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Smetana, S., Mathys, A., Knoch, A. et al. Int J Life Cycle Assess (2015) 20: 1254. doi:10.1007/s11367 -015-0931-6
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https://link.springer.com/article/10.1007/s11367-015-0931-6
Meat Alternatives:
Life Cycle Assessment of Most Known Meat Substitutes
Sergiy Smetana1,2*, Alexander Mathys1, Achim Knoch1, Volker Heinz1
1 German Institute of Food Technologies (DIL-e.V.), Quakenbrück, Germany
2 Institute of Structural Analysis and Planning in Areas of Intensive Agriculture, University of Vechta, Vechta, Germany
Corresponding author. Tel.: +49 (0)5431-183-155; e-mail: s.smetana@dil-ev.de; smsmetana@gmail.com
ABSTRACT
Purpose Food production is among highest human environmental impacting activities. Agriculture itself accounts for 70-
85% of the water footprint and 30% of world greenhouse gases emissions (2.5 times more than global transport). Food pro-
duction projected increase in 70% by 2050 highlights the importance of environmental impacts connected with meat pro-
duction. The production of various meat substitutes (plant-based, mycoprotein-based, dairy-based and animal-based substi-
tutes) aims to reduce the environmental impact caused by livestock. This article outlined the comparative analysis of meat
substitutes’ environmental performance in order to estimate the most promising options.
Methods The study considered “cradle-to-plate” meal life cycle with the application of ReCiPe and IMPACT 2002+ meth-
ods. Inventory was based on literature and field data. Functional unit (FU) was 1 kg of a ready to eat meal at a consumer.
The study evaluated alternative FU (the equivalent of 3.75 MJ energy content of fried chicken lean meat and 0.3 kg of di-
gested dry matter protein content) as a part of sensitivity analysis.
Results and discussion Results showed the highest impacts for lab-grown meat and mycoprotein-based analogues (high de-
mand for energy for medium cultivation), medium impacts for chicken (local feed), dairy-based and gluten-based meat sub-
stitutes, and the lowest impact for insect-based and soymeal-based substitutes (by-products allocated). Alternative FU con-
firmed the worst performance of lab-grown and mycoprotein-based analogues. The best performing products were insect-
based, soymeal-based substitutes and chicken. The other substitutes had medium level impacts. The results were very sensi-
tive to the changes of FU. Midpoint impact categories results were the same order of magnitude as previously published
work, although wide ranges of possible results and system boundaries made the comparison with literature data not reliable.
Conclusions and recommendations The results of the comparison were highly dependable on selected FU. Therefore, pro-
posed comparison with different integrative FU, indicated the lowest impact of soymeal-based and insect-based substitutes
(with given technology level development). Insect-based meat substitute has a potential to be more sustainable with the use
of more advanced cultivation and processing techniques. The same is applicable to lab-grown meat and in a minor degree to
gluten, dairy and mycoprotein-based substitutes.
Keywords: meat substitute, LCA, soy meal, mycoprotein, insect meal
Smetana, S., Mathys, A., Knoch, A. et al. Int J Life Cycle Assess (2015) 20: 1254. doi:10.1007/s11367 -015-0931-6
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1. Introduction
Food production is among the biggest human environmental impacting activities. Agriculture itself is responsible for 70-
85% of water footprint and 30% of world greenhouse gases (GHG) emissions (Shiklomanov 2003; Bellarby et al. 2008;
Pfister et al. 2011; Hoekstra and Mekonnen 2012; Vermeulen et al. 2012; Garnett 2013; Pfister and Bayer 2014) . Moreover,
food demand is projected to increase by 70% till 2050 (FAO 2009), which will result in associated impacts increase as well.
Meat production is the most impacting activity in food production (Steinfeld et al. 2006). At the same time, understanding
environmental and economic costs of meat production led to the development of meat analogues, their successful introduc-
tion to market and production (Tijhuis et al. 2011). The most known and successful meat substitutes are based on plant ma-
terial (soy, peas, lupine, rice, etc.), animal produced proteins (milk, insects, lab-grown) and mycoproteins.
Several studies indicated that meat substitutes had a lower environmental impact than meat (Håkansson et al. 2005;
Nonhebel and Raats 2007; Raats 2007; Blonk et al. 2008; Finnigan et al. 2010; Head et al. 2011; Tuomisto and de Mattos
2011; Berardy 2012; Oonincx and de Boer 2012; Van Huis et al. 2013). However, limitations of transportation systems or
regional production specifics, used in global supply chains, could increase environmental impacts for soy and milk products.
Meanwhile, future processing technologies improvement could be beneficial for meat analogues with early development
stage (lab-grown meat, insect-based analogues). Even though, some comparisons of meat substitutes environmental perfor-
mance were published (Head et al. 2011; Van Huis et al. 2013), the analyses did not include possible differentiation of func-
tional unit in terms of energetic values and digestibility of meat substitutes. In most cases, they presented the functional unit
as 1 kg of product (weight-based and did not include variations of nutritional qualities).
This study aims to compare main types of meat substitutes with chicken as the most environmentally friendly meat (Wil-
liams et al. 2006b; Roy et al. 2009), considering supply chain from raw materials extraction (cradle) to product use by con-
sumer (plate). The functional unit (FU) in the main part of the study is presented as 1 kg ready for consumption product
(fried meat or meat analogue). This way we consider differentiations in production and processing of meat analogues. Com-
plete nutritional profile of foods wasn’t taken into account in the main study as the comparison of results with literature data
was one of the objectives. At the same time, alternative FU were considered in the sensitivity analysis. They were based on
energy content of the products (3.75 MJ) and protein digestibility (0.3 kg of digested proteins). Sensitivity analysis also in-
cluded main results verification with alternative assessment methodology (IMPACT 2002+).
2. Methods
The study concentrates on the attributional Life Cycle Assessment (LCA) as the main approach, as it does not account
for consequences in the surrounding market. We do not aim at the determination of environmental effects for a specific lo-
cation but at an average global comparison of most common meat analogues. The difference in technology development
levels was not considered in the study but discussed in the article. However, a sensitivity analysis (Section 4) includes varia-
tions of performed functions (FU). The calculations were performed via SimaPro 8 software with Ecoinvent 3 and LCA
Food DK Databases (Nielsen et al. 2003; Weidema et al. 2013). The study follows ISO14 040 and 14 044 standards (ISO
14040 2006; ISO 14044 2006) with an exception of external review, as the results of the study are not for specific products
environmental impact public disclosure. The conceptual comparison of main meat analogue types and the identification of
the most promising substitutes for technologies improvement is the main goal of the study.
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2.1. Products studied
The study concentrates on six meat analogues in comparison with the most environmentally efficient meat – (1) chicken
(Williams et al. 2006b; Roy et al. 2009). From one side, the analysis included substitutes based on animal products: (2)
dairy-based; (3) lab-grown; (4) insect-based. From the other side, the study investigated plant- and mycoprotein-based
products: (5) gluten-based; (6) soymeal-based and (7) mycoprotein-based. In total, the study analyzes seven products (Table
1).
2.2. Environmental impacts considered
The characterization method (ReCiPe V1.08), used in the main study, is selected as the most integrative and recent one,
(Goedkoop et al. 2013a). Such approach allows overall single score product comparison, as well as detailed analysis with
multiple characterization factors (climate change, ozone layer depletion, human toxicity, acidification, ecotoxicity, land oc-
cupation, metal and fossil fuels depletion, etc.). This study includes multiple effects for integrated impact visualization (eco-
points). Another integrated methodology (IMPACT 2002+), which includes IMPACT 2002; Eco-indicator 99; CML and
IPCC methods, was used for the sensitivity analysis to indicate the reliability of main study comparison results (Goedkoop
and Spriensma 2001; Guinée et al. 2002; Pennington et al. 2005; IPCC 2007; Goedkoop et al. 2013b) . Land use change
(LUC) is an important environmental aspect of food and feed products, but its estimation and calculation do not follow a
single standardized approach (Muñoz et al. 2013). This study included LUC analysis as a potential impact (due to the differ-
ent levels of technologies development) in the discussion section (see 4.4). For calculating LUC, associated with various
crops and agricultural products, we used an approach from Milà i Canals et al. (2012) with global land use data from FAO-
STAT (FAO 2014). Greenhouse gases emissions associated with LUC were indicated according to published works (BSI
2008; Flynn et al. 2012).
2.3. Functional unit
This study focuses on final product with a weight of 1 kg ready for consumption after assembly, processing, delivering
and frying at a consumer. The use of final product weight was a basis for consumption comparability. Moreover, the selec-
tion of 1 kg weight unit was connected with ability to compare results with those available in the literature. Therefore, the
FU in the main part of the study is the satisfaction of a consumer with 1 kg protein enriched product ready for the consump-
tion.
The study included the comparison of results with alternative FU, which are based on calorific energy content (3.75 MJ)
of ready for consumption product. This unit was identified as the basic integrative unit, which reflects the function of sup-
plying high-quality protein meal with equal energy content. The use of products’ energy content to compare their function
is the basis for such assumption (Schau and Fet 2008). The choice of such approach resulted in the differentiations of the
final products weight: 0.3 kg for chicken and lab-grown meat, 0.4 kg for dairy-based, 0.9 kg for insect-based, 0.375 kg for
gluten-based, 1 kg for soy-meal-based and 0.94 kg for mycoprotein-based meals.
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The other alternative FU included in sensitivity analysis of the study is connected with the function of meat products to
supply the consumer with proteins, as meat is known to be the biggest protein source for human consumption. From this
point, the digestible bulk protein content was considered as a basis for alternative FU. It was determined as 0.3 kg of the
protein product (dry weight) corrected via Protein Digestibility Corrected Amino Acid Score (PDCAAS). PDCAAS for
chicken is 1.00; dairy proteins – 1.00; lab-grown meat (beef source) – 0.92; insect proteins – 0.86; wheat proteins – 0.40;
soy proteins – 1.00; mycoprotein – 0.99 (Hoffman and Falvo 2004; Longvah et al. 2011). The protein content in final prod-
uct (wet content) is: 31% for chicken, 12.5% for dairy-based meat substitute; 26% for lab-grown beef; 13.5% for insect-
based meat substitute; 22.5% wheat protein content; 16.5% for soy meal; 10% for mycoprotein (Van Huis et al. 2013;
USDA 2014). Therefore, PDCAAS corrected weight to get 0.3 kg of digestible protein content (alternative FU) would re-
quire: 0.97 kg of chicken meat; 2.4 kg of dairy-based; 1.25 kg of lab grown; 2.6 kg of insect-based; 3.33 kg of wheat pro-
tein-based; 1.82 kg of soy meal-based; and 3.03 kg of mycoprotein-based meat substitutes.
2.4. System boundaries
The paper relies on a single system boundary, drawn for meat substitutes and chicken (Fig. 1). However, the raw re-
sources, assembly, recipes and processing are different. The system is considered from cradle (raw resources production) to
plate (consumer use). Recycling of packaging and waste treatment after human consumption is not in the scope of the study.
The starting point for the system includes production of raw materials for assembly of the food: protein feed growing for
chicken (1) and dairy cows (2); crops growing for gluten (5), soybeans (6) and insect feed (4); medium growing for myco-
mycelium (7) and cyanobacteria growing and harvesting (3). The assembly and processing stage include: chicken feeding
and slaughtering (1); cows feeding, milking and cheese-like processing with plant fibers (2); meat growing in cyanobacte-
ria-based medium (e.g. Cyanobacteria hydrolysate) with growth factors induced with Escherichia coli bacteria and vitamins
(3); insects feeding, harvesting, drying and processing with plant fibers (4); wheat grains processing into flour and gluten
with texturized product forming (5); soy oil extraction, and soymeal high-moisture extrusion (6); myco-mycelium growing,
harvesting and fermentation (7). The assembly stage includes transportation to a supermarket, cooling on a cooling counter
and additional products application (vegetable oil, salt). The final life cycle stage in this study includes transportation to the
consumer (assumed 10 km) and frying on the electrical stove.
2.5. Data and sources
The LCA relies on data collected from multiple sources. It uses Ecoinvent 3 and LCA Food DK databases to identify the
impact of raw materials growing and harvesting (Nielsen et al. 2003; Weidema et al. 2013); published data on meat substi-
tutes production, processing and environmental impact (Berk 1992; Berlin 2002; Raats 2007; Blonk et al. 2008; Dalgaard et
al. 2008; Finnigan et al. 2010; Tuomisto and Mattos 2010; Head et al. 2011; Tuomisto and de Mattos 2011; van Zeist et al.
2012; Oonincx and de Boer 2012; Van Huis et al. 2013; Deng et al. 2013); primary data of high-moisture extrusion process-
es (Table 1) from the German Institute of Food Technologies (DIL e.V.). The same global average databases, aimed for al-
location, are used for the comparison analysis. Sensitivity analysis, included in the study, represents alternative functional
units and methodology.
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2.6. Allocation
Our study considered a few meat substitutes, produced along with other co-products. Some of the meat substitutes were
by-products of bio-fuel production (6); butter production (2); or produced together with other products such as wheat starch
(5). Option for minced meat production (from dairy cows) is not included in the scope. Literature indicated that lab-grown
meat production aimed at a single product, whereas mycoprotein-based analogue production and insect harvesting often in-
cluded side streams use from other food productions, such as carrot peelings or molasses from sugar beets (Raats 2007;
Oonincx and de Boer 2012; Van Huis et al. 2013). In our analysis insects feeding used carrots and grain mixture (Oonincx
and de Boer 2012), not by-products. As main study FU has a weight-based origin, we used weight allocation for many pro-
cesses in the analysis of meat analogues and meat. Lab-grown meat substitute (3) production required specific cyanobacteria
production solely for the purpose of meat growing medium and, so, no by-products were considered in allocation. We did
not include the waste treatment of the final product in the paper.
3. Results
There were large differences in environmental impacts between meat substitutes at midpoint impact categories of the
studied life-cycle “from-cradle-to-plate” (Fig. 2). The lab-grown meat had the highest impacts in most categories, except for
agricultural land occupation (gluten-based had the highest impact), terrestrial and freshwater ecotoxicity (chicken meat was
leading). Chicken meat also had high relative impacts in most midpoint categories. Gluten production was influential in
metal depletion, human and terrestrial toxicity. Insect-based meal showed high impacts in categories of terrestrial and
freshwater ecotoxicity. Dairy-based substitute impacted high in categories of ozone layer depletion, terrestrial acidification
and agricultural land occupation.
Such differentiation could be explained with the high energy consumption by cyanobacteria medium growth for meat
cultivation (3) and high environmental impacts in most categories associated with energy production. At the same time, the
highest agricultural land occupation was assigned for gluten production (5), which required extensive land resources for
wheat grain production. Use of grains and protein feed for chicken (1) caused the high impacts in ecotoxicity categories.
Lab-grown meat (3) was also responsible for the highest impact (Fig. 3) in endpoint damage assessment categories of
human health (1.49 Pt), resources availability (0.967 Pt) and ecosystem quality (0.09 Pt). As stated previously, lab-grown
meat production required a lot of energy, which caused the highest impact on the environment. The lowest impact in all
endpoint categories was noted for insect-based (4) and soymeal-based (6) meat substitutes. The second highest impact on
human health was assigned for chicken meat (0.383 Pt) and mycoprotein-based meal (0.372 Pt). Resources availability was
also affected by dairy-based, chicken and mycoprotein-based meals (0.17-0.2 Pt). Chicken (1), gluten-based (5) and dairy-
based (2) meals affected ecosystem resources at medium levels (0.05-0.06 Pt).
The comparison of overall environmental impact (eco-points) showed the highest impact caused by the lab-grown meat
(2.55 Pt). It had the highest impact in endpoint categories caused by the respiration inorganic emissions, climate changes
and non-renewable energy consumption (Fig. 4). Mycoprotein-based meat analogue and chicken were the second highest
impacting products among compared. Their overall impact was 0.60-0.62 Pt. The lowest environmental impact was as-
signed for insect-based (4) and soymeal-based (6) meat substitutes (0.27-0.32 Pt). Gluten-based and dairy-based substitutes
had higher impacts (0.45-0.52 Pt).
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The biggest impact of the chicken meal (1) was associated with energy protein crops growing for chicken feed (37%).
Chicken growing added 25% of the impact and slaughtering – 2%. Transportation was responsible for 8% of impacts dis-
tributed along the whole supply chain. Frying at the consumer on the electrical stove was responsible for 26% or 0.156 Pt
(similar for all the products). Other components and additives had a cumulative impact of 2%.
Dairy-based meal (2) had a more diverse contribution impacts. The biggest impact came from energy used for frying at
the consumer (30%); processing and refrigeration (10%). The main ingredients acquisition also affected the system consid-
erably – 35% of overall impact were caused by production of egg protein (17%), oat hull fiber (10%) and skimmed milk
(8%). Higher diversity of ingredients with relatively high mass caused the high impact of transportation (16%). Other com-
ponents and additives have a cumulative impact of 9% (Fig. 5).
Lab-grown meat (3) affected the environment essentially due to the energy consumption used for the medium cultivation
and meat growing (75%). Final product frying resulted in 6% of the overall impact. The urea used for cyanobacteria cultiva-
tion had an impact of 16%. Other ingredients and components of product life cycle were responsible for 3% of the impact.
Impact distribution of insect production (4) was associated with two main factors: energy use for frying (50%) and for
processing (5%); and main feeding ingredients – cereal mix (15%) and carrots (13%). Transportation resulted in 10% of the
impact. Other factors were responsible for 7% of the impact.
Impacts of gluten-based substitute components (5) were assigned similar to dairy-based analogue. The highest impact
was caused by energy use at consumer stage (36%) and at product processing (13%). Wheat growing and harvesting took
around 40% of the overall impact. Transportation and other ingredients were of minor importance (7% for transportation
and 4% for others).
Energy used for frying (58%) and processing (18%) had the highest influence on the impact from soymeal-based substi-
tute (6). Soy meal was a by-product of bioenergy production, which was responsible for 12% of the impact. Transportation
was responsible for 5% of the overall impact. Other components accumulated 7% of the impact.
The production of mycoprotein-based substitute (7) was associated with high energy demand (45% of impact for pro-
cessing and 25% for frying at consumer), components production (10% for egg protein and 11% for nitrogen fertilizer) and
transportation (8%). Other components did not have a considerably high impact.
4. Discussion
As a part of the discussion, we performed a few sensitivity analyses to verify the variability of the results. A number of
parameters were changed to identify changes in environmental impacts connected to the selection of functional unit or as-
sessment methodologies.
4.1. Energy allocation (alternative FU equal to 3.75 MJ energetic value of final product)
The main comparison of meat and meat substitutes was based on the mass of the foods. Some authors could argue that it
is not an essential basis for food comparison as the differences in nutritional value could be significant (Schau and Fet 2008;
Roy et al. 2009). The basic function of food for people is energy supply required to maintain the organism functioning
(however, it is not the only function). That’s why, this study considered an alternative FU (3.75 calorific energy value) to
evaluate the possible impact variations when the comparison was based on basic aggregated nutritional function.
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Alternative analysis (with the same methods used, but alternative energy based FU) indicated that lab-grown meat had
the highest environmental impact (Fig. 6) similar to the main analysis (0.85 Pt). The second highest impact was noted for
the mycoprotein-based meal (0.57 Pt). Dairy-based and gluten-based substitutes had the lowest impacts (~ 0.17 Pt). The
chicken meat had 0.19 Pt. The other meat substitutes had medium environmental impacts without notable differences be-
tween them (~ 0.29 Pt).
4.2. PDCAAS corrected weight (alternative FU equal to 0.3 kg of digested proteins)
As energy calorific content is a simple, aggregated value it does not reflect the full spectrum of nutritional values. In or-
der to take a more nutritional aggregated approach an alternative FU of 0.3 kg of digested proteins was considered. Results
indicated (Fig. 7) that the lab-grown substitute had the highest impact (3.19 Pt). Mycoprotein-based and gluten-based meals
shared second place (1.8 Pt and 1.5 Pt), followed by dairy-based (1.2 Pt) and insect-based (0.8 Pt) substitutes. The lowest
impacts were assigned after chicken (0.6 Pt) and soy-based meat (0.52 Pt).
4.3. IMPACT 2002+ Methodology
Even though we applied recent integrated midpoint and endpoint impact methodology, the results could have been af-
fected due to the selection of one methodology (Guinée et al. 2011). Therefore, results were checked for consistency with
the application of IMPACT 2002+ methodology, which provides results for main midpoint impacts and aggregated data for
endpoint categories. Main study FU (1 kg of ready to eat product) was tested.
With alternative analysis results were distributed in similar to the main study order: lab-grown substitute had the highest
impact (8.86 mPt), insect-based and soymeal-based substitutes had the lowest impact (1-1.2 mPt). Other meals had the me-
dium impacts (1.9-2.2 mPt). Even though the integrated results distribution pattern is similar (Fig. 8), they cannot be com-
pared to the results of the main study. But the midpoint results of the main categories are comparable (included in table 2).
4.4. Comparison of LCA results with published data and their analysis.
Most results of the study were the same order of magnitude as previously published work. As the most published data
reviewed the impacts at levels of midpoint impact categories, we performed the comparison based on main characterization
results (Table 2). The results of main FU assessment with ReCiPe and IMPACT 2002+ methodologies were included in the
comparison. The results highlighted higher impacts for climate change (lab grown meat, gluten-based and mycoprotein-
based meat analogues), land use (gluten-based meat) and energy use (mycoprotein-based meat and chicken meat) compar-
ing to available data in literature. Such differentiations could be explained with inclusion of additional stages and resources
(transportation, frying and cooling at consumer) comparing to the other studies (Blonk et al. 2008; Tuomisto and de Mattos
2011; Tuomisto and Roy 2012; Deng et al. 2013), as results of contribution analysis indicated that frying at consumer was
responsible for about 33% of impact on average. It is accounted for the larger portion of environmental impacts for low-
impacting meat substitutes (50% for insect-based and 58% for soybean based) and for minor influence of highly impacting
alternatives (6% for lab-grown meat). The comparison of this study results with literature data was complicated due to the
variations in system boundaries. This study relied on a product from cradle (feed or raw material production) to plate (cook-
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ing at the consumer). System boundaries of other studies were based on approaches from cradle to gate: as unprocessed
weight at farm gate (Nemecek et al. 2001; Pelletier 2008; Cederberg et al. 2009; Alig et al. 2012; Oonincx and de Boer
2012), dead weight at slaughterhouse (Williams et al. 2006a; Williams et al. 2006b), product at processor gate (Ellingsen
and Aanondsen 2006; Blonk et al. 2008; Dalgaard et al. 2008; Tuomisto and de Mattos 2011; Tuomisto and Roy 2012;
Wiedemann et al. 2012; Deng et al. 2013), product at retail (Katajajuuri et al. 2008; Head et al. 2011) or further processed
product at processing gate (Van Huis et al. 2013). Moreover, environmental performance data of meat substitutes were
varying very considerably in literature, which made the comparison not reliable.
Land use change (LUC) impacts were not included in main study, as most of the crops, used as raw materials of substi-
tutes are not characterized as those having LUC (Milà i Canals et al. 2013). The comparison was based on average world
data and therefore in most cases LUC were not observed for crops at a global level. At the same time such crops as maize,
soya, carrots and palm oil, used for meat and substitutes production, were responsible for LUC at global levels. LUC im-
pacts would add additional GHG amounts to those presented in Table 2. Dairy and insect-based substitutes would add 0.27
kg CO2eq. to climate change category due to LUC. This would not change their relative position in comparison. The Chick-
en meat was responsible for additional 0.8 kg CO2eq. per FU. In this case, it became the second less sustainable product
among compared (FU 1 kg). However, it would not affect the performance of chicken meat with alternative FU. Soymeal
substitute was responsible for additional 1.08 kg CO2eq. due to LUC. Taking into account the overall GHG emissions by
soymeal substitute (2.65-2.78 kg CO2eq.) it was a significant change (more than a quarter). However, it would not affect the
overall comparative performance of soymeal-based substitute, leaving it among the most sustainable.
In order to indicate the possible influence of selected method of assessment (ReCiPe), we also performed an analysis
with other available methodologies (IMPACT 2002+; ILCD 2011 Midpoint; CML-IA baseline V3.00/EU25+3, 2000). The
results indicated similar rates. They were in the ranges indicated in Table 2. The greatest impact is reflected in categories of
climate change (global warming), fossil depletion (non-renewable energy consumption) and particulate inorganic formation
(respiratory inorganics). For some products (chicken, dairy-based and gluten-based) land use category was responsible for
5-10% of impact (FU 1 kg). Therefore, a decrease in energy consumption and non-renewable energy use could significantly
decrease the environmental impact (climate change and fossil energy categories) of compared products.
The variations of results due to the different FU and methodologies indicated that soymeal-based meat substitute is a
more sustainable alternative (at a current technology development level). Its performance, however, could be further im-
proved if the production of the substitute would be performed close to the soy growing agricultural regions. Chicken meat
and insect-based meat substitute performed worse than soy-meal substitute but better than the other alternatives.
The worst environmental performance was noted for lab-grown meat followed by mycoprotein meat substitute due to the
higher consumption of energy. Lowering that consumption with further technologies development would decrease their
negative impact. It is especially evident to lab-grown meat technology, which functions today at lab scale only (Tuomisto
and de Mattos 2011). However, the technological development and adaptation is also possible for other meat substitutes as
well (such as insect-based). Taking into account the need for additional protein sources, which will be more sustainable than
conventional meat, the ongoing LCA analysis of their development would be helpful to indicate the “hotspots” at the devel-
opment stage of products.
We selected mass-based FU as a basis for the main comparison, which aimed to present the equivalent of mass portions
at the consumer. However, the nutritional qualities of compared products were not equal. That’s why the comparison of two
alternative FU (based on food energy and protein digestibility) was included as a part of sensitivity analysis. Food energy is
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an integrated value of products, which is derived from food carbohydrates, fats and proteins. It reflects a function of supply-
ing an organism with energy to sustain its metabolism and movements. Therefore, the equal energy content of different
products was a basis for one FU. The other FU reflected the main aspect of meat foods consumption. The main function of
meat consumption is recognized for its protein content (Jiménez-Colmenero et al. 2001). The content of proteins and their
digestibility varies among meats and meat substitutes. Supplying a consumer with the same equivalent of digested proteins
was the basis for second alternative FU selection. At the same time, we acknowledge that energy and protein content is not
reflecting a complete spectrum of meat nutritional values. It is not reflecting differentiations in the qualities of amino-acid
contents, amounts of vitamins, fat and fatty acids etc. Further assessments, which indicate nutritional value differentiations,
based on integrated single nutritional FU would be a good approach to follow.
Selected meat and meat substitute products have different levels of technology development. Industrial chicken produc-
tion is a highly efficient and has a long history of technology development. Meat substitutes, based on dairy products, my-
coprotein, soymeal and gluten, are presented at industrial production scales, but their production could be further improved
and adjusted. They are on the market of meat substitutes’ production rather recently comparing to the chicken production.
Although, the mentioned substitutes and chicken production are assigned to technology readiness level (TRL) 9 (European
Commission 2014). The third group of lab-grown meat and insect-based meat substitute was considered at the lab scale
(limitation owing to the availability of data). It is not produced industrially yet and assigned with TRL 4. However, the per-
formance of lab-scale technologies could be improved dramatically in the nearest future while efficient production of chick-
en would not probably change. At the same time, the development and improvement of different technologies are not a
straight forward process. It strongly depends on production structural components (type of technology, production comple x-
ity) and system components (research interests, market availability) (Zschieschang et al. 2012). For example, insect-based
meat substitutes would probably rely on existing developed technologies for texturized vegetable products and , therefore,
could be introduced to the market faster than lab-grown meat. For the last product, the production is complicated by the
need to develop technologies for all the stages of production. The predictability of data changes, as well as LCA results with
scale up and improvement of technologies is a complex problem, which wasn’t set as an objective for this study, but would
be a good approach for further research.
5. Conclusions and recommendations
The analysis included three functional units (FU). The first FU was mass-based and represented as 1 kg of a ready-to-eat
meal based on chicken or analyzed meat substitutes. The results showed the highest impact for lab-grown meat (3), which
had been foreseen owing to the early stage of technology development. The high impact was explained due to the high e n-
ergy demand for the medium and meat growing processes. Second highest impacting products were mycoprotein-based (7)
and chicken (1), which was associated with high energy demands (7) and agricultural feed growing activities (1). The study
showed the lowest impact for insect-based (4) and soymeal-based (6) substitutes, which explained with the use of effective
processing and growing technologies and by-products use and side streams utilization. Dairy-based (2) and gluten-based (5)
meals had a medium impact as they had higher demands (compared to chicken) for transportation and energy for the prod-
uct processing.
The second FU was associated with leveling according to the food energy level (3.75 MJ energy content of fried ready-
to-eat meal based on chicken or analyzed meat substitutes). The sensitivity analysis showed considerable changes of results
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in the environmental performance of products. As in the main FU study lab-grown meat (3) had a leading impact and myco-
protein-based analogue (7) was the second one. The best performance was indicated for chicken (1), dairy-based (2) and
gluten-based (5) substitutes. Soymeal-based (6) and insect-based analogues (4) had medium impacts.
The third FU reflected the function of supplying a consumer with the equal amount of digested proteins (0.3 kg dry mat-
ter). The results indicated the worst performance for lab-grown meat (3), followed by mycoprotein-based analogue (7),
making these two substitutes the least sustainable choice at a given level of technologies development. The best performers
were soymeal (6), insect (4) analogues and chicken (1). Gluten (5) and dairy-based (2) substitutes had medium impacts. In
most cases, soymeal-based and insect-based substitutes perform at low or medium levels of environmental impact, which
indicates their potential for being more sustainable meat alternatives. So, the FU in meat substitute comparison studies
played an important role, which should be considered in the selection of comparison basis.
The comparison of the results with literature data was not indicative, taking into account high literature data variability
(system boundaries, FU, allocation). Further studies of evolving meat substitutes’ production technologies are needed. In the
best “ideal case,” it is needed to perform the comparison of different meat substitutes in the same production conditions
with analysis based solely on field data. Performed analysis did not indicate all the alternative emerging meat substitutes
(algae-based, egg-based etc.) which might have a better environmental performance than indicated options.
The article also raised an important question of a functional unit for meat substitutes’ comparison. Changes of the FU al-
tered results quite dramatically, and, therefore, the development of a FU which would reflect the complete integrative nutri-
tional function of meat substitute is needed. It is obvious, that meat substitutes have different nutritional profiles and, there-
fore, nutritional value. At the same time, different aspects of nutritional quality (protein and amino-acid content, vitamins,
fat and fatty acids etc.) vary in different proportion in meat substitutes. Therefore, it is necessary to develop a complex nu-
tritional value estimate, which would reflect the qualities of meat and meat substitutes for further studies.
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Tables
Table 1. Main inputs in the production of meals used in the study (from cradle to plate)
Product
Resources used per FU (1 kg of ready to eat product)
Main ingredients
Electricity,
MJd,g,
Tap water,
kgd
Transport,
kgkmd,h
Otherp
(1) Chicken
1 kg chickena
49.78*
16.3*
850*
-
(2) Dairy-basedk
6 kg skimmed milkb
12.27*
4.2*
360*
0.84 kg oat hull fiberc
(3) Lab-grownl
1 kg uread
103.5
420
110
-
(4) Insect-basedm
0.8 kg
carrotsd
10.762f
1.34f
128.5
0.57 kg grain mix (rye, wheat,
barley)d;
0.048 kg oat hull fiberc
(5) Gluten-basede
1.622 kg wheat
graind
8.94
0.954
141.1
0.15 kg oat hull fiberc
(6) Soymeal-basedn
0.27 kg soy meald
10.002f
0.73f
2791*
0.15 kg oat hull fiberc
(7) Myco-protein-
basedo
3 kg molasses from
sugar beetd
21.32
40
215.45
0.069 kg nitrogen fertilizerd;
0.04 kg egg white
a from a supermarket (LCA Food DK), based on live chick-
en for slaughterhouse (Ecoinvent 3 database)
b from dairy (LCA Food DK), water, electricity and heat
inputs are changed (Ecoinvent 3 database)
c by-product of oat cereals production, includes 2,3 m2 of
arable land occupation, use of 0.023 kg of nitrogen, 0.0048
kg of phosphate and 0.0143 kg of potassium fertilizers. 0.95
MJ of energy for 1 kg production (LCA Food DK, and
Ecoinvent 3 database)
d based on a product from Ecoinvent 3 database
e (van Zeist et al. 2012; Deng et al. 2013)
f data from DIL e.V. are included
g (Foster et al. 2006)
h assumed resources transported 50 km to assembly and su-
permarket, 10 km from a supermarket to the consumer
(McEachern and Warnaby 2006)
i assumed, 20 g of oil needed to fry 0.5 kg of product
j (PYR Ltd 2014)
k (Berlin 2002; Blonk et al. 2008; Head et al. 2011)
l (Tuomisto and Mattos 2010; Tuomisto and Roy 2012)
m (Oonincx and de Boer 2012; Van Huis et al. 2013)
n (Berk 1992; Dalgaard et al. 2008)
o (Raats 2007; Finnigan et al. 2010)
p Table 1 does not include the data similar for all scenarios
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Table 2. The comparison of main characterization results of the study with literature data.
Product
Climate Change, kg CO2 eq. / 1 kg
(FU)
Land Use/Occupation, m2 / 1 kg (FU)
Non-renewable Energy Use, MJ / 1 kg
(FU)
This
study
Literature data
This
study
Literature data
This
study
Literature data
(1)
Chicken
5.2-
5.82
1.3-
1.4
(Katajajuuri et al.
2008; Pelletier 2008;
Cederberg et al.
2009)
3.85-
3.89
2.1-
5.0
(Alig et al. 2012)
51.64-
63.4
1.3-
14.9
(Williams et al. 2006a;
Williams et al. 2006b;
Katajajuuri et al. 2008;
Pelletier 2008)
1.6-
2.4
(Alig et al. 2012;
Wiedemann et al.
2012)
12.8-
20.4
At processing gate
(Wiedemann et al.
2012)
1.5-
5.5
(Williams et al.
2006a; Williams et
al. 2006b)
2.2-
7.3
(Williams et al. 2006a;
Williams et al. 2006b)
17.3-
26.9
(Alig et al. 2012)
54
(Ellingsen and
Aanondsen 2006)
(2) Dairy-
based
4.38-
4.95
3.79-
6.2
(Blonk et al. 2008;
Head et al. 2011)
3.32-
3.41
2.94-
3.1
(Blonk et al. 2008;
Head et al. 2011)
48.79-
59.1
55.5
(Blonk et al. 2008)
(3) Lab-
grown
23.9-
24.64
1.8-
2.3
(Tuomisto and de
Mattos 2011;
Tuomisto and Roy
2012)
0.39-
0.77
0.18-
0.23
(Tuomisto and de Mat-
tos 2011; Tuomisto
and Roy 2012)
290.7-
373
25.2-
31.8
(Tuomisto and de Mat-
tos 2011)
10
Proteins (Tuomisto
and Roy 2012)
31700
(Tuomisto and Roy
2012)
(4) Insect-
based
2.84-
3.02
2.7
Fresh insects
(Oonincx and de
Boer 2012);
1.5-
1.52
3.6
Fresh insects (Oonincx
and de Boer 2012)
32.0-
40.4
34
Fresh insects (Oonincx
and de Boer 2012)
20
Proteins (Van Huis
et al. 2013)
18
Proteins (Van Huis et
al. 2013)
170
Proteins (Van Huis et
al. 2013)
(5) Gluten-
based
3.59-
4.03
1.55
Gluten powder
(Deng et al. 2013)
5.5-
5.82
2.07
Gluten powder (Deng
et al. 2013)
39.7-
49.2
1.4-1.7
Wheat (Nemecek et al.
2001)
2500
Edible wheat (Tuomis-
to and Roy 2012)
(6)
Soymeal-
based
2.65-
2.78
2.54-
3.72
Tofu (Head et al.
2011)
1.06-
1.44
1.95-
2.49
Tofu (Head et al.
2011)
27.78-
36.9
1.5-2.3
Soy (Pelletier et al.
2008)
0.34-
0.9
Soy meal (Dalgaard
et al. 2008)
3.0-
3.6
Soy meal (Dalgaard et
al. 2008)
3000
Edible soy (Tuomisto
and Roy 2012)
(7) Myco-
protein-
based
5.55-
6.15
2.4-
2.6
(Blonk et al. 2008;
Head et al. 2011)
0.79-
0.84
0.41-
1.2
(Blonk et al. 2008;
Head et al. 2011)
60.07-
76.8
38.0
(Blonk et al. 2008)
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Figure captions
Fig. 1. Generalized system boundaries of the study
Fig. 2. Products comparison midpoint characterization factors (from cradle to plate)
Fig. 3. Products comparison endpoint characterization factors (from cradle to plate)
Fig. 4. Single score product comparison FU 1 kg of ready to use product (from cradle to plate)
Fig. 5. Contribution of main life cycle stages to overall impact of the products (FU 1 kg)
Fig. 6. Single score alternative FU (3.75 MJ of food energy) product comparison (from cradle to plate)
Fig. 7. Single score alternative FU (0.3 kg of digested proteins) product comparison (from cradle to plate)
Fig. 8. Single score product comparison FU 1 kg of ready to use product (from cradle to plate) with IMPACT 2002+ meth-
odology
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Figures
Fig. 1. Generalized system boundaries of the study
Smetana, S., Mathys, A., Knoch, A. et al. Int J Life Cycle Assess (2015) 20: 1254. doi:10.1007/s11367 -015-0931-6
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Fig. 2. Products comparison midpoint characterization factors (from cradle to plate)
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Fig. 3. Products comparison endpoint characterization factors (from cradle to plate)
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Fig. 4. Single score product comparison FU 1 kg of ready to use product (from cradle to plate)
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Fig. 5. Contribution of main life cycle stages to overall impact of the products (FU 1 kg)
Smetana, S., Mathys, A., Knoch, A. et al. Int J Life Cycle Assess (2015) 20: 1254. doi:10.1007/s11367 -015-0931-6
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Fig. 6. Single score alternative FU (3.75 MJ of food energy) product comparison (from cradle to plate)
Smetana, S., Mathys, A., Knoch, A. et al. Int J Life Cycle Assess (2015) 20: 1254. doi:10.1007/s11367 -015-0931-6
23
https://link.springer.com/article/10.1007/s11367-015-0931-6
Fig. 7. Single score alternative FU (0.3 kg of digested proteins) product comparison (from cradle to plate)
Smetana, S., Mathys, A., Knoch, A. et al. Int J Life Cycle Assess (2015) 20: 1254. doi:10.1007/s11367 -015-0931-6
24
https://link.springer.com/article/10.1007/s11367-015-0931-6
Fig. 8. Single score product comparison FU 1 kg of ready to use product (from cradle to plate) with IMPACT 2002+ meth-
odology
