Reflecting Regional Conditions in Circular Bioeconomy Scenarios: A Multi-criteria Approach for Matching Technologies and Regions

1. Introduction

As a long-term target of the European Union (EU) [1] and of many countries worldwide [2,3], the bioeconomy (BE) is promoted as an economic concept that can replace the current fossil based and linear economy with the aim to increase sustainability [1]. The European Bioeconomy Strategy describes the BE as a broad concept that covers all sectors and systems relying on biological resources [1]. In 2012, with the publication of the first BE strategy, the EU has already committed itself to the goal of a transition towards BE. [4]. Since then, the potential negative impacts of the BE have also raised concerns. A main environmental concern relates to the resource base of the BE. It is expected that the growing demand for bio-based resources and the associated increase in primary production will potentially intensify production processes in agriculture, forestry and aquaculture as well as the competition for land [5]. This potentially intensifies environmental and social problems such as land use change, global warming [6], biodiversity loss [7] and threatened food security [8]. To prevent this, in the updated BE strategy of 2018, the EU strengthens the focus on sustainability and circularity and defines it as key success factors of the BE [1]. In parallel, the term circular bioeconomy (CBE) was established in the scientific literature since 2015 to describe the fusion of the two concepts of BE and the circular economy [9]. Stegman et al. derive a definition from the elements that constitute the CBE: “the sustainable, resource-efficient valorization of biomass in integrated, multi-output production chains, while also making use of residues and wastes and optimizing the value of biomass over time via cascading” [9]. Moreover, we hypothesize that CBE is a highly regional concept. For example, CBE concepts based on residual biomass are strongly predefined by their availability, which depends on regional conditions such as agro-climatic environment, industry focus and consumption patterns [10]. Further regional conditions exist, including biomass logistics, technological knowledge, and sensitivity to environmental impacts. Accordingly, the CBE approach of a given region is determined by its geographic location, natural resources and economics [11].

Due to the aforementioned risk that the BE contradicts its vision of being a sustainable economic concept and causes social and environmental damage when implemented, a careful planning of the transition process and its framework conditions is required, also for the CBE; for example, through the development of a comprehensive governance framework [2,12,13]. For this a thorough understanding of the transition process is necessary [12]. Acknowledged methods to analyze the CBE transition process are for example (i) the identification of its drivers and barriers [14] or (ii) the assessment of its possible impacts. Many studies are available that identify drivers and barriers (see Table 1). However, most of them do not reflect regional conditions affecting these drivers and barriers. Possible impacts that a CBE transition process may have on economy, society and the environment, are assessed e.g. through explorative scenario analyses depicting potential CBE pathways [15,16,17,18,19,20]. For a precise modeling of certain development paths, it is necessary to integrate specific technological CBE innovations into the model. For example, Wydra et al. [18] examine possible transition pathways and interactions of distinct bio-based niches, i.e. bioplastics, biolubricants, biofuels for road and aviation; or Tsiropoulos [16] investigate competitive and synergetic biomass uses within the energy, biotechnological and chemical sectors using a technology-rich and technology-explicit model. However, the technology selection process in such CBE technology scenarios is often arbitrary and not sufficiently justified and documented: Examples of rather vague justifications we found in the literature are: a limitation to technologies from certain economic sectors [16,17], a limitation to technologies with a direct substitution potential for fossil products [16,17], or a limitation to technologies with high technology readiness level [20]. Conversely, we argue that in CBE scenario building, the selection of technologies should be based on an appropriate assessment of their potential for a successful sustainable implementation. Furthermore, following our hypothesis that CBE is a regional concept, we suggest that this potential should be assessed taking regional conditions into account. Approaches for the evaluation of the success potential of CBE innovations that consider regional conditions have been proposed: For example, Salvador et al. identify drivers and barriers for CBE businesses and present regional differences in these aspects [21]; Or Croxatto Vega et al. present an approach that allows the selection of an ideal technology for a given region based on economic and environmental criteria [22]. However, concrete guidelines for a region-specific technology selection in the context of CBE scenario building cannot be derived from these studies. For this purpose, the analysis by Salvador et al. is not sufficiently refined in terms of both regionality and success criteria. The quantitative approach of Croxatto Vega et al. is suitable to support an informed choice among a small number of technology options. However, intensive data requirements make it difficult to be applied to a large number of technology options for scenario building.

Accordingly, we address two research gaps: (i) Although there is extensive literature analyzing the potential for a successful CBE transition by identifying barriers and drivers, a comprehensive consideration of the role that regional conditions play in this context is lacking. (ii) Furthermore, we identify a lack in practical guidance for the reflection of regional conditions during the selection of CBE technologies in the context of CBE technology scenario building. Therefore, the objective of this study is twofold: (i) The first objective is to compile a comprehensive catalog of CBE success criteria and to demonstrate the extent to which these success criteria are region-specific. In doing so, we aim to substantiate our hypothesis that the CBE is regional in nature and to broaden and deepen awareness and understanding of the important role that regional conditions play in CBE transition processes. (ii) The second objective of our study is to present a methodology for the selection of CBE technologies based on the reflection of their potential for a successful sustainable implementation under the influence of regional conditions. The methodology is based on evaluation matrices that allow to assess technological and regional conditions influencing the success potential of a specific CBE technology in a given region. A matching of CBE technologies with regions is thereby possible, preparing technology selection for the building of regional CBE technology scenarios.

2. Materials and Methods

The first objective of the study is to demonstrate the importance of the regional context for the successful implementation of CBE technologies. With this in mind, in a first step, we identify success criteria for the implementation of CBE technologies from the literature and categorize them. We adopt a broad perspective that includes among others economic, environmental, and social factors both upstream and downstream of the CBE technology. We explicitly do not limit this first step to region-specific criteria. This allows for a comprehensive set of criteria that may include region-specific factors that have not yet been identified as such. It also allows us to demonstrate later that most of the success criteria are indeed region-specific, which emphasizes the importance of this work. In a second step, we validate the CBE success criteria catalog through an expert survey.

The second objective of this study is to provide practical guidance for the selection of technologies in the context of CBE scenario building. To do this, it is necessary to identify success criteria that are both technology- and region-specific, as these criteria must be carefully considered when selecting a CBE technology for a specific region. Therefore, in the third step, we categorize each CBE success criterion according to its region and technology specificity. The final step considers only CBE success criteria that are both technology-specific and region-specific at the subnational level. In this step, for selected CBE success criteria clusters we develop two evaluation matrices each: the CBE Technology Evaluation Matrix and the CBE Region Evaluation Matrix. These matrices allow a separate evaluation of regional and technological characteristics and their potential influence on the respective success criteria cluster. By comparing the results of the two evaluation matrices, it is possible to match a CBE technology with a region regarding the criteria cluster. Figure 1 visualizes the described procedure.

2.1. Identification of success criteria for the implementation of CBE technologies

To identify criteria that influence the success of the implementation of CBE technologies, we conducted a literature review. By applying the search terms driver and barrier in combination with terms referring to the CBE we received 286 results from the web of science database. We first scanned the titles and identified 28 studies as potentially relevant, from which we then read the abstract to finally select 22 relevant peer reviewed journal publications. Table 1 lists the selected studies, indicating bibliographic information and the context. From the publications, we extract CBE success criteria. We compile the original citations in a comprehensive table (SM2) and add for each study a new column. Related criteria from the different studies are grouped together in one row. For each row, we derive a general term that stands for all quotations from this group and define it as the main criterion. In addition, we derive as sub-criteria general terms for specifications and details given in the studies, which help to deepen the understanding of the main criterion. Each main criterion with its sub-criteria is assigned to a superordinate criteria category. Further, we document the number of studies relating to each main and sub-criterion and sort them in descending order, assuming this provides a first indication of their relevance. The main and sub-criteria, as well as their categorization and sorting are compiled in the CBE Success Criteria Catalog.

2.2. Validation of CBE Success Criteria

To validate and improve the results of the literature research we conducted an expert survey. Five experts from three European countries answered a questionnaire (SM4) in which we present our CBE Success Criteria Catalog, including the categorization of the criteria. The experts provided feedback on whether they agree with the catalog or whether and how they would add to the main or sub-criteria or change their categorization or sorting. We merged the expert feedback into one document and changed the criteria list accordingly.

2.3. Categorization of CBE Success Criteria into Region- and Technology-Specific Criteria

To identify CBE success criteria that are both technology- and region-specific at the subnational level, we created a categorization scheme that classifies CBE success criteria according to their region and technology specificity. Based experience, we decided for each sub-criterion whether it is region-specific and/or technology-specific and justify our choice in the result section. We consider factors to be region- or technology-specific, which can either have different states for different regions/technologies or which can be of different importance for different regions/technologies. We distinguish between factors that are region-specific at the national level and those that are region-specific at the subnational level.

2.4. Development of Evaluation Matrices for regions and technologies to allow a matching of regions and CBE technologies regarding selected CBE success criteria clusters

To demonstrate the evaluation and matching process, we select two success criteria clusters: the first cluster examines the topic of social acceptance & consumer awareness, while the second cluster looks at the topic of the biomass supply chain.

In order to compile the CBE Technology and the CBE Region Evaluation Matrix for the two clusters, we conducted two further literature researches in web of science. For the first cluster we combined search terms referring to social acceptance, region, and the BE. A more specific search referring to the CBE was not successful. We excluded mismatches by scanning titles and abstracts and added further publications from the reference lists of suitable publications during the reading process. The list of publications that was finally considered to compile the matrices is summarized in Table 2. For the second cluster we used a combination of search terms referring to residual biomass, accessibility, and region. Scanning of titles and abstracts helped to exclude mismatches. As this search provided mainly studies on supply chains for forestry and agricultural residues, but few for industrial by-products and wastes, we included publications from another search with terms related to biobased industrial by-products and supply chain. The final list of publications used for the matrices’ compilation can be taken from Table 3.

To construct the matrices, we extract from the literature characteristics of both CBE conversion technologies and regions that influence social acceptance and the biomass supply chain, respectively. For each characteristic, we indicate whether it is more likely to increase or decrease the potential for a CBE.

3. Results

3.1. CBE Success Criteria Catalog

From the literature review and the expert survey, we receive 19 main criteria and 76 sub-criteria that influence the success of CBE (see Table 4). We categorize them into the seven criteria categories: biomass resource, technological, environmental, economic, political & legislation, social, and methodological.

The main criterion we found to be mentioned most frequently in the literature, with 20 studies referring to it, is the biomass availability. This is particularly remarkable as this criterion has a comparatively narrow scope, while other main criteria cover a broader range of sub-criteria. Furthermore, there is a high level of awareness towards the criteria of profitability & markets as well as policies, legislation & standards, with 18 studies relating to each. The two criteria logistic & supply chain and availability of technology are also frequently mentioned, with 17 studies each, demonstrating the high relevance of technological aspects. The social category comprises many criteria with medium to high rankings, which indicates that this category as a whole receives a high level of attention. The social category is the only one for which one of the experts proposed a change in the sorting of the main criteria, stating that here is a lack of consensus in the scientific bioeconomy community. The environmental category seems to be of rather low importance, comprising only two main criteria of medium and low ranking. This is surprising as the transition to a CBE is mainly motivated by the environmental problems associated with a linear and fossil-based economy. It is further remarkable that the potential of CBE to influence the environment (negatively or positively) attracts far more attention than the potential for environmental changes to jeopardize the successful implementation of CBE. Worth mentioning is also that three of the five experts suggest not to rank the environmental indicators, as their relevance is highly biomass specific.

3.2. Categorizsation Scheme - region and technology specificity of CBE success criteria

To identify those success criteria that are both region- and technology-specific, we categorize all sub-criteria accordingly. Figure 2 shows the result of this categorization process. It appears that the vast majority of the criteria are technology-specific; only criteria relating to general socio-economic developments, policy implementation and the culture of businesses and regions were classified as independent of the technology under consideration. The majority of technology-specific factors are found to be region-specific, with more factors being region-specific up to the subnational level than only up to the national level. This demonstrates how important it is to match regions and technologies to increase the success of a CBE transition and to strengthen the plausibility of regional CBE scenarios.

In terms of the biomass resource category, we have on the one hand criteria referring to the locally, sustainably available, and usable biomass potential and its supply chain. We classify these criteria as region-specific at subnational level, as (i) the availability of different biomass categories and their spatial density varies from region to region (see also chapter 3.4) , (ii) the use of biomass, especially biogenic residues, and therefore also competing demands for biomass are region-specific, (iii) the infrastructure and organization of the biomass supply chain vary regionally; including transport and storage capacities and the organization of collection, separation and pre-treatment systems for biogenic residues. On the other hand, there are criteria from the biomass resource category that are rather biomass- than region-specific, such as quality aspects and temporal fluctuations, that we classify as not region-specific.

Criteria from the technological category are partly region-specific at both subnational and national level, but also partly regionally independent. Criteria referring to the regional availability of technological knowledge and experience we classify to be region-specific. Aspects relating to advances in technological development (science, maturity, and efficiency) are classified as regionally independent on the assumption that these advances, once implemented in standard technological solutions, can be applied globally. However, we argue that the complexity and investment costs of a technology is perceived differently in different world regions. For example, highly complex and costly technologies are difficult to be financed, operated, and maintained in rural regions in countries of the Global South, whereas this may be less problematic in the surroundings of a modern industrial park.

Environmental factors are mostly region dependent. Impacts caused or mitigated by CBE technologies can be divided into local impacts such as biodiversity loss, land use change, soil and water quality, etc. and global impacts such as climate change and resource scarcity. Conversely, the environmental changes that influence the success of CBE technology implementation are generally region-specific. For example, while GHG emissions lead to the global effect of climate change, its effects differ regionally: in some regions droughts due to climate change might lead to a deterioration of cultivation conditions for specific crops, in other regions higher temperatures might lead to an expansion of potentially cultivable plants.

Economic success factors mostly depend on national conditions. For example, the cost-effectiveness and the competitiveness of innovative biobased products depend on factors like public subsidies or prices of competing (fossil-based) products. Whether a waste can be used as a resource for specific value chains depends on national legislation. The interest of private investors in innovative projects depends among other factors on the political stability of a country. Furthermore, we argue that market conditions vary usually at national level. However, we also consider that some biobased products might be traded on regional markets. In this case, the market related factors should be seen as regional dependent at the subnational level. Economic benefits through business diversification and multi-product output, for example in biorefineries, seems to be possible independently from the region.

Policies & Legislation are primarily implemented at the national or supranational level, leading to national differences in the supportiveness of policies and legislation. However, some relevant policies or legislations might also be implemented at the subnational level. Regarding social criteria, we argue that the social acceptance for production sites is regional dependent at the subnational level, while the consumer awareness plays a role at national level, in case of international markets. In the case of regional markets, differences in consumer acceptance are also of relevance at subnational level. Finally, we argue that all methodological aspects, that are relevant to assess the economic and environmental potential of CBE technologies are regionally independent.

For our further analysis we consider only those success criteria that are both region-specific at the subnational level and technology-specific. We identify four relevant clusters: (i) a cluster on the regional biomass supply chain, that includes criteria referring to the availability, accessibility, deliverability and costs of biomass and covers also aspects of technological knowledge to process the biomass; (ii) a cluster on regional environmental impacts, (iii) a cluster on regional policies and legislation; and (iv) a cluster on the regional social acceptance and consumer awareness, that includes also selected economic aspects. We acknowledge that all four clusters are highly relevant and recommend their consideration when selecting technologies for modeling CBE at the regional scale. However, the remainder of this paper, is limited to the two criteria clusters i and iv. They are chosen because they constitute the two broadest criteria clusters with highest relevance according to the ranking from Table 4.

3.3. Social acceptance & consumer awareness

CBE concepts aim at a holistic transition that involves technological and economic changes, which affect large parts of the economy and societies’ modes of living. Broad acceptance or rather contribution to this transition by different stakeholders and particularly by the civil society is necessary: as neighbors of CBE plants, as consumers of CBE products and as an active political force. That the acceptance of a technology in general and not only in its concrete implementation is of decisive importance is demonstrated by those cases in which the skepticism of civil society led to the delay or cancellation of projects and to a decrease in political support. In the context of BE, the example of BECCS is of relevance. Although BECCS is applied as a mitigation strategy in all 2°C compatible SSP scenarios, due to public protests several CCS projects have been suspended or terminated, R&D funding has been reduced and the German government has not yet included BECCS in its long-term climate strategy [49].

From a regional perspective, it is important to recognize that the social acceptance of BE concepts and their technologies can vary from region to region. For example, support for forest-based biorefineries in the state of Maine, USA, in general was found to be different than in a subgroup that included only mill towns with existing pulp and paper facilities [56]. Also the comparison of public acceptance of biorefineries and aquaponics in a transition region compared to a non-transition region showed regional differences [55]. Particularly familiarity or previous exposure to similar technologies appears to be a factor that favors support and is strongly region-dependent [43,53,58]. A body of literature furthermore acknowledges that the expression of different socio-demographic factors such as gender, age, level of education and income, size of place of residence etc. or the belonging to certain social groups correlates with the acceptance of BE [47,51,56,58,59]. The prevalence of these factors varies regionally, which is for some factors particularly evident, for example the distinction between eastern and western Germany or between rural and urban areas, as considered in [47]. This suggests that the different ways of how people react to manifestations of the BE is an expression of embodied collective experiences that differ along socio-demographic and regional characteristics.

Important is also to understand that citizens do not assess the BE in a generalized but differentiated way. Their acceptance depends on the specific technology [43,54,55]. The literature distinguishes different BE visions that are supported by different societal or stakeholder groups [44,45,50,51]. The BE visions can be differentiated according to their relationship to nature (controlling/dominating vs. preserving/protecting), their attitude towards growth (rejecting vs. demanding), their trust in technological innovations and their openness to change. Accordingly, these visions differ in terms of the envisaged technologies. For example, genetically modified crops would be supported by a vision that believes in the controllability of nature through technological innovation, while a vision that tends to distrust technological innovation and sees the protection of nature as a priority would reject it. Regarding technology acceptance, also the distinction between different acceptance dimensions is important. Three dimensions of social acceptance were first introduced in [83] and have been referred to frequently since then [48,56,57]: (i) the “socio-political acceptance”, which reflects the acceptance of the idea of the BE in general; (ii) the “community acceptance”, which describes the acceptance of the consequences for oneself and one’s environment and which is closely related to the NIMBYism phenomenon; and (iii) “market acceptance”, which refers to the acceptance of consumer products and services offered by the BE [48].

Since the social acceptance of CBE depends on both technology and region, it is important to consider this factor when matching regions with CBE technologies. The underlying question is whether a specific technology is more likely to experience acceptance or rejection from a specific region.

In the following two sections, we will therefore present an approach that helps to (i) derive statements about the acceptability of a CBE technology from its technological characteristics (section 3.3.1) and (ii) estimate how perceptions of this technology might be shaped in a particular region (section 3.3.2).

3.3.1. CBE Technology Evaluation Matrix - social acceptance & consumer awareness

To enable an evaluation of the acceptability of a given technology we create the CBE Technology Evaluation Matrix (Figure 3). As a first step we derive from literature detailed technological factors that influence social acceptance [21,43,44,49,51,52,53,55,56,58,59]. We define for each factor whether it leads rather to an increase or decrease of acceptability and display this accordingly at the horizontal axis of the matrix. Furthermore, we arrange the factors along the vertical axis that reflects the three dimensions of acceptance (community, socio-political, and consumer). A clear demarcation is not possible and reasonable here. For example, ethical and social aspects can have an influence on both social-political and consumer acceptance.

Based on the assumption that different BE visions also differ in the perception of specific technical aspects, we researched from the studies of Hempel et al. [51,52] and Bugge et al. [44] technological factors on which there is no consensus across the visions. We adapt the categorization of Hempel et al. to build three BE visions: (i) the “sufficiency and close affinity to nature” vision focuses on ecological interrelationships and prioritizes the prevention of negative environmental impacts over economic growth; (ii) the vision “technological progress” believes in the controllability of nature through innovative technologies and thus in the possibility of achieving economic growth within planetary boundaries; (iii) “not at any price” is a vision that gives priority to preserving the current standards of living and opposes anything that potentially compromises this standard and therefore does not appear to endorse any bioeconomic transition [51,52]. In order to harmonize the visions with those of Bugge et al. [44], we assume, as suggested by Eversberg and Fritz, that the vision “sufficiency and close affinity to nature” corresponds with the vision “bio-ecology” and the vision “technological progress” with the “bio-technology” vision [47]. We position the obtained factors within the evaluation matrix by dividing the horizontal acceptance axis into three subsections, each reflecting the different views of the three BE visions. We find that the visions differ primarily in the assessment of factors from the socio-political dimension and partly from the consumer acceptance dimension.

The presented CBE Technology Evaluation Matrix for Social Acceptance can be used to assess the acceptance potential of a particular technology. For each factor, the extent to which the respective technology corresponds to this factor must be indicated. In this way, step by step, an overall picture of the acceptance potential emerges, which differentiates between the three acceptance dimensions and the three BE visions.

3.3.2. CBE Region Evaluation Matrix - social acceptance & consumer awareness

To estimate how the perception of a certain CBE technology might be shaped in a specific region, it is helpful to look at the perception, evaluation, and action patterns that the region’s population applies on post-fossil transformation in general and to relate them to the specific BE visions. The habitually applied patterns are based on internalized dispositions gained from lived experience, also referred to as “mentalities”. Eversberg and Fritz identify eleven types of mentalities and group them into three broader camps: (i) the “ecosocial camp” comprises mentalities that are clearly pro-ecological, pro-transformative und skeptical of economic growth; (ii) the “liberal-escalatory camp” includes mentalities with contented, optimistic views and consumerist attitudes that are positive towards growth; (iii) in the “authoritarian-fossilists camp” mentalities are represented that are dominated by feelings of loss and threat, that unconditionally adhere to the status quo and oppose any kind of change [47]. The different mentalities are plotted within a three-dimensional socio-ecological option space, characterizes by the dimensions “technology”, “growth” and “fossilism”. The first two dimensions range between rejection/skepticism/criticism and support/trust/focus/claim towards high-tech innovation and economic growth, respectively. The third dimension describes a continuum of views ranging from those who acknowledge the need for de-fossilization as a consequence of the need for climate protection to those who reject de-fossilization in principle or as soon as it affects the standard of living [47]. The three mentality camps are further assigned to the BE visions that they support: the “sufficiency and close to nature” vision is supported by the “eco-social camp”, the “technological progress” vision by the “liberal-escalatory camp” and the “not at any price” vision by the “authoritarian-fossilist camp”.

The authors also relate the mentalities to different socio-economic contexts to show how approval and rejection of different transformation options are distributed across different social groups. Considered socio-demographic factors are gender, age, educational level, employment (e.g., parttime, fulltime, retired), occupational group (e.g., workers, professionals, low-grade managers, service occupation, self-employment, never worked), net monthly household income, size of place of residence (e.g., metropolis, city, village), residential status (own/rent flat or house), household type/size (e.g., single-person, shared flat, single-parent, childless couples, families), size of living space [46,47]. Mentalities that favor sufficiency over growth and are skeptical towards technologies (e.g., from eco-social camp) are typically represented by women, older people, people that are retired or work part-time, that have low household incomes and live in cities. Mentalities that support growth and technology (e.g., from liberal escalatory camp) occur often among men, very young people, those still in education, from high-income households, in full-time employment, living in villages. Fossilist mentalities arise strongest among men, people from the age group 30-39, those that live in villages, work full-time and in manual jobs. Detailed information on the mentalities socio-economic characteristics can be taken from Figure 4.

We suggest that an examination of the socio-demographic characteristics of a region and their comparison with the sample average could help to derive at least initial justified assumptions about the distribution of different mentalities within a region. Socio-demographic data at the regional level should be mostly accessible. For Germany for example the census data base [84] provides relevant data at NUTS 2 level. Since mentalities are related to BE visions and since these visions can be linked to the approval/disapproval of technological characteristics, we argue that it is possible to broadly match a CBE technology with a region in terms of social acceptance.

3.4. Biomass supply chain

The successful implementation of CBE technologies depends on an adequate supply of sustainable biomass. While economies of scale favor large conversion plants, biomass supply costs can become a significant cost driver as supply distances increase, favoring smaller conversion plants. Accordingly, there is a need to optimize between plant size and a cost effective biomass supply system [75]. Several studies focus on optimizing the costs (partially including environmental and social costs) of the biomass supply chain in order to find the optimal location and/or size of the plant [69,73,74,82,85,86,87,88]. This indicates the relevance of considering biomass supply chain characteristics in spatial BE planning. Large-scale CBE plants require a secure, preferably year-round supply from a robust, efficient, and cost-effective biomass supply chain to ensure uninterrupted operation [76]. However, biomass supply chains are highly complex [24,30,42]. They involve many processing steps and stakeholders and depend on numerous external conditions. An exemplary corn stover feedstock supply system for cellulosic biorefineries includes harvesting, windrowing, baling, field bale collection, field edge stacking, transportation to and handling at a central storage facility, and transportation to the biorefinery [76]. This complexity, in combination with underdeveloped supply chain logistics, results in high logistics costs for biomass [24,30,66,78,81], which is a major challenge for the economic feasibility of biomass utilization [65,66]. This is especially valid for residual biomass streams, which are often more spatially dispersed, more contaminated, and of lower quality in terms of chemical composition and energy content than first-generation biomass [82].

It is acknowledged that differences occur in the potential of regions to provide sufficient biomass for a given CBE technology, primarily because different residual biomasses are available in different regions. Regions have unique agro-economic productivity patterns due to different agro-climatic conditions [71]. This results in different types of agricultural and forestry residues available in the region. For example, in subtropical and tropical areas, the processing of sugar cane results in the availability of sugar cane bagasse [63]; in Mediterranean regions, the processing of citrus fruits generates significant amounts of citrus waste [72]; or in the boreal region, dense forests have a high potential to provide forest residues [61,77]. In addition, the population density or consumption patterns of a region influence the availability of some municipal waste streams [10], whereas the industrial focus of a region influences the availability and types of industrial wastes and by-products [10]. However, in addition to the regional availability of a particular residual biomass, there are also region-specific factors that influence the accessibility and deliverability of that biomass. Tyndall et al. state that the availability of biomass to a defined market “is a function of several unique, dynamic, and regionally variable technological, environmental, infrastructural, economic, and social factors” [78]. The following examples illustrate the region-specific nature of each factor category: In established and diversified forest regions, there is a high availability of technology such as harvesting equipment and specialized transportation systems [78]; The potential environmental impacts of residue removal, such as erosion, nutrient loss and habitat degradation, vary by location [64,78]; The density and condition of a region’s transportation infrastructure affects the biomass supply chain [62,76,82]; Different levels of competition for biomass lead to different economic situations for new utilization paths in different regions [78,82]; Personnel trained to operate specific equipment are more likely to be available in specialized regions. [78]. These dynamic and region-specific supply chain conditions cumulate into temporally and regionally varying residual biomass prices [89]. For example, in 2017, cereal straw prices varied by about 35% between two German states during certain months [89]. Therefore, it is crucial to consider the regional biomass supply chain conditions in regional CBE planning.

The viability of a biomass supply chain is certainly more influenced by the choice of region than by the characteristics of the chosen CBE technology. However, also the CBE technologies have characteristics that affect supply chain requirements or flexibility. First and foremost, the CBE technology defines what residual biomass is needed. And this selected biomass comes with specific characteristics influencing the supply chain, like seasonality [66], spatial dispersion [62,81] or transportation and storage properties [62,65,66,73,75,81]. In addition, CBE technologies differ in the quality requirements [62,65,66] they place on the biomass and the required biomass amount [65]. For example, low-capacity, high-value conversion pathways, such as biopharmaceuticals, are likely to require lower volumes of higher quality compared to large-scale bioenergy uses. Accordingly, technological characteristics have an impact on the viability of the supply chain.

As demonstrated above, a viable biomass supply chain is dependent on both the region and the CBE technology. Therefore, in the following two sections, we present an approach that allows to match a CBE technology with a region in terms of an adequate supply with biomass. This approach is well suited for supply chains that rely on residual biomass, as this is the focus of the publications considered in the review but is also mostly applicable to first generation biomass supply chains. First, the characteristics of a given CBE technology that affect the biomass supply chain can be evaluated using the CBE Technology Evaluation Matrix for Biomass Supply Chains (Figure 5) (section 3.4.2). In a second step the Region Evaluation Matrix for Biomass Supply Chains (Figure 6) can be applied to evaluate characteristics of a given region in terms of a supply chain for the chosen residual biomass type (section 3.4.3).

From the literature we defined characteristics that influence the biomass supply chain and indicate whether they support or hinder an adequate biomass supply. To illustrate the characteristics, we provide examples about how it might be expressed in a technology or region. We further categorize each characteristic along the vertical axes as affecting either biomass availability, accessibility, or deliverability. We define each term as follows: biomass availability describes the general existence of a biomass at a certain period of time in a certain geographical area; biomass accessibility describes the attainability of an available biomass for a CBE conversion technology in terms of the reachability, extractability, obtainability, and usability; biomass deliverability describes the feasibility of overcoming the discrepancy in space and time between the point of occurrence and the point of utilization of an available and accessible biomass.

By first assessing qualitatively the supply chain characteristics of a CBE technology and then of a region, it is finally possible to compare the results and thereby derive a qualified guess as to whether a CBE technology and a region match in terms of biomass supply chain aspects. We recommend to compare technological and a regional characteristics step by step in terms of biomass availability, accessibility, and deliverability. In this way, it is possible to uncover gradually the potential of a CBE technology to mitigate unfavorable conditions of a region or, conversely, the potential of a favorable region to meet the challenging demands of a CBE technology.

3.4.1. CBE Technology Evaluation Matrix - biomass supply chain

The CBE Technology Evaluation Matrix provides a comprehensive set of technological characteristics that influence the viability of the biomass supply chain. It can be used to qualitatively evaluate a particular CBE technology in terms of biomass supply chain aspects. To demonstrate the value and applicability of the matrix, some of the technological characteristics are discussed in more detail below. We assume that for a given technology, the range of applicable residual biomass types is predefined. Therefore, biomass-specific characteristics are also addressed in this matrix.

One of the technological characteristics that could support a sufficient supply of residual biomass is the potential to adjust the installed conversion capacity. Limiting the capacity in accordance with the regional biomass availability helps to decrease transportation distances, to avoid biomass shortages or to prevent installed overcapacities. As said before it is senseful to optimize the plant size by considering both, economies of scale and the biomass supply distances [75]. If the minimum supply threshold for economic viable production is relatively low for a given CBE technology, the potential to downshift installed capacity in favor of a viable biomass supply increases. A CBE technology may also have the freedom to temporarily adjust the production volume. For instance, a company may produce a product that is demanded only during a specific season, such as domestic heating, and therefore may shut down production outside of that period. If this seasonal demand furthermore coincides with the seasonal availability of a combination of residual biomass types, there is great potential for a suitable configuration of the biomass supply chain.

Another option for the CBE technology to increase the regional availability of its feedstock is to enlarge the range of acceptable biomass types. Either the technology is able to convert a mixture of different biomass types simultaneously, or it can switch between different biomass types from time to time. Depending on the requirements of the CBE technology, chemical-physical characteristics can be derived that must be fulfilled by potential feedstocks. These characteristics can be used to find suitable residual biomass types, e.g. from biomass databases like proposed by Black et al. [63]. The matching process between CBE technology and biomass can also be supported by tools, such as the Bio2Match Tool [90]. It is designed to propose an optimal match between biomass resource and conversion technology. It is backed by databases containing extensive information on the specific requirements of a conversion technology on its feedstock and the characteristics of different types of biomasses.

Particularly in the case of spatially dispersed biomass types, the ability to move a conversion plant could help limit transportation costs. This would eliminate the need for frequent transportation of biomass to the conversion facility. Instead, the mobile plant is moved only once to where the biomass is located. This further allows to increase the overall biomass supply radius. Commercialized mobile conversion plants exists as palletization [75] and pyrolysis plants [81]. For example, Yazan et al. investigate the economic and environmental sustainability of different supply chain designs for a mobile and a fixed pyrolysis plant fed with second-generation lignocellulosic biomass, and find that the mobile plant performs slightly better, but that the number of set-ups for the plant should be kept small [81].

Further technological characteristics influencing the biomass supply chain are shown in Figure 5 in the CBE Technology Evaluation Matrix. For example, biomass specific characteristics, such as seasonality, quality, spatial dispersion, and transportation and storage properties of the demanded residual biomass type are described.

3.4.2. CBE Region Evaluation Matrix - biomass supply chain

Regional characteristics affecting the supply of biomass to a CBE technology are compiled in the CBE Region Evaluation Matrix. Following the approach of the previous section, we discuss below for selected characteristics how they potentially affect a biomass supply chain and to what extend they are region dependent.

As previously stated, different regions provide different residual biomass types. Thus, the initial step in matching a CBE technology with a region is to demonstrate that the regional availability of the demanded biomass is quantitatively sufficient. Methods to quantify the potential of different types of residual biomass at a regional level have been proposed [10,91]. Potential analyses often consider not only the availability of residual biomass, but also various technical, economic, and environmental limitations of its extractability. These are reflected in corresponding terms for the biomass potential, i.e. technical, economic and environmental potential [92]. In our CBE Region Evaluation Matrix, we reflect regionally varying restrictions for the accessibility of the demanded biomass, i.e. environmental, technical, and social constrains. Regional potential analyses often stop at theoretical or technical potential, neglecting economic, environmental, or social constraints [88,91,93]. If environmental constraints are included, they are often not considered as region-specific variables. For instance, when applying a "sustainable extraction rate" for straw, average values from the literature are used [10]. However, Paredes-Sánchez et al. demonstrate that it is possible and relevant to consider region-specific techno-economic and environmental constraints for the extraction of forest residues [94], by applying spatial data on slope, erosion risk and carbon content in soil. These are conditions that are typically reflected in environmental residual biomass potentials (see e.g. also [95]). In our literature analysis, however, we identified further environmental impacts that can be caused by the removal of residues from agricultural or forestry land, i.e. disturbance of water and nutrient cycles, biodiversity losses as well as habitat and travel corridor losses. The sensitivity towards these impacts depends on spatial conditions and should be considered in the calculation of environmental potentials through factors valid for the specific region. Furthermore, it is important to acknowledge, that residual biomass potentials are not static, but can change over time in the long term. For example, changes in agro-climatic production conditions like temperature- and rainfall patterns or changes in the frequency of natural interruptions like droughts, wind- and hailstorms, frost, floods, wildfires etc. has the potential to change a regions agricultural and forestry production focus [62,74,79]. In addition, the implementation of more efficient production methods in agriculture and forestry can lead to increased yields [63,71,75]. For instance, the use of high-quality seeds, potentially including GMOs, or precision farming are methods that are under development and have the potential to increase yields and thus the amount of residual biomass in the future. In certain regions, the latest technology in agriculture and forestry, e.g. in terms of mechanized processes or optimized cropping and fertilization patterns, may not yet be applied. When calculating future regional biomass potentials, it is therefore necessary to consider the possible development of a region towards the use of more modern production techniques. Additionally, it is important to note that literature values on yields have limited applicability to other regions or time periods.

In terms of the accessibility the regional competition for the demanded biomass plays an important role. An increasing competition can result in increased transportation distances or the need to also exploit biomass with limited accessibility. Both results in high biomass prices. If it is not possible to supply all the competing uses of biomass in a cost-effective way, there is a risk of installed overcapacity. Existing uses, especially in-plant uses are often prioritized, making it difficult for new technologies to compete. For example, forest residues are often used by plantation or sawmill owners as feedstock for in-plant CHP facilities so that they do not enter the market in the first place [82]. Zimmer et al. find that an existing demand is a decisive factor for the siting of a biofuel production facility: in some of the regions with highest forest density, they find the lowest potential for biofuel production due to the consumption of forest residues in existing CHP plants. The competitiveness of other uses and their level of biomass demand depends on the regional market for their product. If a competing use serves an expanding market, such as the wood pellet market [78], it is likely that the regional competition for the biomass will increase over time. Conversely, current competition may also come from shrinking industries, such as the pulp and paper industry [80], or from industries that are targeted to be downsized in the future, such as livestock production, making the release of residual biomass likely over time. Competing uses may also be exposed to fluctuating product markets, such as the electricity market. In these cases, a market-driven choice between two competing biomass utilization paths within a flexible and combined production system may be advantageous. For example, Black et al. note that just as some sugar mills currently choose between sugar and ethanol production depending on market conditions, it is likely that future sugarcane bagasse utilization will switch between bioethanol and bioelectricity production [63].

Further regional characteristics influencing the biomass supply chain can be taken from the CBE Region Evaluation Matrix in Figure 6. In the category of biomass accessibility, we further describe regional characteristics that influence the willingness of biomass owners to provide the demanded biomass and the regional supply chain costs. In the deliverability category, we discuss regional characteristics such as the availability of specialized equipment, centralized points for collection, storage and pre-treatment or transportation and production distribution infrastructure.

4. Discussion and Conclusions

We have conducted intensive literature research and an expert survey to (i) develop a comprehensive catalog of CBE success criteria that reflects and substantiates the regional nature of CBE, and contributes to broadening and deepening awareness and understanding of regional conditions of CBE transition; and to (ii) evolve a new methodology based on evaluation matrices that allows to match CBE technologies with CBE regions, thus providing practical guidance for reflecting regional conditions in the selection of technologies, e.g. in regional CBE transition scenarios.

The CBE Success Criteria Catalog we provide reflects a broad spectrum of success criteria from the categories: biomass resource, technological, environmental, economic, political & legislation, social, and methodological. The categories are similar to those of the PESTEL analysis (based on [96]) but are supplemented by the categories biomass resource and methodological. This comprehensive set of categories allows for a thorough analysis of the macro environment along the entire CBE supply chain. The PESTEL analysis is a well-known tool, also applied by some of the studies used to research success criteria (see Table 1) [24,28,33]. Other studies use categorization principles based on the SWOT matrix [29,30,41] or distinguishing internal and external drivers [23,33]. Even though a body of literature exists on success criteria for CBE, our criteria catalog complements the existing literature as it is more comprehensive and detailed than any other that we are aware of in the context of CBE transition.

We used a bottom-up approach to research success criteria from the literature. Accordingly, we did not pre-structure the expected results to ensure that influencing factors from all relevant areas are covered. Criteria categories were created after the research was completed by clustering the identified criteria and deriving for each cluster an appropriate category. This implies the uncertainty that important criteria or entire categories are not covered by our catalog. However, the fact that the derived criteria match those of the established PESTEL method indicates that the most important categories are captured. Furthermore, to validate and complete our catalog, we conducted an expert survey with five experts from three European countries. Although a larger number of experts from a wider geographical area would have been desirable to provide more comprehensive feedback with a more international perspective, the expert survey is a valuable contribution to the validation of our results. Our criteria catalog also adds to the existing literature by suggesting a ranking of criteria by relevance. This ranking is derived from the number of studies and experts relating to each criterion. While we acknowledge that the number of references does not necessarily correlate with its relevance, it can at least be an indicator of the attention it receives in the scientific community. The fact that only for the social criteria category an expert proposed to change the ranking of the main criteria indicates that at least the ranking at the main criteria level is consensual.

Our categorization scheme classifies success criteria based on their technology and regional specificity. The scheme supports the reflection on the importance of regional characteristics for the success of CBE implementations. Since most of the success criteria are indeed found to be technology- and region-specific, we consider the initial hypothesis to be proven: the implementation of CBE technologies depends strongly on regional conditions. This finding highlights the importance of reflecting regional conditions in effective CBE transition planning. We therefore recommend complementing national and transnational BE strategies with regional policies, as they have the potential to address the specific characteristics of a given region. Our set of region-specific CBE success criteria can serve as a starting point for developing regional strategies by supporting a thorough analysis of the regional drivers and barriers that affect CBE transition and by indicating in which areas strategies need to be region-specific.

The determination of whether a criterion is region-specific at the national or subnational level can be subject to ambiguity. For example, we determined the sub-criterion “value creation from waste & by-products” to be region-specific at the national level because the usability of a waste depends on national legislation. However, the potential for value creation from waste is not only determined by the legal framework, but also by economic conditions affecting the profitability, such as regional residual biomass costs. A more systematic categorization approach based on scientific literature that examines and demonstrates regional differences for the criterion under consideration would help to achieve a more valid and verified categorization. In the scope of this extensive literature review with 76 sub-criteria it was not possible to substantiate the decision for each criterion. Still, this could be an interesting topic for future research.

Another point for discussion is the consideration of exclusively region- and technology-specific criteria in the matching process. We argue that only criteria that affect both, technologies and regions, have an impact on the compatibility of a technology with a region. However, some criteria, initially classified to be not region-specific play a role during the matching process. For example, we include the temporal fluctuation of biomass or the biomass quality in the evaluation matrix. The reason for this is that these criteria have in combination with region-specific characteristics an influence on the compatibility of region and technology. For instance, a technology that uses a low-quality, temporally varying biomass, yet requiring a constant supply of biomass pre-treated to a high level of purity, has a greater chance of success in a region where a supply chain for this biomass already exists, with central points for collection, pre-treatment, and storage. Nevertheless, we suggest that an initial focus on region- and technology-specific criteria helps to establish an effective workflow. Examining broad criteria clusters during the development of the evaluation matrices allows to reconsider related criteria that were initially excluded from the further analysis.

With the goal of providing practical guidance in selecting appropriate CBE technologies for a given region, we developed a matching approach based on CBE Technology and Region Evaluation Matrices. It is envisaged to be used for the selection of CBE technologies for regional CBE technology scenarios. However, it could also be useful to support decisions on which CBE technologies receive regional funds or consideration in regional policies. It could further support regional development planning by identifying development needs related to key region-specific success criteria.

One limitation of our matching approach is that the evaluation matrices have only been developed for the two most relevant of the four identified region- and technology-specific criteria clusters. However, we acknowledge the importance of all four clusters and recommend considering them when selecting CBE technologies. Therefore, we suggest addressing the construction of the evaluation matrices for the two clusters “regional environmental impacts” and “regional policies & legislation” in future research.

Another limitation that reduces the practicality of the matching approach is that its application is quite time consuming. Particularly, in the case of building CBE transition scenarios, it is questionable whether a matching of each conceivable technology for each of the four identified criteria clusters is feasible. However, compared to a quantitative assessment approach as proposed for example by Croxatto Vega et al. [22] for singling out an ideal technology for a given region based on TEA and LCA, our qualitative approach is less time and data consuming and therefore more suitable for a selection among a variety of technology options. In turn it lacks the precision of a quantitative method.

Our matching approach is limited to the provision of regional and technological characteristics and their discussion and interpretation. When applying the approach, it is necessary to evaluate technologies and regions based on all characteristics from the evaluation matrices. Future research could provide guidance on how to determine the expression of a particular characteristic in a region or technology. For example, to assess the potential of a region for an adequate biomass supply, it is necessary to examine the regional competition for the desired biomass by investigating the development of current and future uses. Such further practices, though, are not addressed in this study. We do, however, provide some literature recommendations, e.g. on methods for quantifying the availability of residual biomass at regional level or how to proceed when selecting specific biomass types for a given technology.

With our evaluation matrices on the biomass supply chain, we cover a broad criteria cluster, considering the availability, accessibility, deliverability, and quality of biomass in terms of technological, legal, economic, social, and environmental aspects. By comparing evaluation results of a region with those of a technology, it is possible to determine the potential of a CBE technology to compensate for unfavorable conditions in a region or, vice versa, the capability of an advantageous region to cope with the demanding requirements of a CBE technology.

From the interpretation of the matrices, we derive a recommendation for future analysis on regional residual biomass potentials that reflect environmental restrictions: (i) In addition to commonly considered post-removal impacts such as erosion or reduction in soil organic carbon, other impacts are also important and should be considered when determining the environmental potential of residual biomass. These are, for example, the disturbance of water and nutrient cycles, the loss of biodiversity, and the reduction of habitat and migration corridors; (ii) Since the sensitivity to these impacts depends on regional characteristics, region-specific data should be included when calculating the environmental potential of residual biomass. We would also like to underline that the regional availability of residual biomass can change continuously in the long term, e.g. due to changes in agro-climatic production conditions, changes in agricultural and forestry production methods or changes in the markets for competing uses. Therefore, we recommend considering the temporal development in residual biomass potential analysis and being cautious when using data from other time frames.

The evaluation matrices on social acceptance & consumer awareness can be used to assess for a given CBE technology the potential for acceptance and to estimate how the acceptance of a given technology might evolve in a particular region. Summarizing and combining the results from the current literature on social acceptance in the context of BE makes this scientific field more accessible to more technology-oriented stakeholders. By combining the concept of different bioeconomy visions including technological characteristics with the concept of different mentalities of people with certain socio-economic characteristics, the potential acceptance of certain social groups towards certain technological characteristics can be derived.

Since social resistance can prevent the large-scale introduction of technologies in general, its potential occurrence must be considered early in CBE planning and in realistic CBE transition scenarios. This is also important because civil society tends to support different visions of the BE than BE experts from industry, politics and science [45]. For example, Dieken et al. [45] find in their literature review that among various groups such as “government & political actors”, “industry & commerce”, “media” or “research”, only the group “citizens & consumers” supports a “bio-ecology vision” similar to the “sufficiency and close affinity to nature" vision of Hempel et al. [51]. A reason for these differences lies in the way the BE is assessed. While experts apply BE-specific evaluation criteria based on technological and economic details, civil society tends to evaluate the BE not in isolation, but against a system of evaluation patterns that are habitually applied to economic, environmental and social problems [47]. This is also reflected in our technology evaluation matrix. It shows that the various bioeconomy visions differ primarily at the socio-political acceptance dimension. This suggests that social groups, and therefore regions, differ in their acceptance mainly in terms of fundamentally different perceptions. Since these are less amenable to influence than, for example, concerns relating to community acceptance, it is recommended to consider them as serious, possibly well-founded and legitimate criticism, that should be integrated with its region-specific expressions into decision making processes of early CBE planning. The technology evaluation matrix indicates that different social groups have conflicting opinions about certain technological characteristics. For instance, the "sufficiency and close affinity to nature" vision favors small technological scales over large industrial scales to avoid potential environmental impacts, while the "technological progress" vision takes the opposite view and prioritizes the potential for economies of scale. Therefore, it is necessary to identify early in the implementation process of CBE technologies, which acceptance issues can potentially arise in a certain region and to accompany its implementation process accordingly.

The prediction of social acceptance is difficult. Even though we propose an approach to deduce, how mentalities are distributed in a region, it is subject of uncertainties and inaccuracy. The correlation between mentalities and socio-demographic characteristics provided by Eversberg et al. [47] is based on survey data from Germany. Its direct applicability to other countries is very limited. They use this correlation to gain insights about which socio-economic milieus are behind the mentalities; whether the reverse prediction from milieus to mentalities, as proposed in our study, is also plausible is not discussed by them. Furthermore, it is difficult to derive from the distribution of single socio-demographic factors a picture about social milieus. Moreover, the differences of the socio-demographic characteristics between the region and the sample average can be very small not allowing any assumption about the prevalence of specific BE mentalities; this applies particularly to large and diverse regions. Even if it is possible to shed light on the prevalence of mentalities in a region, it is not clear which mentalities will actively articulate their acceptance or resistance, for example in the form of participation or protests. This applies even though we know which mentalities are more likely to actively participate and which are less likely to do so. This is especially true as the acceptance of a person can vary between the individual acceptance dimensions. A technology that is accepted from a socio-political perspective may still face opposition from a community acceptance point of view (NIMBYism). Furthermore, acceptance can be influenced by various measures. This means that the acceptance within a region does not only depend on the initial mentalities of its population, but it can be influenced and change over time, adding uncertainty to any prediction. For example, public participation in planning, equity in decision-making processes, transparent information and co-ownership by the community can improve acceptance [48,53,56].

Therefore, the proposed approach to predict a region’s affinity to one of the three bioeconomy visions should be seen as a first attempt, which has the advantage of being able to be conducted as desktop research. It should, however, be supplemented by more precise approaches such as region- and technology-specific surveys or the investigation of the civil society’s involvement during the implementation of similar technologies in a comparable region.