Download The Climate Change Impact of Retail Waste from Horticultural

The Climate Change Impact of Retail
Waste from Horticultural Products
Jenny Gustavsson
Degree project for Master of Science in
Environmental Science
Department of Plant and Environmental Sciences
University of Gothenburg
February 2010
SUMMARY
Waste of food generates unnecessary greenhouse gas emissions, since wasting, to no use,
increases the amount of food produced. The aim of this thesis was to examine how much
retail waste increases the climate change impact of producing 18 different horticultural
products, namely fruit, berries, vegetables and potted flowers. This study also examined the
waste reducing effect of packaging. The results were included in Life Cycle Assessments
(LCA), carried out at the Swedish Institute for Food and Biotechnology (SIK). The levels of
waste were examined in cooperation with one of the leading Swedish retail companies. Nine
retail stores, of two different sizes, contributed data on the annual waste of each product. The
results concluded that retail waste of horticultural products made up 0.4 to 6% of store
supplies. For the same products, retail waste increased the climate change impact of
production by 0.001 to 0.054 kg CO2-equivalent emissions for each kg or plant produced. The
results did not show that packaging reduce waste of horticultural products. The results did
however indicate that small retail stores, compared to large, produce more waste in relative
terms. Large amounts of horticultural products pass through the Swedish retail sector each
year. The fairly low levels of waste do in the end cause considerable amounts of greenhouse
gas emissions.
SAMMANFATTNING
Livsmedelssvinn genererar onödiga växthusgasutsläpp eftersom svinn, till ingen nytta, ökar
mängden producerad mat. Syftet med detta examensarbete var att undersöka hur mycket
detaljhandelssvinn ökar klimatpåverkan från att producera 18 olika trädgårdsprodukter,
nämligen frukter, bär, grönsaker och krukväxter. Denna studie undersökte också huruvida
paketering minskar svinnet. Resultaten inkluderades i livscykelanalyser (LCA), utförda vid
Institutet för Livsmedel och Bioteknik (SIK). Nivåerna av svinnet undersöktes i samarbete
med ett av Sveriges ledande detaljhandelsföretag. Nio butiker, av två olika storlekar, bidrog
med uppgifter om det årliga svinnet av respektive produkt. Resultaten visade att
detaljhandelssvinnet av trädgårdsprodukter utgjorde 0.4 till 6 % av butikslagren. För samma
produkter ökade detaljhandelssvinnet klimatpåverkan från produktion med 0,001 till 0,054 kg
CO2-ekvivalenter för varje producerat kg eller planta. Resultaten visade inte att paketering
minskar svinnet av trädgårdsprodukter. Resultaten indikerade dock att små butiker, jämfört
med stora, relativt sett producerar mer svinn. Stora mängder trädgårdsprodukter passerar varje
år svensk detaljhandel. De relativt låga nivåerna svinn orsakar till slut stora mängder
växthusgasutsläpp.
1
PREFACE
This thesis was part of a Master of Science degree in Environmental Sciences at the
University of Gothenburg. It was carried out between September 2009 and January 2010 at
the Swedish Institute for Food and Biotechnology (SIK) in Gothenburg, Sweden.
First of all, I would like to thank the staff members, at all participating retail stores, who made
this study possible!
Also, I would like to thank my supervisor, Jesper Stage, at the University of Gothenburg for
clever observations and good knowledge in the academic field.
I would also like to thank my supervisors at SIK, Jennifer Davis and Britta Florén, for
encouraging me throughout the process of conducting this study.
Last, but definitely not least, I would like to thank all staff members at the department of
Sustainable Food Production at SIK, for making me feel truly welcome and for including me
as a member of the group.
Thank you all!
Gothenburg January 18th, 2010
Jenny Gustavsson
Master’s Student in Environmental Sciences at the University of Gothenburg
For questions or comments, please contact:
[email protected]
2
TABLE OF CONTENTS
SUMMARY ............................................................................................................................................................ 1
SAMMANFATTNING........................................................................................................................................... 1
PREFACE ............................................................................................................................................................... 2
TABLE OF CONTENTS........................................................................................................................................ 3
INTRODUCTION .................................................................................................................................................. 4
1.1
1.2
1.3
1.4
1.5
1.6
2
BACKGROUND ...................................................................................................................................... 4
THE CLIMATE CHANGE IMPACT OF HORTICULTURAL PRODUCTS ......................................................... 5
WASTE OF HORTICULTURAL PRODUCTS ............................................................................................... 6
SIGNIFICANCE OF TOPIC ........................................................................................................................ 7
AIM AND RESEARCH QUESTIONS ........................................................................................................... 8
DELIMITATIONS .................................................................................................................................... 8
METHOD ...................................................................................................................................................... 9
2.1
LIFE CYCLE ASSESSMENTS ................................................................................................................... 9
2.2
WASTE SURVEY ...................................................................................................................................11
2.2.1
Collection of data ...........................................................................................................................11
2.2.2
Calculations ...................................................................................................................................13
3
RESULTS.....................................................................................................................................................14
3.1
3.2
3.3
3.4
3.5
RETAIL WASTE OF FRUIT, BERRIES AND VEGETABLES SOLD PIECEMEAL...............................................14
RETAIL WASTE OF POTTED FLOWERS ...................................................................................................16
RETAIL WASTE OF PACKAGED COMPARED TO PIECEMEAL SALES .........................................................17
RETAIL WASTE IN SMALL COMPARED TO LARGE RETAIL STORES..........................................................19
CLIMATE CHANGE IMPACT OF RETAIL WASTE FROM HORTICULTURAL PRODUCTS ................................20
4
DISCUSSION...............................................................................................................................................22
5
CONCLUSIONS ..........................................................................................................................................26
6
RECOMMENDATIONS..............................................................................................................................27
REFERENCES.......................................................................................................................................................28
APPENDIX A: Inventory form
APPENDIX B: Waste data for piecemeal sales, small retail stores
APPENDIX C: Waste data for piecemeal sales, large retail stores
APPENDIX D: Waste data for packaged sales
APPENDIX E: Mean waste and standard deviation
APPENDIX F: Climate change impact
3
INTRODUCTION
Environmental issues, including the question of climate change, have been frequently debated
during recent years. The Intergovernmental Panel on Climate Change (IPCC) published a
report, in 2007, which determined that man-made greenhouse gas emissions most likely
increase temperature on earth. The panel also concluded that this temperature rise may
seriously disturb naturally occurring ecological interactions (Swedish Environmental
Protection Agency 2009a).
The Swedish parliament has decided that the national environmental policy should be carried
out in the light of 16 environmental quality objectives. One of these objectives, reduced
climate change, highlights the issue of greenhouse gas emissions. The goal is to limit
emissions to levels where human activity not harmfully affects the climate system (Swedish
Environmental Protection Agency 2009b). In order to reach this goal it is most important to
identify sources of greenhouse gas emissions, in order to reduce them.
1.1 Background
This master’s thesis was part of an ongoing research project carried out at the Swedish
Institute for Food and Biotechnology (SIK) in Gothenburg, Sweden. The SIK project (Davis
et al. 2010) is financed by The Swedish Farmers´ Foundation for Agricultural Research (SLF)
and will be finished in 2010. The project aims to examine the climate change impact of
producing certain horticultural products sold in Swedish retail stores, namely fruit, berries,
vegetables and potted flowers. By doing Life Cycle Assessments (LCA) the project intends to
quantify the amount of carbon dioxide equivalent (CO2-eq) emissions caused by producing
these food and flower products. The LCAs reach from the initial agricultural cultivation to the
final retail distribution and mainly apply to Swedish production. The results will be published
in a report, along with suggestions on how to reduce the climate change impact of production.
Until the completion of this thesis the LCA results, within the SIK research project, applied to
all included production steps, except for waste at the retail level. Retail waste is not a
production activity per se, but it increases the overall climate change impact of production
since waste results in larger quantities being produced. Prior to this thesis, no extensive waste
survey had been conducted at the Swedish retail level. Hence, in order to complete the LCAs
performed at SIK, the climate change impact of retail waste from horticultural products had to
be examined.
4
1.2 The Climate Change Impact of Horticultural products
Fruit, berries and vegetables
There is no doubt that the production of food affects the environment. The effect is to a great
extent caused by the animal holding and crop growing carried out on farms. Furthermore, the
food is refined, transported, stored, and often cooked before being put on the table, which also
has an effect on the environment (Ahlmén 2002). As a consequence of this, food production
causes approximately 20-25% of the Swedish greenhouse gas emissions (Sonesson 2008),
mainly methane and nitrous oxide (Ahlmén 2002). Leakage from various kinds of
refrigerants, sometimes used during transportation and storage of food, as well as carbon
dioxide emissions from the use of fossil fuel, also contribute (Carlsson-Kanyama 1998).
The early steps of production dominate the overall climate change impact of food with an
animal origin, mainly due to feed provision and manure management connected to animal
holding on farms (Sonesson 2009). The situation is somewhat different for food with a
vegetable origin. For these products, the early steps of production sometimes have less impact
on the overall climate change impact. However, the production and application of nitrogen
fertilisers both cause emissions of nitrous oxide and carbon dioxide. The use of diesel, when
operating agricultural machinery, also generates carbon dioxide emissions (Sonesson et al.
2009). Growing food in heated greenhouses often dominates the climate change impact,
provided that fossil fuels are used for heating (Hospido 2008). All these early steps of
production certainly have an impact. However, for food with a vegetable origin the post
production steps often also have an impact. These apply to for example processing,
transportation, packaging and waste handling. The reason for this is not foremost that the post
production activity generates more greenhouse gas emissions when applied to vegetable
products, compared to animal products. Instead, it depends on the fact that the early steps of
production are so different in magnitude between the two. Hence, the relative contribution of
post production activity, to the overall climate change impact of production, is larger for food
with a vegetable origin compared to food with an animal origin.
The production of food uses a lot of resources and produces significant amounts of
greenhouse gas emissions. The industry as a whole is, as mentioned above, one of the major
contributors to Swedish climate change impact.
Potted flowers
Potted flowers are sold in Swedish retail stores, all seasons of the year. Many are produced in
Sweden, which, due to the cold climate, assumes indoor cultivation in heated greenhouses.
Little research has been made on the climate change impact of producing potted flowers.
However, it is known to be mainly caused by the greenhouse cultivation, especially when
fossil fuels are used for heating. Besides this, post production activity, such as transportation
and packaging, also contributes (Bergstrand 2009).
Many producers in the cultivation business have switched from using fossil fuel to renewable
energy sources, to heat their greenhouses. If this trend continues, the post production steps
could very well rise in relative significance for the overall climate change impact of
producing potted flowers (Bergstrand 2009).
5
1.3 Waste of Horticultural Products
Fruit, berries and vegetables
Waste occurs in all steps of the food production chain. The most obvious reason for this is of
course that fresh food is delicate by nature, and simply does not keep for very long. The lack
of coordination among food producers and distributors, as well as inefficient purchase and
meal planning among consumers, further increases waste of food (Sonesson et al. 2009).
WRAP’s report “The Food We Waste” (Ventour 2008) revealed detailed information on the
quantities of food wasted by UK households. According to the study, UK households threw
away about one third of all purchased food. More importantly, 61% of this waste could have
been avoided, if the food had been better stored or handled. The avoidable food waste alone
causes 18 million tonnes of carbon dioxide emissions each year. The food products mostly
wasted were salads (45%), bakeries (31%), fruit (26%) and vegetable products (19%)
(Ventour 2008).
One major reason for the production of household food waste is passed sell by dates. Lots of
food is, due to these labels, thrown away despite being perfectly edible, since the condition of
food not always is examined before discarded. Lack of household planning is another major
reason. Too much food is purchased, which results in fresh food turning mouldy, smelly or
bad tasting. Also, too much food is prepared for meals which results in plate leftovers
(Ventour 2008).
Efforts have been made during recent years to estimate the food waste produced by UK and
American retail companies. Sainsbury’s established that fruit, vegetables and salads made up
about 26% of food-related waste (Garnett 2006). In general, this proportion is appraised at
26% - 44% of food waste at the retail level (Alexander et al. 2008). After having examined
several published reports, Kantor et al. (1997) came to the conclusion that 2% of fresh fruit
and vegetables are wasted within the American retail sector. These studies were however not
based on actual measurements of waste amounts, but on estimates.
The production of retail food waste happens due to a number of different reasons. Lack of
planning within retail stores may lead to over-ordering, oversupplying and over trimming the
supplies. In addition to this, fruit and vegetables are sometimes treated under poor
environmental conditions, which also increases waste at the retail and consumer level (Nunes
et al. 2008). Seasonality is also an important factor when considering retail food waste since
over ordering in connection to drastic changes in weather, or traditional holidays, can create
additional food waste (Alexander 2008, Kantor 1997).
To summarize, food is wasted throughout the production chain, partly because food is delicate
by nature and therefore easily destroyed. Man-made factors such as lack of coordination and
planning throughout the production and consumption chain do however also contribute.
Potted flowers
To the author’s knowledge, no research has been made on the retail waste of potted flowers.
However, the magnitude of, and causes for, are reasonably similar to those for retail waste of
fruit and vegetables.
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1.4 Significance of topic
WRAP’s report (Ventour 2008) forcefully highlights the issue of avoidable food waste,
produced by consumer households. Due to increasing world population, urbanisation and
standards of living, widespread concerns are held regarding diminishing global food
availability and rising food costs. It is of great importance to enlighten food waste in all steps
of the food production chain (Alexander et al. 2008). The retail sector is one such step, where
mainly fresh food is wasted due to unpredictable demand (Sonesson 2008).
Waste of fruit and vegetables at the retail level has significant environmental impact, since
what is wasted is the final product. In other words, all environmentally burdensome
production steps have already been carried out in order to grow, transport and store the food
(Ahlmén 2002). Although these products are known to be highly wasted, new knowledge is
needed to clarify which types of fruit and vegetables that are being thrown away. As
mentioned above, for food with a vegetable origin the post production activity, including
waste handling, sometimes has notable impact on the overall climate change impact of
production (Sonesson et al. 2009).
The share of greenhouse gas burdensome fruit, berries and vegetables sold in Nordic
countries, like Sweden, seems to have increased with time. When walking through a local
retail store today it seems obvious that retailers aim to provide consumers with all kinds of
food, during all seasons of the year. The issue of seasonality seems to have lost its
importance. In fact, research suggests that urban consumers expect to be able to buy fresh
fruit and vegetables all year long (Hospido et al. 2009). In northern parts of Europe this
assumes growing food in heated greenhouses, alternatively importing from countries farther
south. Hence, these demands further increase the climate change impact of production
(Hospido et al. 2009).
In the same fashion, potted flowers are cultivated and sold in Sweden during all seasons of the
year, which also assumes indoor cultivation in heated greenhouses. Two of the top three most
sold potted flowers in Sweden during 2005 were Poinsettia and Kalanchoë. Poinsettia is in
Sweden strongly associated with Christmas time and is therefore mainly cultivated during the
cold winter month of December (Bergstrand 2009). This further exemplifies how stepping
aside from seasonality puts extra strain on the energy use associated with producing
horticultural products.
Furthermore, the waste of fruit, berries and vegetables at the retail level is most likely
dependent on packaging, which sometimes is considered environmentally burdensome due to
increased amounts of material waste (Monkhouse et al. 2004). Packaging can however also be
considered waste reducing, since it protects fragile fruit and vegetables (Sonesson et al. 2009).
The production of food has, as mentioned above, significant climate change impact. Due to
this the food industry is highly affected by one of Sweden’s 16 environmental quality
objectives, reduced climate impact, which aims to reduce the harmful human induced impact
on the climate system (Swedish Environmental Protection Agency 2009b). Therefore, it
seems highly relevant to focus on climate change when estimating the environmental impact
of retail waste from horticultural products.
7
1.5 Aim and research questions
The aim of this study was to examine how much retail waste increases the climate change
impact of producing fruit, berries, vegetables and potted flowers. The results apply for the
Swedish retail level.
The following questions were addressed:
•
•
•
How much is wasted of horticultural products sold at the Swedish retail level?
Does packaging reduce waste of fruit and vegetables at the retail level?
How large is the climate change impact of retail waste from horticultural products?
1.6 Delimitations
The LCAs of the horticultural products included in this study mainly applied for Swedish
production.
This study only examined the levels of waste produced at the Swedish retail level and within
stores located in urban areas.
The levels of retail waste were only examined for fresh fruit, berries, vegetables and potted
flowers. No other items of food or plants were considered.
This study only included the environmental aspect of climate change. Although this thesis
only highlights the specific issue of greenhouse gas emissions, there are other environmental
aspects to be considered in association with food production. They were, however, not dealt
with in this thesis.
8
2 METHOD
2.1 Life Cycle Assessments
All fruit, berries, vegetables and potted flowers included in the SIK research project (Davis et
al. 2010) are presented in table 1 and 2. The climate change impact of production (excluding
retail waste), for each horticultural product, is also presented in table 1 and 2. The SIK
research project applied for Swedish production, except for kiwi which had been imported.
The functional unit of these results was either one kilogram or one plant, incoming to the
retail store.
TABLE 1. The fruit, berries and vegetables included in the SIK research project, as well as
the climate change impact of production (excluding retail waste).
Climate change impact of
production
Excluding
Fruit, berries
retail waste
and vegetables
(kg CO2-eq/kg)
Apples
0.10
Broccoli
0.78
Cabbages
0.36
Carrots
0.24
Cauliflowers
0.36
Celery root
0.29
Cucumbers
1.15
Iceberg lettuce
0.35
Kiwis
1.36
Leeks
0.25
Onions
0.14
Parsnips
0.36
Pears
0.12
Rutabagas
0.18
Strawberries
0.48
Tomatoes
0.72
TABLE 2. The potted flowers included in the SIK research project, as well as
the climate change impact of production (excluding retail waste).
Climate change impact of
production
Excluding
Potted flowers
retail waste
(kg CO2-eq/plant)
Kalanchoës
0.44
Poinsettias
0.58
The results on climate change impact of production are preliminary, and might change
slightly. For final results, please see “Emissions of Greenhouse Gases from Production of 18
Fruits, Vegetables and Flowers sold in Sweden” (Davis et al. 2010).
9
In brief, LCA is an ISO standardised method (ISO 14044:2006), which is used to assess the
overall environmental impact of a product. Which specific environmental impact(s) that are
going to be considered, is decided based on the aim of each assessment. Which parts of the
life cycle that are going to be included, is also decided for each specific LCA (Baumann et al.
2004). What characterises the LCA method in general is that it studies the whole life cycle of
a product, from the cradle to the grave. This is done in order to identify those parts of the life
cycle which entail the largest environmental impact. These need to be considered most, when
aiming to reduce the overall environmental impact of a product.
The LCAs performed at SIK examined the climate change impact of producing certain
horticultural products. The assessments included all climate change contributing production
steps, from initial agricultural cultivation to final retail distribution. All included steps are
illustrated in figure 1. Data on greenhouse gas emissions surrounding these steps was
collected. The different greenhouse gas emissions were then weighted, and expressed as CO2eq emissions, in order to show their relative contribution to the overall climate change impact
(Baumann et al. 2004).
Input
Agricultural cultivation
Retail stage
Distribution
Wholesale
Transportation
Transportation
Industrial processing
Packaging
FIGURE 1. A simplified flowchart of the LCAs of horticultural products, illustrating all climate change
contributing activities included in the assessments.
The climate change impact of a product equals the accumulated amount of greenhouse gas
emissions caused by its production, commonly expressed as kg CO2-eq emissions from
producing one functional unit of a certain product.
10
2.2 Waste Survey
The waste survey within this thesis was carried out in cooperation with one of the leading
Nordic retail companies (anonymous), which contributed data on waste and sales of the fruit,
berries and vegetables included in this study. The participating retail company offers a variety
of goods in the stores, although mostly different kinds of food articles. The company stores,
which are of different sizes, have slightly different ranges of products in order to meet the
needs of different customer groups.
The sales of potted flowers, within the participating retail stores, were handled in accordance
with the shop-in-shop concept. The waste survey was therefore also carried out in cooperation
with one of the major flower distribution companies, connected to the Swedish retail sector.
2.2.1 Collection of data
Retail waste of fruit, berries and vegetables
The retail stores were initially contacted by phone. Firstly, some basic information on this
thesis was given and secondly the staff was asked to participate in the waste survey. After
having established collaboration with a certain store, written instructions were sent in an
email to the person responsible for the fruit and vegetable section, alternatively to the owner,
of the store. The form included specific instructions on which particular data that were of
interest (Appendix A). The staff was asked to send the filled out form back to SIK, prior to a
certain date. If the answer was delayed, a second (and in some cases a third) phone call was
made during which the staff was reminded and encouraged to fulfil the task.
In total, 76 retail stores were contacted. Among these, 36 were fairly small with a gross
turnover of approximately 50 MSEK, and 40 were larger with a gross turnover of between
150 – 650 MSEK. However, not all retail stores initially contacted kept adequate
documentation of the wasted amounts of fruit, berries and vegetables, considering the aim of
this study. Therefore, the participating retail stores were foremost selected based on ability to
deliver the data of interest. Hence, all participating retail stores had ongoing inventory control
systems, keeping track of waste and sales.
Among all the 76 retail stores initially contacted, 39% (30/76) kept documentation of the
wasted amounts of fruit, berries and vegetables. Among the small retail stores 31% (11/36)
did, and among the large retail stores 48% (19/40) did (figure 2).
No. of stores
Waste documentation within contacted retail stores
80
60
No
40
Yes
20
0
Small retail stores
Large retail stores
All retail stores
FIGURE 2. The number of contacted retail stores which did and did not keep documentation of the wasted
amounts of fruit, berries and vegetables.
11
In the end, nine retail stores contributed data to the waste survey, four small and five large.
The reasons why staff chose not to participate were mainly lack of time and/or feeling
uncomfortable with the potential attention this kind of waste survey could give rise to. Since
waste of food is a somewhat delicate topic, the retail company, as well as the retail stores, was
kept anonymous throughout this report.
The collected data applied for the annual quantities of waste and sales for each type of fruit,
berry and vegetable included in this study. The quantities were put in kilograms, numbers or
liters, depending on how the quantities had first been registered within the retail store. The
collected data applied for piecemeal sales of all fruit, berries and vegetables included in this
study. In addition to this, the same data were also collected for apples, kiwis, onions and
tomatoes when sold packaged. Since most retail stores supplied a variety of brands of each
fruit, berry and/or vegetable, the staff was asked to choose one brand for each product.
The quantities of waste had been documented within the different retail stores using
approximately the same routine. The fruit and vegetable supply was inventoried on a daily,
alternatively weekly, basis. All items of fruit, berries and vegetables that were not considered
saleable were then discarded. Before being discarded, the waste was registered digitally by
weight/number/volume and product.
The data applied for the extended time period between October 1st 2008 and October 1st 2009.
This span was chosen since several retail stores did not save their data longer than
approximately 400 days. For one participating retail store, the data instead applied for year
2008.
Retail waste of potted flowers
The flower distribution company was contacted by email. Firstly, some basic information on
this thesis was given and secondly the staff was asked to participate in the waste survey. The
correspondence was held with the sales manager.
The company stated the annual financial loss of store supply for each of the included potted
flowers, sold within the participating retail company. The financial loss was made up of both
physical waste and price lowering waste. The physical waste represented the waste of interest
for this study, namely potted flowers thrown away since they for various reasons had not been
sold. This happened for example because of low demand or poor quality. The price lowering
waste on the other hand represented lost income, during for example clearance sales. The
flower distribution company was not able to specify the physical waste separately, and
therefore it had to be estimated. Staff appraised that the financial loss made up of
approximately 70% physical waste and 30% price lowering waste. Hence, the physical waste
of potted flowers was assumed to be 70% of the stated financial loss.
The data applied for the extended time period between October 1st 2008 and September 30th
2009.
12
2.2.2 Calculations
Waste proportion of store supply for fruit, berries and vegetables
In this study, focus was set on the waste proportion of store supply (W%). Each participating
retail store stated the annual quantities of waste (W) and sales for each fruit, berry and
vegetable included in this survey. The sum of waste and sales equaled the store supply (SS).
W
W% = ____
SS
Waste proportion of store supply for potted flowers
In this study, focus was set on the waste proportion of store supply (W%). The participating
flower distribution company stated the financial loss proportion of store supply (FL%), for
each potted flower included in this survey. The waste proportion of store supply was
estimated to make up 70% of the financial loss proportion.
W% = FL% · 0.7
Climate change impact of production (including retail waste)
The climate change impact of production (including retail waste) was estimated by
multiplying the climate change impact of production (excluding retail waste) with the retail
waste factor described below. W% applied for the waste proportion of store supply.
Retail waste factor =
1
(1 – W%)
Climate change impact of retail waste
The climate change impact of retail waste equalled the difference between climate change
impact of production including, and excluding, retail waste.
13
3 RESULTS
3.1 Retail waste of fruit, berries and vegetables sold piecemeal
The annual quantities of waste and sales, for each type of piecemeal fruit, berry and vegetable
are found in appendix B and C, along with each computed store supply and waste proportion
of store supply. Not every store kept all types of products in supply.
Figure 3 illustrates the annual mean waste proportion of store supply, for fruit, berries and
vegetables sold piecemeal, based on the waste proportions stated by all participating retail
stores (appendix E). The mean waste ranged from 0.4% to 6.3% of store supply.
Mean waste proportion of store supply for piecemeal sales
Waste
0%
1%
2%
3%
4%
5%
6%
7%
Broccoli
Strawberries
Cauliflowers
Celery root
Rutabagas
Kiwis
Parsnips
Pears
Tomatoes
Leeks
Iceberg lettuce
Carrots
Apples
Cucumbers
Cabbages
Onions
FIGURE 3. The annual mean waste proportion of store supply for fruit, berries and vegetables sold piecemeal.
As shown in figure 3, the fruit, berries and vegetables wasted the most in relative terms were
broccoli (6.3%), strawberries (4.8%) and cauliflowers (4.7%). In contrast, the types wasted
the least in relative terms were onions (0.4%), cabbages (0.7%) and cucumbers (0.9%).
14
Also, the overall waste proportion of store supply, of the included fruit, berries and
vegetables, was computed for each participating retail store. The results showed that the
overall waste ranged from 1.4% to 4.4% of store supply (appendix E).
Figure 4 illustrates the dispersion of data on annual waste proportion of store supply, for each
fruit, berry and vegetable sold piecemeal. Each dot represents the waste within one single
retail store (appendix E). Figure 4 also shows the standard deviation (SD) within each group
of data (appendix E).
Dispersion of data on piecemeal sales
SD
Broccoli
0,05
Strawberries
0,07
Cauliflowers
0,02
Celery root
0,05
Rutabagas
0,03
Kiwis
0,04
Parsnips
0,02
Pears
0,01
Tomatoes
0,01
Leeks
0,02
Iceberg lettuce
0,01
Carrots
0,01
Apples
0,01
Cucumbers
0,01
Cabbages
0,00
Onions
0,00
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
Waste
FIGURE 4. The dispersion of data on annual waste proportion of store supply for fruit, berries and vegetables
sold piecemeal.
For piecemeal sales, the overall dispersion of data ranged from 0% to 16.6%. The majority of
waste levels were however between 0% and 6%.
There were a number of major outliers, foremost among the data on strawberries (16.6%),
celery root (15.7%), broccoli (14.6%), rutabagas (11.2%), kiwis (11.3%) and parsnips (8.0%).
These were all single outliers, within each group, which were considerably separated from the
rest of the data. These outliers all derived from three different retail stores (appendix E). The
incidence of outliers, as well as generally scattered data, increased the standard deviation.
15
The span between smallest and largest observed waste proportion was rather wide for three of
the four top wasted products, namely broccoli (2.1% - 14.6%), strawberries (0.5% - 16.6%)
and celery root (1.3% - 15.7%). This was mainly due to one single outlier within each group
of data.
For other products, the span between smallest and largest observed waste proportion was
rather small. This applied for cabbages (0.2% - 1.5%), cucumbers (0.3% - 1.8%) and onions
(0% - 1.6%).
3.2 Retail waste of potted flowers
Figure 5 shows the annual waste proportion of store supply for the two potted flowers
included in this study. Poinsettia generated less physical waste (2.5%) than Kalanchoë, which
generated 3.0%. The financial loss (FL %) was estimated to be 3.6% for Poinsettias and 4.3%
for Kalanchoës.
Waste
Waste proportion of store supply for
potted flowers
4%
3%
2%
1%
0%
Poinsettias
Kalanchoës
FIGURE 5. The annual waste proportion of store supply for potted flowers.
Figure 3 and 5 together show that the mean waste proportions of store supply were similar for
potted flowers as for fruit, berries and vegetables.
16
3.3 Retail waste of packaged compared to piecemeal sales
The annual quantities of waste and sales, for each type of packaged fruit and vegetable are
found in appendix D, along with each computed store supply and waste proportion of store
supply. Not every store kept all types of products in supply. The data on piecemeal sales were
the same as in figure 3 (appendix B & C).
Waste
Figure 6 illustrates the annual mean waste proportion of store supply for apples, kiwis, onions
and tomatoes when sold packaged, compared to when sold piecemeal (appendix E).
M ean waste proportion of store supply for packaged
compared to piecemeal sales
5%
4%
3%
2%
1%
0%
Packaged
Piecemeal
Apples
Kiwis
Onions
Tomatoes
FIGURE 6. The annual mean waste proportion of store supply for apples, kiwis, onions and tomatoes when sold
packaged, compared to when sold piecemeal.
The mean waste proportion of store supply for apples, kiwis, onions and tomatoes ranged
from 0.9% to 3.8% when sold packaged and from 0.4% to 3.8% when sold piecemeal. When
sold packaged, apples, onions and tomatoes generated larger amounts of waste in relative
terms (3.4%, 0.9%, 3.8%), compared to when sold piecemeal (1.1%, 0.4%, 2.2%). The
opposite applied for kiwis, which in relative terms generated less waste when sold packaged
(2.8%) compared to when sold piecemeal (3.8%).
17
Figure 7 illustrates the dispersion of data on annual waste proportion of store supply, for
apples, kiwis, onions and tomatoes sold packaged. Each dot represents the waste within one
single retail store (appendix E). Figure 7 also shows the standard deviation (SD) within each
group of data (appendix E).
Dispersion of data on packaged sales
SD
Apples
0,02
Kiwis
0,02
Onions
0,01
Tomatoes
0,05
0%
5%
10%
15%
20%
25%
Waste
FIGURE 7. The dispersion of data on annual waste proportion of store supply for fruit and vegetables sold
packaged.
The dispersion of data on packaged fruit and vegetables ranged from 0% to 16.1%. All waste
levels except for one, tomatoes at 16.1%, were between 0% and 6% (appendix E).
The outlier on packaged tomatoes, at 16.1%, increased the mean waste of this product
significantly. Without this one outlier, the retail waste of packaged tomatoes was less than for
piecemeal tomatoes (2.1% vs. 3.8%). The tomatoe outlier also increased the standard
deviation within this group of data.
18
3.4 Retail waste in small compared to large retail stores
Figure 8 shows the mean waste proportions of store supply within small and large retail
stores, for piecemeal and packaged sales respectively. The mean waste proportions of store
supply within small retail stores are found in appendix B and D. The mean waste proportions
of store supply within large retail stores are found in appendix C and D. Not every store kept
all types of products in supply.
The small retail stores had in general produced more waste, as illustrated in figure 8. This
applied for 13 of the 16 piecemeal fruit, berries and vegetables. It also applied for three of the
four fruit and vegetables sold packaged.
Mean waste proportion of store supply for piecemeal and packaged sales,
in small and large retail stores
Waste
0%
1%
2%
3%
4%
5%
6%
7%
8%
Broccoli
Strawberries
Cauliflowers
Celery root
Rutabagas
Kiwis
Parsnips
Pears
Tomatoes
Leeks
Small
Iceberg lettuce
Large
Carrots
Apples
Cucumbers
Cabbages
Onions
Apples (packaged)
Kiwis (packaged)
Onions (packaged)
Tomatoes (packaged)
FIGURE 8. The mean waste proportion of store supply for piecemeal, and packaged, sales within small and large
retail stores respectively.
The fruit and vegetables, which differed most between small and large retail stores, were
celery root (7.4% vs. 2.4%), strawberries (6.5% vs. 2.3%) and packaged tomatoes (7.3% vs.
1.7%), which all had generated more waste within the small retail stores (appendix E).
19
The only fruit and vegetables which on average had generated less waste within small retail
stores, compared to large, were broccoli (5.1% vs. 7.4%), carrots (1.0% vs. 1.5%), piecemeal
kiwis (3.1% vs. 4.5%) and packaged apples (3.3% vs. 3.5%) (appendix E).
3.5 Climate change impact of retail waste from horticultural products
Figure 9 shows the climate change impact of retail waste in relation to the overall climate
change impact of production (including retail waste) (appendix F), for the potted flowers and
piecemeal fruit, berries and vegetables included in this study. The black part in each bar
represents the climate change impact of retail waste.
Climate change impact of retail waste in relation to climate change impact
of production (including retail waste), for horticultural products
kg CO2-eq
0,0
0,5
1,0
1,5
Kiwis
Cucumbers
Broccoli
Tomatoes
Strawberries
Poinsettias
Kalanchoës
Cauliflowers
Parsnips
Cabbages
Iceberg lettuce
Celery root
Leeks
Carrots
Rutabagas
Onions
Pears
Apples
FIGURE 9. The climate change impact (CO2-eq emissions/kg/plant) of retail waste (black) in relation to total
climate change impact of production (grey), for all piecemeal horticultural products included in this study.
The overall climate change impacts of production (including retail waste) ranged from 0.10 to
1.41 kg CO2-eq emissions for each produced kg/plant leaving the retail store. As shown in
figure 9, the products generating the largest climate change impact were kiwis (1.41),
cucumbers (1.16) and broccoli (0.83). In contrast, the products generating the least climate
change impact of production were apples (0.10), pears (0.12) and onions (0.14) (appendix F).
20
Figure 10 shows the climate change impact of retail waste for the potted flowers and
piecemeal fruit, berries and vegetables included in this study (appendix F). These results equal
the dark parts of the bars in figure 9.
Climate change impact of retail waste from horticultural products
kg CO2-eq
0,000
0,020
0,040
0,060
Kiwis
Broccoli
Strawberries
Cauliflowers
Tomatoes
Poinsettias
Kalanchoës
Parsnips
Cucumbers
Celery root
Rutabagas
Iceberg lettuce
Leeks
Carrots
Pears
Cabbages
Apples
Onions
FIGURE 10. The climate change impact (CO2-eq emissions/kg/plant) of retail waste for all piecemeal
horticultural products included in this study.
The climate change impact of retail waste ranged from 0.001 to 0.054 kg CO2-eq emissions
for each produced kg/plant leaving the retail store. Three different fruit and vegetables stood
out from the rest of the horticultural products by causing significantly higher climate change
impacts due to retail waste, namely kiwis (0.054), broccoli (0.052) and strawberries (0.029).
Those horticultural products which generated the lowest climate change impact of retail waste
were onions (0.001), apples (0.001) and cabbages (0.002).
The results in figure 9 and 10 together illustrate how the climate change impact of retail waste
mostly followed the magnitude of overall climate change impact of production. There were,
however, a few exceptions. Cucumbers for example caused the second largest climate change
impact of production (figure 9), but due to the low waste level only the tenth largest climate
change impact of retail waste (figure 10).
21
4 DISCUSSION
This study aimed to examine how much retail waste increases the climate change impact of
producing horticultural products. The retail sector is a significant part of the food distribution
chain, handling a considerable amount of fruit, berries, vegetables and potted flowers heading
towards the consumer households. To date, little research has been made on the subject of
retail waste in Sweden. Therefore, this study filled a gap in the LCAs on the climate change
impact of producing horticultural products.
For the fruit, berries and vegetables included in this study, the annual waste proportions of
store supply stretched from 0.4% to 6.3%. Not surprisingly, fragile products, like broccoli
(6.3%), strawberries (4.8%) and cauliflowers (4.7%), were in relative terms wasted the most.
Furthermore, solid fruit and vegetables were found among those categories wasted the least,
for example onions (0.4%), cabbages (0.7%) and carrots (1.3%). Hence, the results in this
study support the reasonable assumption that there is a link between fragility and large
amounts of waste.
How do the results in this study compare to waste levels in other parts of the food distribution
chain? WRAP’s report on UK household food waste presented strikingly different results
when concluding that 45% of all purchased salad, 26% of all purchased fruit and 19% of all
purchased vegetables are thrown away (Ventour 2008). Hence, compared to UK households,
the Swedish retail sector seems to generate significantly lower amounts of fruit and vegetable
waste.
The results in this study did not confirm that packaging reduce waste of fruit and vegetables at
the retail level. Packages fill a purpose of reducing waste by protecting fragile fruit and
vegetables from bruising and turning bad (Sonesson et al. 2009). These are concerns
associated with some of the most frequently packaged products, for example kiwis, which in
this study were wasted less when packaged compared to when sold piecemeal. Apples and
onions, on the other hand, were in this study generally wasted more when sold packaged,
compared to when sold piecemeal. These types of solid fruit and vegetables presumably do
fairly well, even without packaging.
Even though packaging not always seems to reduce waste, it does most likely boost the
financial profit of retail stores by increasing the amounts of fruit and vegetables being sold.
Packages also simplify the administration of sales by being pre market with bar codes. The
production of packages does however take resources in claim, and generates large amounts of
material waste (Williams et al. 2007). Due to these environmental drawbacks, packages
should from an environmental point of view only be used when serving the aim of reducing
waste. Otherwise, the overall environmental burden is most likely larger than the gain.
Packaging should preferably reduce waste at the consumer level, where wasting is most
severe. In order to do so, the size of packages should be optimized to meet the needs of
various customers (Williams et al. 2007). Packages should preferably also consist of materials
with low environmental impact, and be filled in a way so that excessive transportation is
minimised. If not, packaging instead moves food waste from the retail sector to the consumer
households. According to the WRAP report, approximately 28% of all household food waste
was in its original packaging. Among this, 13% consisted of vegetables, 9% of salads and 4%
of fruit (Ventour 2008). Apparently, fruit and vegetables are frequently found among food
products thrown away packaged.
22
The results in this study indicated that small retail stores, compared to large, produce more
waste of fruit berries and vegetables in relative terms. In the same fashion, WRAP’s report on
household food waste concluded that single households produce the most food waste per
capita (Ventour 2008). Hence, it seems as if large entities are beneficial for the purpose of
reducing food waste, both within the retail sector and the consumer households.
What could be possible explanations to the seemingly lower levels of waste in large retail
stores? Waste of fruit and vegetables within the retail sector can be tied to various problems.
Some of these include over-ordering; over-trimming the supplies; insufficient shelf-life;
passed sell-by dates and seasonal ordering (Alexander et al. 2008). In addition to this, all
retail stores regardless of size seem to aim at keeping non-stop filled supplies, which partly
explains why fruit, berries and vegetables turn bad. In order to reduce retail waste it seems
important to limit the time period fresh products spend in the store before being sold. Large
retail stores, compared to small, understandably have a more rapid flow of customers. Large
retail stores also most likely have a wider range of customers, which demand a wider range of
products. All retail stores, regardless of size, would most likely reduce waste if cutting down
the quantities on display and if adjusting order sizes to the current demand, for each product
respectively. Narrowing the overall range of products would probably also reduce waste.
The dispersion of data for fruit, berries and vegetables within this waste survey was large.
Also, several major outliers among the data on piecemeal sales (figure 4) derived from three
specific retail stores. Hence, there seemed to be structural differences in the magnitude of
waste produced within different retail stores. Alternatively, certain retail stores carried out a
more thorough waste documentation. Most likely, personal skills of staff members had some
influence on the wasted amounts within each retail store. The person responsible for the fruit
and vegetable section of the store could do a more or less good job of keeping supplies at the
most waste reducing levels. Also, staff members made different judgements on which food
items that were going to be considered as waste. And finally, every single item of waste might
not have been registered before being thrown away.
The transparency of data on fruit, berries and vegetables within this study was low, since it
solely represented second hand information. The participating retail stores had prior to this
study registered the quantities of waste purely because of internal motives, and not to be part
of a waste survey. This brings questions to the accuracy of data. It does however also
strengthen its credibility by avoiding bias.
All retail stores participating in this study already indirectly worked on reducing the amounts
of waste produced. Well established inventory control systems enabled to identify excessive
wasting, and therefore most likely had a waste reducing effect. Even though the foremost
motive for keeping track of waste surely was to increase the financial profit, the waste
reducing effect would be expected. This bearing was of course a flaw in the process of
choosing which retail stores that were going to be part of the waste survey. It was, however,
necessary since this study depended on the retail stores being able to distribute detailed data
on the amounts of waste produced.
23
The waste proportions of store supply for potted flowers were rough assumptions based on the
financial loss of sales. Since the flower distribution company had no access to detailed data on
the actual waste of potted flowers, these assumptions had to be made. Each financial loss
could however be considered fairly accurate, since it derived from financial bookkeeping.
Considering the low levels, these estimations did not affect the final results a whole lot.
The climate change impact of producing the fruit, berries, vegetables and potted flowers
included in this study was estimated by doing LCAs. This method makes environmental
issues concrete by embodying them in numbers, which of course enables an efficient
visualisation of the problems (Baumann & Tillman 2004). However, so called “hard
numbers” can be somewhat misleading by giving the impression that environmental issues are
more measurable and concrete than they really are (Eriksson & Wiedersheim-Paul 2008).
However, this thesis only included the results from already completed assessments, and the
quality of this thesis should solely be judged based on the methods actually used within it.
Besides this, the LCA method challenges the result interpreter by assuming a certain level of
awareness, regarding for example the choice of system boundaries. These determine which
production steps that are going to be included in the LCA, and will of course affect the
outcome of the assessment. Each LCA is in fact a rather subjective examination of the
environmental impact of a product. Which processes that are included, and which aspects that
are considered, is decided by the people conducting the assessment. Therefore, it is important
as an interpreter of LCA results to study the circumstances, before drawing any conclusions
(Baumann & Tillman 2004).
The climate change impact of producing the fruit, berries and vegetables included in this
study ranged from 0.10 to 1.41 kg CO2-eq emissions for each kg produced (leaving the retail
store). These figures are relatively low, especially compared to food products with an animal
origin. Producing chicken, salmon, cod and pork usually causes a climate change impact of
somewhere between 1 and 5 kg CO2-eq emissions for each kg produced (SIK 2009). The
climate change impact of beef is considerably higher, often ten times that of fruit and
vegetables (SIK 2009). It is however difficult to determine the general climate change impact
of producing certain types of food, due to various production processes being used. However,
producing fruit, berries and vegetables has a relatively low climate change impact.
The climate change impact caused by retail waste of horticultural products is indeed low
compared to that of other food products, mainly due to low climate change impacts of
production. It does, however, also depend on low levels of waste at the retail level. The low
levels of retail waste should however be interpreted in relation to the Swedish consumption of
each product respectively. For example, during year 2006 the Swedish annual per capita
consumption of tomatoes amounted to 10 kg (Board of Agriculture 2010). Assuming that two
thirds of these tomatoes had passed through retail stores, the annual Swedish retail waste of
tomatoes would have totalled approximately 1,400 tons during the same year (over 9 million
inhabitants) (Statistics Sweden 2010). Retail waste of tomatoes thereby caused about 1,000
tons CO2-eq emissions, which equals the average annual emissions from 395 Swedish cars
(Sonesson 2008). These are of course rough assumptions, but do however illustrate how the
low levels of retail waste (0.4% - 6%) in the end generate significant amounts of greenhouse
gas emissions.
24
Another point to be made is that the retail waste levels, as well as the climate change impact
of production, were modestly estimated in this thesis. The retail stores participating in this
study were, as mentioned before, probably wasting less than the average Swedish retail store.
Also, the climate change impact of production in this thesis only applies to Swedish
production (except for kiwis). The impacts of domestic products are often lower than those of
imported products, due to the environmental burden of transportation. There are however
exceptions, since the impacts also depend on the premises for cultivation. Still, the results in
this thesis were most likely not exaggerated, but rather somewhat understated.
How waste is handled after having left the retail store is a relevant question when considering
the overall climate change impact of retail waste. The aspect of waste handling was however
not taken into account when estimating the climate change impact of producing the
horticultural products included in this study. In Sweden, no biodegradable waste is allowed to
be disposed at landfills (Ministry of Environment 2001). This law avoids methane emissions
since food waste at landfills is degraded under anaerobic conditions (Sonesson 2009). Also, at
least 35% of all Swedish food waste produced by households, caterers, restaurants and retail
stores should by 2010 be recovered by means of biological treatment, which applies for
digestion and composting. This goal has been set up in accordance with the Swedish national
environmental objective - A Good Built Environment (Swedish Environmental Protection
Agency 2009c). During year 2008 about 20% of food waste produced within Sweden was
reused in this way (Swedish Environmental Protection Agency 2009d). In addition to this,
food waste is also burned in order to produce energy (Swedish Environmental Protection
Agency 2009e).
Important to remember is that the food wasted by conventional retail stores not always is
below standards for human consumption. Fresh fruit and vegetables easily loose its freshness
and spotless appearance. It may, however, still be perfectly edible. Therefore, certain retail
stores sell surplus food to customers at reduced prices. It also happens that food is donated to
charities for human consumption, or to farms and zoos as animal feed (Alexander et al. 2008).
Reusing retail surplus food, when possible, certainly decreases its climate change impact.
Retail waste of food entails unnecessary climate change impact. The products have through
their production contributed greenhouse gas emissions, only to be wasted. Considering the
future world population growth, food should be considered a scarce resource, and efforts
should by all means be made to continuously minimize wasting throughout the food
production chain. We need not only to focus on how to make food production more efficient.
We also need to focus on how to fully make use of the food already produced.
25
5 CONCLUSIONS
This study aimed to examine how much retail waste increases the climate change impact of
horticultural products. The waste levels produced, of the fruit, berries, vegetables and potted
flowers included in this study, were examined. The potential waste reducing effect of
packaging was also investigated. Finally, the climate change impact of retail waste from
horticultural products was determined.
The results in this study concluded that:
•
The mean waste proportions of store supply for horticultural products sold piecemeal
ranged from 0.4% to 6%, at the retail level. Mostly wasted in relative terms were
fragile products, sensitive to damage.
•
Packaging does not seem to reduce waste of fruit and vegetables at the retail level.
This part of the study did however only include four different products.
•
The levels of waste, in general, seemed larger within small retail stores, compared to
large, for fruit, berries and vegetables.
•
All participating retail stores had ongoing inventory control systems. Hence, the levels
of waste were low within retail stores aware of the amounts of waste produced.
•
The dispersion of waste levels stated by the participating retail stores was large, for
fruit, berries and vegetables sold piecemeal. There were some minor structural
differences, between the participating retail stores, in the amounts of waste produced.
•
The climate change impact of retail waste from horticultural products ranged from
0.001 to 0.054 kg CO2-eq emissions, for each produced kg or plant leaving the retail
stores. Two factors determined the climate change impact of retail waste, namely the
waste proportion of store supply and the climate change impact of production
(excluding retail waste).
26
6 RECOMMENDATIONS
There are several ways in which the climate change impact of retail waste from horticultural
products could be reduced. Based on the results of this study, and conversations held with
staff members at the participating retail stores, the following recommendations can be made:
•
Efforts should by all means be made to continuously reduce retail waste of
horticultural products, considering the large amounts passing through the retail sector
each year. Efforts should however also be focused towards the consumer level, where
wasting is most severe.
•
In order to reduce waste of horticultural products, retail stores should preferably limit
the quantities on display and only keep products in supply which have a steady
customer base. Order sizes should be adjusted to the current demand for each product
respectively.
•
Efforts should be made to introduce inventory control systems, such as waste
documentation, throughout the entire retail sector.
•
Future surveys on the subject of retail waste should, compared to this study, include a
larger number of participating retail stores. Future surveys should also preferably
conduct their own inventories of waste.
•
Surplus food within the retail sector should, when possible, not be wasted but instead
reused. This could for example be done by selling it to consumers at reduced prices,
donating it to charities for human consumption or to farms as animal feed.
27
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30
APPENDIX A: Inventory form
(X = Replaces names, addresses and telephone numbers due to secrecy.)
For the attention of staff members at the fruit and vegetable section of the store,
I have been assigned by The Swedish Institute for Food and Biotechnology to conduct a
survey concerning waste of fruit and vegetables within the Swedish retail sector. The study is
carried out in cooperation with X. However, neither X nor any specific retail stores will be
mentioned in the report. I now need help from a number of retail stores with collecting data
on the annual waste of fruit and vegetables. To be able to compute the waste proportion of
store supply, I also need data on the annual sales of each product.
The data should apply for the extended time period: October 1st 2008 - October 1st 2009.
I will also compare the waste of certain fruit and vegetables, concerning packaging. I will
examine whether waste differs, for the same product, when sold packaged compare to when
sold piecemeal. The chosen fruit and vegetables for this part of the survey are tomatoes,
apples, kiwis and onions.
So, the data I wish to receive from you is (all is included in the tables below):
•
Data on the annual waste (SEK) and sales (SEK) for the entire fruit and
vegetable section of the store.
•
Data on the annual waste (kg) of: tomatoes, cucumbers, cauliflowers, broccoli,
carrots, parsnips, iceberg lettuce, onions, leeks, rutabagas, celery root, cabbage,
apples, pears, strawberries, kiwis and potted salads.
•
Data on the annual sales (kg) of: tomatoes, cucumbers, cauliflowers, broccoli,
carrots, parsnips, iceberg lettuce, onions, leeks, rutabagas, celery root, cabbage,
apples, pears, strawberries, kiwis and potted salads.
•
Data on the annual waste (number of packages) of tomatoes, apples, kiwis and
onions sold packaged, in for example plastic packaging or net.
•
Data on the annual sales (number of packages) of tomatoes, apples, kiwis and
onions sold packaged, in for example plastic packaging or net.
31
Fill out the tables below. Please leave empty if there is no data available.
1.
The waste, October 1st 2008 - October 1st 2009, for the entire store supply of fruit and
vegetables
=
SEK
The sales, October 1st 2008 - October 1st 2009, for the entire store supply of fruit and
vegetables
=
SEK
2. Choose one representative brand within each category!
Piecemeal
October 1st 2008 - October 1st 2009
Category
Waste
(kg)
Sales
(kg)
Tomatoes
Cucumbers
Cauliflowers
Broccoli
Carrots
Parsnips
Iceberg lettuce
Onions
Leeks
Rutabagas
Celery root
Cabbages
Apples
Pears
Strawberries
Kiwis
32
3. Choose one brand representative within each category
Packaged
October 1st 2008 - October 1st 2009
Category
Waste
(Number of
packages)
Sales
(Number of
packages)
Tomatoes
Apples
Kiwis
Onions
I would be very grateful to receive the data by mail/email before X, the address is found
below.
If you have any questions, please contact me:
Jenny Gustavsson, student
SIK, Department of Sustainable Food Production
X
X
X
For questions concerning the cooperation with X, please contact:
X
X
X
X
X
Thank you for participating!
Best regards,
Jenny Gustavsson
33
APPENDIX B: Waste data for piecemeal sales, small retail stores
TABLE A. The annual quantities of waste (W) and sales (S) stated in kilograms, as well as the computed store supply (SS)
and waste proportion of store supply (W%). The data applied for the time period between October 1st 2008 and October 1st 2009.
Annual waste (W), sales (S), store supply (SS) and waste proportion of store supply (W%) - (kilograms)
Small retail stores
Piecemeal
A
B¤
C
D
W
S
SS
W% W S
SS W% W
S
SS
W%
W
S
SS
222 15324 15546 1.4% 81 3800 3881 2.1% 185 12994 13179 1.4% 91 12321 12412
Apples
158 2167 2325 6.8% 55 790 845 6.5% 49 2318 2367 2.1%
Broccoli
45 5651 5696 0.8% 6 1492 1498 0.4% 15 3026 3041 0.5% 64 4694 4758
Cabbages
55 7531 7586 0.7% 35 2169 2204 1.6%
53 9333 9386
Carrots
203 2695 2898 7.0% 48 960 1008 4.8% 78 1775 1853 4.2% 112 1524 1636
Cauliflowers
37
561
598 6.2% 4 220 224 1.8% 32
494
526 6.1% 66
355
421
Celery root
108 16757 16865 0.6% 63 5435 5498 1.1% 272 14712 14984 1.8% 249 13826 14075
Cucumbers
168 8600 8768 1.9% 96 2525 2621 3.7% 276 6686 6962 4.0% 309 8608 8917
Iceberg lettuce
105 6166 6271 1.7% 41 780 821 5.0% 34 1191 1225 2.8%
Kiwis
61 3444 3505 1.7% 17 998 1015 1.7% 50 3051 3101 1.6% 137 2335 2472
Leeks
27 8459 8486 0.3% 9 3225 3234 0.3% 53 10339 10392 0.5% 114 6900 7014
Onions
17
877
894 1.9% 5 320 325 1.5% 89 1018 1107 8.0% 24
546
570
Parsnips
302 5949 6251 4.8% 22 860 882 2.5% 80 5159 5239 1.5% 151 4709 4860
Pears
54 1086 1140 4.7% 8 540 548 1.5% 43
892
935 4.6% 59
467
526
Rutabagas
150 6327 6477 2.3%
119# 600# 719 16.6% 15 2767 2782
Strawberries
235 10972 11207 2.1% 85 4500 4585 1.9% 269 9217 9486 2.8% 446 9069 9515
Tomatoes
* Stated in numbers
¤Data applied for year 2008
# Stated in litres
(The different entities of waste/sales did not affect the results of this study.)
34
W%
0.7%
1.3%
0.6%
6.8%
15.7%
1.8%
3.5%
5.5%
1.6%
4.2%
3.1%
11.2%
0.5%
4.7%
APPENDIX C: Waste data for piecemeal sales, large retail stores
TABLE B. The annual quantities of waste (W) and sales (S) stated in kilograms, as well as the computed store supply (SS)
and waste proportion of store supply (W%). The data applied for the time period between October 1st 2008 and October 1st 2009.
Piecemeal
Apples
Broccoli
Cabbages
Carrots
Cauliflowers
Celery root
Cucumbers
Iceberg lettuce
Kiwis
Leeks
Onions
Parsnips
Pears
Rutabagas
Strawberries
Tomatoes
Annual waste (W), sales (S), store supply (SS) and waste proportion of store supply (W%) - (kilograms)
Large retail stores
E
F
G
H
W
S
SS
W%
W
S
SS
W% W
S
SS
W% W
S
SS
W%
2650 1745721 1748371 0.2% 1235 39533 40768 3.0% 78 41583 41661 0.2% 154 24413 24567 0.6%
8754
9163 4.5% 138 4402 4540 3.0%
372
2172
2544 14.6% 409
85
37621
37706 0.2% 382
25781 26163 1.5% 103 22553 22656 0.5%
121
11450
11571 1.0% 134
5530
5664 2.4% 177 11767 11944 1.5% 317 16017 16334 1.9%
621
10466
11087 5.6% 588
12294 12882 4.6% 158 8205 8363 1.9% 120 8853 8973 1.3%
53
2427
2480
2.1% 169
2621
2790 6.1% 26
1934 1960 1.3% 25 1947 1972 1.3%
753
62678
63431 1.2% 510
90918 91428 0.6% 240 87000 87240 0.3% 318 46617 46935 0.7%
1150 510072 511222 0.2% 813
51647 52460 1.5% 230 47062 47292 0.5% 201 38436 38637 0.5%
210
1641
1851 11.3% 2728* 151717* 154445 1.8% 47
9180 9227 0.5%
340
12362
12702 2.7% 315
16100 16415 1.9% 55 11527 11582 0.5% 33 9837 9870 0.3%
134
45312
45446 0.3% 220
49750 49970 0.4% 64 36175 36239 0.2% 26 26212 26238 0.1%
167
4155
4322
3.9% 206
5456
5662 3.6% 100 4287 4387 2.3% 116 4166 4282 2.7%
839 646058 646897 0.1% 541
26671 27212 2.0% 345 20136 20481 1.7% 733 18051 18784 3.9%
107
6358
6465
1.7% 211
6590
6801 3.1% 507 6678 7185 7.1% 129 5340 5469 2.4%
38
1229
1267 3.0%
754
51013
51767 1.5% 1419 59229 60648 2.3% 463 48466 48929 0.9% 514 36380 36894 1.4%
* Stated in numbers
# Stated in litres
(The different entities of waste/sales did not affect the results of this study.)
35
W
351
I
S
SS
W%
84502 84853 0.4%
62
49
778
34
315
763
20510
8127
13027
2583
86737
59250
20572
8176
13805
2617
87052
60013
0.3%
0.6%
5.6%
1.3%
0.4%
1.3%
460
12
72
759
152
686#
1290
16151
31413
3677
21696
7340
41483#
60615
16611
31425
3749
22455
7492
42169
61905
2.8%
0.0%
1.9%
3.4%
2.0%
1.6%
2.1%
APPENDIX D: Waste data for packaged sales
TABLE C. The annual quantities of waste (W) and sales (S) stated in number of packages, as well as the computed store supply (SS)
and waste proportion of store supply (W%). The data applied for the time period between October 1st 2008 and October 1st 2009.
Annual waste (W), sales (S), store supply (SS) and waste proportion of store supply (W%) - (number of packages)
Small retail stores
Packaged
A
B¤
C
D
W
S
SS
W%
W S
SS
W% W S SS W% W
S
SS
W%
2
166
168
1.2%
4
85
89
4.5%
87
2004
2091
4.2%
Apples
466
6.0% 40 826 866 4.6%
8 1489 1497 0.5%
28 438
Kiwis
8
2431
2439
0.3%
18
435
453
4.0%
8 1011 1019 0.8%
Onions
66
343
409
16.1%
22
656
678
3.2%
27
1069 1096 2.5%
Tomatoes
¤ Data applied for year 2008
TABLE D. The annual quantities of waste (W) and sales (S) stated in number of packages, as well as the computed store supply (SS)
and waste proportion of store supply (W%). The data applied for the time period between October 1st 2008 and October 1st 2009.
Packaged
W
Apples
Kiwis
Onions
Tomatoes
125
0
88
Annual waste (W), sales (S), store supply (SS) and waste proportion of store supply (W%) - (number of packages)
Large retail stores
E
F
G
H
I
S
SS W% W
S
SS
W% W
S
SS
W% W
S
SS
W% W
S
SS
376 5832 6208 6.1% 158 6130 6288 2.5% 123 5647 5770 2.1% 91 2641 2732
5848 5973 2.1% 154 3411 3565 4.3% 73 7161 7234 1.0% 75 3209 3284 2.3% 170 8718 8888
5974 5974 0.0% 84 9115 9199 0.9% 2
4191 4193 0.0% 23 2889 2912 0.8% 146 20520 20666
7170 7258 1.2% 98 23918 24016 0.4% 294 11613 11907 2.5% 290 10513 10803 2.7% 168 8657 8825
(The different entities of waste/sales did not affect the results of this study.)
36
W%
3.3%
1.9%
0.7%
1.9%
APPENDIX E: Mean waste and standard deviation
TABLE E. The waste proportion of store supply stated by each participating retail store, as well as the standard
deviation within each group of data. The mean waste proportion of store supply within stores A-I (all), A-D
(small) and E-I (large) are also shown. The data applied for the time period between October 1st 2008 and
October 1st 2009.
Annual waste proportion of store supply (W%) for piecemeal and packaged sales, and the standard
deviation (SD) within each group of data.
Mean Mean Mean
Retail Store
Piecemeal
SD
A-I
A-D
E-I
A
B¤
C
D
E
F
G
H
I
Apples
Broccoli
Cabbages
Carrots
Cauliflowers
Celery root
Cucumbers
Iceberg lettuce
Kiwis
Leeks
Onions
Parsnips
Pears
Rutabagas
Strawberries
Tomatoes
Overall
Packaged
Apples
Kiwis
Onions
Tomatoes
Overall
1.4%
6.8%
0.8%
0.7%
7.0%
6.2%
0.6%
1.9%
1.7%
1.7%
0.3%
1.9%
4.8%
4.7%
2.3%
2.1%
2.8%
A
1.2%
6.0%
0.3%
16.1%
5.9%
2.1%
6.5%
0.4%
1.6%
4.8%
1.8%
1.1%
3.7%
5.0%
1.7%
0.3%
1.5%
2.5%
1.5%
1.4%
2.1%
0.5%
0.7%
0.2%
14.6%
0.2%
1.0%
5.6%
2.1%
1.2%
0.2%
11.3%
2.7%
0.3%
3.9%
0.1%
1.7%
3.0%
4.5%
1.3%
1.5%
0.6%
2.4%
4.2% 6.8%
4.6%
6.1% 15.7%
6.1%
1.8% 1.8%
0.6%
4.0% 3.5%
1.5%
2.8%
1.8%
1.6% 5.5%
1.9%
0.5% 1.6%
0.4%
8.0% 4.2%
3.6%
1.5% 3.1%
2.0%
4.6% 11.2%
3.1%
16.6% 0.5%
3.0%
1.9% 2.8% 4.7% 1.5% 2.3%
2.4% 3.9% 4.4% 3.1% 2.6%
Retail store
B¤
C
D
E
F
4.5%
4.2%
6.1%
4.6%
0.5% 2.1% 4.3%
4.0%
0.8% 0.0% 0.9%
3.2%
2.5% 1.2% 0.4%
4.1%
2.0% 1.1% 2.9%
¤ Data applied for year 2008
0.2%
3.0%
0.5%
1.5%
1.9%
1.3%
0.3%
0.5%
0.5%
0.5%
0.2%
2.3%
1.7%
7.1%
0.6% 0.4% 0.01
0.05
0.3% 0.00
1.9% 0.6% 0.01
1.3% 5.6% 0.02
1.3% 1.3% 0.05
0.7% 0.4% 0.01
0.5% 1.3% 0.01
0.04
0.3% 2.8% 0.02
0.1% 0.0% 0.00
2.7% 1.9% 0.02
3.9% 3.4% 0.01
2.4% 2.0% 0.03
1.6% 0.07
0.9% 1.4% 2.1% 0.01
1.5% 1.4% 1.7%
G
2.5%
1.0%
0.0%
2.5%
1.5%
H
2.1%
2.3%
0.8%
2.7%
2.0%
I
3.3%
1.9%
0.7%
1.9%
2.0%
SD
0.02
0.02
0.01
0.05
1.1%
6.3%
0.7%
1.3%
4.7%
4.6%
0.9%
1.9%
3.8%
2.1%
0.4%
3.3%
2.6%
4.2%
4.8%
2.2%
1.4%
5.1%
0.8%
1.0%
5.7%
7.4%
1.3%
1.9%
3.1%
2.6%
0.7%
3.9%
3.0%
5.5%
6.5%
2.9%
Mean Mean Mean
A-I
A-D
E-I
3.4%
2.8%
0.9%
3.8%
3.3%
3.7%
1.7%
7.3%
(The different entities of waste/sales did not affect the results of this study.)
37
0.9%
7.4%
0.6%
1.5%
3.8%
2.4%
0.6%
0.8%
4.5%
1.6%
0.2%
2.9%
2.2%
3.2%
2.3%
1.6%
3.5%
2.3%
0.5%
1.7%
APPENDIX F: Climate change impact
TABLE F. Waste proportion of store supply (W%), computed retail waste factor, climate change impact of
production (both excluding and including retail waste) and the climate change impact of retail waste. The
functional unit of production equalled one kg/plant produced.
Horticultural
product
Kiwis
Cucumbers
Broccoli
Tomatoes
Strawberries
Poinsettias
Kalanchoës
Cauliflowers
Parsnips
Cabbages
Iceberg lettuce
Celery root
Leeks
Carrots
Rutabagas
Onions
Pears
Apples
Retail
W% waste
factor
0.04
0.01
0.06
0.02
0.05
0.03
0.03
0.05
0.03
0.01
0.02
0.05
0.02
0.01
0.04
0.00
0.03
0.01
1.04
1.01
1.07
1.02
1.05
1.03
1.03
1.05
1.03
1.01
1.02
1.05
1.02
1.01
1.04
1.00
1.03
1.01
Climate change impact of production
(kg CO2-eq/kg/plant)
Excluding
retail waste
1.36
1.15
0.78
0.72
0.58
0.58
0.44
0.36
0.36
0.36
0.35
0.29
0.25
0.24
0.18
0.14
0.12
0.10
38
Including
Impact of
retail waste retail waste
1.41
1.16
0.83
0.74
0.61
0.59
0.45
0.38
0.37
0.36
0.36
0.30
0.26
0.24
0.19
0.14
0.12
0.10
0.054
0.011
0.052
0.016
0.029
0.015
0.014
0.018
0.012
0.002
0.007
0.014
0.005
0.003
0.008
0.001
0.003
0.001