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Enteric methane emission factors, total emissions and intensities from Germany's livestock in the late 19th century: A comparison with the today's emission rates and intensities

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In its climate protection law, Germany pursues the aim of achieving greenhouse gas neutrality by 2045. To approach this aim, the emissions from all sectors shall be reduced by 65 % by 2030 relative to 1990 and this includes mitigation of enteric methane (CH4) emissions from livestock. The enteric CH4 emission rate must be reduced to 853 kt CH4 by 2030, but if this target rate reaches the level of the pre-agroindustrial era remains to be evaluated. The present study aimed to determine enteric CH4 emission factors, emission rates and intensities for Germany in the 19th century. Historical data about animal numbers in the German Empire were normalized to Germany's current territory. Body weight and performance data of livestock were available for 1883 and 1892. By using Tier 1 and Tier 2 approaches we found that oxen and bulls had the greatest emission factors, followed by dairy cows and young cattle. The annual enteric CH4 emissions from livestock amounted to 898 kt in 1883 and 1061 kt in 1892. Thus, the 2030-emission target is set 45 kt below the emission level of 1883, and livestock in Germany has been emitting comparable amounts or less enteric CH4 since 2003 relative to 1892. Animal performance increased, and while CH4 emission intensities for meat and milk production decreased from 1883 to 1892, these values were higher than values from 1991 to 2020. Although the human population of Germany's current territory more than doubled in the last 130 years, increased gain in animal performance allowed for the reduction in the numbers of ruminants at least during the last 35 years, resulting in declining CH4 emissions. Such a strategy may also be applied by other countries with steadily increasing human populations to balance CH4 emissions and food production from livestock.
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Enteric methane emission factors, total emissions and intensities from
Germany's livestock in the late 19th century: A comparison with the today's
emission rates and intensities
B. Kuhla
,G. Viereck
Research Institute for Farm Animal Research (FBN), Institute of Nutritional Physiology Oskar Kellner, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
Research Institute for Farm Animal Research (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
Historic enteric CH
emission factors are
greatest for adult male cattle.
Enteric CH
emission from German live-
stock was 898 kt in 1883 and 1061 kt in
Compared to 1892, Germany's livestock
has been emitting less enteric CH
emission intensities for meat and
milk decreased from 1883 to 2020.
Animal performance gain reduced CH
emission intensities over the years.
Editor: Jay Gan
Body weight
Dry matter intake
Tier model
Meat production
Human population
In its climate protection law, Germany pursues the aim of achieving greenhouse gas neutrality by 2045. To approach
this aim, the emissions from allsectors shall be reduced by 65 % by 2030 relative to 1990 and this includes mitigation
of enteric methane (CH
) emissions from livestock. The enteric CH
emission rate must be reduced to 853 kt CH
2030, but if this target rate reaches the level of the pre-agroindustrial era remains to be evaluated. The present
study aimedto determine enteric CH
emissionfactors, emission rates and intensities forGermany in the 19th century.
Historical data about animal numbers in the German Empire were normalized to Germany's current territory. Body
weight and performance data of livestock were available for 1883 and 1892. By using Tier 1 and Tier 2 approaches
we found that oxen and bulls had the greatest emission factors, followed by dairy cows and young cattle. The annual
enteric CH
emissions from livestock amounted to 898 kt in 1883and 1061 kt in 1892. Thus, the 2030-emissiontarget
is set 45 kt below the emission level of 1883, and livestock in Germany has been emitting comparable amounts or less
enteric CH
since 2003 relative to 1892. Animal performance increased, and while CH
emission intensities for meat
and milk production decreased from 1883 to 1892,these values were higher thanvalues from 1991 to 2020. Although
the human population ofGermany's currentterritory more thandoubled in the last 130years, increased gain in animal
performance allowed for the reduction in the numbers of ruminants at least during the last 35 years, resulting in
declining CH
emissions. Such a strategy may also be applied by other countries with steadily increasing human pop-
ulations to balance CH
emissions and food production from livestock.
Science of the Total Environment 848 (2022) 157754
Corresponding author.
E-mail address: (B. Kuhla).
Received 7 April 2022; Received in revised form 14 June 2022; Accepted 28 July 2022
Available online 1 August 2022
0048-9697/© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC license (
Contents lists available at ScienceDirect
Science of the Total Environment
journal homepage:
1. Introduction
In its latest Assessment Report, the Intergovernmental Panel on Climate
Change shows that the average temperature of the Earth's atmosphere and
oceans increased by about 1.1 °C from 1850 to 2020 (IPCC, 2021). The rise
in temperature is undoubtedly due to anthropogenic activities associated
with increasing industrialization and accompanying emissions of greenhouse
gases. After carbon dioxide, methane (CH
) emissions make the second larg-
est contribution to global warming. Over the rst 20 years after release, CH
has 84-times more warming potential than CO
(IPCC, 2006). Its concentra-
tion in the atmosphere has dramatically increased since 1800 with the
highest growth rates between 1945 and 1990 (Etheridge et al., 1998).
Nowadays, roughly 42 % of the global CH
emissions are of non-
anthropogenic origin such as wetlands, oceans, lakes, and rivers whereas
the majority is emitted from anthropogenic sources, namely from activities
in the industrial (29 %) and agricultural (29 %)sectors (Knapp et al., 2014).
Two-thirds of the agricultural CH
emissions are released from enteric
fermentation processes of livestock, which amounts to 17 % of total CH
emissions in the beginning of the 21st century (Knapp et al., 2014). Global
emissions from livestock production have increased steadily at least
since the United Nations Food and Agriculture Organization (FAO) began
collecting statistics. While in 1961 the amount of CH
emitted globally
from enteric fermentation was 65.3 Mt, this had increased by 54 % to
100.8 Mt in 2019 (FAO, 2021). However, the emission rates in the individ-
ual regions of the world show quite different trends. While enteric CH
emissions are continuously increasing in Asia, Africa, and South America
since the early 1960s, they have been decreasing in Oceania and North
America since the mid-1970s and in Europe since the mid-1980s. At the
United Nations (UN) climate conference in Paris 2015, 180 countries
agreed to further reduce greenhouse gas emissions to meet the below
2 °C targetby the end of the 21st century.
In Germany, enteric CH
emissions declined from 1773 kt in 1985 to
964 kt in 2019 (FAO, 2021). Germany's national inventory reportsa decline
in enteric CH
emissions from 1313 kt in 1990 to 927 kt in 2020 (UBA,
2022). However, this decline was achieved, among other measures, pre-
dominantly by the reduction of farm animal numbers. For example, the
number of pigs, cattle, and sheep decreased from 36.8, 21.5, and 3.8 Mio
in 1985 to 26.1, 11.3, and 1.5 Mio in 2020, respectively (FAO, 2021).
The reduction in animal numbers without compromising food security in
the last 30 years was achieved due to increasing animal performance. For
example, from 1990 to 2020, milk production in Germany increased by
28 %, from 23.672 kt to 33.155 kt, and meat production by 15 %, from
7.194 kt to 8.291 kt, whereas the numbers of cattle, sheep, and pigs
decreased (Statista, 2021). This productivity gain was observed not only
in Germany, but also in other European countries (Gerber et al., 2011;
Dalgaard et al., 2011;O'Brien et al., 2015), and has been identied as a
major factor reducing CH
emission intensity, which is the ratio between
the amount of CH
produced per unit of animal-derived food (e.g. milk
or meat).
Germany pursues the aim of achieving greenhouse gas neutrality by
2045. To reach this aim, the emissions from all sectors shall be reduced
by 65 % by 2030 relative to 1990 (UBA, 2022). This means that the enteric
emission rate of livestock must be reduced to an annual emission rate of
853 kt CH
by 2030. The question here arises if this target emission rate
would reach the level of the pre-agroindustrial era, meaning the time
when agricultural activities contributed to the just started increase in
atmospheric CH
concentration. To answer this question, data about CH
emissions and animal productivities during the 19th century are required.
Thus, the aim of the present study was to collate historical data about live-
stock in Germany, and, based on these, to calculate enteric CH
factors of livestock and Germany's CH
emissions rate and intensity for
the end of the 19th century.
Knowledge about historical CH
emission factors may help developing
countries to more precisely estimate and inventory their past and current
emissions. For Germany, data about historical CH
emission rates and
intensities could serve to adjust the previously dened 2030-mitigation
target,highlight the importance of further efforts needed to continuously re-
duce enteric CH
emission rates, or direct priority to mitigate greenhouse
gas emissions released from sources other than livestock.
2. Materials and methods
First comprehensive counts of livestock species in Germany were con-
ducted in 1873 and thereafter. The livestock numbers in constituent states
of the German Empire without colonies (4 kingdoms, 6 grand duchies,
5 duchies, 7 principalities, and 3 Free and Hanseatic cities), counted on
10th January 1873, 13th January 1883, and on 1st December 1892, were
listed by the Imperial Statistical Ofce(Kaiserliches Statistisches Amt,
1874, 1884, 1894). Animal numbers for each of the years were calculated
for Germany's current territory to allow comparability with data gathered
in the 20th and 21st century. To this end, data from East-Prussia, West-
Prussia, Posen, and the imperial territory Alsace-Lorraine were excluded
for analysis. Furthermore, animal numbers of the historic provinces
Brandenburg, Pomerania, Silesia, and Schleswig-Holstein were multiplied
by 0.775, 0.603, 0.056 and 0.825, respectively, thereby accounting for
the area portion of these provinces in Germany's current territory, which
was for Brandenburg: 29,654 km
/38,274 km
= 0.775; Pomerania:
23,174 km
/38,401 km
= 0.603, Silesia: 2266 km
/40,335 km
0.056, and Schleswig-Holstein: 15,682 km
/19,018 km
= 0.825. Thus,
animal numbers from 37 subareas of the German Empire were available.
Because data for feed intake, energy intake, energy requirements or
milk constituents of farm animals were not available for the 19th century,
emissions from enteric fermentation was calculated rst by the Tier
1 approach using the default enteric fermentation CH
emission factors
(EF) published in Tables 10.10 and 10.11 by IPCC (2006). The default EF
for developing countries were used, which are valid for mules and asses
with a body weight (BW) of 245 kg (EF = 10 kg CH
/year), goats with a
BW of 40 kg (EF = 5 kg CH
/year), sheep with a BW of 45 kg (EF =
/year), horses with a BW of 550 kg (EF = 18 kg CH
/year), pigs
(EF = 1 kg CH
/year), bulls and young cattle (EF = 58 kg CH
and dairy cows with an annual milk yield of 2.550 kg (EF = 99 kg CH
year) as in some Eastern European countries.
Additionally, CH
emissions from enteric fermentation of cattle, horses,
pigs, and sheep subcategories were estimated based on a simplied Tier 2
approach as suggested by IPCC (2006). To this end, animal numbers and
corresponding BW data for calves (<6 weeks old), calves (between 6
weeks and 6 months old), young cattle (between 6 months and 2 years
old), cows and heifers (>2 years old), oxen and bulls (>2 years old), and
pigs (>1 year old) were obtained from the Imperial Statistical Ofce
(Kaiserliches Statistisches Amt, 1884, 1894). Furthermore, data about the
number of horses (>3 years old), foals (<3 years old), and sheep (<1year
old and >1 year old), but no corresponding BW data, were available
(Kaiserliches Statistisches Amt, 1884, 1894). Data regarding the BW of
horses, foals, and pigs (<1 year old) were available for Prussian districts
(Graf Fink von Finckenstein, 1960); the mean BW of the species were calcu-
lated for the districts Brandenburg, Saxony, Westfalia, and Rhineland and
applied to all German areas. Data for the mean BW of sheep between 5
and 6 months, 6 to 8 months, 8 to 11 months, and >1 year old were ob-
tained from Heinrich (1896) and Conradi (1897).
Based on the BW, dry matter intake(DMI) of cattle was calculated using
the simplied Tier 2 method as recommended by IPCC (2006).Briey, DMI
of oxen and bulls was computed according to Eq. 10.18a of IPCC (2006):
DMI ¼BW0:75 0:0119 NEma
where NE
is the net energy content of the dietto meet the energy require-
ments for maintenance, accretion of body mass (e.g. fat), and physical
work. The NE
content of the ration was assumed to be 6.8 MJ/kg DM,
which typically consists of moderate forage quality (Table 10.8 in IPCC,
2006) and concentrate to meet the requirements for medium-intensive
physical work (Heinrich, 1896).
B. Kuhla, G. Viereck Science of the Total Environment 848 (2022) 157754
The DMI of young cattle and calves was calculated according to
Eq. 10.17 of IPCC (2006):
DMI kgðÞ¼BW0:75 0:2444 NEma0:0111 NEma
assuming a NE
content of the ration of 5.5 MJ/kg DM. This value repre-
sents moderate forage quality (Table 10.8 in IPCC, 2006).
The DMI of dairy cows was calculated according to Eq. 10.18b of IPCC
DMI kgðÞ¼5:4BW=500ðÞ=100DE%ðÞ=100ðÞ,
assuming a feed digestible energy (DE) of 60 %. The DE value corresponds
to the weighted mean when ruminants are kept on pasture during the sum-
mer and fed medium quality hay, beets, potatoes, and some concentrate
during winter (Table 10.2 in IPCC, 2006;Heinrich, 1896;Conradi, 1897;
Klemme, 2003).
Methane production per head and day of calves (between 6 weeks and
6 months old), young cattle, oxen and bulls, and dairy cows was also calcu-
lated based on estimated DMI and BW according to Jentsch et al. (2007):
CH4kJ kg DM 1head1day 1
¼180221:1DMI=BW g=kg
considering a CH
energy content of 39.57 kJ/L and a density of 0.700 kg/
(at 1 bar and 7.5 °C, which was the average annual temperature in the
last two decades of the 19th century). The equation by Jentsch et al.
(2007) was used as it has been derived from 337 observations during
studies performed in Germany inmid-20th century, and because the EF pro-
posed by Dämmgen et al. (2012) is only valid for German cows producing
4700 to 7200 kg milk per year. Methane production of calves <6 weeks
old was calculated based on the data published by Tümmler et al. (2020),
with calves that had nearly ad libitum milk intake and a daily plant dry
matter intake of 100 g, which amounts to 1 kg CH
per head and year.
Thus, CH
emissions from calves with an age of <6 weeks were calculated
according to the Tier 1 method.
Similarly, as the CH
emission factors proposed by IPCC (2006) for
horses, swine, and sheep are only reliable for the given BW, CH
per head and day for horses, pigs, and sheep was calculated according to the
equations by Franz et al. (2010):
for horses :CH4Lhead1day1
¼0:18 BW0:97,
for pigs :CH4Lhead1day 1
¼0:07 BW0:99,
and for sheep :CH4Lhead1day 1
¼0:66 BW0:97:
In addition, because BW data for goats and mules and asses were not
available, enteric CH
production of these species was calculated by the
Tier 1 approach only. Annual CH
emission was calculated by multiplying
the number of animals of each area by the daily CH
emission multiplied
by 365. A normal distribution of animal numbers throughout the year
and within areas was assumed.
The calculation of CH
emission intensity was performed using milk
yield data published by Graf Fink von Finckenstein (1960) and Helling
(1965) for the late 19th century. Therein, the average milk production of
dairy cows in the Prussian districts of Brandenburg, Saxony, Westfalia,
and Rhineland was 1825 kg in 1883 and 2125 kg in 1892, and milk yield
in Bavaria was estimated as 2400 L/year during the last years of the 19th
century. Data about the production of beef and veal (426 kt in 1883,
562 kt in 1892), pork (567 kt in 1883, 736 kt in 1892), and sheep and
goat meat (85 kt in 1883, 86 kt in 1892) were calculated based on the
average consumption per person in the kingdoms Prussia and Saxony
(Esslen, 1912) and the number of persons who lived in Germany's current
territory (Kaiserliches Statistisches Amt, 1884, 1894).
In order to allow the comparison between historical and current emis-
sion levels, data about enteric CH
production in Germany in the 21st
century were obtained from UBA (2022),FAO (2021),andVos et al.
(2022). Milk production and meat production data since 1991 were
obtained from Statista (2021) and the German Ministry for Nutrition and
Agriculture (BMEL, 2021), respectively.
The mean and standard deviation (SD) was calculated, when appropri-
ate, for the 37 areas of the German Empire belonging to Germany's current
territory. Otherwise, no further statistical analysis was performed but data
were interpreted by descriptive statistics.
3. Results
The number of horses, cows, pigs, and goats continuously increased
from 1873 to 1893 whereas the number of mules and asses, other cattle,
and sheep decreased (Table 1). Using the Tier 1 approach, CH
from enteric fermentation of all livestock categories amounted to 1085,
1087, and 1133 kt CH
in 1873, 1883, and 1892, respectively. These
numbers, however, are only rough estimates; therefore, we next applied a
simplied Tier 2 model using BW data of livestock subcategories available
for 1883 and 1892.
From 1883 to 1892, BW of all livestock subcategories increased, and so
did DMI of dairy cows and other cattle (Table 2). Furthermore, the EF, ex-
cept for both pig subcategories and sheep older than 1 year, were lower
than the default-EF proposed for the Tier 1 approach (Table 3). Accord-
ingly, enteric CH
emissions from all livestock categories were lower than
the emissions calculated based on the Tier 1 approach only. Enteric CH
emissions from livestock increased from 898 kt in 1883 to 1060 kt in
1892 (Table 3) and were greatest in the four kingdoms and lowest in the
Hanseatic town Lübeck (Supplemental Table 1).
The entericCH
emission rate continuously decreased during the last 35
years (Fig. 1). Nonetheless, the 1892-level is higher than the annual enteric
emission rate published by the Federal Environmental Ofce (UBA,
2022) for 2003 and thereafter, as well as higher than the emission rate pub-
lished by FAOSTAT (FAO, 2021) for 2009 and thereafter. However, the two
emission levels in the late 19th century are above Germany's 2030-target
emission rate of 853 kt CH
per year (e.g., 65 % reduction relative to the
1990 emission level (UBA, 2022)).
While enteric CH
emissions increased from 1883 to 1892, agricultural
productivity did alike (see Materials and methods section). Accordingly,
emission intensities, except for pork, decreased in the same time and
further declined until 1991; however, CH
emission intensities for beef
and veal have been re-increasing since 1991 (Fig. 2A and B). As expected,
emission intensities are greater for beef, veal, and sheep and goat
Table 1
Number of animals and Tier 1 enteric CH
emissions from livestock categories
adjusted for Germany's current territory.
Animal category Number of animals (thousands)
Enteric CH
(kt × year
1873 1883 1892 1873 1883 1892
Horses 2063 2170 2373 37.1 39.1 42.7
Mules and asses 9.32 6.17 3.65 0.09 0.06 0.04
Pigs 5219 6593 9025 5.22 6.59 9.02
Cows 6689 6733 7343 662 667 727
Other cattle 5130 5258 5116 298 305 297
Sheep 14,603 11,714 8929 73.0 58.6 44.6
Goats 1948 2236 2529 9.7 11.2 12.6
Total 1085 1087 1133
Animal numbers for the German Empire (Kaiserliches Statistisches Amt, 1874,
1884, 1894) were curated for Germany's current territory not including the
Eastern territories (now belonging to Poland and Russia), the imperial territory
Alsace-Lorraine (now belonging to France), and Northern Schleswig (now belong-
ing to Denmark); and the area portions of Brandenburg, Pomerania, Silesia, and
B. Kuhla, G. Viereck Science of the Total Environment 848 (2022) 157754
meat, and are lower for pork and milk production, independent of the years.
Interestingly, enteric CH
emission intensityfor beef and veal production in
1991 was lower than it was for sheep and goat meat production in 1883
(Fig. 2A).
The production level of animal-derived food is closely associated with
the number of citizens of each country. Therefore, we next calculated the
annual enteric CH
-footprint per person. Despite increased animal perfor-
mance, the CH
-footprint per person in Germany's current territory slightly
increased from 1883 to 1892, whereas it decreased by 59 % until 2020
(Fig. 2C).
4. Discussion
4.1. Emission factors
Applying the Tier 1 approach for developing countries (IPCC, 2006)to
Germany's livestock population of the 19th century revealed that the
Table 2
Number and body weight of livestock subcategories as well as dry matter intake of cattle after normalization to Germany's current territory.
Animal subcategory Number of animals
Body weight (kg)
Dry matter intake (kg × day
1883 1892 1883 1892 1883 1892
>3 years old 1834 2089 440 ± 64 486 ± 102
Foals <3 years old 336.5 284.4 190 ± 12 201 ± 17
>1 year old 1469 2078 122 ± 24 125 ± 18
<1 year old 5098 6947 71 76 ± 16
>2 years old (oxen and bulls) 1151 1150 474 ± 62 516 ± 59 11.1 ± 1.1 11.6 ± 2.1
>2 years old (dairy) 6733 7343 390 ± 57 421 ± 54 10.5 ± 1.5 11.1 ± 2.2
<2 years old (all) 2361 3005 204 ± 29 229 ± 40 5.3 ± 0.6 5.6 ± 1.2
>6 weeks to <6 months old 873.3 961.4 93 ± 11 101 ± 15 2.9 ± 0.3 3.1 ± 0.3
<6 weeks old 532.4 416.0 51 ± 7 55 ± 6 0.1 0.1
>1 year old 8969 6419 43 43
<1 year old 2745 2529 28 28
Animalnumbers and body weight of animalsof the German Empire(Kaiserliches Statistisc hes Amt, 1884, 1894) were curatedfor Germany's current territory not including
the Eastern territories (now belonging to Poland and Russia), the imperial territory Alsace-Lorraine (now belonging to France), and Northern Schleswig (now belonging to
Denmark); and the area portions of Brandenburg, Pomerania, Silesia, and Schleswig-Holstein.
Data are given asmean ± SD; SD refers to the deviation of body weightand dry matter intake of animals kept in the 37 areas of the German Empire (see Supplementary
Table 1) belonging to Germany's current territory.
Dry matter intake (DMI) for oxen and bulls: DMI = BW
+ 0.1938)/NE, with net energy content of the ration (NE) = 6.8 MJ/kg DM; for young
cattle and calves: DMI = BW
× (0.2444 × NE 0.0111 × NE
0.472)/NE, with NE = 5.5 MJ/kg DM; for dairycows: DMI = (5.4 × BW/500)/((100 DE%)/100),
with digestible energy (DE) = 60 % (IPCC, 2006).
Table 3
Enteric CH
emission factors and total enteric CH
emissions from livestock subcat-
egories in 1883 and 1892.
Animal subcategory Enteric CH
(kg × head
× year
Enteric CH
(kt × year
1883 1892 1883 1892
>3 years old
16.9 18.6 30.9 38.8
Foals <3 years old
7.5 7.9 2.5 2.2
Mules and asses
10.0 10.0 0.06 0.04
>1 year old
2.1 ± 0.4 2.1 ± 0.3 3.0 4.6
<1 year old
1.2 1.3 6.2 9.1
>2 years old (oxen and bulls)
93.7 ± 10.3 100.2 ± 9.5 104.6 112.4
>2 years old (dairy)
83.8 ± 12.3 89.8 ± 10.1 550.2 667.6
<2 years old (all)
42.6 ± 5.1 46.9 ± 7.0 99.8 138.4
>6 weeks to <6 months old
21.5 ± 2.2 22.9 ± 2 18.9 22.0
<6 weeks old
1.0 1.0 0.5 0.2
>1 year old
6.5 6.5 58.1 41.6
<1 year old
4.3 4.3 11.7 10.7
5 5 11.2 12.6
Total 897.6 1060.3
SD refers to the deviation of enteric CH
emission factors between 37 areas of
the German Empire (Supplementary Table 1) belonging to Germany's current
emissions calculated based on body weights (simplied Tier 2 model) for
(L × head
) = 0.18 × BW
; for pigs: CH
(L × head
) = 0.07 × BW
(L × head
) = 0.66 × BW
(Franz et al.,2010); for oxen and bulls, dairy cows, young cattle, and calves between
(kJ × kg DM
180221.1 × DMI/BW (g/kg) (Jentsch et al., 2007).
Calculated according to IPCC Tier 1 model using the standard emission factors
for mules and asses (10 kg CH
/year), goats (5 kg CH
/year) (IPCC, 2006), and
calves <6 weeks (1 kg CH
/year; Tümmler et al., 2020).
Fig. 1. Enteric CH
emissions in Germany between 1961 and 2019 based on
FAOSTAT statistics (2021) (solid line) and between 1990 and 2021 based on
Germany's Federal Environmental Ofce (UBA, 2022) (dotted line). The horizontal
grey lines indicate the emission level in 1883 and 1892, respectively. Emissions
were calculated according to either the simplied Tier 2 approach for horses,
dairy cows, oxen and bulls, young cattle and calves (6 weeks to 6 months old),
pigs, and sheep, or the Tier 1 model for mules and asses, goats, and calves <6
weeks old.
B. Kuhla, G. Viereck Science of the Total Environment 848 (2022) 157754
enteric CH
emissions amounted to an average of 1123 kt between 1873
and 1892. Although this number was corrected for those parts of the coun-
try not belonging to Germany's current territory, it still underlies some un-
certainties. For example, the EF for horses provided by IPCC (2006)
assumes an average BW of 550 kg, but the mean BW of adult horses (>3
years old) in the last two decades of the 19th century ranged only between
440 and 486 kg. Thus, the default EF of 18kg/year is apparently slightly too
high to be meaningfully used for horses kept in the 19th century. On the
other hand, horses were intensively used as draft-animals, suggesting that
they consumed more feed per kg BW than in the late 20th and early 21st
century. The calculated EF of 16.9 kg CH
for the year 1883 and 18.6 kg
for the year 1892 therefore seem justied.
Furthermore, the default EF for sheep with a mean BW of 45 kgis 5 kg/
year, but the BW of sheep greater than a 1 year old was only 43 kg in the
late 19th century, suggesting again an overstatement of CH
with the Tier 1 approach. However, taking the feeding experiments
(Klemme, 2003) and feeding recommendations for sheep at the end of
the 19th century into account (Heinrich, 1896), in which not just pasture
and hay, but also concentrate feeding, particularly for lactating animals,
is recommended, a higher EF of 6.5 kg/year for a 43 kg-sheep is reasonable.
This EF may underestimate real CH
emissions because Pelchen and Peters
(1998) reported enteric emissions of 20.6 g CH
/d or 7.5 kg CH
/year for a
growing 40 kg sheep. However, both of these factors are lower than the de-
fault EF for sheep with a BW of 65 kg in developed countries (EF = 8 kg
/year) (IPCC, 2006).
The IPCC (2006) proposes a Tier 1 EF for pigs of 1 kg/year for develop-
ing countries and 1.5 kg/year for developed countries. In the current
German emission inventory an EF of 1.15 kg/year for pigs is applied
(Haenel et al., 2020). However, BW gain of fattening pigs steadily increased
in the 20th and 21st century (Haenel et al., 2020), although daily feed in-
take of fattening pigs is comparable between the late 19th and early 21st
century (Conradi, 1897;Heinze, 2011). Consequently, the amount of feed
consumed during the time of birth until slaughter, and thus CH
is much lower today than it was in the 19th century. In addition, in the 19th
compared to the 21st century, pigs were fed higher portions of roughage
feed, and thus crude bre, and sows were not restrictively fed in late gesta-
tion (Heinrich, 1896;Conradi, 1897); both factors increasing annual CH
emissions. Finally, BW at slaughter did not change from 1900 to 2021
(Statista, 2021), and thus the EF for pigs in the 19th century must have
been higher than they are today. Accordingly, the EF calculated based on
our simplied Tier 2 approach (1.2 to 2.1) seems to be reasonable.As a con-
sequence, the Tier 1 model underestimates annual CH
emissions from pigs
by 2.6 kt for 1883 and 4.4 kt for 1892 relative to the Tier 2 model.
The entericCH
emissions from mules and asses andgoats could only be
estimated using the default Tier 1 EF (IPCC, 2006) because of lack of histor-
ical data referring to BW, number of foals, or goat kids. Such data are still
rare today, and subsequently the German national emission inventory
uses a constant EF of 5 kg/year for goats and summarises the emissions
from mules and asses into the horsecategory (Haenel et al., 2020). Al-
though the latter approach certainly overestimates CH
emissions from
mules and asses, and although today's emissions from this animal category
is much lower than in the 19th century, they do not contribute much to the
total CH
emission from livestock.
By contrast, in 1883 and 1892 the cattle category contributed to the
total enteric CH
emissions by 89 % to 90 % (Tier 1 model), or 85 % to
88 % (Tier 2 model). Multiple data sources are required to conrm and se-
cure these emission estimates. While the number of animals in each cattle
Fig. 2. Methane emission intensities for beef and veal, sheep and goat meat (A),
pork and milk production (B), and methane emission per person (C) in Germany's
current territory in 1883 and 1892 as compared to 1991 until 2020. Emissions in-
tensities in the 19th century were calculated based on the numbers presented in
Table 3, and milk and meat production data published by Hoffmann (1965).
Emissions intensities between 1991 and 2020 were calculated based enteric CH
emissions published by Vos et al. (2022), milk and meat production by Statista
(2021) and BMEL (2021).
B. Kuhla, G. Viereck Science of the Total Environment 848 (2022) 157754
subcategory and their BW were available in high special resolution, the
actual DMI was not and had to be estimated based on BW. Oxen and bulls
ingested 11.1 kg DM/d at a BW of 474 kg and ingested 11.6 kg DM/d at
a BW of 516 kg. These data are not comparable to the DMI of modern
500 kg Simmental bulls consuming only 8.7 to 9.5 kg DM/d while reaching
an average daily gain of 1200 g (Gruber, 2014). One might assume that the
daily BW gain of male cattle in the 19th century was lower than 1.2 kg/day,
and thus, DMI per unit of BW would also be lower. However, in the 19th
century, oxen and bulls were intensively used as draft animals. For
middle-hard working animals, the daily organic matter (OM) intake
amounted to 24 kg, for heavily working animals to 26 kg OM, and for ani-
mals kept in tie-stalls to 17.5 kg OM per 1000 kg BW (Conradi, 1897). The
average of these calculates to 11.2 kg OM intake per day/500 kg BW. Con-
sidering that the OM intake misses the portion of mineral intake (and also
soil intake when on pasture), which is approx. 10 % of DMI, oxen and
bulls must have consumed rather 12.3 kg DM/d in the late 19th century.
Hence, the DMI of oxen and bulls calculated by the simplied Tier 2 ap-
proach is not overestimated. This conclusion is further supported by IPCC
(2006) reporting that the average enteric CH
emissions from other cat-
tle, e.g. bulls, growing steers, heifers, and calves, amounts to 58 kg/year
in Eastern European countries and to 57 kg/year in Western European
countries, and that the emissions from male cattle older than 2 years old
are much greater than from growing cattle and calves.
The average daily OM intake of 2 to 3 months old calves with a BW
of 75 kg was given as 1.65 kg/d, for 3 to 6 months old calves (BW =
150 kg) as 3.5 kg/d, and for young cattle (6 to 12 months old, BW =
250 kg) as 6 kg/d (Conradi, 1897). Having in mind again that the OM
intake does not include mineral intake, these data correspond well to the
calculated DMI of calves and young cattle based on the assumed average di-
etary net energy content (5.5 MJ/kg DM) and the IPCC (2006) equation.
Considering the CH
emissions from oxen and bulls, it seems that the
error of the estimated CH
emissions for the 19th century increases with in-
creasing BW of cattle. However, the average EF for oxen and bulls, young
cattle, and calves (6 weeks to 6 months old) calculates to 53 kg CH
1883 and 57 kg CH
in 1882, but these numbers are comparable with the
default EF for the category other cattlein Eastern and Western Europe
(IPCC, 2006).
Methane emissions from calves on milk, e.g. <6weeksold,canhardly
be assessed not at least because IPCC (2006) assumes a digestibility of
feed of 0 % for this subcategory. However, based on the given BW, the
enteric CH
emission from calves younger than 6 weeks old was estimated
according to the experimental data published in Tümmler et al. (2020).
Therein, the average daily DMI of solid feed of calves from birth until 6
weeks of life amounts to 0.1 kg, and daily CH
production of 6 weeks old
calves to 812 L/d. Based on these numbers an EF of 1 kg per calf (<6
weeks old) and year was deduced, but their contribution hardly affects
total CH
emissions from livestock.
By contrast, CH
emissions from dairy cows contributed most to total
emissions and small estimation errors have a tremendous impact on total
emissions. The default Tier 1 EF of dairy cows in Eastern Europe is 99 kg/
year while an average annual milk production of 2550 kg is assumed
(IPCC, 2006). Conversely, milk yield of dairy cows in the Prussian districts
of Brandenburg, Saxony, Westfalia, and Rhineland (Graf Fink von
Finckenstein, 1960) and in the Bavarian kingdom was much lower than
2550 kg per year in the late 19th century (Helling, 1965), suggesting that
the Tier 1 EF of 99 kg/year clearly overestimates real emissions. Following
our simplied Tier 2 approach, the EF fordairy cows was 84 kg in 1883 and
90 kg in 1892, which were lower than the default value from IPCC (2006),
but comparable to current EF for dairy cows in South Africa ranging
between 77 and 92 kg CH
/year (Tongwane and Moeletsi, 2020).
However, besides the level of milkproduction, BW and OM digestibility
are the primary factors determining DMI. In the present study, we assumed
an average of 60 % OM digestibility considering the reported feed stuff fed
in the 19th century (Klemme, 2003) and corresponding digestibilities rang-
ingbetween46and75%(Conradi, 1897;Heinrich, 1896). It has been re-
ported that dairy cows would consume 9.6 kg OM/400 kg BW in the late
19th century, but it remained unclear at which production level this intake
was achieved (Conradi, 1897). Assuming a dietary mineral content of 10 %
of DM, the 9.6 kg OM equals to 10.5 kg DM, which agrees to the DMI of
dairy cows calculated for 1883 and 1892. Moreover, extrapolating the
14.5 kg DMI of a 500 kg-dairy cow producing 4000 kg milk/year (Gruber
et al., 2001) to a 400 kg-dairy cow producing 2000 kg milk/year, results
in a DMI of 10.5 kg. Based on these numbers, we conclude that the use of
an EF of 84 kg in 1883 and 90 kg in 1892 for dairy cows seems to be appro-
priate. In addition, the EF for cattle were calculated using the equation by
Jentsch et al. (2007) and the appropriateness of this equation has been ap-
proved by Piatkowski et al. (2010), who predicted enteric CH
from German cattle to amount to 1036 kt in 2006, which corresponds
well to the FAO value of 1042 kt CH
that was emitted from whole German
livestock in the same year (FAOSTAT, 2021).
4.2. Total enteric CH
The enteric CH
emission level from Germany's livestock was proposed
to be >1500 kt in 1890 (Muylaert de Araujo et al., 2007), however, this
number is highly overstated, likely because animal numbers were not
corrected for the territory b oundaries and because inadequate default emis-
sion factors were used. After 1890 and until the mid-80s of the 20th cen-
tury, livestock numbers in Germany have steadily increased and their
contribution to the atmospheric CH
load was assumed to be 2.9 % of the
global enteric CH
emissions (Muylaert de Araujo et al., 2007). Due to the
reasons mentioned above this number is denitely overestimated. Our
calculations provide also evidence to the prediction of historic methane
emissions using an extrapolation modelling approach (Gütschow et al.,
2016), the latter estimating CH
emissions from the agricultural sector to
amount to 0.98 Mt in 1883 and 1.07 Mt in 1892.
In the 21st century, the enteric CH
emission rate in Germany (UBA,
2022) reached or felt below the 1892-value for the rst time since 2003.
However, the 2030-target emission rate of 853 kt CH
per year is below
the 1883-emission level. Thus, it remains to be examined in future studies
when in the 19th or 18th century the enteric CH
emission rate was equal
or lower than 853 kt. Hence, <10 % of the 1990 enteric CH
level remain to be reduced to meet the 2030-target rate. Although further
effort is needed to reach this aim (see suggestions below), focussing only
on the reduction of enteric CH
emissions may overlook the fundamental
importance of reducing CO
emissions as quickly as possible, because CO
emissions from oil and natural gas systems have been underestimated in
the past (Rutherford et al., 2021).
Historical studies have shown that global enteric CH
emissions started
to increase by at least 1860 (Stern and Kaufmann, 1996). In France, CH
emission from livestock were lower in 1852 than 1885 (Garnier et al.,
2019), suggesting that the increase in CH
emissions from livestock had al-
ready started in the middle of the 19th century or even earlier.
4.3. Productivity and enteric CH
emission intensities
Germany's current CH
emission rate can further be reduced, particu-
larly in view of its self-sufciency rate in milk, pork, and cheese production
amounting to 112 %, 120 %, and 121 %, respectively (Statista, 2021). Con-
sidering the emissions from individual livestock species in 2020 (Vos et al.,
2022), a further 20 % reduction in pig numbers would save 5 kt, and a
further 12 % reduction in dairy cow numbers would save 66 kt enteric
per year without jeopardizing self-sufciency or nutritional practices
related to milk and pig product consumption while falling below the
national 2030-target level. It is noteworthy that the German Empire had a
butter export surplus of 6.4 and 9.8 % in 1874 and 1884, respectively,
(Teuteberg, 1988), demonstrating that overproduction of some milk prod-
ucts had already begun in the late 19th century. At least some portion of
this overproduction was achieved by grain imports, mainly from Russia
(Mahlerwein, 2016). On the other hand, the German Empire imported
more beef than it had exported in the late 19th century (Lohheide, 2008).
Nowadays, Germany's self-sufciency rate in beef production is only 97 %
B. Kuhla, G. Viereck Science of the Total Environment 848 (2022) 157754
(Statista, 2021), and as such,Germany, like many other EU27countries, im-
ports food with one of the highest carbon footprints (Bellarby et al., 2013).
Many studies have shownthat a reduction in beefconsumption linked with
reduced global production is the most effective CH
mitigation option
(Popp et al., 2010;Bellarby et al., 2013;Shaullah et al., 2021). The annual
meat consumption in Germany ranged between 55 and 62 kg per person be-
tween 2000 and 2020 (Statista, 2021), whereas it was only 33 kg and 38 kg
in 1883 and 1892, respectively (Hoffmann, 1965). These data underline
that Germany's further CH
mitigation potential lies in reducing beef con-
sumption to further reduce beef import, and that the resulting protein gap
could be closed by consuming milk products possessing a lower CH
sion intensity than beef.Dyer et al. (2020) suggested for Canada a reduction
in beef production and instead an expansion of broiler production to satisfy
the required national protein intake; however, the annual consumption of
meat from poultry in Germany has already increased from <2kginthe
19th century to >22 kg per person in 2020 (Hoffmann, 1965;Statista,
2021), and, unlike beef consumption, exacerbates feed-food competition
(Windisch, 2021).
The human population in Germany's current territor y increased from
34 Mio in 1883 to 83 Mio in 2020. In the same time, consumption of
animal-derived food increased and enteric CH
intensity and emissions
per person decreased, indicating a signicant improvement in agricul-
tural production efciency. Gerber et al. (2011),forexample,demon-
cow leads to an overall CO
-equivalents reduction by a factor of four.
The improvement in animal efciency and the parallel reduction in an-
imal numbers may be an example for reversing increasing enteric CH
emissions in developing countries with a steadily increasing human
population, such as in Asia and Africa. Such a strategy may balance
climate impacts and food security.
5. Conclusion
By using Tier 1 and Tier 2 approaches we found that oxen and bulls
had the greatest emission factors, followed by dairy cows and young cat-
tle. These emission factors, as far as applicable, can be used by other
countries in case the IPCC or other default factors are not appropriate,
and thus may serve to rene national inventories. Germany's emission
mitigation aims for the 2030-target an emission of 45 kt CH
less than
the area-normalized historic emission level of 1883. Thus, <10 % of
the 1990 enteric CH
emission level remain to be reduced, and further
effort, such as the reduction of dairy cow numbers, is needed to reach
thetargetratesothatinthelong-term,thebelow 2 °C targetadopted
in Paris in 2015 can still be achieved.
Given that the production of some milk products exceeded Germany's
self-sufcient rate already in the late 19th century, the highest CH
tion potential lies in the further reduction of milk production by decreasing
dairy cow numbers and lowering the utilisation of edible biomass. How-
ever, relative to the national inventory, Germany has been emitting equal
or less enteric CH
since 2003 compared to 1892 and thereafter despite
a near doubling of the human population from the late 19th to the
early 21st century. The combination of the increase in animal performance
and reduction of animal numbers secured the food supply and reduced
enteric CH
emission intensity and total CH
emissions in the last three
decades. This strategy should be continued, and could also be applied by
developing countries to balance national CH
emissions from livestock
Supplementary data to this article can be found online at https://doi.
CRediT authorship contribution statement
G.V. developed the idea and provided historical data. B.K. performed
the calculations and wrote the manuscript. Both authors contributed
to the interpretation of the results and approved the nal version of the
Declaration of competing interest
The authors declare that they have no known competing nancial inter-
ests or personal relationships that could have appeared to inuence the
work reported in this paper.
The authors thank Rebecca Eichhorn, Research Institute for Farm
Animal Biology (FBN) for her help in literature search and Katherine M.
Kennedy for language editing. The publication received nancial support
from FBN.
Bellarby, J., Tirado, R., Leip, A., Weiss, F., Lesschen, J.P., Smith, P., 2013. Livestock green-
house gas emissions and mitigation potential in Europe. Glob. Chang. Biol. 19, 318.
BMEL - Federal Ministry of Food and Agriculture, 2021. Versorgungsbilanz Fleisch ab 1991.
https://www. bmel-statisti
(Accessed 6 March 2022).
Conradi, A., 1897. Fütterungslehre. second ed. Parey, Berlin.
Dalgaard, T., Olese n, J.E., Peterse n, S.O., Petersen , B.M., Jørgens en, U., Kristens en, T.,
Hutchings, N.J., Gyldenkærne, S., Hermansen, J.E., 2011. Developments in greenhouse
gas emissions and net en ergy use in Danish agric ulture - how to achieve subs tantial
CO2 reductions? Environ. Pollut. 159, 31933203.
Dämmgen,U., Rösemann, C., Haenel,A.-D., Hutchings, N.J., 2012. Entericmethane emissions
from German dairy cows. Landbauforsch. 62, 2132.
Dyer, J.A., Worth, D.E., Vergé, X.P.C., Desjardins, R.L., 2020. Impact of recommended red
meat consumption in Canada on the carbon footprint of Canadian livestock production.
J. Clean. Prod. 266, 121785.
Esslen, J.B., 1912. Die Entwicklung von Fle ischerzeugung und Fleischverbrauch auf dem
Gebiete des heutigen Deutschen Reiches seit dem Anfang des 19. Jahrhunderts und ihr
gegenwärtiger Stand. Jahrb. National. Stat. III (43), 705769.
Etheridge, D.M., Steele, L.P., Francey, R.J., Langenfelds, R.L., 1998. Atmospheric methane be-
tween 1000 A.D. and present: evidence of anthropogenic emissions and climatic variabil-
ity. J. Geophys. Res. Atmos. 103, 1597915993.
FAO, 2021. FAOSTAT Climate Change, Emissions, Emissions Totals.
faostat/en/#data/GT. (Accessed 28 February 2022).
FAOSTAT, 2021. Statistical Database of the Food and Agriculture Organization of the United
Nations (FAO). Rome. (Accessed 13 December
Franz, R.,Soliva, C.R., Kreuzer, M., Steuer, P., Hummel,J., Clauss, M., 2010. Methane produc-
tion in relation to body mass of ruminants and equids. Evol. Ecol. Res. 12, 727738.
https://www.ev olutionary-ecol v12/n06/ddar2569 .pdf. (Accessed 6
March 2022).
Garnier, J., Le Noë, J., Marescaux, A., Sanz-Cobena, A., Lassaletta, L., Silvestre, M., Thieu, V.,
Billen, G., 2019. Long-term changes in greenhouse gas emissions from French agriculture
and livestock (18522014): from traditional agriculture to conventional intensive sys-
tems. Sci. Total Environ. 660, 14861501.
Gerber, P., Vellinga, T., Opio, C., Steinfeld, H., 2011. Productivity gains and greenhouse gas
emissions int ensity in dairy sys tems. Livest. Sc i. 139, 100108. htt ps:// 10.
Gruber, L., Guggenber ger, T., Steinwidder, A., usler, J., Schauer, A., Stein wender, R.,
Wenzel, W., Stei ner, B., 2001. Vorh ersage der Futter aufnahme von Milchkühen auf
Basis der Fütterungsversuche der BAL Gumpenstein. 28. Viehwirtschaftliche Fachtagung,
BAL Gumpenstein.
dateien.html ?path=Tagungen %252FViehwir tschaftstagung %
252FViehwirtschaftstagung_2004%252F1v_2004_gruber.pdf. (Accessed 6 March 2022).
Gruber, L., 2014. Tab elle zur Fütterung in de r Rindermast. Bayer ische Landesanstalt für
Landwirtschaft (LfL). nen/daten/
informationen/p_31941.pdf. (Accessed 6 March 2022).
Gütschow, J., Jeffery, L., Gieseke, R., Gebel, R., Stevens, D., Krapp, M., Rocha, M., 2016. The
PRIMAP-hist national historical emissions time series. Earth Syst. Sci. Data 8, 571603.
Haenel, H.-D., Rösemann, C., Dämmgen, U., Döring, U ., Wulf, S., Eurich-Menden, B.,
Freibauer, A., Döhler, H., Schrei ner, C., Osterburg, B., Fuß, R., 202 0. Calculations of
Gaseous and Particula te Emissions From German Agriculture 1990-20 18: Report on
Methods and Data (RMD) Submission 2020, Thünen-Report 77. Johann Heinrich von
Thünen-Institut, Braunschweig.
Heinrich, R., 1896. Futter und Fütterung der landwirtschaftlichen Nutztiere. Parey, Berlin.
Heinze, A., 2011. Empfehlungen und Richt werte zur Schwei nefütterung. Sc hriftenreihe
"Landwirtschaft und Landschaftspege in Thüri ngen" 3/2 011.
Helling, G., 19 65. Berechnung ei nes Index der Agrarp roduktion in Deutschland im 19.
Jahrhundert. Jahrb uch für Wirtschaftsge schichte/Economi c History Yearbook. 6( 4),
pp. 125151.
Hoffmann, W.G. , 1965. Das Wachs tum der deutschen Wirt schaft seit der Mi tte des 19.
Jahrhunderts. Springer, Berlin/Heidelberg/New York.
B. Kuhla, G. Viereck Science of the Total Environment 848 (2022) 157754
IPCC, 2006. IPCC Gu idelines for National Greenhous e Gas Inventories, Prepared by the
National Greenhouse Gas Inven tories Programme. Agricultur e, Forrestry and Other
Land Use: Emissions from Livestock and Manure Management. IGES, Hayama.
IPCC, 2021. Summary for policymakers. Climate Change 2021: The Physical Science Basis.
Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmen-
tal Panel on Climate Change. Cambridge University Press, Cambridge, New York.
Jentsch, W., Schweigel, M., Weissbach, F., Scholze, H., Pitroff, W., Derno, M., 2007. Methane
production in cattle calculated by the nutrient composition of the diet. Arch. Anim. Nutr.
61, 1019.
Kaiserliches Statistisches Amt, collab, 1874. Vierteljahreshefte zur Statistik des Deutschen
Reichs. 2. Jg., 3. H., 2. Abt. Puttkammer &Mühlenbrecht, Berlin , pp. 72140. https://
Kaiserliches Statistisches Amt, 18 84. Monatshefte zur Statistik des Deu tschen Reiches, 1.
Theil, Heft I-VI. pp. VI, 1-64Puttkammer &Mühlenbrecht, Berlin. https://hdl.handle.
Kaiserliches Statistisches Amt, 1894. Vierteljahreshefte zur Statistik desDeutschen Reiches, 3.
Jg. pp. I, 125-132, II, 71-133Puttkammer &Mühlenbrecht, Berlin. https://hdl.handle.
Klemme, J., 2003. Entwicklung der Er nährungsfors chung bei Wiederk äuern im 19.
Jahrhundert. - Füt terungsversuche, Energieha ushalt und Eiweißs toffwechsel. Thes is
Tierärztliche Hochschule Hann over. https://nbn- /urn:nbn:de:g bv:95-
Knapp, J.R., Laur, G.L., Vadas, P.A., Weiss, W.P., Tricarico, J.M., 2014. Invited review: enteric
methane in dairy cattle production: quantifying the opportunities and impactof reducing
emissions. J. Dairy Sci. 97, 32313261.
Lohheide, B., 2008. Agrobusiness und Globalisierung. Die Entstehung des transatlantischen
Rindeischmarktes 1870-1914. Thesis University Cologne.
Mahlerwein, G., 2016. Grundzüge der Agrargeschichte, Bd. 3: Die Moderne (1880-2010).
Böhlau, Köln.
Muylaert de Araujo, M.S., Pires de Campos, C., Pinguelli Rosa, L., 2007. Historical emissions,
by country, of N2O from animal manure management and of CH4 from enteric fermenta-
tion in domestic livestock. Clim. Res. 34, 253258.
O'Brien, D., Hennessy, T., Moran, B., Shalloo, L., 2015. Relating the carbon footprint of milk
from Irish dairy farms to economic performance. J. Dairy Sci. 98, 73947407. https://
Pelchen, A., Peters, K.J., 1998 . Methane emissi ons from sheep. Small Rumin. Res. 2 7,
Piatkowski, B., Jentsch, W., Derno, M., 2010. Neue Ergebnisse zur Methanproduktion und zu
deren quantitativer Vorhersage beim Rind. Züchtungskunde 82, 400407.
Popp, A., Lotze-Campen, H., Bodirsky, B., 2010. Food consumption, diet shifts and associated
non-CO2 greenhouse gases from agric ultural producti on. Glob. Environ. Cha ng. 20,
Rutherford, J.S., Sherwin, E.D., Ravikumar, A.P., Heath, G.A., Englander, J., Cooley, D., Lyon,
D., Omara, M., Langtt, Q., Brandt, A.R., 2021. Closing the methane gap in US oil and
natural gas production emissions inventories. Nat. Commun. 12, 4715.
Shaullah, M., Khalid,U., Shahbaz, M., 2021. Does meat consumption exacerbate greenhouse
gas emissions? Evidence from US data. Environ. Sci. Pollut. Res. Int. 28, 1141511429.
Statista , 2021]. (Accessed 6 March 2022).
Stern, D.I., Kaufmann, R.K., 19 96. Estimates of global anthropogenic methane emissions
18601993. Chemosphere 33, 159176.
Teuteberg, H.J., 1988. Anfänge des modernen Milchzeitalters in Deutschland. In: Teuteberg,
H.J., Wiegelmann, G. (Eds.), Unsere gliche Kost. Coppenrath, Münster , pp. 163184.
Tongwane, M.I., Moeletsi, M.E., 2020. Emission factors and carbon emissions of methane
from enteric fermentation of cattle produced under different management systems in
South Africa. J. C lean. Prod. 265, 121 931. https://do /j.jclepro.20 20.
Tümmler, L.M., Derno, M., Röttgen, V., Vernunft, A., Tuchscherer, A., Wolf, P., Kuhla, B.,
2020. Effects of 2 colostrum and subsequent milk replacer feeding intensities on methane
production, rumen development, and performance in young calves. J. Dairy Sci. 103,
UBA - German government environmental agency, 2022. Treibhausgas-Emissionen. https:// (Accessed
6 March 2022).
Graf Fink von Finckenstein, H.W., 1960. Die Entwicklung der Landwirtschaft in Preußen und
Deutschland. 1800-1930. Holzner, Würzburg.
Vos, C., Rösemann, C., Haenel, H.-D., Dämmgen, U., Döring, U., Wulf, S., Eurich-Menden, B.,
Freibauer, A., Döhler,H., Schreiner, C., Osterburg, B.,Fuß, R., 2022]. Calculations of Gas-
eous and Particulate Emissions From German Agriculture 1990-2020: Input Data and
Emission Results.
Windisch, W., 2021. Can we do without livestock? J. Consum. Prot. Food Saf. 16, 193194.
B. Kuhla, G. Viereck Science of the Total Environment 848 (2022) 157754
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This study empirically investigates the effect of meat consumption on greenhouse gas emissions (carbon dioxide, methane, and nitrous oxide) in the USA. The impact of meat consumption on greenhouse gas emissions is examined by controlling for economic growth and energy consumption. The empirical analysis finds that all these variables are cointegrated for the long run. Moreover, meat consumption aggravates greenhouse gas emissions. Specifically, meat consumption (except for beef) has a U-shaped relationship with carbon emissions and an inverted U-shaped relationship with methane and nitrous oxide emissions. The causality analysis indicates a unidirectional causality running from meat consumption to greenhouse gas emissions. These empirical findings indicate that the USA livestock sector has the potential to become more environmentally friendly with careful policy formulation and implementation.
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A growing need exists for the development of practical feeding strategies to mitigate methane (CH4) emissions from cattle. Therefore, the objective of this study was to evaluate the influence of milk replacer feeding intensity (MFI) in calves on CH4 emission, rumen development, and performance. Twenty-eight female newborn Holstein calves were randomly assigned to 2 feeding groups, offered daily either 10% of the body weight (BW) in colostrum and subsequently 10% of the BW in milk replacer (MR; 10%-MR), or 12% of the BW in colostrum followed by 20% of the BW in MR (20%-MR). In wk 3, half of each feeding group was equipped with a permanent rumen cannula. Both groups were weaned at the end of wk 12. Hay and calf starter (mixture of pelleted grains) were offered from d 1 until wk 14 and 16, respectively. A total mixed ration was offered from wk 11 onward. Feed intake was measured daily and BW, anatomical measures, and rumen size weekly. Methane production and gastrointestinal passage rate were measured pre-weaning in wk 6 and 9 and post-weaning in wk 14 and 22, with additional estimation of organic matter digestibility. Rumen fluid, collected in wk 1, 2, 3, 6, 9, 14, 18, and 22, was analyzed for volatile fatty acid concentrations. Although the experimental period ended in wk 23, rumen volume of 17 calves was determined after slaughter in wk 34. Data was analyzed using ANOVA for the effects of feeding group, cannulation, and time, if applicable. Dry matter intake (DMI) of solid feed (SF) in 20%-MR animals was lower pre-weaning in wk 6 to 10 but mostly higher post-weaning. From wk 6 onward, anatomical measures and BW were greater in 20%-MR animals, and only the differences in body condition score gradually ceased post-weaning. Following the amount of SF intake, 10%-MR calves emitted more CH4 pre-weaning in wk 9, whereas post-weaning the 20%-MR group tended to have higher levels. Methane emission intensity (CH4/BW) was lower pre-weaning in 20%-MR animals but was comparable to the 10%-MR group post-weaning. Methane yield (CH4/DMI of SF) and estimated post-weaning organic matter digestibility were not affected by MFI. Rumen size normalized to heart girth was greater in 10%-MR calves from wk 5 to 10, but differences did not persist thereafter. In wk 34, rumen volume was higher in 20%-MR calves, but normalization to BW revealed no difference between feeding groups. In conclusion, high MFI reduces CH4 emission from calves pre-weaning, although this effect ceases post-weaning.
Production of livestock is important for sustainability of human nutrition and overall livelihoods. Demand for livestock products is increasing due to the growing global human population. Cattle production plays an important role in South Africa's socio-economics and largely benefits from vast rangelands available for grazing. Similarly, cattle and their management are significant emitters of greenhouse gases. Quantification of past cattle emissions in the country is, however, affected by unreliable activity data and emission factors. This study therefore aims to calculate emission factors for methane (CH4) produced by cattle during enteric fermentation and the related historical CH4 carbon emissions. The emission factors are developed for each cattle subcategory and management system. Feeding practices are collated from the survey conducted in 2015 and the literature. Dairy cattle have the highest emission factors, followed by subsistence beef and commercial beef cattle. However, the large population of commercial beef cattle results in the highest total emissions by category whilst dairy cattle are the smallest producers of CH4. Of the total CH4 emissions from enteric fermentation of 0.87 million tonnes in 2018, commercial beef cattle contributed 48% while subsistence beef cattle and dairy cattle accounted for 36% and 17% respectively. Declining population particularly of commercial beef cattle results in a reduction in emissions with time. Trends of implied emission factors and emissions per energy-corrected milk and animal carcass weight for beef cattle show that cattle production efficiencies are improving in South Africa. Despite relatively lower meat prices for beef compared to poultry, poultry consumption in the country is higher than that of beef and is still growing. This pattern will out-market beef consumption and ultimately cause the emissions to decline.
The recommendation in the 2019 Canada Food Guide to diversify protein sources in the human diet could lead to less red meat consumption by Canadians. The main goal of this paper was to assess the potential impact of the reduction in red meat consumption on the carbon footprint of Canadian livestock production. Beef, pork and broilers were used to represent Canadian carcass based food commodities. Three scenarios for allowable red meat (beef and pork) consumption were tested based on medical recommendations of 15.9, 23.7 and 27.6 kg (boneless weight) per capita per year. Maintaining national dietary protein intake at 0.39 Mt was the main boundary condition for the projected reduction of red meat. A spreadsheet model was used to interpolate published Greenhouse Gas emission estimates from 1981 to 2006 for beef, pork and broiler production to 2017. This model accounted for the life cycles, age-gender categories, and supporting crop complexes of each livestock type. Three production scenarios based on two different apportionments of allowable red meat to beef and pork, and two alternative beef diets, were combined with the three medical scenarios to formulate nine projected consumption recommendations. These projections generated the slaughter animal live weights, Greenhouse Gas emissions from their production, and their protein contents. All nine scenarios required a major expansion of broiler production to satisfy the required national protein intake. The amounts by which the nine scenarios reduced Greenhouse Gas emissions ranged from 0% to 31% of the 32.6 Mt of total national CO2e emissions for the production of these three commodities in 2017.
France was a traditionally agricultural country until the first half of the 20th century. Today, it is the first European cereal producer, with cereal crops accounting for 40% of the agricultural surface area used, and is also a major country for livestock breeding with 25% of the European cattle livestock. This major socioecological transition, with rapid intensification and specialisation in an open global market, has been accompanied by deep environmental changes. To explore the changes in agricultural GHG emissions over the long term (1852–2014), we analysed the emission factors of N2O from field experiments covering major land uses, in a gradient of fertilisation and within a range of temperature and rainfall, and used CH4 emission coefficients for livestock categories, in terms of enteric and manure management, considering the historical changes in animal excretion rates. We also estimated indirect CO2 emissions, rarely accounted for in agricultural emissions, using coefficients found in the literature for the dominant energy consumption items (fertiliser production, field work and machinery, and feed import). From GHG emissions of ~30,000 ktons CO2 Eq yr⁻¹ in 1852, reaching 54,000 ktons CO2 Eq yr⁻¹ in 1955, emissions more than doubled during the ‘Glorious thirties’ (1950–1980), and peaked around 120,000 ktons CO2 Eq yr⁻¹ in the early 2000s. For the 2010–2014 period, French agriculture GHG emissions stabilised at ~114,000 ktons CO2 Eq yr⁻¹, distributed into 49% methane (CH4), 22% carbon dioxide (CO2) and 29% nitrous oxide (N2O). A regional approach through 33 regions in France shows a diversity of agriculture reflecting the hydro-ecoregion distribution and the agricultural specialisation of local areas. Exploring contrasting scenarios at the 2040 horizon suggests that only deep changes in the structure of the agro-food system would double the reduction of GHG emissions by the agricultural sector.