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TYPE Original Research
PUBLISHED 11 January 2023
DOI 10.3389/frsus.2022.1051091
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EDITED BY
George Tsalidis,
Delft University of
Technology, Netherlands
REVIEWED BY
Enrica Vesce,
University of Turin, Italy
Teresa Maria Gulotta,
University of Messina, Italy
*CORRESPONDENCE
Henrik Haller
Henrik.haller@miun.se
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Frontiers in Sustainability
RECEIVED 22 September 2022
ACCEPTED 19 December 2022
PUBLISHED 11 January 2023
CITATION
Elnour M, Haller H and Martin M (2023)
Life cycle assessment of a retail store
aquaponic system in a cold-weather
region. Front. Sustain. 3:1051091.
doi: 10.3389/frsus.2022.1051091
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Life cycle assessment of a retail
store aquaponic system in a
cold-weather region
Mugahid Elnour1, Henrik Haller1*and Michael Martin2,3
1Department of Ecotechnology and Sustainable Building Engineering, Mid Sweden University,
Sundsvall, Sweden, 2Division of Life Cycle Management, Department of Sustainable Society, IVL
Swedish Environmental Research Institute, Stockholm, Sweden, 3Department of Sustainable
Development, Environmental Science and Engineering, KTH Royal Institute of Technology,
Stockholm, Sweden
Alternative food production technologies are being developed to meet the
global increase in population and demand for a more sustainable food supply.
Aquaponics, a combined method of vegetable and fish production, is an
emerging technology that is widely regarded as sustainable. Yet, there has
been limited research on its environmental performance, especially at a
commercial scale. In this study, life cycle analysis (LCA) was used to assess the
environmental impacts of food produced by an urban commercial aquaponic
system located next to a retail store in a cold-weather region (Östersund,
Sweden). The functional unit (FU) used is 1 kg of fresh produce, which includes
cucumber (Cucumis sativus), tomatoes (Solanum Lycopersicum), and Atlantic
salmon (Salmo salar). The system boundary is set from cradle to farm or
retailer’s gate due to the proximity of the aquaponic system to the retail
store. Results were reported employing eight environmental impact categories,
including global warming potential (GWP), marine eutrophication (MEU), and
cumulative energy demand (CED). According to contribution analysis, the main
hotspots of the system are electricity, CO2enrichment, and heating. Potential
areas to mitigate the impact of these parameters were highlighted in this
study, including the establishment of symbiotic links to utilize urban waste and
by-products. The impact per vegetable or fish produced was partitioned using
energy and economic allocation and compared to other common cultivation
methods. The yearly harvest from the aquaponic system was also compared
to importing these food items from other European countries which showed
lower annual greenhouse gas (GHG) emissions for the aquaponic system.
KEYWORDS
aquaponic system, environmental impacts, life cycle assessment, urban farming, food
production, cold climate agriculture
1. Introduction
The world’s population is expected to reach 9.7 billion by 2050, with cities housing an
additional 2.5 billion people (UN, 2014). Food demand is estimated to rise by 70% over
the same period, putting an additional burden on production systems (Linehan et al.,
2012). Major environmental impacts, such as climate change, water pollution, and land
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Elnour et al. 10.3389/frsus.2022.1051091
use, are directly linked to food production and distribution
(Willett et al., 2019;Delshad, 2022). Farms are responsible for
the majority of this impact since they are the physical source of
production (McAuliffe et al., 2020). Alternative food production
systems have been developed to meet the growing demand
for food items while trying to reduce the negative impact of
conventional farming (Breitenstein and Hicks, 2022). To address
the challenge of sustainable food production, it is important
to understand the extent of environmental impacts related to
these systems in order to make an informed decision about
their application.
Aquaponics is an emerging food production technology
that is being promoted as a sustainable method for growing
both aquatic animals and plants (König et al., 2018;Goddek
et al., 2019;Greenfeld et al., 2022). The system combines
recirculating aquaculture systems (RAS) with hydroponics for
optimized nutrient and water fluxes between the two units
(Proksch and Ianchenko, 2019). As the fish consume fish
feed, they produce waste, which is employed as a fertilizer
that the plants can absorb. The plants serve as a water filter
by absorbing these nutrients, and the water is recycled back
to the fish tank. As a result, aquaponic systems typically
use fewer pesticides, herbicides, or other harsh chemicals
(Farhan, 2021;Greenfeld et al., 2022). The synergy between
aquaculture and hydroponics in these systems has been reported
to reduce energy use (Körner et al., 2017), water consumption
(Cohen et al., 2018;Goddek et al., 2019), and lower the
overall environmental impacts of food products as opposed
to conventional farming (Yacout et al., 2016;Jaeger et al.,
2019).
Aquaponic systems can also play a major role in enabling the
local production of food items in cities. This provides the urban
population with access to high-quality fresh products while
supporting cities to become self-sufficient (Llorach Massana,
2017;Goddek et al., 2019). Urban aquaponics are also able
to establish relationships with local businesses to exchange
resources for mutual benefits through urban and industrial
symbiosis, which can help reduce the overall impact and
improves resource efficiency (Martin and Harris, 2018;Parker
and Svantemark, 2019). Additionally, by reducing the distance
that food needs to travel (food miles), urban farming can
lessen the impacts of transportation, packaging, storage, and
food wasted during these processes (De Bon et al., 2010;
dos Santos, 2016). However, many authors have argued that
reducing food miles is not an effective measure of food
sustainability due to its small impact compared to production
systems (Edwards-Jones et al., 2008;Coley et al., 2009;Ziegler
et al., 2013;Heller, 2017). Heller (2017) emphasized the
need for research to evaluate regional variations in food
production as well as possible trade-offs in transportation as an
appropriate approach to mitigating the environmental impacts
of food.
Despite the growing scientific knowledge on agri-food
systems, there has been limited research that focuses on the
environmental implications of aquaponics (Wu et al., 2019;
Greenfeld et al., 2022). To the best of the authors’ knowledge,
there are a total of 23 studies published that performed
LCA on aquaponic systems between 2014 and 2022. The
majority of these studies were conducted on small or pilot-
scale research systems (e.g., Hindelang et al., 2014;Gennotte
et al., 2017;Verdoodt, 2019;Chen et al., 2020;Bhakar et al.,
2021), theoretical systems (Forchino et al., 2017;Cohen et al.,
2018;Körner et al., 2021), and only five were based on large-
scale commercial aquaponics (Boxman, 2015;Thorarinsdottir,
2015;Boxman et al., 2016;Hollmann, 2017;Greenfeld et al.,
2021). Greenfeld et al. (2022) highlighted the importance of
quantifying the impact of large-scale commercial aquaponics as
a way to inform policymakers and justify public support. The
impact of food production can be greatly influenced by climate
conditions. Cold-climate countries have lower temperatures
and shorter daylight hours, resulting in aquaponics requiring
more energy to operate, which can significantly increase their
environmental impacts (Valappil, 2021). While several studies
have been conducted on cold-weather aquaponics (Cohen
et al., 2018;Ghamkhar et al., 2020,2022;Körner et al.,
2021;Valappil, 2021), they are based on theoretical or small-
scale applications.
In terms of produce, most LCA studies of aquaponic systems
have focused on similar types of fish (e.g., tilapia, rainbow trout,
or ornamental fish), but no studies on salmon production were
identified. This can be attributed to the fact that salmon is
a cold-water fish and is challenging to raise in warm regions
(Brooke, 2019;Tennøy, 2022). Leafy greens (including lettuce,
basil, and kale) are the predominantly researched vegetables
from the hydroponic units of aquaponic systems. Despite
tomato and cucumber being commonly grown vegetables in
aquaponics according to surveys [about 69%, 42% based on an
international survey and 32%, 16% based on a European survey
respectively (Love et al., 2014;Villarroel et al., 2016)], there have
been relatively few studies that assessed their environmental
performance (Hindelang et al., 2014;Thorarinsdottir, 2015;
Körner et al., 2021).
In this study, LCA was used to quantify the environmental
impacts of an urban commercial-scale, cold-weather aquaponic
system (Östersund, Sweden), which cultivates cucumber,
tomato, and salmon. A total of eight environmental impact
categories were used to provide a holistic view of the
environmental performance of the system, identify major
contributing parameters, and highlight potential mitigation
strategies for these impacts. The results from the aquaponic
system’s produce were compared with other production systems.
A comparison was also made for the global warming trade-offs
between the urban aquaponic system and food imported from
other European countries.
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2. Materials and methods
2.1. System description
The aquaponic system assessed in this study is based
on a commercial system called “Complete” developed by
the company Agtira AB. This study focuses on Agtira’s
first Complete system, which was under construction at the
time of this study. The aquaponic system is considered one
of the largest facilities in the world for combined salmon
and vegetable production in an urban environment (Svedin,
2021). The system is roughly 1,200 m2in area and is
located in the parking lot of ICA Maxi supermarket in
Östersund. Due to the proximity in location, the cultivated
food can be sold in the retail store hours after harvest. The
aquaponic system is designed to produce roughly 75 tons
of cucumbers, 15 tons of tomatoes, and 8 tons of Atlantic
salmon annually.
2.2. Goal and scope definition
The main purpose of this study was to assess the
environmental impacts of a commercial-scale urban aquaponic
system located in northern Sweden. The functional unit (FU)
used for the study is 1 kg of fresh produce. This FU was chosen
as the system is designed to produce three key products (salmon,
tomato, and cucumbers) all of equal importance. To calculate
the impacts of each these products, two allocation methods were
employed to partition the impacts of the system. The time scale
is set for food produced from the aquaponic system over a period
of 1 year.
2.2.1. System boundary
The system boundaries, i.e., which processes are to be
included or omitted, are set from cradle-to-gate (ISO, 2006).
This can be considered as the farm or retailer’s gate due to
the proximity in locations of the two systems. The impact
evaluation thus includes the production side of the food value
chain including input materials, transportation, energy use, and
infrastructure as shown in Figure 1. Waste from the aquaponics
system was excluded from the scope of the study due to a lack
of data.
2.2.2. Allocation
Allocation, i.e., the process of partitioning the share of the
environmental impact of a unit or process to the system under
study, was used to calculate how much impact is contributed by
each crop and fish produced (Lee and Inaba, 2004). The choice
of allocation method, however, can largely influence the results.
According to ISO 14044 standards, allocation should be used
based on physical relations between the different products (e.g.,
TABLE 1 Allocation factors based on the two allocation methods.
Products Allocation factor (%)
Energy Economic
Cucumber 38 96
Tomato 9 2
Salmon 53 2
energy), or other relations including their economic value (ISO,
2006).
Due to the sensitivity of the results to the method chosen,
two methods were considered for this study (energy and
economic allocation) in order to show their influence on the
results. Using multiple methods also helps in reflecting the
relationship between the different products in the system from
multiple perspectives. Table 1 shows the allocation factor for the
three products grown in the aquaponic system studied. Data for
the cost of products in Sweden in 2022 was retrieved from Selina
Wamucii (2022), while data for food energy content is based on
the USDA database (USDA, 2019).
2.3. Life cycle inventory
The fish are grown in a hatchery and transported to the
aquaponic system with an average size of approximately 100
g/fish. A hatchery process was created based on inventory data
from Song et al. (2019) for Chinese salmon production adjusted
to represent a Swedish hatchery condition (e.g., electricity source
and transportation). Fish feed was modeled based on data from
Jaeger et al. (2019). Plants are also purchased and brought to the
farm as seedlings with an assumed weight of about 95 g/plant
(Klapwijk and De Lint, 1974). Transportation for input plants
and fish as well as fish feed are conducted employing trucks, with
a total transportation distance of 1,034 km.
CO2is supplied to the system for carbon enrichment, as CO2
is required for plant growth during the day. The source of CO2
is a by-product of industrial processes and is transported in a
liquid form at about 545 km. Data for liquid CO2production
was taken from Ecoinvent and accounts for processes such
as purification and liquefaction of the gas (Ecoinvent, 2019).
Most nutrients needed for plant fertilization come from the fish
tank, with a small amount of external nutrients added to the
system due to deficiencies in some micro and macronutrients.
This was assumed based on Davis et al. (2011) and Lall and
Kaushik (2021), considering 10% of the amount typically used
by aquaculture or hydroponic systems (Agtira, 2022).
Water is recycled inside the system and used for plant
growth with an average daily usage of about 4,000 liters. District
heating is used to maintain an adequate indoor temperature.
Calculations for district heating were assumed based on Davis
et al. (2011) for the amount of heating needed for tomato and
cucumber production in Swedish greenhouses.
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FIGURE 1
Product system and system boundaries.
Lighting is a major component of the aquaponic system
and consumes more than 90% of the electricity used. Due
to limitations in the databases for ready-to-use electric
components, an LED process was created based on data from
Casamayor et al. (2018). Other assumptions were also made
for comparable products in the database, including oxygen
generators and greenhouse fans. Sensors and actuators were
excluded from the study due to a lack of data. Transportation of
materials used for infrastructure is assumed to be included in the
Ecoinvent database, i.e., the “market for” datasets (Ecoinvent,
2019). Waste from the system and plant residues are partly
reintroduced to the greenhouse, with other waste streams treated
as biowaste. This process is excluded from the scope of the study
due to a lack of data. Table 2 shows the inventory data including
all the processes and materials used for the impact assessment.
2.4. Life cycle impact assessment
2.4.1. Impact categories
SimaPro version 5.19.1.0.8 was used to model the life cycle
inventory data and calculate impact results (PRé Sustainability,
2020). The software is a comprehensive LCA tool capable of
simulating different systems including agricultural ones. Life
cycle impact analysis results were calculated using the ReCiPe
2016 methodology. This method was considered suitable for the
European context and most appropriate for LCA in the food
sector by Amani and Schiefer (2011). This is due to its extensive
quantitative assessment for all impact categories including 18
midpoint and three endpoint results (Amani and Schiefer, 2011).
Seven impact categories were analyzed and included in this
study considering their appropriateness for food production
systems. These categories are (abbreviation, unit) global
warming (GWP, kg CO2-eq), terrestrial acidification (TAC, kg
SO2-eq), freshwater eutrophication (FWEU, kg P-eq), marine
eutrophication (MEU, kg N-eq), fossil depletion (FD, kg oil-
eq), water consumption (WC, m3), and ecotoxicity (EC, kg
1.4-DCB). The ecotoxicity category includes the impact of
freshwater ecotoxicity (FWEC, kg 1.4-DCB), marine ecotoxicity
(MEC, kg 1.4-DCB), and terrestrial ecotoxicity (TEC, kg 1.4-
DCB). Previous studies have also included similar impact
categories for aquaponic, hydroponic, and aquaculture systems
(see e.g., Ayer and Tyedmers, 2009;Jaeger et al., 2019;Martin
et al., 2022). In addition to the ReCiPe methodology, the
cumulative energy demand (CED, MJ) was also included in this
study to showcase the direct and indirect energy use throughout
the food production cycle.
2.4.2. Sensitivity analysis
Sensitivity analysis (SA) was carried out to determine the
most influential input parameters that affect the impact results
received (ISO, 2006). Identifying these influential parameters
can also assist in prioritizing mitigation strategies that have
the highest potential in reducing the overall impact of
the system.
In this study, SA was performed with each value from the
inventory inputs varied by ±10%, with other parameters held
constant. The impact results were then recalculated to identify
the input parameters that are most sensitive. A sensitivity factor
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TABLE 2 Inventory data based on 1 kg FU.
Input/output Category Product/process Amount Unit Lifetime (years)
Inputs Seedlings and fish Cucumber 5.80E-03 kg -
Tomato 7.00E-04 kg -
Fish 3.10E-03 kg -
Materials Fish feed 5.00E-02 kg -
CO2(enrichment) 3.09E-01 kg -
Water 1.49E+01 liters -
Nitrogen (N) 3.17E-01 g -
Phosphorus (P) 1.31E-01 g -
Potassium (K) 3.15E-01 g -
Iron (Fe) 6.50E-02 g -
Copper (Cu) 4.90E-01 g -
Energy inputs Total electricity 1.06E+01 kwh -
District heating 5.76E+00 kwh -
Infrastructure Structure Greenhouse 1.09E-02 m2 30
Galvanized steel 2.14E-02 kg 30
Glass fiber for fish tank 9.20E-03 kg 10
Controls/Electronics Greenhouse Fans 1.20E-03 kg 10
Air compressor 1.00E-05 unit 10
Oxygen generator 2.00E-05 unit 10
Water pump 2.00E-05 unit 10
LED Lights 1.90E-03 unit 15
Server 1.00E-05 unit 10
Growing mdia/piping Growing bed (gravel) 2.72E-06 kg 30
PE pipes 1.10E-03 m25
Outputs Harvest Cucumber 7.65E-01 kg -
Tomatoes 1.53E-01 kg -
Fish 8.16E-02 kg -
Supplementary Table A1 shows the datasets and references used for these processes and materials.
(SF) was also calculated by dividing the relative variation of the
results by the relative change in input data (Ghamkhar et al.,
2020,2022). For input parameters with a SF of <0.1 in all impact
categories (i.e., changing the input parameter by ±10% will lead
to <1% change in the results), the impact results are excluded,
and the parameter is thought to be less influential. The sensitivity
of the choice of electricity source (as one of the most influential
inputs) was also performed by using the Nordic mix and EU mix
instead of the Swedish electricity mix.
3. Results and analysis
The following sections outline the results of the life
cycle assessment, followed by an analysis of the sensitivity to
parameters and data and finally the influence of the allocation
method on the results.
3.1. Life cycle environmental impacts
Impact analyses were performed on the aquaponic system
based on 1 kg of fresh produce over a period of 1 year. The
impact results and contribution of the different input parameters
are shown in Figure 2.
The contribution analysis revealed that electricity, CO2
enrichment, and heating are the major sources of the
system’s impact (hotspots), accounting for more than 80%
in all categories except EU (75.8%) and WC (48.7%). Fish
feed scored high in terms of EU, with 64% of impact in
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FIGURE 2
The overall parameter contributions for each impact category under study. The other parameters include the impacts from input seedlings and
fish as well as fertilizers. The transportation parameter excludes transportation of infrastructure and fertilizers as they were included in the
Ecoinvent datasets for these processes. The numbers above each bar represent the quantified environmental impact of that category per 1 kg of
food produced. Data for the figure are provided in Supplementary Table A2.
that category but <7% in other categories. Similarly, the
impact from water use was primarily toward WC (15%),
with other categories accounting for <1%. Apart from EU,
electricity consumption is responsible for the majority of the
environmental impact (more than 40%), indicating the need for
mitigation measures in electricity use in order to reduce the
overall impact.
3.2. Sensitivity analysis
SA was performed to assess which of the inventory
parameters the results were most influenced by. This was
calculated as SF by dividing the absolute percentage change
of the final results by the absolute percentage change in
input value (10%). Parameters with SF <0.1 were excluded
due to low sensitivity (fertilizers, transportation, and input
seedlings/fish). On the other hand, impact results were
sensitive to input parameters from electricity, CO2enrichment,
heating, infrastructure, fish feed, and water, as can be seen in
Figure 3.
Electricity consumption was the most influential parameter
in all impact categories except MEU, which was more sensitive
to fish feed. The model was also highly influenced by the
CO2enrichment process, having the second highest results in
GWP, FWEU, FD, and ET categories. Water use was the least
influential parameter in all categories except for WC. Heating
was the second most sensitive parameter in TAC and CED after
electricity use. The SF for all input parameters can be seen in
Supplementary Table A3.
The sensitivity to the choice of electricity source was also
investigated by using Nordic mix (Nordic Countries Power
Association) and EU grid mix instead of the Swedish mix. For
GWP, using the Nordic mix would increase the results by 15%
compared to the Swedish mix, and the EU mix would increase
it by 370%. The EU mix also gave the highest impact in all
categories except for WC, where more impact resulted from the
Nordic mix. The Swedish mix gave the lowest results in most
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FIGURE 3
SFs (axis) for the most influential parameters in each impact category (outer labels). Further details are provided in Supplementary Table A3.
categories except FWEU, MEU, and ET, Nordic mix scored lower
in these categories. Figure 4 and Table 3 show the results for the
assessed categories based on the different electricity sources.
3.3. Allocation of impact
Table 4 shows the allocation of impact for all categories
based on energy and economic allocation. The results
are reported per 1 kg of each product in the system
(cucumber, tomato, and salmon). The choice of allocation
method provides different results for emission contribution
from each product. Cucumbers have the highest share
of impact in economic allocation due to their high price
value but the least impact based on energy content.
Salmon had the highest impact on energy allocation
due to a higher calorific value compared to the crops
harvested.
4. Discussion
4.1. Hotspots and mitigation
The results of this study presented the environmental impact
of an aquaponic system based in a cold-weather region of
northern Sweden. According to the contribution analysis, the
system’s main sources of impacts were electricity consumption,
CO2enrichment, and heating.
Electricity is widely regarded as the most significant
contributor to the impact of aquaponic systems (Hindelang
et al., 2014;Boxman et al., 2016;Maucieri et al., 2018;Jaeger
et al., 2019;Verdoodt, 2019), with more electricity required
in cold weather aquaponics (Chen et al., 2020;Ghamkhar
et al., 2020,2022;Valappil, 2021) due to lower temperatures
and shorter daylight hours (Valappil, 2021). Similar results
were observed in this study, with electricity consumption
(primarily for lightning) accounting for more than half of the
impact in nearly all categories. The Swedish grid system is
primarily powered by renewable sources, which significantly
reduces the overall impact of the system. Food produced
in aquaponics powered by fossil-based electricity has been
reported to have a significantly higher impact. In contrast to
this study’s maximum of 6.94 kg CO2-eq/kg of fish, Valappil
(2021) reported a GWP of 68 kg CO2-eq/kg of fish from an
aquaponic system in Canada, with fossil and coal-based grid
systems accounting for 95% of the impact. Valappil (2021)
considered a scenario with wind energy and energy efficiency
measures, which reduced the GWP by 97% compared to the
original impact. The aquaponic system under investigation also
employs LED lights, which are known for their efficiency.
The system additionally uses high-tech devices to optimize
operation conditions and minimize losses, which was identified
as a recommended strategy for energy efficiency as well as
reducing manpower (see e.g., Junge et al., 2017;Valappil,
2021).
In terms of heating, the contribution reported in this study
was lower than other cold-weather aquaponics research, which
can also be attributed to the heating source. For example,
Ghamkhar et al. (2020,2022) used natural gas for heating,
whereas Chen et al. (2020) and Valappil (2021) used fossil-
based electricity; of which 88% was derived from coal in Chen
et al. and about 21% renewable in Valappil. The utilization
of district heating by the aquaponic system under study can
be considered an advantage in reducing the overall emissions
from heating. Similar findings on the use of district heating for
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FIGURE 4
The environmental impacts based on Swedish, Nordic, and European grid mixes (log scale).
TABLE 3 The sensitivity to the choice of electricity mix, results for the Swedish, Nordic and EU grid mixes for the impact categories under study.
Impact category GWP TAC FWEU MEU FD WC ET CED
kg CO2-eq kg SO2-eq kg P-eq kg N-eq kg oil-eq m3kg 1.4-DCB MJ
Swedish mix 1.07E+00 4.52E-03 4.30E-04 1.92E-04 2.28E-01 9.78E-02 9.74E+00 1.18E+02
Nordic mix 1.23E+00 4.79E-03 3.86E-04 1.70E-04 2.71E-01 1.94E-01 9.26E+00 1.03E+02
EU mix 5.01E+00 2.08E-02 4.80E-03 4.58E-04 1.32E+00 1.13E-01 1.88E+01 1.40E+02
TABLE 4 Comparison of the results based on dierent allocation approaches based on energy and economic allocation (per 1 kg of each product).
Method Impact
category
GWP TAC FWEU MEU FD WC ET CED
Unit kg CO2-eq kg SO2-eq kg P-eq kg N-eq kg oil-eq m3kg 1.4-DCB MJ
Energy Cucumber 5.34E-01 2.26E-03 2.15E-04 9.61E-05 1.14E-01 4.89E-02 4.87E+00 5.92E+01
Tomato 6.00E-01 2.54E-03 2.42E-04 1.08E-04 1.28E-01 5.51E-02 5.48E+00 6.66E+01
Fish 6.94E+00 2.94E-02 2.80E-03 1.25E-03 1.48E+00 6.36E-01 6.33E+01 7.69E+02
Economic Cucumber 1.34E+00 5.67E-03 5.40E-04 2.41E-04 2.86E-01 1.23E-01 1.22E+01 1.48E+02
Tomato 1.26E-01 5.35E-04 5.10E-05 2.28E-05 2.70E-02 1.16E-02 1.15E+00 1.40E+01
Fish 2.79E-01 1.18E-03 1.12E-04 5.02E-05 5.95E-02 2.56E-02 2.55E+00 3.09E+01
aquaculture in Sweden have been found (see e.g., Nilsson and
Martin, 2022).
Further reduction in heating demand can be achieved
through better insulation and effective space heating through
optimization of the volume of the aquaponic system (reducing
unnecessary space) (Ghamkhar et al., 2022). Heating can
also be recycled from exhaust heat in nearby buildings or
factories, including the refrigerated cooling rooms in the
adjacent supermarket as suggested by Körner et al. (2021).
According to a Finnish study on greenhouse tomato production,
using industrial waste heat can reduce GWP by more than
half when compared to district heating (Marttila et al.,
2021).
In this study, CO2enrichment was identified as a major
contributor, with sensitivity analysis indicating that it has the
potential to reduce the overall impact. To the best of the
authors’ knowledge, this input material was not considered in
the inventory data in previous aquaponic studies, which could
be due to the majority of these studies being on a small scale
and that CO2enrichment is not an essential additive to the
hydroponics systems. CO2enrichment, on the other hand, is
common in commercial greenhouses due to its role in increasing
food production efficiency (Li et al., 2018;Marttila et al.,
2021). This study demonstrates the importance of including
this parameter in the analysis, if used, due to its considerable
contribution to the overall impact.
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Elnour et al. 10.3389/frsus.2022.1051091
Part of the emissions from the supplied CO2is caused
by energy used for gas liquefaction, as well as transportation
(∼550 km) from t he industrial source. To mitigate this impact, a
local supply of CO2via pipeline from an industrial facility or
the combined heat and power (CHP) plant in Östersund can
be used. Transportation of CO2via pipeline is also regarded as
more cost-effective and stable than road transport (Johansson
and Pétursdóttir, 2021). This method is used at Thanet Earth,
a greenhouse complex in the United Kingdom, where a CHP
plant uses water pumps to supply CO2in addition to heat and
electricity to five greenhouses through water pumps (Gentry,
2019;Goddek et al., 2019).
In the current study, fish feed had a relatively low impact
in most categories, with the exception of EU, which contributed
nearly half of the impact in this category. Feed conversion
ratio (FCR) is used to describe the quantity of feed required
to produce 1 kg of fish, and the value in this study was
0.62. Many authors have identified fish feed as a hotspot for
impact in aquaponics (Boxman, 2015;Boxman et al., 2016;
Forchino et al., 2017;Cohen et al., 2018;Ghamkhar et al.,
2020,2022;Valappil, 2021) and aquaculture systems (Ayer and
Tyedmers, 2009;Yacout et al., 2016). This can be attributed
to the high FCR values reported by these studies, which are
typically >1, with Ghamkhar et al. (2022) reporting FCR up
to 5.4. A low FCR indicates efficiency in converting feed
into fish weight (Charles Bai et al., 2022). More analysis
into feed ingredients and composition can provide an insight
into how this impact can be reduced. These ingredients
can also be sourced locally through an industrial symbiotic
network including microalgae farms and breweries (Haller et al.,
2022).
Infrastructure is often excluded in agri-food LCA research
due to assumptions of negligible contribution to the overall
impacts (Ayer and Tyedmers, 2009;Ghamkhar et al., 2020),
while identified by others as a main contributor in aquaponics,
recommending that it should not be excluded (Forchino et al.,
2017;Valappil, 2021;Ghamkhar et al., 2022). In this study,
the impact from infrastructure was the highest and most
sensitive toward ET (15%) and FWEU (8.2%), iterating the
importance of considering this parameter in the analysis.
Mitigating the impact of these categories can be achieved
through choosing lower-impact materials and increasing the
life span of equipment, e.g., through regular maintenance
(Forchino et al., 2017;Ghamkhar et al., 2022). Aquaponic
systems are often praised for low water usage compared to
other systems (Hindelang et al., 2014;Xie and Rosentrater,
2015;Junge et al., 2017;Cohen et al., 2018). Further reduction
was suggested in previous research by employing rainwater
collection systems and minimizing daily losses (e.g., by using
covers and vent traps) (Junge et al., 2017;Pattillo, 2017;Valappil,
2021). Other parameters (fertilizers, input fish and seedlings,
and transportation) were the least impactful and sensitive
parameters in this study.
4.2. Comparison of impacts
The allocation of impact per crop cultivated generated quite
different results depending on the method employed. Cucumber
had the largest impact when measured by economic allocation
due to its high economic value. However, when the system
is seen in terms of energy content, cucumber had the least
impact and fish production accounted for the majority of the
emissions (53%). This illustrates the sensitivity of the results to
the allocation method and the importance of considering several
methods in order to obtain a good understanding of the system
under study.
In the following sub-sections, results from the allocated
impact are compared to the same produce in conventional,
aquaculture, and hydroponics systems. External comparison
with other systems is common in aquaponics research
(Hindelang et al., 2014;Thorarinsdottir, 2015;Hollmann, 2017;
Verdoodt, 2019;Ghamkhar et al., 2022) to help put the results
into perspective. For this study, this is presented with respect
to 1 kg of fresh product at the farm gate to provide a common
basis for comparison. The assessment is based on the GHG
emissions (i.e., GWP), which is the most reported category
in LCA literature (Bjørn et al., 2020), as well as FCR for the
fish product. To highlight the food mile’s part of the impact,
this comparison mentions the GWP of food items imported
to Sweden based on data from Moberg et al. (2019), which
includes transportation, packaging, storage, refrigeration, and
losses along the supply chain.
4.2.1. Tomato
Tomatoes produced from the aquaponic system had a GWP
of roughly 0.6 and 0.13 kg CO2-eq per kg based on energy
and economic allocation, respectively. Tomatoes are commonly
cultivated in open fields, heated, and unheated greenhouses.
Open field cultivation takes place in warm regions and its
impact is usually low due to minimal energy requirements.
Lam et al. (2018) reported that GWP for open field tomato
production in different countries ranged between about 0.02 and
0.06 kg CO2-eq per kg of fresh product. This is in line with
a study from Iran at 0.05 kg CO2-eq/kg (Zarei et al., 2019),
and lower than those reported for the US at 0.11 kg CO2-eq/kg
(Parajuli et al., 2021).
For greenhouses located in Sweden, Anders et al. (2006)
estimated a GWP of about 2.7 kg CO2-eq/kg while several
studies (Karlsson, 2011;Röös and Karlsson, 2013;Bosona and
Gebresenbet, 2018) reported a GWP of roughly 0.3 kg CO2-
eq per kg of tomato from heated greenhouses. The greatest
contribution to the impact in these studies was electricity
consumption, which is in line with the results of this study.
Unheated greenhouses reported a lower GWP at about 0.21 kg
CO2-eq/kg (Karlsson, 2011;Röös and Karlsson, 2013). The
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Elnour et al. 10.3389/frsus.2022.1051091
results of this study are higher than open field farming but lower
than greenhouses in Sweden with economic allocation.
Tomatoes from heated greenhouses in the Netherlands have
a GWP of 0.95 and 2 kg CO2-eq/kg according to Torrellas
et al. (2012) and Röös and Karlsson (2013), respectively. For
Spain, unheated tunnel greenhouses reported 0.25 kg CO2-
eq/kg (Torrellas et al., 2012) and heated greenhouses at 0.54 kg
CO2-eq per kg (Röös and Karlsson, 2013). Regardless of
allocation methods, this study shows lower impact than heated
greenhouses in the Netherlands but higher than greenhouses in
Spain with energy allocation.
Sweden mostly imports tomatoes from the Netherlands
(about 52%) and Spain (21%) (OEC, 2020). The impact of
tomatoes at the retailer’s gate in Sweden from the Netherlands
(greenhouses) is estimated at 2.05 kg CO2-eq/kg, while from
Spain at 0.45 and 0.51 kg CO2-eq/kg from greenhouses
and open-field, respectively (Moberg et al., 2019). Tomatoes
imported from the rest of Europe had a GWP of 1.35 kg CO2-
eq/kg from greenhouses and 0.48 kg CO2-eq/kg from open-field
cultivation (Moberg et al., 2019). The impact reported in this
study is higher than imports from open field cultivation with
energy allocation and lower than imports from greenhouses
beside Spain.
4.2.2. Cucumber
According to this study, the GWP from cucumbers was
approximately 0.53 and 1.34 kg CO2-eq per kg for energy and
economic allocation, respectively. Contrary to tomato farming,
there is a lack of LCAs on cucumber production in Europe to be
used as a basis for comparison.
Potter et al. (2020) reviewed the environmental impact
of plant-based foods and identified only two studies on the
environmental impact of cucumbers that are relevant to the
Swedish market. The GWP from heated greenhouses in Sweden
was estimated by Davis et al. (2011) to be around 1 kg CO2-
eq per kg, and González et al. (2011) reported a GWP of
heated greenhouses using electricity and fuel oil to be 0.75 and
2.6 kg CO2-eq per kg of cucumber, respectively. The GWP from
average global cucumber production in heated greenhouses is
estimated at 2.1 kg CO2-eq per kg according to meta-analysis
data by Clune et al. (2017) (based on 7 studies).
Cucumber farming in warm regions reported a lower
GWP impact due to low heating requirements. According
to Zarei et al. (2019), cucumber cultivation in Iran’s open
fields has a GWP of 0.162 kg CO2-eq/kg and greenhouse
cultivation has 0.07 kg CO2-eq per kg. The GWP from cucumber
reported in this study is lower than the global average from
heated greenhouses and greenhouses in Sweden heated with
fuel oil according to González et al. (2011). The results are
however higher than cucumber grown in Iran as well as heated
greenhouses in Sweden with economic allocation according to
other studies.
Similar to tomatoes, Sweden imports cucumbers mostly
from the Netherlands and Spain at roughly 64% and 29%,
respectively (OEC, 2020). Moberg et al. (2019) estimated that
cucumbers imported from the Netherlands (greenhouses) have
a GWP of 1.54 kg CO2-eq per kg at retailer’s gate in Sweden and
from greenhouses and open-fields in Spain at 0.44 and 0.51 kg
CO2-eq/kg, respectively. The rest of Europe has 0.49 kg CO2-eq
per kg based on open-field cultivation (Moberg et al., 2019). The
cucumbers cultivated from the aquaponic system have a lower
GWP than imports from the Netherlands but higher for Spain
and the rest of Europe.
4.2.3. Salmon
Salmon production had GWP of roughly 6.94 and 0.28 kg
CO2-eq per kg based on energy and economic allocation.
Martin and Carlsson (2018) reported a GWP of 1.9 kg CO2-
eq per kg for land-based RAS in Sweden. For open net-pen
systems, Liu et al. (2016) reported a GWP of about 3.4 kg CO2-eq
per kg for a study based in Norway. Ayer and Tyedmers (2009)
assessed the impact of salmon production from four salmon
farming systems in Canada. The study reported a GWP of
roughly 2 kg CO2-eq /kg from marine net-pen, marine floating
bags, and land-based flow-through systems. Land-based RAS
had a GWP of more than 28 kg CO2-eq/kg of salmon due
to reliance on electricity for production. Pelletier et al. (2009)
estimated the environmental impact of salmon production based
in Norway, the UK, Canada, and Chile. The study reported an
average GWP of roughly 2 kg CO2-eq per kg of salmon produced
in these countries.
Sweden imports most of its Atlantic salmon from Norway
(92%) (OEC, 2020). Moberg et al. (2019) assessed the average
impact of salmon production in Norway at the farm’s gate at
3.03 kg CO2-eq per kg and at the retailer’s gate in Sweden
(edible weight) at 6.07 kg CO2-eq /kg. The aquaponic system in
this study shows lower results for salmon production based on
economic allocation but higher with energy allocation except for
land base RAS in Ayer and Tyedmers (2009).
FCR for the aquaponic system is calculated at 0.62 which
is also lower when compared to common systems. The FCR
from the previous studies was 1.1 in Martin and Carlsson
(2018), 1.27 in Liu et al. (2016), and between 1.1 and 1.5 in
Pelletier et al. (2009). Having a lower FCR in aquaponics is
in line with experimental results by Atique et al. (2022) where
aquaponics recorded FCR around 0.85 compared to separate
RAS at roughly 1.06.
4.3. Benefits from symbiosis
Because the aquaponics system in this study is located next
to the retail store, the impacts of transportation, packaging,
cooling, and storage are avoided. The impact of food waste
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Elnour et al. 10.3389/frsus.2022.1051091
FIGURE 5
Comparison of GWP from the aquaponics’ harvest as opposed to importing the same amount of items at retailer’s gate. Further details on the
calculations are provided in Supplementary Tables A4,A5.
during distribution is also eliminated, with roughly a quarter of
global food production lost between the farm and the retailer’s
gate (Onwude et al., 2020).
Several authors have argued that long-distance transport of
food items is more environmentally beneficial than off-season
local production in cold climates (Benis et al., 2017;Goldstein,
2017). Heller (2017) after reviewing 17 studies in greenhouse
tomato production concluded that heated greenhouses for
local tomato production outweigh the impacts of long-distance
transportation. However, this was due to high GWP from
greenhouses reported in their review (average about 1.8 kg
CO2-eq/kg) as opposed to on-field production (0.25–0.4 kg
CO2-eq /kg). Comparing the results of this study to other
system showed mixed results with open field cultivation mostly
having lower GWP and greenhouses having higher or lower
impact depending on the allocation method. The aquaponic
system also showed lower GWP than imports from the
Netherlands as oppose to Spain where the system mostly have
higher impact.
The total yearly harvest from the aquaponic system is 75
tons of cucumbers, 15 tons of tomatoes, and 8 tons (live
weight) of salmon. Measuring the GWP impact from the
total yearly harvest results in around 104.5 tons CO2-eq.
The impact of importing the same amount according to data
from Moberg et al. (2019) and statistics from OEC (2020)
mentioned in section 4.2 will result in about 105.3 tons CO2-
eq. The production from the aquaponic system have lower
GWP than importing the same amount of food items. The
share of each produced or imported food item can be seen in
Figure 5.
Another advantage of the symbiosis is the opportunity to
utilize urban infrastructure and cooperate with local industries
through industrial and urban symbiosis. Establishing symbiotic
links between different businesses can lead to better utilization
of resources that, otherwise, would be wasted or not fully
utilized. This can lead to benefit sharing and further reduction in
impact from input heat, fertilizers, fish feed, and carbon dioxide.
Similar findings are also highlighted in Martin and Carlsson
(2018) and Martin et al. (2022) for symbiotic production
of foods.
4.4. Limitations
There are a few limitations of this study that can influence
the quality of the results received. Firstly, as the aquaponic
system was under construction at the time of this study, some
data were missing on the operation condition of the system. As
such the results are only an indication of the potential impacts of
the system and should be confirmed once the system is in place.
Furthermore, several datasets were also lacking from SimaPro
databases. Assumptions were made from secondary literature or
for comparable processes which may not accurately describe the
actual situation.
The system under study uses high-tech devices and artificial
intelligence for automatic production processes. Automation in
agri-food production is a new area of research with the potential
to reduce emissions due to optimized operations and resource
usage. This was not investigated during this study due to a lack
of data and warrants future research.
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Elnour et al. 10.3389/frsus.2022.1051091
5. Conclusions
This study presents the environmental impact of a
commercial cold-weather aquaponic system located in an urban
environment in northern Sweden. The environmental impacts
were assessed through eight impact categories, and the results
suggest that electricity, CO2enrichment, and heating were the
main contributors in all categories. Results were also most
sensitive to these parameters indicating that intervention in
them will lead to a noticeable reduction in the overall emissions.
The presence of the aquaponic system in an urban environment
provides the potential to utilize industrial waste and by-products
(e.g., exhaust heat and CO2) to mitigate these impacts. Further
research is needed to quantify these potential symbiotic benefits.
The combination of aquaculture and hydroculture in
aquaponics revealed that synergies can potentially lead to
reductions in the environmental burden for these systems
compared to operating them separately. Salmon grown in
the aquaponics’ RAS, for example, have less than fifth the
GWP impact than from independent RAS or other common
production systems with economic allocation. However, looking
at the system in term of energy content will result in mostly
higher impact from the salmon grown in the aquaponics. This
demonstrates the potential for aquaponic systems in meeting the
future demand for sustainable food products. In addition, the
system can contribute to cities realizing self-sufficiency of food
items with lower GWP than importing them from elsewhere.
Data availability statement
The original contributions presented in the study are
included in the article/Supplementary material, further inquiries
can be directed to the corresponding author/s.
Author contributions
ME and HH contributed to conceptualization and data
collection. ME contributed to life cycle assessment, data
analysis, and manuscript writing. MM and HH contributed
with supervision as well as reviewing and editing the final
manuscript. All authors contributed to the article and approved
the submitted version.
Funding
This research was partly funded by the Swedish research
council for sustainable development Formas (Grant Number:
2021-00068). It was also funded by the Swedish Innovation
Agency (Vinnova), within the Research Program, Innovations
for a Sustainable Society, in the project Urban farming for
resilient and sustainable food production in urban area (Grant
Code: 2019-03178).
Acknowledgments
We would like to thank Daniel Juhlin from Agtira
AB for providing the necessary data for this study.
We are also thankful to anonymous reviewers for their
inputs and suggestions that helped improve the quality
of the article.
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those
of the authors and do not necessarily represent those
of their affiliated organizations, or those of the publisher,
the editors and the reviewers. Any product that may be
evaluated in this article, or claim that may be made by
its manufacturer, is not guaranteed or endorsed by the
publisher.
Supplementary material
The Supplementary Material for this article can be
found online at: https://www.frontiersin.org/articles/10.3389/
frsus.2022.1051091/full#supplementary-material
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