ArticlePDF Available

Dietary greenhouse gas emissions of meat-eaters, fish-eaters, vegetarians and vegans in the UK


Abstract and Figures

The production of animal-based foods is associated with higher greenhouse gas (GHG) emissions than plant-based foods. The objective of this study was to estimate the difference in dietary GHG emissions between self-selected meat-eaters, fish-eaters, vegetarians and vegans in the UK. Subjects were participants in the EPIC-Oxford cohort study. The diets of 2,041 vegans, 15,751 vegetarians, 8,123 fish-eaters and 29,589 meat-eaters aged 20-79 were assessed using a validated food frequency questionnaire. Comparable GHG emissions parameters were developed for the underlying food codes using a dataset of GHG emissions for 94 food commodities in the UK, with a weighting for the global warming potential of each component gas. The average GHG emissions associated with a standard 2,000 kcal diet were estimated for all subjects. ANOVA was used to estimate average dietary GHG emissions by diet group adjusted for sex and age. The age-and-sex-adjusted mean (95 % confidence interval) GHG emissions in kilograms of carbon dioxide equivalents per day (kgCO(2)e/day) were 7.19 (7.16, 7.22) for high meat-eaters ( > = 100 g/d), 5.63 (5.61, 5.65) for medium meat-eaters (50-99 g/d), 4.67 (4.65, 4.70) for low meat-eaters ( < 50 g/d), 3.91 (3.88, 3.94) for fish-eaters, 3.81 (3.79, 3.83) for vegetarians and 2.89 (2.83, 2.94) for vegans. In conclusion, dietary GHG emissions in self-selected meat-eaters are approximately twice as high as those in vegans. It is likely that reductions in meat consumption would lead to reductions in dietary GHG emissions.
Content may be subject to copyright.
Dietary greenhouse gas emissions of meat-eaters,
fish-eaters, vegetarians and vegans in the UK
Peter Scarborough &Paul N. Appleby &Anja Mizdrak &
Adam D. M. Briggs &Ruth C. Travis &
Kathryn E. Bradbury &Timothy J. Key
Received: 24 October 2013 / Accepted: 31 May 2014
#The Author(s) 2014. This article is published with open access at
Abstract The production of animal-based foods is associated with higher greenhouse gas
(GHG) emissions than plant-based foods. The objective of this study was to estimate the
difference in dietary GHG emissions between self-selected meat-eaters, fish-eaters, vegetarians
and vegans in the UK. Subjects were participants in the EPIC-Oxford cohort study. The diets of
2,041 vegans, 15,751 vegetarians, 8,123 fish-eaters and 29,589 meat-eaters aged 2079 were
assessed using a validated food frequency questionnaire. Comparable GHG emissions param-
eters were developed for the underlying food codes using a dataset of GHG emissions for 94
food commodities in the UK, with a weighting for the global warming potential of each
component gas. The average GHG emissions associated with a standard 2,000 kcal diet were
estimated for all subjects. ANOVA was used to estimate average dietary GHG emissions by diet
group adjusted for sex and age. The age-and-sex-adjusted mean (95 % confidence interval)
GHG emissions in kilograms of carbon dioxide equivalents per day (kgCO
e/day) were 7.19
(7.16, 7.22) for high meat-eaters (>=100 g/d), 5.63 (5.61, 5.65) for medium meat-eaters (50-
99 g/d), 4.67 (4.65, 4.70) for low meat-eaters (< 50 g/d), 3.91 (3.88, 3.94) for fish-eaters, 3.81
(3.79, 3.83) for vegetarians and 2.89 (2.83, 2.94) for vegans. In conclusion, dietary GHG
emissions in self-selected meat-eaters are approximately twice as high as those in vegans. It is
likely that reductions in meat consumption would lead to reductions in dietary GHG emissions.
1 Introduction
Production, transport, storage, cooking and wastage of food are substantial contributors to green-
house gas (GHG) emissions (Committee on Climate Change 2010;Garnett2008;
Intergovernmental Panel on Climate Change 2007). These GHG emissions include carbon dioxide
(from fossil fuels used to power farm machinery and to transport, store and cook foods), methane
Climatic Change
DOI 10.1007/s10584-014-1169-1
P. Scarborough (*):A. Mizdrak :A. D. M. Briggs
British Heart Foundation Centre on Population Approaches for Non-Communicable Disease Prevention,
Nuffield Department of Population Health, University of Oxford,
Old Road Campus, Headington, Oxford OX3 7LF, UK
P. N. Appleby :R. C. Travis :K. E. Bradbury:T. J. Key
Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Old Road
Campus, Roosevelt Drive, Oxford OX3 7LF, UK
(from enteric fermentation in ruminant livestock) and nitrous oxide (released from tilled and
fertilised soils). Both methane and nitrous oxide are many times more potent GHGs than carbon
dioxide and the majority of GHG emissions related to food are produced at the agricultural stage
(Audsley et al. 2009;Garnett2011). When measured by consumption (that is, all GHG emissions
related to products consumed in the UK, regardless of where they were produced) food is
responsible for approximately one fifth of all GHG emissions attributable to the UK (Berners-Lee
et al. 2012;Garnett2008). There is considerable variation in the amount of GHG emissions related
to different food groups, with animal-based products generally having much greater emissions than
plant-based products per unit weight (Audsley et al. 2009; Carlsson-Kanyama and Gonzalez 2009;
Committee on Climate Change 2010; Gonzalez et al. 2011; Steinfeld et al. 2006). This is largely
because of the inefficiencies involved in growing cereal crops to be used as animal feed, and
methane produced in the digestive system of ruminants (Steinfeld et al. 2006). Although new
technologies and changes in farming practices provide some scope for reduction in GHG emissions,
substantial reductions can only be achieved through changes in consumption patterns and reduction
in food waste (Stehfest et al. 2009; Weidema et al. 2008). This paper is concerned with differences in
dietary GHG emissions between different diet groups within the UK and contributes to the debate
regarding what constitutes a healthy, sustainable diet. Specifically, we use comparable data on
actual diets of vegans, vegetarians, fish-eaters and meat-eaters to estimate the difference in dietary
GHG emissions attributable to these four diet groups. Previous estimates of dietary GHG emissions
for self-selected dietary groups have not compared meat consumers with those who abstain from
meat (Vieux et al. 2013; Masset et al. 2014). Other estimates of GHG emissions by diet groups have
been produced using modelled estimates of reduced meat diets (Baroni et al. 2007; Berners-Lee et al.
2012; Macdiarmid et al. 2012;Saxeetal.2013; Vieux et al. 2012;Wilsonetal.2013) and may not
reflect true differences in consumption behaviour between dietary groups.
2.1 Subjects and study design
The analyses are based on data from participants in the EPIC-Oxford cohort, which consists of
65,000 participants generally aged 20 and over at recruitment between 1993 and 1999 (Davey
et al. 2003). Participants were resident in the UK and recruited through collaborating general
practitioners, by post via vegetarian and vegan societies, and by adverts in vegetarian and
health food magazines. Participants were also asked to recruit friends and relatives
(snowballing). A validated semi-quantitative food-frequency questionnaire (FFQ) that esti-
mates intake (frequency of consumption) of 130 different food items over the previous
12 months (Bingham et al. 1994; Bingham et al. 1995) was completed at recruitment by most
participants. For the analyses in this paper, we excluded individuals aged less than 20 years or
80 years and over at recruitment (n=532), those who did not complete the FFQ or whose
estimated daily energy intake from the FFQ was outside realistic values (men<3.3 MJ or>
16.7 MJ, women<2.1 MJ or>14.7 MJ) or for whom more than 20 % of relevant food
frequencies were unreported (n=9,304), and 71 participants with unknown diet group, leaving
a final analysis dataset of 12,666 males and 42,838 females.
2.2 Classification of diet groups
For these analyses, six dietary groups were identified: high meat-eaters (>= 100 g/d), medium
meat-eaters (50 to 99 g/d), low meat-eaters (>0 and< 50 g/d), fish-eaters, vegetarians and
Climatic Change
vegans. Initially, subjects were categorised into meat-eaters, fish-eaters, vegetarians and vegans
according to responses to the following yes/no questions:
&Do you eat any meat (including bacon, ham, poultry, game, meat pies, sausages)?
&Do you eat any fish?
&Do you eat any eggs?
&Do you eat any dairy products (including milk, cheese, butter, yoghurt)?
2.3 Calculation of dietary GHG emissions
Nutritional analyses of the 130 food-item FFQ were based on nutritional data for 289 food
codes taken from UK food composition tables, primarily the McCance & Widdowson series
(Roe et al. 2002). We estimated the GHG emissions associated with these 289 food codes,
measured as kgCO
e (that is, kg of GHG weighted by global warming potential over a 100 year
time frame, with carbon dioxide weighted as 1, methane weighted as 25 and nitrous oxide
weighted as 298) per 100 g of food. The method used was adapted from a previous investigation
of the health impact of applying a carbon tax to foods in the UK (Briggs et al. 2013). The source
document for GHG parameters was Audsley et al. (2009), which estimates comparable GHG
emissions for 94 food commodities consumed in the UK. These parameters incorporate the life
cycle of food commodities from the earliest stages of production to the retail distribution centre.
Different parameters are estimated for foods produced in the UK, the EU and outside the EU.
We produced single UK estimates of GHG emissions for each food commodity, weighted by
current import and export patterns using 2007 food balance sheet data from the FAO (Food and
Agriculture Organization. FAOSTAT. July 2013). The weighted estimates for the 94 food
commodities are presented in the appendix. The GHG emissions for the 289 food codes were
then constructed from these 94 parameters using two techniques which we describe below as
adjusting for densityand estimating GHG emissions for recipes.
Adjusting for density For cheese, fruit juices, dried fruit and soya milk, the weight of food that
is consumed is not equivalent to the weight of food that is produced. GHG emissions
parameters for these food categories were not available, so we applied adjustment factors to
their primary commodity to account for the change in weight between production and
consumption. Where possible these adjustment factors were taken from published life cycle
analyses, but when these were unavailable we used information from specific food products.
The adjustment factors that were applied are shown in Table 1.
Estimating GHG emissions for recipes For the remaining food codes a recipe was sought
which was used to split the weight of the food between food commodities. This split was then
used to construct a GHG emissions estimate using the GHG parameters of the original
commodities. The UK food composition table (Roe et al. 2002) which provides nutritional
data for the FFQ was used as the first source for identifying recipes. If no recipe was found
then a Google search was performed with the food code name as the search term and the top
website found with a recipe for the food was used. Where ingredients were identified that were
not comparable to a food commodity (e.g. flaky pastry), then a recipe was identified for the
ingredient using the same method. For each food code the weights of the ingredients were
added in the order of heaviest to lightest, and a 90 % threshold was used such that once a value
greater than 90 % was achieved the remaining ingredients were disregarded. This threshold
was applied to remove small ingredients with unknown GHG emissions from the calculations
Climatic Change
Tab le 1 Adjustment factors for cheese, fruit juices, dried fruit and soya milk
Food Related GHG emissions commodity kgCO2e per 100 g of commodity Adjustment
kgCO2e per 100 g of food Rationale
Cheese Milk 0.184 10.1 1.858 10.1 L of milk required for 1 kg
semi-hard cheese (Berlin 2002)
Orange juice Oranges 0.006 3.2 0.019 3.22 kg of oranges required for 1 kg
of juice (combining natural
and concentrated) (Beccali et al. 2009)
Apple juice Apples 0.072 1.4 0.099 Copella website states 3lbs of apples are
packed into every litre of apple juice
(Copella. Copella fruit juices.
our-juices/juices Accessed July 2013)
Soya milk Soy beans 0.201 0.1 0.025 Recipe website suggests 160 g soy beans
combined with 1.5-2 L of water
( Homemade soy milk.
make-soy-milk/Accessed September
Raisins Grapes 0.083 3.2 0.264 Comparison of water content in grapes
and raisins in UK food composition
tables (Roe et al. 2002)
kgCO2e, kilograms of carbon dioxide equivalents (carbon dioxide has weighting 1, methane has weighting 25, nitrous oxide has weighting 298)
Climatic Change
(e.g. a pinch of nutmeg). We did not account for the cooking process (either at the industrial
stage or at home) for any of the food codes.
For seven food codes (drinking chocolate, chocolate digestive biscuits, semi-sweet biscuits,
Coffeemate, Horlicks powder, mixed toffees, and soft drinks) the use of a recipe seemed
implausible given that these products are largely produced on an industrial scale. Here recipes
were estimated (using percentages in the ingredients list where available) by a single researcher
and agreed by the research team. A complete spreadsheet showing recipes and calculations for
all 289 food codes is available upon request.
2.4 Standardisation of diets to 2,000 kcal
GHG emissions for each individual were standardised to a 2,000 kcal daily diet (the level used for
guideline daily energy intake for adults in the UK) so that differences in estimated energy consump-
tion between diet groups do not affect the results. This was done for three reasons. Firstly, the FFQ
does not allow for differences in portion sizes of fruit, vegetables and cereals which may differ
between dietary groups and could exaggerate differences in energy intake between groups. Secondly,
to address under and over-reporting that is common to diet studies (Scagliusi et al. 2008). Thirdly, so
that the standardised results can be used to estimate the change in GHG emissions that would result
from changing between dietary groups without changing the energy intake of the diet, which may be
more relevant when considering the potential impact of changing diets on GHG emissions.
2.5 Statistical analysis
The arithmetic means and standard deviations of dietary GHG emissions for each diet group
were calculated. An ANOVA was conducted to estimate GHG emissions by diet group
adjusted for sex and age, categorised in 10 years age bands from 2029 to 7079. Statistical
significance was set at the 5 % level and all analyses were conducted using the Stata statistical
package (StataCorp 2011).
The analysis dataset included 2,041 vegans, 15,751 vegetarians, 8,123 fish-eaters and 29,589
meat-eaters. Baseline characteristics by meat consumption are shown in Table 2. Meat-eaters
tended to be older than fish-eaters, vegetarians and vegans. Assuming an ordered
categorisation (high meat medium meat low meatfish-eaters vegetariansvegans),
there were significant trends towards lower total fat, saturated fat and protein consumption and
higher carbohydrate, total sugar, fibre and fruit and vegetables consumption as animal-based
food consumption decreased.
Table 3shows differences in dietary GHG emissions by diet group. The highest dietary
GHG emissions were found in high meat-eating men and the lowest dietary GHG emissions
were found in vegan women. The mean observed values of dietary GHG emissions for meat-
eaters (results reported for women and then men) was 46 % and 51 % higher than for fish-
eaters, 50 % and 54 % higher than for vegetarians and 99 % and 102 % higher than for vegans.
The results of the ANOVA analysis showed highly statistically significant differences
(p<0.0001) in dietary GHG emissions between the six diet groups after adjustment
for age and sex, with progressively higher emissions for groups with greater intakes
of animal-based products.
Climatic Change
Tab le 2 Descriptive statistics
High meat
Medium meat
Low meat
Fish-eaters Vegetarians Vegans p for
N 29,589 8,286 11,971 9,332 8,123 15,751 2,041
Mean (SD) age at recruitment 49.1 (12.8) 49.7 (12.3) 49.8 (12.6) 47.5 (13.3) 41.8 (12.9) 38.6 (12.7) 37.3 (13.1) <0.0001
% female 76.9 72.1 77.8 80.0 82.2 76.9 63.4 0.13
Mean (SD) energy intake (kcal/d) 1,972 (535) 2,214 (528) 1,933 (500) 1,809 (508) 1,889 (526) 1,872 (528) 1,747 (554) <0.0001
Mean (SD) total fat (% energy) 31.6 (5.9) 33.2 (5.4) 31.4 (5.7) 30.5 (6.2) 30.7 (6.3) 30.5 (6.5) 28.0 (7.3) < 0.0001
Mean (SD) saturated fat (% energy) 11.5 (3.3) 12.4 (3.1) 11.5 (3.2) 10.9 (3.4) 10.6 (3.3) 10.6 (3.4) 6.5 (2.1) <0.0001
Mean (SD) protein (% energy) 17.0 (3.0) 18.5 (3.1) 17.1 (2.8) 15.6 (2.5) 14.7 (2.4) 13.6 (2.1) 13.3 (2.3) < 0.0001
Mean (SD) carbohydrate (% energy) 48.0 (6.2) 45.0 (5.7) 48.1 (5.7) 50.5 (6.3) 51.0 (6.5) 52.5 (6.6) 55.6 (7.8) < 0.0001
Mean (SD) total sugars (% energy) 24.3 (5.7) 22.5 (5.1) 24.4 (5.4) 25.8 (6.3) 25.1 (6.3) 25.4 (6.3) 24.7 (8.7) <0.0001
Mean (SD) dietary fibre (NSP; g/d) 18.7 (6.8) 18.6 (6.2) 18.3 (6.5) 19.4 (7.4) 21.3 (7.5) 21.6 (7.8) 26.1 (9.3) < 0.0001
Mean (SD) fruit and vegetables (80 g portions/d) 6.4 (3.5) 6.1 (3.2) 6.3 (3.2) 6.9 (4.0) 7.3 (3.9) 7.1 (3.9) 8.7 (5.6) <0.0001
SD, Standard deviation
High meat= 100 g/d meat consumption; Medium meat =5099 g/d; Low meat =<50 g/d. p values indicate significance of trend along ordered categorisation high meat medium
meatlow meat fish-eatersvegetariansvegans
Climatic Change
Tab le 3 Mean greenhouse gas emissions per 2,000 kcal by diet type and sex
Men (observed values) Women (observed values) Adjusted for age and sex
N Mean dietary GHG emissions
SD N Mean dietary GHG emissions
SD Mean dietary GHG emissions
95 % CIs
All meat-eaters 6,380 5.93 2.01 22,759 5.71 1.75
High meat-eaters (100 g/day) 2,310 7.26 2.11 5,976 7.17 1.94 7.19 (7.16, 7.22)
Medium meat-eaters (5099 g/day) 2,654 5.66 1.60 9,317 5.62 1.38 5.63 (5.61, 5.65)
Low meat-eaters ( <50 g/day) 1,866 4.67 1.35 7,466 4.67 1.05 4.67 (4.65, 4.70)
Fish-eaters 1,448 3.94 1.12 6,675 3.90 0.88 3.91 (3.88, 3.94)
Vegetarians 3,641 3.85 1.29 12,110 3.80 0.93 3.81 (3.79, 3.83)
Vegans 747 2.94 1.25 1,294 2.87 0.90 2.89 (2.83, 2.94)
SD, Standard deviation; CIs, Confidence intervals; N, Number of Participants
kgCO2e, kilograms of carbon dioxide equivalents
Climatic Change
We have shown that dietary GHG emissions associated with self-selected diets in the UK are
strongly associated with the amount of animal-based products in the diet. After adjustment for
sex and age, an average 2,000 kcal high meat diet had 2.5 times as many GHG emissions than
an average 2,000 kcal vegan diet. This is the first study to demonstrate these differences in real
self-selected diets of meat eaters and those who abstain from meat. There were also significant
trends towards lower saturated fat, higher fibre and higher fruit and vegetable intake (but a
higher intake of sugars) as the quantity of animal-based products in the diet decreases.
Previous analyses of the same cohort have demonstrated lower BMI (Davey et al. 2003)and
fewer ischaemic heart disease events (Crowe et al. 2013) in diet groups with lower intakes of
animal products. Improved cardiovascular outcomes for vegetarian diets have been demon-
strated in meta-analyses of cohort studies conducted in western populations (Huang et al.
2012; Key et al. 1999). Although observational studies are susceptible to residual confounding,
non-systematic reviews of RCTs have demonstrated beneficial effects of plant-based diets on
lipids (Ferdowsian and Barnard 2009) and weight status (Berkow and Barnard 2006). This
suggests that advice to reduce the amount of meat and animal-based products in the diet would
be consistent with the definition of a healthy, sustainable diet, although reductions of meat at
the population level may pose nutritional challenges for key nutrients including iron and zinc
which should be monitored (Millward and Garnett 2010).
A recent representative survey in the UK using four day weighted food diaries, the National
Diet and Nutrition Survey 2008/10 (Bates et al. 2012), found that the average amount of meat
consumed in adults aged 1964 (including non-consumers) was 110 g/day, which suggests that
the majority of adults in the UK would be categorised as high meat consumersin our analysis.
Reducing the amount of animal-based products in the diet represents an achievable way for an
individual to reduce their carbon footprint. Assuming that the average daily energy intake in the
UK is 2,000 kcal, then moving from a high meat diet to a low meat diet would reduce an
individuals carbon footprint by 920kgCO
e every year, moving from a high meat diet to a
vegetarian diet would reduce the carbon footprint by 1,230kgCO
e/year, and moving from a high
meat diet to a vegan diet would reduce the carbon footprint by 1,560kgCO
e/year. For context, an
individual travelling on an economy return flight from London to New York has an addition to
their carbon footprint of 960kgCO
e (Carbon Footprint. Carbon footprint calculator. www. Accessed July 2013). A family running a 10 year old small
family car for 6,000miles has a carbon footprint of 2,440kgCO
e (Carbon Footprint. Carbon
footprint calculator. Accessed July 2013), roughly
equivalent to the annual carbon saving of two high meat eating adults moving to a vegetarian diet.
Two previous studies have estimated the difference in dietary GHG emissions of self-
selected dietary groups (Vieux et al. 2013;Massetetal.2014). Both of these studies were
based on the representative Individual and National Survey on Food consumption in France.
Vieux et al. (2013) showed that those who consumed a healthy diet, defined by low energy
density, high nutrient density and low consumption of saturated fat, sugar and sodium, had
higher dietary GHG emissions than those who consumed an unhealthy diet. Consumption of
ruminant meat and pork, poultry and eggs was similar in both healthy and unhealthy diet
groups. Masset et al. (2014) showed that diets with lower than average GHG emissions tended
to be less healthy, defined using a nutrient density index. These low GHG diets consisted of
approximately 20 % less meat, fish and eggs than the average diet. They also identified a
subset of the population who consumed a healthy and low GHG emissions diet which did not
cost more than an average diet and which was characterised by a higher content of plant-based
products. In contrast to the study reported here, the authors did not directly compare diet
Climatic Change
groups defined by levels of meat consumption. Other studies have estimated the difference in
dietary GHG emissions between diet groups, but have used modelled reduced meat dietary
scenarios for comparison. The modelling has been conducted using three methods: diets have
been constructed from scratch with reference to nutritionists (Baroni et al. 2007); observed
meat-eating diets have been modified with selected replacement foods(Berners-Lee et al.
2012;Saxeetal.2013;); or optimisation programmes have constructed a low-meat diet that
meets several pre-determined sustainability and nutritional criteria (Macdiarmid et al. 2012;
Vieux et al. 2012; Wilson et al. 2013). Most of these modelling studies suggested that reducing
animal-based products would reduce dietary GHG emissions (Baroni et al. 2007; Berners-Lee
et al. 2012; Macdiarmid et al. 2012;Saxeetal.2013), but one scenario considered by Vieux
et al. (2012) suggested that reduced meat diets may increase dietary GHG emissions. In this
scenario, meat was isocalorically replaced in the diet by fruit and vegetables - since the GHG
emissions per 100 kcal of food in their database were generally higher for fruit and vegetables
than for meat products, this resulted in an increase in GHG emissions. Saxe et al. (2013)found
that a vegetarian diet in Denmark would reduce dietary GHG emissions compared to the
average Danish diet by 27 %, compared to our estimate of 35 % reduction between meat eaters
and vegetarians. The difference may be due to the criterion in the Saxe et al. analysis that the
vegetarian diet should contain equal protein levels as the average Danish diet in the EPIC-
Oxford sample protein levels are significantly lower in vegetarians than in meat-eaters. By
comparing the actual diets of self-selected diet groups, our results are not limited by restrictive
criteria that may not be representative of true dietary behaviour. However, our data are based
on cross-sectional comparisons between dietary groups, and as such they do not tell us how
people would replace meat in the diet (although, the diet groups do at least represent diets that
are actually consumed in the population). This is an important limitation that should be
addressed by future longitudinal studies with repeated dietary measures.
The GHG emissions data used in this paper were developed specifically for this analysis.
Although the nutrient intakes estimated by the FFQ have been validated against food diaries and
some biomarkers (Bingham et al. 1994; Bingham et al. 1995), the GHG emissions have not. The
GHG estimates for food items used in this paper are subject to uncertainty that is not captured in
the confidence intervals shown in this paper for example, LCAs of animal-based foods have
shown considerable variation in GHG estimates, due to differences in methods used and in forms
of agricultural production (Nijdam et al. 2012; de Vries and de Boer 2010; Roy et al. 2009).
Estimates of total food-related GHG emissions using measurements of food consumption (such as
the FFQ) are underestimates because they do not take account of food wastage. Throughout the
analyses presented here we have assumed that GHG emission related to food wastage is
reasonably similar across all food groups, but this may not be the case. Estimates of food wastage
in the UK suggest that wastage of fruit and vegetables is higher than for meat products (Quested
et al. 2013), which could reduce the difference in GHG emissions between the dietary groups.
Consumption estimates derived from FFQs are also prone to under-reporting (Becker and Welten
2001; Scagliusi et al. 2008). Similarly, we have not adjusted for differences in raw and cooked
weight of foods in these analyses. In most instances, such an adjustment results in smaller cooked
weights, as it incorporates discarding inedible material (e.g. bones, skin, cores etc.), which would
inflate the size of the dietary GHG estimates reported here.
The diets observed in the EPIC-Oxford cohort may not represent current consumption
patterns in the UK. Firstly, they are taken from the baseline data collection period which was
conducted in the 1990s. Secondly, a large proportion of the meat-eaters in the EPIC-Oxford
cohort consists of family or friends of vegetarians and vegans, who are likely to have diets
which differ from those of the general population in the UK. This difference can be assessed
by comparing the amount of meat consumed in meat-eaters recruited through the snowballing
Climatic Change
technique with those recruited directly by participating GPs. This shows that 24 % of meat-
eaters recruited via the snowballing technique were high meat consumers, compared to 41 %
of meat-eaters recruited directly. Restricting the data by removing participants directly recruit-
ed makes little difference to the results (results not shown). Thirdly, the cohort tended to
consume a healthier diet than the current UK population. For example, average consumption
of fruit and vegetables in the EPIC Oxford cohort is over 6 portions per day, even in the meat
eaters.ThemostrecentNationalDietandNutritionSurvey(Batesetal.2012) estimated that
average consumption in the UK was 4.1 portions per day.
Further work is needed to establish a defined healthy, sustainable diet, which should include the
recommendation to reduce the consumption of animal-based foods. This is already a recommenda-
tion put forward by the Health Council of the Netherlands. Guidelines for a healthy diet: the
ecological perspective. Health Council of the Netherlands: The Hague and The (2011) Although this
study has only considered the impact of food on GHG emissions, reducing animal-based food
consumption has also been proposed as a mechanism for achieving global food security given future
trends in yield and agricultural land use (Foley et al. 2011;Godfrayetal.2010; Ray et al. 2013)and
could also play a role in reducing water stress and biodiversity loss (Steinfeld et al. 2006). Although
the epidemiological evidence largely supports the health-promoting effects of a vegetarian diet, this
evidence is primarily drawn from observational studies and residual confounding cannot be ruled
out. Further research is required to determine the longitudinal health effects of reducing animal-
based products within the diet, preferably in randomised trials. This work should consider micro-
nutrient intakes in vulnerable groups (Macdiarmid 2013; Millward and Garnett 2010)aswellasrisk
factors for cardiovascular disease and cancer.
The current trend in the UK is towards increased meat consumption. The percentage of
vegetarians and vegans in UK adults has decreased from an estimated 5 % in 2000/01 to 2 % in
2008/10, although these estimates are based on relatively small samples (Bates et al. 2012;
Henderson et al. 2002). Over the same period FAOSTAT estimates that total meat supply in the
UK increased from 78.5 kg/person/year to 84.2 kg/person/year (Food and Agriculture Organization.
FAO STAT. Accessed July 2013), including an
increase in consumption of beef in 1961 (when FAOSTAT records began) total meat supply
was only 69.2 kg/person/year. It is necessary to find strategies and interventions that can turn this
trajectory around and support a population that is increasingly unfamiliar with a low meat diet.
Analysis of observed diets shows a positive relationship between dietary GHG emissions and
the amount of animal-based products in a standard 2,000 kcal diet. This work demonstrates
that reducing the intake of meat and other animal based products can make a valuable
contribution to climate change mitigation. Other work has demonstrated other environmental
and health benefits of a reduced meat diet. National governments that are considering an
update of dietary recommendations in order to define a healthy, sustainable dietmust
incorporate the recommendation to lower the consumption of animal-based products.
Acknowledgments Peter Scarborough is supported by a programme grant from the British Heart Foundation
(021/P&C/Core/2010/HPRG). Anja Mizdrak is supported by the Oxford Martin School. The EPIC-Oxford
Cohort study is supported by Cancer Research UK. Adam DM Briggs is supported by the National Institute
for Health Research.
Conflicts of interest Timothy J Key is a member of the Vegan Society. The authors have no other conflicts of
interest to declare.
Climatic Change
Open Access This article is distributed under the terms of the Creative Commons Attribution License which
permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are
Table 4 Greenhouse gas emis-
sions for the 94 food commodities,
weighted for production in the UK,
imports from the EU, and imports
from outside the EU
Food category UK GHG emissions (kgCO2e/kg)
Alcoholic Beverages 3.3
Animal Fats 40.1
Apples 0.7
Aquatic Animals, Others 0.0
Aquatic Plants 0.0
Aquatic Products, Other 0.0
Bananas 1.4
Barley 3.8
Beans 0.8
Beer 3.8
Beverages, Alcoholic 3.5
Beverages, Fermented 2.4
Bovine Meat 68.8
Butter, Ghee 1.8
Cephalopods 5.4
Cereals - Excluding Beer 1.8
Cereals, Other 1.8
Citrus, Other 0.7
Cocoa Beans 3.4
Coconut Oil 2.1
Coconuts - Incl Copra 2.1
Coffee 10.1
Cream 2.4
Crustaceans 5.4
Dates 1.1
Demersal Fish 5.4
Eggs 4.9
Fats, Animals, Raw 35.6
Fish, Body Oil 0.0
Fish, Liver Oil 0.0
Fish, Seafood 5.4
Freshwater Fish 5.4
Fruits - Excluding Wine 0.9
Fruits, Other 0.9
Grapefruit 0.8
Grapes 0.8
Groundnut Oil 0.9
Groundnuts (Shelled Eq) 1.4
Honey 1.0
Lemons, Limes 0.6
Climatic Change
Tab le 4 (continued)
Food category UK GHG emissions (kgCO2e/kg)
Maize 0.7
Maize Germ Oil 0.4
Marine Fish, Other 5.4
Meat 35.9
Meat, Other 35.7
Milk - Excluding Butter 1.8
Molluscs, Other 0.0
Mutton & Goat Meat 64.2
Oats 1.0
Offals 35.9
Oilcrops 1.8
Oilcrops Oil, Other 2.4
Oilcrops, Other 2.3
Olive Oil 4.5
Olives 4.5
Onions 0.5
Oranges, Mandarines 0.6
Palm Oil 3.3
Palmkernel Oil 0.0
Peas 1.2
Pelagic Fish 5.4
Pepper 2.5
Pigmeat 7.9
Pimento 3.2
Pineapples 1.9
Plantains 1.6
Potatoes 0.4
Poultry Meat 5.4
Pulses 3.3
Pulses, Other 3.5
Rape and Mustard Oil 2.9
Rape and Mustardseed 2.9
Rice (Milled Equivalent) 3.9
Rye 1.0
Sesameseed 4.2
Sesameseed Oil 4.2
Soyabean Oil 1.8
Soyabeans 2.0
Spices 1.6
Spices, Other 1.6
Starchy Roots 0.4
Stimulants 0.0
Sugar & Sweeteners 0.1
Sugar (Raw Equivalent) 0.1
Sunflowerseed Oil 3.3
Sweeteners, Other 0.0
Climatic Change
Audsley E, Brander M, Chatterton J, Murphy-Bokern D, Webster C, Williams A (2009) How low can we go? an
assessment of greenhouse gas emissions from the UK food system and the scope to reduce them by 2050.
Food Climate Research Network & WWF, London, UK
Baroni L, Cenci L, Tettamanti M, Berati M (2007) Evaluating the environmental impacts of various dietary
patterns combined with different food production systems. Eur J Clin Nutr 61:279286
Bates B, Lennox A, Prentice A, Bates C, Swan G (2012) National diet and nutrition survey. Headline results from
years 1, 2 and 3 (combined) of the rolling programme (2008/20092010/11). Department of Health, London, UK
Beccali M, Cellura M, Iudicello M, Mistretta M (2009) Resource consumption and environmental impacts of the
agrifood sector: life cycle assessment of Italian citrus-based products. Environ Manag 43:707724
Becker W, Welten D (2001) Under-reporting in dietary surveys implications for development of food-based
dietary guidelines. Public Health Nutr 4:683687
Berkow S, Barnard N (2006) Vegetarian diets and weight status. Nutr Rev 64(4):17588
Berlin J (2002) Environmental life cycle assessment (LCA) of Swedish semi-hard cheese. Int Dairy J 12(11):939953
Berners-Lee M, Hoolohan C, Cammack H, Hewitt C (2012) The relative greenhouse gas impacts of realistic
dietary choices. Energy Policy 43:184190
Bingham SA, Gill C, Welch A, Day K, Cassidy A, Khaw KT, Sneyd MJ, Key TJA, Roe L, Day NE (1994)
Comparison of dietary assessment methods in nutritional epidemiology: weighed records v. 24 h recalls,
food-frequency questionnaires and estimated-diet records. Br J Nutr 72:619643
Bingham SA, Cassidy A, Cole TJ, Welch A, Runswick SA, Black AE, Thurnham D, Bates C, Khaw KT, Key
TJA et al (1995) Validation of weighed records and other methods of dietary assessment using the 24 h urine
nitrogen technique and other biological markers. Br J Nutr 73:531550
Briggs A, Kehlbacher A, Tiffin R, Garnett T, Rayner M, Scarborough P. Incorporating the societal cost of
greenhouse gases into the price of foods could save lives from cardiovascular disease and cancer in England:
a comparative risk assessment modelling study. BMJ Open, 2013 (in press)
Carbon Footprint. Carbon footprint calculator. Accessed July 2013.
Carlsson-Kanyama A, Gonzalez A (2009) Potential contributions of food consumption patterns to climate
change. Am J Clin Nutr 89:1S6S
Committee on Climate Change (2010) The fourth carbon budget. Reducing emissions through the 2020s.
Committee on Climate Change, London, UK
Copella. Copella fruit juices. Accessed July 2013.
Crowe F, Appleby P, Travis R, Key T (2013) Risk of hospitalization or death from ischemic heart
disease among British vegetarians and nonvegetarians: results from the EPIC-Oxford cohort study.
Am J Clin Nutr 97:597603
Davey G, Spencer E, Appleby P, Allen N, Knox K, Key T (2003) EPIC-Oxford: lifestyle characteristics and
nutrient intakes in a cohort of 33,883 meat-eaters and 31,546 non meat-eaters in the UK. Public Health Nutr
de Vries M, de Boer I (2010) Comparing environmental impacts for livestock products: a review of life cycle
assessments. Livest Sci 128:111
Ferdowsian H, Barnard N (2009) Effects of plant-based diets on plasma lipids. Am J Cardiol 104(7):94756
Foley J, Ramankutty N, Brauman K, Cassidy E, Gerber J, Johnston M et al (2011) Solutions for a cultivated
planet. Nature 478:337342
Tab le 4 (continued)
Food category UK GHG emissions (kgCO2e/kg)
Tea 1 .9
Tomatoes 1.5
Treenuts 2.0
Vegetable Oils 3.2
Vegetable s 1.6
Vegetables, Other 2.2
Wheat 1.0
Wine 1.0
Climatic Change
Food and Agriculture Organization. FAOSTAT. Accessed July 2013.
Garnett T (2008) Cooking up a storm. Food, greenhouse gas emissions and our changing climate. Food Climate
Research Network, Guildford, UK
Garnett T (2011) Where are the best opportunities for reducing greenhouse gas emissions in the food system
(including the food chain)? Food Policy 36:S23S32
Godfray C, Beddington J, Crute I, Haddad L, Lawrence D, Muir J et al (2010) Food security: the challenge of
feeding 9 billion people. Science 327:812818
Gonzalez A, Frostell B, Carlsson-Kanyama A (2011) Protein efficiency per unit energy and per unit greenhouse
gas emissions: potential contribution of diet choices to climate change mitigation. Food Policy 36:562570
Health Council of the Netherlands. Guidelines for a healthy diet: the ecological perspective. Health Council of
the Netherlands: The Hague, The Netherlands, 2011.
Henderson L, Gregory J, Swan G (2002) The national diet and nutrition survey. Adults aged 19 to 64. Volume 1:
types and quantities of foods consumed. HMSO, London
Huang T, Yang B, Zheng J, Li G, Wahlqvist ML, Li D (2012) Cardiovascular disease mortality and cancer
incidence in vegetarians: a meta-analysis and systematic review. Ann Nutr Metab 60:233240
Intergovernmental Panel on Climate Change (2007) IPCC fourth assessment report: climate change 2007. IPCC,
Geneva, Switzerland
Key TJ, Fraser GE, Thorogood M, Appleby PN, Beral V, Reeves G, Burr ML, Chang-Claude J, Frentzel-Beyme
R, Kuzma JW, Mann J, McPherson K (1999) Mortality in vegetarians and nonvegetarians: detailed findings
from a collaborative analysis of 5 prospective studies. Am J Clin Nutr 70(3S):516S524S
Macdiarmid J (2013) Is a healthy diet and environmentally sustainable diet? Proc Nutr Soc 72(1):1320
Macdiarmid J, Kyle J, Horgan G, Loe J, Fyfe C, Johnstone A, McNeill G (2012) Sustainable diets for the future:
can we contribute to reducing greenhouse gas emissions by eating a healthydiet? Am J Clin Nutr 96:632639
Masset G, Vieux F, Verger E, Soler L-G, Touazi D, Darmon N. Reducing energy intake and energy density for a
sustainable diet: a study based on self-selected diets in French adults. American Journal of Clinical Nutrition,
Millward D, Garnett T (2010) Food and the planet: nutritional dilemmas of greenhouse gas emission reductions
through reduced intakes of meat and dairy foods. Proc Nutr Soc 69(1):1031118
Nijdam D, Rood T, Westhoek H (2012) The price of protein: review of land use and carbon footprints from life
cycle assessments of animal food products and their substitutes. Food Policy 37:760770
Quested T, Ingle R, Parry A (2013) Household food and drink waste in the United Kingdom 2012. WRAP, London
Ray D, Mueller N, West P, Foley J (2013) Yield trends are insufficient to double global crop production by 2050.
PLoS One 8(6):e66428
Roe M, Finglas P, Church S (2002) McCanceand Widdowsons the composition of foods, 6th edn. Royal Society
of Chemistry, London, UK
Roy P, Nei D, Orikasa T, Xu Q, Okadome H, Nakamura N, Shiina T (2009) A review of life cycle assessment
(LCA) on some food products. J Food Eng 90(1):110
Saxe H, Larsen TM, Morgensen L (2013) The global warming potential of two healthy Nordic diets compared
with the average Danish diet. Clim Chang 116:249262
Scagliusi F, Ferriolli E, Pfrimer K, Laureano C, Cunha C, Gualano B, Lourenco B, Lancha A (2008) Under-
reporting of energy intake is more prevalent in a healthy dietary pattern cluster. Br J Nutr 100(5):10601068 Homemade soy milk.
to-make-soy-milk/ Accessed September 2013.
StataCorp (2011) Stata: release 12. College Station, Texas
Stehfest E, Bouwman L, van Vuuren D, den Elzen M, Eickhout B, Kabat P (2009) Climate benefits of changing
diet. Clim Chang 95:83102
Steinfeld H, Gerber P, Wassenaar T, Castel V, Rosales M, de Haan C (2006) Livestocks long shadow:
environmental issues and options. FAO, Rome, Italy
Vieux F, Darmon N, Touazi D, Soler L (2012) Greenhouse gas emissions of self-selected individual diets in
France: changing the diet structure or consuming less? Ecol Econ 75:91101
Vieux F, Soler L-G, Touazi D, Darmon N (2013) High nutritional quality is not associated with low greenhouse
gas emissions in self-selected diets of French adults. Am J Clin Nutr 97:569583
Weidema B, Hermansen J, Kristensen T, Halberg N (2008) Environmental improvement potentials of meat and
dairy products. European Commission, Brussels, Belgium
Wilson N, Nghiem N, Ni Mhurchu C, Eyles H, Baker M, Blakely T (2013) Foods and dietary patterns that are
healthy, low-cost, and environmentally sustainable: a case study of optimization modelling for New Zealand.
PLoS One 8(3):e59648
Climatic Change
... The unmitigated effects of the global food system on GHG emissions could grow by~50-80% by 2050 [3,4], which, along with unmitigated fossil fuel emissions, portend unconscionable risks on the agricultural sector, including systemic crop failures, dilution of the nutritional quality of food for human and animal consumption, and especially profound impacts on small shareholder farms in developing economies [5][6][7][8]. Alternatively, the food system has been identified as a key sector for climate mitigation and aggressive action, particularly via the deployment of technologies that reduce GHG emissions and increase C sequestration in agricultural systems [9][10][11][12][13]. Whether the future food system adds to or reduces GHG emissions, and thereby contributes to global climate targets, hinges on a mix of consumer decisions, technology deployment, management practices, and policies. ...
... Food system transformation has the capacity to radically reduce GHG emissions and could possibly achieve sector-wide net negative emissions, which is defined as the point wherein gross GHG emissions are lower than gross GHG removal (i.e., carbon dioxide removal, carbon dioxide equivalent removal, and C sequestration, referred to as CDR hereafter). Several studies have analyzed scenarios under which GHG emissions can be reduced through consumer decisions, particularly a switch in the foods consumed and their consequent effects on agricultural GHG emissions [9][10][11][12]. When consumers rely more heavily on plant sourced foods grown under conventional practices [9,12], for example, the amount of land required to support human nutrition may be reduced [9,13], potentially increasing natural ecosystem CDR via land sparing and vegetation recovery. ...
... Several studies have analyzed scenarios under which GHG emissions can be reduced through consumer decisions, particularly a switch in the foods consumed and their consequent effects on agricultural GHG emissions [9][10][11][12]. When consumers rely more heavily on plant sourced foods grown under conventional practices [9,12], for example, the amount of land required to support human nutrition may be reduced [9,13], potentially increasing natural ecosystem CDR via land sparing and vegetation recovery. Furthermore, sheep, cattle, and goats emit methane (CH 4 ), a potent GHG. ...
Full-text available
Most climate mitigation scenarios point to a combination of GHG emission reductions and CO 2 removal for avoiding the most dangerous climate change impacts this century. The global food system is responsible for ~1/3 of GHG emissions and thus plays an important role in reaching emission targets. Consumers, technology innovation, industry, and agricultural practices offer various degrees of opportunity to reduce emissions and remove CO 2 . However, a question remains as to whether food system transformation can achieve net negative emissions (i.e., where GHG sinks exceed sources sector wide) and what the capacity of the different levers may be. We use a global food system model to explore the influence of consumer choice, climate-smart agro-industrial technologies, and food waste reductions for achieving net negative emissions for the year 2050. We analyze an array of scenarios under the conditions of full yield gap closures and caloric demands in a world with 10 billion people. Our results reveal a high-end capacity of 33 gigatonnes of net negative emissions per annum via complete food system transformation, which assumes full global deployment of behavioral-, management- and technology-based interventions. The most promising technologies for achieving net negative emissions include hydrogen-powered fertilizer production, livestock feeds, organic and inorganic soil amendments, agroforestry, and sustainable seafood harvesting practices. On the consumer side, adopting flexitarian diets cannot achieve full decarbonization of the food system but has the potential to increase the magnitude of net negative emissions when combined with technology scale-up. GHG reductions ascribed to a mixture of technology deployment and dietary shifts emerge for many different countries, with areas of high ruminant production and non-intensive agricultural systems showing the greatest per capita benefits. This analysis highlights potential for future food systems to achieve net negative emissions using multifaceted “cradle-to-grave” and “land-to-sea” emission reduction strategies that embrace emerging climate-smart agro-industrial technologies.
... Animal-based foods have been widely recognised as having the highest environmental impact (Willett et al., 2019). Among those, meats, especially beef, are considered the food with the highest impact from all environmental sustainability perspectives, being the main contributors to climate change because they have the highest greenhouse gas emissions and land and water use (Scarborough et al., 2014;Willett et al., 2019). For this reason, dietary patterns restringing animal foods, such as plant-based diets, are constantly considered sustainable (Carey et al., 2023). ...
... The food sector is a major contributor to climate change, responsible for one-third of global greenhouse gas emissions [45]. Research has shown that shifting to a diet that includes low-impact foods like plants can reduce the food sector's emissions by half [52]. However, there are many barriers that prevent consumers from making this shift, including a lack of knowledge about the environmental impact of individual food choices [24,38,41] and which foods are considered sustainable [35,45]. ...
Full-text available
Food consumption is one of the biggest contributors to climate change. However, online grocery shoppers often lack the time, motivation, or knowledge to contemplate a food's environmental impact. At the same time, they are concerned with their own well-being. To empower grocery shoppers in making nutritionally and environmentally informed decisions, we investigate the efficacy of the Scale-Score, a label combining nutritional and environmental information to highlight a product's benefit to both the consumer's and the planet's health, without obscuring either information. We conducted an online survey to understand user needs and requirements regarding a joint food label, we developed an open-source mock online grocery environment, and assessed label efficacy. We find that the Scale-Score supports nutritious purchases, yet needs improving regarding sustainability support. Our research shows first insights into design considerations and performance of a combined yet disjoint food label, potentially altering the label design space.
... In 2019, 37 researchers from 16 countries collaboratively published the Eat-Lancet report (Willett et al., 2019), which advocates for the global adoption of a predominantly plant-based diet, and significant reductions in consumption of animal products such as dairy, in order to reduce greenhouse gas emissions from methane, as well as to avoid severe environmental degradation (Steinfeld et al., 2006;Scarborough et al., 2014). The first advisory report from the UK's Committee on Climate Change in 2020 also echoes these recommendations, arguing that a shift away from meat and dairy consumption must be encouraged if the UK is to reach its net-zero greenhouse gas emission target by 2050 (Committee on Climate Change, 2020). ...
Full-text available
Existing regulation in the UK states that the term ‘milk’ can only be used in labelling to describe products that originate from animals. We conducted an observational study, which surveyed the availability and labelling of milk substitutes in UK supermarkets, and an online experimental study, which assessed the impact of using the term ‘milk’ on milk substitute labelling. In the experimental study, 352 UK adults were randomised to one of the two conditions where they saw milk substitutes that were either labelled with UK regulations (e.g., soya drink) or using the term ‘milk’ (e.g., soya milk). Our primary aims were to assess whether adding the term ‘milk’ to labels would (1) more accurately communicate the uses of milk substitutes or (2) confuse consumers about which products come from an animal source. In our observational study, milk substitutes were readily available and labelling varied significantly. In our experimental study, labelling products with the term ‘milk’ increased understanding of the product's use. However, participants who saw the term ‘milk’ on milk substitute labelling misidentified more milk substitutes as coming from an animal source. Future policy should consider the clarification of such labelling.
Full-text available
Konjonktürel gelişme ve değişmeler diğer alanlarda olduğu gibi tüketici tercihlerini de etkilemektedir. Bilinçlenen ve duyarlılığı artan tüketicilerin sürdürülebilirlik kapsamında yer alan çevre, hayvan, doğayı koruma alanlarında eko-sisteme daha fazla önem vermeye başlaması ile birlikte, tüketici alışkanlıklarının beslenme, kozmetik, giyim vb. sektörlerde farklılaştığı görülmektedir. Vegan ve vejetaryen satın alma davranışları, yaşam tarzını şekillendirmeye evrilmektedir. Bu yaşam tarzını benimseyen tüketicilerin her geçen gün artmasıyla birlikte, tüketici davranışlarını etkileyen faktörler arasında eko-sistem önemli olmaya başlamış ve işletmeler ürün ve/veya hizmetlerine vegan ve vejetaryen içerik eklemeleri ile bu hedef pazarları da seçmiştir. Vegan ve vejetaryen tüketimin ekolojik, sosyal ve ekonomik sürdürülebilirlikle ilişkisinin önemli rol oynaması ile birlikte, işletme faaliyetleri de bu tüketim anlayışına yönelmiştir. İşletmeler bu durumu ürün ve hizmetlerini genişletmek, ürün karmasını arttırmak için bir fırsata çevirmekte, vegan ve vejetaryen pazarına yönelik ürünler geliştirmektedir. Tüketicilerin vegan ve vejetaryen tüketim anlayışını benimsemelerinde ekolojik, sosyal, sağlık, din ve etik motivasyonlarının etkisi bulunmaktadır. Bu çalışmada, vegan ve vejetaryen tüketim anlayışını, bu anlayışın sürdürülebilirlik rolünü ve markaların internet sayfalarından vegan ve sürdürülebilir içerik oluşturma durumlarını analiz ederek, öneriler getirmek amaçlanmıştır. En çok tercih edilen vegan markalarda ikincil veri kaynağı (Twentify, 2021) kullanılmış ve bu markaların internet sayfalarının içeriklerinde, vegan ürün kategorisi, sürdürülebilirlik ve vegan tüketim ve sürdürülebilirlik ilişkisinin yer alma durumu, değerlendirilmiştir. Bu markaların bazılarında vegan ürün kategori sayfası ve çok azında sürdürülebilirlik sayfası bulunmakta, hiçbirinde vegan tüketim sürdürülebilirlik ilişkisi açıklanmamaktadır. Yeni bir hedef pazar olan, vegan tüketici grubuna yönelik olarak markaların internet sayfalarında, vegan tüketim ve sürdürülebilirlik ilişkisini de kapsayıcı içerik oluşturmaları önerilmektedir
Full-text available
Climate change, conflicts, and various crises have exposed the vulnerabilities of global food systems. Acute food insecurity and undernourishment have become more prevalent in recent times, and the imperative is to build more robust and sustainable food systems that do not adversely impact the environment. The COVID-19 pandemic has only underlined the importance of food security in times of crises. This brief explores the promise of climate-smart agriculture in combating climate change and global food insecurity, and in nurturing sustainable food systems.
Full-text available
The gut microbiome is a key element for health preservation and disease prevention. Nevertheless, defining a healthy gut microbiome is complex since it is modulated by several factors, such as host genetics, sex, age, geographical zone, drug use, and, especially, diet. Although a healthy diet has proven to increase microbial alpha and beta diversity and to promote the proliferation of health-related bacteria, considering the current environmental and nutritional crisis, such as climate change, water shortage, loss of diversity, and the obesity pandemic, it should be highlighted that a healthy diet is not always sustainable. Sustainable diets are dietary patterns that promote all dimensions of people’s health and well-being while exerting low pressure on the environment, and being accessible, affordable, safe, equitable, and culturally acceptable. Examples of diets that tend to be sustainable are the Planetary Health Diet of the EAT-Lancet Commission or territorial diets such as the Mediterranean and the Traditional Mexican diet (milpa diet), adapted to specific contexts. These diets are principally plant-based but include small or moderate amounts of animal-based foods. Characterising the effects of sustainable diets on gut microbiota is urgent to ensure that the benefits for human health are aligned with environmental preservation and respect the sociocultural aspects of individuals.
Full-text available
Studies on theoretical diets are not sufficient to implement sustainable diets in practice because of unknown cultural acceptability. In contrast, self-selected diets can be considered culturally acceptable. The objective was to identify the most sustainable diets consumed by people in everyday life. The diet-related greenhouse gas emissions (GHGE) for self-selected diets of 1918 adults participating in the cross-sectional French national dietary survey Individual and National Survey on Food Consumption (INCA2) were estimated. "Lower-Carbon," "Higher-Quality," and "More Sustainable" diets were defined as having GHGE lower than the overall median value, a probability of adequate nutrition intake (PANDiet) score (a measure of the overall nutritional adequacy of a diet) higher than the overall median value, and a combination of both criteria, respectively. Diet cost, as a proxy for affordability, and energy density were also assessed. More Sustainable diets were consumed by 23% of men and 20% of women, and their GHGE values were 19% and 17% lower than the population average (mean) value, respectively. In comparison with the average value, Lower-Carbon diets achieved a 20% GHGE reduction and lower cost, but they were not sustainable because they had a lower PANDiet score. Higher-Quality diets were not sustainable because of their above-average GHGE and cost. More Sustainable diets had an above-average PANDiet score and a below-average energy density, cost, GHGE, and energy content; the energy share of plant-based products was increased by 20% and 15% compared with the average for men and women, respectively. A strength of this study was that most of the dimensions for "sustainable diets" were considered, ie, not only nutritional quality and GHGE but also affordability and cultural acceptability. A reduction in diet-related GHGE by 20% while maintaining high nutritional quality seems realistic. This goal could be achieved at no extra cost by reducing energy intake and energy density and tincreasing the share of plant-based products.
Full-text available
This report first presents a systematic overview of the life cycle of meat and dairy products and their environmental impacts, covering the full food chain. It goes on to provide a comprehensive analysis of the improvement options that allow reducing the environmental impacts throughout the life cycle. Finally, the report assesses the different options regarding their feasibility as well as their potential environmental and socioeconomic benefits and costs. The report focuses on improvement options in three main areas: • Household improvements, mainly to reduce food losses (wastage) and to reduce car use for shopping; • Agricultural improvements, mainly to reduce water and air emissions (in particular nitrate, ammonia and methane) and land requirements; • Power savings in farming, food industry, retail, catering, and for household appliances. The study presents the consequences that the adoption of these options might have on a broad range of different environmental issues, including global warming, eutrophication, respiratory health impacts, etc. It shows that when all environmental improvement potentials are taken together, the aggregated environmental impacts (external costs) of meat and dairy products may be reduced by about 20 %. The study has also quantified the economic costs and benefits of implementing the different options.
Full-text available
To model the impact on chronic disease of a tax on UK food and drink that internalises the wider costs to society of greenhouse gas (GHG) emissions and to estimate the potential revenue. An econometric and comparative risk assessment modelling study. The UK. The UK adult population. Two tax scenarios are modelled: (A) a tax of £2.72/tonne carbon dioxide equivalents (tCO2e)/100 g product applied to all food and drink groups with above average GHG emissions. (B) As with scenario (A) but food groups with emissions below average are subsidised to create a tax neutral scenario. Primary outcomes are change in UK population mortality from chronic diseases following the implementation of each taxation strategy, the change in the UK GHG emissions and the predicted revenue. Secondary outcomes are the changes to the micronutrient composition of the UK diet. Scenario (A) results in 7770 (95% credible intervals 7150 to 8390) deaths averted and a reduction in GHG emissions of 18 683 (14 665to 22 889) ktCO2e/year. Estimated annual revenue is £2.02 (£1.98 to £2.06) billion. Scenario (B) results in 2685 (1966 to 3402) extra deaths and a reduction in GHG emissions of 15 228 (11 245to 19 492) ktCO2e/year. Incorporating the societal cost of GHG into the price of foods could save 7770 lives in the UK each year, reduce food-related GHG emissions and generate substantial tax revenue. The revenue neutral scenario (B) demonstrates that sustainability and health goals are not always aligned. Future work should focus on investigating the health impact by population subgroup and on designing fiscal strategies to promote both sustainable and healthy diets.
This article was submitted without an abstract, please refer to the full-text PDF file.
The potential greenhouse gas (GHG) emissions from the production of food for three different diets are compared using consequential Life Cycle Assessment. Diet 1 is an Average Danish Diet (ADD); diet 2 is based on the Nordic Nutritional Recommendations (NNR), whilst diet 3 is a New Nordic Diet (NND) developed by the OPUS project. The NND contains locally produced Nordic foods where more than 75 % is organically produced. NNR and NND include less meat and more fruit and vegetables than the ADD. All diets were adjusted to contain a similar energy and protein content. The GHG emissions from the provision of NNR and NND were lower than for ADD, 8 % and 7 % respectively. If GHG emissions from transport (locally produced versus imported food) are also taken into account, the difference in GHG emissions between NND and ADD increases to 12 %. If the production method (organic versus conventional) is taken into account so that the ADD contains the actual ratio of organically produced food (6.6 %) and the NND contains 80 %, the GHG emissions for the NND are only 6 % less than for the ADD. When the NND was optimised to be more climate friendly, the global warming potential of the NND was 27 % lower than it was for the ADD. This was achieved by including less beef, and only including organic produce if the GHG emissions are lower than for the conventional version, or by substituting all meat with legumes, dairy products and eggs.