




































 

 

 
19 

† Corresponding author 
© 2015 Conscientia Beam. All Rights Reserved. 

 

CLIMATE RELEVANT EMISSIONS FROM ANIMAL PRODUCTION AND 

REDUCTION POTENTIALS 

 

Gerhard Flachowsky1 --- Dirk von Soosten2 --- Ulrich Meyer3* 
1,2,3Institute of Animal Nutrition Friedrich-Loeffler-Institut (FLI) Federal Research Institute for Animal Health Bundesallee, 

Braunschweig Germany 

 

ABSTRACT 

Animal production contributes substantially to global greenhouse gas emissions (about 14.5%). The so-

called Carbon Footprint (CF) considers the greenhouse gas potential of climate relevant gases (e.g., CO2 x 1; 

CH4 x 23; N2O x 296) and is given in CO2-eq per g or kg product or per unit edible protein. The CF may 

help to assess the greenhouse gas emissions associated with the production of foods of animal origin such as 

milk, meat, eggs or fish. The CF may contribute to sensitizing producers and consumers to a more resource-

efficient and environmentally-friendly production, to the consumption of food of animal origin, and to 

avoiding food wastage. The highest CF per unit edible protein is calculated for products of growing 

ruminants (beef and lamb), followed by milk and pork and eggs and poultry meat with the lowest values. 

Discrepancies in the results of various studies are mainly explained by different system boundaries, allocation 

methods and computation of emissions, especially with regard to land use changes, enteric methane emissions 

and nitrous oxide emissions. A more standardized approach for data collection and CF-calculations would 

be a very useful tool to compare CF between production systems, regions and countries, and an indicator for 

food labelling, and is considered in the first part of this paper. The second part of the paper deals with the 

potential to reduce climate relevant gases from animal production. Some specific influencing factors, such as 

plant and animal breeding, feed production, animal feeding as well as animal keeping, animal health and 

excrement management are analysed more in detail. Most attention has been spent to the methane reduction 

potentials in the rumen. The reduction of CF in ruminant production per product should focus on a 

lowering of methane emissions from enteric fermentation and an increase of low production levels as well a 

reduction of ineffective animal numbers. In the future, results of plant and animal breeding may also 

substantially contribute to lower GHG emissions. Furthermore, new potentials to improve protein supply for 

human nutrition should be used. The production of food of animal origin is a very complex process and 

selective consideration, i.e., focussing on single factors, does not provide an assessment that reflects the 

complexity of the subject. Recommendations for further research activities are given. 

Animal Review 
2015 Vol. 2, No. 2, pp. 19-57 
ISSN(e): 2409-6490 
ISSN(p): 2412-3382 
DOI: 10.18488/journal.ar/2015.2.2/101.2.19.57 
© 2015 Conscientia Beam. All Rights Reserved. 

 

 

http://crossmark.crossref.org/dialog/?doi=10.18488/journal.ar/2015.2.2/101.2.19.57


Animal Review, 2015, 2(2): 19-57 

 

 

20 
© 2015 Conscientia Beam. All Rights Reserved. 

Keywords: Greenhouse gas emissions, Carbon footprints, Reduction potentials, Animals, Milk, Meat, Eggs, 

Aquaculture, Edible protein. 

Received: 6 November 2014/ Revised: 24 March 2015/ Accepted: 28 March 2015/ Published: 2 April 2015 

 

1. INTRODUCTION 

More people and higher need for feed and food are associated with a growing demand for 

limited natural resources such as water, fuel, minerals, arable land, etc., and elevated emissions 

with greenhouse gas (GHG) potential such as carbon dioxide (CO2), methane (CH4), nitrous oxide 

(laughing gas; N2O) and other substances (e.g., N, P, trace elements etc.). According to the [1, 2], 

the human population will increase globally from currently about 7 billion to more than 9 billion 

people in 2050, but the increase in the output of food of animal origin is estimated to be about 70% 

[3]; [4]. These changes characterize the situation all over the world (e.g., [5]; [6]; [7]; [1, 2]; 

[8]; [9]; [10]; [11]. Malnutrition in all its forms (under-nutrition, micronutrient deficiencies 

(e.g., iron, iodine, vitamin A, etc.), and over-nutrition – the so-called ―triple burden‖ of 

malnutrition) is still recognized as a serious and intractable problem for humans [12]; [13]. Food 

of animal nutrition, also called animal source food (ASF; [14], may contribute to overcoming 

micronutrient deficiencies [15]. 

The energy and protein conversion efficiency from feed into food of animal origin is low and 

may vary between 3 % (energy - beef) and up to 40 % (energy - dairy; protein - chicken for 

fattening; [16]; [17]. In some countries (e.g., USA) between 67 % (energy) and 80% (protein) of 

the crops are used as animal feed [17]. 

These developments and complex connections present the following question: ―Is there any 

need for food of animal origin?‖ As vegans demonstrate, there is no essential need for food of 

animal origin, if the human diets are supplemented with all essential nutrients. But on the other 

hand, the consumption of meat, fish, milk and eggs may contribute significantly to meeting the 

human requirements of amino acids (e.g., [18]; [19]; [20]; [21]; [22], [13, 15]; [23] and some 

important trace nutrients (such as Ca, P, Zn, Fe, I, Se, Vitamins A, D, E, B12) especially for 

children and juveniles as well as for pregnant and lactating women [24]. Human nutritionists 

(e.g., [25]; [26] have recommended that about one third of the daily protein requirements (0.66 - 

1g per kg body weight; e.g., [27]; [26]; [19] should originate from protein of animal origin. 

Consequently, about 20 g of the daily intake of about 60 g protein should be of animal origin, 

which is lower than the present average consumption throughout the world. Presently, there is an 

average consumption of protein of animal origin (without fish) of about 24 g per capita and day, 

ranging between 1.7 (Burundi) and 69.0 g (USA; Table 1). It is a challenge for the future to 

overcome this imbalance [23]. Meat, milk and eggs provide around 13% of the energy and 28% of 

protein consumed globally, with the higher share in the so-called developed countries (around 20 

and 40 % resp., [1]. It is difficult to assess the protein intake from fish and other animal protein 

sources (e.g., insects). [28] estimate that half of the world´s population consumes at least 15% of 

their animal protein from aquaculture.  

 



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21 
© 2015 Conscientia Beam. All Rights Reserved. 

Table-1. Intake of milk, meat and eggs as well as protein of animal origin per capita and year and portion (%) of total 

protein intake (global minimum-values; maximum-values and averages as well as German values for comparison; kg per 

capita and year: data base 2005; [1] 

Food Minimum Average Maximum Germany 

Milk (kg per year) 1.3 
(Kongo) 

82.1 367.7 
(Sweden) 

248.7 

Meat1) (kg per year) 3.1 
(Bangladesh) 

41.2 142.5 
(Luxembourg) 

83.3 

Eggs (kg per year) 0.1 
(Kongo) 

9.0 20.2 
(China) 

11.8 

Edible protein of animal origin (g 
per capita and day) 

1.7 
(Burundi) 

23.9 69.0 
(USA) 

52.8 

Portion of animal protein in % of 
total protein intake per capita 

4.0 
(Burundi) 

27.9 59.5 
(USA) 

53.7 

  1)  Probably empty body weight (meat plus bones) 

 

Other reasons for consumption of food of animal origin are the high bioavailability of most 

nutrients and their considerable ―enjoyment value‖. Such food is presently also considered as an 

indicator for the standard of living in many regions of the world. Eating food of animal origin, 

esp. meat, is not only a reflection of nutritional needs, but it is also determined by taste, odour, 

and texture, as well as by geographical area, culture, ethics and wealth. Further reasons for the 

higher demand of food of animal origin in some countries are the increased income of the 

population [29] [30]; [31]; [12] and the imitation of the so-called ―Western style of life‖ 

regarding the nutrition. Many developing countries continue to consume more animal products 

than they produce. Therefore, they will continue to drive the world demand for all agricultural 

products, including food of animal origin [32]. Higher food amounts of animal origin require 

higher plant yields and/or more area for feed production [33]; [34]; [35]; [36] and more 

animals and/or higher animal yields as well an increase in agricultural trade. Therefore, some 

authors propose a redefinition of agricultural yield and agriculture in general: ―from tonnes to 

people nourished per hectare‖ [31]; [17] and ask for more sustainable animal agriculture (e.g., 

[37], [38]; [39]. 

On the other hand, changing the eating patterns [40] and eating less or no livestock 

products, esp. meat, are often seen as possible solutions to reduce the environmental impact of 

animal agriculture [41]; [42], [43] and to reduce the per capita land requirements (e.g., [44]. 

In the future there will be strong competition for arable land and further non-renewable 

resources such as fossil carbon-sources, water [45]; [46]; [47]; [48], some minerals (such as 

phosphorus; [49]; [50] as well as between feed, food, fuel, fibre, flower and fun; (6 F`s-concept; 

[51] and areas for settlements and natural protected areas.  

In this connection, more attention should been paid to the need of limited natural resources 

per amount of animal product, expressed as footprints per product such as ―Water Footprints‖ 

[52]; [53], ―Mineral (esp. phosphorus; P) Footprints‖, ―Land (arable or total land) Footprints‖ 



Animal Review, 2015, 2(2): 19-57 

 

 

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© 2015 Conscientia Beam. All Rights Reserved. 

(see [54]; [55]; [56], [36]. These Footprints are given in kilograms, litres or tonnes per unit 

product and characterize the efficiency of various production processes. 

On the other side, special attention has also been paid to the outputs from agriculture e.g., 

[7]; [10] including livestock keeping esp. so-called GHG relevant emissions‖ such as CO2, CH4, 

N2O and further gases. All the climate relevant emissions are summarized to so-called Carbon 

Footprints (CF). They have also been modified or called Ecological Footprint (EF), Eco-Balances 

(EB), Life Cycle Assessments (LCA) or Life Cycle Impact Assessment (LCIA). In all cases the 

term means a summarized parameter for all gaseous emissions with greenhouse gas potential to 

sensitize producers and consumers, e.g., [57]; [58]; [59], to an efficient use of fossil carbon 

sources and to reduce GHG emissions per product (see also [60]. CF or LCA are used as a tool 

for estimating environmental effects caused by products or processes. Furthermore, CF may also 

contribute to assessing the resource and feed efficiency between various regions and production 

systems. Recently, some authors have written about problems with LCAs, e.g., [61]; [62]; [63] 

and new developments such as more comprehensive Life Cycle Sustainability Analysis (LCSA; 

[64], but a unified solution to the subject is still lacking. Therefore, CF are calculated and 

interpreted in the present paper in a common way. 

Agriculture, and especially animal husbandry, are considered as important GHG sources 

because of the high GHG potential of some emissions associated with animal production (e.g., 

methane (CH4) and laughing gas (N2O)), which are estimated at 7.1 Gt CO2-eq per annum, 

representing about 14.5% of human-induced GHG [65]. Table 2 summarized the present 

production of food of animal origin, expected growing rates and emissions for animal groups. 

Globally, ruminant supply chains are estimated to emit 5.7 Gt CO2-eq per year, of which 81%, 11% 

and 8% are associated with cattle, buffalo and small ruminant production [66].  

 

Table-2. Present production, growth rates and emissions for some food producing animal groups (calculated from data by 

Gerber, et al. [65]; MacLeod, et al. [67], Opio, et al. [66] 

Animal groups Ruminants Pigs Poultry 
Production 
(Mio. t) 

Milk: 864 
Meat:   81 

CW1): 110 Eggs:  58 
CW:    72 

Growth rate (% per year; until 2030/50) Milk:  1.1 
Meat:  1.3 

1.3 Eggs: 1.6 
Meat: 2.4 

Emissions (Gt; CO2-eq per year) Milk:   2.0 
Meat:   3.7 

0.7 Eggs:   0.2 
Meat:   0.4 

  1)  Carcass weight 

 

Based on the developments mentioned above, philosophers and natural scientists of various 

disciplines studied and analysed more and more these global developments. The balance between 

Planet (global resources and emissions) – People (social aspects of population all over the world) 

and Profit (economic aspects, money-making) in the so-called 3P-concept, [68]; [69], is an 

important prerequisite for sustainable life and development on the earth. Some authors are afraid 

that the balance between the 3Ps is being more and more disturbed and that an ethical dimension 



Animal Review, 2015, 2(2): 19-57 

 

 

23 
© 2015 Conscientia Beam. All Rights Reserved. 

should be introduced as the fourth dimension [68]. Profit should not and cannot be the single 

objective of production. We need to find a balance between a careful and sustainable use of limited 

resources (see above) on the one hand [70]; [71] and low emissions with local and global 

consequences for later generations [72] on the other hand. 

More studies and analyses should be the base for consequences for a more efficient use of 

limited resources and lower emissions per product. Therefore, the objective of the present 

contribution is to analyse sources and amounts of greenhouse relevant gases associated with the 

production of food of animal origin and to deduce parameters to assess the level of emissions from 

animal production. Furthermore, possibilities to lower the GHG emission from animal 

production, esp. methane, are discussed in the second part of the paper. The Livestock 

Environmental Assessment and Performance (LEAP) initiative of the FAO [73] is an activity in 

many countries to include such environmental improvements in the livestock supply chain. 

 

2. CALCULATIONS OF CARBON FOOTPRINTS (CF) 

Carbon Footprints are defined as the total amount of GHG emissions (under consideration of 

their GHG potential) associated with a product along its supply (human food) chain. This chain 

includes ―Plant production incl. harvesting, storing and treatment – Feed preparation – Feeding 

of food producing animals – Preparation of food (milk, meat, eggs etc.) – Distribution, market – 

Households‖. Sometimes CF includes also emissions from consumption, end-of-life recovery and 

disposal. Usually, CF`s are expressed in kg or t of carbon dioxide equivalents (CO2-eq) per unit 

product [66]. Studies and publications about CF have increased dramatically during the last few 

years, demonstrating that the interest for more resource-efficient and cleaner production has been 

enhanced. Agriculture, and especially animal husbandry, are considered as important GHG 

sources because of the high greenhouse potential of their emissions (e.g., CO2 x 1; CH4 x 23 and 

N2O x 296; [6]. Carbon Footprints consider the GHG potential of climate relevant gases and are 

given in CO2-eq per g or kg per product. Various authors calculated such CF for agriculture in 

general, but also for separate segments. 

The public interest in CF is discussed in the context of global warming and possible climate 

changes [6]; [74]. The paper attempts to present the most important factors in agricultural 

primary production along the whole food chain, i.e., soil, plant production (harvesting, 

conservation), industrial feed production, livestock-keeping (incl. excrement management). It also 

addresses possible other influencing factors such as system boundaries, feed and food processing, 

transport and trade, resulting in climate-related emissions. Consequences of land-use change 

(LUC; e.g., change of forest into cropland or pasture) for CF-calculations should also be 

considered, but in some cases the values are not known or not considered in calculations (e.g., 

import of feeds). 

A number of factors (e.g., plant yield, animal species and performances, type of production) 

cannot be ignored when taking into account the greenhouse gas potential of the various gases (see 

above) to derive CF and for the comparison of values along the food chain. The origin of the most 



Animal Review, 2015, 2(2): 19-57 

 

 

24 
© 2015 Conscientia Beam. All Rights Reserved. 

important GHG, such as carbon dioxide, methane and nitrous oxide, are discussed in the next 

paragraphs. 

 

2.1. Carbon Dioxide (CO2) 

The direct carbon dioxide emission from the animals can be considered as emission-neutral. 

CO2 will be fixed by photosynthesis of plants and excreted by the animals as a result of animal 

metabolism. But nevertheless, the CO2 emission must be seen along the whole food chain and 

based on burning of fossil carbon during feed production and land-use changes (LUC; [75]; [76]; 

[59]; [67]. In general, non-carbon dioxide GHG such as methane (CH4) and nitrous oxide (N2O) 

come directly from animals or from animal manure practices. 

 

2.2. Methane (CH4) 

Methane is emitted under anaerobic conditions from the enteric fermentation in the digestive 

tract of animals, mainly in the rumen, but also during the manure management. Excess of 

hydrogen during anaerobic fermentation in the rumen is catalysed by various reduction processes. 

The last step is catalysed with Methyl-Coenzyme M reductase of reduction of CO2 to CH4 by 

hydrogenotropic methanogenic archaea [77]. Details of the enteric methane production are 

described in many papers e.g., [78]; [79]; [80]; [81]; [82] and prediction equations are given, 

e.g., [6]; [83]; [84]; [85]; [86]; [87, 88]; [89]. Reduction potentials are analysed in Chapter 5 

of this paper. Methane contributes not only to the greenhouse effect, between 2 and 12% of the 

ingested cross energy of ruminants can be lost to methane [90] depending on diet composition 

and other influencing factors. Apart from the environmental effect, this energy could potentially 

be used by the animals for growth and lactation as shown in a model calculation in Table 3. 

 

Table-3. Model calculation to show the influence of methane reduction on the energy available for dairy cows and milk 

yields (Conditions for calculation: DMI: 20 kg per cow per day; body weight: 650 kg per cow, energy intake: 7 MJ NEL 

per kg DM with 20 g CH4-emission; Niemann, et al. [91] 

Methane reduction 
(g per kg DMI) 
(g per cow per day) 

 
30 
600 

 
25 
500 

 
20 
400 

 
15 
300 

Energy intake (MJ NEL1) per day) 130 135 140 145 

Milk yield (kg per day) 28.0 29.5 31.0 32.5 
Methane emission (g per kg milk) 21.4 17.0 12.9 9.2 
Carbon footprint (g CO2eq per kg milk) 735 585 440 315 

1) Net energy lactation 

 

The methane emissions from the manure management are generally not directly associated 

with animals, but the losses can be considerably high [87, 88]; [92], esp. if the excreta are stored 

under anaerobic conditions. 

 

 



Animal Review, 2015, 2(2): 19-57 

 

 

25 
© 2015 Conscientia Beam. All Rights Reserved. 

2.3. Nitrous Oxide (Laughing Gas, N2O) 

Animals do not excrete nitrous oxide directly, but it can be formed in manure depending on 

the storage conditions and following land application, e.g., [93]; [88, 94]; [92]. N2O is mainly 

produced in soils by microbial nitrification (the oxidation of ammonium NH4
+ to nitrate NO3

-) and 

denitrification (reduction of NO3
- to N2; [95]. These microbial processes depend on temperature, 

moisture content and oxidation status of the environment. High N-fertilization and soil 

compaction are important factors that increase N2O emissions. Since 1750, the tropospheric 

concentration of N2O increased from 270 to 320 ppb [96]. More details about N2O production 

and emission from the soil are described by many authors and should not be considered in further 

details in the present paper, e.g., [97]; [98]; [99]; [100]; [101]; [102]; [103]. 

 

3. CF FOR FOOD OF ANIMAL ORIGIN 

Beginning with one and two studies per year in 1998-2000, about 20 studies per year were 

published in the last years [28]. The studies dealt with calculations of CF for nearly all types of 

food of animal origin (see summaries by Williams, et al. [104]; Leip, et al. [105]; Gruenberg, et 

al. [106]; Flachowsky [107]; Flachowsky, et al. [108]; Lesschen, et al. [109]; Gerber, et al. 

[65]; MacLeod, et al. [67]; Opio, et al. [66].  

Results of CF-calculation for foods of animal origin depend on many influencing factors such 

as animal species and categories, animal yields and endpoints of animal production. Advantages 

and weaknesses of endpoints (outputs) of various forms of animal production are summarized in 

Table 4. All endpoints are characterized by some advantages and disadvantages. From nutritional 

and scientific points of view edible protein seems to be the most favourable measurement (see 

Chapter 4), but in the case of meat production its measurement is not easy and requires some 

analytical work. 

 

Table-4. Advantages and disadvantages of various outputs/endpoints of animal yields concerning the calculation of 

carbon footprints (by Flachowsky and Kamphues [110] 

Animal yields Advantages Disadvantages 

Milk, Eggs Easily measurable, almost complete 
edible 

Variation in protein, fat and 
energy yield, analyses may be 
useful 

Body weight gain Easily measurable High portion of non edible 
fractions in the gains 

Carcass weight Easily measurable Still contains fractions, which are 
not edible (e.g., bones) 

Meat, edible fraction Completely edible Categorization and separation not 
easy 

Edible protein Most important objective of animal 
production; Comparison of various 
ways and sources to produce protein 
of animal origin 

Categorization of various fractions 
as edible and difficulties to 
measure; additional analytical 
work; variation in N/protein 
content 

 

For practical reasons carcass weight or weight gain (warm or cold) would be the most 

important endpoint to measure the yield of slaughtered animals because this weight is measurable 



Animal Review, 2015, 2(2): 19-57 

 

 

26 
© 2015 Conscientia Beam. All Rights Reserved. 

in the slaughtering houses [111] and can be used for further calculations. Ways to calculate CF 

and examples for various food of animal origin are shown and discussed in the following sections 

(see Tables 6-11). 

 

3.1. CF of Milk 

Table 5 demonstrates some important emission sources and steps to calculate emissions per 

cow and year and per kg of milk. The values per cow or per kg milk depend mainly on the levels 

of emissions and on the milk yield. The calculation shows that in this case about 2/3 of emissions 

come from methane. 

 
Table-5. Calculation of emissions per cow and year (Parameters: body weight: 650 kg per cow, milk yield: 8000 kg per 
year, 1 calf per year (by Dämmgen and Haenel [112] 

 Emissions 
(kg per cow per year) 

Source of emissions CO2 CH4 N2O 
Fertilizer 210 5.5 1.1 
Feed 83  1.2 
Transport, treatment 43   
Rumen fermentation  119  
Fermentation of excrement management  19 0.9 
Emissions from soil2)  - 1 1.8 
Total 336 143 5 
CO2-Equivalents (kg/cow and year) 5200 
                            (g/kg milk)1) 650 

CO2- Equivalents of emission (kg/cow) 336 3290 1500 
(% of total emissions) 6 65 29 

1)
 without calf and heifer, 2) no land-use change (LUC) 

 

Table 6 shows exemplary the CF for milk under consideration of various boundaries. A clear 

definition of the system boundaries and the comprehensibility are important prerequisites for 

following the calculations and for making the results comparable [113, 114]; [115]. 

Furthermore, a clear definition of milk (e.g., energy, protein or fat corrected milk; see Table 6) is 

also necessary to compare calculations by various authors. Scientists working in this field should 

agree on the system boundaries and GHG factors of climate relevant gases. 

 
Table-6. Model calculation to demonstrate the effects of various system boundaries of CF of milk (g CO2-eq per kg of milk; 
30 kg milk per cow and day; diet on DM-base: 60% roughage, 40% concentrate; 4% milk fat, 3.4% milk protein; 305 days of 
lactation; 60 days dry period, 3 years lactation; 30 months calf and heifer period (by Flachowsky, et al. [108]) 

System System boundaries CF (g CO2-eq/kg milk) 

1 Animal caused emissions (incl. CH4 during lactation period) 280 
2 1 + Emissions of feed production (without LUC) 430 

3 2 + Dry period of cows 500 
4 3 +  Heifer period 730 

5 4 + Animal housing and milking 760 

6 5 + Excrement management 820 
7 6 + Processing, transportation and trade of milk 1 100 

 



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The large range in CF of milk comparing results of various authors depends on many 

influencing factors is shown in Table 7. The CF for milk by various authors varies between 0.4 

and 1.5 kg CO2-eq/kg in Europe, North America and Oceania, and under consideration of different 

world regions between 1.3 (Europe and North America) and >10 kg CO2-eq/kg in sub-Saharan 

Africa or highlands in Peru [8]; [116]; see Table 7). Most authors considered only the emissions 

during production, but sometimes LUC as well as processing, transport and trade are also 

included in calculations. In their recent publication, [66] mentioned ranges from 1.6 to 9.0 kg 

CO2-eq/kg fat and protein corrected milk (FPCM) for regional emission intensity. Generally, milk 

production in low productive systems has higher emissions per kg FPCM than in high production 

systems [117]. Methane and nitrous emissions per cow increase, but they decrease per kg milk 

with increasing productivity, while carbon dioxide increases because of a higher feeding of 

concentrates, but on a much lower scale.  

 

Table-7. Examples for CF (kg CO2-eq/kg milk) in dependence on type of production (conventional or organic) published 

by various authors 

    Country               Type of production/farming Authors 

 Conventional Organic  

Germany 0.83 0.84 [118] 

Germany 0.85 0.78 [119] 

Sweden 0.90 0.94 [120] 

Germany 0.94 0.88 [121] 

The NL 0.97 1.13 [122] 

Germany 0.98 0.92 [123] 

Sweden 0.99 0.94 [124] 

UK 1.06 1.23 [104] 
Austria 1.20 1.00 [125] 

UK 1.20 1.30 [126] 

Germany 1.30 1.30 [127] 

The NL 1.40 1.50 [128] 

UK 1.6 (1.0-3.2) 1.3 (0.9-2.4) [129] 

Without differentiation conventional/organic 

Germany 0.40 (40 kg milk/day) [130] 

(Model 0.55 (20 kg milk/day) ― 

calculation) 1.00 (10 kg milk/day) ― 

Germany 0.65  [112] 

New Zealand 0.65-0.75 [131] 

Literature review 0.8 – 1.4 (on farm) 
0.9 – 1.8 (on farm + post farm emissions) 

[132] 

New Zealand 0.86 [133] 

Germany 0.98 (10 000) - 1.35 (6000kg milk per year; without allocation) [134] 

Sweden 1.00 [135] 

Canada 1.00 [136] 

UK 1.06 [104] 
USA 1.09 [137] 

EU 1.3 (1.0-2.3; EU-27) [109] 

Ireland 1.3-1.5 [138] 

USA 1.35 [111] 

Norway 1.5 – 1.6 
(Combined milk/meat; expanded boundaries) 

[139] 

Global 2.4 (1.3-7.5; global) [140] 

Global, Cow 
Buffalo 
Small ruminants 

2.8 
3.4 
6.5 

[66] 

Peru; Coast 
Highlands 

3.2 
13.8 

[116] 

 



Animal Review, 2015, 2(2): 19-57 

 

 

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3.2. CF of Food from Slaughtered Animals and Eggs 

It is much more difficult to measure the yield from the animal body after slaughtering and 

processing of animals (see Table 4). Calculation of CF may base on various outputs. For practical 

reasons, carcass weight (warm or cold) or weight gain would be the most important endpoint to 

measure the yield of slaughtered animals. Based on the values derived from Table 8, CF is 

calculated for various endpoints under consideration of differences in feeding and GHG emissions 

and are shown in Table 9. 

 
Table-8. Model-calculations of CF for beef (150-550 kg body weight1)) in dependence on feeding2),3), weight gain, 
methane- and N-emissions (by Flachowsky [118] 

 
1) Production of calf up to 150 kg BW is not considered;  2) CO2-Output: 120 g/kg roughage-DM; 220 g/kg concentrate-DM, 3) Feed sources 
may have a strong influence on CF.  

 

Co-products of feed and food industry (see [119] can reduce the CF of food of animal origin 

[120] because of their lower environmental costs [121]; see also Section 5.3. 

 

Table-9. Model calculation for illustrating various endpoints for growing/fattening bulls (150-550 kg body weight; 

calculation based on data by Flachowsky [122] 

Brutto 
weight 
gain 
(g/day) 

Weight gain 
without 
content of 
intestinal 
tract (g/day) 

Carcass 
weight 
(warm; % 
of weight 
gain) 

Carcass 
weight 
gain 
(warm; 
g/day) 

Meat 
gain (% 
of 
weight 
gain) 

Meat 
gain 
(g/day) 

Edible 
fraction 
gain1) 
(g/day) 

Edible 
protein 
(g/day; 19% 
protein in 
edible 
fraction) 

500 438 50 250 40 200 250 48 

1 000 900 53 530 44 440 490 93 
1 500 1 385 56 840 48 720 770 146 

1) Meat plus other edible tissues  

 

Under farm conditions, only the GHG-balance per kg body weight gain can be calculated. 

Normally, the GHG emissions for the whole beef system include also emissions of cows, calves 

and heifers needed to produce beef. They are much higher than in the system dairy cow – 

growing/fattening bulls for beef. The GHG-emissions to produce pork and poultry meat should 

also include the emissions of parent animals (sows and laying animals). 

The term ―meat‖ is not clearly described and is used for both ―real meat‖ and meat plus bones. 

[111] introduced the term ―hot standard carcass weight‖ (HSCW) as the weight at the exit gate 



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of the meat processing plant. It varies between 50-62% of the live weight of slaughtered cattle, but 

it may vary between 50% in the case of sheep and up to 80% for fattening turkeys [122]; [104]; 

[111] Therefore it is accompanied by substantial difficulties to find an adequate CF for meat or 

edible products from slaughtered animals (see Tables 4 and 9). Various authors used different 

bases to calculate CF for products from slaughtered animals. Williams, et al. [104] estimated the 

killing out percentages for beef and poultry with 55 and 70% and 72, 75 and 77% for pigs with 

final body weights by 76, 87 and 109 kg resp. Lesschen, et al. [109] used fixed values to calculate 

the carcass fraction from the final body weight of animals (e.g., 58% for beef; 75% for pork and 

71% for poultry). Most authors used a fixed fraction of 0.9 for all animal species for conversion of 

carcass weight to edible meat.  

 

Beef 

The ruminant sector contributed to about 29% of the global meat production, but 5.7 Gt CO2-

eq representing about 80% of the global livestock emissions per year come from all ruminants (see 

Table 2; [66]. The large range in CF comparing results of various authors, depending on many 

influencing factors, is shown in Table 10 for beef. The values are much higher than those for milk 

(compare Tables 7 with 10) and are influenced by body weight gain, feed production with or 

without LUC, feeding and keeping of animals as well as system boundaries. The calculation base 

for the output of growing animals is more difficult (see Tables 8 and 9) than calculating it for milk 

or eggs (see Table 4). In dependence on the calculation base, the authors found a high variation in 

CF of beef. The highest values are given for beef cows (Table 10). In general, all of the results, 

e.g., [111]; [123]; [108], [66], indicate that policies which are targeted at improvements in 

productivity and efficiency of resource use will result in a lower GHG-emission or lower CF per 

unit of product. In the case of beef production, about 15% of total emissions are associated with 

the expansion of grassland (LUC) from forests [66]. 

 

Pork 

The pig sector contributes with 37% to global meat production, it will grow by 32% during 

the period 2005-2030 [67]. Only 0.7 Gt CO2-eq per annum representing about 9% of the livestock 

sector´s emissions comes from pigs (see Table 2; [67]. The main emission sources from global pig 

supply chains are feed production (60%) and excrement management (27%). The remaining 13% 

arises from post-farm processing, transport, enteric fermentation and indirect energy use in pig 

production [67]. 13% of the total emissions arise from LUC driven by increasing demand for feed 

crops (e.g., forest into arable land). MacLeod, et al. [67] compared the results of 14 studies with 

pigs from Europe, North America and Australia and found a range in emissions between 2.01 and 

6.36 kg CO2-eq/kg carcass weight. Later, the same authors adjusted all studies to the same scope 

according to FAO-rules and calculated values between 3.34 and 6.37 without LUC and values 

between 4.71 and 9.85 kg CO2-eq/kg carcass weight with LUC. Tan, et al. [124] analysed three 

case studies from Australia and Canada and found similar results (4.5 kg CO2-eq per kg pork). 



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Table-10.  Examples for CF (kg CO2-eq/kg carcass weight gain) of beef cattle in dependence on type of production by 

various authors 

Type of production/farming Authors 

Country Conventional Organic  

Germany 8.5 29.0 (beef cow) [146] 

Germany 8.7/10.1 10.2 [118] 

Australia 9.9 
(grain finished) 

12.0 
(grass finished) 

[111] 

Global 10 
(intensive – dairy beef) 

32 – 40 
(organic – suckler beef) 

[126] 

Germany 13.3 11.4 [121] 

Germany 15.2 17.5 [147] 

UK 15.8 18.2 [104] 

Ireland 23.6 20.2 [113] 

Global 24.5 20.9 [148] 

Without differentiation conventional/organic 

Germany 
 

5.6 (6000) – 14.6 (10 000 kg milk per cow 
per year; without allocation)          

[134] 

Canada 5.9 – 10.4 [136] 

Germany 7.0 – 23.0 [130] 

Germany 8.4 (Fattening of calves from dairy cows) 
16.8 (Fattening of calves from beef cows) 

[119] 

Sweden 10.1 [149] 

Ireland 13.0 (11.3 – 15.6) [113, 114] 

EU 16.0-19.9 
27.3 (suckler herd) 

[55] 

Norway 17.7 – 18.4 
Combined milk/meat; expanded boundaries 

[139] 

Global 15.6 (Fattening of calves from dairy cows) 
20.2 (Fattening of calves from beef cows) 

[8] 

Japan 19.6 [150] 

Japan 36.4 (beef cows, fattening bulls; 40% meat yield) [151] 

5 studies, literature 
review 

32 [152] 

Global; beef 
buffalo 
small ruminants 

46.2 
53.4 
23.8 

[66] 

 

All values mentioned above are much lower than data from beef (see Table 10). The main 

reasons for this are the enteric methane production in ruminants and the low growth intensity of 

beef cattle (mostly <0.5% weight gain per day of body weight) compared with pigs (mostly >1% 

weight gain per day of body weight; see also Table 10). 

 

Poultry (Meat and Eggs) 

Chickens meat accounts to about 24% to the global meat production. The global demand for 

chicken meat and chicken eggs are forecasted to grow by 61 and 39%, resp., during the period 

2005-2030. Chickens are estimated to emit 0.6 Gt CO2-eq per year, representing about 8% of the 

livestock sector`s emissions (see also Table 2; [67]. In the case of chicken meat on the global 

scale, 78% of emissions come from feed production and only small amounts directly from farm 

energy use (8%), processing and transport of meat (7%) and excrement management (6%; [67]. 

Some authors did not consider emissions from LUC where it occurs. In such cases about 21% of 

poultry meat emissions and 13% of egg emissions came from LUC through the conversion of 

forest into arable land; [67]. These authors compared the emissions of 18 studies with broilers 



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from Europe, North America, Brazil and Australia and found a range between 1.30 and 5.53 kg 

CO2-eq/kg carcass weight. Later, the same authors adjusted all studies to the same scope according 

to FAO-rules and calculated values between 1.89 and 5.00 without LUC and values between 1.93 

and 7.71 kg CO2-eq/kg carcass weight with LUC. Tan, et al. [124] calculated 2.9 kg CO2-eq/kg 

meat in three case studies on chicken from Brazil and Finland. The most important influencing 

factors of CF of broilers are the feed amounts needed per weight gain (feed conversion rate) and 

the feed transport [125]. The land-use change should not be neglected.  In the case of eggs, feed 

production contributes to 69% and direct on farm energy use to 4%, post-farm processing and 

transport 6%, the rest of the emissions (about 20%) is manure storage and processing (excrement 

management; [67]. Pelletier, et al. [126] came to a similar assessment after analysis of egg 

production in the Midwestern United States. Composition of eggs is well defined, but it may vary 

between various sources and in dependence on animal breed, feeding of animals and other 

influencing factors (see Table 11). The yield can be measured as weight (kg, etc.) or on the basis of 

standardized products (e.g., standardized protein, fat, dry matter or energy). Therefore analysis of 

egg composition (protein; fat) may contribute to a more specific measuring of the animal yield 

incl. the energy yield. Eggs may be entirely used as food (except small amounts for egg shells; see 

Table 11). 

In conclusion, growing intensity, laying performance, feed conversion rate (FCR), healthy 

animals and low animal losses are the key determinants of the emission intensity per kg food of 

animal origin from non-ruminants (pork, broiler meat and eggs).  

 

3.3. CF of Aquaculture and Further Protein Sources 

Aquaculture is a strongly upcoming way to produce food protein of animal origin. Recently 

some authors tried to determine CF for various forms of aquaculture. Mungkung, et al. [127] 

carried out a case study of combined aquaculture systems for carp and tilapia. The studied system 

included fingerling production in hatcheries, fish rearing in cages and transport of feed as well as 

that of harvested fish to markets.Avadi and Freon [28] reviewed 16 LCA-studies applied to 

fisheries and considered in the comparison the following aspects: scope and system boundaries, 

functional unit allocation strategies for co-products, conventional and fishery specific impact 

categories, fuel use, impact assessment methods, level of detail of inventories, normalisation of 

results and sensitive analysis. Fishery-specific impact categories and fuel use in fishing operation 

were identified as the main contributors to environmental impact. Nijdam, et al. [56] analysed 18 

and 11 studies for seafood from fisheries and agriculture resp. The authors summarized CF 

between 1-86 for seafood from fisheries and 3-15 kg CO2-eq for seafood from agriculture resp. 

These authors also [28] define the need for a standardisation of fisheries LCA research for further 

studies on sustainability of seafood and fisheries-based agrifood. Apart from milk, meat, fish and 

eggs, other sources of protein of animal origin, such as wild animals and insects, are also 

consumed by humans. Nothing is known about CF of food from wild animals. Insects and their 

larvae are used in many countries. They are rich in protein (20 – 70%) and contain considerable 

amounts of fat (10 – 50% of dry matter; [8, 128]. More than two billion people include processed 



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insects in their diets [8]; [129]. Experts assess [129] that about 1900 insect varieties are used as 

food and feed. The feed conversion of insects could be better than in ―traditional‖ animals and 

lower CF are expected, but more research in these fields, and also concerning feeding and feed 

supplementation with insects is required [8]; [130]; [131]; [132]. 

 

4. CF FOR EDIBLE PROTEIN OF ANIMAL ORIGIN 

The production of protein of animal origin is one of the most important goals of animal 

husbandry [54]; [109]; [110]; [56]. On the other hand, the efficiency and the emissions of food 

of animal origin can be also compared on the basis of edible protein. The N or protein (N x 6.25) 

content of various food of animal origin may vary from values used for calculations in Table 11. 

These data do not substantially disagree with values from human food tables [133]. Nijdam, et al. 

[56] used 160-200 g protein per kg food for seafood from fisheries and 170-200 g protein per kg 

food for seafood from agriculture for the calculation of CF. 

 

Table-11. Protein content of some edible animal products by various authors (in g per kg edible product) 

 References 

Product [144] [162-165] [161] [166] [109]1) [56] 
Cows’ milk 34 34 33.3 

(30.8-37.0) 
34 34.4 35 

Beef 190 170-200 2202) 
(206-227) 

206-212 206 200 

Pork 150 157 
(129-178) 

2202) 
(195-240)  

183-216 156 200 

Poultry meat 200 n.d. 199 182-242 206 200 
Eggs 120 121 

(110-124) 
125 125 119 130 

1) N-content x 6.25; 2) Muscle only; n.d.: no data  

 

Under consideration of various influencing factors such as animal yields, feeding, edible 

fractions and protein content in the edible fractions, the yield of edible protein per day and per kg 

body weight of animals is given in Table 12. The feeding may influence the CF of food of animal 

origin. In the case of ruminants, higher amounts of concentrate are required with higher animal 

yields. The proportion of co-products, e.g., [121]; [119] used in animal nutrition not only has 

nutritional implications, but it also affects the results of calculations on land use [134]. There are 

large differences in animal protein yield per animal per day, or per kg body weight and day, 

depending on animal species and categories as well as their performances and the fractions 

considered as edible (see Table 12). 

Table 12 shows the highest protein yields per kg body weight for growing broilers as well for 

laying and lactating animals, and the lowest values for growing/fattening ruminants. Based on 

those values, emissions per kg edible protein are given in Table 13. Higher portions of edible 

fractions or higher protein content may increase the protein yield and reduce the CF per product. 

At high levels of performance there are remarkable differences in CO2 emissions due to a human 



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consumption of 1 g protein from food of animal origin (eggs and meat from poultry < pork < milk 

< beef, see Table 13). 

 

Table-12. Influence of animal species, categories and performances on yield of edible protein [122] 

Protein source 
(Body weight) 

Performance 
per day 

Dry 
matter 
intake 
(kg per 
day) 

Roughage 
to 
concentrate 
ratio (on 
DM base, 
%) 

Edible 
fraction 
(% of 
product 
or body 
mass) 

Protein in 
edible 
fraction 
(g per kg 
fresh 
matter) 

Edible 
protei
n 
(g per 
day) 

Edible 
protein 
(g per 
kg 
body 
weight) 

Dairy cow (650kg) 10kg milk 
20kg milk 
40kg milk 

12 
16 
25 

90/10 
75/25 
50/50 

95 34 323 
646 
1292 

0.5 
1.0 
2.0 

Dairy goat (60kg) 2kg milk 
5kg milk 

2 
2.5 

80/20 
50/50 

95 36 68 
170 

1.1 
2.8 

Beef cattle (350kg) 500g1) 

1000g1) 

1500g1) 

6.5 
7.0 
7.5 

95/5 
85/15 
70/30 

50 190 48 
95 
143 

0.14 
0.27 
0.41 

Growing/fattenin
g pig (80kg) 

500g1) 

700g1) 

1000g1) 

1.8 
2 
2.2 

20/80 
10/90 
0/100 

60 150 45 
63 
81 

0.56 
0.8 
1.0 

Broiler (1.5kg) 40g1) 
60g1) 

0.07 
0.08 

10/90 
0/100 

60 200 4.8 
7.2 

3.2 
4.8 

Laying hen (1.8kg) 50%2) 

70%2) 

90%2) 

0.10 
0.11 
0.12 

20/80 
10/90 
0/100 

95 120 3.4 
4.8 
6.2 

1.9 
2.7 
3.4 

1)Weight gain, 2)Laying performance 

 

Table-13. Influence of animal species, categories and performances on emissions (per kg edible protein, own calculations 

on the base of data from Tables 11 and 12, see [110] 

Protein source 
(Body weight) 

Performance 
per day 

N-
excretion 
(% of 
intake) 

Methane 
emission 
(g per 
day)3) 

Emissions in kg per kg protein  

 
   P 

 
   N 

   
CH4

3) 

 
  CO2-eq 

Dairy cow (650kg) 10kg milk 
20kg milk 
 
40kg milk 

75 
70 
 
65 

310 
380 
 
520 

0.10 
0.06 
 
0.04 

0.65 
0.44 
 
0.24 

1.0 
0.6 
 
0.4 

30 
16 
 
12 

Dairy goat (60kg) 2kg milk 
5kg milk 

75 
65 

50 
60 

0.08 
0.04 

0.5 
0.2 

0.8 
0.4 

20 
10 

Beef cattle (350kg) 500g1) 

1000g1) 

1500g1) 

90 
84 
80 

170 
175 
180 

0.30 
0.18 
0.14 

2.3 
1.3 
1.0 

3.5 
1.7 
1.2 

110 
55 
35 

Growing/fattening 
pig (80kg) 

500g1) 

700g1) 

900g1) 

85 
80 
75 

5 
5 
5 

0.20 
0.12 
0.09 

1.0 
0.7 
0.55 

0.12 
0.08 
0.05 

16 
12 
10 

Broilers (1.5kg) 
 

40g1) 

60g1) 

70 
60 

Traces 0.04 
0.03 

0.35 
0.25 

0.01 
0.01 

4 
3 

Laying hen (1.8kg) 50%2) 

70%2) 
90%2) 

80 
65 
55 

Traces 0.12 
0.07 
0.05 

0.6 
0.4 
0.3 

0.03 
0.02 
0.02 

7 
5 
3 

1)Weight gain  2)Laying performance  3)CH4-emission depending on composition of diet 

 



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Nijdam, et al. [56] analysed 52 LCA-studies (Table 14) and summarized CF per kg product 

and per kg edible protein of animal origin. The results indicate that large differences exist 

between the studies and the products. The outcomes for milk, pork, poultry meat and eggs show 

much more homogeneity than those for beef, mutton, lamb and seafood. This is largely because of 

the very wide variety in production systems of the last food groups. Meat from non-ruminants has 

a lower CF than those from ruminants because methane is the main contributor to CF in 

ruminants. Because of too low values for feed production and processing (see Tables 5 and 6), 

most values shown in Table 13 are considerably lower than data given in Table 14. 

 

Table-14. Carbon footprints of protein of food of animal origin according to several LCA studies summarized by Nijdam, 

et al. [56] 

Protein source  (studies)                      kg CO2-eq per kg product          kg  CO2-eq per kg 
protein 

Cow milk (n = 14) 1 - 2 28-43 
Beef, Intensive system (n = 11) 
Meadow, suckler herds (n = 8) Extensive 
pastoral systems (n = 4) 

9 – 42 
23 – 52 
12 - 129 

45-210 
114-250 
  58-643 

Mutton and Lamb (n = 5) 10 - 150   51-750 
Pork (n = 11) 4 - 11    20-55 
Poultry meat (n = 5) 2 - 6    10-30 
Eggs (n = 5) 2 - 6    15-42 

Seafood from fisheries (n = 18) 1 - 86      4-540 
Seafood from agriculture (n = 11) 3 - 15     4-75 

 

Apart from protein, food of animal origin also contains other main nutrients (fat and lactose 

in the case of milk; fat in the case of meat and eggs), which contribute to human nutrition and 

which may replace energy of plant origin in human food. But at this point it has to be emphasized 

that this protein intake is accompanied - willingly or not - by an energy intake from the protein 

itself. Therefore, the exclusive attribution of the CO2 burden to the protein fraction ("edible 

protein") should be avoided. To prevent this fact from being neglected, there are different 

alternatives. In a first simple method, the CO2 emissions due to 1 kg edible protein could be used 

as CO2 burden of consumed energy (for example: 1 kg edible protein of eggs corresponds to about 

8 kg egg, corresponds to 51.6 MJ energy; this combined intake is related to a certain amount of 

CO2-eq). "Nutritional allocation" and/or ―economic allocation‖ [135]; [136]; [106]; [137]; [28]; 

[138] may distribute CO2 emissions to different functions of the food, but should not be discussed 

in the present paper.  

 

5 CHALLENGES FOR LOWER METHANE EMISSIONS AND REDUCTION 

POTENTIALS 

Numerous factors contribute to the greenhouse gas emissions by animals. Developing 

strategies to reduce emissions offers the potential to increase production efficiency and to reduce 

the impact of animals on the environment. Most attention has been spent to reduce the methane 



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© 2015 Conscientia Beam. All Rights Reserved. 

production in ruminants as summarized recently by Hristov, et al. [88]. Methane reduction 

potentials will be considered in the following subchapters. 

 

5.1. Plant Breeding 

Plant breeding can be considered as the starting point of the food chain (see [139]; [140]. 

Traditional breeding, as well as ―green‖ biotechnology or green chemistry [11], may result in 

changing of composition and nutritive value of feed plants. Lower fibre content and higher 

digestibility of plants may reduce methane emission from the rumen. Presently, special attention 

is given to the adaptation of plants to expected climate changes, e.g., [141]; [142]; [143]; [144] 

and to improving their yield and the nutritive value for global food security [145].  

Genetically modified plants may contribute to achieving these objectives (see [146], but are 

presently under critical public discussion. Nutritionists distinguish genetically modified (GM) 

plants into plants of the first and second generation. This designation is purely pragmatic or 

historical; it does not reflect any particular scientific principle or technological development. 

The first generation of GM plants is generally considered to be crops carrying simple input 

traits such as increased resistance to pests or tolerance against herbicides. Other inputs, such as 

more efficient use of water and/or nutrients, or an increased resistance against heat and drought, 

are not expected to cause any substantial change in composition and nutritive value. The newly 

expressed proteins that confer these effects occur in GM-plants in very low concentrations and do 

not change their composition or feeding value significantly when compared with isogenic lines. 

GM-plants of the so-called second generation (or plants with output traits or substantial 

changes in composition) are being developed with specific benefits for the consumer or the 

animals. Such biofortified crops contain higher amounts of desirable nutrients/substances such as 

proteins/amino acids, specific fatty acids, minerals, vitamins, enzymes, antioxidative substances, 

etc., or lower contents of undesirable substances, such as fibre/lignin, phytates, glucosinolates, 

mycotoxins, etc., [147] give a review about new events of GM crops in the pipeline as feed for 

animal nutrition. Adequate feeding studies for the nutritional assessment of such feed of the 

second generation of GM crops are required. 

Attention should be also devoted to changes in plant/feed composition in consequence of 

traditional plant breeding. 

 

5.2. Feed Production, Harvesting, Storing and Processing 

About 10 to 80% of GHG-emissions of animal husbandry come from feed production (see 

chapters above; lower values for ruminants, higher values for non-ruminants). 

Feed production contributes to GHG-emissions by land uses changes (LUC; e.g., change of 

forest into cropland or pasture with the consequences of high CO2-emissions; see [67], by N2O-

emission in consequence of fertilizing the soil and by CO2 from burning of fuel by machinery on 

the field, during harvesting and further processing of feed before feeding. 

Reduction of post-harvest losses and losses during feed storage can be considered as an 

important contribution to lower CF per feed unit [11] 



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More details and reduction potentials of GHG during feed production, harvesting, storing 

and processing incl. production of mixed feed for animals have been described by many authors, 

e.g., [121], [148] and his team; [108]. 

 

5.3. Feeds  

The high portion of GHG-emission in non-ruminants comes from feed production (see 

Chapters 3.2 and 5.1). Therefore, an effective use of feeds and the partial replacement of feeds by 

co-products of agriculture, food and bio-fuel industry may contribute to reducing CF for food of 

animal origin. The reduction of feeds in animal nutrition, which can also be used in human 

nutrition (such as cereals, beans, oilseeds etc.), would also be a real challenge for animal feeding 

[149]. 

Apart from roughages and concentrates, co-products from agriculture, such as cereal straw, 

e.g., [150]; [151], but also from food production, e.g., [152]; [153] and the biofuel-industry 

[119] are commonly used in animal feeding.  

Co-products are by-products of main processes such as grain production (e.g., straw, stalks, 

husks), processing of raw products in the food industry (e.g., extracted oil meals from the oil 

industry, bran from the cereal processing; beet pulp or bagasse from the sugar industry; animal 

co-products from milk, fish or meat processing) or from the biofuel industry (e.g., Distillers Dried 

Grains with Solubles (DDGS); rape seed cake/meal or rape seed extracted oil meal as well as 

cakes and meals from other oil seeds). According to the FAO [8], between 10 and 50% of the 

estimated concentrate feed comes from co-products in various global regions [117]. In some 

countries, up to 100% of concentrate may base on co-products.  

Co-products are used in various amounts and proportions in animal diets. Cereal straws and 

other co-products rich in plant cell-walls are mostly characterized by a low digestibility and are 

thus poor in energy and protein delivery to the animal. They are fed to ruminants with low animal 

yields or to meet their maintenance requirements. For high yielding ruminants they can only be 

considered as a source of fibre. Normally, they are not used in the feeding of non-ruminants.  

The importance of co-products of the food and biofuel industry as feed for animal nutrition 

will increase during the next few years [119]. Co-products from the food and fuel industry 

contain two to three times as many nutrients, which are not removed by processing (e.g., protein 

in the case of DDGS). They can be used as valuable sources of protein, minerals and other 

nutrients depending on the source material and the chemical or physical processing without any 

land-footprint. In the future more grains will be used for food and fuel and more co-products will 

be available for animal nutrition [131]. More details about the nutritive value and the utilisation 

of co-products from biofuel industry in animal nutrition were recently compiled by Makkar 

[119]. Co-products of agriculture and of industry are used to replace concentrates and roughage 

from grassland.  

In the future, we may expect some new developments in the field of co-products as animal 

feed. More people all over the world need more food and more energy. Therefore cereals, legumes 

and oilseeds will be used directly in larger amounts for human nutrition and will be more 



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© 2015 Conscientia Beam. All Rights Reserved. 

extracted during processing. That means that less concentrate and more extracted co-products 

will be available for animal nutrition. More analytical data are required for such co-products. The 

detoxification of substances rich in protein and energy would be also a challenge to increase the 

potential of feeds and co-products [131]. 

Kitchen refusals are still used in many countries in animal nutrition. Presently, the feeding of 

such refusals is not permitted in the European Union because for hygienical reasons. 

Because of the BSE-crisis (Bovine Spongiform Encephalopathy), the feeding of co-products 

from slaughterhouses (e.g., meat meal, blood meal, bone meal) has not been permitted in the 

European Union since 2001. Some research activities are underway for an efficient use of these 

valuable protein, energy and mineral sources in the future. 

 

5.4. Animal Feeding and Animal Yields (Productivity) 

One of the most important challenges to reduce the emissions per animal product is the 

increase of animal yields or an improved production efficiency [154]; [155]; [117] and in 

consequence, a reduction of animal numbers [156]. Investments in the productivity 

simultaneously result in reduced emission per unit of product as exemplarily shown in Table 15 

and Figure 1 for the milk production. 

The level of feed intake of animals is one of the most important prerequisites for animal 

yields. The higher the feed intake, the higher the portion of energy and nutrients available for 

animal performance, as shown in Table 15 for milk  

 

Table-15. Model calculation to show the influence of dry matter intake (DMI; 7.0 MJ NEL/kg DM) of dairy cows (body 

weight: 650 kg; 4% milk fat; [157] on energy intake, percentage of energy for maintenance and milk yield, energy per kg 

of milk as well as emissions per kg of milk [91] 

Dry Matter Intake (DMI, kg per day) 10 15 20 25 30 
Energy intake (MJ NEL per day) 70 105 140 175 210 
Energy requirement for maintenance (37.7 MJ 
NEL per cow per day; % of total NEL-Intake) 

53.9 35.9 26.9 21.5 18.0 

Energy requirement for milk production (3.3 MJ 
NEL per kg) 

9.8 20.4 31.0 41.6 52.2 

Net energy per kg milk (MJ NEL per kg milk) 7.1 5.1 4.5 4.2 4.0 
Methane emission1) 

(g per day) 
(g per kg milk) 

 
240 
24.5 

 
360 
17.6 

 
480 
15.5 

 
600 
14.4 

 
720 
13.8 

Carbon footprint (g CO2eq per kg milk)2) 825 605 530 495 475 

1) according to Flachowsky and Brade [78]: 24g CH4 per kg DMI for all diets 

2) calculated on the basis of the greenhouse potential of CH4 (x 23) and the calculations by Dämmgen and Haenel [112] 

 

Similar trends can be seen in milk yield per year and emission per kg FPCM (Figure 1). The 

average of CF for the whole herd can be reduced after elimination of cows without milk or with 

very low milk yields. 

 



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38 
© 2015 Conscientia Beam. All Rights Reserved. 

 
Figure-1. Emission intensity (CF kgCO2eq) in dependence of milk yield of cows (kg/year; by Gerber, et al. [117]; Opio 

[73] 

 

5.5.  Rumen Fermentation and Methane (CH4) Emission 

Some possibilities for the reduction of methane mitigation, such as increasing forage 

digestibility and digestible forage intake, dietary lipids or concentrate portions in the ruminant 

diets [158]; [159]; [160], as well as the application of various feed additives are shown by some 

authors, e.g., [161]; [162]; [108]; [163]; [164] (Table 16). 

 

 

Table-16. Feed measurements to reduce enteric methane emissions, importance on farm level and research need in 

ruminants 

Measurements Significance (esp. for Europe) on 
farm level 

Research Need 

More concentrate, less fibre in the 
diet 

Limited, because of high amounts 
already in many diets 

~ 

Forages with high digestibility, 
low fibre content 

Consideration in plant breeding 
and practical feeding 

 

Fats and fatty acids in the diets 
 

Limited, because of some side 
effects in the rumen 

 

Application of feed additives   

Halogen compounds (e.g., 
chloral hydrates) 

Banned in the EU  ~ 

Ionophores (e.g., monensin) Banned in the EU   
Addition of hydrogen 
acceptors, such as fumaric 
acid, acrylic acid etc. 

Presently no significance  

Addition of phytogenic 
substances (essential oils; 
plant extracts or plants 
containing such substances;  
e.g., garlic, tannines, 
saponines) 

Presently no significance   

Addition of 3-nitrooxy-
propanol and other nitrooxy-
carboxylic acids 

Presently no significance   

Further additives, such as 
yeasts, enzymes, etc. 

Presently no significance  

 : High need; : Need; ~: less important 



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Enhanced animal productivity and feed efficiency with metabolic modifiers, such as growth 

hormones and ionophoric antibiotics [87], would reduce GHG emissions, but the applicability of 

these mitigation practices is limited to regions where the use of these substances is permitted. 

Appuhamy, et al. [165] analysed the methane reduction potential of the ionophoric substance 

monensin via meta-analysis. Data from 22 controlled feeding studies were used. The methane 

mitigation effects of monensin were small (12 or 14 g/d in dairy cows and beef cattle) when 

adjusted for the monensin dose. 

Hydrogen acceptors, such as fumaric acid, acrylic acid and further substances may also 

contribute to H2-binding in the rumen, but the in vivo effects are low and inconsistent, e.g. [166]; 

[167]. Many studies were done with phytogenic substances such as tannins, non-tannins, 

phenols, saponins, essential oils and whole plants or parts of plants, e.g., [168].  

Despite of limitations of dietary fat in the range of 5% in ruminant rations [169], caused by 

lower fibre digestion and modification of the microbial population, experiments with single fatty 

acids and rapeseed oil showed potential to decrease methanogenesis. In vitro incubation of 

ruminal fluid added with ricinoleic acid resulted in a decline of 28 % in methane production. A 

reason for that observation could be differential toxic effects on not know methanogens [170] 

New metatranscriptomic approaches applied to ruminal fluid (sequencing of the rumen 

microbiome) give new insight into the abundance of rumen microorganisms and their gene 

expression. A novel group of methanogens (Thermoplasmata archaea) was recently described 

using this approach. Thermoplasmata uses methylamine as a substrate for methanogenesis and 

rapeseed oil supplementation reduced the occurrence of these thermoplasmata and methyl-

coenzym M reductase. From these observations the authors concluded that thermoplasmata are a 

high potential target to reduce methane production in ruminants [171]. 

The development of new feed additives, mainly based on plant extracts to decrease methane 

production within the rumen, has attracted research activities over the last 20 years. The results 

remain variable and contradictory as summarized by Benchaar and Greathead [172]. The 

effectiveness of plants or plant extracts having a high content of saponins, flavonoids and tannins 

(see Table 16) varied depending upon the source, type and level of secondary metabolite present 

in the plant material. These may restrict the uptake and use of such phytogenic substances in the 

animal feeding market. The reasons for such restrictions may be related to several factors, 

including the lack of persistency of the effects when they are tested in vivo due to the adaptation 

of the microbial ecosystem, the variability of concentration of active compounds in plant extracts, 

the stability of the active substance within the rumen, and possible side effects that compromise 

overall rumen fermentation [173]. 

Most of the substances were tested in in vitro studies, they may have a potential to reduce 

methane emissions from ruminants although their long-term effect has not been well established 

and some are toxic, or may not be economically feasible. Impressive results of in vitro studies were 

mostly not repeated under in vivo conditions. Therefore, [174] proposed a five-stage programme 

to evaluate the effects of such additives under special consideration of phytogenic substances: 

1. Botanical characterization of the plant(s) and their composition 



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2. Analytical characterization of the active phytogenic substance(s) 

3. in vitro studies to test effects of substances on rumen fermentation and methanogenesis 

(i.e., screening) 

4. in vivo studies (e.g., feed intake, rumen fermentation, CH4 emissions) 

5. Long-term feeding studies with target animal species/categories (e.g., animal health and 

performance, quality and safety of food of animal origin, environmental impact, 

adaptation of microbes). 

Another reason for the restricted use of phytogenic substances as methane inhibitors may be 

their unclear transfer from feed into food of animal origin and possible residues in animal products 

and their effects in humans, e.g. [175]; [176]; [177]. 

The development of synthetic compounds with specific activities to influence metabolic 

pathways essential to ruminal archaea may overcome some restrictions of phytogenic compounds. 

Methyl-Coenzyme M reductase catalyses the last step of reduction of CO2 to CH4 by 

hydrogenotrophic methanogenic archaea [77]. 

In preliminary studies, e.g. [178]; [179]; [180, 181], some authors tested the effects of 

molecules, substituted at various positions with at least one nitrooxy group, as inhibitors of 

methyl-coenzyme M reductase, such as nitrooxy-propionate compounds on the ruminal 

fermentation and the methane emissions. These substances are able to reduce the final step of CO2 

to CH4 by methanogenic archaea [182]. [183] studied the effect of ethyl-3-nitroxy propionate 

(E3NP) and 3-nitrooxypropanol (3NP) in vitro and in vivo in non-lactating sheep on ruminal 

methane production, fermentation pattern, the abundance of major microbial groups, and feed 

degradability. The in vitro batch culture trial tested 2 doses of E3NP and 3NP (40 and 80 µL/L) 

and found a substantial reduction of methane production (up to 95%) without affecting 

concentration of volatile fatty acids. In sheep methane production decreased by 29% in 

comparison with the unsupplemented control, without any effect on rumen dry matter 

degradation. 

Reynolds, et al. [184] tested effects of feeding of 0.5 and 2.5 g 3-nitrooxypropanol per cow 

and day on methane emissions, digestion and energy and nitrogen balance of lactating cows. The 

substance was administered through the rumen fistula. Daily methane production was reduced by 

3NP of 6.6 and 9.8% for 0.5 and 2.5 g/d, respectively. A homogenous mixing with feed or a 

sustained-release bolus may be more effective than application used in the present studies. 

Haisan, et al. [185] applied the additive by hand-mixing 2.5 g 3NP per cow and day into the 

total mixed ration (TMR) once daily and measured a reduction of methane emission of about 60% 

(from 17.8 to 7.2 g/kg dry matter intake). Dry matter intake of cows, milk yield and milk 

composition were not significantly affected by the additive, but the additive increased body weight 

gain (1.06 vs. 0.39 kg/d), indicating that the reduction of methane emissions increased energy 

availability to animals. The inconsistency in methane reduction in studies with dairy cows 

requires further experimental studies to understand the mode of action of 3-nitrooxypropanol in 

the rumen (see [174].  

 



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5.6. Excrement Management 

Anaerobic excrement storage may contribute to methane emission from the excreta. About 

18% of the global methane emissions from animal husbandry come from excreta [7]. Therefore, 

the excreta should be used as substrate in biogas fermenters [186] or stored in airtight 

containers. 

There are a number of animal and management practices that are feasible and can effectively 

reduce N2O emissions from manure storage and/or land application [92]. 

Optimizing the animal diet to improve N use efficiency and balancing N input with 

production level are important steps in reducing N2O emissions from the manure [187]; [188]. 

Due to the complex interaction between nutrition, production, animal health, and economic 

performance, diet modification to reduce N inputs should be done carefully to prevent reduced 

fibre digestibility and to maintain animal productivity [92]. 

 

5.7. Animal Keeping, Genetic and Animal Health 

Animal health, low animal losses, long periods of productive life of reproductive animals such 

as dairy cows, sows etc., a reduction in the number of ―unproductive‖ or low yielding animals and 

a feeding of animals according to species/categories as well as performances avoiding excess and 

deficiencies are general potentials for lower emissions with greenhouse potential. Some recent 

reviews analysed and summarized GHG-emissions during animal keeping,e.g., [189]; [190]; 

[191], animal feeding and management mitigation options [87, 88, 94]; [92]; [66]. In an 

excellent review [88] summarized non-CO2 GHG mitigation opportunities by:  

- Feed additives and feeding strategies 

- Manure handling strategies 

- Animal management strategies 

- Reproductive management strategies 

- Interactions among non-CO2 GHG. 

The authors assess the relative effectiveness, the input required to achieve desired effects and 

the applicability to regions. Improvement of Feed Conversion Rate (FCR) is one of the most 

efficient ways to reduce emission per kg animal product and to decrease CF. This statement is 

right for ruminants [66], non-ruminants [126] and aquaculture [127]; [192]. Special attention 

should be paid to the non-CO2-emissions.Improved genetics and animal health care as well animal 

management in combination with better reproduction and feeding (higher digestibility and quality 

of forages) and reduction the breeding overhead (i.e., animals kept to maintain the herd and old 

animals without lactation) may contribute to reducing emissions (esp. CH4) and CF [88]; [66]. 

[65] estimates that reducing the gap between livestock operations that generate high emissions 

vs. those that put out low emissions per unit of product could cut emissions by about 30 percent. 

Higher feed intake is a key element for higher animal yields, improved feed efficiency and 

lower emissions per product [91], see Table 15. Another possibility to increase feed efficiency and 

to reduce emissions per unit edible protein is an increase in protein content in food of animal 

origin. It is not easy to increase the protein content of milk by cattle breeding, but it would be an 



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© 2015 Conscientia Beam. All Rights Reserved. 

efficient measurement to reduce the GHG-emissions per kg milk protein as shown in a model in 

Table 17. Control cows should produce 9 000 kg milk per year with 3.4% protein (306 kg protein 

per year; 1 000 cows produce 306 t protein per year). Table 17 shows the consequences of protein 

rich milk on animal numbers, methane emissions and GHG-amount per year in order to produce 

306 t milk protein [193, 194]. 

 

Table-17. Required number of cows to produce 306 t milk protein in dependence on protein content of milk as well as 

methane emission from digestive tract, total GHG-emission and GHG-emission per kg milk protein [193, 194] 

kg milk 
per cow 
and year 

Milk 
fat (%) 

Milk 
protein 
(%) 

Required 
number 
of cows 

CH4 from 
enteric 
fermentation 
(t/year) 

GHG-
potential (t 
CO2eq/year) 

CO2eq per 
kg edible 
milk 
protein 

9 000 
9 0001) 
9 000 
9 000 
9 000 

4.2 
4.1 
3.7 
3.6 
3.4 

3.35 
3.40 
3.60 
3.65 
3.75 

1 015 
1 000  
945 
932 
907 

129 
126 
116 
114 
110 

4 522 
4 421 
4 046 
3 959 
3 790 

1.48 
1.44 
1.32 
1.29 
1.24 

1) Shown in bold type: basal variant for comparison (9 000 kg milk/year with 3.4% milk protein) 

 

In summary, the reduction of CF in ruminant production per product should focus on a 

lowering of methane emissions from enteric fermentation and an increase of low production levels 

as well a reduction of ineffective animal numbers [78]; [65]; [88, 94]. In the future, results of 

plant (see [146] and animal breeding (e.g. [91]; [195] may also substantially contribute to lower 

GHG emissions.  

 

6. CONCLUSIONS 

Global emissions from livestock are estimated at 7.1 Gt CO2-eq per year representing about 

14.5% of human-induced GHG emissions [65]. Beef and milk cattle, pigs for meat production as 

well as  poultry for meat and egg production contribute to 41, 20, 9 and 8% resp. of the total 

emissions. Feed production and processing and enteric fermentation from ruminants represent 45 

and 39% of the total emissions. 

Carbon Footprints may help to assess the GHG emissions associated with the production of 

food of animal origin. They may contribute to sensitizing producers and consumers to a more 

resource-efficient and environmentally-friendly production and consumption of food of animal 

origin and to avoiding food wastage [196]. 

Clear areas with high mitigation potential are the following: 

- Improving the feed production, esp. fertilization (N, manure), management and reduced 

LUC. 

- Reduction of post harvest feed losses, storing losses and losses and waste at food 

consumption [11]. 

- Improving feed supply, feeding practices and digestibility of diets. 



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© 2015 Conscientia Beam. All Rights Reserved. 

- Improving animal yields through genetics, animal health, feeding practices, animal 

management (incl. excrement management) and, in consequence, reduction of the 

number of low yielding animals. 

Differences in the calculated CF per kg product or per kg edible protein are obvious. 

Discrepancies in the results of various studies are explained by different system boundaries [197], 

allocation methods [137] and computation of emissions, especially with regard to land use 

changes, enteric methane and nitrous oxide emissions. 

A more standardized approach for CF-calculations would be very useful tool to provide an 

indicator for food labelling, to compare CF between production systems, regions and countries as 

well to assess the resource efficiency, esp. in non-ruminants. The high portion of methane in the 

CF of food from ruminants does not allow use of the CF of food from ruminants and non-

ruminants and conclude both food groups concerning feed efficiency.  

Therefore, some authors (e.g. [62]; [197, 198]; [59]; [199] analysed limitations of CF as 

indicator of environmental sustainability and recommended significant efforts in more dynamic 

modelling to ameliorate the problems of spatial variation and local environmental uniqueness. 

Furthermore, methodological problems must be solved [12] and more diverse researchers should 

be involved in such studies in order to improve the data basis. 

Reduction of methane emissions from ruminants and other emissions with greenhouse 

potential are a great challenge for all those involved in feed production and animal feeding. Some 

examples to do this are demonstrated in the paper. 

In summary, the production of food of animal origin is a very complex process and selective 

consideration, i.e., focussing on single factors, does not provide an assessment that reflects the 

complexity of the subject. 

 

Funding: This study received no specific financial support. 
 

Competing Interests: The authors declare that they have no competing interests. 
 

Contributors/Acknowledgement: All authors contributed equally to the conception and design of the study.  

 

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