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The green, blue and grey water footprint of farm animals and animal products

  • Water for food Institute at University of Nebraska

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The projected increase in the production and consumption of animal products is likely to put further pressure on the globe’s freshwater resources. The size and characteristics of the water footprint vary across animal types and production systems. The current study provides a comprehensive account of the global green, blue and grey water footprints of different sorts of farm animals and animal products, distinguishing between different production systems and considering the conditions in all countries of the world separately. The following animal categories were considered: beef cattle, dairy cattle, pig, sheep, goat, broiler chicken, layer chicken and horses. The study shows that the water footprint of meat from beef cattle (15400 m3/ton as a global average) is much larger than the footprints of meat from sheep (10400 m3/ton), pig (6000 m3/ton), goat (5500 m3/ton) or chicken (4300 m3/ton). The global average water footprint of chicken egg is 3300 m3/ton, while the water footprint of cow milk amounts to 1000 m3/ton. Per ton of product, animal products generally have a larger water footprint than crop products. The same is true when we look at the water footprint per calorie. The average water footprint per calorie for beef is twenty times larger than for cereals and starchy roots. When we look at the water requirements for protein, we find that the water footprint per gram of protein for milk, eggs and chicken meat is about 1.5 times larger than for pulses. For beef, the water footprint per gram of protein is 6 times larger than for pulses. In the case of fat, we find that butter has a relatively small water footprint per gram of fat, even lower than for oil crops. All other animal products, however, have larger water footprints per gram of fat when compared to oil crops. The study shows that from a freshwater resource perspective, it is more efficient to obtain calories, protein and fat through crop products than animal products.
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ISSN 1432-9840
Volume 15
Number 3
Ecosystems (2012) 15:401-415
DOI 10.1007/s10021-011-9517-8
A Global Assessment of the Water
Footprint of Farm Animal Products
Mesfin M.Mekonnen & Arjen
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A Global Assessment of the Water
Footprint of Farm Animal Products
Mesfin M. Mekonnen* and Arjen Y. Hoekstra
Department of Water Engineering and Management, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
The increase in the consumption of animal prod-
ucts is likely to put further pressure on the world’s
freshwater resources. This paper provides a com-
prehensive account of the water footprint of animal
products, considering different production systems
and feed composition per animal type and country.
Nearly one-third of the total water footprint of
agriculture in the world is related to the production
of animal products. The water footprint of any
animal product is larger than the water footprint of
crop products with equivalent nutritional value.
The average water footprint per calorie for beef is
20 times larger than for cereals and starchy roots.
The water footprint per gram of protein for milk,
eggs and chicken meat is 1.5 times larger than for
pulses. The unfavorable feed conversion efficiency
for animal products is largely responsible for the
relatively large water footprint of animal products
compared to the crop products. Animal products
from industrial systems generally consume and
pollute more ground- and surface-water resources
than animal products from grazing or mixed sys-
tems. The rising global meat consumption and the
intensification of animal production systems will
put further pressure on the global freshwater
resources in the coming decades. The study shows
that from a freshwater perspective, animal products
from grazing systems have a smaller blue and grey
water footprint than products from industrial sys-
tems, and that it is more water-efficient to obtain
calories, protein and fat through crop products than
animal products.
Key words: meat consumption; livestock pro-
duction; animal feed; water consumption; water
pollution; sustainable consumption.
Global meat production has almost doubled in the
period 1980–2004 (FAO 2005) and this upward
trend will continue given the projected doubling of
meat production in the period 2000–2050 (Steinfeld
and others 2006). To meet the rising demand for
animal products, the on-going shift from traditional
extensive and mixed to industrial farming systems
is likely to continue (Bouwman and others 2005;
Naylor and others 2005; Galloway and others
2007). There is a rich literature on the expected
environmental consequences of increased con-
sumption of animal products (Naylor and others
2005; Myers and Kent 2003; McAlpine and others
2009; Pelletier and Tyedmers 2010; Sutton and
others 2011), and on the pros and cons of industrial
versus conventional farming systems (Lewis and
others 1990; Capper and others 2009). Specific
fields of interest include, amongst others, animal
welfare (Fraser 2008; Thompson 2008), excessive
use of antibiotics (Gustafson and Bowen 1997;
Witte 1998; Smith and others 2002; McEwen 2006),
the demand for scarce lands to produce the required
Received 30 June 2011; accepted 21 December 2011;
published online 24 January 2012
Electronic supplementary materials: The online version of this article
(doi: 10.1007/s10021-011-9517-8) contains supplementary material
which is available to authorized users.
Author Contributions: MMM designed the study, performed research,
analysed data and wrote the paper; AYH designed the study, contributed
new methods, analysed data and wrote the paper.
*Corresponding author; e-mail:
Ecosystems (2012) 15: 401–415
DOI: 10.1007/s10021-011-9517-8
Ó 2012 The Author(s). This article is published with open access at
feed (Naylor and others 2005; Keyzer and others
2005; Nepstad and others 2006) and the contribu-
tion of livestock to the emission of greenhouse gases
(Pelletier and Tyedmers 2010; Tilman and others
2001; Bouwman and others 2011). Although it is
known that animal products are very water-inten-
sive (Pimentel and others 2004; Chapagain and
Hoekstra 2003), little attention has been paid thus
far to the total impact of the livestock sector on the
global demand for freshwater resources. Most of the
water use along the supply chain of animal products
takes place in the growing of feed. As a result of the
increasing global trade in feed crops and animal
products and the growth of meat preservation over
longer periods, consumers of animal products have
often become spatially disconnected from the pro-
cesses necessary to produce the products, so that the
link between animal products and freshwater con-
sumption is not well known (Naylor and others
2005; Hoekstra 2010; Hoekstra and Chapagain
There are earlier publications on the water use
behind animal production (Steinfeld and others
2006; Galloway and others 2007; Pimentel and
others 2004; Chapagain and Hoekstra 2003, 2004;
De Fraiture and others 2007; Peden and others
2007; Van Breugel and others 2010; Renault and
Wallender 2000), but a detailed comprehensive
global assessment was lacking. The objective of the
current paper is to provide such an assessment by
quantifying the water footprint of farm animals and
of the various derived animal products per country
and per animal production system. The period of
analysis was 1996–2005. The water footprint of a
product consists of three colour-coded components:
the green, blue and grey water footprint (Hoekstra
and Chapagain 2008). The blue water footprint
refers to the volume of surface and groundwater
consumed (that is evaporated after withdrawal) as
a result of the production of the product; the green
water footprint refers to the rainwater consumed.
The grey water footprint refers to the volume of
freshwater that is required to assimilate the load of
pollutants based on existing ambient water quality
standards. Water footprint calculations have been
based on the recently established global water
footprint standard (Hoekstra and others 2011),
which was developed based on earlier water foot-
print studies (see for example, Chapagain and
others 2006; Hoekstra and Chapagain 2007; Ger-
bens-Leenes and others 2009; Aldaya and others
With the exception of Chapagain and Hoekstra
(2003, 2004), no previous study has estimated the
water footprint of animal products by product and
country at a global level. Although Chapagain and
Hoekstra (2003, 2004) were able to estimate the
water footprint of farm animals and animal prod-
ucts per country, they have made very crude
assumptions regarding the composition and
amount of feed consumed by different animals.
Besides, the water footprints of feed crops were
estimated based on national average climatic data.
The main differences with Chapagain and Hoekstra
(2003, 2004) are: (1) we estimated the amount of
feed consumed per animal category, per production
system and per country based on estimates of feed
conversion efficiencies and statistics on the annual
production of animal products, (2) we took into
consideration the relative occurrence of the three
production systems (grazing, mixed and industrial)
in each country and (3) we estimated the green,
blue and grey water footprints of growing feed
crops using a grid-based dynamic water balance
model that takes into account local climate, soil
conditions and data on irrigation at a high spatial
The Water Footprint of an Animal
We follow the water footprint definitions and
methodology as set out in Hoekstra and others
(2011). The blue water footprint refers to con-
sumption of blue water resources (surface and
groundwater) along the supply chain of a product.
‘Consumption’ refers to loss of water from the
available ground-surface water body in a catch-
ment area. Losses occur when water evaporates,
returns to another catchment area or the sea or is
incorporated into a product. The green water
footprint refers to consumption of green water
resources (rainwater in so far as it does not become
runoff). The grey water footprint refers to pollution
and is defined as the volume of freshwater that is
required to assimilate the load of pollutants given
natural background concentrations and existing
ambient water quality standards.
We consider eight farm animal categories: beef
and dairy cattle, pigs, sheep, goats, broiler and layer
chickens, and horses. When estimating total feed
amounts and total water footprints per category,
we include ‘buffaloes’ in the category of ‘beef
cattle’ and ‘asses and mules’ in the category of
The water footprint of a live animal consists of
different components: the indirect water footprint
of the feed and the direct water footprint related to
the drinking water and service water consumed
402 M. M. Mekonnen and A. Y. Hoekstra
(Chapagain and Hoekstra 2003, 2004). The water
footprint of an animal is expressed as:
WF½a; c; s¼WF
½a; c; sþWF
½a; c; s
þ WF
½a; c; s
where WF
[a,c,s], WF
[a,c,s] and WF
represent the water footprint of an animal for animal
category a in country c in production systems s
related to feed, drinking water and service-water
consumption, respectively. Service water refers to
the water used to clean the farmyard, wash the
animal and carry out other services necessary to
maintain the environment. The water footprint of an
animal and its three components can be expressed in
terms of m
/y/animal, or, when summed over the
lifetime of the animal, in terms of m
/animal. For
beef cattle, pigs, sheep, goats and broiler chick-
ens—animals that provide their products after they
have been slaughtered—it is most useful to look at
the water footprint of the animal at the end of its
lifetime, because it is this total that will be allocated
to the various products (for example, meat, leather).
For dairy cattle and layer chickens, it is most
straightforward to look at the water footprint of the
animal per year (averaged over its lifetime), because
one can easily relate this annual animal water foot-
print to its average annual production (milk, eggs).
The water footprint of an animal related to the
feed consumed consists of two parts: the water
footprint of the various feed ingredients and the
water that is used to mix the feed:
½a; c; s
Feed½a; c; s; pWF
þ WF
½a; c; s
½a; c; s
Feed[a,c,s,p] represents the annual amount of
feed ingredient p consumed by animal category a in
country c and production system s (ton/y),
[p] the water footprint of feed ingredient p
/ton), WF
[a,c,s] the volume of water
consumed for mixing the feed for animal category a
in country c and production system s (m
and Pop
[a,c,s] the number of slaughtered animals
per year or the number of milk or egg producing
animals in a year for animal category a in country c
and production system s.
The Water Footprint of Feed Ingredients
The water footprints of the different crops, rough-
ages and crop by-products (WF
[p], m
/ton) that
are eaten by the various farm animals have been
calculated following the methodology developed by
Hoekstra and Chapagain (2008) and Hoekstra and
others (2011). The water footprints of feed crops
were estimated using a crop water use model that
estimates crop water footprints at a 5 9 5 arc
minute spatial resolution globally (Mekonnen and
Hoekstra 2010, 2011). Grey water footprints were
estimated by looking at leaching and runoff of
nitrogen-fertilizers only, following Mekonnen and
Hoekstra (2010, 2011). As animal feed in a country
originates from domestic production and imported
products, for the calculation of the water footprint
of animal feed in a country, we have taken a
weighted average water footprint according to the
relative volumes of domestic production and im-
; pWF
; p
; p
in which P[p] is the production quantity of feed
product p in a country (ton/y), T
,p] the im-
ported quantity of feed product p from exporting
nation n
(ton/y), WF
[p] the water footprint of
feed product p when produced in the nation con-
sidered (m
/ton) and WF
,p] the water foot-
print of feed product p as in the exporting nation n
/ton). The water footprint of crop residues such
as bran, straw, chaff and leaves and tops from sugar
beet have already been accounted for in the main
product, therefore their water footprint was set
equal to zero.
Volume and Composition of Feed
The volume and composition of the feed consumed
vary depending on the type of animal, the pro-
duction system and the country. The amount of
feed consumed is estimated following the approach
of Hendy and others (1995), in which the total
annual feed consumption (including both concen-
trates and roughages) is calculated based on annual
production of animal products and feed conversion
efficiencies. Only for horses we have used the ap-
proach as in Chapagain and Hoekstra (2003),
which means that we multiplied the estimated feed
consumption per animal by the number of animals,
thus arriving at an estimate of the total feed con-
sumed by horses.
Assessment of the Water Footprint of Farm Animals 403
The total feed per production system for both
ruminants and non-ruminants animals is calcu-
lated as follows:
Feed½a; c; s¼FCE½a; c; sP½a; c; sð4Þ
where Feed[a,c,s] is the total amount of feed con-
sumed by animal category a (ton/y) in country c
and production system s, FCE[a,c,s] the feed con-
version efficiency (kg dry mass of feed/kg of prod-
uct) for animal category a in country c and
production system s, and P[a,c,s] the total amount
of product (meat, milk or egg) produced by animal
category a (ton/y) in country c and production
system s. The estimated global amount of feed
consumption per animal category and world region
is presented in Appendix II (Supplementary mate-
rial). Feed consumption per production system is
shown in Appendix III (Supplementary material).
Estimating Feed Conversion Efficiencies
Feed conversion efficiency is defined as the amount
of feed consumed per unit of produced animal
product (for example, meat, milk, egg). Feed con-
version efficiencies were estimated separately for
each animal category (beef cattle, dairy cattle,
sheep, goats, pigs, broiler chickens and egg-layer
chickens), for each animal production system and
per country. Although the term used may suggest
precisely the opposite, animals that have a low ‘feed
conversion efficiency’ are efficient users of feed. We
use the term here as generally used in livestock
studies. The feed conversion efficiencies (FCE, kg
dry mass/kg product) for non-ruminants (pigs and
chickens) were adopted from Hendy and others
(1995). For ruminants (cattle, goats, sheep), feed
conversion efficiencies were estimated through
dividing feed intake per capita by annual produc-
tion (of beef, milk, sheep and goat meat) per capita:
FCE½a; c; s¼
FI½a; c; s
PO½a; c; s
where FI[a,c,s] is the feed intake per head by
ruminant animal category a in country c and pro-
duction system s (kg dry mass/y/animal), and
PO[a,c,s] the product output per head for ruminant
animal category a in country c and production
system s (kg product/y/animal). The product out-
put (beef, milk, sheep and goat meat) per animal
for ruminants is calculated as:
PO½a; c; s¼
P½a; c; s
Pop½a; c; s
in which P[a,c,s] is the total annual production of
beef, milk, sheep meat or goat meat in country c
in production system s (kg/y) and Pop[a,c,s] the
total population of beef cattle, dairy cattle, sheep
or goats in that country and production system.
Region-specific feed conversion efficiencies are
presented in Appendix I (Supplementary mate-
Estimating the Total Annual Production
of Animal Products
The meat production (P
, ton/y) per animal
category a (beef cattle, pigs, sheep and goats) in
country c and production system s is estimated by
multiplying the carcass yield per slaughtered
animal by the annual number of animals slaugh-
½a; c; s¼CY½a; c; sSA½a; c; sð7Þ
The carcass yield (CY, kg/animal) for each animal
category per production system was estimated by
combining country average carcass yield data from
FAO (2009) with data on animal live weight per
production system per economic region (Hendy
and others 1995) and data on carcass weight as
percentage of live weight (FAO 2003). The ob-
tained carcass yields were scaled such that the total
meat production per animal category equals the
value provided by FAO (2009). The number of
slaughtered animals per production system (SA,
number of animal/y) was calculated by multiplying
the total animal number by the animal off-take rate
per production system:
SA½a; c; s¼Pop½a; c; sOR½a; c; sð8Þ
where Pop[a,c,s] is the population of animal cate-
gory a in country c for production system s and
OR[a,c,s] the off-take rate, which is the fraction of
the animal population that is taken out in a given
year for slaughter (dimensionless).
Milk and egg production per production system
and country were calculated as:
½a; c; s¼MY½a; c; sDC½ a; c; sð9Þ
½a; c; s¼f
½a; c; sP
½a; cð10Þ
where P
[a,c,s] and P
[a,c,s] represent produc-
tion of milk and egg in country c and production
system s, respectively (ton/y), MY[a,c,s] milk yield
per dairy cow in country c and production system
s (ton/dairy cow), DC[a,c,s] the number of
dairy cows in country c and production system s,
[a,c,s] the fraction of egg produced in country c
and production system s and P
[a,c] the total
amount of egg produced in country c (ton/y).
404 M. M. Mekonnen and A. Y. Hoekstra
Estimating the Feed Composition
Animal feeds are generally divided into ‘concen-
trates’ and ‘roughages’. The volume of concentrate
feed has been estimated per animal category and
per production system as:
Concentrate½a; c; s¼Feed½a; c; sf
½a; c; sð11Þ
where Concentrate[a,c,s] is the volume of concen-
trate feed consumed by animal category a in
country c and production system s (ton/y) and
[a,c,s] the fraction of concentrate in the total feed
for animal category a in country c and production
system s. For the latter variable, data have been
obtained from Bouwman and others (2005) and
Hendy and others (1995).
The composition of concentrate feeds varies across
animal species and regions of the world. To our
knowledge, there are no datasets with global cov-
erage on the composition of feed for the different
animals per country. Therefore, we have made a
number of assumptions concerning the concentrate
feed composition of the different animal species.
According to Hendy and others (1995), the diets of
pigs and poultry include, on average, 50–60%
cereals, 10–20% oil meals and 15–25% ‘other con-
centrates’ (grain substitutes, milling by-products,
non-conventional concentrates). Wheeler and oth-
ers (1981) provide the feed composition in terms of
major crop categories for the different animal cate-
gories. We have used these and other sources in
combination with FAOSTAT country average con-
centrate feed values for the period 1996–2003 (FAO
2009) to estimate the diet composition of the dif-
ferent animal species. To estimate the feed in terms
of specific crops per animal, we first estimated the
feed in terms of major crop categories following
Wheeler and others (1981). The feed in terms of
major crop categories is further distributed to each
crop proportional to the crop’s share in its crops
category as obtained from FAO (2009). The rough-
age feed is divided into fodder, grass and crop resi-
dues using the data obtained from Bouwman and
others (2005). The estimated fraction of concentrate
feed in total feed dry matter, per animal category,
production system and world region is presented in
Appendix IV (Supplementary material).
A large amount of data has been collected from
different sources. A major data source for animal
stocks, numbers of animals slaughtered each year,
annual production of animal products, and con-
centrate feed per country is FAOSTAT (FAO 2009).
Other important sources that have been used are:
Bouwman and others (2005), Sere
and Steinfeld
(1996), Wint and Robinson (2007), Hendy and
others (1995), FAO (2003) and Wheeler and others
(1981). Appendix V (Supplementary material)
summarizes how specific data have been obtained
from these different sources.
The Water Footprint of Animal Products
per Ton
By combining the feed conversion efficiency—dis-
tinguishing between different animals, production
systems and countries (Hendy and others
1995)—and the water footprint of the various feed
ingredients (Mekonnen and Hoekstra 2011)we
estimated the water footprint of different animals
and animal products per production systems and
per country. The water footprints of animal prod-
ucts vary greatly across countries and production
systems. The type of production system is highly
relevant for the size, composition and geographic
spread of the water footprint of an animal product,
because it determines feed conversion efficiency,
feed composition and origin of feed. Differences
between countries are related to existing country
differences in feed conversion efficiencies, but also
to the fact that water footprints of feed crops vary
across countries as a function of differences in cli-
mate and agricultural practice. The Netherlands, for
example, shows lower total water footprints for
most animal products if compared to the USA. The
USA, in turn, generally shows lower total water
footprints for animal products than India (Table 1).
The smaller water footprint in the Netherlands
compared to the USA and India, is due to the fact
that animal production in the Netherlands is
dominated by the industrial production system,
which generally has a smaller total water footprint
than grazing and mixed systems. In addition, the
water footprint per ton of feed material in the
Netherlands is lower than in the two other coun-
tries. Due to the specific climate and poor agricul-
tural practices in India, the water footprint per ton
of feed in this country is larger than in the Neth-
erlands and the USA.
When we look at global averages (Table 1), we
see that the water footprint of meat increases from
chicken meat (4,300 m
/ton), goat meat
(5,500 m
/ton), pig meat (6,000 m
/ton) and
sheep meat (10,400 m
/ton) to beef (15,400 m
ton). The differences can be partly explained from
the different feed conversion efficiencies of the
Assessment of the Water Footprint of Farm Animals 405
Table 1. The Green, Blue and Grey Water Footprint of Selected Animal Products for Selected Countries and the Weighted Global Average
Animal products Farming system China India Netherlands USA Weighted average
Green Blue Grey Green Blue Grey Green Blue Grey Green Blue Grey Green Blue Grey Total
Beef Grazing 16,140 213 0 25,913 242 0 19,102 525 590 21,121 465 243 21,829
Mixed 13,227 339 103 16,192 533 144 10,319 761 664 12,726 546 768 14,803 508 401 15,712
Industrial 10,922 933 1,234 12,412 1,471 866 3,934 349 225 2,949 356 551 8,849 683 712 10,244
Weighted average 12,795 495 398 15,537 722 288 5,684 484 345 12,933 525 733 14,414 550 451 15,415
Sheep meat Grazing 9,606 388 0 11,441 489 0 11,910 312 18 15,870 421 20 16,311
Mixed 5,337 454 14 7,528 582 316 8,248 422 35 9,842 318 74 7,784 484 67 8,335
Industrial 2,366 451 22 4,523 593 484 0 0 0 4,607 800 216 5,623
Weighted average 5,347 452 14 7,416 582 314 8,248 422 35 10,948 315 44 9,813 522 76 10,412
Goat meat Grazing 5,073 272 0 8,081 374 0 9,277 285 0 9,562
Mixed 2,765 283 0 4,544 381 9 2,443 453 4 4,691 313 4 5,007
Industrial 1,187 437 0 2,046 436 30 2,431 413 18 2,863
Weighted average 2,958 312 0 4,194 393 13 2,443 454 4 5,185 330 6 5,521
Pig meat Grazing 11,134 205 738 3,732 391 325 4,048 479 587 5,118 870 890 7,660 431 632 8,724
Mixed 5,401 356 542 4,068 893 390 3,653 306 451 4,953 743 916 5,210 435 582 6,226
Industrial 3,477 538 925 9,236 2,014 1,021 3,776 236 427 3,404 563 634 4,050 487 687 5,225
Weighted average 5,050 405 648 5,415 1,191 554 3,723 268 438 4,102 645 761 4,907 459 622 5,988
Chicken meat Grazing 4,695 448 1,414 11,993 1,536 1,369 2,535 113 271 2,836 294 497 7,919 734 718 9,370
Mixed 3,005 297 905 7,676 995 876 1,509 76 161 1,688 183 296 4,065 348 574 4,987
Industrial 1,940 195 584 3,787 496 432 1,548 77 165 1,731 187 303 2,337 210 325 2,873
Weighted average 2,836 281 854 6,726 873 768 1,545 77 165 1,728 187 303 3,545 313 467 4,325
Egg Grazing 3,952 375 1,189 10,604 1,360 1,176 1,695 76 161 1,740 183 331 6,781 418 446 7,644
Mixed 2,351 230 708 6,309 815 699 1,085 51 103 1,113 121 212 3,006 312 545 3,863
Industrial 2,086 206 628 3,611 472 400 1,187 55 113 1,218 132 232 2,298 205 369 2,872
Weighted average 2,211 217 666 4,888 635 542 1,175 55 111 1,206 130 230 2,592 244 429 3,265
Milk Grazing 1,580 106 128 1,185 105 34 572 50 32 1,106 69 89 1,087 56 49 1,191
Mixed 897 147 213 863 132 65 431 40 23 582 59 88 790 90 76 956
Industrial 500 43 25 444 61 100 1,027 98 82 1,207
Weighted average 927 145 210 885 130 63 462 41 25 647 60 89 863 86 72 1,020
Butter Grazing 8,600 577 696 6,448 572 188 3,111 272 176 6,022 373 482 5,913 305 265 6,484
Mixed 4,880 799 1,161 4,697 716 352 2,345 218 123 3,169 321 478 4,297 492 415 5,204
Industrial 2,720 233 136 2,417 330 543 5,591 532 448 6,571
Weighted average 5,044 789 1,141 4,819 706 341 2,513 224 134 3,519 324 483 4,695 465 393 5,553
Milk powder Grazing 7,348 493 595 5,510 489 160 2,658 232 151 5,145 319 412 5,052 261 227 5,540
Mixed 4,169 683 992 4,013 612 301 2,003 186 105 2,708 274 409 3,671 421 354 4,446
Industrial 0 0 0 0 0 0 2,324 199 116 2,065 282 464 4,777 455 382 5,614
Weighted average 4,309 674 975 4,117 603 291 2,147 191 114 3,007 277 413 4,011 398 336 4,745
406 M. M. Mekonnen and A. Y. Hoekstra
animals. Beef production, for example, requires 8
times more feed (in dry matter) per kilogram of
meat compared to producing pig meat, and 11
times if compared to the case of chicken meat. This
is not the only factor, however, that can explain
the differences. Another important factor is the
feed composition. Particularly the fraction of con-
centrate feed in the total feed is important, because
concentrate feed generally has a larger water foot-
print than roughages. Chickens are efficient from a
total feed conversion efficiency point of view, but
have a large fraction of concentrates in their feed.
This fraction is 73% for broiler chickens (global
average), whereas it is only 5% for beef cattle.
For all farm animal products, except dairy prod-
ucts, the total water footprint per unit of product
declines from the grazing to the mixed production
system and then again to the industrial production
system. The reason is that, when moving from
grazing to industrial production systems, feed
conversion efficiencies get better (Appendix I
Supplementary Material). Per unit of product,
about three to four times more feed is required for
grazing systems when compared to industrial sys-
tems. More feed implies that more water is needed
to produce the feed. The fraction of concentrate
feed in the total feed is larger for industrial systems
if compared to mixed production systems and lar-
ger for mixed systems if compared to grazing sys-
tems (Appendix IV Supplementary Material).
The water footprint per kg of concentrate feed is
generally larger than for roughages, so that this
works to the disadvantage of the total water foot-
print of animals raised in industrial systems and to
the advantage of the total water footprint of ani-
mals raised in grazing systems. This effect, how-
ever, does not fully compensate for the unfavorable
feed conversion efficiencies in grazing systems.
In dairy farming, the total water footprint per
unit of product is comparable in all three pro-
duction systems. For dairy products, the water
footprint happens to be the smallest when derived
from a mixed system and a bit larger but compa-
rable when obtained from a grazing or industrial
Blue and Grey Water Footprints per Ton
of Product
All the above is about comparing the total water
footprints of animal products. The picture changes
when we focus on the blue and grey water foot-
print components. With the exception of chicken
products, the global average blue and grey water
footprints increase from grazing to industrial
Table 1. continued
Animal products Farming system China India Netherlands USA Weighted average
Green Blue Grey Green Blue Grey Green Blue Grey Green Blue Grey Green Blue Grey Total
Cheese Grazing 7,812 540 633 5,857 535 171 2,826 263 160 5,470 355 438 5,371 293 241 5,905
Mixed 4,432 742 1,055 4,267 666 320 2,130 214 111 2,878 307 435 3,903 463 377 4,743
Industrial 2,471 227 124 2,196 315 493 5,078 500 406 5,984
Weighted average 4,581 732 1,036 4,377 657 310 2,283 219 121 3,196 310 439 4,264 439 357 5,060
Leather (beef cattle) Grazing 14,300 266 0 25,195 310 0 21,290 657 658 20,905 535 240 21,680
Mixed 11,719 377 91 15,743 593 140 11,883 947 765 14,185 681 856 16,701 644 453 17,799
Industrial 9,677 904 1,093 12,068 1,505 842 4,530 513 259 3,287 497 614 9,487 805 763 11,056
Weighted average 11,323 515 352 15,103 777 280 6,067 589 369 14,450 658 819 15,916 679 498 17,093
Assessment of the Water Footprint of Farm Animals 407
production systems (Table 1). The larger blue and
grey water footprints for products obtained from
industrial production systems are caused by the fact
that concentrate feed takes a larger share in the
total feed in industrial systems when compared to
grazing systems. For beef cattle in grazing systems,
the global average share of concentrate feed in total
feed is 2%, whereas in industrial systems it is 21%.
Mixed systems are generally somewhere in be-
tween. Although the feed crops that are contained
in the concentrate feed are often to a great extent
based on green water, there is a blue water foot-
print component as well, and the larger the con-
sumption of feed crops compared to roughages, the
larger the total amount of blue water consumed.
This explains the larger blue water footprint per ton
of product in industrial production systems for beef,
milk, cheese, and pig, sheep and goat meat. The
application and leaching of fertilizers and other
agro-chemicals in feed crop production results in
the fact that the grey water footprint of animal
products from industrial systems, where the
dependence on feed crops is the greatest, is larger
than for grazing systems. Given the fact that
freshwater problems generally relate to blue water
scarcity and water pollution and to a lesser extent
to competition over green water, industrial systems
place greater pressure on ground- and surface-
water resources than grazing systems, because
grazing systems hardly depend on blue water.
In the case of chicken products (chicken meat
and egg), the industrial production system has, on
average, a smaller blue and grey water footprint per
ton of product compared to the other two produc-
tion systems. The reason is that chickens strongly
rely on concentrate feed in all production systems,
intensive or extensive. Broiler chickens in exten-
sive systems have a share of concentrate feed in
total feed of 63%, whereas this is 81% in intensive
industrial systems. There is still a difference, but the
differences in feed composition for both broiler and
layer chickens is smaller if compared to the other
animal categories. As a result, the relatively unfa-
vorable feed conversion efficiency in extensive
systems is not compensated by a more favorable
composition of the feed as is in the other animal
The trends in the global averages do not always
hold for specific countries. This can be seen from
Table 1, which provides country average water
footprints for China, India, the Netherlands and the
USA as well as global averages. The feed composi-
tion varies per production system but also from
country to country; as a result, the magnitude of
the different components of the water footprint in
the different countries varies significantly from the
global mean. Cattle in US grazing systems, for
example, are also fed relatively large amounts of
grains, predominantly maize, which is irrigated and
fertilized, which explains the relatively large blue
and grey water footprints of US beef from grazing
systems. In China and India, cattle in grazing and
mixed systems are mainly fed with pasture and
crop residues that have no blue and grey water
footprints. Beef from industrial systems in China
and India, on the contrary, have a relatively large
blue and grey water footprint, which can be ex-
plained from the fact that the concentrates in
Chinese and Indian industrial systems have a rel-
atively large blue and grey water footprint. This
shows that systems that belong to the same cate-
gory, grazing, mixed or industrial, differ in the feed
they provide to animals. Often, the feed ingredients
in the different countries have different water
footprints, resulting in differences in the total
green, blue and grey water footprint of the animal
The Total Water Footprint of Animal
During the period 1996–2005, the total water
footprint for global animal production was 2,422
/y (87.2% green, 6.2% blue and 6.6% grey
water). The largest water footprint for animal pro-
duction comes from the feed they consume, which
accounts for 98% of the total water footprint.
Drinking water, service water and feed-mixing
water further account the only for 1.1, 0.8 and
0.03% of the total water footprint, respectively.
Grazing accounts for the largest share (38%), fol-
lowed by maize (17%) and fodder crops (8%).
The global water footprint of feed production is
2,376 Gm
/y, of which 1,463 Gm
/y refers to crops
and the remainder to grazing. The estimate of green
plus blue water footprint of animal feed production
is consistent with estimates of earlier studies
(Table 4). The total water footprint of feed crops
amounts to 20% of the water footprint of total crop
production in the world, which is 7,404 Gm
(Mekonnen and Hoekstra 2011). The globally
aggregated blue water footprint of feed crop
production is 105 Gm
/y, which is 12% of the blue
water footprint of total crop production in the
world (Mekonnen and Hoekstra 2011). This means
that an estimated 12% of the global consumption
of groundwater and surface water for irrigation is
for feed, not for food, fibers or other crop products.
Globally, the total water footprint of animal pro-
duction (2,422 Gm
/y) constitutes 29% of the
408 M. M. Mekonnen and A. Y. Hoekstra
water footprint of total agricultural production
(8,363 Gm
/y). The latter was calculated as the
sum of the global water footprint of crop produc-
tion (7,404 Gm
/y, Mekonnen and Hoekstra 2011),
the water footprint of grazing (913 Gm
/y, this
study) and the direct water footprint of livestock
(46 Gm
/y, this study).
When we consider the total water footprint per
animal category (Table 2), we find that beef cattle
have the largest contribution (33%) to the global
water footprint of farm animal production, fol-
lowed by dairy cattle (19%), pigs (19%) and
broiler chickens (11%). Mixed production systems
account for the largest share (57.4%) in the global
water footprint of animal production. Grazing and
industrial production systems account for 20.3 and
22.3%, respectively. In the grazing system, over
97% of the water footprint related to feed comes
from grazing and fodder crops and the water foot-
print is dominantly (94%) green. In the mixed and
industrial production systems, the green water
footprint forms 87 and 82% of the total footprint,
respectively. The blue water footprint in the graz-
ing system accounts for 3.6% of the total water
footprint and about 33% of this comes from the
drinking and service-water use. In the industrial
Table 2. Average Annual Water Footprint of One Animal, per Animal Category (1996–2005)
Water footprint
of live animal
at end of life
time (m
Average animal
weight at end
of life time
Average water
footprint at end
of life time
life time
Average annual
water footprint
of one animal
Annual water
footprint of
animal category
Beef cattle 7,477 253 1,889 3.0 630 798 33
Dairy cattle 20,558 10 2,056 469 19
Pigs 3,831 102 390 0.75 520 458 19
Broiler chickens 3,364 1.90 6 0.25 26 255 11
Horses 40,612 473 19,189 12 1,599 180 7
Layer chickens 47 1.4 33 167 7
Sheep 4,519 31.3 141 2.1 68 71 3
Goats 3,079 24.6 76 2.3 32 24 1
Total 2,422 100
Calculated by multiplying the water footprint of the live animal at the end of its lifetime in m
/ton and the average animal weight.
Calculated by dividing the average water footprint of the animal at the end of its life time by the average life time.
Table 3. The Water Footprint of Some Selected Food Products from Vegetable and Animal Origin
Food item Water footprint per ton
Water footprint per unit
of nutritional value
Green Blue Grey Total Calorie
(liter/g protein)
(liter/g fat)
Sugar crops 130 52 15 197 285 0.0 0.0 0.69 0.0 0.0
Vegetables 194 43 85 322 240 12 2.1 1.34 26 154
Starchy roots 327 16 43 387 827 13 1.7 0.47 31 226
Fruits 726 147 89 962 460 5.3 2.8 2.09 180 348
Cereals 1,232 228 184 1,644 3,208 80 15 0.51 21 112
Oil crops 2,023 220 121 2,364 2,908 146 209 0.81 16 11
Pulses 3,180 141 734 4,055 3,412 215 23 1.19 19 180
Nuts 7,016 1367 680 9,063 2,500 65 193 3.63 139 47
Milk 863 86 72 1,020 560 33 31 1.82 31 33
Eggs 2,592 244 429 3,265 1,425 111 100 2.29 29 33
Chicken meat 3,545 313 467 4,325 1,440 127 100 3.00 34 43
Butter 4,695 465 393 5,553 7,692 0.0 872 0.72 0.0 6.4
Pig meat 4,907 459 622 5,988 2,786 105 259 2.15 57 23
Sheep/goat meat 8,253 457 53 8,763 2,059 139 163 4.25 63 54
Beef 14,414 550 451 15,415 1,513 138 101 10.19 112 153
Assessment of the Water Footprint of Farm Animals 409
system, the blue water footprint accounts for 8% of
the total water footprint.
Water Footprint of Animal versus Crop
Products per Unit of Nutritional Value
As a general picture we find that animal products
have a larger water footprint per ton of product
than crop products. As we see from Table 3, the
global average water footprint per ton of crop in-
creases from sugar crops (roughly 200 m
/ton) and
vegetables (300 m
/ton) to pulses (4,000 m
ton) and nuts (9,000 m
/ton). For animal prod-
ucts, the water footprint increases from milk
(1,000 m
/ton) and egg (3,300 m
/ton) to beef
(15,400 m
/ton). Also when viewed from a
caloric standpoint, the water footprint of animal
products is larger than for crop products. The
average water footprint per calorie for beef is 20
times larger than for cereals and starchy roots.
When we look at the water requirements for pro-
tein, we find that the water footprint per gram of
protein for milk, eggs and chicken meat is about 1.5
times larger than for pulses. For beef, the water
footprint per gram of protein is 6 times larger than
for pulses. In the case of fat, we find that butter has
a relatively small water footprint per gram of fat,
even lower than for oil crops. All other animal
products, however, have larger water footprints per
gram of fat when compared to oil crops. The gen-
eral conclusion is that from a freshwater resource
perspective, it is more efficient to obtain calories,
protein and fat through crop products than animal
products. A note should be made here, however,
that types of proteins and fats differ across the dif-
ferent products.
Meat-based diets have a larger water footprint
compared to a vegetarian diet. We explored the
implications of our results by examining the diet
within one developed country—the USA—to
determine the effect of diet composition on water
footprint. Meat contributes 37% towards the food-
related water footprint of an average American
citizen. Replacing all meat by an equivalent
amount of crop products such as pulses and nuts
will result in a 30% reduction of the food-related
water footprint of the average American citizen.
The result of the current study can be compared
with results from earlier studies. However, only a
few other studies on the water footprint per unit of
animal product and the total water footprint of
animal production are available. We will first
compare our estimates of the water footprints per
ton of animal product with two earlier studies and
subsequently we will compare the total water
footprint related to animal feed production with
five earlier studies.
The rough estimates made by Pimentel and
others (2004) for the water footprints of beef and
meat from sheep, pigs and chickens are partly very
close to our global estimates but partly also quite
different. As Pimentel’s studies did not include the
grey water footprint component, we will compare
only the green plus blue water footprint from our
estimate with that of Pimentel and others (2004).
They report a water footprint of chicken meat of
3,500 m
/ton, which is only a bit lower than our
global average estimate of 3,858 m
/ton. They
report a water footprint of pig meat of 6,000
/ton, which is a slightly larger than our global
average estimate. For sheep meat, they report a
water footprint of 51,000 m
/ton and for beef
43,000 m
/ton, values that are very high when
compared to our estimates (10,400 m
/ton for
sheep meat and 15,400 m
/ton for beef). We con-
sider the values reported by Pimentel as rough
estimates, for which the underlying assumptions
have not been spelled out, so that it is difficult to
explain differences with our estimates.
The study of Chapagain and Hoekstra (2004)is
the only publication with global estimates of
the water footprint of animal products with
specifications by country. The current study gives
better estimates due to a refined assessment as
explained in the introductory section, so that the
previous estimates cannot be used for validation
of the estimates from the current study. However,
it is worth comparing the results from the two
studies to see the differences. At a global level,
the estimated water footprints per ton of animal
and animal product compare very well with the
estimates from Chapagain and Hoekstra (2004),
with an r
of 0.88 (Figure 1A). The good agree-
ment at the global level between the two studies
is probably that the global average water foot-
prints for various feed ingredients are very close
in the two studies. The trend line in Figure 1Ais
slightly above 1, which is caused by our higher
estimates for the water footprints of sheep and
goat meat. For most other animal products, the
current study gives a bit lower estimates than the
earlier study.
When we compare our estimates with Chapagain
and Hoekstra (2004) at a country level, more dif-
ferences are found (Figure 1B–F). The two studies
show a relatively good agreement for pig meat,
chicken meat and egg—although for egg the earlier
410 M. M. Mekonnen and A. Y. Hoekstra
study systematically gives higher numbers—but
little agreement for beef and dairy products. In
general we find that Chapagain and Hoekstra
(2004) underestimated the water footprints for
African countries and overestimated the water
footprints for OECD countries. As already pointed
out in the introductory section, there are three
main reasons why the estimates from the current
study can differ from the 2004-study and are con-
sidered more accurate. First, the current study is
based on better data for the estimation of the
quantity and composition of animal feed. Second,
the current study takes into consideration the rel-
ative presence of the three production systems per
country and accounts for the differences between
those systems. Third, we have estimated the water
footprints of the various feed ingredients more
accurately by using a high-resolution grid-based
crop water use model, including the effect of
Figure 1. Comparison of average water footprint of A animals and animal products at global level, and B beef, C milk, D
pig meat, E chicken meat and F egg at the country level as estimated in the current study and Chapagain and Hoekstra
(2004). From the current study we show here the sum of green and blue water footprints, excluding the grey water
footprint, because that component was excluded in the 2004 study.
Assessment of the Water Footprint of Farm Animals 411
water deficits where they occur, making explicit
distinction between the green and blue water
footprint components and including the grey water
footprint component.
As one can see in the overview presented in Ta-
ble 4, our estimate of the total evaporative water use
(green plus blue water footprint) for producing ani-
mal feed (2,217 Gm
/y) is 3% larger than the estimate
by De Fraiture and others (2007) and 5% smaller
than the estimate by Zimmer and Renault (2003).
Our estimate of the global consumptive water use for
producing feed crops (1,304 Gm
/y) does not signif-
icantly differ from the estimate by De Fraiture and
others (2007). Our estimate of global consumptive
water use for grazing (913 Gm
/y) is 9% larger than
the estimate by De Fraiture and others (2007). The
differences with three other studies that reported on
the consumptive water use related to grazing are
much larger, which is caused by another definition
applied. Postel and others (1996) estimated the water
evaporated from grazing land to be 5,800 Gm
/y. In
more recent studies, Rost and others (2008)and
Hanasaki and others (2010) estimate the total
evapotranspiration from grazing land to be 8,258 and
12,960 Gm
/y, respectively. However, unlike the
current study, the estimates in these three studies
refer to the total evapotranspiration from grazing
lands rather than to the evaporation related to the
grass actually consumed. This makes a comparison of
our results with theirs unjustified. According to De
Fraiture and others (2007), reported ‘grazing lands’
are only partly actually grazed. Besides, the harvest
efficiency—the fraction of grass actually consumed
by the animal compared to the standing biomass—is
quite small. In a recent study in the USA, Smart and
others (2010) showed that, depending on the animal
stocking density, harvest efficiencies reach between
14 and 38%.
There are several uncertainties in this study in
the quantification of the water footprint of animals
and animal products. Due to a lack of data, many
assumptions have to be made. There are a number
of uncertainties in the study, but particularly two
types of uncertainty may have a major effect on the
final output of the study. First, data on animal
distribution per production system per country for
OECD countries is not available. Wint and Robin-
son (2007) provide livestock distributions per pro-
duction system per country for developing
countries but not for OECD countries. For these
countries we are forced to use the data from Sere
and Steinfeld (1996), which provide livestock dis-
tribution per economic region. These data have the
limitation that they are not country-specific and
may lead to errors in distribution of animals into
the different production system for some countries.
The second major uncertainty is related to the
precise composition of feed per animal category per
country. Such data are not directly available so that
we had to infer these data by combining different
data sources and a number of assumptions. Despite
the uncertainties in the data used, the order of
magnitudes of the figures presented are unlikely to
be affected. Similarly, the general findings regard-
ing the overall comparison between different ani-
mals and different production systems and the
comparison between animal versus crop products is
not likely to change with better data.
Although the scope of this study is very com-
prehensive, there are many issues that have been
left out. One issue is that we neglected the indirect
water footprints of materials used in feed produc-
tion and animal raising. We expect that this may
add at most a few percent to the water footprint
estimates found in this study (based on Hoekstra
and others 2011). In the grey water footprint
Table 4. Comparison of the Results of the Current Study with the Results from Previous Studies
Study Period Global water footprint
related to
animal feed production (Gm
Grazing Crops Total
Postel and others (1996) 1995 5,800
Zimmer and Renault (2003) 2000 2,340
De Fraiture and others (2007) 2000 840 1,312 2,152
Rost and others (2008) 1971–2002 8,258
Hanasaki and others (2010) 1985–1999 12,960
Current study
1996–2005 913 1,304 2,217
The numbers in the table, also the ones from the current study, refer to the green plus blue water footprint. None of the previous studies included the grey water footprint
412 M. M. Mekonnen and A. Y. Hoekstra
estimations we have looked at the water pollution
by nitrogen-fertilizers only, excluding the potential
pollution by other fertilizer components or by
pesticides or other agro-chemicals. Besides, we
have not quantified the grey water footprint com-
ing from animal wastes, which is particularly rele-
vant for industrial production systems. Neglecting
nitrogen leaching and runoff from manure under-
estimates the grey water footprint related to animal
production. The magnitude of this underestimate
can roughly be shown by estimating the grey water
footprint related to manure based on the global
nitrogen input from manure found in the litera-
ture. Global nitrogen input from manure for the
year 2000 varies from 17 million tons per year (Liu
and others 2010) to 92 million tons per year
(Bouwman and others 2011). Based on the relative
contribution of manure to the total nitrogen input
and the global total nitrogen leaching/runoff, the
nitrogen leaching/runoff from manure can be
estimated at 6.0–14.5 million tons per year. This
amount of nitrogen leached/runoff to the fresh-
water systems can be translated into a grey water
footprint of 600–1,450 Gm
/y. The grey water
footprint is more significant in the intensive animal
production system, which often generates an
amount of waste that cannot be fully recycled on
the nearby land. The large amount of waste gen-
erated in a concentrated place can seriously affect
freshwater systems (FAO 2005; Steinfeld and oth-
ers 2006; Galloway and others 2007). Finally, by
focusing on freshwater appropriation, the study
obviously excludes many other relevant issues in
farm animal production, such as micro- and macro-
cost of production, livelihood of smallholder farm-
ers, animal welfare, public health and environ-
mental issues other than freshwater.
In conclusion, we provide a detailed estimate of the
water footprint of farm animals and animal prod-
ucts per production system and per country. The
results show that the blue and grey water footprints
of animal products are the largest for industrial
systems (with an exception for chicken products).
The water footprint of any animal product is larger
than the water footprint of crop products with
equivalent nutritional value. Finally, 29% of the
total water footprint of the agricultural sector in the
world is related to the production of animal prod-
ucts; one-third of the global water footprint of
animal production is related to beef cattle.
The global meat production has almost doubled
in the period 1980–2004 (FAO 2005) and this trend
is likely to continue given the projected doubling of
meat production in the period 2000–2050 (Stein-
feld and others 2006). To meet this rising demand
for animal products, the on-going shift from tradi-
tional extensive and mixed farming to industrial
farming systems is likely to continue. Because of
the larger dependence on concentrate feed in
industrial systems, this intensification of animal
production systems will result in increasing blue
and grey water footprints per unit of animal prod-
uct. The pressure on the global freshwater
resources will thus increase both because of the
increasing meat consumption and the increasing
blue and grey water footprint per unit of meat
Managing the demand for animal products by
promoting a dietary shift away from a meat-rich
diet will be an inevitable component in the envi-
ronmental policy of governments. In countries
where the consumption of animal products is still
quickly rising, one should critically look at how
this growing demand can be moderated. On the
production side, it would be wise to include
freshwater implications in the development of
animal farming policies, which means that partic-
ularly feed composition, feed water requirements
and feed origin need to receive attention. Animal
farming puts the lowest pressure on freshwater
systems when dominantly based on crop residues,
waste and roughages. Policies aimed to influence
either the consumption or production side of farm
animal products will generally entail various sorts
of socio-economic and environmental tradeoffs
(Herrero and others 2009; Pelletier and Tyedmers
2010). Therefore, policies aimed at reducing the
negative impacts of animal production and con-
sumption should be able to address these potential
tradeoffs. Policies should not affect the required
increase in food security in less developed coun-
tries neither the livelihood of the rural poor should
be put in danger through intensification of animal
This study provides a rich data source for further
studies on the factors that determine how animal
products put pressure on the global water re-
sources. The reported incidents of groundwater
depletion, rivers running dry and increasing levels
of pollution form an indication of the growing
water scarcity (Gleick 1993; Postel 2000; UNESCO
2009). As animal production and consumption play
an important role in depleting and polluting the
world’s scarce freshwater resources, information on
the water footprint of animal products will help us
understand how we can sustainably use the scarce
freshwater resources.
Assessment of the Water Footprint of Farm Animals 413
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License which permits any noncommercial use,
distribution, and reproduction in any medium,
provided the original author(s) and source are
Aldaya MM, Martinez-Santos P, Llamas MR. 2010. Incorporat-
ing the water footprint and virtual water into policy: Reflec-
tions from the Mancha Occidental Region, Spain. Water Res
Manag 24(5):941–58.
Bouwman AF, Van der Hoek KW, Eickhout B, Soenario I. 2005.
Exploring changes in world ruminant production systems.
Agric Syst 84:121–53.
Bouwman L, Goldewijk KK, Van Der Hoek KW, Beusen AHW,
Van Vuuren DP, Willems J, Rufino MC, Stehfest, E. 2011.
Exploring global changes in nitrogen and phosphorus cycles in
agriculture induced by livestock production over the 1900-
2050 period. Proceedings of the National Academy of Sciences
USA doi:10.1073/pnas.1012878108.
Capper JL, Cady RA, Bauman DE. 2009. The environmental
impact of dairy production: 1944 compared with 2007. J
Animal Sci 87(6):2160–7.
Chapagain AK, Hoekstra AY. 2004. Water footprints of nations.
Value of Water Research Report Series No. 16. Available on-
line: [].
Delft, the Netherlands: UNESCO-IHE.
Chapagain AK, Hoekstra, AY. 2003. Virtual water flows between
nations in relation to trade in livestock and livestock products.
Value of Water Research Report Series No. 13. Available on-
line: []. Delft,
the Netherlands: UNESCO-IHE.
Chapagain AK, Hoekstra AY, Savenije HHG, Gautam R. 2006.
The water footprint of cotton consumption: an assessment of
the impact of worldwide consumption of cotton products on
the water resources in the cotton producing countries. Ecol
Econom 60(1):186–203.
De Fraiture C, Wichelns D, Rockstro
m J, Kemp-Benedict E,
Eriyagama N, Gordon LJ, Hanjra MA, Hoogeveen J, Huber-
Lee A, Karlberg L. 2007. Looking ahead to 2050: scenarios of
alternative investment approaches. In: Molden D, Ed. Water
for food, water for life: a comprehensive assessment of water
management in agriculture. London, Colombo: Earthscan,
International Water Management Institute. pp 91–145.
FAO. 2003. Technical conversion factors for agricultural com-
modities. Available online: [
plates/ess/documents/methodology/tcf.pdf]. Rome: Food and
Agriculture Organization.
FAO. 2005. Livestock policy brief 02. Rome: Food and Agricul-
ture Organization.
FAO. 2009. FAOSTAT database. Available online: [http://faos-]. Rome: Food and Agriculture Organization.
Fraser D. 2008. Toward a global perspective on farm animal
welfare. Appl Animal Behav Sci 113(4):330–9.
Galloway J, Burke M, Bradford GE, Naylor R, Falcon W, Chap-
again AK, Gaskell JC, McCullough E, Mooney HA, Oleson KLL,
Steinfeld H, Wassenaar T, Smil V. 2007. International trade in
meat: the tip of the pork chop. Ambio 36:622–9.
Gerbens-Leenes W, Hoekstra AY, Van der Meer TH. 2009. The
water footprint of bioenergy. Proc Natl Acad Sci 106(25):
Gleick PH, Ed. 1993. Water in crisis: a guide to the world’s fresh
water resources. Oxford: Oxford University Press. p 473.
Gustafson RH, Bowen RE. 1997. Antibiotic use in animal agri-
culture. J Appl Microbiol 83(5):531–41.
Hanasaki N, Inuzuka T, Kanae S, Oki T. 2010. An estimation of
global virtual water flow and sources of water withdrawal for
major crops and livestock products using a global hydrological
model. J Hydrol 384:232–44.
Hendy CRC, Kleih U, Crawshaw R, Phillips M. 1995. Livestock
and the environment finding a balance: Interactions between
livestock production systems and the environment, Impact
domain: concentrate feed demand. Available at: [www.fao.
org/wairdocs/lead/x6123e/x6123e00.htm#Contents]. Rome:
Food and Agriculture Organization.
Herrero M, Thornton PK, Gerber P, Reid RS. 2009. Livestock,
livelihoods and the environment: understanding the trade-
offs. Curr Opin Environ Sustain 1(2):111–20.
Hoekstra AY. 2010. The water footprint of animal products. In:
D’Silva J, Webster J, Eds. The meat crisis: developing more
sustainable production and consumption. London: Earthscan.
p 22–33.
Hoekstra AY, Chapagain AK. 2007. Water footprints of nations:
water use by people as a function of their consumption pat-
tern. Water Res Manag 21(1):35–48.
Hoekstra AY, Chapagain AK. 2008. Globalization of water:
Sharing the planet’s freshwater resources. Oxford: Blackwell
Publishing. p 208.
Hoekstra AY, Chapagain AK, Aldaya MM, Mekonnen MM.
2011. The water footprint assessment manual: Setting the
global standard. London: Earthscan. p 203.
Keyzer MA, Merbis MD, Pavel IFPW, Van Wesenbeeck CFA.
2005. Diet shifts towards meat and the effects on cereal use: Can
we feed the animals in 2030? Ecol Econom 55(2):187–202.
Lewis JM, Klopfenstein TJ, Stock RA, Nielsen MK. 1990. Eval-
uation of intensive vs extensive systems of beef production
and the effect of level of beef cow milk production on post-
weaning performance. J Animal Sci 68(8):2517–24.
Liu J, You L, Amini M, Obersteiner M, Herrero M, Zehnder AJB,
Yang H. 2010. A high-resolution assessment on global nitro-
gen flows in cropland. Proc Natl Acad Sci 107(17):8035–40.
McAlpine CA, Etter A, Fearnside PM, Seabrook L, Laurance WF.
2009. Increasing world consumption of beef as a driver of
regional and global change: A call for policy action based on
evidence from Queensland (Australia), Colombia and Brazil.
Global Environ Change 19(1):21–33.
McEwen SA. 2006. Antibiotic use in animal agriculture: what
have we learned and where are we going? Animal Biotechnol
Mekonnen MM, Hoekstra AY. 2010. A global and high-resolu-
tion assessment of the green, blue and grey water footprint of
wheat. Hydrol Earth Syst Sci 14(7):1259–76.
Mekonnen MM, Hoekstra AY. 2011. The green, blue and grey
water footprint of crops and derived crop products. Hydrol
Earth Syst Sci 15(5):1577–600.
Myers N, Kent J. 2003. New consumers: the influence of affluence
on the environment. P Natl Acad Sci USA 100(8):4963–8.
Naylor R, Steinfeld H, Falcon W, Galloway J, Smil V, Bradford E,
Alder J, Mooney H. 2005. Agriculture: losing the links be-
tween livestock and land. Science 310(5754):1621–2.
414 M. M. Mekonnen and A. Y. Hoekstra
Nepstad DC, Stickler CM, Almeida OT. 2006. Globalization of the
Amazon soy and beef industries: opportunities for conserva-
tion. Conserv Biol 20(6):1595–603.
Peden D, Tadesse G, Misra AK, Ahmed FA, Astatke A, Ayalneh
W, Herrero M, Kiwuwa G, Kumsa T, Mati B, Mpairwe D,
Wassenaar T, Yimegnuhal A. 2007. Water and livestock for
human development. In: Molden D, Ed. Water for food, water
for life: a comprehensive assessment of water management in
agriculture. London: Earthscan International Water Manage-
ment Institute. p 485–514.
Pelletier N, Tyedmers P. 2010. Forecasting potential global
environmental costs of livestock production 2000–2050. Proc
Natl Acad Sci USA 107(43):18371–4.
Pimentel D, Berger B, Filiberto D, Newton M, Wolfe B, Karabi-
nakis E, Clark S, Poon E, Abbett E, Nandagopal S. 2004. Water
resources: agricultural and environmental issues. Bioscience
Postel SL. 2000. Entering an era of water scarcity: the challenges
ahead. Ecol Appl 10(4):941–8.
Postel SL, Daily GC, Ehrlich PR. 1996. Human appropriation of
renewable freshwater. Science 271(5250):785–8.
Renault D, Wallender WW. 2000. Nutritional water productivity
and diets. Agric Water Manag 45:275–96.
Rost S, Gerten D, Bondeau A, Lucht W, Rohwer J, Schaphoff S.
2008. Agricultural green and blue water consumption and
its influence on the global water system. Water Resource
Research 44:W09405. doi:10.1029/2007WR006331.
C, Steinfeld H. 1996. World livestock production systems:
current status, issues and trends. Animal production and
health paper 127. Rome: Food and Agriculture Organization.
Smart AJ, Derner JD, Hendrickson JR, Gillen RL, Dunn BH,
Mousel EM, Johnson PS, Gates RN, Sedivec KK, Harmoney
KR, Volesky JD, Olson KC. 2010. Effects of grazing pressure
on efficiency of grazing on North American Great Plains
rangelands. Rangeland Ecol Manag 63(4):397–406.
Smith DL, Harris AD, Johnson JA, Silbergeld EK, Morris JG.
2002. Animal antibiotic use has an early but important impact
on the emergence of antibiotic resistance in human com-
mensal bacteria. Proc Natl Acad Sci USA 99(9):6434–9.
Steinfeld H, Gerber P, Wassenaar T, Castel V, Rosales M, de Haan
C. 2006. Livestock’s long shadow: environmental issues and
options. Rome: Food and Agriculture Organization. p 390.
Sutton MA, Oenema O, Erisman JW, Leip A, Van Grinsven H,
Winiwarter W. 2011. Too much of a good thing. Nature
Thompson PB, Ed. 2008. The ethics of intensification: Agricul-
tural development and cultural change. The International
Library of Environmental, Agricultural and Food Ethics Vol.
16. New York: Springer. doi:10.1007/978-1-4020-8722-6.
Tilman D, Fargione J, Wolff B, D’antonio C, Dobson A, Howarth
R, Schindler D, Schlesinger WH, Simberloff D, Swackhamer D.
2001. Forecasting agriculturally driven global environmental
change. Science 292(5515):281–4.
UNESCO. 2009. Water in a changing world: The United Nations
World Water Development Report 3. Paris: UNESCO Pub-
lishing, Earthscan.
Van Breugel P, Herrero M, Van De Steeg J, Peden D. 2010.
Livestock water use and productivity in the Nile Basin. Eco-
systems 13(2):205–21.
Wheeler RO, Cramer GL, Young KB, Ospina E. 1981. The world
livestock product, feedstuff, and food grain system, an analysis
and evaluation of system interactions throughout the world,
with projections to 1985 Little Rock (AK): Winrock Interna-
Wint GRW, Robinson TP. 2007. Gridded livestock of the world
2007. Rome: Food and Agriculture Organization.
Witte W. 1998. Medical consequences of antibiotic use in agri-
culture. Science 279(5353):996–7.
Zimmer D, Renault D. 2003. Virtual water in food production
and global trade: review of methodological issues and pre-
liminary results. In: Hoekstra AY, Ed. Virtual water trade:
Proceedings of the International Expert Meeting on Virtual
Water Trade. Value of Water Research Report Series No.12,
Available at [
port12.pdf] Delft, The Netherlands: UNESCO-IHE. p93-109.
Assessment of the Water Footprint of Farm Animals 415
... Water footprint chains in plants is typically less than estimated for livestock production (Mekonnen & Hoekstra, 2010). However, when compared to virtual water used in coffee production, independently of the management evaluated in this study, overcomes the water footprint of poultry (4,474.0 ...
... V = virtual water content (m³ t ha -1 ); pf = Product fraction (t per t of primary product). around 19,500.0 m 3 t -1 exceeds the water footprint of coffee (Hoekstra & Hung, 2002;Mekonnen & Hoekstra, 2010). ...
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Water footprint of Arabica coffee from "Matas de Minas" under shade management 1 Studies related to climate change and agricultural value chains have in common the growing concern on conserving water resources. Thus, the concept of the water footprint stands out, which measures the amount of water (in volume) necessary to produce a unit (in mass) of a given product. Among Brazilian agricultural activities, coffee farming emerges as one of the most important, even though the crop is sensitive to potential climatic changes, especially to the increase in temperature and periods of drought. An alternative to mitigate the effects of climate change is shade management, which is common in agroforestry systems. Therefore, the objective of this study was to evaluate the influence of shade management on the water footprint of coffee activity in the region of "Matas de Minas". The water footprint was calculated for the field and product processing phase. Despite reducing the evapotranspiration of the coffee plant, shade management provided an increase in the water footprint, since it decreased the crop yield. The water footprint data obtained are expressive, with a calculated value of 13,862 m 3 t-1 for full sun management and 16,895 m 3 t-1 for shade management, in which both are the most recommended for the agricultural sector.
... Among agricultural sectors, beef production has particularly come under scrutiny. Accusations of large amounts of water use and land degradation by beef production lead to a common recommendation of reducing meat consumption in order to decrease water use (Marlow et al., 2009;Mekonnen and Hoekstra, 2010). However, such generalizations are based on estimates of the virtual water content of meat, which fails to describe the environmental relevance of water use in a product life cycle (Ridoutt et al., 2012). ...
... (2013) reported a total water footprint of about 20,000 L/kg; however, approximately 18,000 L/kg of the total footprint is attributed to green water. Mekonnen and Hoekstra (2010) reported m 3 /ton green water values as 19,102, blue water as 525, and grey water as 590, which is equivalent to 21,056 L/kg green water, 579 L/ kg blue water, and 650 L/kg grey water for a US grazing beef production system. ...
Conference Paper
ABSTRACT: A study was conducted with the objective to determine the rumen microbiome and fermentation parameters of three ruminally cannulated Angus-crossbred heifers (232 + 12 kg BW) on dormant native rangelands over one year. We hypothesize that as seasons of the year change so will diet quality, rumen fermentation end products and bacterial populations present in the rumen. Heifers were maintained on native range and supplemented 20% CP range cube. Ruminal fluid was collected from April, 2016 to February, 2017 approximately every two to three months for ruminal ammonia, VFA, and bacterial population composition. Amplification and sequencing of the V4 hypervariable region of the 16S rRNA gene using the Illumina MiSeq. Bacteroidetes (43.4%) and Firmicutes (40.5%) were the major phyla throughout the sampling period. Firmicutes differed by day with the greatest population occurring February (45.8 + 2.2%), while Bacteroidetes did not differ by sampling day. The predominant genera throughout study remained Prevotella (17.4%) and Bacteroides (9.3%) and did not differ by sampling day (P > 0.15). Total VFA concentrations (P < 0.01) and acetate:propionate (P < 0.01) increased for the duration of the study. Ammonia levels differed by sampling day with the greatest level occurring during February (17.0 + 1.4%). These data shows the rumen fermentation parameters and microbiome are influenced by the varying diet quality that occurs on native rangelands. Key words: Ruminal ammonia, Microbiome, Rangeland
... However, many studies have focused on diets, providing total WFs per product or category without differentiating between the WFs of different production systems [41][42][43], which can vary quite substantially. For instance, in the case of livestock production, extensive grassland-based systems generally present lower blue-and nitrogen-related grey WFs compared with intensive landless systems [44]. Another example is the organic crop production versus the conventional production system. ...
... Scattered studies comparing both systems also point to significant differences in blue and grey WFs between them [45,46]. Further research is needed to include the green, blue, and grey WFs and related impacts of the different types of livestock production systems and organic versus conventional production systems in diet studies as they vary in terms of water pressure [44][45][46]. ...
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Today, human activities are highly dependent on fossil fuels and industrialized forms of agriculture and have reached a level that could damage the Earth’s systems [...]
... These values are taken for the district level from Shrestha et al. (2013), and the total crop yield of the district was from district agriculture statistics. Total water use by livestock was calculated by taking the per capita cattle water use (daily drinking water and service water) (Mekonnen & Hoekstra 2010) and the total livestock population in the district. The number of beef cattle, buffalo, goats, pigs, fowl, and ducks, obtained from the district agriculture and livestock statistics, were included in the calculation. ...
The newly enacted national water policy is envisioned as ensuring water sustainability in Nepal. Despite theoretical pertinence, questions remain about the effective implementation due to limited studies on key aspects of sustainability, such as water supply and demand, pollution, and impacts of climate change and socio-economic growth. This study analyses the current and future availability of water under climate change scenarios and determines water resources carrying capacity (WRCC) as the maximum socio-economic growth that can be supported in a case study on the Kaski District, Nepal. Annual average water availability was estimated to be 11,030.7 million cubic meters (MCM) for the baseline period (1992–2010), and 7,677.4 and 7,674.2 MCM for the future period (2022–2050) under the representative concentration pathway (RCP) 4.5 and 8.5 emission scenarios, respectively. For the baseline period, WRCC far exceeds the current population; therefore, water resources will not be a limiting factor for local socio-economic development. Nevertheless, sustainable water infrastructure development policies are necessary to ensure a reliable water supply able to cope with increasing seasonal variability and declining future water availability. A total of 30,049 tons of biological oxygen demand (BOD) loads were estimated based on the economic activities of the Kaski District in 2011, with the direct and indirect sectoral roles of water pollution determined for the first time. Rather than a single pollution control strategy based on pollution loads, multiple sector-specific strategies are necessary to effectively implement water pollution control policies.
... It has been confirmed by similar studies that the WF of agricultural activities is relatively high, especially in arid regions with continental climates [17,36]. The WF of animal husbandry aims to produce meat, milk, or other products from cattle, sheep, goats, camels, and poultry [81,82] and the total volume of water is used directly and indirectly [83]. The total water used for the production of fodders (forage) crops corresponds to approximately one-third of all agricultural activities on a global scale [84], it is calculated within the livestock WF in the current study. ...
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Rapid urbanization, pollution, and increasing water consumption together with climate change necessitated to process of more effective measurement, management, and decision mechanisms on regional water resources. The concept of water footprint (WF) is a parameter that has been introduced to the scientific literature in recent years similar to the ecological and carbon footprints. The WF of any field or product refers to the total volume of water resources that are processed or contaminated directly or indirectly during the production process. The current work is the first study assessing and discussing the agricultural water footprint of an Iraqi governorate by analyzing blue and green WFs of agricultural production in Qadisiyah governorate, southern Iraq for 2010-2020. Recently developed WF methodology has been used. The blue and green evapotranspiration amounts were estimated by the crop water requirement (CWR) option in CROPWAT 8.0 software. The statistical data including meteorological data, rainfall statistics, local crop coefficients, cultivation area, crop production amounts and animal statistics data have been utilized. The average annual agricultural WF of Qadisiyah governorate for the 10 years between 2010-2020 was determined to be 1,315,201,621 Mm ³ /yr. The largest water-consuming sector is crop production (54%). Cereal and feed crops are the main component of water consumption. The rice crop followed by wheat is the primary crop production comprising about 44% of the total WF and require water supplied from rivers. Vegetable production has only 14% of the crops WF. The green WF was only 15% of the crop production WF. The largest share of water used for animal production is related to broiler chickens (44%) and 37% for dairy cattle. The study area is fertile land for crop production. However, limited water resources and scarcity of the region restrict the agricultural activities. The sustainability of freshwater resources of the governorate could be provided by reducing the WF and blue water contents. This study is expected to contribute to the national authorities to develop more accurate irrigation water management policies.
... The water quality standard of the receiving water is crucial in determining the grey WF. The Water Footprint Network (WFN) defines the grey WF as the volume of freshwater required to dilute a pollutant so that its concentration meets the 'prevailing water quality standards' (Mekonnen and Hoekstra 2010;Hoekstra et al. 2011). However, what constitutes the appropriate prevailing water quality standard is equivocal and dependent on the end use of the water in question. ...
The Canterbury Region of New Zealand has undergone rapid and significant land use intensification over the last three decades resulting in a substantial increase of nitrate-nitrogen leached to the environment. In this article, we determined the nitrate grey water footprint of milk, which is the amount of water needed to dilute nitrogen leached past the root zone to meet different receiving water nitrate standards per milk production unit. Our analysis revealed the nitrate grey water footprint for Canterbury ranged from 433 to 11,110 litres of water per litre of milk, depending on the water standards applied. This footprint is higher than many estimates for global milk production, and reveals that footprints are very dependent on inputs included in the analyses and on the water quality standards applied to the receiving water. The extensive dairy farming in Canterbury is leading to significant pollution of the region’s groundwater, much of which is used for drinking water. Dairy farming at this intensity is unsustainable and if not reduced could pose a significant risk to human health and the market perception of the sustainability of the New Zealand dairy industry and its products.
Official dietary guidelines emphasize the importance of consuming pulses due to the advantageous nutritional composition and based on aspects of public health and sustainable production. Along with a global trend of increased focus on sustainability, launching locally produced plant-based food products have thus gained commercial interest. The purpose of this study is to investigate various pulses and how information about their origin affects the willingness to try and willingness to pay for hummus made from these pulses. In addition, variation seeking tendencies and attitude towards the environment were measured. The research design is a quantitative study including data obtained via online surveys. Respondents,(N = 363 Danish speaking and resident consumers) were presented with images of one traditional chickpea and four experimental versions of pulse-based hummus. Participants were presented with representative photos of the hummus samples and respective pulses and randomly selected to be given information regarding origin of the pulses (n = 164) or presented blind (n = 199). To investigate modulation of variation seeking tendency and individual attitude towards the environment, the VARSEEK scale and EAI-24 scale were applied respectively. Results suggest that providing information regarding origin has a positive effect on willingness to try and willingness to pay. Increase in variety seeking tendency significantly increased both willingness to try, willingness to pay, and ratings for appetizing appearance. Increased attitude towards the environment showed only a slightly significant increase on appetizing appearance. Furthermore, providing information about the pulses to respondents, particularly the segment with low variation seeking tendency had a significantly positive effect on willingness to try and ratings of appetizing appearance.
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La Corporación Destino Paraíso surgió en el año 2008 mediante la asociatividad de entes gubernamentales y privados, con recursos del BID, por medio de un proyecto que tuvo una duración de 3 años. Sin embargo, la corporación tuvo un proceso de deserción de asociados debido a la percepción de algunos de no recibir beneficios significativos, por lo cual, actualmente cuenta con catorce asociados que sostienen la corporación con la idea de dar continuidad a sus principios y lograr su misión y objetivos planteados. Debido a lo anterior, resulta determinante el planteamiento de estrategias de posicionamiento para el Corredor Turístico Destino Paraíso, donde la corporación juegue un papel protagónico, apoyando a sus integrantes conherramientas útiles que les permita fortalecerse como entidad. Para ello, se realizó una investigación con enfoque cuantitativo usando técnicas cualitativas como la encuesta, aplicada tanto a los asociados como a algunos clientes, y una entrevista a autoridades y expertos del sector con el fin de identificar el estado y posicionamiento del corredor turístico. Se evidenció que la corporación se encuentra inmersa en una añoranza del pasado que no le ha permitido evolucionar para adaptarse a las nuevas dinámicas turísticas, pues posee una trayectoria y marca que no puede desestimarse y, por el contrario, se debe fortalecer mediante los beneficios del marketing digital y relacional tanto con entes gubernamentales como con los clientes de los negocios asociados a la corporación. Palabras Clave: Estrategias de posicionamiento, Corporación Destino Paraíso, Corredor turístico, Marketing turístico, Estrategias de marketing.
Since the adoption of the open-door policy, the Chinese dietary pattern has changed greatly. Based on the dietary changes, this study analyzed the arable land and water footprints (WFs) for the food consumption of urban and rural residents in China. The results showed that the arable land demand and WFs for meat, vegetable oil, soybeans and liquor exceeded those for other foods, and the per capita arable land and WFs for food consumption of urban residents were higher than those of rural residents. The total arable land and WFs for the food consumption of residents increased by 16.9 million ha (from 91.1 to 108 million ha) and 214.5 billion m³ (from 457.9 to 672.4 billion m³), respectively, from 1983 to 2017. Specifically, the total arable land and WFs for the food consumption of urban residents increased by 45.9 million hm² (from 22.6 to 68.5 million hm²) and 318.3 billion m³ (from 113.2 to 431.5 billion m³), respectively. Additionally, those of rural residents decreased by 29.7 million hm² (from 69.2 to 39.5 million hm²) and 103.9 billion m³ (344.8 to 240.9 billion m³), respectively, mainly due to the migration of the rural population to cities and the reductions in per capita arable land and WFs due to increased crop yields. The arable land and blue WFs required for food consumption will reach 127.7 million hm² and 221.1 billion m³, respectively, in 2030. However, these values will be reduced by approximately 23% and 20%, respectively, to 98.9 million hm² and 177.8 billion m³ under a balanced dietary pattern. Measures such as improving the investment in agricultural research and development, advocating a balanced diet, and increasing the import of resource-intensive foods could alleviate the pressure on land and water resources.
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This paper uses Nielsen Homescan data from 2014 to 2019 to investigate consumer spending on plant‐based meat alternative (PBMA) products. First, we measure determinants of different PBMA spending levels and summarize spending on PBMA and other food products. We then examine spending over time on PBMA and other food items when a household first purchases a PBMA product. A household spends USD 8 on PBMA products in the first month it purchases PBMA. PBMA spending, however, drops by over 75% in the months following this initial purchase. Spending on meat does not decrease in the first month these households purchase PBMA, though spending on dairy, deli, and dry grocery products does drop.
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People use a lot of water for drinking, cooking and washing, but significantly more for producing things such as food, paper and cotton clothes. The water footprint is an indicator of water use that looks at both direct and indirect water use of a consumer or producer. Indirect use refers to the 'virtual water' embedded in tradable goods and commodities, such as cereals, sugar or cotton. The water footprint of an individual, community or business is defined as the total volume of fresh water that is used to produce the goods and services consumed by the individual or community or produced by the business. This book offers a complete and up-to-date overview of the global standard on water footprint assessment as developed by the Water Footprint Network. More specifically it: provides a comprehensive set of methods for water footprint assessment shows how water footprints can be calculated for individual processes and products, as well as for consumers, nations and businesses contains detailed worked examples of how to calculate green, blue and grey water footprints describes how to assess the sustainability of the aggregated water footprint within a river basin or the water footprint of a specific product includes an extensive library of possible measures that can contribute to water footprint reduction. Arjen Y. Hoekstra is Professor in Water Management at the University of Twente, the Netherlands; creator of the water footprint concept and Scientific Director of the Water Footprint Network. Ashok K. Chapagain was an irrigation engineer in Nepal for more than a decade, has worked as a researcher at the University of Twente and currently works for the WWF in the UK. Maite M. Aldaya works as a consultant for the United Nations Environment Programme (UNEP) and is a researcher at the Water Footprint Network.
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A description of the methods used to produces FAO's Gridded Livestock of the World datasets, along with illustrations of the potential and actual uses of these data.
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The increasing demands placed on the global water supply threaten biodiversity and the supply of water for food production and other vital human needs. Water shortages already exist in many regions, with more than one billion people without adequate drinking water. In addition, 90% of the infectious diseases in developing countries are transmitted from polluted water. Agriculture consumes about 70% of fresh water worldwide; for example, approximately 1000 liters (L) of water are required to produce 1 kilogram (kg) of cereal grain, and 43,000 L to produce 1 kg of beef. New water supplies are likely to result from conservation, recycling, and improved water-use efficiency rather than from large development projects.
Globalization of Water is a first-of-its-kind review of the critical relationship between globalization and sustainable water management. It explores the impact of international trade on local water depletion and pollution and identifies "water dependent" nations. Examines the critical link between water management and international trade, considering how local water depletion and pollution are often closely tied to the structure of the global economy Offers a consumer-based indicator of each nation's water use: the water footprint Questions whether trade can enhance global water use efficiency, or whether it simply shifts the environmental burden to a distant location Highlights the hidden link between national consumption and the use of water resources across the globe, identifying the threats facing 'water dependent' countries worldwide Provides a state-of-the-art review and in-depth data source for a new field of knowledge.
Fresh water is a renewable resource, but it is also finite. Around the world, there are now numerous signs that human water use exceeds sustainable levels. Groundwater depletion, low or nonexistent river flows, and worsening pollution levels are among the more obvious indicators of water stress. In many areas, extracting more water for human uses jeopardizes the health of vital aquatic ecosystems. Satisfying the increased demands for food, water, and material goods of a growing global population while at the same time protecting the ecological services provided by natural water ecosystems requires new approaches to using and managing fresh water. In this article, I propose a global effort (1) to ensure that freshwater ecosystems receive the quantity, quality, and timing of flows needed for them to perform their ecological functions and (2) to work toward a goal of doubling water productivity. Meeting these challenges will require policies that promote rather than discourage water efficiency, as well as new partnerships that cross disciplinary and professional boundaries.
During the past half century, the less industrialized countries experienced rapid increases in animal production through both large-scale confinement systems and traditional small-scale systems. These countries now produce the majority of the world's meat. The regulations and other programs designed to safeguard animal welfare in the European and English-speaking countries may prove ineffective in the diverse and burgeoning production systems of the less industrialized nations. However, improvements to animal welfare may still be achieved (1) through the basic economic incentive to reduce losses caused by injury, stress and malnutrition, (2) through disease control programs, as long as these are well conducted, and (3) by international corporations applying their existing animal welfare standards on a more global basis. Moreover, low labour costs in less industrialized countries could allow labour-intensive, non-confinement systems to flourish, especially if there is an international market for such products. Although animal welfare plays no role in the agreements of the World Trade Organization, internationally recognized standards may still be incorporated by mutual agreement in bilateral and multilateral trade agreements, and they may be required in future by international food companies and their customers. There are important opportunities for animal welfare scientists to support animal protection initiatives in the less industrialized countries, especially through technical assistance programs, research and education.