Supermarket food waste
Prevention and management with the focus on reduced
waste for reduced carbon footprint
Faculty of Natural Resources and Agricultural Sciences
Department of Energy and Technology
Swedish University of Agricultural Sciences
Acta Universitatis agriculturae Sueciae
ISBN (print version) 978-91-576-8436-3
ISBN (electronic version) 978-91-576-8437-0
© 2015 Mattias Eriksson, Uppsala
Print: SLU Service/Repro, Uppsala 2015
Cover: Romanesco in a degraded state
(photo: Klaus Pichler)
Supermarket food waste - Prevention and management with the
focus on reduced waste for reduced carbon footprint
Food waste occurs along the entire food supply chain and gives rise to great financial
losses and waste of natural resources. The retail stage of the supply chain contributes
significant masses of waste. Causes of this waste need to be identified before potential
waste reduction measures can be designed, tested and evaluated. Therefore this thesis
quantified retail food waste and evaluated selected prevention and valorisation
measures, in order to determine how the carbon footprint of food can be reduced by
decreasing food waste in supermarkets.
Food waste was quantified in six supermarkets in the Uppsala-Stockholm region of
Sweden. Data were recorded over five years between 2010 and 2014 by the retail
company in a daily waste recording procedure. In addition, suppliers contributed data
on deliveries and rejections. The main suppliers contributed data on wholesale pack
size and shelf-life, which allowed the relationship between these and their effect on
waste to be analysed. Life cycle assessment was used to investigate the carbon footprint
associated with production and distribution of food and managing the waste.
The wasted mass was dominated by fresh fruit and vegetables and rejection on
delivery was the main reason for this food being wasted. Expressed in terms of carbon
footprint rather than mass, the relative importance of meat waste increased and that of
fruit and vegetables decreased.
A reduction in storage temperature to prolong shelf-life proved to have the potential
to reduce waste in all supermarket departments studied. However, when the
temperature reduction was achieved by extended use of the current electricity mix, a net
lowering of carbon footprint was only found for the meat department. For food
products with a high carbon footprint, e.g. beef, there was much greater potential to
lower the carbon footprint by preventing waste through source reduction than by
upgrading the waste management option. If food waste cannot be prevented, donation
to charity and anaerobic digestion of the waste were found to have the greatest potential
to reduce the carbon footprint, depending on the substituted bread value and biogas
potential, respectively. This follows the EU waste hierarchy, although there are
variations from the trend of more favourable options at higher levels of the hierarchy.
Keywords: Food waste, Supermarket, Prevention, Valorisation, Life cycle assessment
Author’s address: Mattias Eriksson, SLU, Department of Energy and Technology,
P.O. Box 7032, 750 07 Uppsala, Sweden
To all the food waste geeks out there
We cannot solve our problems with the same
thinking we used when we created them.
List of Publications 7
1 Introduction 10
1.1 The food waste problem 10
1.2 The role of supermarkets in the food supply chain 11
2 Objectives and structure of the thesis 13
2.1 Objectives 13
2.2 Structure of the thesis 13
2.3 Other publications by the author relating to the thesis 14
3 Background 16
3.1 Definitions of food waste in the literature 16
3.2 Waste and losses in the food supply chain 18
3.3 Carbon footprint of food production and waste handling 20
3.4 The waste hierarchy 21
3.5 Structuring waste reduction efforts 23
3.5.1 Quantities 23
3.5.2 Causes and risk factors 24
3.5.3 Measures 27
4 Material and Methods 30
4.1 Classification and definition of food waste 31
4.2 Collection and analysis of store data 33
4.2.1 Data collection for recorded waste and rejections 33
4.2.2 Data collection for unrecorded waste 34
4.2.3 Data collection for delivered and sold mass 35
4.2.4 Analysis of waste data 36
4.2.5 Identification of systematic causes and risk factors of waste 36
4.3 Carbon footprint of processes related to food waste 38
4.3.1 Carbon footprint associated with cradle to retail emissions 38
4.3.1 Carbon footprint associated with waste management options 39
4.4 Waste prevention and valorisation framework 40
5 Results 42
5.1 Quantities 42
5.1.1 Quantities of wasted perishable food 42
5.1.2 Mass balance of fresh fruit and vegetables 47
5.2 Risk factors for food waste and causes of discarding food 48
5.3 Measures 51
5.3.1 Prevention measures 51
5.3.2 Valorisation measures 54
5.3.3 Comparison of valorisation and prevention measures 55
6 Discussion 57
6.1 Quantities of food waste 57
6.1.1 Use of different units for quantification 57
6.1.2 Data quality and selection of study objects 58
6.1.1 Uncertainties in carbon footprint of food 59
6.1.2 Issues regarding data quality for fruit and vegetables 61
6.1.3 Comparison of indicator values of waste generation 63
6.2 Waste reduction measures 65
6.2.1 Perspectives on waste prevention and valorisation 65
6.2.2 Factors influencing the evaluation of waste reduction measures 67
6.3 Potential to increase sustainability by reducing food waste 68
7 Conclusions 71
8 Future research 73
Appendix I. Store department level results. 84
Appendix II. Food category level results. 85
Appendix III. Food product level results 88
Appendix IV. Article level results 93
List of Publications
This thesis is based on the work contained in the following papers, referred to
by Roman numerals in the text:
I Eriksson, M., Strid, I. & Hansson, P-A. (2012). Food losses in six Swedish
retail stores - wastage of fruit and vegetables in relation to quantities
delivered. Resources, Conservation and Recycling 68, 14-20.
II Eriksson, M., Strid, I. & Hansson, P.-A. (2014). Wastage of organic and
conventional meat and dairy products - a case study from Swedish retail.
Resources, Conservation and Recycling 83, 44-52.
III Scholz, K., Eriksson, M. & Strid, I. (2015). Carbon footprint of supermarket
food waste. Resources, Conservation and Recycling 94, 56-65.
IV Eriksson, M., Strid, I. & Hansson, P.-A. (2015). Food waste reduction in
supermarkets – net costs and benefits of reduced storage temperature.
V Eriksson, M., Strid, I. & Hansson, P.-A. (2015). Carbon footprint of food
waste management options in the waste hierarchy - a Swedish case study.
Journal of Cleaner Production 93, 115-125.
Papers I-III and V are reproduced with the permission of the publishers.
The contribution of Mattias Eriksson to Papers I-V was as follows:
I Planned the paper in cooperation with the co-authors. Performed data
collection, observations in stores, physical measurements and analysis of
data. Interpreted the data and wrote the manuscript together with the co-
II Planned the paper in cooperation with the co-authors. Performed data
collection, calculations and analysis of data. Interpreted the data and
wrote the manuscript with input from the co-authors.
III Planned the paper together with the co-authors. Supervised the data
collection, calculations and analysis of data. Provided input to the writing
of the manuscript and was corresponding author.
IV Planned the study. Performed data collection, calculations and analysis of
data. Interpreted the data and wrote the manuscript with input from the
V Planned the study with input from the co-authors. Performed data
collection, calculations and analysis of data. Interpreted the data and
wrote the manuscript with input from the co-authors.
Carbon dioxide equivalents
European Article Number
Food and Agricultural Organisation of the United Nations
Fresh fruit and vegetables
Global Warming Potential
Life Cycle Assessment
Material/mass flow analysis
Multiple linear regression
Minimum order size
Waste Framework Directive
Providing enough food for the world’s growing population is easy, but doing
this at an acceptable cost to the planet is more challenging (Nature, 2010). This
challenge requires changes in the way food is produced, stored, processed,
distributed and consumed. Godfrey et al. (2010) suggest five major strategies
to meet these challenges: Closing the yield gap; increasing production limits by
genetic modification; expanding aquaculture; dietary changes; and reducing
waste. These all involve utilising the full potential of the production system so
that more food can be consumed without increased resource demand at the
same rate. Reducing waste is unique in this context, since it focuses on food
that is already produced, but not consumed for various reasons. Since reduced
waste of edible food is also one of the least controversial ways to make the
food supply chain more productive, it has the potential to be used immediately
to decrease the competition for natural resources that could be saved for future
production to avoid a future food crisis (Nellemann et al., 2009).
1.1 The food waste problem
Waste, loss or spoilage of food is an efficiency issue that has attracted
increasing attention from the media, researchers, politicians, companies and the
general public in recent years. Although food waste seems like a simple
problem, the solution “to just stop throwing it away” is much more complex
than would appear at first glance. This is because food waste is not just a
problem, but also a solution to other problems, such as public health or
economic profit, which are often a higher priority. Food is also wasted for a
large number of reasons, which makes it difficult to find a ‘quick fix’ to reduce
food waste once and for all. In many countries the food waste in itself creates a
problem if it is dumped in landfill and generates methane. In other countries,
Sweden included, landfilling of organic waste is prohibited and surplus food is
considered a resource that can be used for biogas production or for feeding
people in need. It is therefore not the wasted food that should be the main
concern, but the wasteful behaviour that results in unnecessary food
The complexity of the food waste issue also links it to the three parts of
sustainable development: economics, social issues and environmental impact.
This does not mean that reduced food waste automatically results in sustainable
development, but reducing unnecessary food waste has the potential to make
an important contribution and also has a high symbolic value. Food waste can
be related to waste of money (FAO, 2013) and natural resources (Steinfeldt et
al., 2006; Garnett, 2011), but also has moral implications in relation to food
security (Stuart, 2009; FAO, 2012). The political will to work on food waste
reduction can be seen as rational and positive, since there are few good
arguments for keeping on wasting food. This has resulted in several goals on
waste reduction among companies (Tesco, 2014), states (Rutten, 2013) and
international organisations (EC, 2011). As pointed out by Garnett (2011),
reducing food waste is not the only way to make the food supply chain more
sustainable, but it has the potential to save money too and is less controversial
than e.g. reducing meat consumption.
One of the problems closely associated with food waste is food security and
the moral implications of throwing away food while people in parts of the word
are starving (Stuart, 2009). However, just finishing off the food on one’s plate
will not make a starving person any happier, since the problem of starvation is
also connected to the global economy and how resources are distributed around
the world. Therefore a reduction in food waste in a supermarket in Sweden will
not necessarily lead to less starvation in the world, but may have an indirect
influence due to reduced demand for the finite resources needed for food
1.2 The role of supermarkets in the food supply chain
The loss of food is a problem along the whole food supply chain but since
more value, in terms of both money and resources, is added for every step in
the food supply chain, waste represents more loss of value at the end of the
chain when more subprocesses have been in vain (Eriksson & Strid, 2013;
Strid et al., 2014). This means that the potential economic benefits of reducing
waste per unit mass are higher in later stages of the value chain (SEPA, 2012).
However for some products, especially those of animal origin, much of the life
cycle emissions are generated already at farm level (Röös, 2013) and food
waste reduction will therefore have the same high reducing effect along the
whole supply chain after farm level.
Supermarkets are located close to the end of the supply chain and also
collect large quantities of food in a limited number of physical locations.
Therefore these are potentially good targets for waste reduction measures, even
though supermarkets contribute a relatively small share of waste in comparison
with other stages in the food supply chain (Jensen et al., 2011a; FAO, 2011;
Göbel et al., 2012). Recent studies of food waste in supermarkets mostly focus
on describing the quantity of waste, problems causing it and how it could be
given to charity in order to avoid waste (Alexander & Smaje, 2008; Buzby et
al., 2009; 2011; Lee & Willis, 2010; Gustavsson & Stage, 2011; Stenmarck et
al., 2011; Lebersorger & Schneider, 2014). There is therefore a need to take
this problem one step further and investigate waste prevention and waste
valorisation measures, and the potential to reduce the environmental, social and
economic impacts related to food waste.
This thesis focuses on waste quantification in order to move further towards
finding potential ways of preventing food waste in supermarkets or, when
prevention is not possible, reducing the negative outcome regarding the carbon
footprint of handling food waste. Such knowledge could be used to reduce the
negative impact of the food supply chain and thereby contribute to sustainable
development for future generations.
2 Objectives and structure of the thesis
The overall aim of this thesis was to provide new information on how to reduce
food waste and the carbon footprint associated with wasted food. Specific
objectives were to describe the quantity of wasted food in supermarkets in
terms of mass and carbon footprint, analyse some risk factors that can increase
waste and perform a theoretical evaluation of various waste valorisation and
2.2 Structure of the thesis
In order to fulfil these objectives, the thesis was structured according to the
four steps of waste reduction shown in Figure 1. The first step is to quantify the
extent of the problem and potential hotspots. The quantities defined can then be
analysed to find causes and risk factors influencing waste generation. With this
information, efficient measures can be designed to reduce the risk factors.
When effective measures have been introduced, they can be evaluated in terms
of how much they save by reducing waste and how much they cost.
Papers I and II focus on the wasted mass in supermarkets, concentrating on
fruit and vegetables and organic meat, deli, cheese and dairy products. The
carbon footprint associated with production and distribution of the wasted food
is the main focus in Paper III.
Paper II also examines causes relating to turnover, shelf-life and minimum
order size. This relationship is further developed in Paper IV, where it is used
to design and theoretically evaluate a waste prevention measure of increasing
the shelf-life by reducing the storage temperature.
Several waste valorisation options are evaluated in Paper V, together with
theoretic measures regarding donation of surplus food and its use in animal
2.3 Other publications by the author relating to the thesis
During the work of this thesis, a number of ideas or problems in need of further
investigation were identified. It was not possible to explore all of these ideas in
Papers I-V and therefore a number of other papers have been written based on
the material and experience collected. These related publications are included
together with Papers I-V in Figure 1 and are listed with a short description in
Table 1. Only publications where the author of this thesis was co-author and
where the investigation centred on waste in the food supply chain are shown.
Figure 1. Schematic diagram of Papers I-V in this thesis and related publications. The vertical
levels illustrate different steps in the waste reduction process and the horizontal segments
illustrate different stages in the food supply chain.
Table 1. Brief summary of other publications related to the work in this thesis
Eriksson & Strid (2011)
Pre-study of Paper I quantifying in-store
waste of fruit and vegetables, cheese, dairy,
deli and meat during 2010.
Marklinder et al. (2012)
The 2011 mass experiment of the Swedish
version of researchers’ night, where school
children were engaged to measure the
temperature in several places in domestic
Marklinder & Eriksson (2012)
Marklinder & Eriksson (2015)
Summary of the findings of Papers I and II.
Strid & Eriksson (2013)
Evaluation of a pilot test where
supermarkets froze down meat cuts and
sold them to a restaurant.
Eriksson & Strid (2013)
Describing and calculating the potential
savings and cost of six food waste
reduction measures in supermarkets.
Strid et al. (2014)
Investigating losses in Swedish production
and distribution of iceberg lettuce.
Strid & Eriksson (2014)
Food is wasted in all stages of the food supply chain, but since the food
distribution system is large and complex, there are significant variations in
quantities over time, between products and between different types of
businesses. Due to the complexity of the food supply chain there is a need for
many large studies to fully cover the quantities of waste generated and the
underlying causes, and ultimately what could be done to reduce the negative
consequences of food waste. This chapter presents some existing knowledge
about food waste in general, but with the emphasis on food waste in
3.1 Definitions of food waste in the literature
In order to quantify food waste, there is first a need to define what the
quantification should include. Since food consists of a large and diverse group
of products, it is complicated to find an easy definition that fits all purposes.
Moreover, waste and the process that turns food into waste include many
situations and perspectives. Therefore the literature is full of expressions such
as “food loss” (e.g. FAO, 2011; Strid & Eriksson, 2014), “food waste” (e.g.
DEFRA, 2010), “post-harvest loss” (e.g. Hodges et al., 2011), “food and drink
waste” (e.g. Griffin et al., 2009; Lee & Willis, 2010) and “spoilage” (e.g.
Lundquist et al., 2008). According to Östergren et al. (2014), the list may even
be much longer. Some of these expressions are overlapping and some are used
to define different type of waste.
One problem with developing the definition of food waste, as explained by
Schneider (2013b), is the commonly used EU definition of food (EC, 2002).
This legal definition
excludes plants prior to harvesting. Therefore plants
which are not harvested due e.g. to low market price are not counted as food
waste (Schneider, 2013). This creates a problem, since the food waste issue
does not necessarily start at harvest. Therefore Östergren et al. (2014) propose
a definition that includes products prior to harvest, which is a clear distinction
from many other studies. Their definition of food waste
uses a definition of
the food supply chain
, which includes products ready for harvest or slaughter,
not just products defined as food by EC (2002). Since the definition by
Östergren et al. (2014) also includes inedible parts of food products, it covers
as subcategories other commonly used categorisations such as “avoidable”,
“possibly avoidable” and “unavoidable” food waste (EC, 2010; WRAP, 2011).
The definition used is of course a matter of opinion and as long as it is
clearly stated in publications, it does not create problems. Problems appear,
however, when quantities of food waste based on different definitions are
merged together and used as if defined similarly. An example of this is the
Institution of Mechanical Engineers (2013) statement that 30-50% (or 1.2-2
billion metric tonnes (tons)) of all food produced never reaches a human
stomach, based on FAO (2011) and Lundquist et al. (2008). The problem with
this is that Lundquist et al. (2008) compare the basic production with what is
REGULATION (EC) No 178/2002, Article 2, Definition of ‘food’:
For the purposes of this Regulation, ‘food’ (or ‘foodstuff’) means any substance or product,
whether processed, partially processed or unprocessed, intended to be, or reasonably expected to
be, ingested by humans.
‘Food’ includes drink, chewing gum and any substance, including water, intentionally
incorporated into the food during its manufacture, preparation or treatment. It includes water after
the point of compliance as defined in Article 6 of Directive 98/83/EC and without prejudice to the
requirements of Directives 80/778/EEC and 98/83/EC.
‘Food’ shall not include: (a) feed; (b) live animals unless they are prepared for placing on the
market for human consumption; (c) plants prior to harvesting; (d) medicinal products within the
meaning of Council Directives 65/65/EEC (1) and 92/73/EEC (2); (e) cosmetics within the
meaning of Council Directive 76/768/EEC (3); (f) tobacco and tobacco products within the
meaning of Council Directive 89/622/EEC (4); (g) narcotic or psychotropic substances within the
meaning of the United Nations Single Convention on Narcotic Drugs, 1961, and the United
Nations Convention on Psychotropic Substances, 1971; (h) residues and contaminants.
Food waste is any food, and inedible parts of food, removed from the food supply chain to be
recovered or disposed of (including composted, crops ploughed in/not harvested, anaerobic
digestion, bio-energy production, co-generation, incineration, disposal to sewer, landfill or
discarded to sea).
The food supply chain is the connected series of activities used to produce, process, distribute
and consume food. The food supply chain starts when the raw materials for food are ready to
enter the economic and technical system for food production or home-grown consumption. This is
a key distinction, in that any products ready for harvest or slaughter being removed are within
scope, not just those harvested and subsequently not used. It ends when the food is consumed or
‘removed’ from the food supply chain.
eaten to estimate the waste, which means that animal feed is included in waste.
FAO (2011), on the other hand, defines food waste and losses as food that was
originally meant for human consumption but which unfortunately leaves the
human food chain (even if directed to a non-food use). Inclusion of animal feed
as a food waste or not has a large impact and could explain the difference
between 30% and 50% waste. Stating these values as a range clearly gives the
reader a false impression of the size of the waste problem, since the waste can
actually be both 30% and 50% at the same time.
3.2 Waste and losses in the food supply chain
Several studies in recent years have attempted to estimate parts of the global
food waste and its consequences. According to FAO (2011), approximately
one-third of the food produced in the world is wasted, corresponding to 1.3
billion tons of food waste every year. To put this figure into context, FAO
(2013) also estimates that this food waste gives rise to greenhouse gases
corresponding to 3.3 billion tons of carbon dioxide
year, costs around $750 billion annually and guzzles a volume of water
equivalent to the annual flow of Russia's Volga River. These figures are of
course rough estimates associated with both large variations and insecure data,
but clearly much of the food produced in the world is not consumed as
There seems to be a trend in the waste pattern of the whole food supply
chain for much of the waste to occur during primary production and in the
consumer stage (FAO, 2011; Jensen et al., 2011a; Göbel et al., 2012). The
stages in between, including processing, wholesale and retail, contribute
smaller amounts in this perspective, which could be the reason why consumers
are often the target of waste reduction campaigns and other efforts to reduce
food waste (NFA, 2015; WRAP, 2015). However, even if the waste occurring
in the retail stage of the supply chain is less than in some other stages, the
amounts involved are still enormous, e.g. approximately 70 000 tons per year
in Sweden (SEPA, 2013) and 4.4 million tons per year in the EU-27 (EC,
The contribution of the retail sector to waste in the Swedish food supply
chain (excluding agriculture) is estimated to be 39 000 tons per year,
corresponding to 3.8% (Jensen et al., 2011a). However, that estimate is based
only on the organic waste fraction and therefore Stare et al. (2013) investigated
the mixed waste fraction and upgraded the amount to 67 000 tons per year,
corresponding to 6.1% of the whole food supply chain (excluding agriculture).
The values presented in Figure 2 are based on data from Jensen et al. (2011a)
and Stare et al. (2013), updated by SEPA (2013) to represent the year 2012.
These figures, which can be considered the official Swedish food waste
statistics, show that 70 000 tons of food per year are wasted in Swedish
supermarkets. Göbel et al. (2012) estimated that the retail stage of the German
food supply chain contributes 3% of its food waste. This seems low in
comparison with the Swedish estimate of 6.1% (Stare et al., 2013), but Göbel
et al. (2012) include agriculture and if food waste from Swedish primary
production were to be included, it is likely that the Swedish value would be at a
The retail sector of the food supply chain is not the largest contributor of
food waste, but the amounts are still high and the share of unnecessary waste is
also high (Figure 2), which makes it an important issue. Other aspects are that
food waste becomes concentrated in a limited number of physical locations,
making food rescue measures feasible. Supermarkets also represent an
important link between producers and consumers, with potential influence over
large parts of the food supply chain. This makes it possible for retailers to
communicate with consumers in order to increase their environmental
awareness and also to choose suppliers and producers that fulfil their corporate
responsibility. Retailers are particularly important for the Swedish food supply
chain, since the market is extremely concentrated and is completely dominated
by just a few large companies (Eriksson, 2012). For example, the market share
Figure 2. Estimated volumes of food waste generated in Sweden in 2012 (SEPA, 2013).
of the five largest food retailing companies in Sweden amounted to 94.7% in
2002, which was the highest in Europe, where the average level was 69.2%
(Vander Stichele et al., 2006). These five companies also own or control large
parts of the distribution chain and, via private brands, some of the production.
3.3 Carbon footprint of food production and waste handling
Life cycle assessment (LCA) is a method for analysing the environmental
impact of a product or service by analysing different aspects such as land use,
water use, eutrophication, climate impact and acidification. Since many
different aspects are included, a substantial review of environmental impact
can be assessed. The problem is of course that it requires large reasearch
resources to make a full LCA with many impact categories for a variety of
products or services, with many geographical regions and production systems
that need to be considered. Carbon footprint (CF) assessment provides a
limited perspective, since only the global warming potential (GWP) is
included. However, a less extensive assessment can instead allow analysis of a
larger number of scenarios or a more extensive product range, using the same
A large number of studies on the GWP or CF of food products have been
performed (Roy et al., 2009; Röös, 2012). As pointed out by Röös (2013), the
results vary widely between different food products, but also for a particular
food product depending on factors such as production system and
methodological choices in the assessment. However, one pattern which has
emerged is that products of animal origin generally have a considerably larger
CF than products of vegetable origin (EC, 2006), and that this footprint are
generated already at farm level. Meat, particularly lamb and beef, has an
exceptionally high CF, followed by cheese, due to the contribution of methane
) from enteric fermentation in ruminants. Meat from monogastric animals,
such as pigs and poultry, has lower CF values than products from ruminants,
but still higher than most foods of plant origin, due to the large amount of feed
needed in livestock production and emissions from manure handling. Some
fruit and vegetables can have a considerably high CF if produced in heated
greenhouses, transported by air or produced in low-yielding systems (Stoessel
et al., 2012). For many food products, nitrous oxide (N
O) emissions from soil
also contribute significantly to the CF.
Losses in the food supply chain are seldom included in the CF of food
products, possibly due to lack of data. If the wasted part were to be included,
the CF of some food products could increase significantly, since surplus
production is needed to cover both the fraction consumed and the fraction
wasted. If food waste is managed properly, it could be used as a byproduct that
can replace other virgin materials and thereby, to some extent, reduce the CF.
However, according to Hanssen (2010), producing biogas from food waste
only saves approximately 10% of the emissions generated during the
production of surplus food, so the recovery of food waste can be considered a
small part of the life cycle of food.
Even though waste management only can recover a small fraction of the
resources invested in food production, it is still important to consider waste
management due to the large quantity of waste generated. According to many
review studies (e.g. Bernstad & la Cour Jansen, 2012; Laurent et al., 2013a;
2013b), the CF of food waste could be reduced by shifting from less favoured
options in the EU waste hierarchy (EC, 2008) to higher priority options.
According to Laurent et al. (2013a), the most common order in the waste
hierarchy is landfilling as least favourable, followed by composting, thermal
treatment and anaerobic digestion as the most favourable. However, there is
great variation due to differences in local contexts, but also the use of different
methodology to assess the different waste management systems (Bernstad & la
Cour Jansen, 2012; Laurent et al., 2013a; 2013b).
3.4 The waste hierarchy
The EU waste hierarchy is set in the European Waste Framework Directive
(WFD), which ranks waste prevention and management options in order of
priority (EC, 2008). The WFD also obliges member states to encourage options
that deliver the best overall environmental outcome from a life cycle
perspective, even when this differs from the waste hierarchy. However, since
the environmental outcome is not defined in the WFD, this goal can be
achieved in many ways. Addressing GWP is one way to do so, but GWP alone
offers only a limited perspective on the overall environmental outcome,
although to some extent it can act as an indicator of other environmental
impact categories (Röös et al., 2013).
Early versions of the waste hierarchy have been part of European policy
since the 1970s (EC, 1975). While it has been developed and amended (EC,
2008), it still provides only very general guidelines for all waste, including the
priority order from prevention, re-use and preparation for re-use, recycling,
recovery and, last and least favourable, dumping in landfill. Guidelines relating
specifically to food waste have therefore been devised. Examples of such
systems are the Moerman ladder in the Netherlands (Dutch Ministry of
Economic Affairs, Agriculture and Innovation, 2014), the Food Recovery
Hierarchy in the United States (USEPA, 2015) and the Food Waste Pyramid in
the United Kingdom (Feeding the 5000, 2014). All these systems prioritise
prevention, since all other waste management options include downcycling and
loss of the intended product. Despite the order of priority in the waste
hierarchy, only a few studies measure waste prevention in the context of waste
management (Laurent et al., 2013a). This omission may be due to the
methodical difficulties in measuring something that is not there (Zorpas &
Lasaridi, 2013) or, as discussed by van Ewijk & Stegemann (2015), to
prevention being fundamentally different from waste management.
The US Food Recovery Hierarchy, which is shown in Figure 3 (USEPA,
2015), agrees with the general principles of the EU waste hierarchy (EC,
2008), but has one important difference in that it separates the prevention stage
into what can be seen as two sublevels. The more preferred sublevel is source
reduction and the less preferred sublevel is feeding hungry people. This is
important, since it implies that even though the food is eaten in the latter
option, which corresponds to its intentional use, it is better to be proactive and
reduce food production.
Figure 3. The Food Recovery Hierarchy developed by the USEPA (2015).
Feeding hungry people is also limited by the fact that food waste can only
be donated to charity if it is surplus food still fit for human consumption
(Papargyropoulou et al., 2014). Since the food hygiene or biosecurity
requirements increase at higher levels in the waste hierarchy, there is a
decreasing likelihood that the whole waste flow will be suitable for the same
type of waste management if using a more preferred method. This creates a
need for more complex systems where part of a food waste flow is developed
and used for higher priority waste treatments, while the rest is treated with a
lower priority, more general method (Vandermeersch et al., 2014).
3.5 Structuring waste reduction efforts
In organisations and companies, waste reduction is often sought by copying the
best practice within the organisation or by taking inspiration from other
successful examples of waste reduction measures (EC, 2010; Lagerberg
Fogelberg et al., 2011). Whether the suggested measures actually reduce the
waste and by how much are seldom reported, and thus it is difficult to compare
different measures and decide on the most efficient methods to reduce waste.
Therefore, in this thesis a more analytical approach was adopted, based on the
Deming cycle (also known as the plan-do-check-act methodology) used for
environmental management systems in order to reduce waste (ISO, 2010). This
strategy was suggested by Eriksson (2012) and involves:
1. Quantification of waste.
2. Analysis of causes.
3. Introduction of measures.
4. Evaluation of measures.
The steps to reducing waste involve describing the problem and the
underlying reasons for risky behaviour, testing solutions and then evaluating
how well the solutions actually reduce the problem and how much they cost.
Retail food waste has been quantified in a few previous studies (Table 2). In all
these studies, different system boundaries, methods and units have been used.
In addition, different products have been studied, making comparisons
difficult, although the results from the studies do not vary widely. The results
indicate that retail food waste for different product groups is often in the range
0-10%. Many previous studies have focused on fresh fruit and vegetables
(FFV), which often give high percentage waste, e.g. 10% for the European
retail distribution sector according to FAO (2011).
No previous publication states the percentage of waste originating from the
retail sector in Sweden. However, if the wasted 70 000 tons per year reported
by SEPA (2013) are divided by the 3.5 million tons per year delivered to
Swedish supermarkets, approximated from Jensen et al. (2011b), these
supermarkets waste approximately 2% of the mass delivered. This is well in
line with the 1-2% waste reported for Finnish supermarkets (Katajajuuri et al.,
Table 2. Brief review of studies in the literature quantifying food waste in supermarkets
Katajajuuri et al.
Göbel et al.
Buzby et al.
8.4 - 10.7
8.4 - 10.3
Buzby & Hyman
Beretta et al.
8 – 9
Fehr et al. (2002)
Sales in cost
FFV (only in-
Buzby & Hyman
Sales in cost
3.5.2 Causes and risk factors
Food can be wasted for a large variety of reasons, which makes the food waste
issue difficult to solve with one single solution. Common reasons for food
being discarded in supermarkets are expired shelf-life or visual defects that
make food unsellable (at least at full price). However, as pointed out by
Lindbom et al. (2014), it is important to identify not just the reason for food
being discarded but also the underlying root cause of the problem. However,
such identification is problematic, since there are so many potential root causes
of e.g. expired shelf-life, such as too short shelf-life, too large inflow of
products, unexpected lack of demand, or a combination of all of these. Since it
is very difficult to identify a single root cause, risk factors are used here since
they better capture the multiplying effect when several risk factors are present
and include factors not necessarily leading to food waste, but just increasing
the risk of waste. Possible risk factors can be low demand, short shelf-life,
unsuitable packaging or storage conditions and inappropriate handling by staff
In an extreme perspective, an inflow of food that is unbalanced with regard
to the outflow required can even be assumed to be the only root cause of food
waste. If so, all problems that prevent a supermarket from selling the food are
risk factors. These risk factors can also have an effect on the inflow, since the
supermarket will try to order just the right amount of all products, but anything
that creates variation will make this forecast more difficult. Thus to summarise,
if the forecast is just right there will be no waste and no empty shelves, but
everything that introduces variation will make forecasting more difficult and
increase the risk of food waste (or empty shelves).
There are several activities and problems introducing variation. One is
increased product variety (Lindbom et al., 2014), since having more different
types of products decreases turnover for each and makes forecasting more
difficult. On the other hand, providing a large variety of products also means
freedom for customers, which supermarkets might use as a competitive
advantage to differentiate them from their competitors. Since larger variety
might thus be expected to increase profits, it might be something that the
retailers are unwilling to alter, and waste is simply a part of the price they have
to pay for the larger range of products sold.
Promotions have a similar effect on food waste since they temporarily shift
the turnover of products and make forecasting more difficult. According to
Hernant (2012), some promotions prompt the customer to buy the promoted
product, but to reject other similar products as a consequence. Since
forecasting of sales is more difficult when there are many aspects to consider,
temporary shifts in sales can be difficult for retailers to predict accurately. This
leads to a larger than necessary stock of not promoted products and, since the
store must not run out of the promoted product, also a surplus of the promoted
product. The result of the campaign is increased waste of the promoted product
and also increased waste of other similar products. Added to the cost of the
waste is the lack of profit that arises when the store sells products at a lower
margin than usual. Thus promotions can really seem a waste of effort (Hernant,
2012), but they are unlikely to disappear since they are there to attract
customers and thereby increase overall profits. Promotions can therefore be
viewed as a marketing cost and waste as simply part of that cost.
In many cases the food waste does not appear in the same organisation that
caused it. If customers decide to stop buying a certain product, this product is
likely to end up as food waste if the supplier cannot stop its production fast
enough or find an alternative market. If this change in purchasing behaviour is
made by a single customer it might not affect the food logistics system at all,
but when many customers unexpectedly change their behaviour the food
supply chain simply cannot react fast enough to prevent overproduction and
eventually food waste. A fast reaction from a customer group might also cause
a chain reaction along the value chain that increases the effect and, in the end,
creates large amounts of food waste in primary production. According to
Taylor (2006), there are a number of actions in the supermarket that can lead to
a “bullwhip effect”, where the amplitude of the customer reaction increases
from retail to wholesale, from wholesale to industry and from industry to
primary production and everyone along the chain increases/decreases
production and increases/decreases stock in order to compensate for the
customer reaction. Increased communication along the logistics chain so that
primary producers get their signals directly from the end customers could be
one way to deal with this problem. Another way to decrease the risk of a
bullwhip effect could be by reducing the activities that increase variation.
According to Taylor (2006), these activities include promotions, large numbers
of products and/or actors in the logistics chain, and ordering and production in
large batches with large stocks. Therefore the same risk factors for food waste
can be problematic both within supermarkets and in other parts of the food
Most types of waste and losses are unintentional, but since several risk
factors are accepted as a normal part of any activity, waste must also be
accepted as something natural. A common reason for accepting the presence of
risk factors is that they are too expensive or too difficult to prevent. There can
also be a conflict of interest between waste reduction and increased profit or
public health, with waste reduction being likely to be a lower priority. To put
this simply, there are a large number of problems causing food waste that are
not interesting to solve because the potential benefits are believed to be less
than the cost of change. On the other hand, there are also many problems that
could easily be economically justified and therefore should be dealt with in
order to reduce food waste (Eriksson & Strid, 2013). The problem is knowing
which problems have low required management intensity (Garrone et al.,
2014), meaning that they are cheap and/or easy to solve. With this knowledge,
a countermeasure to reduce risk factors can be designed so the potential
savings can be compared with the expected cost of the intervention.
In order to reduce food waste in supermarkets, there is a need for measures that
solve the basic problems which cause waste. Waste quantification and cause
identification are often performed in order to design measures. These can be
seen as necessary pre-studies in order to identify where to target a measure, but
also to select the measures with the largest potential for reduction and/or the
Food waste reduction measures can be categorised in several different
ways, but the main distinction is between prevention and valorisation
measures. Prevention measures aim to reduce the production of food, while
valorisation measures aim to create value from the waste occurring and thereby
reduce the negative effect of the waste. Donation to charity can be considered a
prevention measure, since the food is eaten by humans, but also a valorisation
measure, since it handles the surplus food rather than reducing the production
of food. Valorisation in this case can be considered in strictly monetary terms,
as done by Eriksson & Strid (2013), who only considered measures that use the
food for human consumption. Value in this case can have a wider meaning, i.e.
including any byproduct that reduces the negative effects of the waste
(Vandermeersch et al., 2014), but it can also just apply to food (and uneatable
parts of food) sent to animal feed, bio-material processing or other industrial
uses (Östergren et al., 2014). In their wider meaning, valorisation measures can
include any waste management option that recovers nutrients, energy or
byproducts from the food waste. It can also include waste management options
that give rise to less emissions or less general problems then the worst option,
e.g. landfill or even illegal dumping.
Most previous studies on waste management methods for food waste, or
organic waste including food waste, describe and sometimes compare landfill,
incineration, composting and anaerobic digestion (Bernstad & la Cour Jansen,
2012; Laurent et al., 2013a; 2013b). However, all these options occur within
the less prioritised part of the waste hierarchy defined by the European Waste
Framework Directive (EC, 2008). Some studies also include animal feed in the
comparison (e.g. Lee et al., 2007; Menikpura et al., 2013; Vandermeersch et
al., 2014), but none includes comparisons with the highest levels in the waste
hierarchy, such as donation and prevention. However, some studies describe
the environmental benefits of preventing food waste. For example, Gentil et al.
(2011) concluded that there are significant benefits of reducing food waste,
especially wasted meat, by 20% in a food waste stream. However, those
authors do not specify how this reduction should be achieved, or the cost of
doing so. Williams & Wikström (2011) & Williams et al. (2008) investigated
whether waste reduction can justify the increased use of packaging material
and found that it could do so for resource-consuming products such as cheese
and beef. However, those studies did not specify how large the potential
reduction could be if the packaging was redesigned. Another prevention study,
by Salhofer et al. (2008), regarded prevention as being equal to donation, but
did not quantify the actual potential in this measure. Moreover, Schneider
(2013a) valued donated food by its emissions during production, instead of the
produce that could be replaced. The lack of studies quantifying higher levels of
the waste hierarchy with a method comparable to the lower levels makes it
difficult to evaluate the actual environmental benefits of donation and
prevention in relation to other waste management options. Without such an
extended analysis, the life cycle perspective described in the WFD will not
actually be considered when selecting waste management options.
Among the large number of publications reviewed by Laurent et al. (2013a;
2013b), a pattern emerged in studies comparing different waste management
alternatives. The least favourable option was landfill, followed by composting
and thermal treatment, and the most favourable was anaerobic digestion.
However, not all studies fitted this pattern. Therefore Laurent et al. (2013a)
concluded that local infrastructure is essential for the outcome, making it more
difficult to generalise results.
Despite the order of priority in the waste hierarchy, only a few studies have
measured waste prevention in the context of waste management (Laurent et al.,
2013a). This omission may be due to the methodical difficulties of measuring
something that is not there (Zorpas & Lasaridi, 2013) or, as discussed by van
Ewijk & Stegemann (2015), to prevention being fundamentally different from
waste management. One of the differences that make it fundamentally different
is that waste management options are carried out by professions handling waste
management facilities, such as a municipal department, but prevention
measures can only be handled by staff in the supermarket or by logistic
departments in retail and wholesale companies. This means that supermarket
staff have little influence over what happens with the food waste after it leaves
the supermarket and that waste management professionals have little influence
over what happens with the food before it becomes waste.
Prevention of food waste relates more to resource management than to
waste management and therefore it is important to achieve source reduction,
i.e. reduced production, and not just prevent the food entering the supermarket.
However, there is no guarantee that the waste will not just move to an earlier
stage in the food supply chain and sub-optimisations like this reduce the effect
of the prevention measure. From an environmental perspective, it is not a
solution to move the waste as a way to prevent it occurring, even though when
waste occurs earlier in the food supply chain some sub-processes such as
transportation, storage and packaging might still be avoided (Strid & Eriksson,
2014; Strid et al., 2014). From an economic perspective, it might be enough to
reduce the inflow of food into the supermarket, although the food will then be
wasted at the supplier or producer, as long as the supermarket does not have to
pay. Moreover, the producer may increase the price of the food supplied in
order to cover the waste cost and if so, the supermarket will have to pay for the
Swedish supermarkets are likely to use the local infrastructure available for
waste management, which means that if they do not prevent food waste or
donate it to charity, they send it to incineration, composting or anaerobic
digestion. Since it has been illegal to dump organic matter in landfill in
Sweden since 2005 (Ministry of the Environment and Energy, 2001), it is very
unlikely that any of the Swedish supermarket food waste is disposed of in this
way. According to Jensen (2011a), 22% of the food wasted in Swedish
supermarkets is managed with biological treatment, while the rest can be
assumed to be incinerated for production of district heating.
4 Material and Methods
The work presented in this thesis is based on case studies performed in the
context of six supermarkets located in Stockholm and Uppsala in Sweden.
Paper I used the data to quantify wasted fruit and vegetables and Paper II
quantified waste of organic food from the cheese, dairy, deli and meat
departments and analysed causes of this waste. Through an extended literature
review, Paper III added the perspective of CF associated with the wasted
quantities. Paper IV combined the causes analysis in Paper II and the CF
analysis of wasted food from Paper III with a literature review to examine
shelf-life extension potential and energy consumption at reduced storage
temperature. To extend this perspective, Paper V investigated different waste
management options that could be used for the fractions of the food waste that
cannot be prevented.
The six supermarkets investigated are owned, and were selected for the
study, by the head office of Willy:s, which is a major actor on the Swedish low
price retail market. The stores were selected within a specified region close to
the university performing the research and to provide a representative view of
the whole retail chain with regard to factors such as turnover, percentage waste
and profit. Within these supermarkets, the fresh fruit and vegetables, dairy,
cheese, meat and deli departments were selected for in-depth study, in
consultation with the retail company, due to their large contribution to food
waste and the expected high environmental impact of this waste. The bread
department also makes a large waste contribution, but this is managed
separately by the suppliers and was therefore not included in the quantification
studies. Wasted bread is considered in Paper V, but using only assumptions
regarding the wasted mass.
The material and methods used for data collection are described in detail in
Åhnberg & Strid (2010), Eriksson & Strid (2011; 2013) and Eriksson (2012).
In the study by Eriksson (2012), material flow analysis (MFA) was used as a
method to investigate the incoming and outgoing flows of food within a group
of supermarkets (Brunner & Rechberger, 2005). Variations on the MFA
approach (including life cycle inventories) were used in Papers I-V in order to
establish the mass of each type of food leaving the supermarkets either as any
type of waste or as sold food. In Paper I the use of MFA was most extensive,
since a full mass balance was performed for the waste in the FFV department.
More extensive LCA was performed in Paper III regarding the CF from cradle
to retail, in Paper IV regarding the cost and benefits of reducing waste through
reduced storage temperature and in Paper V where different waste management
options for the food waste were assessed (Figure 4).
4.1 Classification and definition of food waste
The definition of food waste used in this thesis is that proposed by Östergren et
al. (2014): “Food waste is any food, and inedible parts of food, removed from
the food supply chain to be recovered or disposed of (including composted,
crops ploughed in/not harvested, anaerobic digestion, bio-energy production,
co-generation, incineration, disposal to sewer, landfill or discarded to sea)”.
Since supermarkets sell food products that have not yet been separated into
their edible and inedible parts, the waste consists of a mix of avoidable,
possibly avoidable and unavoidable food waste (EC, 2010; WRAP, 2011).
Since e.g. a banana is sold in the supermarket with the peel on, it is also wasted
with peel and a categorisation like that suggested by EC (2010) and WRAP
(2011) is only applicable at a stage in the FSC where the banana is consumed.
Food waste from supermarkets can be divided into several categories
depending on system boundaries (Östergren et al., 2014) but, as described in
Figure 4. The food supply chain with the system perspective from each of the papers (III-V)
using LCA as a method. Paper IV also relies heavily on results from Paper III that are not
included in the diagram.
Paper I, food waste (or retail food waste) was defined in this thesis as products
discarded in the supermarkets studied, irrespective of whether they belonged to
the supplier or the supermarket. This meant that losses of mass due to theft or
evaporation were not considered food waste and are therefore included in a
separate category (missing quantities) in Figure 5.
Pre-store waste consisted of items rejected by the supermarket at delivery
due to non-compliance with quality requirements. This waste belongs to the
supplier in accounting terms, since it is rejected by the supermarket, but is
usually discarded at the supermarket. Pre-store waste is defined through
documented complaints to suppliers, which according to the rules must be done
within 24 hours of delivery. This waste is on rare occasions sent back to the
supplier for control, but is still wasted.
Recorded in-store waste was defined as food waste occurring after purchase
from the supplier. This waste is sorted out and discarded by supermarkets when
there is little or no possibility of selling the products. This could be due to
exceeded best-before date or product deterioration for unpackaged fresh fruit
Unrecorded in-store waste consisted of food waste that was discarded but
not recorded. This means that it had the potential to be either pre-store waste or
recorded in-store waste if recorded in any of these categories. Unrecorded in-
store waste originated from two sources: underestimated mass when recording
unpackaged waste; and unrecorded of wasted items. The latter can occur in
Figure 5. Flow chart with an overview of the waste categorisation used and the physical flow of
food marked with arrows.
error or as a deliberate act, e.g. it is not cost-effective to record small amounts
The three food waste categories all contributed to fill up the waste
containers of the supermarkets studied, but there was also a category of
missing quantities. This was due to loss of mass between outgoing and ingoing
flows, the two main reasons for which are believed to be theft and mass loss
due to evaporation. Stolen food is considered not to be an environmental
problem, since it is believed to be eaten. Evaporation losses are also not
primarily food waste, since the food items are left, but with a higher dry matter
content and smaller mass. However, when visible, this might act as a secondary
effect, leading to losses of food in one of the waste categories.
4.2 Collection and analysis of store data
4.2.1 Data collection for recorded waste and rejections
Food that was sorted out and discarded was recorded as part of a daily routine
normally performed by the stores and established years before this
investigation (Åhnberg & Strid, 2010). This routine was not introduced by the
author, only used in order to collect data. The routine starts with an inventory
in the morning where products considered unsellable are sorted out. Products
are considered unsellable if they have passed their best-before or use-by date.
Since some FFV are sold without a date label, the sorting of these products is
based on visual appearance and the unsellable limit is defined by each staff
member based on whether they would buy the product themselves (Willy:s,
Products from the deli, meat, dairy and cheese departments are recorded
directly with a mobile scanner connected to the company database and then
discarded. Waste due to poor quality at delivery is economically reimbursed by
the supplier if the member of staff presses a one-digit code on the mobile
scanner to indicate whether the waste is charged to the supermarket, the main
supplier (DAGAB) or other suppliers.
Discarded fruit and vegetables are placed in the storage room until the end
of the shift, when the staff record the waste. Recording is often done by the
team leader or other experienced member of staff using the mobile scanner for
waste at the supermarket’s expense. Waste due to rejections is registered first
on paper and then transferred to the website of the logistics company (SABA)
delivering all fruit and vegetables to the supermarkets. Since all products are
owned by Axfood when handled by SABA, the data on rejections are then
transferred to a database within Axfood (Figure 6).
The records on wasted products are stored in the retail company database.
Data on rejections are stored by DAGAB and Axfood and were provided in the
form of weekly reports to the author.
4.2.2 Data collection for unrecorded waste
From observations and interviews with the staff, it became clear that the
recording of wasted fruit and vegetables is not completely accurate. To
quantify the missing part of the waste, a control measurement of the waste was
performed. This method was closely related to the data collection methods
used for household waste surveillance (Ventour, 2008; Andersson, 2012), with
the distinction that the waste was not allowed to enter the waste container
before recording. This manual recording of otherwise unrecorded waste was
the only data collection process that could not harvest data from an existing
system within the supermarkets.
The data collection was performed after the staff had recorded the waste,
when instead of dumping the waste they left it together with printouts of the
record. All fruit and vegetables in the pile were then measured on a set of
scales to check the masses, which were compared with the masses recorded
During the first measurement of unrecorded waste, which lasted for two
weeks, only differences between recorded and measured mass were quantified.
It then became clear that some items were discarded without being recorded at
all, and that some items were recorded without being found in the pile of
waste, possibly discarded directly by mistake. Therefore a second
Figure 6. Flow chart with an overview of the companies involved in supplying food to the
supermarkets investigated here.
quantification was performed during three days taking into account items
discarded but not recorded, and vice versa. The absence of some items from the
waste pile was tracked by asking the staff about every missing item to
determine whether the item was expected to be in another location than the
waste pile at that time, e.g. if some items were supposed to be discarded later
or had already been discarded. All items that the staff did not expect to be in
the pile were excluded from the study.
4.2.3 Data collection for delivered and sold mass
Sold products from all five departments investigated are recorded by the
cashier at the pay point in the supermarket, or at a self-scanning pay point.
These data are then stored in the financial records that the company is obliged
to keep. Most products are recorded with the European Article Number (EAN)
code on the packages, but some products, mostly fruit and vegetables sold
unpackaged, are weighed at the pay point and identified by a four-digit price
look-up (PLU) code typed in by the cashier. Mistakes in self-scanning or with
the PLU codes are likely to create uncertainty in the data. The extent of this
problem is unknown, but can be assumed to have no significant effect on the
results presented in this thesis.
Delivered fruit and vegetables are recorded by the supplier as part of the
financial records. These data were used in Paper I in order to calculate the
The supermarket departments studied are defined by the retail chain. The
meat department sells fresh meat from terrestrial animals, mainly beef, pork
and chicken, but also lamb and game meat. It also sells grilled chicken, raw
sausages and some frozen meat. In the deli department, processed meat
products such as sausages, meatballs and cold cuts, as well as black pudding
and pâté, are sold. Besides dairy products such as milk, cream, butter and
yoghurt, the dairy department also carries eggs and beverages based on fruit,
vegetables or grain. The cheese department sells various cheeses, mainly hard
or semi-hard cheese, soft cheese and cream cheese, but also tofu. The fruit and
vegetable department sells a wide range of domestic and imported fresh
All food products sold in the departments investigated can be aggregated at
several levels. The lowest level of aggregation is the article level, where each
article is defined by individual article number (EAN code). Some of these
articles may have the same name, but different brands or package sizes. If the
article code was changed over time without any change to the article, it was
still considered as two separate articles in this thesis. The articles sold in the
stores are grouped into categories defined by the supermarkets. These
categories are grouped into departments, which in this thesis included the five
departments cheese, dairy, deli, meat and fresh fruit and vegetables, all
belonging to the division of perishable food. Since the store has no level for
apples or oranges, an aggregation level between article and category, called
product level, was created. The definition of products was not as robust as the
other aggregation levels set by the supermarket, since there are several possible
sublevels where the product level can be set and this level differs between
different products. This can be exemplified by granny smith apples, which
have more than one article number. In this thesis the product level was set to
apple, but not to granny smith apple, which could also have been a possibility.
4.2.4 Analysis of waste data
Articles sold piecemeal were allocated a mass based on the mass stated on the
package when this was possible. For articles sold without packaging (only
FFV), the mass was set using the estimates used by the supplier for each
article. (All masses stated as tons in this thesis refers to metric tons.)
Relative waste (RW) was calculated either in relation to the actual mass
delivered (D) (Equation 1) or in relation to estimated mass delivered (Equation
2). The sum of sold products (S), pre-store waste (PW) and in-store waste (IW)
was used as estimated mass delivered. The difference between the equations is
the lack of a ‘missing goods’ term in Equation 2.
Equation 2 was mostly used in this thesis due to the lack of data on actual
delivered mass of cheese, dairy, deli and meat. The exception was in Paper I,
where Equation 1 was used since delivery data were available for the fresh fruit
and vegetables department.
For unrecorded in-store waste, the difference between measured waste and
recorded waste was calculated for each supermarket studied. The percentage
difference was then used to calculate the difference for a whole year for each
store, which gave the mass of unrecorded in-store waste.
4.2.5 Identification of systematic causes and risk factors of waste
The causes of food waste can be divided into systematic causes, which are
often small but happen over a long time or on many occasions, and occasional
causes, which are often the outcome of mistakes or rarely occurring events.
Three systematic causes or risk factors, short shelf-life, low turnover and
large minimum order size, were analysed in more depth in Paper II. Shelf-life
(SL) was defined as the time between the production (or packing) date and the
best-before date (or use-by date) or, in the case of eggs, from the production
date to the last legal sale date (Persson, 2015). Turnover (T) was defined as the
average number of items sold per week in weeks when the product was sold.
Minimum order size (MOS) was defined as the minimum number of items a
store can order on a single occasion. This was assumed to equal the wholesale
pack size, which is the number of items delivered together in some kind of
The waste risk factors were analysed in Paper II with the focus on organic
products, which are often found to have high waste ratios. To test the
hypothesis that low turnover, in combination with fluctuating demand, leads to
wasted products, waste quantifications were supplemented with data on
minimum order size and shelf-life for those deli products for which DAGAB
had available data. The data on MOS (number of items) and SL (weeks) were
combined with data on weekly turnover T (number of items per week) for each
store to calculate the β-indicator (β), as shown in Equation 3.
The β-indicator was used to explain part of the organic food waste in the
dairy, cheese, deli and meat departments (Paper II), but since the data for both
conventional and organic waste were used, the β-indicator can be applied to
other products, especially those with low turnover. The β-indicator was
developed in Paper II, but multiple linear regression (MLR) was also
performed to confirm this method. The method of using MLR to obtain an
equation describing how waste depends on T, SL and MOS was further
developed in Paper IV, where it was used to simulate the outcome of prolonged
To establish the connection between reduced food waste and extended
shelf-life, the model first presented in Eriksson (2012) and further developed in
Eriksson & Strid (2013), Paper II, Björkman (2015) and Persson (2015) was
used. This model employs multiple linear regression to provide an equation
describing how the relative waste depends on T (sold items per week), SL
(days) and MOS (number of items) from products where data on all parameters
are available. In the MLR, the analysis was limited to only include food items
with a shelf-life shorter than 85 days. The result was based on 984 articles
consisting of 92 cheese articles, 258 dairy articles, 333 deli articles and 311
meat articles and Equation 4 were created from the MLR results, with an
value of 0.666. The reduction in relative waste depending on
increased shelf-life was calculated with Equation 4 and then applied to the
recorded waste of each product in Paper IV.
4.3 Carbon footprint of processes related to food waste
Life cycle assessment (LCA) (ISO, 2006a; 2006b) was used to calculate the
global warming potential (GWP) associated with cradle to retail emissions in
Paper III, emissions related to cold storage in Paper IV and different waste
management options in Paper V. The functional unit used was always 1 kg of
food, but due to the different contexts both production or prevention of 1 kg
food delivered to the supermarket (Papers III and IV) and removal of 1 kg food
(waste) from supermarket (Paper V) were used.
In LCA, emissions relating to waste are normally allocated to the product or
service assessed. Therefore food waste cannot have a carbon footprint (CF) by
itself, but just increases the CF of the consumed product. The food waste CF
used in this thesis should therefore be interpreted as the CF of the food before
it became waste, even though waste was not the intended product. From this, it
follows that if this waste were to be avoided, the life cycle emissions of that
specific product would also be avoided.
4.3.1 Carbon footprint associated with cradle to retail emissions
In all papers, CF was used synonymously with GWP
. The CF was expressed
in terms of carbon dioxide equivalents (CO
e). The CO
O and CH
emissions were included, where the GWP of N
O and CH
relative to CO
according to the IPCC values (Solomon et al., 2007).
In order to analyse the carbon footprint pattern of retail food waste, the CF
of cradle to retail was calculated for different food products. Waste
management of the food waste was not included, due to the low impact
described in Nilsson (2012) and Paper V. The waste carbon footprint was
defined as the specific CF value of a product, comprising emissions associated
with the production and distribution up to delivery to the supermarket,
multiplied by the total mass that was wasted in the stores (including pre-store
waste) of the respective product. The specific CF values were determined
based on existing literature, but the literature values were modified regarding
transportation in order to better fit the distance from the actual country of
origin to the supermarket located in Stockholm, as described in Scholz (2013).
The CF from cradle up to delivery to the retailer of all products was
calculated based on information from the literature. These CF values and the
literature consulted are listed in the appendix to Paper III. When more than one
study on a specific product existed, the study that best represented the product
at the store in terms of country of origin and production method and which
used most current data was selected. Where the scope of the available literature
did not exactly fit the purpose of the present study, assumptions or calculations
were made as described in more detail in Paper III. In general, the most
commonly included emissions associated with primary production, as well as
emissions caused by processing and transportation up to the retailer, were
considered. Potential emissions from land use change were not included.
Emissions associated with store operations and packaging were also not
included, since data availability was not sufficient and their impact was
considered to be relatively low (Cederberg et al., 2009; Stoessel et al., 2012).
4.3.1 Carbon footprint associated with waste management options
In Paper V, five food products with different properties were selected to
represent different waste streams that could be separated in the supermarkets.
For each of the food products, a waste management scenario was applied and
the CF associated with the management and substituted systems were
calculated. The scenarios used were landfill, incineration, composting,
anaerobic digestion, animal feed and donation, since they all represent possible
ways to treat food waste locally with existing infrastructure. The first five
waste management options have been described in several studies (Laurent et
al., 2013a) and the methodology is therefore well used. However, to the best of
my knowledge the same methodology with system expansion has not
previously been applied to food donation, with the exception of Eriksson
In the system expansion, the donated food replaced other food products that
would otherwise have been bought by the charity and consumed by people in
need. There is a wide variety of food items that could be replaced by donated
products, but the same assumption as made by Eriksson & Strid (2013) was
used, i.e. that all donated food replaced bread based on energy content. The
reason why bread was selected as a substituted product is because it is one of
the cheapest types of food that can be bought in Sweden with regard to energy
content, and because it does not require preparation, unlike other cheap and
energy-rich products such as pasta and potatoes.
4.4 Waste prevention and valorisation framework
In this remainder of this thesis, the framework presented in Figure 7 is used to
describe how different waste management and prevention options relate to
food waste and to each other. This framework is inspired by Papargyropoulou
et al. (2014), Garrone et al. (2014), Östergren et al. (2014) and Eriksson &
Strid (2013), but focuses only on the supermarket perspective. Due to
supermarket specialisation, no distinction is made between avoidable and
unavoidable food waste, since these are not separated until the consumer stage.
The concept of waste prevention differs depending on the perspective. From
an environmental perspective, waste is prevented as long the food is never
produced or used for its intended purpose, i.e. eaten by humans. From an
economic perspective, it would be a waste to sell the food at a reduced price,
since that is a loss of money. With this logic, the measure of cutting the price
by 50% on the day before the best-before day may prevent food from being
wasted, but still wastes some of the value of the product. However, since a
price reduction also means that half the value is saved and since this thesis
Figure 7. A waste management framework inspired by Papargyropoulou et al. (2014), Garrone et
al. (2014), Östergren et al. (2014), Eriksson & Strid (2013) and findings within this thesis.
applied an environmental perspective, this type of measure was categorised as
prevention through economic valorisation (Figure 7), since the food is sold
through normal channels with a price reduction in order to save some of the
economic value and possibly the whole environmental value.
In Figure 7 there are a few important trends that follow the order of priority
in the EU waste hierarchy. First, the less prioritised measures are all general
and do not require food waste with high levels of product quality, biosecurity,
separation or storage conditions. Therefore these options are cheap and
general, but have an outcome with much lower economic value than the
original food products. In order to prevent food from being wasted (i.e. using it
for human consumption), there are high hygiene requirements that need to be
met, which makes separation and proper storage important. These options
therefore need more effort from the supermarket, but in return provide a more
valuable outcome. The problem is that the outcome of most waste management
options is profitable for society (SEPA, 2011, 2012), but not necessarily for the
This results chapter is structured into three sections describing quantities, risk
factors and measures. The first section mainly presents results from Papers I-
III, while data for the years not included in these papers are presented in
Appendix I-IV, including department data, category data, product data and
article data. The second section describes a few problems causing food waste
which are mainly covered in Papers II and IV. In the third section, different
measures covered in Papers IV and V that reduce waste or reduce the carbon
footprint of food waste are described.
5.1.1 Quantities of wasted perishable food
During 2010 to 2014, a total of 2.4 kton of food waste was recorded in the five
departments studied in the six selected supermarkets. The majority (84%, 2.0
kton) of the recorded mass was wasted in the fresh fruit and vegetables
department and 77% or 1.6 kton of this was recorded as pre-store waste.
A summary of waste from the different supermarket departments during
three years (2010-2012) is shown in Figure 8. Fruit and vegetables had a
dominant position when the mass of waste was considered, contributed 86% of
the waste, but only 72% of the cost of the waste and 48% of the carbon
footprint produced in vain when wasting the food. The meat department
displayed the opposite pattern to the FFV department, since meat only
contributed 4% of the wasted mass, but 12% of the cost of the waste and 30%
of the wasted CF. The deli and cheese departments followed the same trend as
the meat department, but on a slightly smaller scale.
In order to find hotspots in the waste data, it is not only whole departments
that need to be investigated, but also the actual products within these
departments. Paper I showed that the products making the largest contribution
to FFV in-store waste mass were everyday fruit and vegetables, which are sold
in large quantities, and not exotic fruits, which have higher percentage waste.
For organic deli products, the largest waste contribution also came from
products sold in large quantities, e.g. meatballs and Falun sausage (Paper II).
Since Paper I only shows in-store waste during 2010 in the analysis of wasted
products and Paper II only organic products, Appendices II-IV present data on
the most wasted categories, products and articles.
For each of the five departments, a few articles represented a large share of
the total wasted mass. The most extreme was the dairy department, where five
products contributed almost half (47%) of that department’s waste. In the other
departments, the top five most wasted products contributed between 34% and
41% of the waste within each department. In terms of the carbon footprint, the
concentration of waste from a few products differed and for some departments
was even higher. In the FFV department, tomatoes, bananas and lettuce made a
combined contribution of 36% to the waste carbon footprint. In the meat
Figure 8. Total waste of perishable products from different departments in the six supermarkets
studied during five years, quantified in terms of mass, purchase cost to the supermarket and
carbon footprint (CF) associated with the lifecycle from cradle to retail for the wasted products.
(130 ton CO2e/store/year)
Share of waste from each department (%)
Fruit and vegetables Deli Meat Dairy Cheese
(130 ton CO
department, minced beef contributed 17% of the carbon footprint associated
with that department’s waste (Appendix III).
Since food waste can be quantified in different units, it is important to set
the goals for waste reduction using units that actually measure what is intended
to be achieved. Figure 9 exemplifies this issue when comparing the five
supermarket departments investigated in terms of wasted mass and wasted
carbon footprint. In comparison with 2010, the waste increased by 12% in
2011 in terms of mass, but decreased by 5% in terms of wasted CF. This was
due to increased FFV waste and decreased waste of mainly meat. The trend of
both increasing and decreasing waste continued to 2013, when the waste in the
FFV department also started to decrease. This led to a total decrease in food
waste, both in terms of mass and carbon footprint, from 2010 to 2014 by 21%
and 26% measured in mass and carbon footprint, respectively (Figure 9).
It is not only the use of different units that complicates food waste
quantification. The waste is often set in relation to something else in order to
make the results comparable between e.g. supermarkets of different sizes.
When the waste in the present case was related to estimated delivered mass
(Equation 2), it is clear that the main flow of delivered and sold food was
important. Since the sold mass in the six supermarkets studied decreased by
12% from 2010 to 2014, the relative waste presented in Figure 10 gives a
slightly different result compared with the absolute waste in Figure 9. When
20 10 20 11 20 12 20 13 20 14
Wasted CF (t CO
Wasted mass (t)
Figure 9. Total waste per year from different departments in the six supermarkets studied during
five years, quantified in terms of mass and carbon footprint (CF) associated with the lifecycle
from cradle to retail for the wasted products. The scale is set so the bars for 2010 are equally high
in the diagram.
the waste was related to the sum of sold and wasted mass in all five
departments, the relative wasted mass showed its peak value in 2012, while the
relative wasted CF peaked in 2013. It is also clear that the trend of reduced
wasted CF in 2010-2013 followed the reduced sold CF, and in relative terms
therefore did not decrease (Figure 10).
Apart from variations due to the use of different units and absolute/relative
numbers, there are also natural variations over time. In Figure 11 this is
illustrated by showing the weekly average relative waste for each store during
the whole study period. The highest weekly relative waste rate in a single
supermarket was 7.3% and the lowest 0.5%. Since there are only a few high
waste peaks in Figure 11, a long quantification period can be used to reduce the
influence of these peaks. If waste is quantified during a short period, it might
be heavily affected by an occasional high peak. If the waste is quantified for a
less aggregated level than a whole supermarket, the variation between high and
low values will increase.
20 10 20 11 20 12 20 13 20 14
Relative wasted CF (%)
Relative wasted mass (%)
Figure 10. Total waste related to estimated deliveries per year from the different departments in
the six supermarkets studied during five years, quantified in terms of mass and carbon footprint
(CF) associated with the lifecycle from cradle to retail for the wasted products. The scale is set so
that the bars for 2010 are equally high in the diagram.
Figure 11. Mean, maximum and minimum values of the weekly relative waste in the six supermarkets studied during 2010-2014.
Relative waste (%)
Mean Min Max
5.1.2 Mass balance of fresh fruit and vegetables
In Paper I, a mass flow analysis was performed to create a mass balance of
fruit and vegetables in the six supermarkets, where 94.6% of the delivered
mass was sold and the rest was distributed over the three categories of waste
(4.3%) and missing quantities (1.1%). Missing quantities were calculated
simply to achieve a balance between the inflow and outflow of food.
A similar mass flow analysis was performed with data for the following
years (Table 3) with a maximum of pre-store waste during 2012, the same year
as missing quantities reached the maximum. It is worth noting that the year
with the highest pre-store waste (2012) also had the lowest in-store waste,
while the year with the lowest pre-store waste (2014) had the highest in-store
waste. Since the unsold mass was also lowest during 2014, it appears that the
larger the share of in-store waste, the less total waste there is.
Table 3. Results of mass flow analysis of fruit and vegetables in all six supermarkets studied
during all five years. ‘Unsold mass’ corresponds to delivered mass minus sold mass; ‘Recorded
waste’ corresponds to recorded pre-store and in-store waste
Missing quantities and
The missing quantities can be explained by theft or weight loss due to
evaporation and this problem was in line with the in-store waste (1.3%
compared with 1.1%). However, the small yearly variation seems to be a
coincidence when looking at the same data divided by supermarket (Figure
12). Here the variation was larger and two supermarkets even showed negative
missing quantities, which makes the theft and evaporation explanation more
problematic. Store 3 stands out, with negative missing quantities during three
of the five years, reducing the unsold mass to a lower level than recorded
waste. Store 2 stands out with negative missing quantities that equal the
recorded waste during 2012, meaning that 100% of the delivered mass was
sold, according to the records on delivered and sold products.
The other supermarkets investigated had no negative missing quantities.
Instead, they had large masses in this category, with a maximum in
supermarket 6 during 2011 of 5.7% of delivered mass, which was higher than
the sum of in-store and pre-store waste (5.2%). This high loss of mass also
resulted in the largest difference between delivered and sold products, where
only 89.1% was sold (Figure 12).
5.2 Risk factors for food waste and causes of discarding food
Analysis of causes and risk factors for food waste in supermarkets is important
in order to progress from identifying flows of waste to actually reducing these
by introducing measures. Often these measures solve some kind of problem
that has been causing waste or limit the potential effect of risk factors. Expired
shelf-life is one reason for discarding food and short shelf-life could therefore
be considered a risk factor for food waste. Short shelf-life was analysed in
Paper II to find out if the time span between packing date and best-before date
could explain the greater waste of organic products in comparison with
conventional products. Since shelf-life did not differ between organic and
conventional products, Paper II did not find short shelf-life to be a cause of
food waste. However, a plot of the logarithm of shelf-life against the logarithm
of relative waste (relative to the sum of wasted and sold mass) and absolute
waste revealed a trend for increasing waste as shelf-life decreased (Figure 13).
Nevertheless, the curve fit was far from perfect and therefore other risk factors
must also influence the level of food waste.
Figure 12. Results of mass flow analysis of fruit and vegetables for each of the six supermarkets
studied during each of the five years investigated. The level of net unsold mass corresponds to the
difference between sold and delivered mass.
Store 1 Store 2 Store 3 Store 4 Store 5 Store 6
In-store Pre-store Missing+unrecorded Net unsold food
In Paper II, low turnover was also investigated as a risk factor to explain the
high relative waste of organic products. In Figure 14, the logarithm of turnover
is plotted against the logarithm of relative waste in order to identify its
potential to cause food waste in comparison with the shelf-life factor. The trend
visible in the diagram and the R
values of the linear fit both indicate that low
turnover to a higher extent than short shelf-life caused food waste. However,
the analysis is not complete, since low turnover could also be seen as a risk
factor rather than the only root cause, which means that stocking too many
products will produce waste since they might not all be sold before the end of
the shelf-life, but the effect of overstocking will be even worse if the turnover
is very low. Figure 14 also illustrates that the waste in absolute terms increases
with increased turnover, simply because larger volumes are handled, but at the
same time the relative waste decreases with larger turnover.
Since the minimum order size (MOS) is one parameter influencing the
inflow of products, it was also analysed to see how it corresponded to relative
waste. It was found that MOS was corresponded even less to relative waste
than turnover and shelf-life (Figure 15).
0.5 1 1.5 2 2.5 3
Waste (Log (Waste))
Shelf life (Log (days))
Waste (%) Waste (kg) Linear (Waste (%)) Linear (Waste (kg))
Figure 13. Logarithm of shelf-life is plotted against logarithm of relative waste (red symbols)
and absolute waste (blue symbols), with a linear trend line added to each plot.
-1 -0.5 0 0.5 1 1.5 2 2.5 3 3.5
Waste (Log (Waste))
Turnover (Log (Items/week))
Waste (%) Waste (kg) Linear (Waste (%)) Linear (Waste (kg))
0 0.5 1 1.5 2 2.5
Waste (Log (Waste))
Minimum order size (Log (items))
Waste (%) Waste (kg) Linear (Waste (%)) Linear (Waste (kg))
Figure 14. Logarithm of turnover plotted against logarithm of relative waste (red symbols) and
absolute waste (blue symbols), and a linear trend line added to each plot.
Figure 15. Logarithm of minimum order size plotted against logarithm of relative waste (red
symbols) and absolute waste (blue symbols), with a linear trend line added to each plot.
In Paper II, both large MOS and short SL were found to be risk factors for
food waste, but only turnover was found to differ between organic and
conventional products. Therefore low turnover is a risk factor explaining why
organic food has higher relative waste than conventional products. The fact
that food is organic was not found to be a risk factor, although higher
production costs can have an effect on the sell price and thereby the turnover.
In order to reduce food waste, there is a need for waste reduction measures.
Potential target areas for these measures are the largest problems found in
waste quantification, if these problems are caused by issues that can be dealt
with. The basis used for categorisation of measures was presented in the
introduction section of this thesis. The measures presented in this sub-section
focus on the prevention measures presented in Paper IV and the valorisation
measures presented in Paper V. Following this, these two fundamentally
different ways of dealing with food waste, source reduction and waste
management, are compared.
5.3.1 Prevention measures
The most efficient way of completely preventing food waste from occurring is
of course to stop overproducing food and thereby potentially cause a lack of
supply, but for obvious reasons this is not desirable. Instead, measures must
both reduce waste and not jeopardise food security, which makes achieving
complete prevention of food waste less likely. Therefore it might be more
correct to talk about waste reduction rather than waste prevention, since waste
is unlikely to completely disappear without radical changes in the food system.
Some of the waste at the end of the food supply chain can still be prevented,
however, thereby reducing the need for production. Just reducing the need for
food production does not mean that food production will actually be reduced,
but in all calculations of waste reduction benefits presented below this source
reduction was assumed to take place.
In Paper IV, food waste was reduced by prolonging shelf-life through
reducing the storage temperature for chilled products. Prolongation of shelf-life
has the potential to lead to reduced waste, but also to increased energy use. The
net effect of reducing storage temperature was calculated by deducting the cost
of increased electricity use from the potential savings from reduced food waste.
This gave a value for each supermarket department showing whether a
reduction in temperature was justified from a reduced waste perspective.
If the storage temperature used for cheese, deli and dairy products were to
be decreased from 8°C to 5°C, the waste associated with these products would
potentially decrease by 15%, from 7.8 to 6.7 ton/store/year. The corresponding
reduction for these products if the temperature were to be reduced from 8°C to
4°C and 2°C would be 18% and 25%, respectively. For the supermarket’s meat
department, a reduction in storage temperature from 4°C to 2°C would
potentially lead to a 19% reduction in mass of wasted meat. Taking each
supermarket department separately, the reduction potential would be in the
range 9-30% (Figure 16), with the highest reduction potential at the lowest
storage temperature in each department.
The largest net saving of carbon footprint was found in the meat
department, where the potential savings from waste reduction were larger than
the increased emissions related to reducing the storage temperature. This was
due to the comparatively high level of waste, but also to the high CF per unit
mass, which makes the need for cooling low and the potential waste reduction
high. The dairy department was the opposite to the meat department, with a net
cost of reducing storage temperature. This was due to the already low waste in
the dairy department, but also the large quantities of water in dairy products
that would be need to be chilled to reduce the storage temperature (Figure 17).
The deli and the cheese department can be described as intermediate
between dairy and meat, with a moderate carbon footprint, price per kg,
turnover and level of waste. The cheese department showed a trend for
decreased net savings when the temperature decreased and the shelf-life was
prolonged. In the deli department, the increased energy costs equalled the
reduced emissions associated with food waste, so the measure of reduced
storage temperature gave no net saving, just a shift from food-related emissions
to energy-related emissions.
Figure 17. Net effect of reduced storage temperature in different supermarket departments
considering the benefits, in terms of carbon footprint, of reduced waste and the cost of increased
0 1 2 3 4 5 6 7 8
Net saving (ton CO
cheese dairy deli meat
0 1 2 3 4 5 6 7 8
Wasted mass reduction potential (%)
cheese dairy deli meat
Figure 16. Potential wasted mass reduction (%) for different perishable food departments at
different storage temperatures.
5.3.2 Valorisation measures
When food waste cannot be prevented, there are several different options
available to manage the waste. In Paper V, six scenarios with differing priority
in the waste hierarchy were evaluated. The results showed a trend for
decreasing levels of carbon footprint with higher priority levels in the food
waste hierarchy (Figure 18). For all five food products investigated, landfill
was the option with the highest carbon footprint. At the other end of the scale,
donation and anaerobic digestion were the alternatives with the lowest carbon
footprint from the five food products. Donation was the alternative with the
lowest emissions for grilled chicken and bread (even though incineration
proved the lowest emissions for bread), but for bananas, lettuce and beef
anaerobic digestion generated the lowest emissions.
The other scenarios did not fully agree with the waste hierarchy.
Incineration was a good option for dry food like bread and grilled chicken, but
a poor option for the wetter lettuce and bananas, for which composting
provided a better alternative (Figure 18). Similarly, anaerobic digestion was a
better alternative than animal feed, for some products better than donation.
According to these scenarios the priority order applied to bananas, grilled
chicken, iceberg lettuce, beef and bread should therefore be anaerobic
Banana Chicken Lettuce Beef Bread
CF for WM (kg CO
Waste management scenario and type of food wasted
Landfill Incineration Composting Anaerobic digestion Animal feed Donation
Figure 18. Carbon footprint (CF) of each waste management (WM) scenario and food product
investigated in Paper V.
digestion, donation, animal feed, incineration, composting and, the least
favourable alternative, landfill, when solely considering carbon footprint and
general options. When considering specific options for specific food products,
incineration with energy recovery is a favourable alternative for dry foodstuffs.
Different foodstuffs have different features that make them more or less
suitable for different waste management scenarios. Bananas consist of a fairly
large proportion of peel that was sorted out in the donation scenario, which
meant that a lot of the wasted mass could not be used to replace bread. In the
other scenarios, however, the banana peel was managed the same way as the
rest of the banana and therefore only the donation scenario was affected. Since
the chicken was grilled it was much dryer than beef, which made the energy
content per unit mass higher and the water content lower. Grilled chicken was
therefore much better to incinerate than beef, but for the same reason it gave
rise to more methane in the landfill scenario. Grilled chicken produced less
methane in the anaerobic digestion scenario, because the product included the
whole carcass with bones. Bones were assumed either to be sorted out in the
pre-treatment or simply not to produce any methane due to the short retention
time in the biogas reactor. The bones were also considered not to be eaten in
either the donation or animal feed scenario, which reduced the outcome from
the chicken in these scenarios.
Lettuce has a low energy content and a high water content, which is why
lettuce could be treated in any of the scenarios investigated without large
differences in outcome. Bread was the opposite, with high energy content and
low water content. Because of its energy carrying capacity, bread was useful
for incineration, anaerobic digestion, animal feed and donation. However, its
biogas potential was not as high as for meat products like beef and chicken,
which resulted in less methane production in the landfill scenario and
anaerobic digestion scenario. The energy content per unit dry matter was also
higher in chicken and beef, due to a higher fat content.
5.3.3 Comparison of valorisation and prevention measures
Placing the results from Paper IV into the context of Paper V allowed
comparison of all stages in the waste hierarchy. Figure 19 shows the outcome
using all wasted beef products as an example. The combined waste was 0.95%
in relation to estimated delivered mass. In the waste prevention scenario the
waste was reduced by 20% when the storage temperature was reduced from
4°C to 2°C.
Even when the waste reduction was only 20% of the wasted beef, the
prevention scenario reduced the carbon footprint from the food waste more
than any other waste management scenario (Figure 19). The second best
alternative was anaerobic digestion, which reduced the carbon footprint by 0.7
e/kg food waste. This is much lower than the prevention scenario,
which reduced the carbon footprint by 4.2 kg CO
e/kg food waste. In the
prevention scenario, 80% of the food waste was composted (in line with the
donation scenario in Paper V) but if this waste were instead sent for anaerobic
digestion, the benefit of the prevention measure would increase to a reduction
of 4.8 kg CO
e/kg food waste.
Figure 19. Comparison of different ways to manage all wasted beef in the supermarkets using a
combination of scenarios in Paper IV and Paper V and the effects on carbon footprint (CF). In the
prevention scenarios, 20% of the waste was prevented and 80% was managed by composting or
by anaerobic digestion.
CF for waste management (kg CO
Since only a small part of this thesis focused on causes of food waste, this
discussion chapter focuses on quantities and measures in separate sections,
while causes are included in both these sections.
6.1 Quantities of food waste
From the data presented in this thesis, it is clear that the waste composition is
dominated by fruit and vegetables. This is well in line with other studies (e.g.
Buzby & Hyman, 2012; Beretta et al., 2013; Lebersorger & Schneider, 2014),
although their dominance would probably have been reduced if bread had been
included in the study (Scherhaufer & Schneider, 2011; Lebersorger &
Schneider, 2014; Stensgård & Hanssen, 2014). Other studies do not include the
pre-store waste that dominated the fruit and vegetable waste in the present
case, but since the sum of pre-store and in-store waste from the stores
investigated (4.7%) corresponded almost exactly to the most frequent waste
level in Lebersorger & Schneider (2014), it is likely that the waste was at a
normal level and that recorded cost was just booked differently than in
supermarkets in other studies.
Even if the waste was on a similar level as other studies, there was
considerable variation in the material. First, there was large natural variation
within the stores over time and between articles. Data can also be presented
using different units or relative numbers, which increases the number of
possible perspectives although it does not actually increase variation.
6.1.1 Use of different units for quantification
Choice of analytical method had an effect on the results presented in this
thesis. For example, all results presented in terms of mass resulted in bulky
products with a high water content, e.g. fruit, vegetables and dairy products,
having a large influence on the results. When the results were presented using
the monetary value of the waste, more expensive products, e.g. herbs such as
basil, gained importance at the expense of e.g. potatoes. Use of carbon
footprint shifted the focus relatively more to meat and cheese products rather
than fruit and vegetables and dairy. The weakness of using units of mass in this
kind of study is that the products with a large environmental impact can be
associated with low mass, which can be interpreted as meaning that they are
not important (Strid, 2012). For this reason, the monetary value corresponds
better to environmental impact than units of mass and would therefore work
better as an indicator of environmental hotspots then analysing units of mass.
The strength of using mass values is good transparency, since the unit is well-
defined and does not change along the food supply chain, except during
processing. Both monetary values and values describing the environmental
impact need detailed definitions and have a tendency to differ over time and
along the value chain, even without processes that change the properties of
foodstuffs. For example, the value of products increases not only when they are
processed, but also when they change owners, are transported or are kept in a
Using a unit of mass makes the results comparable with those of other
studies. However, it is not only the units that make comparisons complicated.
Results based on monetary values are often compared with the value of sold
products, since this is the basis of income in a company and the figure against
which all costs must be compared. When percentage waste is as low as it was
in this study, this causes no significant problems, since percentage waste of
1.00% calculated with Equation 1 corresponds to a value of 1.01% if the waste
is compared with the sold value instead. The choice of comparison is more
influential for products with higher values of percentage waste. Some of the
exotic fruits described in Paper I, with waste of above 50%, would have values
of over 100% if the waste were related to sold quantity instead of delivered
6.1.2 Data quality and selection of study objects
The six supermarkets used in this work were selected by the parent company,
which introduces a possible bias, even though the company claimed that they
represented the average. It is unlikely that the company selected stores with
high percentage waste, since high levels of waste tend to be something
shameful and might repel customers if the information became publicly
available. Therefore the supermarkets studied can be expected to represent an
average Willy:s store or have lower percentage waste than the average Willy:s
store. The selected stores were also found to be larger than average in terms of
turnover of fruit and vegetables (Paper I), which further increases the potential
for them to waste less than average (Hanssen & Schakenda, 2011). However,
even if the representativity cannot be proven, all supermarkets within the
company are based on a detailed concept (Willy:s, 2010), making large
variations between individual supermarkets unlikely. The level of waste in the
six supermarkets investigated is therefore unlikely to differ greatly from the
average supermarket within the Willy:s chain.
Material flow analysis performed in Eriksson (2012) showed that the
unrecorded waste category and missing quantities differed in size between
departments. These two categories are a good indicator of the quality of
recorded data. If large quantities are lost without any reasonable explanation, a
likely cause is that the recording of waste does not function well and items are
discarded without recording. From the analysis, it is clear that data based on
EAN code scanning are more accurate than data based on estimated weights.
Therefore the results for cheese, dairy, deli and meat can be considered more
accurate than those for FFV. This is true even though efforts were made to
quantify unrecorded in-store waste of FFV by physical measurements.
6.1.1 Uncertainties in carbon footprint of food
The carbon footprint of the wasted food products in Paper III was mainly
calculated based on the existing literature on LCA studies. Although the LCA
methodology is ISO-standardised, the choice of some aspects, such as the exact
system boundary, functional unit, allocation method or use of emission factors,
is slightly open. Therefore, the results for the same product can vary and in
general the results of different studies are not directly comparable. Moreover,
for agricultural products the chosen production system and the production
country is crucial. In this thes