Comparison of individual food products may underestimate the underlying environmental impacts

Comparison of individual food products may underestimate the underlying environmental impacts | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparison of individual food products may underestimate the underlying environmental impacts Venla Kyttä, Merja Saarinen, Marja Roitto, Hanna L. Tuomisto This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4532942/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Life cycle assessment (LCA) is commonly used to compare the environmental impacts of products with similar functions. Multifunctional processes are usually handled by allocation, permitting the analysis of results for a single product. In this study, instead of only comparing animal source foods with other alternatives, we compared dairy cattle, beef cattle, pork, cultured meat and tofu production at the system level in terms of climate change, land use and fossil resource scarcity impacts. Here, we first present the theoretical background to the system expansion method in attributional LCA. Then, the method is implemented by comparing dairy cattle, beef cattle, pork, cultured meat and tofu systems, which are standardised to include equal functions. Since animal production systems generate inedible by-products that find utility as feeds, fertilizers, and energy sources, we enhance comparability by including the alternative production of these by-products. The system-level results obtained through system expansion are then compared with economically allocated product results. The assessment revealed that the system-level results differed noticeably from the allocated product-level results, as the dairy system had the highest environmental impacts in all the assessed categories. This contradicts previous attributional assessments that primarily relied on allocation between by-products, particularly concerning beef derived from beef cattle. Although the system expansion method possesses certain limitations, we deem it appropriate for providing a novel perspective when comparing multifunctional systems. By maintaining the connections between products originating from the same production system, this assessment approach offers valuable insights into the diverse functionalities provided by different systems. Figures Figure 1 Figure 2 Figure 3 1. Introduction Life cycle assessment (LCA) is commonly used to compare the environmental impacts of different foods[1]. Several attributional LCAs of foods have demonstrated the greater greenhouse gas emissions and land use of animal source foods compared to other foods, and the need to decrease the consumption of animal-source foods is therefore recommended[2]. However, the edible parts of bovine animals constitute only 45–47% of their live weight[3,4]. The other parts of the animals, accounting for more than a half of their mass, are used for various purposes, such as pet foods, animal feeds, leather goods, and the production of biogas, biodiesel, and fertilizers[5,6]. A decrease in beef consumption due to the transition towards plant- and novel food-based diets would therefore potentially require alternative ways to produce these materials[7]. In livestock production systems, there are often many by-products (or side flows) that interconnect product systems and may result in other end products. However, inedible by-products from livestock production systems have only been considered in a few LCA studies on livestock products[5,8]. A harmonized method for allocating between by-products of animal origin has not yet been agreed upon by the LCA community, although some proposals have been made[3,9]. The LCA ISO standard ultimately instructs that allocation should be avoided whenever possible by dividing the process into sub-processes or by "expanding the product system to include the additional functions related to the co-products"[1]. Since animals cannot be divided into sub-processes, the inclusion of co-functions by expanding the system boundaries is an obvious way forward. Because products from multifunctional systems cannot be produced without additionally producing by-products, the use of system expansion would also represent the reality more accurately than allocation. This study aims to examine the feasibility of the system expansion method in attributional LCA when assessing the environmental impacts of animal source foods in comparison to plant-based and novel foods. Our specific objectives are to i) discuss and clarify the use of system expansion in attributional LCAs, ii) delineate the strengths and weaknesses of the method, and iii) compare the relative environmental impacts of animal source foods using system expansion and economic allocation methods. Rather than comparing individual animal source foods with other food products, our study compares all the functions derived from the dairy system with alternative systems that deliver the same functions. 2. Materials and Methods 2.1. SYSTEM EXPANSION Tillman et al.[10] introduced the concept of the ‘technological whole system’, according to which the demand for functions provided by a system is assumed to be stable, and all the physical products and processes that are affected by changes in demand are therefore included inside the system boundaries of an assessment. When comparing multiple systems, it is necessary to include similar functions, such as equivalent products or services fulfilling the same purposes (Figure 1). Therefore, additional functions may be added to the systems to ensure an equal functional unit (FU) and expand the FU to cover the multifunctionality of a system. This concept forms the basis for system expansion, which is further described in ISO technical report 14049[11]. However, the term "system expansion" is used for two different and opposite methods: actual system expansion by including all products involved in multifunctionality in the FU, and substitution, where multi-product systems are narrowed down to single-product functional units by excluding avoidable burdens associated with co-products from the FU[12]. The substitution method is sometimes used in attributional assessments, although it has been argued to be suitable primarily for consequential models[13]. If the allocation guidelines provided in the ISO standard are strictly followed, system expansion is implemented by expanding systems to include all functions provided by the system under study[12,14]. In this literal interpretation, system expansion as substitution is not feasible, and functions can only be added to systems. The average market datasets of products can be used as the extra functions when expanding systems. For instance, the ecoinvent[15] database offers market datasets representing a product's consumption mix in a specific region. When using market mix datasets, it is necessary to exclude by-products (e.g., tallow) from the market dataset used as an alternative (e.g., the market for biodiesel) because these products are already included in one system and should not be included in the compared system as a market dataset. If a product's market dataset cannot be defined or does not exist, single products can be used. 2.2. ASSESSED SYSTEMS The comparison of the dairy production system with beef, pork, cultured meat, and tofu production was conducted based on the principles of system expansion outlined in ISO technical report 14049. In system expansion, the functional unit (FU) includes all functions derived from the systems[12]. For this study, the FU encompassed all materials derived from dairy cattle, beef cattle, pork production, cultured meat production, and tofu production. Rather than comparing single food products, the entire production systems were compared, using the dairy production system as a reference due to its generation of the highest number and volume of by-products. To align the functions of the beef (beef cattle), pork, cultured meat, and tofu production systems with the dairy system, missing functions were added to these systems in the form of alternative products that could serve as substitutes for the dairy system's by-products. The proportion of by-products derived from bovine animals and their subsequent uses were directly obtained from a meat company, while the processing of by-products and yields of final products were modeled based on literature sources. The compared systems were standardized to include one kilogram of meat (and edible offal) or tofu for human consumption. System expansion was carried out until the point of substitutability, where the products are ready for use. Therefore, the use phase and end-of-life treatment were not included in the assessment. Manure was also excluded from the assessment since it typically circulates within the systems as a fertilizer. System expansion was applied solely to foreground processes, specifically the production of main products, as including the multifunctionality of every background process in every system would lead to endlessly growing systems. Background processes, such as the processing of by-products and production of inputs, were included as structured in databases. 2.3. COMPARISON TO ALLOCATED PRODUCT-LEVEL RESULTS To examine the differences between comparing allocated product-level results and system-level results, the impacts of beef meat (and edible offal) from dairy and beef cattle, pork meat (and edible offal), tofu, and cultured meat were assessed using economic allocation. For beef and pork meat, the default economic allocation factors provided by FEDIAF[16] were employed, specifically 92.9% for beef and 98.9% for pork meat. The analysis of cultured meat's price revealed substantial variation based on production technology[17,18]. The study utilized the estimated affordability threshold of $25 kg-1 for cultured meat in the early market stage[17]. The economic values of lactic acid and tofu were obtained from the ecoinvent database[15]. 2.4. DATA AND DATA SOURCES The systems were modelled with the ecoinvent database (apos) 3.6 database[15] in OpenLCA 1.10.2 software by using the ReCiPe 2016 Midpoint (H) (V1.1) impact assessment method[19]. Due to the availability of market activity data with global coverage, the ecoinvent database[15] was used to model all the processes. The unallocated dataset for dairy production was utilized, which accounts for the production of 0.0299 kg of cattle (live weight) for slaughtering per kilogram of milk. For beef production, a market dataset was created by removing the share of dairy production from the market dataset of cattle for slaughtering. The slaughtering process for bovine animals was modeled based on data from Mogensen et al.[4] (S2). Global data from the ecoinvent database[15] were employed for pork primary production, and the slaughtering phase was modeled based on data from Reckmann et al.[20] (Table S2). Pork generates similar by-products to beef but with differing amounts (as presented in Table S1). These by-products undergo further processing, similar to beef products. Food-grade bones from both beef and pork production were assumed to be used for meat and bone meal (MBM) based on data obtained from a food company. The environmental impacts of cultured meat production were derived from Tuomisto et al.[21]. The study utilized the Cultured meat combined (CMC) scenario, which represents larger-scale production. To represent global production, the scenario was modified by adjusting the energy consumption using global electricity data from the ecoinvent database[15]. In cultured meat production, 0.766 kg of lactic acid by-product is generated per kilogram of meat, and this amount was included in the other systems. Data on tofu production from soybeans and the process yields for the by-products okara and whey (used for feed) were obtained from the ecoinvent database[15]. 2.5. BY-PRODUCTS AND THEIR ALTERNATIVES The processing of by-products and the production of replacement products were sourced from the ecoinvent database[15] whenever available. For processes not available in the database, literature sources were consulted, and global data from the ecoinvent database[15] were used for modeling. The supplementary material provides comprehensive details on the remodeled processes and the classification of by-products into different categories. The processing of hides into leather was modeled based on adapted data from Joseph and Nithya[22] (S3), which encompassed stages of preservation, tanning, finishing, and waste management. Due to variations in the qualities of textiles and the unsuitability of the textile market dataset as an alternative for leather, a market dataset for suspension polymerized PVC (artificial leather) was employed as a proxy for leather alternatives. Inedible offal (category 3 material) and category 2 material are used in pet food and animal feed. No processing before the point of substitution was assumed for pet food, as the ingredients used are fresh by-products[16]. Considering that the function of these products is to provide nutrition and the nutrient content of by-products displays considerable variation, the substituting amounts were aligned based on protein content. The protein contents of 3.1% (ecoinvent) and 0.5% (average)[23] were used for the tofu by-products okara and whey, respectively. The market process for alternatives such as pet food and fur animal feed was created by subtracting beef and pork by-products from the average pet food ingredients presented by FEDIAF[16] (S5). Category 3 and 2 by-products not used for pet food undergo rendering, resulting in 25% meat and bone meal (MBM) and 17% tallow[15]. MBM is employed as a fertilizer, with nutrient content of 8% N and 5% P[24]. As alternatives for these nutrients, global market datasets for N fertilizer and P fertilizer from the ecoinvent database[15] were utilized. The tallow from rendering is further processed into biodiesel, which was modeled based on data presented by López et al.[25] (S6). A market dataset for diesel (ecoinvent) was used as an alternative product for biodiesel, as no market datasets for biofuels were available, and the share of renewables in global fuel consumption is relatively low, around 7% in 2020[26]. Category 1 animal by-product material is treated with anaerobic digestion, yielding biogas and digestate. The nutrient content of digestate from the anaerobic digestion of slaughterhouse waste was assumed to be 0.76% N and 0.12% P[27]. The global market datasets for N fertiliser and P fertiliser were used as alternatives for these nutrients. The impacts from the anaerobic digestion process were assumed to be similar to the treatment of biowaste by anaerobic digestion (ecoinvent) per treated kilogram of feedstock. The global market dataset for natural gas was used as an alternative for biogas. Lactic acid, which is formed as a by-product of cultured meat production, has commercial value as a raw material in industrial processes. Hence, the equivalent amount of lactic acid was added to dairy, beef, pork and tofu systems. A market dataset for lactic acid was used as an alternative for the lactic acid formed in cultured meat production. A summary of the systems used as FUs is presented in Table 1. Table 1. Compared systems of dairy cattle, beef cattle, pork, cultured meat and tofu, including the products produced by each system and the products added to each system to make the systems equivalent. The amounts of pet food and fur animal feed alternatives differ from the outputs of the beef system due differences in the protein content. MBM = meat and bone meal, N = nitrogen, P= phosphorus Main system Meat/tofu, kg Milk, kg a Leather, kg b Pet food/ feed, kg c MBM, N g d MBM, P g e Biodiesel, kg f Biogas, methane m 3 g Digestate, N g d Digestate, P g e Lactic acid, kg h Dairy cattle 1.00 70 0.02 0.54 6 4 0.052 0.033 1.2 0.2 Added products 0.77 Beef cattle 1.00 0.02 0.54 6 4 0.052 0.033 1.2 0.2 Added products 70 0.77 Pork 1.00 0.13 4 3 0.034 0.021 0.8 0.1 Added products 70 0.02 0.51 2 1 0.018 0.012 0.4 0.1 0.77 Cultured meat 1.00 0.77 Added products 70 0.02 0.67 6 4 0.052 0.033 1.2 0.2 Tofu 1.00 0.34 Added products 70 0.02 0.33 6 4 0.052 0.033 1.2 0.2 0.77 Alternative product added: a market for soybean beverage (ecoinvent), b market for PVC (ecoinvent), c market dataset for pet food (created), d market for N fertiliser (ecoinvent), e market for P fertiliser (ecoinvent), f market for diesel (ecoinvent), g market for natural gas (ecoinvent), h market for lactic acid (ecoinvent) 2.6. SENSITIVITY AND UNCERTAINTY ANALYSES Since the utilization rate of edible parts of animals and the use of the by-products differ from those presented in the literature, presumably due differences in the characteristics of cattle and processing technologies, alternative scenarios regarding these data were tested (Table 2). The processing of by-products was assumed to be similar to the baseline beef scenario, except that gelatine production from food grade bones was added to this model, whereas the bones were used to make MBM in the baseline model. In this scenario, the pet food yield from tofu production and gelatine from pork bones exceeds the amount derived from beef. Hence, the proportion of excess beef system products was subtracted from the tofu and pork systems for the alternative products. Table 2. By-product amounts and uses of beef in earlier studies. Average derived from the values presented in other studies[3,4,6]. The by-product categories (Cat.) are explained in the supplementary material (section 1.3.). Product Use % of live weight in earlier studies % of live weight in this study Meat & edible offal Food 45% 47.9% Food grade bones Gelatine 5% - Hides Leather 6% 3.6% Cat. 3 material Animal feed/ pet food 15% * 26% Cat. 2 material Meat and bone meal, Biodiesel 8% 14.8% Cat. 1 material Biogas 20% ** 7.6% Shrinkage/loss 1% 0% * Cat. 3 fat from Gac et al.[3] included ** Special risk material included The processing of gelatine was modeled based on conventional production methods using data adapted from Ma et al.[28]. Several options for gelatine alternatives exist, but due to the lack of data, gelatine was assumed to be substituted with pectin extracted from pomegranate peels, with pectin being equivalent to gelatine in terms of mass. Pectin production was modeled based on the data presented in the study by Shinde et al.[29] using mass allocation between products. No impacts were allocated to pomegranate peels from pomegranate production. For uncertainty analyses, a Monte Carlo analysis with 100 runs was performed in OpenLCA software for all the models. 3. Results 3.1. The impacts of expanded product systems The dairy system had the highest impacts in all the assessed impact categories, having over six times higher land use impacts and over two times higher global warming impacts (Figure 2). Including the processing of animal by-products into different end products, such as leather or pet food, hardly increased the impacts of the animal systems, whereas adding the alternative products notably increased the impacts (Figure 2). In pork, cultured meat and tofu systems, the milk alternative accounted for the majority of the impacts. 3.2. Comparison of allocated product-level results with system-level results Comparison of the relative allocated product-level results for meat led to contrasting climate impacts for beef from dairy cattle and beef from beef cattle (Figure 3). In addition, the relative impacts of other products had notable changes, especially in terms of land use. 3.3. Sensitivity of impacts to by-product quantities and uses The amounts and uses of beef by-products derived from companies were compared with those presented in the literature, and the compared systems of pork, cultured meat and tofu were altered to be equivalent. These changes in the uses and amounts of by-products especially affected the results for fossil resource scarcity, but the relative order of the products remained the same (Figure 4). 4. Discussion 4.1. Results of expanded systems and comparison with allocated results The results of our study show that a dairy cattle system producing an equal amount of milk and meat as a beef cattle system extended with milk replacement has higher environmental impacts in terms of global warming, land use, and fossil resource scarcity. This is contrary to previous attributional assessments based on allocation between by-products (e.g., in Poore & Nemecek[2]). Our findings suggest that milk replacements have the potential to significantly reduce environmental impacts related to land use and greenhouse gas emissions. An important confounding factor and source of uncertainty in the interpretation of the results is the highly different nutritional quality of milk and milk substitutes, which is ignored here, as the focus was on beef and its substitute protein products. It is also noteworthy that the ecoinvent data used as a proxy for plant-based milks in this study contains considerably lower impacts for soy milk than, for example, the impacts presented in Clune et al.[30]. However, using the climate impacts reported by Clune et al.[30] would still result in dairy cattle having the highest impacts. A previous LCA study that assessed the environmental impacts of animal by-product alternatives reported similar results to our study[5]. However, due to differences in by-product categories, system boundaries, and methods, the comparison between the two studies is only approximate. Luske and Blonk[5] found that most greenhouse gas emissions arise from the alternative production of fats (substituted with palm oil) and pet food (substituted with chicken), whereas in terms of land use, the urea used as a substitute for different types of rendered meals had the highest impacts. The impacts of other materials, such as fuels, were found to be low. 4.2. System expansion as a modeling method for multifunctional systems Our results indicate that allocation methods inevitably separate physical systems, treating products separately even though they cannot be produced without each other. Therefore, product-level results may be misleading, implying that beef produced from the dairy cattle has lower impacts than beef from beef cattle. For example, according to the product-level results, the lowest emissions would result from choosing beef from dairy cattle and milk from plant-based alternatives, but such a combination would not be physically possible. Therefore, expanded system boundaries and system-level results provide a more realistic representation of the physical reality. System expansion can also help prevent the loss of impacts between different product systems' life cycles and avoid potential double counting in general-level LCAs, providing valuable information for decision-making processes. Double counting may occur when combining results from different studies without harmonizing the methodological basis, particularly when impacts from beef production are allocated solely to beef in one study while industries using the by-products also allocate impacts to their raw materials from beef production in the LCA study for derived products. System expansion takes into consideration the volume, quality, and usage of by-products, which are challenging to address with a single allocation method. Economic allocation, for example, considers the economic value of by-products, and large volumes of materials used as raw materials for other products may lack economic value or even have negative value in the case of animal by-products. Economic value is often a criterion for distinguishing between products and waste[31]. The ISO standard defines a product as "any good or service" and waste as "substances or objects which the holder intends or is required to dispose of." Therefore, comparison assessments conducted by expanding system boundaries differ from economically allocated product-level results, especially when the system produces significant volumes of by-products (e.g., beef) or by-products with relatively high economic value (e.g., tofu). As the definition of output products already involves an allocation choice, this choice could follow the allocation steps provided in the ISO standard[1]. When defining which outputs are products and which are waste, causal criteria could be used, considering whether the presence or absence of the material directly affects some product on the market (e.g., if there is no feedstock for anaerobic digestion, no biogas can be produced). Although the method used in this study treats the compared systems more equally and provides a broader perspective on production systems, it does not capture the consequential impacts of choosing one system over another and should not be used for such decision-making purposes. Thomassen et al.[32] argued that system expansion is difficult to implement in attributional modelling, since there is no change in demand, unlike in consequential models that are based on assessing the impact of a change, and thus avoided burdens cannot be defined. Undeniably, consequential features cannot entirely be avoided in this type of modelling. Nevertheless, since market datasets are used, with the absence of a product provided by the compared system, system expansion captures the attributional impact of the actual consumption situation. There are no changes in demand or ‘what if’ assumptions, as in consequential models. While both allocation methods and system expansion involve methodological choices and thus introduce uncertainty, it is argued that system expansion more accurately represents the industrial reality[33]. The most critical step in implementing the system expansion method is defining the functions and alternative products to be added to comparative product systems, considering that a product may serve multiple functions, and a mixture of products may be needed to replace all functions (market of functions substituted with different markets of functions). System expansion also has a significant limitation when applied in attributional LCA, as it is impractical to expand the system boundaries endlessly to include all processes related to the studied system, especially in complex systems. In this study, the expansion was only implemented in foreground processes, while the remaining processes were included as structured in databases. Consequently, possible allocation issues in background processes were not addressed. Also, when comparing novel foods, such as cultured meat in this study, it is important to consider the time frame since production technologies constantly evolve. It is not meaningful to compare the environmental impacts of novel foods with those of conventional foods assessed decades before the existence of novel food scenarios. Therefore, prospective LCA should also be considered for conventional products to enable meaningful comparisons. The expanded system results notably differ from allocated results, especially for product systems that require considerable volumes of added alternative products. We believe that system expansion is applicable when comparing multifunctional systems that contain by-products with variations in terms of volume, quality, and usage. Unlike allocation methods, system expansion maintains the linkages between products derived from the same production system, providing valuable insights into the diverse functions performed by different systems. This this type of perspective can bring valuable information regarding the various functions provided by different systems. It may therefore provide a solid basis for actors in production chains to understand the real-life environmental impacts associated with raw materials from animal production by-products, not only in theory. However, the method has a few notable limitations. It is impossible to determine the impacts of single products, and the implementation for each process in a life cycle is not feasible. Therefore, conventional attributional LCA studies are likely to require allocation to achieve the study goals. Nor can the method presented in this study replace consequential models, as the approaches of these methods are fundamentally different. In summary, while system expansion offers valuable insights into multifunctional systems and the environmental impacts of by-products, it is not a comprehensive solution and must be used in conjunction with other methods depending on the research goals and system characteristics. Continued investigation and development are required to refine and validate the use of system expansion in various contexts. Declarations Acknowledgements/FUNDING The authors gratefully acknowledge the data obtained from companies and funding from the Finnish Association of Academic Agronomists, the August Johannes and Aino Tiura Agricultural Research Foundation and the Foundation for Nutrition Research. Competing interests The authors have no relevant financial or non-financial interests to disclose. Data availability All relevant data are included in the article and/or its supplementary information files. Author contributions V.K. conducted the methodology, analysis and wrote the manuscript. V.K. and H.L.T. designed the study and H.L.T. M.S. and M.R. reviewed the manuscript. H.L.T. and M.S. supervised the research. References ISO 14040:2006, 2006. Environmental management. Life cycle assessment. Principles and framework ISO 14040:2006.. Poore, J., Nemecek, T., 2018. Reducing food’s environmental impacts through producers and consumers. Science. 360, 987–992. https://doi.org/10.1126/science.aaq0216 Gac, A., Lapasin, C., Laspière, P.T., Guardia, S., Ponchant, P., Chevillon, P., Nassy, G., 2014. Co-products from meat processing: the allocation issue, in: Proceedings of the 9th International Conference on Life Cycle Assessment in the Agri-Food Sector LCA Food 2014.. San Francisco, USA. ACLCA, Vashon, WA, USA, pp. 438–442. Mogensen, L., Kristensen, T., Nielsen, N.I., Spleth, P., Henriksson, M., Swensson, C., Hessle, A., Vestergaard, M., 2015. Greenhouse gas emissions from beef production systems in Denmark and Sweden. Livest. Sci. 174, 126–143. https://doi.org/10.1016/j.livsci.2015.01.021 Luske, B., Blonk, H., 2009. Milieueffecten van dierlijke bijproducten 1–79. Opio, C., Gerber, P., Mottet, A., Falcucci, A., Tempio, G., MacLeod, M., Vellinga, T., Henderson, B., Steinfeld, H., 2013. Animal Production and Health Division – A global life cycle assessment. FAO, Rome. Lafarga, T., Hayes, M., 2014. Bioactive peptides from meat muscle and by-products: Generation, functionality and application as functional ingredients. Meat Sci. https://doi.org/10.1016/j.meatsci.2014.05.036 Mogensen, L., Nguyen, T.L.T., Madsen, N.T., Pontoppidan, O., Preda, T., Hermansen, J.E., 2016. Environmental impact of beef sourced from different production systems – focus on the slaughtering stage: input and output. J. Clean. Prod. 133, 284–293. https://doi.org/10.1016/j.jclepro.2016.05.105 Chen, X., Wilfart, A., Puillet, L., Aubin, J., 2017. A new method of biophysical allocation in LCA of livestock co-products: modeling metabolic energy requirements of body-tissue growth. Int. J. Life Cycle Assess. 22, 883–895. https://doi.org/10.1007/s11367-016-1201-y Tillman, A.M., Ekvall, T., Baumann, H., Rydberg, T., 1994. Choice of system boundaries in life cycle assessment. J. Clean. Prod. 2, 21–29. https://doi.org/10.1016/0959-652694.90021-3 ISO, 2012. Technical report 14049. Environmental management — Life cycle assessment — Illustrative examples on how to apply ISO 14044 to goal and scope definition and inventory analysis. Heijungs, R., Allacker, K., Benetto, E., Brandão, M., Guinée, J., Schaubroeck, S., Schaubroeck, T., & Zamagni, A., 2021. System Expansion and Substitution in LCA: A Lost Opportunity of ISO 14044 Amendment 2. Frontiers in Sustainability, 0, 40. https://doi.org/10.3389/FRSUS.2021.692055 Brander, M., Wylie, C., 2011. The use of substitution in attributional life cycle assessment. Greenhouse Gas Measurement and Management 1, 161–166. https://doi.org/10.1080/20430779.2011.637670 Pelletier, N., Ardente, F., Brandão, M., De Camillis, C., & Pennington, D., 2015. Rationales for and limitations of preferred solutions for multi- 58 functionality problems in LCA: is increased consistency possible? Int J Life Cycle Assess 20, 74–86. https://doi.org/10.1007/s11367-014-0812-4 Wernet, G., Bauer, C., Steubing, B., Reinhard, J., Moreno-Ruiz, E., Weidema, B., 2016. The Ecoinvent database version 3. Int. J. Life Cycle Assess. FEDIAF, 2018. Product Environmental Footprint Category Rules. Prepared Pet Food for Cats and Dogs. CE Delft, 2021. TEA of cultivated meat. Future projections of different scenarios. Humbird, D., 2020. Scale-Up Economics for Cultured Meat: Techno-Economic Analysis and Due Diligence 104. Huijbregts, M.A.J., Steinmann, Z.J.N., Elshout, P.M.F., Stam, G., Verones, F., Vieira, M., Zijp, M., Hollander, A., van Zelm, R., 2017. ReCiPe2016: a harmonised life cycle impact assessment method at midpoint and endpoint level. Int. J. Life Cycle Assess. 22, 138–147. https://doi.org/10.1007/s11367-016-1246-y Reckmann, K., Traulsen, I., Krieter, J., 2013. Life Cycle Assessment of pork production: A data inventory for the case of Germany. Livest. Sci. 157, 586–596. https://doi.org/10.1016/j.livsci.2013.09.001 Tuomisto, H.L., Allan, S.J., Ellis, M.J., 2022. Prospective life cycle assessment of a bioprocess design for cultured meat production in hollow fiber bioreactors. Sci. Tot. Environ. 851, 158051. https://doi.org/10.1016/j.scitotenv.2022.158051 Joseph, K., Nithya, N., 2009. Material flows in the life cycle of leather. J. Clean. Prod. 17, 676–682. https://doi.org/10.1016/j.jclepro.2008.11.018 Chua, J.Y., Liu, S.Q., 2019. Soy whey: More than just wastewater from tofu and soy protein isolate industry. Trends Food Sci. Technol. https://doi.org/10.1016/j.tifs.2019.06.016 Kivelä, J., Chen, L., Muurinen, S., Kivijärvi, P., Hintikainen, V., Helenius, J., 2015. Effects of meat bone meal as fertilizer on yield and quality of sugar beet and carrot. Agric. Food Sci. 24, 68–83. López, D.E., Mullins, J.C., Bruce, D.A., 2010. Energy life cycle assessment for the production of biodiesel from rendered lipids in the United States. Ind. Eng. Chem. Res. 49, 2419–2432. https://doi.org/10.1021/ie900884x BP, 2021. Statistical Review of World Energy 2021. https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2021-full-report.pdf Delin, S., 2015. Fertilizer value of phosphorus in different residues. Soil Use Manag. 32, 17–26. https://doi.org/10.1111/sum.12227 Ma, Y., Zeng, X., Ma, X., Yang, R., Zhao, W., 2019. A simple and eco-friendly method of gelatin production from bone: One-step biocatalysis. Clean. Prod. 209, 916–926. https://doi.org/10.1016/j.jclepro.2018.10.313 Shinde, P.N., Mandavgane, S.A., Karadbhajane, V., 2020. Process development and life cycle assessment of pomegranate biorefinery. Sci. Pollut. Res. 25785–25793. https://doi.org/10.1007/s11356-020-08957-0 Clune, S., Crossin, E., Verghese, K., 2017. Systematic review of greenhouse gas emissions for different fresh food categories. J. Clean. Prod. 140, 766–783. https://doi.org/10.1016/j.jclepro.2016.04.082 European Commission. 2010.. International Reference Life Cycle Data System ILCD. Handbook - General guide for Life Cycle Assessment – Detailed guidance. In Constraints. https://doi.org/10.2788/38479 Thomassen, M.A., Dalgaard, R., Heijungs, R., De Boer, I., 2008. Attributional and consequential LCA of milk production. Int. J. Life Cycle Assess. 13, 339–349. https://doi.org/10.1007/s11367-008-0007-y Jung, J., Von Der Assen, N., Bardow, A., 2013. Comparative LCA of multi-product processes with non-common products: A systematic approach applied to chlorine electrolysis technologies. J. Life Cycle Assess. 18, 828–839. https://doi.org/10.1007/s11367-012-0531-7 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4532942","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":536853628,"identity":"52999f8d-8c1e-445e-a081-a9602038de96","order_by":0,"name":"Venla Kyttä","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYHACxgMMDAlgxoMHIAbzwQaCesBaeNgYmA0SQFrYEonXwiYB0ZKAX7nB8d4DB34wpCXul29+VpHYlibHwMaM3xaDM+cSDvYw5CT2sLGZ3UhsyzFmYGPEr0VyRo7BAR6GCqAWBpCWisQG+UYCWua/MTj4B6yF/VsBUEt9AyFb+CV4DA7zgB3GY8YAdFgCQYfx8+QYHJYxSDPuOZZTLJFwLs2wjZAWNvYzhg/fVCTLtjcf3/jhQ1myPD8b+wO8WiDAgMERbjIbEerBwJ5YhaNgFIyCUTACAQAwxESYMbG91QAAAABJRU5ErkJggg==","orcid":"","institution":"University of Helsinki","correspondingAuthor":true,"prefix":"","firstName":"Venla","middleName":"","lastName":"Kyttä","suffix":""},{"id":536853629,"identity":"32f0075e-9d61-419a-999f-a390faabc3db","order_by":1,"name":"Merja Saarinen","email":"","orcid":"","institution":"Natural Resources Institute Finland","correspondingAuthor":false,"prefix":"","firstName":"Merja","middleName":"","lastName":"Saarinen","suffix":""},{"id":536853630,"identity":"3d893d48-f1de-4d47-a025-4bbd05c56689","order_by":2,"name":"Marja Roitto","email":"","orcid":"","institution":"University of Helsinki","correspondingAuthor":false,"prefix":"","firstName":"Marja","middleName":"","lastName":"Roitto","suffix":""},{"id":536853631,"identity":"2bc84ac5-284b-4c2c-b138-6d53f833896c","order_by":3,"name":"Hanna L. Tuomisto","email":"","orcid":"","institution":"University of Helsinki","correspondingAuthor":false,"prefix":"","firstName":"Hanna","middleName":"L.","lastName":"Tuomisto","suffix":""}],"badges":[],"createdAt":"2024-06-05 09:27:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4532942/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4532942/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94718031,"identity":"721f0559-e625-4a98-9463-8942de525fcb","added_by":"auto","created_at":"2025-10-30 04:21:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":17649,"visible":true,"origin":"","legend":"\u003cp\u003eThe principles of adding processes to make compared systems include the provision of equivalent functions. Adapted from Tillman et al.[10].\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4532942/v1/5b77862b726f4e5518e2fbe6.png"},{"id":94730009,"identity":"dabaff3e-ae16-4241-a6f5-e69f5b602f57","added_by":"auto","created_at":"2025-10-30 07:05:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":469893,"visible":true,"origin":"","legend":"\u003cp\u003eThe carbon footprint (kg CO\u003csub\u003e2\u003c/sub\u003e eq.), land use (m\u003csup\u003e2\u003c/sup\u003ea crop eq.) and fossil resource scarcity (kg oil eq.) of expanded dairy cattle, beef cattle, pork, cultured meat and tofu systems (expanded FU presented in Table 1). Main production system illustrates the unallocated impacts arising from the production system of the main product, and other processes the impacts arising from further processing of the by-products or impacts of producing an equivalent alternative product. Rendering of animal by-products yields MBM fertilisers and tallow for biodiesel production. The error bars represent the standard deviation derived with 100 runs of Monte Carlo analysis. MBM\u0026nbsp;= meat and bone meal, N\u0026nbsp;= nitrogen, P\u0026nbsp;= phosphorus\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4532942/v1/1407fb9e9051dd673b4b9df8.png"},{"id":94718030,"identity":"cc03a3c6-a2d1-4e08-ac5b-673a497ca159","added_by":"auto","created_at":"2025-10-30 04:21:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":134604,"visible":true,"origin":"","legend":"\u003cp\u003eRelative carbon footprint, land use and fossil resource scarcity for the extended systems (Figure. 2, FU in Table 1) and for FU of 1 kg of tofu, cultured meat, pork (meat and edible offal) and beef (meat and edible offal) from dairy cattle and beef cattle, when using economic allocation.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4532942/v1/9bc7cd878d7f5ad82117cbcb.png"},{"id":94731209,"identity":"6d2580cf-2780-44ba-bd13-d027fb047cd8","added_by":"auto","created_at":"2025-10-30 07:07:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1086116,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4532942/v1/d48ca62f-c777-4ce2-9090-999269bde1f8.pdf"},{"id":94718033,"identity":"231dd1b6-99bc-4fa3-b022-8d1b163bdf14","added_by":"auto","created_at":"2025-10-30 04:21:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":265064,"visible":true,"origin":"","legend":"","description":"","filename":"SystemexpansionSupplementarymaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4532942/v1/673f3dd3d100d7ba75508e10.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of individual food products may underestimate the underlying environmental impacts","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLife cycle assessment (LCA) is commonly used to compare the environmental impacts of different foods[1]. Several attributional LCAs of foods have demonstrated the greater greenhouse gas emissions and land use of animal source foods compared to other foods, and the need to decrease the consumption of animal-source foods is therefore recommended[2]. However, the edible parts of bovine animals constitute only 45–47% of their live weight[3,4]. The other parts of the animals, accounting for more than a half of their mass, are used for various purposes, such as pet foods, animal feeds, leather goods, and the production of biogas, biodiesel, and fertilizers[5,6]. A decrease in beef consumption due to the transition towards plant- and novel food-based diets would therefore potentially require alternative ways to produce these materials[7]. In livestock production systems, there are often many by-products (or side flows) that interconnect product systems and may result in other end products. However, inedible by-products from livestock production systems have only been considered in a few LCA studies on livestock products[5,8]. A harmonized method for allocating between by-products of animal origin has not yet been agreed upon by the LCA community, although some proposals have been made[3,9]. The LCA ISO standard ultimately instructs that allocation should be avoided whenever possible by dividing the process into sub-processes or by \"expanding the product system to include the additional functions related to the co-products\"[1]. Since animals cannot be divided into sub-processes, the inclusion of co-functions by expanding the system boundaries is an obvious way forward. Because products from multifunctional systems cannot be produced without additionally producing by-products, the use of system expansion would also represent the reality more accurately than allocation.\u003c/p\u003e\n\u003cp\u003eThis study aims to examine the feasibility of the system expansion method in attributional LCA when assessing the environmental impacts of animal source foods in comparison to plant-based and novel foods. Our specific objectives are to i) discuss and clarify the use of system expansion in attributional LCAs, ii) delineate the strengths and weaknesses of the method, and iii) compare the relative environmental impacts of animal source foods using system expansion and economic allocation methods. Rather than comparing individual animal source foods with other food products, our study compares all the functions derived from the dairy system with alternative systems that deliver the same functions.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e2.1. \u0026nbsp; \u0026nbsp; \u0026nbsp;SYSTEM EXPANSION\u003c/p\u003e\n\u003cp\u003eTillman et al.[10] introduced the concept of the \u0026lsquo;technological whole system\u0026rsquo;, according to which the demand for functions provided by a system is assumed to be stable, and all the physical products and processes that are affected by changes in demand are therefore included inside the system boundaries of an assessment. When comparing multiple systems, it is necessary to include similar functions, such as equivalent products or services fulfilling the same purposes (Figure 1). Therefore, additional functions may be added to the systems to ensure an equal functional unit (FU) and expand the FU to cover the multifunctionality of a system. This concept forms the basis for system expansion, which is further described in ISO technical report 14049[11].\u003c/p\u003e\n\u003cp\u003eHowever, the term \u0026quot;system expansion\u0026quot; is used for two different and opposite methods: actual system expansion by including all products involved in multifunctionality in the FU, and substitution, where multi-product systems are narrowed down to single-product functional units by excluding avoidable burdens associated with co-products from the FU[12]. The substitution method is sometimes used in attributional assessments, although it has been argued to be suitable primarily for consequential models[13]. If the allocation guidelines provided in the ISO standard are strictly followed, system expansion is implemented by expanding systems to include all functions provided by the system under study[12,14].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this literal interpretation, system expansion as substitution is not feasible, and functions can only be added to systems. The average market datasets of products can be used as the extra functions when expanding systems. For instance, the ecoinvent[15] database offers market datasets representing a product\u0026apos;s consumption mix in a specific region. When using market mix datasets, it is necessary to exclude by-products (e.g., tallow) from the market dataset used as an alternative (e.g., the market for biodiesel) because these products are already included in one system and should not be included in the compared system as a market dataset. If a product\u0026apos;s market dataset cannot be defined or does not exist, single products can be used.\u003c/p\u003e\n\u003cp\u003e2.2. \u0026nbsp; \u0026nbsp; \u0026nbsp;ASSESSED SYSTEMS\u003c/p\u003e\n\u003cp\u003eThe comparison of the dairy production system with beef, pork, cultured meat, and tofu production was conducted based on the principles of system expansion outlined in ISO technical report 14049. In system expansion, the functional unit (FU) includes all functions derived from the systems[12]. For this study, the FU encompassed all materials derived from dairy cattle, beef cattle, pork production, cultured meat production, and tofu production. Rather than comparing single food products, the entire production systems were compared, using the dairy production system as a reference due to its generation of the highest number and volume of by-products. To align the functions of the beef (beef cattle), pork, cultured meat, and tofu production systems with the dairy system, missing functions were added to these systems in the form of alternative products that could serve as substitutes for the dairy system\u0026apos;s by-products. The proportion of by-products derived from bovine animals and their subsequent uses were directly obtained from a meat company, while the processing of by-products and yields of final products were modeled based on literature sources. The compared systems were standardized to include one kilogram of meat (and edible offal) or tofu for human consumption.\u003c/p\u003e\n\u003cp\u003eSystem expansion was carried out until the point of substitutability, where the products are ready for use. Therefore, the use phase and end-of-life treatment were not included in the assessment. Manure was also excluded from the assessment since it typically circulates within the systems as a fertilizer. System expansion was applied solely to foreground processes, specifically the production of main products, as including the multifunctionality of every background process in every system would lead to endlessly growing systems. Background processes, such as the processing of by-products and production of inputs, were included as structured in databases.\u003c/p\u003e\n\u003cp\u003e2.3. \u0026nbsp; \u0026nbsp; \u0026nbsp;COMPARISON TO ALLOCATED PRODUCT-LEVEL RESULTS\u003c/p\u003e\n\u003cp\u003eTo examine the differences between comparing allocated product-level results and system-level results, the impacts of beef meat (and edible offal) from dairy and beef cattle, pork meat (and edible offal), tofu, and cultured meat were assessed using economic allocation. For beef and pork meat, the default economic allocation factors provided by FEDIAF[16] were employed, specifically 92.9% for beef and 98.9% for pork meat. The analysis of cultured meat\u0026apos;s price revealed substantial variation based on production technology[17,18]. The study utilized the estimated affordability threshold of $25 kg-1 for cultured meat in the early market stage[17]. The economic values of lactic acid and tofu were obtained from the ecoinvent database[15].\u003c/p\u003e\n\u003cp\u003e2.4. \u0026nbsp; \u0026nbsp; \u0026nbsp;DATA AND DATA SOURCES\u003c/p\u003e\n\u003cp\u003eThe systems were modelled with the ecoinvent database (apos) 3.6 database[15]\u0026nbsp;in OpenLCA 1.10.2 software by using the ReCiPe 2016 Midpoint (H) (V1.1) impact assessment method[19]. Due to the availability of market activity data with global coverage, the ecoinvent database[15]\u0026nbsp;was used to model all the processes. The unallocated dataset for dairy production was utilized, which accounts for the production of 0.0299 kg of cattle (live weight) for slaughtering per kilogram of milk. For beef production, a market dataset was created by removing the share of dairy production from the market dataset of cattle for slaughtering. The slaughtering process for bovine animals was modeled based on data from Mogensen et al.[4] (S2).\u003c/p\u003e\n\u003cp\u003eGlobal data from the ecoinvent database[15]\u0026nbsp;were employed for pork primary production, and the slaughtering phase was modeled based on data from Reckmann et al.[20] (Table S2). Pork generates similar by-products to beef but with differing amounts (as presented in Table S1). These by-products undergo further processing, similar to beef products. Food-grade bones from both beef and pork production were assumed to be used for meat and bone meal (MBM) based on data obtained from a food company.\u003c/p\u003e\n\u003cp\u003eThe environmental impacts of cultured meat production were derived from Tuomisto et al.[21]. The study utilized the Cultured meat combined (CMC) scenario, which represents larger-scale production. To represent global production, the scenario was modified by adjusting the energy consumption using global electricity data from the ecoinvent database[15]. In cultured meat production, 0.766 kg of lactic acid by-product is generated per kilogram of meat, and this amount was included in the other systems. Data on tofu production from soybeans and the process yields for the by-products okara and whey (used for feed) were obtained from the ecoinvent database[15].\u003c/p\u003e\n\u003cp\u003e2.5. \u0026nbsp; \u0026nbsp; \u0026nbsp;BY-PRODUCTS AND THEIR ALTERNATIVES\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe processing of by-products and the production of replacement products were sourced from the ecoinvent database[15]\u0026nbsp;whenever available. For processes not available in the database, literature sources were consulted, and global data from the ecoinvent database[15]\u0026nbsp;were used for modeling. The supplementary material provides comprehensive details on the remodeled processes and the classification of by-products into different categories.\u003c/p\u003e\n\u003cp\u003eThe processing of hides into leather was modeled based on adapted data from Joseph and Nithya[22] (S3), which encompassed stages of preservation, tanning, finishing, and waste management. Due to variations in the qualities of textiles and the unsuitability of the textile market dataset as an alternative for leather, a market dataset for suspension polymerized PVC (artificial leather) was employed as a proxy for leather alternatives.\u003c/p\u003e\n\u003cp\u003eInedible offal (category 3 material) and category 2 material are used in pet food and animal feed. No processing before the point of substitution was assumed for pet food, as the ingredients used are fresh by-products[16]. Considering that the function of these products is to provide nutrition and the nutrient content of by-products displays considerable variation, the substituting amounts were aligned based on protein content. The protein contents of 3.1% (ecoinvent) and 0.5% (average)[23] were used for the tofu by-products okara and whey, respectively. The market process for alternatives such as pet food and fur animal feed was created by subtracting beef and pork by-products from the average pet food ingredients presented by FEDIAF[16] (S5).\u003c/p\u003e\n\u003cp\u003eCategory 3 and 2 by-products not used for pet food undergo rendering, resulting in 25% meat and bone meal (MBM) and 17% tallow[15]. MBM is employed as a fertilizer, with nutrient content of 8% N and 5% P[24]. As alternatives for these nutrients, global market datasets for N fertilizer and P fertilizer from the ecoinvent database[15]\u0026nbsp;were utilized. The tallow from rendering is further processed into biodiesel, which was modeled based on data presented by L\u0026oacute;pez et al.[25] (S6). A market dataset for diesel (ecoinvent) was used as an alternative product for biodiesel, as no market datasets for biofuels were available, and the share of renewables in global fuel consumption is relatively low, around 7% in 2020[26].\u003c/p\u003e\n\u003cp\u003eCategory 1 animal by-product material is treated with anaerobic digestion, yielding biogas and digestate. The nutrient content of digestate from the anaerobic digestion of slaughterhouse waste was assumed to be 0.76% N and 0.12% P[27]. The global market datasets for N fertiliser and P fertiliser were used as alternatives for these nutrients. The impacts from the anaerobic digestion process were assumed to be similar to the treatment of biowaste by anaerobic digestion (ecoinvent) per treated kilogram of feedstock. The global market dataset for natural gas was used as an alternative for biogas.\u003c/p\u003e\n\u003cp\u003eLactic acid, which is formed as a by-product of cultured meat production, has commercial value as a raw material in industrial processes. Hence, the equivalent amount of lactic acid was added to dairy, beef, pork and tofu systems. A market dataset for lactic acid was used as an alternative for the lactic acid formed in cultured meat production. A summary of the systems used as FUs is presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e \u003cem\u003eCompared systems of dairy cattle, beef cattle, pork, cultured meat and tofu, including the products produced by each system and the products added to each system to make the systems equivalent. The amounts of pet food and fur animal feed alternatives differ from the outputs of the beef system due differences in the protein content. MBM\u0026nbsp;= meat and bone meal, N\u0026nbsp;= nitrogen,\u0026nbsp;P= phosphorus\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"919\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eMain system\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMeat/tofu, kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMilk,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ekg \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLeather,\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;kg \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePet food/ feed, kg \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMBM, N g \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMBM, P g \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBiodiesel, kg \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBiogas, methane m\u003csup\u003e3 g\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDigestate, N g \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDigestate, P g \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLactic acid, kg \u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDairy cattle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Added products\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeef cattle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Added products\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePork\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Added products\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCultured meat\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Added products\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTofu\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Added products\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAlternative product added: \u003csup\u003ea\u003c/sup\u003e market for soybean beverage (ecoinvent), \u003csup\u003eb\u003c/sup\u003e market for PVC (ecoinvent), \u003csup\u003ec\u003c/sup\u003e market dataset for pet food (created), \u003csup\u003ed\u0026nbsp;\u003c/sup\u003emarket for N fertiliser (ecoinvent), \u003csup\u003ee\u003c/sup\u003e market for P fertiliser (ecoinvent),\u003csup\u003e\u0026nbsp;f\u003c/sup\u003e market for diesel (ecoinvent),\u003csup\u003e\u0026nbsp;g\u003c/sup\u003e market for natural gas (ecoinvent), \u003csup\u003eh\u003c/sup\u003e market for lactic acid (ecoinvent)\u003c/p\u003e\n\u003cp\u003e2.6. \u0026nbsp; \u0026nbsp; \u0026nbsp;SENSITIVITY AND UNCERTAINTY ANALYSES\u003c/p\u003e\n\u003cp\u003eSince the utilization rate of edible parts of animals and the use of the by-products differ from those presented in the literature, presumably due differences in the characteristics of cattle and processing technologies, alternative scenarios regarding these data were tested (Table 2). The processing of by-products was assumed to be similar to the baseline beef scenario, except that gelatine production from food grade bones was added to this model, whereas the bones were used to make MBM in the baseline model. In this scenario, the pet food yield from tofu production and gelatine from pork bones exceeds the amount derived from beef. Hence, the proportion of excess beef system products was subtracted from the tofu and pork systems for the alternative products.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eBy-product amounts and uses of beef in earlier studies. Average derived from the values presented in other studies[3,4,6]. The by-product categories (Cat.) are explained in the supplementary material (section 1.3.).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e% of live weight in earlier studies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e% of live weight in this study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMeat \u0026amp; edible offal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFood grade bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGelatine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLeather\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCat. 3 material\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAnimal feed/ pet food\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15% *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCat. 2 material\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMeat and bone meal, Biodiesel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCat. 1 material\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBiogas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20% **\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.6%\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eShrinkage/loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Cat. 3 fat from Gac et al.[3] included ** Special risk material included\u003c/p\u003e\n\u003cp\u003eThe processing of gelatine was modeled based on conventional production methods using data adapted from Ma et al.[28]. Several options for gelatine alternatives exist, but due to the lack of data, gelatine was assumed to be substituted with pectin extracted from pomegranate peels, with pectin being equivalent to gelatine in terms of mass. Pectin production was modeled based on the data presented in the study by Shinde et al.[29] using mass allocation between products. No impacts were allocated to pomegranate peels from pomegranate production.\u003c/p\u003e\n\u003cp\u003eFor uncertainty analyses, a Monte Carlo analysis with 100 runs was performed in OpenLCA software for all the models.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e3.1. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;The impacts of expanded product systems\u003c/p\u003e\n\u003cp\u003eThe dairy system had the highest impacts in all the assessed impact categories, having over six times higher land use impacts and over two times higher global warming impacts (Figure 2). Including the processing of animal by-products into different end products, such as leather or pet food, hardly increased the impacts of the animal systems, whereas adding the alternative products notably increased the impacts (Figure 2). In pork, cultured meat and tofu systems, the milk alternative accounted for the majority of the impacts.\u003c/p\u003e\n\u003cp\u003e3.2. \u0026nbsp; \u0026nbsp; \u0026nbsp; Comparison of allocated product-level results with system-level results\u003c/p\u003e\n\u003cp\u003eComparison of the relative allocated product-level results for meat led to contrasting climate impacts for beef from dairy cattle and beef from beef cattle (Figure 3). In addition, the relative impacts of other products had notable changes, especially in terms of land use.\u003c/p\u003e\n\u003cp\u003e3.3. \u0026nbsp; \u0026nbsp; \u0026nbsp; Sensitivity of impacts to by-product quantities and uses\u003c/p\u003e\n\u003cp\u003eThe amounts and uses of beef by-products derived from companies were compared with those presented in the literature, and the compared systems of pork, cultured meat and tofu were altered to be equivalent. These changes in the uses and amounts of by-products especially affected the results for fossil resource scarcity, but the relative order of the products remained the same (Figure 4).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e4.1. Results of expanded systems and comparison with allocated results\u003c/p\u003e\n\u003cp\u003eThe results of our study show that a dairy cattle system producing an equal amount of milk and meat as a beef cattle system extended with milk replacement has higher environmental impacts in terms of global warming, land use, and fossil resource scarcity. This is contrary to previous attributional assessments based on allocation between by-products (e.g., in Poore \u0026amp; Nemecek[2]). Our findings suggest that milk replacements have the potential to significantly reduce environmental impacts related to land use and greenhouse gas emissions. An important confounding factor and source of uncertainty in the interpretation of the results is the highly different nutritional quality of milk and milk substitutes, which is ignored here, as the focus was on beef and its substitute protein products. It is also noteworthy that the ecoinvent data used as a proxy for plant-based milks in this study contains considerably lower impacts for soy milk than, for example, the impacts presented in Clune et al.[30]. However, using the climate impacts reported by Clune et al.[30] would still result in dairy cattle having the highest impacts.\u003c/p\u003e\n\u003cp\u003eA previous LCA study that assessed the environmental impacts of animal by-product alternatives reported similar results to our study[5]. However, due to differences in by-product categories, system boundaries, and methods, the comparison between the two studies is only approximate. Luske and Blonk[5] found that most greenhouse gas emissions arise from the alternative production of fats (substituted with palm oil) and pet food (substituted with chicken), whereas in terms of land use, the urea used as a substitute for different types of rendered meals had the highest impacts. The impacts of other materials, such as fuels, were found to be low.\u003c/p\u003e\n\u003cp\u003e4.2. System expansion as a modeling method for multifunctional systems\u003c/p\u003e\n\u003cp\u003eOur results indicate that allocation methods inevitably separate physical systems, treating products separately even though they cannot be produced without each other. Therefore, product-level results may be misleading, implying that beef produced from the dairy cattle has lower impacts than beef from beef cattle. For example, according to the product-level results, the lowest emissions would result from choosing beef from dairy cattle and milk from plant-based alternatives, but such a combination would not be physically possible. Therefore, expanded system boundaries and system-level results provide a more realistic representation of the physical reality. System expansion can also help prevent the loss of impacts between different product systems' life cycles and avoid potential double counting in general-level LCAs, providing valuable information for decision-making processes. Double counting may occur when combining results from different studies without harmonizing the methodological basis, particularly when impacts from beef production are allocated solely to beef in one study while industries using the by-products also allocate impacts to their raw materials from beef production in the LCA study for derived products.\u003c/p\u003e\n\u003cp\u003eSystem expansion takes into consideration the volume, quality, and usage of by-products, which are challenging to address with a single allocation method. Economic allocation, for example, considers the economic value of by-products, and large volumes of materials used as raw materials for other products may lack economic value or even have negative value in the case of animal by-products. Economic value is often a criterion for distinguishing between products and waste[31]. The ISO standard defines a product as \"any good or service\" and waste as \"substances or objects which the holder intends or is required to dispose of.\" Therefore, comparison assessments conducted by expanding system boundaries differ from economically allocated product-level results, especially when the system produces significant volumes of by-products (e.g., beef) or by-products with relatively high economic value (e.g., tofu). As the definition of output products already involves an allocation choice, this choice could follow the allocation steps provided in the ISO standard[1]. When defining which outputs are products and which are waste, causal criteria could be used, considering whether the presence or absence of the material directly affects some product on the market (e.g., if there is no feedstock for anaerobic digestion, no biogas can be produced).\u003c/p\u003e\n\u003cp\u003eAlthough the method used in this study treats the compared systems more equally and provides a broader perspective on production systems, it does not capture the consequential impacts of choosing one system over another and should not be used for such decision-making purposes. Thomassen et al.[32] argued that system expansion is difficult to implement in attributional modelling, since there is no change in demand, unlike in consequential models that are based on assessing the impact of a change, and thus avoided burdens cannot be defined. Undeniably, consequential features cannot entirely be avoided in this type of modelling. Nevertheless, since market datasets are used, with the absence of a product provided by the compared system, system expansion captures the attributional impact of the actual consumption situation. There are no changes in demand or ‘what if’ assumptions, as in consequential models. While both allocation methods and system expansion involve methodological choices and thus introduce uncertainty, it is argued that system expansion more accurately represents the industrial reality[33].\u003c/p\u003e\n\u003cp\u003eThe most critical step in implementing the system expansion method is defining the functions and alternative products to be added to comparative product systems, considering that a product may serve multiple functions, and a mixture of products may be needed to replace all functions\u0026nbsp;(market of functions substituted with different markets of functions). System expansion also has a significant limitation when applied in attributional LCA, as it is impractical to expand the system boundaries endlessly to include all processes related to the studied system, especially in complex systems. In this study, the expansion was only implemented in foreground processes, while the remaining processes were included as structured in databases. Consequently, possible allocation issues in background processes were not addressed.\u003c/p\u003e\n\u003cp\u003eAlso, when comparing novel foods, such as cultured meat in this study, it is important to consider the time frame since production technologies constantly evolve. It is not meaningful to compare the environmental impacts of novel foods with those of conventional foods assessed decades before the existence of novel food scenarios. Therefore, prospective LCA should also be considered for conventional products to enable meaningful comparisons.\u003c/p\u003e\n\u003cp\u003eThe expanded system results notably differ from allocated results, especially for product systems that require considerable volumes of added alternative products. We believe that system expansion is applicable when comparing multifunctional systems that contain by-products with variations in terms of volume, quality, and usage. Unlike allocation methods, system expansion maintains the linkages between products derived from the same production system, providing valuable insights into the diverse functions performed by different systems. This this type of perspective can bring valuable information regarding the various functions provided by different systems. It may therefore provide a solid basis for actors in production chains to understand the real-life environmental impacts associated with raw materials from animal production by-products, not only in theory.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, the method has a few notable limitations. It is impossible to determine the impacts of single products, and the implementation for each process in a life cycle is not feasible. Therefore, conventional attributional LCA studies are likely to require allocation to achieve the study goals. Nor can the method presented in this study replace consequential models, as the approaches of these methods are fundamentally different.\u003c/p\u003e\n\u003cp\u003eIn summary, while system expansion offers valuable insights into multifunctional systems and the environmental impacts of by-products, it is not a comprehensive solution and must be used in conjunction with other methods depending on the research goals and system characteristics. Continued investigation and development are required to refine and validate the use of system expansion in various contexts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements/FUNDING\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the data obtained from companies and funding from the Finnish Association of Academic Agronomists, the August Johannes and Aino Tiura Agricultural Research Foundation and the Foundation for Nutrition Research.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003eData availability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll relevant data are included in the article and/or its supplementary information files.\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eV.K. conducted the methodology, analysis and wrote the manuscript. V.K. and H.L.T. designed the study and H.L.T. \u0026nbsp;M.S. and M.R. reviewed the manuscript. H.L.T. and M.S. supervised the research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eISO 14040:2006, 2006. Environmental management. Life cycle assessment. Principles and framework ISO 14040:2006..\u003c/li\u003e\n\u003cli\u003ePoore, J., Nemecek, T., 2018. Reducing food\u0026rsquo;s environmental impacts through producers and consumers. Science. 360, 987\u0026ndash;992. https://doi.org/10.1126/science.aaq0216\u003c/li\u003e\n\u003cli\u003eGac, A., Lapasin, C., Laspi\u0026egrave;re, P.T., Guardia, S., Ponchant, P., Chevillon, P., Nassy, G., 2014. Co-products from meat processing: the allocation issue, in: Proceedings of the 9th International Conference on Life Cycle Assessment in the Agri-Food Sector LCA Food 2014.. San Francisco, USA. ACLCA, Vashon, WA, USA, pp. 438\u0026ndash;442.\u003c/li\u003e\n\u003cli\u003eMogensen, L., Kristensen, T., Nielsen, N.I., Spleth, P., Henriksson, M., Swensson, C., Hessle, A., Vestergaard, M., 2015. Greenhouse gas emissions from beef production systems in Denmark and Sweden. Livest. Sci. 174, 126\u0026ndash;143. https://doi.org/10.1016/j.livsci.2015.01.021\u003c/li\u003e\n\u003cli\u003eLuske, B., Blonk, H., 2009. Milieueffecten van dierlijke bijproducten 1\u0026ndash;79.\u003c/li\u003e\n\u003cli\u003eOpio, C., Gerber, P., Mottet, A., Falcucci, A., Tempio, G., MacLeod, M., Vellinga, T., Henderson, B., Steinfeld, H., 2013. Animal Production and Health Division \u0026ndash; A global life cycle assessment. FAO, Rome.\u003c/li\u003e\n\u003cli\u003eLafarga, T., Hayes, M., 2014. Bioactive peptides from meat muscle and by-products: Generation, functionality and application as functional ingredients. Meat Sci. https://doi.org/10.1016/j.meatsci.2014.05.036\u003c/li\u003e\n\u003cli\u003eMogensen, L., Nguyen, T.L.T., Madsen, N.T., Pontoppidan, O., Preda, T., Hermansen, J.E., 2016. Environmental impact of beef sourced from different production systems \u0026ndash; focus on the slaughtering stage: input and output. J. Clean. Prod. 133, 284\u0026ndash;293. https://doi.org/10.1016/j.jclepro.2016.05.105\u003c/li\u003e\n\u003cli\u003eChen, X., Wilfart, A., Puillet, L., Aubin, J., 2017. A new method of biophysical allocation in LCA of livestock co-products: modeling metabolic energy requirements of body-tissue growth. Int. J. Life Cycle Assess. 22, 883\u0026ndash;895. https://doi.org/10.1007/s11367-016-1201-y\u003c/li\u003e\n\u003cli\u003eTillman, A.M., Ekvall, T., Baumann, H., Rydberg, T., 1994. Choice of system boundaries in life cycle assessment. J. Clean. Prod. 2, 21\u0026ndash;29. https://doi.org/10.1016/0959-652694.90021-3\u003c/li\u003e\n\u003cli\u003eISO, 2012. Technical report 14049. Environmental management \u0026mdash; Life cycle assessment \u0026mdash; Illustrative examples on how to apply ISO 14044 to goal and scope definition and inventory analysis.\u003c/li\u003e\n\u003cli\u003e Heijungs, R., Allacker, K., Benetto, E., Brand\u0026atilde;o, M., Guin\u0026eacute;e, J., Schaubroeck, S., Schaubroeck, T., \u0026amp; Zamagni, A., 2021. System Expansion and Substitution in LCA: A Lost Opportunity of ISO 14044 Amendment 2. Frontiers in Sustainability, 0, 40. https://doi.org/10.3389/FRSUS.2021.692055\u003c/li\u003e\n\u003cli\u003e Brander, M., Wylie, C., 2011. The use of substitution in attributional life cycle assessment. Greenhouse Gas Measurement and Management 1, 161\u0026ndash;166. https://doi.org/10.1080/20430779.2011.637670\u003c/li\u003e\n\u003cli\u003e Pelletier, N., Ardente, F., Brand\u0026atilde;o, M., De Camillis, C., \u0026amp; Pennington, D., 2015. Rationales for and limitations of preferred solutions for multi- 58 functionality problems in LCA: is increased consistency possible? Int J Life Cycle Assess 20, 74\u0026ndash;86. https://doi.org/10.1007/s11367-014-0812-4\u003c/li\u003e\n\u003cli\u003e Wernet, G., Bauer, C., Steubing, B., Reinhard, J., Moreno-Ruiz, E., Weidema, B., 2016. The Ecoinvent database version 3. Int. J. Life Cycle Assess.\u003c/li\u003e\n\u003cli\u003e FEDIAF, 2018. Product Environmental Footprint Category Rules. Prepared Pet Food for Cats and Dogs.\u003c/li\u003e\n\u003cli\u003e CE Delft, 2021. TEA of cultivated meat. Future projections of different scenarios.\u003c/li\u003e\n\u003cli\u003e Humbird, D., 2020. Scale-Up Economics for Cultured Meat: Techno-Economic Analysis and Due Diligence 104.\u003c/li\u003e\n\u003cli\u003e Huijbregts, M.A.J., Steinmann, Z.J.N., Elshout, P.M.F., Stam, G., Verones, F., Vieira, M., Zijp, M., Hollander, A., van Zelm, R., 2017. ReCiPe2016: a harmonised life cycle impact assessment method at midpoint and endpoint level. Int. J. Life Cycle Assess. 22, 138\u0026ndash;147. https://doi.org/10.1007/s11367-016-1246-y\u003c/li\u003e\n\u003cli\u003eReckmann, K., Traulsen, I., Krieter, J., 2013. Life Cycle Assessment of pork production: A data inventory for the case of Germany. Livest. Sci. 157, 586\u0026ndash;596. https://doi.org/10.1016/j.livsci.2013.09.001\u003c/li\u003e\n\u003cli\u003eTuomisto, H.L., Allan, S.J., Ellis, M.J., 2022. Prospective life cycle assessment of a bioprocess design for cultured meat production in hollow fiber bioreactors. Sci. Tot. Environ. 851, 158051. https://doi.org/10.1016/j.scitotenv.2022.158051\u003c/li\u003e\n\u003cli\u003eJoseph, K., Nithya, N., 2009. Material flows in the life cycle of leather. J. Clean. Prod. 17, 676\u0026ndash;682. https://doi.org/10.1016/j.jclepro.2008.11.018\u003c/li\u003e\n\u003cli\u003eChua, J.Y., Liu, S.Q., 2019. Soy whey: More than just wastewater from tofu and soy protein isolate industry. Trends Food Sci. Technol. https://doi.org/10.1016/j.tifs.2019.06.016\u003c/li\u003e\n\u003cli\u003eKivel\u0026auml;, J., Chen, L., Muurinen, S., Kivij\u0026auml;rvi, P., Hintikainen, V., Helenius, J., 2015. Effects of meat bone meal as fertilizer on yield and quality of sugar beet and carrot. Agric. Food Sci. 24, 68\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003eL\u0026oacute;pez, D.E., Mullins, J.C., Bruce, D.A., 2010. Energy life cycle assessment for the production of biodiesel from rendered lipids in the United States. Ind. Eng. Chem. Res. 49, 2419\u0026ndash;2432. https://doi.org/10.1021/ie900884x\u003c/li\u003e\n\u003cli\u003eBP, 2021. Statistical Review of World Energy 2021. https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2021-full-report.pdf\u003c/li\u003e\n\u003cli\u003eDelin, S., 2015. Fertilizer value of phosphorus in different residues. Soil Use Manag. 32, 17\u0026ndash;26. https://doi.org/10.1111/sum.12227\u003c/li\u003e\n\u003cli\u003eMa, Y., Zeng, X., Ma, X., Yang, R., Zhao, W., 2019. A simple and eco-friendly method of gelatin production from bone: One-step biocatalysis. Clean. Prod. 209, 916\u0026ndash;926. https://doi.org/10.1016/j.jclepro.2018.10.313\u003c/li\u003e\n\u003cli\u003eShinde, P.N., Mandavgane, S.A., Karadbhajane, V., 2020. Process development and life cycle assessment of pomegranate biorefinery. Sci. Pollut. Res. 25785\u0026ndash;25793. https://doi.org/10.1007/s11356-020-08957-0\u003c/li\u003e\n\u003cli\u003eClune, S., Crossin, E., Verghese, K., 2017. Systematic review of greenhouse gas emissions for different fresh food categories. J. Clean. Prod. 140, 766\u0026ndash;783. https://doi.org/10.1016/j.jclepro.2016.04.082\u003c/li\u003e\n\u003cli\u003eEuropean Commission. 2010.. International Reference Life Cycle Data System ILCD. Handbook - General guide for Life Cycle Assessment \u0026ndash; Detailed guidance. In Constraints. https://doi.org/10.2788/38479\u003c/li\u003e\n\u003cli\u003eThomassen, M.A., Dalgaard, R., Heijungs, R., De Boer, I., 2008. Attributional and consequential LCA of milk production. Int. J. Life Cycle Assess. 13, 339\u0026ndash;349. https://doi.org/10.1007/s11367-008-0007-y\u003c/li\u003e\n\u003cli\u003eJung, J., Von Der Assen, N., Bardow, A., 2013. Comparative LCA of multi-product processes with non-common products: A systematic approach applied to chlorine electrolysis technologies. J. Life Cycle Assess. 18, 828\u0026ndash;839. https://doi.org/10.1007/s11367-012-0531-7\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4532942/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4532942/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Life cycle assessment (LCA) is commonly used to compare the environmental impacts of products with similar functions. Multifunctional processes are usually handled by allocation, permitting the analysis of results for a single product. In this study, instead of only comparing animal source foods with other alternatives, we compared dairy cattle, beef cattle, pork, cultured meat and tofu production at the system level in terms of climate change, land use and fossil resource scarcity impacts. Here, we first present the theoretical background to the system expansion method in attributional LCA. Then, the method is implemented by comparing dairy cattle, beef cattle, pork, cultured meat and tofu systems, which are standardised to include equal functions. Since animal production systems generate inedible by-products that find utility as feeds, fertilizers, and energy sources, we enhance comparability by including the alternative production of these by-products. The system-level results obtained through system expansion are then compared with economically allocated product results. The assessment revealed that the system-level results differed noticeably from the allocated product-level results, as the dairy system had the highest environmental impacts in all the assessed categories. This contradicts previous attributional assessments that primarily relied on allocation between by-products, particularly concerning beef derived from beef cattle. Although the system expansion method possesses certain limitations, we deem it appropriate for providing a novel perspective when comparing multifunctional systems. By maintaining the connections between products originating from the same production system, this assessment approach offers valuable insights into the diverse functionalities provided by different systems.","manuscriptTitle":"Comparison of individual food products may underestimate the underlying environmental impacts","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 04:21:16","doi":"10.21203/rs.3.rs-4532942/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a2ec192f-a26c-4e01-9ec2-9dee21a57587","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-30T04:21:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 04:21:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4532942","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4532942","identity":"rs-4532942","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}