Environmental assessment of the impact of school meals in the United Kingdom

Abstract

The aim of this research work is the creation of a robust methodology and a related tool (Environmental Assessment Tool for School meals-EATS) that can facilitate those involved with providing / deriving school meals menus to assess the environmental performance of their school meals. The EATS tool utilizes secondary data to calculate values of carbon footprint and water footprint for a school meal from cradle to plate. This includes four phases: (1) food production, (2) transport of each ingredient from the country of origin to the UK, (3) storage at regional distribution centre and (4) meal preparation in a generic school kitchen. EATS was tested against a set of nutritionally compliant meals; this paper presents the results from which it can be seen that there is a predominance of the production phase in the overall carbon footprint. In addition there is a decrease in carbon and water intensiveness when shifting from meat based recipes to non-meat ones. The main outcome of this work is the creation of a tool that can potentially be used by any school and catering provider in the UK to assess the performance of its menus and which, thanks to its simple user interface, has a great potential for engaging non-scientific audiences on the topic of sustainable food choices.

Full text

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
Environmental assessment of the impact of school meals in the United Kingdom
Valeria De Laurentiis1,*, Dexter V.L. Hunt1 and Christopher D.F. Rogers1
1 Civil Engineering/College of Engineering and Physical Sciences, University of Birmingham, Birmingham B152TT, UK
* Corresponding author: Email: VXD317@bham.ac.uk
ABSTRACT
The aim of this research work is the creation of a robust methodology and a related tool
(Environmental Assessment Tool for School meals - EATS) that can facilitate those involved with
providing / deriving school meals menus to assess the environmental performance of their school
meals. The EATS tool utilizes secondary data to calculate values of carbon footprint and water
footprint for a school meal from cradle to plate. This includes four phases: (1) food production, (2)
transport of each ingredient from the country of origin to the UK, (3) storage at regional distribution
centre and (4) meal preparation in a generic school kitchen.
EATS was tested against a set of nutritionally compliant meals; this paper presents the results from
which it can be seen that there is a predominance of the production phase in the overall carbon
footprint. In addition there is a decrease in carbon and water intensiveness when shifting from meat
based recipes to non-meat ones. The main outcome of this work is the creation of a tool that can
potentially be used by any school and catering provider in the UK to assess the performance of its
menus and which, thanks to its simple user interface, has a great potential for engaging non-scientific
audiences on the topic of sustainable food choices.
Keywords: Public food procurement, carbon footprint, water footprint, environmental impact, sustainable diets.
1. Introduction
There is increasing awareness of the role schools play in both promoting healthy eating habits and
providing education for sustainable development (Jones et al., 2012, Morgan and Sonnino, 2007,
Weitkamp et al., 2013). In the last decade a number of programs have appeared in the literature, with
a shared aim of reconnecting school pupils with the natural component of food. The underlying ethos
of each was to form empowered consumers (i.e. children and parents), aware of the consequences of
their food choices on their health and the environment. In Italy for instance a program called Cultura
che Nutre (Culture that Feeds) was set up in order to teach schoolchildren about the links between
products and places with the sole purpose of making them aware of the value of locally produced high
quality food (Morgan and Sonnino, 2007). Likewise, in the UK the Food for Life Partnership, a
coalition of charities that promote food-based environmental learning in schools, collaborated with
over 3600 schools between 2007 and 2011 (Weitkamp et al., 2013).
Within this context, we propose a methodology and a related tool (Environmental Assessment
Tool for School meals - EATS) that can facilitate those involved with providing / deriving school
meals menus (e.g. catering providers and schools) to assess the environmental performance of their
school meals. The aim is to develop a robust methodology, based on quantitative assessment of the
environmental impacts of food (in terms of carbon footprint and water footprint) that can be used to
assess and compare existing menus and help suggest improvements therein. Additionally this tool can
be used for educational purposes to teach pupils / parents / stakeholders about the impact of food -
engendering more sustainable choices. This paper explains how EATS was created (Section 2) and
how it takes into account the different phases of the life cycle of a meal, whilst in the results section a
number of meals are analyzed and compared using EATS (Section 3). A discussion of the findings is
provided in Section 4 and conclusions are subsequently drawn in Section 5.
2. Methods
The ethos behind EATS is that it should provide the users with a simple-to-use interface (Figure 1)
that allows them to input information on an individual recipe and be provided with respective outputs
on the impact of each portion served.

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
As such the following inputs are required from the user:
- Name, weight and country of production of each ingredient;
- Number of portions required;
- Cooking appliances used and for how long.
The respective outputs are given:
- Carbon Footprint (CF)
- Water Footprint (WF)
Figure 1: Interface for the EATS tool
The study is from Cradle-to-Plate and therefore system boundaries and assumptions are required
within the following phases of the life cycle (Figure 2):
1. Production (Section 2.1);
2. Transport (Section 2.2);
3. Storage at regional distribution centre (RDC) (Section 2.3);
4. Meal Preparation (Section 2.4).
Figure 2: System boundaries and life cycle phases

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
For example, waste is included along Phases 1, 3 and 4 (waste during the transport phase is assumed
to be zero) but waste generated at the consumption stage (i.e. plate waste) is not taken into account.
2.1 Phase 1: Production (cradle to gate)
In this phase EATS provides values of CF and WF for the list of food items within the menu
relative to the production phase. The corresponding values were obtained through the collection of
secondary data, which led to the creation of a database. To ensure completeness of the database, the
food items to be included were obtained from the analysis of the results of the Primary School Food
Survey, a national survey conducted in 2009 by the School Food Trust (Haroun et al., 2009) to collect
information on school dinners across the UK.
For each food item, a search was performed through peer reviewed articles, conference papers,
existing databases and Environment Product Declarations (EPDs) of food items in order to collect
existing values of:
- Carbon Footprint (i.e. Global Warming Potential - GWP): these are calculated following the
life cycle assessment (LCA) methodology, as specified in the ISO 14040/14044 (ISO, 2006a,
b).
- Water Footprint: this includes green, blue and grey-water calculated according to the
methodology set out in Hoekstra et al., (2009) [The authors appreciate that ISO 14046 (2014)
is directly applicable to WF. However, due to data availability, when collecting values of WF
of food products it is preferable to use the methodology developed by Hoekstra et al., (2009)].
When collecting values of GWP, some articles included a range of system boundaries, therefore
only values relative to the ‘production’ phase were extracted.
Emissions related to packaging production were typically included in the system boundaries of the
studies consulted. However, there appeared to be a lack of a systematic approach adopted by authors
in order to verify this.
The functional unit considered in the EATS database is 1 kg of each product. Specifically, for
meat and fish products, the functional unit considered is 1 kg of retail weight. When in the studies
consulted the functional unit was different (e.g. 1 kg of carcass weight or 1 kg of live weight), the
conversion methodology proposed by Nijdam et al. (2012) was adopted.
2.2 Phase 2: Transport
In this phase the EATS tool calculates emissions related to transport for each ingredient inserted
by the user, based on the country of origin selected (these are accessed via a dropdown menu).
Average transport routes from every European capital to the UK and respective values for
transportation distances were taken from the following websites:
- Transport routes from http://www.cargorouter.com/;
- Sea distances from http://www.sea-distances.org/;
- Road distances from http://maps.google.co.uk/.
The corresponding emissions were calculated using coefficients for road freight (1 Km = 0.1625
gCO2/Kg) and sea freight (1 Km = 0.0156 gCO2/Kg) suggested by DEFRA (2015).
2.3 Phase 3: Storage at regional distribution centre (RDC)
Emissions related to storage of food at regional distribution centers (Phase 3) were not included as
they are considered to be negligible (Brunel University, 2008). However, this phase was taken into
account when assessing waste levels through the life cycle of a meal (see Section 2.5).
Similarly, emissions related to refrigerated storage in school kitchens were not included as the
purpose of the tool is to enable a comparison between different meals. [Any changes in the menus

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
offered would unlikely affect the number and size of refrigerators utilized and their consequent energy
use - at least in the short term (Garnett, 2008)].
2.4 Phase 4: Meal Preparation
The contribution to CF of the preparation phase is calculated according to values of energy
consumption (kWh/minute) for a range of cooking appliances - see Carlsson-Kanyama and Faist
(2001) - and the cooking time. These values were converted into corresponding emissions (gCO2)
using coefficients for the UK electricity grid (1 kWh = 0.5311 KgCO2) and natural gas consumption
(1 kWh = 0.2093 KgCO2) provided by DEFRA (2015).
Based on the inputs provided by the user (i.e. type of cooking appliance used, the cooking time
and the number of portions), the tool calculates the relative CF for preparation of each portion(s) of
the meal analyzed. Water use during the preparation phase is assumed negligible when compared to
production phase (Strasburg and Jahno, 2015).
2.5 Waste
The values of CF and WF relative to the production phase are recorded in the EATS database
according to the functional unit of 1 kg at farm/factory gate. When the user inputs the weight of each
ingredient in the tool, these values are scaled accordingly (see example below). However, some
additional considerations are required to account for waste through the remaining parts of the supply
chain (gate to plate). In other words if a recipe requires, for example, 100 g of broccoli, 110 g will
need to leave the farm (Figure 3). These include a rate of 2% waste at regional distribution centers
(RDC), akin to our Phase 3 (Brunel University, 2008) and a rate of 7.4% waste at Phase 4, meal
preparation (Quested et al., 2012)
Figure 3: Food flows through the life cycle of a meal, waste at Phase 2 (transport) is equal to zero
Hence, in this case the user will input 100 g of broccoli into EATS. The tool will extract the
corresponding values of CF from the database (i.e. 1 kg of broccoli = 377 gCO2e) and scale them to
110 g, which equals to 41.5 gCO2e. The same applies to the WF values.
An example application of EATS is provided in the following section.
3. Results
3.1 Application of EATS to an individual recipe.

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
For this paper the example of a fish-based recipe “Salmon and Broccoli Pasta”, suggested by the
School Food Plan Alliance (http://www.schoolfoodplan.com/) was inserted into the EATS tool in
order to assess its environmental performance in terms of CF and WF.
The list of ingredients required as input parameters for this recipe are shown in Table 1. The
respective weighted quantities necessary to produce 13 portions (i.e. a typical primary school serving)
are shown in the right column. The cooking procedure according to the recipe comprises 30 minutes
on an electric stove. The total CF and WF per portion are 382 gCO2e and 113 liters respectively.
Breakdowns of the CF and WF according to each ingredient are represented in Figures 4 and 5
respectively. The figures show that Salmon contributes most significantly to CF (62%) whilst Pasta
contributes most significantly to WF (64%). In fact both Pasta and Milk feature strongly in both the
CF and WF (Pasta – CF = 20% and WF = 64%, Milk – CF = 13% and WF = 22%).
Table 1: Ingredients for Salmon and Broccoli Pasta
Ingredient
Food Name
Country of Production
Weight [g]
1
PASTA
Italy
650
2
SALMON
United Kingdom
800
3
BROCCOLI
United Kingdom
200
4
MARGARINE
United Kingdom
35
5
ONIONS
United Kingdom
100
6
WHEAT FLOUR
United Kingdom
35
7
MILK
United Kingdom
500
8
SPICES
World
5
Figure 4: Contribution of each ingredient to the Carbon Footprint (CF)

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
Figure 5: Contribution of each ingredient to the Water Footprint (WF)
Figure 6 shows the predominance of the production phase of CF, this is in line with the findings
from existing literature (Heller et al., 2013). In addition and as found in similar studies conducted
(Carlsson-Kanyama, 1998, Davis and Sonesson, 2008, González-García et al., 2012, Saarinen et al.,
2012, Sonesson et al., 2005), the transport phase tends to have a minor weight if no product is
transported through air freight (Carlsson-Kanyama and Gonzalez, 2009). The preparation phase may
have a larger weight in recipes that involve a more extensive use of cooking appliances. However in
this case the contribution from transport amounted to only to 30.6 gCO2e (3% of total) per portion.
Figure 6: Contribution of each phase to the Carbon Footprint (CF)
3.2 Comparison between a set of meal recipes
The same analysis was performed for seven additional meals suggested by the School Food Plan
Alliance (http://www.schoolfoodplan.com/). All of them comply with the nutritional requirements of
the British government (Department for Education, 2015). One half of these recipes are vegetarian
(V1 to V4) and the other half contain either meat (M1 to M3) or fish products (F1). The overall
numerical results of CF and WF for all eight recipes are presented in Table 2 and Figures 7 and 8.

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
Table 2: CF and WF of the eight meals analyzed
Meal Name
Code
Carbon Footprint
[gCO2e/portion]
Water Footprint
[liters/portion]
Mumbai meatballs
M1
1865
501
Sticky chicken and vegetable rice
M2
957
432
Macaroni and cheese with pork
M3
764
720
Salmon and broccoli pasta
F1
382
113
Cheese and broccoli quiche
V1
650
194
QuornTM curry
V2
458
159
Pizza with vegetable sauce
V3
464
151
Vegetable curry
V4
569
185
Figure 7: CF of meal recipes analyzed
Figure 8: WF of meal recipes analyzed
This analysis shows clearly how the meat-based recipes (M1, M2 and M3) have a higher carbon
and water footprint than the non-meat ones. This is in line with a large body of existing research
(Audsley et al., 2010, Baroni et al., 2007, Carlsson-Kanyama and Gonzalez, 2009, Davis et al., 2010,
Heller et al., 2013, Saxe et al., 2012). In addition the recipe that performs best in terms of CF and WF
(F1) is fish-based. From a carbon perspective this is due to the low quantity of carbon intensive dairy
products required in the recipe (Pulkkinen et al., 2015). From a water perspective this is due to the

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
fact that the main ingredient, fish, has zero WF, as the freshwater inputs to marine aquaculture and
marine capture are considered to be negligible (Hoekstra, 2003, Verdegem et al., 2006).
4. Discussion
4.1. Why is EATS limited to two categories of CF and WF?
The EATS tool considers only two impact categories, CF and WF, and this is due to a number of
reasons.
Firstly, the aim of the tool was to create results that are easy for non-LCA experts to interpret. This
includes catering staff operators, school staff in charge of choosing the menus and non-scientific
audiences. As such EATS allows the concept of carbon and water footprint to be easily explained to
students, and provides results that can be used not only to influence menu choices but also with an
educational purpose (similar to work done by Saarinen et al. (2012)).
Secondly, as the tool includes a database (of secondary data) collected from literature, the choice
of impact categories had to take into account the issue of data availability. Most studies of LCA of
food products include amongst their results the impact category GWP (Teixeira, 2015), considered to
be most appealing because of its simplicity, which makes it easy to communicate (Weidema et al.,
2008). As for WF, an extensive collection of values of water footprint of most food items was
published by the leading organization in this field, the Water Footprint Network (Mekonnen and
Hoekstra, 2010a, b). This was used as the main source for the water footprint values included in the
database.
4.2. How accurate are the values of CF calculated within the EATS database?
There is a great variability in the values of CF of food products, depending on many aspects,
including the production method and the production country (Head et al., 2014, Elin Röös et al., 2014,
E. Röös and Nylinder, 2013, Scholz et al., 2015). One example is the case of vegetables grown in
open fields versus heated greenhouses. As shown in a study by González et al. (2011), the latter group
has significantly higher carbon emissions, with the value of CF varying according to the type of fuel
used to heat the greenhouse. In the above-mentioned work, the following values of CF (in gCO2e/kg
product) are reported for cucumbers: 80 for open field, 750 for electrically heated greenhouse and
2600 for fuel heated greenhouse. These variations have to be kept in mind in the interpretation of the
results. To record this level of variability in the database, and how this affects the results of the tool, a
sensitivity analysis was conducted. To this end, for each food item, the average, minimum and
maximum values of CF are recorded in the database.
Figure 9 shows this range for the ingredients in meal F1. The figure shows the high variability in
CF related to Salmon. Figure 10 shows the range for each recipe considered within this paper, from
which it can be seen that there is high variability (hence uncertainty) for M1 and vice versa for V4.
The high value of M1 is in line with the findings of Teixeira (2015), who conducted a statistical
analysis of an agri-food database, in which the meals that experienced the largest variations had beef
as the main ingredient.

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
Figure 9: Carbon footprint of the ingredients of meal F1 with min, average and max values.
Figure 10: Carbon footprint of the eight meals calculated with average, minimum and
maximum value for each meal.
4.3 What is the potential for future impact from the EATS tool?
Thanks to the ease with which users can engage with EATS and be provided with a visualization
of the results, there is the potential for significant impact. Firstly in the way school menus are selected
and secondly in the way students are introduced to and taught about sustainable food choices. Thirdly
as a tool that enables easy identification of hotspots, in other words ingredients that are carbon / water
intensive. This would allow those responsible for school menus to create alternative recipes, replacing
these ingredients with similar ones that perform better from an environmental perspective.
Notwithstanding this potential, one should keep in mind that the fundamental importance of school
meals is to provide healthy and nourishing food to students. Therefore, EATS could either be used to

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
compare existing recipes deemed to be equal in terms of nutritional value, or to suggest alternative
recipes after testing their nutritional quality. This may be a valuable future addition to the tool.
5. Conclusions
This study presents EATS, a tool derived for schools and catering providers in order to self-assess
the environmental performance of the menus being served. EATS enables its users to carry out a
cradle to plate assessment of the carbon footprint and water footprint of a recipe with the purpose of
identifying hotspots and suggesting better performing menus. The paper demonstrated the application
of the tool to eight meals and compared them in terms of their carbon footprint and water footprint,
showing substantial variations amongst them and a general trend of lower impact in the case of meat-
free meals. These results prove that an accurate choice of the type of meals served by a caterer can
have a significant impact on the overall environmental performance of the service provided.
EATS is a tool that can potentially be used by any school and catering provider in the UK to assess
the performance of its menus and identify hotspots amongst its recipes. It does not require any prior
knowledge of the LCA methodology and only basic informatics skills to be used. In order to meet
these conditions, a number of simplifications had to be made, for instance the reduction of the impact
categories to only carbon and water footprint and the use of secondary data as a starting point for the
assessment. Hence, it is important to emphasize that it does not represent an alternative to a complete
LCA study.
Thanks to a simple user interface EATS can be used to engage non-scientific audiences (including
students) on the topic of sustainable food choices, and therefore has great potential both as a tool for
decision making (i.e. menu improvement and creation) and education.
Acknowledgements
The authors wish to thank the Engineering and Physical Sciences Research Council for their support
under the Liveable Cities (EP/J017698) Programme Grant.
6. References
Audsley, E., Angus, A., Chatterton, J., et al. (2010) "Food, land and greenhouse gases. The effect of
changes in UK food consumption on land requirements and greenhouse gas emissions. The
Committee on Climate Change.".
Baroni, L., Cenci, L., Tettamanti, M., et al. (2007) Evaluating the environmental impact of various
dietary patterns combined with different food production systems. Eur J Clin Nutr, 61: (2):
279-286.
Brunel University (2008) "Greenhouse Gas Impacts of Food Retailing. Report F0405 for Defra".
London.
Carlsson-Kanyama, A. (1998) Climate change and dietary choices - How can emissions of
greenhouse gases from food consumption be reduced? Food Policy, 23: (3-4): 277−293.
Carlsson-Kanyama, A. and Faist, M. (2001) "Energy Use in the Food Sector: A Data Survey. FMS
Report.".
Carlsson-Kanyama, A. and Gonzalez, A.D. (2009) Potential contributions of food consumption
patterns to climate change. Am J Clin Nutr, 89: (5): 1704S-1709S.
Davis, J. and Sonesson, U. (2008) Life cycle assessment of integrated food chains—a Swedish
case study of two chicken meals. The International Journal of Life Cycle Assessment, 13: (7):
574-584.

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
Davis, J., Sonesson, U., Baumgartner, D.U., et al. (2010) Environmental impact of four meals with
different protein sources: Case studies in Spain and Sweden. Food Research International, 43:
(7): 1874-1884.
DEFRA (2015) Greenhouse Gas Conversion Factor Repository [online].
http://www.ukconversionfactorscarbonsmart.co.uk/ [Accessed 07/04/2016]
Department for Education (2015) School food in England. Departmental advice for
governing bodies [online]. https://www.gov.uk/government/publications/standards-for-
school-food-in-england [Accessed 05/04/2016
Garnett, T. (2008) "Cooking up a storm. Food, greenhouse gas emissions and our changing
climate". Guildford, UK, Food Climate Research Network. Centre for Environmental Strategy,
University of Surrey.
González-García, S., Castanheira, É.G., Dias, A.C., et al. (2012) Environmental life cycle
assessment of a dairy product: the yoghurt. The International Journal of Life Cycle
Assessment, 18: (4): 796-811.
González, A.D., Frostell, B. and 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: (5): 562-570.
Haroun, D., Harper, C., Pearce, J., et al. (2009) "Primary School Food Survey 2009". School Food
Trust.
Head, M., Sevenster, M., Odegard, I., et al. (2014) Life cycle impacts of protein-rich foods:
creating robust yet extensive life cycle models for use in a consumer app. Journal of Cleaner
Production, 73: 165-174.
Heller, M.C., Keoleian, G.A. and Willett, W.C. (2013) Toward a life cycle-based, diet-level
framework for food environmental impact and nutritional quality assessment: a critical review.
Environ Sci Technol, 47: (22): 12632-12647.
Hoekstra, A.Y. (2003) "Virtual water: An introduction". Delft, IHE-Delft.
Hoekstra, A.Y., Chapagain, A.K., Aldaya, M.M., et al. (2009) "Water footprint manual: state of the
art 2009". Enschede, The Netherlands, Water Footprint Network.
ISO (2006a) "ISO 14040 International Standard". Environmental Management - Life Cycle
Assessment - Principles and Framework. Geneva, Swizerland, International Organization for
Standardisation.
ISO (2006b) "ISO 14044 International Standard". Environmental Management - Life Cycle
Assessment - Requirements and Guidelines. Geneva, Swizerland., International Organization
of Standardization.
ISO (2014) "ISO 14046 International Standard". Environmental Management – Water
Footprint – Principles, Requirements and Guidelines. Geneva, Switzerland, International
Organization for Standardization.
Jones, M., Dailami, N., Weitkamp, E., et al. (2012) Food sustainability education as a route to
healthier eating: evaluation of a multi-component school programme in English primary
schools. Health Educ Res, 27: (3): 448-458.

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
Mekonnen, M.M. and Hoekstra, A.Y. (2010a) "The green, blue and grey water footprint of crops
and derived crop products.".
Mekonnen, M.M. and Hoekstra, A.Y. (2010b) The green, blue and grey water footprint of farm
animals and animal products.
Morgan, K. and Sonnino, R. (2007) Empowering consumers: the creative procurement of school
meals in Italy and the UK. International Journal of Consumer Studies, 31: 19-25.
Nijdam, D., Rood, T. and 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: (6): 760-770.
Pulkkinen, H., Roininen, T., Katajajuuri, J.-M., et al. (2015) Development of a Climate Choice meal
concept for restaurants based on carbon footprinting. The International Journal of Life Cycle
Assessment.
Quested, T., Ingle, R. and Parry, A. (2012) "Household Food and Drink Waste in the United
Kingdom 2012". London, WRAP.
Röös, E., Ekelund, L. and Tjärnemo, H. (2014) Communicating the environmental impact of meat
production: challenges in the development of a Swedish meat guide. Journal of Cleaner
Production, 73: 154-164.
Röös, E. and Nylinder, J. (2013) "Uncertainties and Variations in the Carbon Footprint of
Livestock Products". Uppsala, Sweden.
Saarinen, M., Kurppa, S., Virtanen, Y., et al. (2012) Life cycle assessment approach to the impact
of home-made, ready-to-eat and school lunches on climate and eutrophication. Journal of
Cleaner Production, 28: 177-186.
Saxe, H., Larsen, T.M. and Mogensen, L. (2012) The global warming potential of two healthy
Nordic diets compared with the average Danish diet. Climatic Change, 116: (2): 249-262.
Scholz, K., Eriksson, M. and Strid, I. (2015) Carbon footprint of supermarket food waste.
Resources, Conservation and Recycling, 94: 56-65.
Sonesson, U., Mattsson, B., Nybrant, T., et al. (2005) Industrial processing versus home cooking:
An environmental comparison between three ways to prepare a meal. Ambio, 34: (4): 414-421.
Strasburg, V.J. and Jahno, V.D. (2015) Sustentabilidade de cardápio: avaliação da pegada hídrica
nas refeições de um restaurante universitário. Ambiente e Agua - An Interdisciplinary
Journal of Applied Science.
Teixeira, R.F.M. (2015) Critical Appraisal of Life Cycle Impact Assessment Databases for Agri-
food Materials. Journal of Industrial Ecology, 19: (1): 38-50.
Verdegem, M.C.J., Bosma, R.H. and Verreth, J.A.J. (2006) Reducing Water Use for Animal
Production through Aquaculture. International Journal of Water Resources Development,
22: (1): 101-113.
Weidema, B.P., Thrane, M., Christensen, P., et al. (2008) Carbon Footprint. Journal of Industrial
Ecology, 12: (1): 3-6.

De Laurentiis V., Hunt D.V.L., Rogers C.D.F., 2016. Environmental assessment of the impact of school meals in the United Kingdom. In:
Proc. of 10th International Conference on Life Cycle Assessment of Food 2016, Dublin. UCD, 939-951.
Weitkamp, E., Jones, M., Salmon, D., et al. (2013) Creating a Learning Environment to Promote
Food Sustainability Issues in Primary Schools? Staff Perceptions of Implementing the Food for
Life Partnership Programme. Sustainability, 5: (3): 1128-1140.