interpretation as an essential concept to
eliminate contradiction of the results (40). In this review the majority of studies describe emissions on (a
/kg live weight or carcass weight) for beef production systems. The two exceptions to this are studies of
who expressed output as bone-free meat and protein (28) (39). While for the dairy farms there are many
units which can be used for the FU for the emissions (e.g., L of milk, Kg of protein, kg of fat and protein
corrected milk (FPCM) and Kg of Energy Corrected Milk (ECM) (20) (24) (42).
2.3. Standardization of Methodology
The CF of livestock production is difficult
to define; considerable discussion exists as
to the ideal methodology and metric for its
quantification. Within academia, this is
understandable due to the intent to validate
models and methodologies to search for
improved knowledge (41). However,
Decisions need to be based on sound
estimates. It is therefore important that the
industry supports the development and use
of more precise methods to calculate
national inventories and the extension of
inventories to developing countries not
Figure 3. Flowchart of the ‘cradle to farm-gate’ (Boer et al., 2003)
currently signatories to emissions reduction obligations. In the same way the industry should press for
standardization of life cycle analysis methodology to overcome the confusion that currently exists (40).
Comparative studies that provide insight into the relative impact of systems or production practices and
thus the possibilities to improve the delta (i.e., the difference between the systems) may be far more
valuable. This is especially pertinent to CF quantified via LCA studies (e.g. the beef production in the
United States, Canada, Sweden, Australia, and Japan (Table 1), However, variation in methodology,
boundaries, and time points for each system render direct comparisons unreliable. Therefore the need for
a coordinated international methodology is very vital for LCAs studies.
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2.4. Comparison of LCAs studies
Much of the difference among LCA studies can be partly explained by inherent differences among
the production systems investigated [4]. In the contrary [15] emphasizing that the range in GHG
intensities reflects not only differences among farming systems, but also different assumptions,
approaches, and algorithms in calculating emissions, so direct comparison among studies is not
recommended. Nevertheless, it is possible to draw some general conclusions from these analyses.2As
though an overview of recently published studies of GHG emissions from beef and dairy production
systems is selected in (Tables 2) and, a schematic diagram of the hotspots of all these analysis is
presented in (Fig.4). However, not all of these impact categories are considered. Only the impact
categories which are typically analyzed in this review are: Global Warming Potential, climate change,
Non-renewable Energy, Eutrophication potential, Acidification potential, Carbon footprint, Cumulative
Energy Use. With a system performance assessment evaluating the production system by testing different
scenarios. Consequently there are 16 studies for beef production systems , which do not include
Research question

(CF)10
(PEU)9
(CEU)

(AP)

Economic
optimization
model

FU

12

(SW)8
Results
Interpretation
11
of GWP
parameters

LCIA 7

Scenarios for

1

6

(EP)5
(NRE)4

Verification
of model
components
Sensitivity
analysis

Land occupation

Environmental
Performance

Co-product
Evaluating
financial or
social costs

Model2

Animal, Farm
Management
Pastoral land,
Soil C balance

System
Performance

Evaluating
Production
system

Apportion
resource use
of multi-output
systems

Quantifying
production

Comparison with
previous studies

Model Validation

Soil erosion

Carbon
Sequestration

On/Off- pasture

Intensifying
production

Feedlot, N
fertilizer

Figure 4. A schematic overview of the Hotspots of the LCA analysis (Sarhan, 2013)

studies describing emissions from dairy calf to beef production systems which are generally much
lower than those in beef cow systems as a result of cow GHG emissions being mostly allocated
to milk production for dairy systems . In many cases, the approach used was to integrate a number
of models which were then utilized to complete various components of the analysis required. For
example, [13] used a farm simulation model, a feed formulation program and a nutrient budgeting
model simultaneously to investigate New Zealand cattle farming systems. Similarly, [1]; [6]; and [8]
used a multiple model approach to quantify GHG emissions from beef production systems. While
For dairy systems, there were studies coupled two or more models for different aspects of the
analysis [37] and [42] applied a whole farm GHG model to investigate European dairy farm systems
1

Research question for either (quantification, comparing between different emissions inventories); 2 Develop certain model
independently or integrate sub-models together; 3 Capture, compute data to quantify actual GHGs emissions from national
inventories or other literature; 4 Non-renewable Energy; 5 Eutrophication potential; 6 Acidification potential; 7 life cycle impact
assessment ; 8 Solid Waste; 9 Primary Energy Use; 10 Carbon footprint; 11 Global Warming Potential; 12 Cumulative Energy Use

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in various regions, while [20] developed a farm level accounting method to model Dutch dairy
research farm systems. Most models were single year whole farm system studies with the exception
of [1] who adopted a multi-year (8year) approach using the lifespan of a breeding female as the time
reference, [14] is more likely to yield a representative national value for GHG emissions from English beef
production systems given the industry level farm data used. In contrast, the approach of [1] can facilitate
investigation of implications of alternative production strategies on GHG emissions for the farming systems.

2.5 Animal Performance for combined milk and meat production systems
Improvements in live weight gain for Irish beef production
systems based on use of finishing bulls compared to steers
reducing emissions by 6 and 5%/kg beef was founded by
[4]; [5] (Fig.5) to be an important mitigation strategy,
respectively. [10] compared grain fed feedlot systems, with
high levels of animal performance, with grassland pastoral
systems and found that grain fed systems had3 higher
emissions while [12] found the opposite. However, the
studied systems according to [10] were with different
regions, breed types and, apparently, different management
1
systems (intensive US feedlot system and a traditional Figure 5. Implications of level of animal performance
African pastoral system) and also the technical efficiency making it is difficult to draw definitive
conclusions where the methane intensity of the pastoral mode is much larger because of the lower
productivity of these systems. In the contrary [1]; [6]; [8] and [9] were conducted in the context of the
3 components of cow calf to beef production systems being, cow calf, stocker (i.e., the period
between weaning and start of finishing), and the feedlot. In all cases, the cow calf phase had the
highest emissions/kg product largely due to the relatively higher emissions from beef cows
compared with younger non-lactating animals. In these studies, the feedlot phase had the lowest
emissions with the stocker phase being intermediate.
In accordance with these findings (Flysjö et al.
2012) in the study of the link between milk and beef
production in LCA and CF studies of milk it is
assumed that the meat from both the culled dairy
cow and the raised dairy calf replaces beef meat
produced in a cow-calf system (Fig.6). However,
The production of 5 g meat from a cow-calf system
in Europe emits 0.14 kg CO2e, which is more than
the difference between the CF of the two production
systems (1.13 kg CO2e for the organic system and
1.07 for the high yielding conventional system) this
2
could be explained maybe because dairy farms with Figure 6. Product flows during a lifetime of a dairy cow in Denmark
high meat production can deduct a high level of CO2e from avoided beef production in less climate
1

(live weight gain; g/d) on GHG emissions for Irish suckler beef production systems (27a)
(number of calves, tonnes of milk (energy corrected milk (ECM)) and meat (carcass weight (CW)) and percent of replacement
and surplus calves for organic (O) and high yielding conventional (C) milk production systems) taken from (Flysjö et al., 2012)
2

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friendly cow-calf systems (11). In general variations in animal performance levels on GHG emissions
from dairy production systems is somewhat less clear, although improved milk performance/cow
can reduce emissions [4], However, if a breeding strategy aimed at improving lactational
performance resulted in impaired fertility and, consequently longer calving intervals and higher
culling rates, overall emissions may increase (23). This is supported by (12), who found that a
reduction of 10% in replacement rate, combined with a strategy to sell surplus heifers at birth,
reduced total emissions by 10%. It is apparent that a balanced breeding strategy optimizing milk
production capacity while minimizing the number of non-milk producing cattle is important with
regard to minimizing emissions from dairy production systems. Nonetheless, [11] recommend
combined dairy and beef systems as a means of reducing the impacts of calf production, since dairy cows
produce both milk and calves whereas beef cow/calf herds are maintained for calf production only. This
may be due to the explanation presented by (29) that the cow–calf phase is the dominant contributor to
most impact categories regardless of finishing strategy. This is largely attributable to the low fecundity of
cattle compared to other species such as pigs and chickens. Since a cow will produce at most one calf per
year, a mature cow is maintained (along with bulls and heifers) for every marketed animal.
3. The effect of production intensification
The GHG related to both pastoral and feedlot production systems are compared with other
environmental impact indicators both quantitatively and qualitatively with reference to their potential
usefulness in assessing livestock systems [10]. And so LCA research has been used to account for multifunctionality of sheep farming systems (SFSs) in the CF of lambs in the Mediterranean in Spain [46], or
to examine GHG intensity of conventional and organic milk production in Sweden [11], Ireland [4], and
the relative importance of the cow–calf and finishing phases for the farm-gate [10]. And the environmental
impacts of Japanese beef production [7].While [9] investigated the influence of management strategies on
GHG emissions in conventional beef production in the US.
3.1...... Beef production systems
To examine the characteristics of LCA on meat production studies is difficult because of the strong
discrepancies between them (Table 3). The main reason is the different methodologies adopted. Which
explains the difficulty to explain the variability of results. However, other variables were considered:
production system, management practices, mitigation strategies.
3.1.1... Pasture and feedlot based beef production systems
3.1.1.1 System performance assessment
4

[8] from the Upper Midwestern US who tried to evaluate four
important measures of environmental performance (CEU,
ecological CF, GHG emissions, and EP) for three distinct beef
production strategies when weaned calves are either: sent
directly to Iowa feedlots; sent to out-of-state small-grain (wheat
and other) pastures (back grounded) then finished in Iowa

1

Figure 7. GHG/kg beef live weight for feedlot and
grass based 1

Finishing systems in the United States assuming either equilibrium conditions for soil organic C (grey bars) or 0.12
kg C sequestered/ha/yr for cow calf systems and 0.4 t C sequestered/ha/yr for intensive grazing (black bars) (30).

7|Page


feedlots; or finished on pasture and hay in Iowa. [8] Reported that GHG emissions per unit of beef were
greater in pasture-finished systems (Fig.7) than in feedlot systems. In the contrary [41] explained that this
result seems intuitively incorrect for two reasons, the first one because a conventional system that finishes
animals on corn-based diets grown with significant fertilizer inputs, transports both feed and animals
across the country, and houses animals in confinement seems to have an intrinsically greater
environmental impact than a grass-finishing system and the second one [43] demonstrated that the results
from a biological viewpoint are easy to explain though growth rates are considerably less in animals
finished on grass, and it is difficult to achieve heavier slaughter weights; therefore, grass-finished cattle
are usually slaughtered at around 486 kg at 679 days of age, compared with 569 kg at 453 days of age in
a conventional system. While the intensification of the beef production of typical (NZ) sheep and beef
farming systems in the study of (47) were evaluated by feeding maize silage (MS) or applying nitrogen
(N) fertilizer, on two farm types differing in the proportions of cultivatable land to hill land (25% vs. 75%
hill) and incorporating a beef feedlot into each of the farm types. [13] Found that Feeding MS or applying
N fertilizer substantially increased the amount of beef produced per ha because MS or N helps the farmer
to increase the utilization of pasture grown on farm. While intensifying production was also associated
with increased total N leaching (from 11 to 14 kg N/ha) due to small annual additions of N fertilizer (<50
kg N/ha/yr) applied in autumn and late winter and GHG emissions (from 3280 to 4000 kg
CO2e/ha).although, Feeding MS resulted in lower environmental impact than applying N even after taking
into account the land to grow the MS. As a consequence the beef feedlot reduced environmental emissions
per kg of beef produced but considerably decreased profitability due to higher capital, depreciation, and
labor costs [13].
In Ireland according to this study (27b) estimated the potential effects of changing management to attain
reductions in GHG emissions from a simulation of different selection of production options or scenarios
by scaling a FU of live weight per year (kg CO2 kg LW yr-1) the suckler-beef system was estimated to
produce 11.26 kg CO2 kg LW yr-1 and the cow phase added a significant amount to emissions and had the
greatest impact when attenuated. In terms of supplementary management strategies for GHG reduction,
the broad range of supplement combinations evaluated yielded no major reduction within a grassdominated system. Besides the potential to reduce GHG emissions allocated to beef production by over
30% if management moves away from using suckler herds and source cows that are essentially redundant
except for the production of the beef animal. The difficulty with moving to this more efficient scenario is
that the quality of beef produced may be much lower than that achieved by the specialist beef breeds [4].
In the mean while [10] expressed GHG (Table 4). Environmental impacts results (per kg beef)
emissions indices in climate change
compared with market values per unit of
beef costs, by taking the form $/kg CO2
based on the approach of biophysical
capital alteration introduced by (45) which
means an ecosystem’s ability to use solar energy to maintain the biosphere’s structure and function. (Table
4), summarizes obtained convergent results of comprehensive GHG emissions analysis and the
biophysical capital alteration approach, with environmental impacts of the feedlot system 1.8 times greater
than that of the pastoral system in both approaches. [10] Concluding that the conventional pollution
assessment has tended to find that intensive agriculture is more polluting because of N runoff and
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emissions related to fuel and fertilizer inputs for stock feed. While rangeland and pastoral agriculture tend
to involve lower levels of conventional pollution. In contrast, most GHGs emissions analyses completed
in recent years assume that the emissions intensity related to traditional agriculture is much higher than
the intensive form, because lower productivity translates into higher methane emissions per unit of
product.
3.1.1.2 Environmental impact of farming system
Based on this research (44) demonstrated that the Japanese
black cattle (Wagyu) are fed for a longer period both in the
feedlot and/or pasture to obtain a higher quality beef (e.g. higher
marbling score). Hence [7] investigated the environmental load
of beef-fattening system in japan and found that the major
source in the impact category of GWP was (2,851 kg of CO2 e)
due to enteric CH4 emissions, AP from cattle wastes and EP due
to ammonia emissions from animal management (i.e., cattle
Figure 8. Effects of feeding length on each
environmental impact category
barn, cattle manure in the stage of waste treatment) and treated
the matter of production intensification from the point of view of the feeding length because the feed
production had the highest impact on the system. Therefore [7] concluded that shortening feeding length
had fewer environmental impacts in all categories taken into account in this study (Fig.8). In such a way
that shortening feeding length by 1 mo decreased the environmental impacts of AP and EP by 4.5%, and
decreased the impacts of GW and CEU by 4.1% reduction. The quantities of this emission and the energy
use were mainly due to the feed intake of cattle, which increases until 17 month of age in response to the
growth of cattle and declines to 65% of the maximum in the last 6 mo of fattening. However, a longer
feeding length makes cattle heavier, causing an increase in beef yield [7]. While the shorter feeding length
(by 2 mo) had a smaller environmental impact per unit weight of beef (e.g. feeding cattle until 28 and 26
mo of age were 20.6 and 19.7 kg of CO2e) and so Defining the FU as 1 kg of beef provides an answer for
this problem because in this study FU was defined as one animal which proves the necessity of fixing FU
(31).5GHG emissions was evaluated through computer (Table 5). Annual GHG emissions in CO2e per product 1
spreadsheets scenarios from U.S. beef and dairy
livestock systems from nine locations (48) and the
Cattle beef systems of the cow-calf herd emitted the
most (Table 5) due to the smaller CH4 coefficient and
feedlot cattle the least enteric CH4 and N2O per unit
product. However, stocker cattle emitted the most and
cow-calf the least total GHG CO2e per head. CO2 emissions per unit product were the least for the cowcalf and greatest for the feedlot scenarios due primarily to the energy expended in the cultivation and
processing of grains and transportation of grain and cattle [9].
These final results were obtained also on a Canadian simulation studies simulated over an 8-year
production cycle in western Canadian farms (17). Where the cow–calf system accounted for about 80%
of total GHG emissions and the feedlot system for only 20% and about 84% of enteric CH4 was from the
1

a: Product is kg live weight gain; b: Product is kg milk; The "stocker" segment was comprised of cattle between weaning and
feedlot placement; (Mean±SD) for US livestock systems

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cow–calf herd (Fig.9), mostly from mature cows. The
lower CH4 emission from this system is due mainly to its
relatively brief duration and, to a lesser extent, to the use
of grain-based finishing rations. Despite all these
findings, the authors demonstrate how these systems can
have many ancillary environmental benefits, by affording
wise use of grazing and forage lands. Such lands not only
preserve soil C reserves, thereby withholding CO2 from
the air, but also have many other ecosystem services
including the conservation of biodiversity, water quality,
wildlife habitat, and aesthetic value [1].

Figure 9. Source of GHG emission CO2e for a beef farm

3.1.2... Pasture, Mixed, and Zero-grazing beef production systems
3.1.2.1 System performance assessment
[9] Studied the adaptation of the production systems required
to maximize revenue in response to changes in economic scale
(26). For instance Farm D: continued with the same number of
calving’s and the same intensive beef production system (17month-old young bulls). However, not all cull cows are
fattened, as 57% are sold as store animals and the fattened
heifers are all sold at 31 months of age, these herd management
adjustments result in a 3% drop in total beef production and free Figure 10.Farm income, NRE consumption, and GHG
up 3.6 ha of land for crop farming. Cattle revenue therefore falls
emissions for 2012 in comparison to 2006
2% (-1885 euros) while cash crop revenue surges 62% (+7410 euros). Thus there is a 4% increase in
overall farm revenue. In the contrary Farm E: mirroring farm D, the economic optimization to the 2012
time horizon cuts back on meat production (-11%) in favor of cash crops. The number of calving’s is kept
stable, but only 25% of cull cows are fattened and the males are sold 6 months earlier than in 2006. All
the scenarios (Fig.10), run highlighted, system adjustments designed to minimize the drop in income %
(except at farm E which enjoys greater flexibility due to its available tillable area), have only a very limited
impact on NRE consumption and GHG emissions. Besides Fuels and lubricants were the main factors of
NRE consumption, followed by fertilizers and farm equipments. Therefore, farms running mixed crop–
livestock systems enjoy greater flexibility to adjust their farming systems than grassland-based farms
enabling them to minimize the drop in income over the timeframe to 2012 (-3%) [9].
3.1.2.2 Environmental performance assessment
While the study of (46) which explored the CF in three contrasting sheep farming systems (SFSs) in
the north-eastern part of Spain, i.e. a pasture-based system, a mixed sheep–cereal system, and an industrial
(zero-grazing) system, accounting both for the production of meat and for the cultural ecosystem services
provided (e.g. biodiversity and landscape conservation). GHGs emission per kg of lamb live weight
without ES allocation among the SFSs was reversed (Table 6) with lowest values for the pasture-based
system (13.9 kg CO2-eq per kg of lamb live weight) and highest for zero-grazing system (19.5 kg CO2eq per kg of lamb live weight) and, with ES allocation GHGs emission per kg of lamb live weight was
highest for pasture-based (25.9 kg CO2-eq), intermediate for mixed (24.0 kg CO2-eq) and lowest for zero10 | P a g e


grazing system(19.5 kg CO2-eq). While the contribution of each gas to total GHGs emissions differed
among SFSs according to the intensification degree, as expected the share of enteric methane emissions
was the largest with contribution around 58–62% to the total emissions. Therefore, these results prove that
when6CF allocated to lamb meat production only according to the intensification level, the emissions per
kg of product decreased, and when accounting for the cultural ecosystem services, GHGs Emissions per
kg of product increased according to their degree of intensification [14].
(Table 6). Total GHGs emissions for the three different production systems 1

While the study of (26) investigated the adaptation of the French Charolaise suckler cattle from different
farming systems (Table 7) analysis with a model assessing GHGs. In overall terms, French Charolaise
suckler cattle farm systems produce 14.3–18.3 tCO2eq/ton of LW produced over 1 year and from 4.77 to
7.00 tCO2eq/ha ”bovine” which are consistent with the results of [4]. Methane emissions specifically and
exclusively released during ruminant farming (enteric fermentation and manure management) are the main
farm-based driver of GWP at around 61% of total GWP. The least GHG-emitting farms per ton of LW
produced were C (0.99 LU/ha) and D (1.38 LU/ha), which fatten all their animals and where cows account,
respectively, for 45% and 46% of the livestock units (LU). Farms B (1.08 LU/ha), and E (1.22 LU/ ha),
which sell all their animals as store cattle generate, respectively, 17.1 and 18.3 tCO2eq/t LW. Farm B is a
grassland-based farm system with few inputs, notably using little N fertilizer, which means it generates
lower N2O emissions than farm E. Because of its calf-to-weanling system and its relatively intensive
production system. Farm E is the most GHG-emitting farm per ton of LW produced because it uses more
inputs than B. Farm A, which produces weaners and fattened females, gives intermediate emission figures
(16.6 tCO2eq/t LW). We can conclude from these results obtained from [9] that the stocking rate and
therefore the quantity of live weight produced per hectare is the main driver of the GHG emissions per ha
for the herd.
(Table 7). GHGs for the years 2006 and 2012. tCO2e/ton of LW produced over 1 year

1

GHGs emissions (CO2-eq/kg) with or without ES allocation for lamb live weight or lamb meat and contribution (%) of CO 2,
CH4 and N2O to total GHGs; ES: Ecosystem services (46).

11 | P a g e


3.1 Conclusion
Based on the study of Environmental consequences of different beef production systems in the EU (25)
The environmental costs per kg EU beef leaving the farm gate were 16.0–27.3 kg CO2e for GWP, 101210 g SO2e for AP, 622-1651 g NO3e for EP, 41.3-59.2 MJ for NRE and 16.5-42.9 m2 year for land
occupation. Of the two fattening categories, fattening based on suckler herds appeared to be less
environmentally friendly than if based on intensively reared dairy calves. In terms of land use, the results
(25) suggested that the dairy bull calf system is better than the suckler herd system for Beef production if
potential land use change and land opportunity cost are taken into account [3]. Nonetheless red meat
production in Australia (32), as well as the comparison with overseas literature, underlines the fact that
varying farm operations can significantly influence the environmental performance of red meat production
with other identified variables (1) the lifetime of the animals (13-33 months), (2) the regime of manure
management, (3) varying IPCC conversion factors for GHGs, (4) effects from the inclusion of LUC, (5)
country-specific impacts from energy production, and (6) animal breed. Whether the reduced enteric CH4
emissions from a grain diet can provide greater GHG savings than those caused by the production of the
grain feed, and whether other environmental impacts from grain production such as Eco toxicity potentials
will become a concern, will eventually and for most depend on the production system practiced [12].
3.2 Milk production systems
To examine the characteristics of LCA on milk production studies is difficult because of the strong
discrepancies between them (Table 2). The main reason is the different methodologies adopted. Which
explains the difficulty to explain the variability of results. However, other variables were considered:
production system, stocking rate, milk productivity, mitigation strategies.
3.2.1 Organic vs. conventional farming
Organic farming is considered much more environmentally friendly than conventional farming
and several LCA studies aimed to demonstrate this hypothesis. Among those studies in the literature
that have been examined there are 3 papers which compared the GHG emitted from a conventional
with an organic dairy farming system. In the case of (20); (51) the GHG emission associated with
organic milk was higher than that associated with conventional milk [16] and in another (28) in the organic
dairy farms, the indirect emissions are lower than in conventional dairy farms, because there is a
reduced use of fossil fuel for the production and transport of concentrates and chemical fertilizers [11].
On the contrary, direct emissions are higher: in particular, CH4 emission associated to 1 kg of milk
increases in organic farms. Cows in organic farms are widely recognized to be less productive than
cows in conventional farms. While results from other studies demonstrated that in the dairy systems
approximately one-half of the total GHG CO2e were from CH4 and one-third from N2O (26) which means
more CH4 than N2O on a per kg milk basis. Mitigation strategies, such as Intensive grazing according to
these study conditions, location and production management system reduced the total number of CO2e per
unit production or live weight gain by approximately 10% in both beef and dairy systems [9]. While the
study (28) Compared GHG emissions on a whole farm or ‘life cycle’ basis for conventional and organic
dairy farms in Sweden. [11] Estimated the conventional Swedish dairy system to produce 0.99 kg CO2e
per kg milk similar to the study (48) of [9].without embodied costs, of 1.09 kg CO2e per kg milk.

12 | P a g e


3.2.1.1 Environmental impact assessment
An LCA was performed on organic (O) and conventional (C) milk production at the farm level in
Sweden (28) with special focus was aimed at substance flows in concentrate feed production and nutrient
flows on the farms. And this study shows that O milk production is a way to reduce pesticide use and
mineral surplus in agriculture but this production form also requires substantially more farmland than C
production. Concerning other environmental impacts, e.g. GWP, AP, and EP, it appears when comparing
the environmental performance of C and O food production systems which have such differences in
material and energy flows, land use must be assessed in both quantitative and qualitative terms. The results
are shown in (Fig.11). It is evident that the use of
fossil fuel is only to a minor extent connected to
GWP impact category. Emissions of N2O
connected to the N cycle on the farms (losses
from soil) and N2O-emissions from synthetic
fertilizer production play a larger part than CO2emissions from the use of fossil fuel. The most
important contributor to GWP in milk production
is, however, CH4. Due to the feeding strategy Figure 11. Contribution to GWP, kg CO2-eq per FU. Time horizon is 100
with a larger share of roughage fodder it is
years for both (O) and (C) milk production in Swedish environment
estimated that methane emissions are 10–15% higher from cows in O production compared with C
production. There seems, however, to be considerable variations in the EF for CH4 from cattle. In the study
of [11], emission data from the Swedish Environmentally Protection Agency (EPA) were used, estimating
methane losses of 155 kg per C dairy cow and year and, because of their larger intake of roughage fodder,
12% higher emissions for the O cows. In the IPCC manual, the methane losses for High yielding cows are
estimated to be considerably lower: 118 kg methane per dairy cow and year [17]. Similarly According to
this Dutch’03study (20) results showed that environmental performance concerning energy use and EP per
kg of milk for O farms than for C farms. Furthermore, higher on-farm acidification potential and GWP
per kg O milk implies that higher ammonia (NH3), CH4, and NO2 emissions occur on farm per kg O milk
than for C milk. Total AP and GWP per kg milk did not differ between the selected C and O farms. In
addition, results showed lower land use per kg C milk (p< 0.001) compared with O milk. Purchased
concentrates was found to be the hotspot in the selected C farms in off farm and total impact for all impact
categories. Whereas in the selected O farms, concentrates was found to be the hotspot in off farm impact
besides roughage. Dutch’03study (20) results were compared with results of two Swedish’01/’02 (52); (51)
studies and one German’89 (53) study and only differences and not actual numbers between the different
systems in the studies can be compared, because of differences in computational methods [16]. And so
the findings were on land use (O higher) and energy use (C higher), product-related AP (in tonnes milk)
and product-related EP (in tonnes milk) was lower for O production agree with all three studies (Table 6)
The similar climate change of C and O milk production agrees with the (52); (51) ; (53) studies. whereas
In the Swedish’01/’02 study O production had the highest emission of NH3 and highest leaching of nitrate
(NO3-) per kg milk, which resulted in a 25% higher product-related eutrophication, but this increase was
not significant compared with C production. And in the German’89 study, the C production had a higher
area-related AP (136 and 119 kg SO2-eq/farm ha) and eutrophication (566 and 326 kg NO3-eq/farm ha)
compared with O production (107 kg SO2 -eq/farm ha; 141 kg NO3-eq/farm ha).
13 | P a g e


3.2.2 Intensive vs. extensive farming
[16] Found that the reduction in milk production per land unit corresponded to a higher CF. the stocking
rate can determine the mass of nutrients (fertilizer and concentrates) and of energy used per unit of animal
product. Some LCA studies highlighted this issue; (27a) simulated an increase of approximately 1020% of the stocking rate and estimated a corresponding increase of approximately 5-6% of GWP
associated to 1 hectare of land; in contrast, there was no effect on environmental burden of 1 kilogram of
milk. [16] Observed that the sample they took of C dairy farms had an average stocking rate of 2.13 LU/ha,
whereas O dairy farms averaged 1.7 LU/ha. In this case, the authors observed a significant difference of
milk production per cow. If there is no difference in respect to animal productivity, the reduction in the
stocking rate does not influence the GWP of 1 kg of milk, but decreases the environmental burden
associated to the land unit (35). A point that some authors make is the rational and efficient use of N feed
and N fertilizers. Excess nitrogen is often associated to high GHG emission per FU, because it indicates
low efficiency of feeding, chemical, and energetic resource utilization (22). (3) analyzed the relationship
between milk productivity and GHG per kilogram of FPCM and concluded that the emissions of CO2eq decrease as milk production increases. In their simulation. While (23) did not find any difference in
GHG emission per Kg of milk among 3 Holstein-Friesian cattle strains. In this case, the differences in
milk production were probably not big enough to be detected with the sensitivity of an LCA analysis. In
the simulation of (43) showed that the increase in individual milk production from 1944 to 2007
resulted in a reduction in CF per kilogram of milk from 3.65 to 1.35 kg of CO2-eq, due to dilution of
(Table 6). Results of two Swedish’01/’02 (52); (51) and one German’89 (53) LCA studies compared with results of this Dutch’03study (20)
results of this Dutch study (Dutch
’03
) rounded to two digitGHGs for the years 2006 and 2012. tCO2e/ton of LW produced over 1 year

maintenance feed requirements. However, (54) showed that the increase in milk productivity determines
a reduction in emissions, even when the expansion system is used and an increase in beef cattle
population is hypothesized. Finally, the increase in milk production per cow means that, given the quota
regimen as in Europe, the number of dairy cattle is reduced. In turn, the population of suckler cows should
increase to meet the demand of meat, and an increase in GHG emissions from beef cattle is expected (55).
Finally The study of CF of dairy production through partial LCA (42) which it was based on a DairyGHG
model to predict all important sources and sinks of CH4, N2O, and CO2 from primary and secondary
sources in dairy production estimated that The cradle-to-farm gate C footprint of commonly used
production practices was found to vary from 0.37 to 0.69 kg of CO2/kg of ECM produced, depending upon
milk production level and the feeding and manure handling strategies used in the production system [15].
14 | P a g e


3.2.3. Mitigation strategies
From the literature results examined, explicitly address mitigation options for beef and dairy. however
it appears that they are sensitive to local conditions and/or variations in production practices adapted.
For example, [2] showed that elimination of fertilization for forages had a modest impact on emissions
for beef farmers in Alberta (Canada) but resulted in large increases in emissions/kg product for
farmers in Saskatchewan and Manitoba (Canada) due to differing yield potentials among locations
(39). Certainly,(42) found that biogas production from enclosed manure storage systems reduced
emissions by 39%/kg milk. The most promising strategy is the anaerobic digestion of the manure (14),
thanks to methane recovery. Anaerobic digestion reduces GHG emissions and does not influence the level
of NH3 emissions. GHG emissions from manure management can be most effectively abated, if CH4
emissions during storage are reduced. This can be achieved by a reduction in slurry dry matter and easily
degradable organic matter content. But probably there is also the need to use more appropriately the soil’s
ability to sink the carbon, by adopting forage systems and agronomic techniques which preserve the soil’s
organic carbon stocks (24).
Therefore there is increasing research effort being focused on calculating the reduction in GHG
emissions associated with increased livestock farming efficiency (e.g. in the NZ study of improving
production efficiency as a strategy to mitigate GHG emissions) (49). A farm scale mechanistic cow
model was used to model a typical pasture based NZ dairy farm as the baseline farm which
considers effects of dietary manipulations on CH4 emissions for more accurate assessment of the
potential impact of 5 GHG mitigations which were: (1) improved reproductive performance of the
herd resulting in lower replacement rates, (2) increased genetic merit of the cows combined with
lower stocking rate and longer lactations, (3) keeping lactating cows on a loafing pad for 12 h/day
for 2 mo during autumn, (4) growing low protein crops of grains and/or MS, barley and oats on
a portion of the farm and feeding this to lactating cows, (5) reducing fertilizer N use and replacing
some of this with nitrification inhibitors and the plant growth stimulant gibberellins. [17] found
that No single mitigation strategy achieved both targets of increasing production by 10–15% and
reducing GHG emissions by 20%, but when all were simultaneously implemented in the baseline
farm, milk production increased by 15–20% to 1200 kg milk fat + protein/ha, and absolute GHG
emissions decreased by 15–20% to 0.8 kg CO2-eq (CO2-e)/kg (FPCM), which is equivalent to a
decrease from 11.7 to 8.2 kg CO2-e/kg fat + protein. Besides The synergies of the mitigations
resulted in reduced DM intake and enteric CH4 emissions, a reduction in N input and N dilution
in feed, and, therefore, reduced urinary N excretion onto pastures, and an increase in feed conversion
efficiency (i.e., more feed was used for production and less for maintenance).
As indicated by (56) pursuing a suite of intensive and extensive reproductive management technologies
provides a significant opportunity to reduce GHG emissions. Recommended approaches will differ by
region and species but should target increasing conception rates in dairy, beef, and increasing fecundity
in small ruminants, and reducing embryo mortality in all species. The result will be fewer replacement
animals needed, fewer males required where artificial insemination is adopted, longer productive life, and
higher breeding production. While Nitrous oxide fluxes can be reduced by using enhanced-efficiency
fertilizers. Another option that was tried with positive results on N2O and CH4 emissions is the addition
of straw to farmyard manures. Soil N2O emissions can be cut by reduced manure application, corn-

15 | P a g e


soybean rotation, and restoration of prairies However, slurry application strategies can have variable
results according to crop, soil type and slurry source.
Conclusion
The IPCC methodologies provide a set of generalized guidelines for compiling and reporting
national inventories and, as such, provide a transparent and consistent framework for comparing
national GHG emissions at various times. However, limitations with respect to this national and
sectorial approach undermine the usefulness of the methodology for modelling at the farm level.
In this respect, whole farm modelling is widely employed for farm level GHG emissions modelling.
LCA is an effective tool to evaluate the environmental impact of a product, process, or activity
throughout its life cycle with the importance of considering the ‘whole farm’ scenario when estimating
GHG emissions from agriculture. From the perspective of a CF, extensive livestock systems relate to low
production efficiency, which then delivers high GHGs emissions per FU. This highlights the potential
conflict between carbon efficiencies and other environmental objectives.
From the literature examined, it appears that there is a wide discrepancy among studies, probably
because the differences between the methodologies applied are too great. In addition, many mitigation
strategies have not been tested in specific contests and so there are no specific EF. CF could be used for
benchmarking by comparing GHG emissions from cattle from different countries or different production
systems. It could also be used to evaluate the improvements of a farm, a region, or a state after the
introduction of technical innovations or political strategies. It could be very effective as a mitigation
indicator of results obtained from the enforcement of environmental political decisions.
Nowadays, the number of dairy cows in Europe has decreased as a result of an increased milk yield per
cow. If this trend keeps up, more and more beef will have to be derived from suckler herds implying an
increase in the environmental loads contributed by beef production. It is time to step up efforts to work
out improvement measures towards beef production based on suckler herds.
Two main things are needed to make CF a practical tool in dairy cattle production. The first is to have
a widely accepted standardized methodology, and in this, the IDF’s initiative can be considered very
promising. The second is to use EF obtained from direct measurements in the specific environmental
conditions they are referred to; only then can LCA be sensitive enough to verify the effectiveness of a
mitigation strategy in a specific contest.
Emissions from livestock systems that influence climate change are fundamentally different from other
pollutants in that they impact to a much greater extent at a global level. Solutions must therefore involve
international collective action and in particular allow participation by developing countries where most of
the growth in demand, production, and therefore EI will take place. Side by side researchers need to
understand what characterizes sustainable dairy and/or beef farming and analyses scenarios for a future
sustainable food production and consumption.
Finally, few LCA studies consider the role of soil in carbon sequestration, through understanding the
factors influencing carbon sequestration and deriving an operational carbon methodology for grassland
carbon sequestration as affected by land management and land use while it is generally recognized to be
an important factor in the environmental sustainability of livestock systems.
16 | P a g e


5. Appendixes
5.1. Appendix I (Table 1) Assembled LCA investigated studies for each country during the review
with a brief description of the approaches, system boundaries, and emission factors utilized for each
study
Nº

[1]

[2]

[3]

[4]

[5]

[6]

Study

Beauchemin
et al.(2010)

Stewart et al.
(2009)

Country

Methodology

Canada

Multiple-year over the
lifespan of a breeding
animal.

Canada

Modelling of four
hypothetical
farms
representing a range of
climatic and soil
conditions.

Single-year,
whole
Nguyen et al. Denmark farm system model
(2010)
developed for typical
European suckler and
dairy-beef production
systems.
Single year, whole
Casey
et Ireland system model. Based
al.(2006a,b)
on typical Irish cowcalf farm finishing all
cattle.
Single-year,
whole
Crosson et al. Ireland farm system model of
(2010)
beef cow systems.
Modelled scenarios.

Veysset et al.
(2010)

17 | P a g e

France

Coupled a linear
programming
bio
economic model with
an
environmental
assessment model for
beef farming systems.

System Boundaries

Emissions
factors EF
Direct
on
farm, IPCC
(2006)
purchased inputs, and methodology For
indirect nitrous oxide Canada.
emissions. Excludes
Capital
and
machinery.
Direct
on
farm, IPCC
(2006)
purchased
inputs, methodology For
LUC and indirect Canada.
nitrous
oxide
emissions and sinks.
Excludes Capital and
machinery.
Direct
on
farm, Primarily IPCC
purchased inputs, and (2006).
indirect nitrous oxide
emissions.

Direct
on
farm,
purchased
inputs
emissions. Excludes
capital,
machinery
and chemicals
Direct
on-farm,
purchased inputs, and
emissions. Excludes
capital and machinery.
Direct
on
farm,
purchased inputs and
Does
not include
emissions

IPCC (1997) for
enteric
fermentation and
direct
nitrous
oxide emission.
Primarily IPCC
(2006).

IPCC
(2006)
methodology for
France.


[7]

Ogino et al.
(2004)

Japan

[8]

Pelletier et al.
(2010)

USA

[9]

Phetteplace
et al.(2001)

USA

[10] Subak
(1999)

USA

Single year, whole
farm system model.
Based on Japanese
cow-calf to finishing
production system.
Single year, whole
farm system model of
cow calf, stocker and
feedlot
production
systems.
Systems modelling of
cow calf to beef
American production
systems
Environmental
analysis
of
hypothetical pastoral
and
feedlot
beef
production systems.

Single year, whole
[11] Cederberg et Sweden farm system model
al.(2000)
developed for system
expansion allocation
of beef from dairy
system
An LCA model for
[12] Peters et al. Australia production emissions
(2010)
and an input–output
analysis for
other
emissions including
purchased chemicals.
[13] White et al.
(2010)

18 | P a g e

New
Zealand
(NZ)

Direct
on
farm,
emissions from energy
consumption
and
imported animal feed.

Empirical
data
from
experimental
systems (Enteric
fermentation).
Direct
on
farm, IPCC (2006).
emissions. Excludes
Direct
on
farm, IPCC (2006).
emissions. Excludes
CH4,
and
CO2 IPCC (2006).
emissions from fuel
usage. Also includes
emissions associated
with alternative land
uses.
Direct
on
farm, IPCC (1997).
emissions. Excludes
Direct
on
farm, IPCC
(1997)
purchased inputs, and methodology for
Also
includes Australia
missions
at
the
processing plant.

Direct
on
farm,
Farm simulation, feed purchased inputs for IPCC
(1997)
Formulation,
and feed production but methodology for
nutrient
budgeting not for purchased New Zealand
models.
feeds, and indirect
nitrous
oxide
emissions. Excludes


[14] R.
RipollBosch et al.
(2013)

Spain

[15] Rotz et al.
(2010)

USA

[16] Thomassen
et al. (2008)

NL

[17] Beukes et al.
(2011)

NZ

19 | P a g e

A model was used to
capture
the most
important interactions
in complex SFSs, to
compute data required
to determine for GHGs
based on the LCA
model used by FAO
(2013)

Direct
on
farm,
purchased
inputs,
emissions
at
the
production ,processes
of medicines, and also
the cultural ecosystem
services, machinery
and buildings were
excluded from the
analysis
Whole farm system, Direct
on
farm,
Semi-mechanistic
GHG
simulation indirect nitrous Oxide
model.
Modelled emissions. Excludes
pasture-based
and buildings.
confinement US dairy
production systems
Cradle to farm gate
analysis
of
ten
conventional and 11
Organic Dutch dairy
production systems.

Integrated
three
models (a dynamic,
mechanistic
whole
farm
simulation
model, a mechanistic
animal model and
nutrient flow model)
to
investigate
mitigation scenarios
for typical
New
Zealand dairy systems

IPCC
(2006)
methodology for
Spain

Primarily IPCC
(2006) and
literature-sources
emission factors
for secondary
emission sources

Emission factors
taken from the
literature for
most
sources
(IPCC (1997))
emission factors
for nitrous oxide
from
managed
soils)
Direct
on
farm, IPCC
purchased inputs and methodology for
indirect nitrous oxide New Zealand
emissions
Direct
on
farm,
emissions. Excludes
chemicals
and
buildings.


5.2. Appendix I (Table 2) Total GHGs CO2-eq contributions of different results from milk
production
GWP
Author

Study

Total GHG CO2-eq
CH4

CO2

N2O

19443.66 17

61.8 2

1

412 3

20071.35

26.8

1

230

Capper et al.,
(2009)
Casey et al.,
(2006)

6
7
8
9

310

Sweden milk
production system

Conventional1.09
Organic0.90

25

1

298

Sweden milk
production system

No allocation1.05 4
Economical 0.92
Biological 0.85
Expansion 0.6

25

1

298

New Zealand and
Sweden milk
production system

NZ 1.0 4
S1.16

63.1

8.13

25.7

50.1

15.9

32.3

Irish milk production
system

For three Holstein-Friesian
strains  0.73-0.81 or 1.116

23

1

Phetteplace et al.,
(2001)

5

1

O’Brien et al.,
(2010)

4

21

Flysjö et al.,
(2012)

3

Conventional1.54
Efficient1.26
Only dairy1.2
Integrated1.05

Cederberg and
Stadig, (2004)

2

Irish milk production
system

Cederberg and
Mattsson, (2000)

1

US dairy production

Simulated beef and
dairy livestock systems
in the United States

Cow-calf20.6 5

8.65 2

0.94

10.9

Stocker14.4
Feedlot5.66
Cow-calf through
feedlot15.5

6.58

1.4

6.41

1.32

2.1

7.84

6.28

1.3

2.22

Includes CO2 emissions from animals, plus CO2equivalents from CH4 and N2O.
Includes CH4 emissions from enteric fermentation and manure.
Includes N2O emissions from manure (both years) and from inorganic fertilizer application (2007 only).
Kg ECM (Estimated Corrected Milk).
Kg live weight gain.
Product is kgCO2e/kg milk.
Kg of fat and protein corrected milk (FPCM).
Kg CO2eq Includes CH4 emissions from enteric fermentation and manure.
Kg CO2eq Includes CH4 emissions from soil and manure.

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Dairy1.09 6
Thomassen et al.,
(2008)

Dutch dairy production
systems.

0.58

0.14

Conventional1.4 7
Organic1.5

23

1

0.37

298

5.3. Appendix I (Table 3) Total GHGs CO2-eq contributions of different results from beef and meat
production
GWP
Author

Study

Total GHG CO2-eq
CH4

Beauchemin et
al. (2010)
Nguyen et al.
(2010)

CO2

N2O

276 8

277

208 9

1

Dairy bull calf (12 mo)16.0
Dairy bull calf (16 mo)17.9
Steers (24 mo)19.9

476 2
197
265
376

26
9
10.8

23

1

40%

14.8

20%

16.2

41%

19.2

Beef production

21.731

in western Canada

13.04 5

Different beef
production systems in
the EU

Suckler cow–calf27.3

20.7

Ogino et al.
(2004)

Japanese beef-fattening
system with different
feeding lengths

22.6

Pelletier et al.
(2010)

cow calf, stocker and
feedlot production
systems in the Upper
Midwestern United
States

Feedlot-finished from
Weaning 26.9
Feedlot finished following
store period29.5
grass-finished34.9

Intensive US feedlot
system and a traditional
African pastoral system

American feedlot-finished
14.8
African pasture-finished8.4

50108 0.0811
29

0.04

Economic performance
assessments in French
Charolaise suckler cattle
farms

Calf-to-weanling and fattened
females16.6; calf-to
weanling grassland
farm17.1; Calf-to-beef.
Beef steers production14.9;
baby beef production14.6;
calf-to-weanling and cereals
production19.0

10.1
11.3
8.7

2.3
2.0
2.2

4.1
3.9
4.0

8.5

1.8

4.0

11.5

2.3

5.2

Subak (1999)

Veysset et al.
(2010)

10
11

In kg CO2e/kg beef carcass
Expected social costs of climate change: $6.2–45.2:tonne C or $1.7–9.2 tonne CO2

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296


5.4. Appendix II: A whole farm GHG models91

Figure 6.Carbon and nitrogen flow diagram of a ruminant livestock system (Schils et al., 2005) (38)

Figure 5.Diagram of the pools and flows contained within the model (Stewart et al., 2009) (39)
1

Selected models examples according to the international LCA citation rate and the relevance of the utilized references in
this review, which considered the main corner stone for a full accounting holistic LCA based studies by many scientists and
researchers on the Carbon footprint (CF) and evaluation of the farming systems management practices and emissions.

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Figure 8 Flows of C and N in and out of the total model farm system FarmGHG (Olesen et al., 2006) (12)

Figure 7.HOLOS model (Beauchemin et al., 2012) (15) (16) (17)

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Figure 9.Operational diagram of greenhouse gas (GHG) model (O’Brien et al. 2011) (37)

24 | P a g e


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