Valorizing Biodiesel and Bioethanol Side-Streams: Sustainability Potential Assessment through a Multicriteria Decision Analysis Framework and Appraisal of Valuable Compound Recovery Prospects

Citation: Macias Aragonés, M.; Ondrejíˇcková, P.; Ugarte Lodeiro, R.; Arroyo Torralvo, F. Valorizing Biodiesel and Bioethanol Side-Streams: Sustainability Potential Assessment through a Multicriteria Decision Analysis Framework and Appraisal of Valuable Compound Recovery Prospects. Energies 2023,16, 176. https://doi.org/10.3390/ en16010176 Academic Editors: David Baxter and Solange I. Mussatto Received: 15 November 2022 Revised: 12 December 2022 Accepted: 21 December 2022 Published: 23 December 2022 Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). energies Article Valorizing Biodiesel and Bioethanol Side-Streams: Sustainability Potential Assessment through a Multicriteria Decision Analysis Framework and Appraisal of Valuable Compound Recovery Prospects Marta Macias Aragonés1,* , Petra Ondrejíˇcková2, Raul Ugarte Lodeiro 3and Fátima Arroyo Torralvo 4 1Fundación Corporación Tecnológica de Andalucía, C Albert Einstein S/N, 41092 Seville, Spain 2ENVIRAL, a.s., Trnavskácesta, 920 41 Leopoldov, Slovakia 3TECNALIA, Basque Research and Technology Alliance (BRTA), Astondo Bidea, Edificio 700, 48160 Derio, Spain 4Departamento de Ingeniería Química y Ambiental, Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092 Seville, Spain *Correspondence: [email protected]; Tel.: +34-95-446-1352 Abstract: A framework for assessing, from a sustainability and circular bioeconomy point of view, the best valorization approach for biorefineries side-streams has been developed and validated. Two biorefinery side streams are considered as case-studies for validation: rapeseed meal from biodiesel and corn oil from bioethanol production. Firstly, a methodology to evaluate different valorization scenarios has been developed following a holistic approach that addresses technical aspects, environmental impact, and economic analysis. This way, a framework (inspired by the Battelle Method and using insights from Multicriteria Decision Analysis) has been produced where the sustainability potential of each scenario can be assessed. Such framework has been validated for five valorization scenarios for rapeseed meal and seven scenarios for corn oil. It can be concluded that protein extraction through alkaline (NaOH) hydrolysis is the best approach for rapeseed meal valorization while carotenoids recovery through ion exchange extraction is the most suitable strategy for corn oil. Secondly, for the selected scenarios, an estimation of the maximum recoverable amount of valuable compounds is conducted at the European and country-level. The use of this framework substantially aids in the best choice of the cutting-edge conversion technologies, supporting industry practitioners in the selection of processes to be further scaled-up. Keywords: sustainability; biorefinery; circular bioeconomy; biomass; biodiesel; bioethanol 1. Introduction Concerning sustainability and biorefineries, special attention is paid to biofuels and bioenergy production, as legislation and strategies are aimed at reducing carbon emissions and ensuring energy sustainability. Nowadays, there is an emerging interest worldwide for new valorization approaches of side-streams of biodiesel and bioethanol production, improving their environmental and economic profile, and ensuring greater sustainability of the bioenergy supply chain. These industrial processes usually produce by-products that are currently mostly utilized for energy, animal feed, or other low-value purposes. Specifically, rapeseed meal (RSM) linked to biodiesel production and corn oil (CO) and thin stillage (from bioethanol production) represent excellent sources of bioactive compounds that can be used in different industries such as food supplements [ 1 ], specialty chemicals [ 2 ], cosmetics [ 3 ], and ingredients for detergent market [ 4 ]. There are already several attempts of side-stream utilization into other value-added applications (e.g., production of biomethane from thin stillage by anaerobic digestion [ 5 ]), but without uncovering and exploiting the Energies 2023,16, 176. https://doi.org/10.3390/en16010176 https://www.mdpi.com/journal/energies Energies 2023,16, 176 2 of 16 full potential residing within these streams. In these scenarios, new valorization processes must be developed and further upgraded. To have a fully integrated sustainability approach, it is necessary to align the different assessments considering social, environmental, and economic aspects, as well as other set of relevant factors that have also been considered more recently ( e.g., technical, human, etc. ). Since the idea of sustainable development was identified as distinct from balancing economic wealth growth and environmental deterioration by the end of the sixties, the number of techniques, models, and strategies for measuring sustainability has significantly risen [ 6 ]. As a sustainability concept and its evaluation becomes more and more widespread, it is anticipated that the number of instruments for sustainability assessment will rise. Assessment tools already come in over a thousand different varieties. Currently, there is a plethora of sustainability assessment methods that have been extensively reviewed in several publications [6,7] , some of them delving deeper into life cycle sustainability assessment [8,9] . These publications conclude that a strategic approach for a coherent and logical framework including pertinent theory and real-world experience, based on a critical study of the state of the art, is needed to design a new evaluation instrument in the field of sustainable development [ 6 ]. Practitioners of sustainability assessment have created a growing array of tools, but there is not a tool yet that has been pointed out as the tool of reference, valid for all use-cases. This aspect becomes especially relevant when circular bioeconomy considerations add up to sustainability assessment exercises. To detect and prevent methods that promote circularity but result in unintended externalities, it is necessary to compare the sustainability of circular bioeconomy techniques to their linear counterparts [ 10 ]. Circularity measurements frequently contradict one another, yet operations research techniques like Multicriteria Decision Analysis (MCDA) may be able to resolve this issue. Walzberg et al. [ 10 ] noted that this issue makes it necessary to combine several approaches in order to evaluate more accurately the sustainability performance of circular bioeconomy. To maximize each method’s benefits and reduce its drawbacks, they have devised hybrid techniques, which integrate various methodologies. Numerous methodologies may be used to examine circularity and have already been integrated in order to address a wide range of research problems. No solution, though, has yet been able to comprehensively address issues regarding the circular bioeconomy. In this scenario, Walzberg et al. [ 10 ] conclude that combining techniques from operations research, such as MCDA (as the prevalent inconsistencies between circularity metrics may be resolved by this approach), with techniques from complex systems science and industrial ecology might be an attractive direction for future study. Life Cycle Sustainability Evaluation is one of the methods frequently employed for sustainability assessment (LCSA). The necessity to preserve the life cycle view while including the three pillars of sustainable development—environmental, economic, and social impacts—led to the creation of this development [ 8 ]. The Life Cycle Cost (LCC) approach is employed in LCSA for the examination of economic difficulties. However, it has two major drawbacks: complexity of input–output models and how externalities are handled [9]. It can be drafted that there is still a gap when it comes to industry practitioners making decisions about which technology is the keenest to be scaled-up from a sustainability and circular economy perspective. This is due to the fact that the majority of sustainability assessment methods focus on the three main sustainability pillars (economic, environmental, and social) and require lots of information from the process, but often lack considering technical aspects relevant to easiness and pertinence of the scale-up process that impact sustainability, e.g., need for custom-made vs. off-the-shelf equipment. In this sense, a few publications delve into evaluating the scalability features of technologies while considering some of the three main pillars from sustainability. Piccino et al. [ 11 ] focus on life cycle assessment (LCA) studies as a base for developing a framework for scaling up chemical processes. They present a method for simulating industrial scale manufacturing using data at hand without the need for understanding large-scale behavior (process chemistry). Such method is intended to be utilized by LCA practitioners who have no background in Energies 2023,16, 176 3 of 16 chemistry or chemical engineering and can assist in carrying out a scale-up strategy based on a methodical and logical process. Still, it is important to go further and consider not only the environmental dimension of sustainability, but to address the other sustainability dimensions since the application of fully integrated sustainability evaluation methods does not only ensure the comparability of results but also enhances consistency and reduces complexity in data gathering [12]. To the best of this publication authors’ knowledge, a decision-making support framework that has a holistic approach for sustainability and scalability assessment has not been developed nor validated for biomass valorization options selection. Within this context, the research presented herein focuses on MCDA due to its potential to address several aspects at the same time, providing the holistic feature. The three components that make up the MCDA’s strength are: (1) the information found in the criteria that were chosen; (2) the weights assigned to each criterion; and (3) consensus among the stakeholders over the weights assigned to each criterion [ 6 ]. It was also considered very important to include in the framework to be developed normalization, aggregation, and weighting. If weighting and aggregation are not conducted explicitly, each reader will ascribe weighting to the data based on their own value system, which will result in varying interpretations [ 9 ]. The way to tackle this and to ensure that the framework can be easily used and replicated for other processes is thanks to the transference functions. Specifically, the method developed by the Battelle-Columbus Institute [ 13 ], the so-called Battelle Method (BM), is the main quantitative method that has been developed for the evaluation of environmental impacts. Its objective is the systematic evaluation of the impacts of a project using homogeneous indicators, which are defined through different parameters demonstrating the representativeness of the environmental impact derived from the actions considered. The parameters are arranged in different components grouped in multiple environmental categories with their corresponding values being transformed into commensurable units to assure subsequent comparison by means of transformation techniques. This way, in the frame of the present investigation, a BM inspired framework based in MCDA principles has been developed and validated for assessment of sustainability potential for innovative valorization approaches for biodiesel and bioethanol side-streams. Accordingly, the following research questions (RQ) have been addressed: • RQ1. How can a methodology for side-streams valorization scale-up selection be developed from the sustainability perspective that is easy to use and that does not require extensive knowledge or specific software deployment? •RQ2. What is the most suitable approach to support a holistic assessment? • RQ3. Which aspects from a technological process are linked to sustainability (from the environmental, technical, and economic fields)? • RQ4. Which is the most suitable approach for valorizing rapeseed meal and corn oil as biorefinery side-streams? • RQ5. What is the maximum quantity of valuable compounds that Europe could produce if the selected side-streams would be fully valorized? The research presented is structured as follows: An overview of the selected side-streams and valorization approaches as well as how the framework has been shaped is provided in Section 2. Here, the selected biorefineries (biodiesel and bioethanol productions) are presented, together with the selected side-streams and their characterization. The collection of data used for the recovery potential estimation and the way that the BM approach has been used as the key idea for the framework development are explained (answers to RQ1 and RQ2), delving into the technical, economic, and environmental assessment techniques so as to define the Sustainability Potential Index (SPI, answer to RQ3). Section 3starts presenting the results from the validation exercise as the framework is used to assess five scenarios for RSM and seven scenarios for CO valorization (answer to RQ4). Then, the estimation of the quantity of valuable compounds that could be recovered through the selected scenarios in European countries is provided (answer to RQ5). Section 4discusses the results and Section 5concludes Energies 2023,16, 176 4 of 16 by summarizing the key findings, highlighting the research’s shortcomings, and outlining any possibilities and future development prospects. 2. Materials and Methods Steps followed towards the development of the sustainability potential assessment framework and the subsequent valuable compounds recovery prospect evaluation are described next. Case studies used for validating the proposed framework are presented here as well. 2.1. Sustainability Potential Assessment Framework Development The rationale for the sustainability potential assessment is based on an MCDA approach. Specifically, the Analytic Hierarchical Process (AHP) approach has been followed as a trade-off solution between the reliability of the solution, amount of information needed, and ease of use. According to Vaidya et al. [ 14 ], the unique quality of AHP is its adaptability to be coupled with other strategies, allowing the user to gain advantages from all the combined ways and thus better accomplish the intended aim. This is why the authors have deemed this MCDA approach as the most suitable one to be combined with BM. AHP is a precise method for calculating the relative importance of the various decision-making factors. Through pair-wise comparisons, the experiences of individual experts are used to assess the relative magnitudes of different aspects. The BM dimension is considered since such method is identified as quantitative and reliable as it can consider different measurements from an objective point of view as it converts different measurements into common units by means of a scalar or “value function”. Following the goal of developing a framework that is easy to be implemented and used by all kinds of stakeholders, the decision matrix has been created in an Excel file. Steps followed during the development of the framework are presented next. Most of them are the usual ones for MCDA frameworks development while some of them have been added due to the BM consideration: 1. Goal and scope definition: the MCDA will use, for the environmental and technical aspects assessment, the same system boundaries and functional unit, focusing on the process itself, i.e., the same system boundaries and functional unit as the LCA will be considered, as this will be the methodology used for environmental impact assessment. As for the economic aspects, the equipment costs and maintenance are considered as well. It is important to notice that, while the LCA does not consider local conditions, organizational issues or local regulatory issues, the MCDA could consider these aspects in the decision making at a later stage. 2. Selection of systems for comparison: scenarios to be assessed and compared need to be fully defined. It is very important that, for each scenario, the following aspects are clearly identified: feedstock, main technology and expected final products. 3. Definition of criteria and sub-criteria: here is where the application of BM principles starts to be considered. BM names the main criteria as categories and the sub-criteria as components. Therefore, for each of the selected categories (environmental, technical, and economic), components need to be defined. 4. Rating: to be able to rank the different systems, and to capture local interests and conditions, each set of categories and components (criteria and sub-criteria in the developed framework) need to be rated in accordance with their relative importance. Hence, a total of 1000 sustainability potential units are allocated to each component (similar to BM where 1000 units of measurement are distributed among the different components). 5. Definition of the transformation functions: for each component, a transformation function is defined, making it possible to conduct the assessment process unequivocally and objectively. The fourth and fifth steps are presented in Section 3, since they are developed ad hoc for the biodiesel and bioethanol side-streams valorization approaches assessed. Energies 2023,16, 176 5 of 16 Concerning the goal and scope definition, the study has been conducted in the frame of the Bio-Based Industries Joint Undertaking funded EXCornsEED project, an innovation project devoted to valorization of biorefinery side-streams through a combination of innovative extraction, concentration, and purification technologies. The case study for this project has been the Envien Group, based in the Central and Eastern Europe region (Slovakia, Czech Republic, Hungary, Croatia, and Poland, being one of the largest and most significant groups of companies in such area) active in the production of biofuels. As for the selection of systems for comparison, the side-streams considered in the frame of the present research are RSM and CO. RSM is a free-flowing material resulting from the production of crude rapeseed oil, obtained by the subsequent extraction of rape seeds after the pressing process, being a very valuable nutritional side-stream full of proteins (min. 33% in weight), minerals, and other very interesting compounds, e.g., sinapic acids and polyphenols. CO is a liquid side-stream of bioethanol production, isolated from corn thin stillage and is rich in lipophilic bioactive substances such as carotenoids, phytosterols, tocopherols, and omega 6. The main composition of RSM and CO streams mentioned has been published elsewhere [14]. Regarding the valorization scenarios to be assessed in order to validate the proposed framework, twelve scenarios have been selected for the valorization of the selected sidestreams. For each one, the following aspects have been identified: (1) feedstock; (2) main technology; and (3) expected final products. These 12 scenarios are 12 different valorization technologies developed in the frame of the aforementioned EXCornsEED project (Table 1). Table 1. Scenarios from the selected case studies (rapeseed meal and corn oil valorization) used for validating the proposed sustainability potential assessment framework. Scenario Feed Product Technology R1 RSM Proteins Alkaline hydrolysis (NaOH) R2 RSM Polyphenols Ion extraction R3 RSM Polyphenols Enzymatic extraction R4 RSM Proteins Enzymatic extraction R5 RSM Proteins Alkaline hydrolysis (Na2CO3) C1 CO Carotenoids Ion extraction C2 CO Triglycerides Liquid-liquid extraction C3 CO Bioactives (mix) Supercritical extraction with alumina C4 CO Bioactives (mix) Supercritical extraction with silica gel C5 CO Triglycerides Ionic liquid extraction C6 CO Bioactives (mix) Solid extraction (bind and elute) C7 CO Triglycerides Solid extraction (fractioning) With respect to the definition of categories and components, this has been done following a holistic approach concerning sustainability. In order to properly address and assess all aspects and dimensions that conform sustainability, circular bioeconomy and scale-up target, environmental, economic, and technical issues have been considered. This approach is aligned with recent publications about sustainability assessment [15,16]. This way, categories have been sorted into three main sustainability criteria: addressing technical performance, environmental aspects, and economic aspects. As for the environmental aspects, the LCA is considered. For the economic aspects, different ratios and economic information are examined, while process characteristics evaluation is related to the technical aspect. In order to define the set of components and subsequent rating, i.e., sustainability potential units allocated to each component, a DELPHI Method [ 17 ] inspired workshop was organized where partners from the EXCornsEED project participated. Expertise among this group ranges from circular bioeconomy, biorefineries, process development, process scale-up and optimization to environmental impact assessment, economics, etc. As a first output of this workshop, the following set of components was defined as follows and as depicted in Figure 1. Energies 2023,16, 176 6 of 16 Energies 2023, 16, x FOR PEER REVIEW 6 of 17 economic information are examined, while process characteristics evaluation is related to the technical aspect. In order to define the set of components and subsequent rating, i.e., sustainability potential units allocated to each component, a DELPHI Method [17] inspired workshop was organized where partners from the EXCornsEED project participated. Expertise among this group ranges from circular bioeconomy, biorefineries, process development, process scale-up and optimization to environmental impact assessment, economics, etc. As a first output of this workshop, the following set of components was defined as follows and as depicted in Figure 1. Figure 1. Set of categories and components defined as a result of the DELPHI Method inspired workshop:  Technical Performance: Process yield, Final product purity, Selectivity; Is it possible to reuse process effluents? and Does the process allow for producing an active compound useful in different markets?  Environmental Impact: Global warming potential, Photochemical oxidation potential, Acidification potential, and Eutrophication potential.  Economic Aspects: Profitability; Does the process use commercial equipment? Might the process, at a theoretical commercial side, require any high maintenance? and Input–Output balance. The second conclusion from this workshop was the rating and transference function definition. For each component, the different qualitative and quantitative values (e.g., yield in % for technical category, global warming potential for environmental category or OPEX in € for economic category, among others) are converted to normalized commensurable units (from 0 to 1) through transference functions (or scalar functions). This commensurable unit that results from the transference function is called Sustainability Value in the proposed framework. Once sustainability potential points are allocated to the different components and the normalized transference functions are defined, it is possible to calculate the Sustainability Values for each defined scenario together with the corresponding SPI. Calculations are done according to Equation (1): Sustainability Potential Index ( SPI ) = ∑ ( Xi · Wxi )     (1) where Xi are the Sustainable Potential units for every ‘i’ component, and Wxi are the Sustainable values for every ‘i’ component calculated using the aforementioned transference functions (values between 0 and 1). Figure 1. Set of categories and components defined as a result of the DELPHI Method inspired workshop. • Technical Performance: Process yield, Final product purity, Selectivity; Is it possible to reuse process effluents? and Does the process allow for producing an active compound useful in different markets? • Environmental Impact: Global warming potential, Photochemical oxidation potential, Acidification potential, and Eutrophication potential. • Economic Aspects: Profitability; Does the process use commercial equipment? Might the process, at a theoretical commercial side, require any high maintenance? and Input–Output balance. The second conclusion from this workshop was the rating and transference function definition. For each component, the different qualitative and quantitative values (e.g., yield in % for technical category, global warming potential for environmental category or OPEX in € for economic category, among others) are converted to normalized commensurable units (from 0 to 1) through transference functions (or scalar functions). This commensurable unit that results from the transference function is called Sustainability Value in the proposed framework. Once sustainability potential points are allocated to the different components and the normalized transference functions are defined, it is possible to calculate the Sustainability Values for each defined scenario together with the corresponding SPI. Calculations are done according to Equation (1): Sustainability Potential Index (SPI)=∑12 i=1(Xi·Wxi)(1) where X i are the Sustainable Potential units for every ‘i’ component, and W xi are the Sustainable values for every ‘i’ component calculated using the aforementioned transference functions (values between 0 and 1). 2.2. Literature Review and Data Gathering for Recovery Prospects Appraisal Firstly, a literature review [ 18 ] was done to gather the numerical data needed for the recovery potential estimation. Data were collected from both scholarly journals and non-academic organizations. The rationale behind this approach is that sometimes this kind of information (production data, business information) can be found not only in peer-reviewed material but also in publications from the professional domain. Moreover, as the data to be retrieved are linked to circular bioeconomy, this decision was backed by conclusions from Geissdoerfer et al. [ 19 ]: “The inclusion of non-peer-reviewed articles is appropriate since circular economy is a new area of research and ( . . . ) has not been extensively addressed by peer reviewed articles”. As a result, publications from business organizations, Eurostat datasets and website, project reports, Science Direct, Web of Science, MDPI, Springer, Taylor & Francis, Google Scholar, and others have been vetted as data sources. The key words used in the data search were (i) “bioethanol” AND “side-stream” OR “side-stream” AND “production” OR “availability”; (ii) “biodiesel” AND “side-stream” OR “side-stream” AND “production” OR Energies 2023,16, 176 7 of 16 “availability”; (iii) the various names of selected side-streams (RSM and CO) were also searched separately next to AND “production”. Based on scanning the identified documents, data that were considered not reliable, outdated or not representative were discarded. Content of valuable compounds in the selected side-streams was gathered from literature [20,21]. Valuable compounds product prices were checked with market suppliers. 3. Results 3.1. Sustainability Potential Assessment Framework Development and Validation Following the main principles of BM and through the DELPHI-inspired workshop already described, a total of 1000 Sustainability Potential units were allocated among the different components (sub-criteria) for each of the categories (main criteria, namely environmental, economic, and technical). The allocation of this units is represented in Figure 2. Energies 2023, 16, x FOR PEER REVIEW 7 of 17 2.2. Literature Review and Data Gathering for Recovery Prospects Appraisal Firstly, a literature review [18] was done to gather the numerical data needed for the recovery potential estimation. Data were collected from both scholarly journals and nonacademic organizations. The rationale behind this approach is that sometimes this kind of information (production data, business information) can be found not only in peer-re- viewed material but also in publications from the professional domain. Moreover, as the data to be retrieved are linked to circular bioeconomy, this decision was backed by conclusions from Geissdoerfer et al. [19]: ‘‘The inclusion of non-peer-reviewed articles is appropriate since circular economy is a new area of research and (…) has not been extensively addressed by peer reviewed articles’’. As a result, publications from business organizations, Eurostat datasets and website, project reports, Science Direct, Web of Science, MDPI, Springer, Taylor & Francis, Google Scholar, and others have been vetted as data sources. The key words used in the data search were (i) “bioethanol” AND “side-stream” OR “side-stream” AND “production” OR “availability”; (ii) “biodiesel” AND “side-stream” OR “side-stream” AND “production” OR “availability”; (iii) the various names of selected side-streams (RSM and CO) were also searched separately next to AND “production”. Based on scanning the identified documents, data that were considered not reliable, outdated or not representative were discarded. Content of valuable compounds in the selected side-streams was gathered from literature [20,21]. Valuable compounds product prices were checked with market suppliers. 3. Results 3.1. Sustainability Potential Assessment Framework Development and Validation Following the main principles of BM and through the DELPHI-inspired workshop already described, a total of 1000 Sustainability Potential units were allocated among the different components (sub-criteria) for each of the categories (main criteria, namely environmental, economic, and technical). The allocation of this units is represented in Figure 2. Figure 2. Sustainability Potential Units distribution among the different categories and components. Figure 2. Sustainability Potential Units distribution among the different categories and components. After allocating the Sustainability Potential Units, the transference functions were defined. The next paragraphs describe how the transference functions for technical performance components have been defined: • Process yield, final product purity, and selectivity: the value is linearly extrapolated according to the corresponding ratio where 0 is for 50% and 1 for 100%. • Effluents reutilization: the value is extrapolated according to the corresponding reuse ratio where 0 is for 0% reuse and 1 is for 100% reuse. • For Products useful in different markets, 4 target markets: food (elders), food (toddlers), cosmetics and chemicals were identified, and a discrete function was defined as follows: for 1 market, factor = 0.25; for 2 markets, factor = 0.5; for 3 markets, factor = 0.75; and for 4 markets, factor = 1. In the case of environmental impact components, transference functions are as follows: • Global warming potential, Photochemical oxidation potential, Acidification potential, Eutrophication potential rate from 0 to 1 according to the results of the LCA carried out to the different scenarios. The rating will be 0 for the highest amount (kg CO 2 eq/kg–kg C 2 H 4 eq/kg–kg SO 2 eq/kg–kg PO 4−3 eq/kg, respectively), and 1 to the lowest amount, and rates for the intermediate values will be extrapolated. The transference functions for economic aspects are presented next: Energies 2023,16, 176 8 of 16 • Profitability: Prices from final products per kg or per L were considered. The lower price would be equivalent to 0.2 and the higher price would be equivalent to 1, extrapolating for the rest of scenarios values. In case of a scenario providing several final products, the price of the different products would be summed up; • Kind of equipment: Since ad-hoc equipment could affect process economics by increasing the CAPEX, the following rating considerations could be used (having in mind a full commercial scale): All the process equipment needs to be tailor-made: 0; Only one piece of equipment (the one related to the core of the proposed process) and one piece of auxiliary equipment need to be tailor-made: 0.2; Only one piece of equipment (the one related to the core of the proposed process) needs to be tailor-made: 0.4; Several auxiliary equipment need to be tailor-made: 0.6; Only one piece of auxiliary equipment needs to be tailor-made: 0.8; Both main and auxiliary equipment can be acquired from commercial catalogues: 1; • Scale-up potential: Rating was defined after the answer of the following two main questions: (1) is the business easy to scale up: is the possibility to multiply incomes based on sustainable investments?, and (2) Does the scalability of production mean an optimization of costs production? For (1) no; and (2) no; the factor is 0. For (1) no; and (2) yes; the factor is 0.33. For (1) yes; and (2) no; the factor is 0.67. For (1) yes; and (2) yes; the factor is 1. • Maintenance of the process: High maintenance (e.g., replacement of at least one main equipment, all auxiliaries, membranes, sensors, etc. once per year) ~0; High-medium maintenance (e.g., replacement of all auxiliaries, membranes, sensors, etc. once per year) ~0.25; Medium maintenance (e.g., replacement of all auxiliaries, membranes, sensors, etc. every two years) ~0.5; Medium-low maintenance (e.g., replacement of membranes every two years) ~0.75; Low maintenance (no major replacement of main equipment, nor auxiliaries, etc. is expected within 3 years of operation) ~1; • Input–Output balance: This component is related to OPEX and the income from selling process of produced bioactive compounds. The input-output balance needs to be calculated per each scenario and then a rating allocation and extrapolation would need to be done as in the case of profitability. The above presented framework was used to rank the different developed technologies. Firstly, transference functions were used to calculate the Sustainability Values for each component. The results for the different categories are provided in Tables 2and 3. Table 2. Calculated Sustainability values for the defined components. Case study: rapeseed meal valorization. Component R1 R2 R3 R4 R5 Process yield 0.30 0.00 0.00 0.00 0.00 Product purity 0.82 0.60 0.00 0.85 0.00 Selectivity 0.90 0.40 0.80 0.70 0.60 Effluents reutilization 0.00 0.00 1.00 0.00 0.00 Multi-marketed products 1.00 1.00 0.50 0.50 0.50 Global warming potential 0.95 0.96 0.90 0.81 0.00 POP * 0.95 0.96 0.83 0.72 0.00 Acidification potential 0.94 0.96 0.91 0.82 0.00 Eutrophication potential 0.91 0.93 0.87 0.71 0.00 Profitability 0.80 0.80 0.80 1.00 0.60 Kind of equipment 1.00 1.00 1.00 0.80 0.80 Maintenance required 0.75 0.75 1.00 0.50 0.75 Input-Output balance 0.70 0.70 0.80 0.60 0.60 * POP: Photochemical Oxidation Potential. Energies 2023,16, 176 9 of 16 Table 3. Calculated Sustainability values for the defined components. Case study: corn oil valorization. Component C1 C2 C3 C4 C5 C6 C7 Process yield 0.40 0.00 0.00 0.00 0.00 0.00 0.00 Product purity 0.80 0.05 0.05 0.10 0.05 0.05 0.00 Selectivity 0.80 0.35 0.35 0.10 0.05 0.05 0.00 Effluents reutilization 0.00 0.90 0.50 0.90 0.90 0.90 0.00 Multi-marketed products 1.00 0.50 0.50 0.15 0.00 0.00 0.25 Global warming potential 0.34 0.94 1.00 0.98 0.85 0.63 0.96 POP * 0.41 0.95 1.00 0.97 0.90 0.74 0.96 Acidification potential 0.29 0.95 1.00 0.98 0.85 0.64 0.96 Eutrophication potential 0.28 0.92 1.00 0.99 0.77 0.43 0.93 Profitability 1.00 0.15 0.15 0.15 0.15 0.15 0.00 Kind of equipment 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Maintenance required 0.75 0.75 0.75 0.75 0.75 0.75 0.75 Input-Output balance 0.80 0.70 0.70 0.70 0.70 0.70 0.20 * POP: Photochemical Oxidation Potential. It is worth noticing that, when a scenario has 0 points, it means that the assessed component has the worst value compared with the rest of assessed scenarios (as it is the case of the environmental components for R5) or that obtains 0 according to the transference function (as it is the case for C7 in most of the technical components). Then, it was possible to obtain the SPI for each scenario and rank them accordingly. Calculations were done according to Equation (1). Results are provided in Figure 3. Energies 2023, 16, x FOR PEER REVIEW 10 of 17 Figure 3. Sustainability Potential Indexes for the assessed scenarios. It can be pointed out, from analyzing the chart provided in Figure 3, that the scenario with highest SPI for RSM valorization is R1 (protein production through alkaline (NaOH) hydrolysis). In the case of CO valorization, the highest SPI is the one for carotenoids production through ion extraction. 3.2. Appraisal of Recovery Prospects Once the different valorization alternatives have been evaluated, the recovery prospects of the valuable compounds to be extracted through the most advantageous options (proteins from RSM and carotenoids from CO) have been quantified for European countries. This has been carried out by conducting the corresponding calculations, using as a starting point the data retrieved through the literature review exercise that has been performed (previously described in Section 2.2 Literature review and data gathering for recovery prospects appraisal). Table 4 presents the total production of the side-streams considered in the present research (RSM and CO). There was a lack of data for some countries for side-stream volumes since they are sometimes classified as waste and therefore production data are not quantified and/or made public. For these cases, the total production in 2020 for biodiesel and bioethanol [22,23] has been used as calculation basis and side-stream volumes have been estimated accordingly. In line with the ePure report [23], around 51% w/w from all bioethanol produced in Europe comes from corn, while Duren et al. [24] report that 79% from European biodiesel comes from rapeseed. Additionally, the RSM amount generated during biodiesel accounts, on average, for 0.6579 tons of RSM being produced per each t of biodiesel [25]. The distribution of products and side-streams obtained when processing 1 bushel of corn for bioethanol production is: 18.2 lbs of ethanol, 15.5 lbs of DDGs, 0.7 lbs of technical CO [26]. Then, these calculations were extended in order to consider dry weight figures. According to [26], dry weight RSM without impurities equals 90.46% w. while dry weight CO without impurities amounts to 99.5% w [21]. Figure 4 provides qualitative information of the RSM and CO production. Figure 3. Sustainability Potential Indexes for the assessed scenarios. It can be pointed out, from analyzing the chart provided in Figure 3, that the scenario with highest SPI for RSM valorization is R1 (protein production through alkaline (NaOH) hydrolysis). In the case of CO valorization, the highest SPI is the one for carotenoids production through ion extraction. 3.2. Appraisal of Recovery Prospects Once the different valorization alternatives have been evaluated, the recovery prospects of the valuable compounds to be extracted through the most advantageous options (proteins from RSM and carotenoids from CO) have been quantified for European countries. This has been carried out by conducting the corresponding calculations, using as a starting point the data retrieved through the literature review exercise that has been performed (previously described in Section 2.2 Literature review and data gathering for recovery prospects appraisal). Energies 2023,16, 176 16 of 16 21. 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