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Trends in Food Science & Technology
journal homepage: www.elsevier.com/locate/tifs
Review
Mapping energy consumption in food manufacturing
Alia Ladha-Sabur
a
, Serafim Bakalis
a,b
, Peter J. Fryer
a
, Estefania Lopez-Quiroga
a,∗
a
School of Chemical Engineering, The University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
b
Faculty of Engineering, The University of Nottingham, Nottingham, NG7 2RD, UK
ARTICLE INFO
Keywords:
Energy demand
Food manufacturing
Sustainability
UK
ABSTRACT
Background: The food industry is heavily dependent on fossil fuels and significantly contributes to GHG emis-
sions. The global population is also growing and food demand is expected to increase a 60% by 2050. To combat
environmental pollution and create a more sustainable food sector, energy use during manufacturing needs to be
reduced.
Scope and approach: To gain a better understanding of the energy employed in manufacturing and distribution of
foods - within the UK and globally - energy usage within the food industry has been collected from literature and
clustered by product, processing technique and transportation method.
Key findings and conclusions: Energy figures show that instant coffee, milk powder, French fries, crisps and bread
are among the most energy intensive food products. The thermal processes involved in their manufacturing
consumed large proportions of the total processing energy. In the meat and dairy processing sectors, energy and
water use have increased due to a rise in hygienic standards and cleaning requirements. Additionally, meat
products are processed - and sometime over processed - to a higher degree for consumer convenience, all this
increasing the associated energy usage for manufacture. Regarding food transportation, more than 98% of all
foods within the UK are transported by road, and the distances travelled have increased in recent years. Tertiary
distribution using rigid vehicles was the most energy intensive transportation method, while primary distribu-
tion at ambient temperature was the least. Refrigerated transportation, which is more intensive than stationary
refrigerated systems, has also increased during the past years.
1. Introduction
The food sector consumes globally approx. 200 EJ per year (FAO,
2017;EIA, 2017), of which a 45% corresponds to processing and dis-
tribution activities (FAO, 2011;Sims, Flammini, Puri, & Bracco, 2015).
In the UK, the food processing industry is the largest single manu-
facturing sector, with an annual turnover of £97.3bn and 400 k em-
ployees (Food and Drink Federation, 2018). It is also the fourth largest
industrial energy user: 117 petajoules (PJ) consumed in 2017
(Department for Business, Energy and Industrial Strategy, 2018a).
This energy intensity is linked to large levels of greenhouse gas
emissions (GHGEs) and depleting resources (FAO, 2017). While the use
of solid fuels has steadily declined, the food industry is still reliant on
other fossil energy sources (FoodDrinkEurope, 2015;Department for
Business, Energy and Industrial Strategy, 2018a,b) like natural gas and
petroleum, so current practices in food manufacture are considered
unsustainable (EEA, 2015;FAO, 2017). The environmental impact of
food distribution also needs to be considered. The amount of food
transported by heavy goods vehicles (HGVs) in the UK has increased by
23% since 1978 - 287 Mt only in 2017 (Department for Transport,
2018) - and distances travelled have increased by more than 50%
(DEFRA, 2005). The globalisation of the food industry has caused
concerns over food security and an increasing gap between suppliers
and consumers. It has also initiated a debate over the environmental
impacts and cost of food miles (Coley, Howard, & Winter, 2009;Pretty,
Ball, Lang, & Morison, 2005).
In response to environmental policies and rising social concerns, the
food manufacture sector has already undertaken important transfor-
mations to meet long-term reduction goals on energy and water de-
mand (e.g. fuel switching, investment in new energy efficient equip-
ment and low carbon technologies). Initiatives like the “Five-Fold
Environmental Ambition” promoted by the UK Food and Drink
Federation have led to a 44% reduction (by 2014 from the 1990
baseline) in CO
2
emissions from energy used in manufacturing (FDF,
2016). However, in a global scenario of growing population and food
demand – the food industry will have to meet the demands of 9 billion
https://doi.org/10.1016/j.tifs.2019.02.034
Received 5 June 2017; Received in revised form 31 December 2018; Accepted 6 February 2019
∗
Corresponding author.
E-mail addresses: ladhaa@adf.bham.ac.uk (A. Ladha-Sabur), serafim.bakalis@nottingham.ac.uk (S. Bakalis), p.j.fryer@bham.ac.uk (P.J. Fryer),
e.lopez-quiroga@bham.ac.uk (E. Lopez-Quiroga).
Trends in Food Science & Technology 86 (2019) 270–280
Available online 08 February 2019
0924-2244/ © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/BY/4.0/).
T
people by 2050 (FAO, 2017) – additional efforts (Gowreesunker,
Mudie, & Tassou, 2017) are required to meet the 2050 sustainability
goals (80–95% energy reduction from the 1990 baseline) (European
Commission, 2012).
To achieve further reductions on energy demand during food
manufacture and distribution, hotspots must be first identified. Energy
data corresponding to different food processes can be found in a
number of handbooks providing a general overview of food systems
(Arendt & Zannini, 2013;Singh, 2013;Smith, Cash, Nip, & Hui, 1997;
Van Alfen, 2014) or focusing on food and energy (Klemes, Smith, &
Kim, 2008;Morawicki & Hager, 2014;Pimentel & Hall, 1984;Stanhill,
1984;Wang, 2008) and on climate change (Paloviita & Järvelä, 2016).
On the other hand, detailed, comprehensive surveys compiling energy
consumption data for a variety of food products are scarce. One of the
most complete surveys on energy use within the food sector was con-
ducted by Carlsson-Kanyama and Faist (2000). A large amount of data
on food processing was collected, and details about the products, pro-
cesses and energy sources were often specified. Similarly, Foster et al.
(2006) analysed the life cycle of many food products in a report pro-
duced for DEFRA (Department of Environment, Food and Rural Affairs,
UK Government) to provide UK-specific information. Energy use across
stages of the life cycle of products was clearly shown and the most
energy intensive stages were easy to identify. The analysis undertaken
attempted to identify activities that were energy intensive, but data was
predominantly reported in terms of primary energy use, making it more
difficult to compare the energy efficiency with other literature. Ana-
logous studies focused on energy consumption in the U.S. food system
were conducted by Hendrickson (1996), who summarised energy data
by food sub-sectors and also provided a deep analysis on potential re-
duction measures to be adopted, and more recently by Compton, Willis,
Rezaie, and Humes (2018), who updated processing energy use data
and reported more efficient processes.
Typically, studies reporting data on energy use focus on foods
grouped by chain/sub-sector (e.g. cereals, confectionary products, etc).
For example, energy use data for different dairy products has been re-
ported by Cox and Miller (1986),Briam, Walker, and Masanet (2015),
Ramirez, Patel, and Blok (2006a),Xu and Flapper (2009;2011) and Xu,
Flapper, and Kramer (2009). Similarly, Therkelsen, Masanet, and
Worrell (2014) focused on reporting efficiency opportunities in the U.S.
baking sector, Özilgen (2016) calculated energy consumption in snacks
and Wojdalski et al. (2015) evaluated energy efficiency in the manu-
facture of confectionary products. Processors can also be useful sources
of data (e.g. British Sugar) as well as LCA studies - for example works by
Braschkat, Patyk, Quirin, and Reinhardt (2003) on bread, Del Borghi,
Gallo, Strazza, and Del Borghi (2014) on tomato products, Pardo and
Zufía (2012) on food preservation technologies, Rivera and Azapagic
(2016) on ready meals or Konstantas, Jeswani, Stamford, and Azapagic
(2018) and Konstatas, Stamford, and Azapagic (2019) on chocolate and
ice cream, respectively. Energy use data of single foods products is often
paired with specific processes, particularly for emerging technologies.
Examples can be found in Jindarat, Sungsoontorn, and Rattanadecho
(2014) for microwave assisted drying of coffee beans, in Sharma and
Prasad (2006) for microwave drying of garlic cloves, in Atuonwu et al.
(2018) for pasteurisation of orange juice using high pressure, ohmic
and microwave processes, or in Moejes and van Boxtel (2017) for the
manufacture of milk powder. Information on energy consumption for
indivual processes is sparse. For example, Pathare and Roskilly (2016)
investigated meat cooking; Liu, Zhao, and Feng (2008) studied freeze-
drying; Swain (2006) assessed energy consumption in refrigeration
processes; Motevali, Minaei, and Khoshtagaza (2011) focused on
drying; while Li, Ziara, Dvorak, and Subbiah (2018) provided energy
data for packing (meat).
Overall, available energy use data for food manufacture is very
fragmented, and a single comprehensive database is lacking. To address
this and update previous work, energy use for the processing and
transportation of food goods was obtained from the literature to isolate
energy intensive activities and provide starting points for energy re-
duction measures. This data can be also used to feed sustainability
analysis tools such as Life Cycle Assessment (LCA) and carbon or water
footprint, helping to assess and secure the environmental performance
of the whole food chain. Processing energy use figures were clustered
both by product (Section 3and Appendices A-G in the Supplementary
Data) and by technique (see Appendix H,Supplementary Data). Data
collected for transportation methods was analysed in terms of distances
and product carried (Section 4 and Appendix I in the Supplementary
Data). Packaging, the retail sector and consumer activities were outside
the scope of this study. General and UK specific trends were identified
where possible (Section 5). The survey also exposed areas where data is
not available.
2. Methodology framework
A literature survey was carried out to collect energy consumption
for the food manufacturing sector for the time period 1980 to 2015.
ScienceDirect was the main source for published papers, and Knovel
was used for online access to books. Full access to some publications
was obtained from the authors (Carlsson-Kanyama & Faist, 2000;Van
Alfen, 2014)). Specific energy consumption (SEC) data for products,
processes and food distribution was collected based on product-based
energy intensity (PEI) metrics (Briam et al., 2015), where energy input in
megajoules (MJ) was divided by product output in kilograms (kg) -
energy intensity expressed in different units was converted when pos-
sible. This format was chosen to provide a consistent comparative basis.
Data was manipulated as little as possible to minimise errors as SEC
values were collected for a large range of products, processes, locations
and dates. LCA (Life Cycle Assessment) studies reporting lumped SEC
values were not considered for this analysis. Nor were energy audits
that reported overall energy use from processing plants. This search
yielded a total of 44 publications, with the Netherlands, New Zealand
and Sweden being the countries where most studies were found.
Energy studies used different accounting methods and system
boundary conditions when quantifying a product or activity. This re-
sulted in a large range of SEC values where the steps and processes
involved were unknown. The accuracy of data was also often not
mentioned. Different energy sources were reported, and these were kept
in their original format to analyse the ratio of each type used for a given
activity. Equipment details were rarely provided and often details like
the location of the study, the processes included, the production scale
and the energy sources were not specified, as also observed by Xu and
Flapper (2011). Energy intensities of products and processes obtained
by studying the total energy consumed by processing plants (Xu &
Flapper, 2011) did not always account for differences in product mixes,
locations, energy sources, production scale and equipment age
(Carlsson-Kanyama & Faist, 2000;Van Alfen, 2014). These factors could
have a large impact on SEC values obtained. Allocating SEC values for
multi-product activities was also particularly complex; as an example,
whey production shares processes with cheese making. To quantify SEC
values for whey production, some researchers included energy con-
sumed by those shared operations while others excluded them (Foster
et al., 2006).
Once the data set was collated, the following information was re-
corded: the date and location of the study, product description, pro-
cesses involved, energy sources, and bibliographic reference. Before
analysis, the data was sorted into the following groups: prior to 2000,
2000–2004, and 2005–2015, to account for changes in technologies,
processing and fuel efficiencies, and structural changes within the
sector. A large number of energy studies were conducted in the 1970's
and 1980's - Berry and Makino (1974);Beech (1980);Cleland, Earle,
and Boag (1981);Slesser and Wallace, (1982);Stanhill (1984);
Pimentel and Hall (1984);Cox and Miller (1986) - and it is noteworthy
that recent publications, such as Ramirez et al. (2006a),Van Alfen
(2014) or Xu et al. (2009), still report those figures due to the lack of
A. Ladha-Sabur, et al. Trends in Food Science & Technology 86 (2019) 270–280
271
more recent data. Average energy consumption values for processes and
products were only calculated when more than two replicates were
obtained from literature. Additionally, only energy expressed in its final
form was analysed as conversion efficiencies can vary. For example, the
efficiency of electricity production can differ based on the type of fuel,
the power plant capacity and the technology employed for production
(OECD, 2012). Finally, food products were clustered in seven cate-
gories: grains and oilseed milling, sugar and confectionary, fruit and
vegetable, dairy, bakery, meat and others - SEC values are shown in
Appendices A-G. Energy use figures organised by process are listed in
Appendix H, while transportation data is presented in Appendix I. All
the Appendices are available as Supplementary Data.
3. Energy consumption by product
Total energy consumption data in the literature was reported with
different combinations of energy sources. In some cases, the energy
source was not specified. Therefore, results are presented in three dif-
ferent formats to allow for comparison:
•Electricity and thermal energy
•Electricity, fuel and steam energy
•Total energy, source unspecified
Unless stated otherwise, all energy consumption figures in this work
do not include packaging.
3.1. Grains and oilseed milling - Appendix A
Apart from flour milling, energy consumption data in this sector was
very sparse. Between 2005 and 2015, an average of 0.42 MJ/kg of
electricity and 0.03 MJ/kg of fuel was reported for the milling process
(Appendix A). Rice required the least amount of energy and was quoted
to consume 0.43 MJ/kg in 2013. Data from multiple sources from 1975
to 1996 reported 66 MJ/kg was used for manufacture of breakfast
cereals (Appendix A), including grinding, milling, wetting, drying and
baking. Aguilera, Simpson, Welti-Chanes, Aguirre, and Barbosa-
Cánovas (2011) confirmed the findings on breakfast cereals and dis-
cussed milling of flour as an energy intensive process. Three milling
methods are commonly used: wet, semi-dry and dry. Dry milling is the
most energy efficient process while wet milling is energy intensive
(Arendt & Zannini, 2013). This suggests that the low SEC values ob-
tained from literature might be for dry milling.
3.2. Sugar and confectionery - Appendix B
SEC data for popular confectionery products like chocolates and
sweets is lacking. Average SEC values for the production of sugar from
beets and sugar cane are presented in Appendix B. No data prior to
2005 was found. The average fuel consumption appears to decrease
over time while slightly more electricity is used. As data shows, the
average total energy (6.90 MJ/kg) was higher than the sum of average
electricity and fuel use within the same time frame (3.26 MJ/kg). Sugar
extraction data from 1986 ranged from 2.3 to 26 MJ/kg.
In 2010, 160 million kg of sugar was produced globally, with 20%
produced from sugar beets. A Japanese sugar factory reported that 65%
of its thermal energy was used by the evaporative crystalliser. Melting
and centrifugal drying consumed 25% and 22% of total electricity, re-
spectively (The Energy Conservation Centre, 2016). However, this en-
ergy demand might be decreased by using multi-stage evaporation and
heat exchanger networks. An alternative energy-reduced sugar manu-
facturing process also exists: the juice purification step is removed and
evaporative crystallisation of sugar is replaced by cooling crystal-
lisation from concentrated raw juice (Klemes, 2013). Energy can also be
recovered by using biofuels like bagasse, the lignocellulose residue
obtained from sugar cane post extraction (Singh, 2013).
3.3. Fruits and vegetables - Appendix C
From data collected, potato-based products consumed the most
energy (Fig. 1). No data for crisps and French fries were found later
than 1998. These values, when compared to other products within the
same time frame, were significantly higher.
Drying potatoes consumes large amounts of energy due to the high
initial water content of the raw material (Wu, Tassou, Karayiannis, &
Jouhara, 2013). Crisps are dried until a 2% water content is achieved,
and since potato flakes have a lower final water content than French
fries, their production is much more energy intensive (Foster et al.,
2006). Single and double-drum dryers are typically used (Mujumdar,
2014) to dehydrate potato-based products. Increasing the drying air
temperature can increase the drying rate, however the product quality
might be damaged. The use of ultrasound to improve water mobility has
been proposed, with experimental results showing that the drying time
can be shortened by 40% compared to experiments where ultrasound
was not used (Ozuna, Cárcel, García-Pérez, & Mulet, 2011). The energy
consumed to produce vegetable oil was not included in any of the lit-
erature discussing these products. Energy studies on multi-ingredient
products were rarely found.
Fig. 1. Energy consumed to process fruits and vegetables (Source: Appendix C).
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272
3.4. Dairy - Appendix D
Dairy processing is considered one of the most energy intensive
sectors within the food industry (Briam et al., 2015). Many dairy pro-
ducts are manufactured by concentrating raw milk and separating so-
lids to varying degrees. Electricity is typically used for pumps, re-
frigeration, control and separation while thermal energy is employed
for cleaning, evaporation and pasteurisation (Xu & Flapper, 2011).
Daily cleaning-in-place (CIP) operations consume large amounts of
energy (Xu et al., 2009), since raw milk is highly perishable and strict
hygiene standards must be followed. Fig. 2 summarises the energy used
by dairy products, where concentrated milk includes evaporated and
condensed milk. Milk powder requires significantly more energy than
cheese, since both drying and evaporation steps are required (Ramirez
et al., 2006a). However, when SEC data reported as total consumption
values were analysed, cheese was the most energy intensive (13.85 MJ/
kg), followed by powdered milk (10.30 MJ/kg) (Appendix D). More
data for processed milk and cheese were found, perhaps due to the size
of the market and the milk quota system that resulted in close mon-
itoring of milk production in Europe (Ramirez et al., 2006a). On the
other hand, data for butter, cream, ice cream and yoghurt were scarce.
Milk pasteurisation can consume 17%–26% of the total energy (Van
Alfen, 2014). This process can be optimised by recovering 90%–94% of
heat input (Ramirez et al., 2006a). Ultra-high temperature (UHT) and
sterilisation processes are more energy intensive as higher temperatures
are required. Most data collected did not specify the type of treatment
employed to process the milk (Appendix D). For the production of milk
powder, the concentration and drying steps were the most energy in-
tensive, accounting for 45% and 51% of primary energy respectively
(Appendix E). Spray drying is the most common drying process used,
requiring 10 to 20 times more energy per kg of water evaporated
compared to drying using evaporators. To reduce energy use, eva-
porators are used to pre-concentrate prior to drying (Ramirez et al.,
2006a).
Compared to processed milk, cheese requires over nine times more
water, four times as much raw milk and electricity, and three times
more fuel (Foster et al., 2006). The energy required can vary
significantly depending on the type of cheese, process conditions, and
the plant age and size (Xu et al., 2009). Cheese typically needs to be
ripened in a controlled environment. If cheese needs to be ripened for
more than 14 days, this can increase the specific energy demand by
9–65% (Van Alfen, 2014).
Differences in raw material and final product characteristics, pro-
cesses involved and operating conditions can affect the energy con-
sumed by dairy products. For example, cheese plants may supply liquid
whey that needs further concentration prior to drying (Xu & Flapper,
2011). Additionally, soya milk is produced using soybeans and requires
significantly more processing than cow's milk such as peeling, grinding,
filtering, adding sugar and flavours (Foster et al., 2006). Dairy in-
dustries in Canada, Norway, the Netherlands and the United States use
heat pumps to reduce energy use in processes like pasteurisation, eva-
poration and drying.
The dairy processing industry needs more tools and programs to
reduce energy demands. However, many dairy organisations may not
have the resources to undertake thorough assessments that would
hasten energy reductions in this sector (Xu & Flapper, 2011).
3.5. Bakery - Appendix E
Energy studies in this sector focused on baking and bread manu-
facturing. The average SEC value obtained was 5.21 MJ/kg (Appendix
E). Less than 1% of bread in the UK is imported, and it is regularly
consumed by 96% of the population. Three quarters of sold bakery
goods are produced by large-scale plant bakeries, and the remainder is
made by smaller in-store and craft bakeries (Foster et al., 2006).
However, bakeries can consume twice as much energy as large bread
factories (Braschkat et al., 2003).
A US study conducted by Therkelsen et al. (2014) was used to
compare bread production to other bakery goods. Four products un-
dergoing similar processes were examined, and average SEC for each
product reported. Baking and freezing constituted the most energy
demanding steps (see Fig. 3), while biscuits, breads and rolls required
longer baking times than cakes and pies - their SEC values were
therefore higher than the 2.50 MJ/kg consumed by cakes (Fig. 3).
Fig. 2. Average final electricity and fuel energy consumed to produce dairy products (Source: Appendix D).
A. Ladha-Sabur, et al. Trends in Food Science & Technology 86 (2019) 270–280
273
Energy intensity of baking processes is related to the low values of
convective heat transfer coefficients through air (approx. 30 W/m
2
K)
(page 508, Klemes et al., 2008). Direct-fired natural gas ovens are often
used, although electric ovens appear to be more efficient (page 508,
Klemes et al., 2008). In continuous gas fired ovens, large amounts of
heat are dissipated through exhaust gases (page 508, Klemes et al.,
2008). Such percentages can vary significantly depending on the op-
erating conditions, which suggest ovens can be optimised to increase
Fig. 3. Energy consumed to produce bakery products (Adapted from: Therkelsen et al., 2014).
Fig. 4. Average primary SEC values for meat processing (Source: Appendix F).
A. Ladha-Sabur, et al. Trends in Food Science & Technology 86 (2019) 270–280
274
energy efficiency (Khatir, Paton, Thompson, Kapur, & Toropov, 2013;
Therdthai, Zhou, & Adamczak, 2002), e.g. by recirculating part of the
oven exhaust gas. However, this should be done without impeding the
product safety and quality. Large amounts of hot water and steam are
also consumed in baking plants. Steam is used for temperature and
humidity control in fermentation boxes and rooms, and cleaning
equipment. Boiler systems can be optimised using different measures
such as proper sizing and process control.
3.6. Meat and fish - Appendix F
In 2001, the UK meat sector consumed 32 petajoules (PJ) of primary
energy. UK electricity usage increased by 2.9% annually from 1990 to
2001 from increased demands for refrigeration and motor drive power
(Ramirez, Patel, & Blok, 2006b). An increase in the consumption of
poultry and processed meat products has been observed also in Europe -
9% rise from 2007 to 2014 according to (Marquer, Rabade, & Forti,
2015). Processes that use large proportions of electricity and fuels in
different meat sectors were reported by Ramirez et al. (2006b): poultry
slaughtering consumes more energy than other meats due to hair and
feather removal, and singeing operations. An increase in the use of
automated equipment, temperature control and hot cleaning water has
raised energy consumption in slaughterhouses.
Meat products are frozen, cut and deboned more often to provide
convenient products for consumers. These processes are compared in
Fig. 4. There was a lack of SEC data in this sector so primary energies
were employed. Final energy values could not be calculated as the study
was carried out in different countries.
Typically, meat frozen products consumed more energy than chilled
ones (Fig. 4). Poultry products were the most energy intensive while
beef, veal and sheep were the least. Greater refrigeration requirements
and higher temperatures during hard scalding make poultry products
more energy demanding. Conversely, to produce 1 kg of broiler meat,
poultry feeding requirements are 3.1 kg of dry matter feed, compared to
6.3 kg for pigs and 24 kg for beef cattle (Ramirez et al., 2006b). Vacuum
packed and ready-to-eat products are also raising energy use. As this
sector is largely influenced by consumer preferences, they must be
considered when analysing energy consumption to better understand
the progress made in energy efficiency. Also, life-cycle studies rarely
focus on meat processing, as stated by Roy et al. (2009).
Energy studies on seafood processing were scarce. Average SEC
values for fish processing were 0.38 MJ/kg electricity and 1.87 MJ/kg
fuel (Appendix F), although the accuracy of the analysis is uncertain
due to the limited data found.
3.7. Others - Appendix G
Coffee was the most energy intensive product in this category. The
UK, with a preference for medium roasted and instant coffee (Chanakya
& De Alwis, 2004), consumes approximately 95 millions of coffee cups
per day (The Bristish Coffee Association, 2018). Coffee beans, obtained
from primary processing, are sent for secondary processing, which in-
cludes dehulling, roasting and grinding. Roasted coffee consumes an
additional 0.4 MJ/kg of electricity and fuel compared to non-roasted
coffee (Wang, 2014). A continuous roaster consumes approximately
0.5 MJ/kg green coffee compared to a batch roaster that uses 1.84 MJ/
kg (Okada, Rao, Lima, & Torloni, 1980). While these energy figures do
not appear significant, data collected in 2013 reported a total of
23.24 MJ/kg for the processing of coffee (Lillywhite, Sarrouy,
Davidson, May, & Plackett, 2013). Instant coffee, produced from ter-
tiary processing, consumed 2.70 MJ/kg of electricity and 45 MJ/kg of
fuel in 1980 (Cleland et al., 1981), while a more recent study
(Morawicki & Hager, 2014) reported 8.3 MJ/kg of electricity and
30.2 MJ/kg of fuel. Processing coffee requires a much larger quantity of
thermal energy compared to electricity. The thermal energy used by
each unit operation to produce instant coffee as reported by (Okada
et al., 1980) is shown in Table 1. Instant coffee is more energy intensive
due to the spray drying process. Freeze-drying is also used for instant
coffee production and it can consume 0.42 MJ/kg to freeze and as much
as 31 MJ/kg to dry (Appendix H). A combined microwave-hot air
spouted bed was recently explored as a novel drying method and pro-
duced good quality coffee (Jindarat et al., 2014). Developing good
flavour is crucial in the coffee industry, however, energy reductions
must be made during the extraction, concentration and drying steps.
4. Transportation
Most of the research found focused on the transportation of un-
processed goods. Centralised and local food systems were also often
compared to determine the validity of food miles. While reducing food
miles lowers transport-related energy consumption, Carlsson-Kanyama
(1998) showed that food miles may be irrelevant, in that farm-gate
emissions for the production, storage and transportation of tomatoes
from Israel to Sweden were lower than those for local production in UK
glasshouses. According to this, the supply chain might be better eval-
uated as a whole. Tassou, De-Lille, and Ge (2009) summarised the
average energy consumed at different stages of food distribution in the
UK. Articulated vehicles (32t to 44t) are typically used for primary and
secondary distribution, and account for 80% of the tkm of all good
movements in the UK. Rigid vehicles up to 32t transport goods in ter-
tiary distribution and are the most energy intensive. Mixed temperature
distribution is energy intensive as heat transfer between different
compartments must be controlled. Additionally, refrigeration systems
must be designed to minimise disruptions from activities like loading
products and opening doors (Tassou et al., 2009).
The energy consumed during temperature-controlled distribution
varied with the distance, type of vehicle, distribution, and product
(chilled or frozen). While a higher temperature difference is needed for
frozen products, chilled foods can consume more energy. Higher air
flows are needed for uniform temperature distribution, products respire
and temperature control requirements are tougher. The varied en-
vironmental conditions and vibrations from the road were also found to
result in higher emissions for transportation refrigeration systems
compared to stationary systems. As major retailers in the UK are
making more home deliveries and quality expectations are increasing,
light vehicle refrigerated transportation must be optimised (Tassou
et al., 2009). More than 98% of all foods within the UK are transported
by road. Regional distribution centres (RDCs) are therefore often lo-
cated next to a motorway (Jones, 2002).
Data corresponding to energy intensity of road transportation
alongside other common modes of transport can be found in Van
Hauwermeiren, Coene, Engelen, and Mathijs (2007). According to this
source, air transportation was the most energy intensive while inland
bulk transportation by vessel was the least. The transportation distance
was also compared to model transportation between neighbouring
countries, continental and international transport. Transportation by
electric freight train was more energy intensive than by truck, however,
SEC values are dependent on factors like the transportation speed, load
factor and weather condition (Van Hauwermeiren et al., 2007).
Transportation to and from the loading points was not included.
The energy use of railroad transportation has decreased significantly
Table 1
Thermal energy required to produce instant coffee (Adapted from: Okada et al.,
1980).
Process Units Thermal energy
Roasting MJ/kg product
∗
3.73
Extraction MJ/kg product
∗
8.50
Concentration MJ/kg product
∗
7.45
Spray drying MJ/kg product
∗
21.10
∗
Instant coffee.
A. Ladha-Sabur, et al. Trends in Food Science & Technology 86 (2019) 270–280
275
over the years. Road freight vehicles are now considered more energy
intensive, and the number of electric freight trains in the EU is rising.
GHG emissions are lowered by the reduction of road traffic and the use
of electric powered vehicles (Gazzard, 2014).
5. UK energy consumption trends
Consumer preferences and regulations have influenced the energy
requirements, structure and level of concentration of the UK processing
industry. For example, through market reform, the number of sugar
factories in Europe has decreased and the processing capacity of beets
has increased. The UK is one of the top producers of sugar beet, growing
around 8 million tonnes per year (British Sugar, 2018). As beets have a
water content of 75% by mass, significant amounts of energy are
needed to produce dry crystalline sugar (Appendix B).
Potatoes are important vegetables in the UK food market and ap-
proximately 6 million tonnes are processed each year (Foster et al.,
2006). As previously mentioned, drying potatoes is energy intensive. In
terms of dairy products, cheese is the second most consumed product
after milk, particularly cheddar, and cheese production continues to
increase (Foster et al., 2006). In 2000, 30% of the net fuel use in the UK
dairy processing sector was consumed by drying and concentration
processes (Ramirez et al., 2006a). The UK sector was less energy in-
tensive in 2005 compared to Netherlands, Denmark and Norway, par-
tially due to a lower production of energy-intensive products. However,
UK GHGEs were the highest, probably due to different shares of energy
sources (Xu et al., 2009).
In the 2017, energy used in food processing was mainly obtained
from natural gas (58%) and electricity (34%) (Department for Business,
Energy and Industrial Strategy, 2018a), accounting petroleum and coal
for the rest.
The relationship between the energy density, the weekly UK con-
sumption and processing energy use for different products were com-
pared in Fig. 5 and Fig. 6. Consumption data were obtained from
DEFRA (2015) and average energy densities were calculated from a
nutrient database produced by the US Department of Agriculture
(USDA, 2016). There were no clear trends between the variables, al-
though this may be due to a lack of data for diverse products. The
modern diet in developed countries consists of more energy-dense foods
that can prompt weight gain. Food processing can increase the energy
density as the water and fibre content are often reduced. The addition
of sugar, fat and salt can enhance palatability, which may lead to
overconsumption (Webb, 2012) and non-communicable diseases
(Augustin et al., 2016) like diabetes. Relatively large volumes of soft
drinks are consumed (Fig. 6), which are energy dense due to the high
sugar content (Bagchi, 2010). Processed foods with low nutritional
value are not considered part of a sustainable diet according to the Food
and Agriculture Organisation of the United Nations, although they may
have lower associated GHGEs (Drewnowski et al., 2014). Approxi-
mately 25% of adults and 20% of children in the UK are obese, and
reducing the energy density of processed foods could have an impact on
lowering these figures (Cunningham & Harney, 2012).
6. Discussion and remarks
6.1. Limitations of the study
Identifying energy consumption trends is difficult as the food pro-
cessing industry is very fragmented, products are processed to varying
degrees and production is not always continuous (Preface, Klemes et al.,
2008).
This survey has collated data that gives a better understanding of
energy consumption across different food processing sectors. While the
accuracy of reported data could not be determined, i.e. error mea-
surements or uncertainties are rarely reported in energy accounting
studies (Paoli, Lupton, & Cullen, 2018), general trends in processing can
be identified as well as hot spots. There is a lack of comprehensive and
up to date data, and many recent sources still reported dated figures.
Estimation and reporting of energy consumption data did not follow a
standard methodology, and there were large variations in the estimated
energy used for the same food products or processes. Consequently, SEC
values could only be assigned to general food groups rather than spe-
cific food products. In addition, some energy studies quantified energy
consumed by individual plants, however a wide range of SEC values
were often reported due to differences in product mixes and equipment
condition. The level of capacity utilisation would also affect the SEC
values assigned to products (Ramirez et al., 2006a). To ease future in-
vestigations and increase the level of accuracy, standardised accounting
methods for energy use during food processing that include estimation
and propagation of uncertainty must be developed. Paoli et al. (2018)
Fig. 5. The energy density, UK consumption and final processing energy use (as end use energy consumption) of solid food products. The sizes of the circles represent
the energy densities.
A. Ladha-Sabur, et al. Trends in Food Science & Technology 86 (2019) 270–280
276
has allocated a 25% uncertainty to useful energy demand of the UK
industrial sector – this needs to be broken down for the food industry
sector.
No account has been taken on the fuel mix for energy generation.
This can vary widely between countries: Swedish electricity is almost
entirely generated through hydropower and nuclear energy (Foster
et al., 2006). In contrast, the UK food manufacturing sector heavily
relies on fossil fuels – natural gas accounts for 58% of energy consumed
in 2017, with coal and petroleum representing a 6% (Department for
Business, Energy and Industrial Strategy, 2018a) - and in consequence it
generates more GHGEs (a total of 23 Mt CO
2
e in 2015 (DEFRA, 2018a)).
Figs. 2, 3 and 5 also reflect this strong dependency on fossil fuels. While
more energy intensive activities may not necessarily result in higher
levels of GHGEs, effective energy management is also important to re-
duce costs and alleviate risks associated with changes in energy prices
and supply shortages (Briam et al., 2015).
Little data has been found on ready-to-eat meals that are increas-
ingly popular and typically need to be cooked, preserved, and chilled or
frozen (Pardo & Zufía, 2012). The meat industry produces a wide
variety of products, however a detailed analysis was not possible due to
the lack of data. While some data was available for meat and poultry,
little data on seafood products was found. Similarly, food products
within the grain and oilseed milling, and sugar and confectionery ca-
tegories were difficult to find. To better understand how resources are
used in the food processing industry, more support is needed from
producers to allow site-specific data to be obtained (Andersson,
Ohlsson, & Olsson, 1998). The energy consumed to manufacture more
complex meals also needs to be quantified.
6.2. Phase change processes
Thermal processes are energy intensive and responsible for a large
proportion of the energy consumed in food processing. According to
Klemes et al. (2008), p. 140, the US food and drink industry consumes
647 PJ for process heating and 73 PJ for refrigeration. In the UK, it has
been estimated that about 68% of the energy is used for process and
space heating, 8% is electric heating and 6% corresponds to refrigera-
tion (AEA Energy and Environment, 2007). Heat is extensively used in
heat preservation techniques (i.e. sterilisation and pasteurisation, see
Appendix H).
Many other food thermal processes require first the addition of
water to the product followed by its removal, which usually involves a
phase change. For example, baking, drying and freeze-drying are en-
ergy intensive (see Appendix H) operations due to the high latent heat
of vaporisation and sublimation of water present in the raw material or
added in during processing (freeze-drying involves both phase
changes). Consequently, products that are freeze-dried - like instant
coffee (average of 50.20 MJ/kg, Appendix H) or milk powder (average
of 16.22 MJ/kg, Appendix E) - or dried - such as French fries (average of
15.16 MJ/kg, Appendix D) and crisps (average of 17.30 MJ/kg,
Appendix D) - consume significant amounts of energy. The thermal
efficiency of industrial dryers is also low, so large amounts of energy are
wasted (Wang, 2008). Commonly this energy is supplied by fossil fuels
rather than electricity, as indicated in Fig. 1. Although electricity and
gas show very similar high performance in terms of efficiency and
flexibility of use, the lower price of gas might explain its preferred use -
average prices of 1.8 pence/kWh and 8.3 pence/kWh for gas and
electricity, respectively in 2017 as reported by the UK Department for
Business, Energy and Industrial Strategy (2018b).
6.3. Energy - efficient processes
Energy reductions can be made through process optimisation,
technological and manufacturing behavioural changes (Tassou et al.,
2014). The food industry could use methodologies employed in other
industries like pinch analysis, where minimum process heating and
cooling needs are determined prior to design (Ahmed & Rahman,
2012). An example of the potential reductions of this approach is given
in Walmsley, Atkins, Walmsley, Philipp, and Peesel (2018), where
savings up to 51% in thermal energy were estimated for production of
milk powder. However, small food producers and processors are im-
plementing energy optimisation strategies at a slower rate than their
counterparts in other similarly sized industries (page 144, Klemes et al.,
2008). For example, ca. 2300 small and medium sized enterprises
produce bakery products in the UK (DEFRA, 2018b), and producing at a
smaller scale is more energy intensive. Baking accounts for the majority
Fig. 6. The energy density, UK consumption and processing energy use (as end use energy consumption) of liquid food products. The sizes of the circles represent the
energy density.
A. Ladha-Sabur, et al. Trends in Food Science & Technology 86 (2019) 270–280
277
of the energy consumed in this sector, and direct-fired natural gas ovens
are still popular. Replacing them with electric ovens could help to re-
duce energy use. A rise in hygiene standards and cleaning requirements
has increased energy use in the dairy and meat processing sectors. The
dairy industry continues to be energy intensive due to the thermal
processes employed to ensure microbial safety, however the use of
falling film evaporators, heat recovery systems (Ramirez et al., 2006a)
or process integration and optimisation (Fritzson & Berntsson, 2006)
can significantly reduce energy demand.
More energy efficient process technologies can also provide energy
savings. For example, supercritical extraction can replace concentration
through boiling (Fellows, 2009), the use of membrane filtration
(Ramirez et al., 2006a) can increase efficiency of dairy processes and
osmotic pre-treatments can help to decrease the heating loads and times
in drying processes (Prosapio & Norton, 2017). Emerging technologies,
e.g. high pressure processing (HPP) (Juliano et al., 2012), ohmic (OH)
(Barba et al., 2016) or microwave heating (MWH) (Jindarat et al.,
2014), might increase the efficiency of food processes, while reducing
the use of non-renewable resources (Barba et al., 2016). Their wide-
scale application in the industry is limited by investment costs (Barba
et al., 2016;Jermann, Koutchma, Margas, Leadley, & Ros-Polski, 2015),
although they are slowly replacing and complementing conventional
preservation technologies (Barba et al., 2016). For instance, microwave
is used for drying, thawing or pasteurising (Barba et al., 2016;Atuonwu
et al., 2018), an it is used as part of hybrid processing technologies too,
e.g. or microwave -assisted freezing (Xanthakis et al., 2018, pp.
176–181). Non-thermal processes, like HPP, typically need less water
and heat and could have a lower environmental impact (Atuonwu et al.,
2018). Furthermore, the required energy source is electricity that could
be generated from renewable resources, like biomass from food wastes
(Pardo & Zufía, 2012). According to Jermann et al. (2015), ultraviolet
light (UV) (Koutchma, Popović, Ros-Polski, & Popielarz, 2016), MWH
and HPP technologies have the greatest commercialisation potential.
On-going research focuses on reaching a complete understanding of
process conditions and adapting HPP microbial safety protocols.
6.4. Decentralised food chains – distributed food manufacture
Energy is intensively used both for manufacture and product
transport to the consumer. However, it might be possible to balance the
intensity of the most energy demanding processes by decreasing the
energy use at the transportation stage. For example, manufacturing of
convenience food typically requires more energy, but it could reduce
energy demand for storage and preparation in the retail and residential
sector. Dried food products are also lighter to transport and their shelf
life is extended, sometimes without the need of refrigeration (Ramirez
et al., 2006b), e.g. transport of tea bags is more efficient than transport
of bottled water. Distributed manufacture methods, in which only va-
luable ingredients are transported and other ingredients added later at
the local level may lead to more energy efficient food chains (Roos
et al., 2016). Such use of distributed manufacture will create entirely
new decentralised food supply chains. In this decentralised food man-
ufacture paradigm, techno-economic assessment tools are needed to
decide which processes are the most efficient ones (Almena, Lopez-
Quiroga, Theodoropoulos, Fryer, & Bakalis, 2017). LCA studies that
evaluate the whole food chain will also be critical to understand how
specific processes can impact other stages of the life cycle.
6.5. Future challenges
In addition to the environmental impact, the current global food
system also creates socio-economic challenges such as market distor-
tions and a dependence on food imports. However, the implications of
creating a more decentralised/localised food supply system also need to
be assessed (Almena et al., 2017). Findings that could improve the
sustainability of the food system must reach a wider audience,
including consumers and policy-makers, to allow concerned individuals
to make more informed decisions. Recently, France has adopted a food
labelling system, Nutri-Score (Santé Publique France, 2018) that allows
consumers to compare nutritional characteristics in a standardised
basis. A similar approach to energy efficiency labelling might be
adopted in foods, aiding in the lifestyle changes needed to reduce en-
ergy use in the food industry. To make this possible, a greater colla-
borative effort is needed to report energy use data not only at proces-
sing stages but all across the food chain. Policies defining standard
accounting basis must be developed to this purpose.
7. Conclusions
Energy demand quantification during food manufacturing and dis-
tribution is key to identify intensive activities, providing useful in-
formation for policy and industry decision makers. By targeting those
processes that represent a hot spot (such as those involving phase
changes) significant reductions on the sector energy consumption can
be achieved.
Despite the variability on the energy demand figures for different
products and processes available in the consulted sources, a database of
energy consumption has been created from literature (Appendices
available as Additional Material) and general trends on consumption
due to manufacturing and transportation methods have been identified,
paying special attention to the UK food system. The most energy in-
tensive food products are powders (i.e. instant coffee and milk powder),
fried goods (i.e. French fries and crisps) and bread, all involving
thermal processes such freeze-drying or drying in their manufacture; in
addition, hygienic and cleaning requirements are the main sources of
water consumption and waste in the meat and dairy industries.
In terms of transportation, current trends point towards more de-
centralised/distributed supply systems and to local production.
However, the environmental benefits of these changes are not always
clear. Global environmental assessment tools (such LCA, carbon and
water footprint) that take the whole food chain into consideration will
be increasingly important.
Overall, it is necessary to standardise reported consumption data
across the sector and policy efforts must be devoted to this task ur-
gently. Only then will it be possible to develop efficient strategies to
optimise the whole food system, allocate resources more effectively and
reduce both waste and fossil fuel dependency.
Acknowledgments
Authors acknowledge financial support received from the RCUK
Centre for Sustainable Energy Use in Food Chains (EPSRC grant no. EP/
K011820/1).
Supplementary data
Supplementary data to this article (Appendices A–I) can be found
online at https://doi.org/10.1016/j.tifs.2019.02.034.
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