Reflecting Regional Conditions in Circular Bioeconomy Scenarios: A Multi-Criteria Approach for Matching Technologies and Regions
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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 1). We categorize them into the seven criteria categories: biomass resource, technological, environmental, economic, political and legislation, social, and methodological.
The main criterion we found to be mentioned most frequently in the literature, with 20 studies referring to it, is 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 and markets, as well as policies, legislation, and standards, with 18 studies relating to each. Two criteria, logistics and 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 there 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 with medium and low rankings. 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. It is also worth mentioning that three of the five experts suggest not ranking the environmental indicators, as their relevance is highly biomass-specific.
3.2. Categorization Scheme—Territory 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. The sub-criteria are categorized as either territory-specific at the regional or national level or as non-territory-specific and as either technology-specific or non-technology-specific. 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 territory-specific, with more factors being territory-specific at the regional 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, as (i) the availability of different biomass categories and their spatial density varies from region to region (see also Section 3.4); (ii) the use of biomass, especially biogenic residues, and therefore competing demands for biomass are region-specific; and (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-specific than territory-specific, such as quality aspects and temporal fluctuations, which we classify as non-territory-specific.
Criteria from the technological category are partly territory-specific at both regional and national levels, but also partly territory-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 territory-independent based 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 are perceived differently in different regions of the world. For example, highly complex and costly technologies are difficult to be financed, operated, and maintained in rural areas 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, their 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 the 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 region-dependent. Economic benefits through business diversification and multiproduct outputs, for example, in biorefineries, seem to be possible regardless of the region.
Policies and 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 legislation might also be implemented at the regional level. Regarding social criteria, we argue that the social acceptance for production sites is region-dependent, while the consumer awareness plays a role at the national level in the case of international markets. In the case of regional markets, differences in consumer acceptance are also relevant at the regional level. Finally, we argue that all methodological aspects that are relevant to assess the economic and environmental potential of CBE technologies are territory-independent.
For our further analysis, we consider only those success criteria that are both region-specific and technology-specific. We identify four relevant clusters (see Table S5): (i) a cluster of the regional biomass supply chain that includes criteria referring to the availability, accessibility, deliverability, and costs of biomass and covers aspects of technological knowledge to process the biomass; (ii) a cluster of regional environmental impacts, (iii) a cluster of regional policies and legislation; and (iv) a cluster of regional social acceptance and consumer awareness that also includes selected economic aspects. We acknowledge that all four clusters are highly relevant and recommend their consideration when selecting technologies for CBE scenarios at the regional scale. However, the remaining part of the study that presents the methodological approach to match CBE technologies with regions is limited to two of the four criteria clusters. This sufficiently demonstrates the procedure of the method and its value so that it can be applied to the other criteria clusters in subsequent studies. We chose the broadest and most relevant criteria clusters (i) biomass supply chain and (iv) social acceptance and consumer awareness. As shown in Table S5, these criteria clusters contain most of the region- and technology-specific sub-criteria and achieve the highest rankings of the sub-criteria belonging to these criteria clusters.
3.3. Social Acceptance and 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 [48].
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 [55]. Additionally, the comparison of public acceptance of biorefineries and aquaponics in a transition region compared to a non-transition region showed regional differences [53]. Particularly, familiarity or previous exposure to similar technologies appears to be a factor that favors support and is strongly region-dependent [42,52,57]. A body of literature furthermore acknowledges that various socio-demographic factors, such as gender, age, level of education and income, size of the place of residence, or the affiliation with certain social groups, correlate with the acceptance of BE [46,51,55,57,58]. The prevalence of these factors varies regionally, which is particularly evident for some factors, for example, the distinction between eastern and western Germany or between rural and urban areas, as considered by Eversberg and Fritz [46]. This suggests that the different ways how people react to manifestations of the BE is an expression of embodied collective experiences that differ along socio-demographic and regional characteristics.
It is also important to understand that citizens do not assess the BE in a generalized but in a differentiated way. Their acceptance depends on the specific technology [42,53,54]. The literature distinguishes different BE visions that are supported by different societal or stakeholder groups [43,44,49,51]. 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, the distinction between different acceptance dimensions is also important. Three dimensions of social acceptance were first introduced by Wüstenhagen et al. [82] and have been referred to frequently since then [47,55,56]: (i) “socio-political acceptance”, which reflects the acceptance of the idea of the BE in general; (ii) “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 [47].
Since the social acceptance of CBE depends on both the 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 a technology might be shaped in a particular region (Section 3.3.2).
3.3.1. CBE Technology Evaluation Matrix—Social Acceptance and 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 the literature detailed technological factors that influence social acceptance [17,42,43,48,50,51,52,53,55,57,58]. We define whether each factor leads rather to an increase or decrease in acceptability and display this accordingly along the horizontal axis of the matrix. Furthermore, we arrange the factors that reflect the three dimensions of acceptance (community, socio-political, and consumer) along the vertical axis. A clear demarcation is not possible and reasonable here. For example, ethical and social aspects can have influences 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 the studies of Hempel et al. [50,51] and Bugge et al. [43] and obtained technological factors on which there is no consensus across the visions. We adapt the categorization of Hempel et al. [51] 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 “technological progress” vision believes in the controllability of nature through innovative technologies and thus in the possibility of achieving economic growth within planetary boundaries; and (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 appears not to endorse any bioeconomic transition [50,51]. In order to harmonize the visions with those of Bugge et al. [43], we assume, as suggested by Eversberg and Fritz [46], that the vision “sufficiency and close affinity to nature” corresponds with the vision “bio-ecology” and that the vision “technological progress” corresponds with the “bio-technology” vision. 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. A user of the matrix needs to indicate for each factor the extent to which the technology corresponds to that factor. 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 and 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 to 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 [46] 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, and that unconditionally adhere to the status quo and oppose any kind of change. The different mentalities are plotted within a three-dimensional socio-ecological option space characterized 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 [46]. 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” (a detailed description for each of the 11 mentalities can be taken from Figure S1).
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. The considered socio-demographic factors are gender, age, educational level, employment (e.g., part time, full time, retired), occupational group (e.g., workers, professionals, low-grade managers, service occupations, self-employed, never worked), net monthly household income, size of the 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), and the size of the living space [45,46].
Mentalities that favor sufficiency over growth and are skeptical towards technologies (e.g., from the eco-social camp) are typically represented by women, older people, people that are retired or work part time, those who have low household incomes, and those living in cities. Mentalities that support growth and technology (e.g., from the liberal–escalatory camp) occur often among men, very young people, and those still receiving an education, from high-income households, in full-time employment, and living in villages. Fossilist mentalities arise strongest among men, people from the age group of 30–39, and those that live in villages, work full time, and in manual jobs. Detailed information on the mentalities and associated socio-economic characteristics can be taken from Figure 4 [46].
We suggest that an examination of the socio-demographic characteristics of a region and their comparison with the sample average could help to derive justified initial assumptions about the distribution of different mentalities within a region. Socio-demographic data at the regional level should be mostly accessible. For Germany, the census database [83] provides relevant data at the 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 the relationship between plant size and a cost-effective biomass supply system [74]. 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 [68,72,73,81,84,85,86]. 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 [75]. However, biomass supply chains are highly complex [26,35,38]. 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 [75]. This complexity, in combination with underdeveloped supply chain logistics, results in high logistic costs for biomass [35,38,65,77,80], which is a major challenge for the economic feasibility of biomass utilization [64,65]. 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 [81].
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 [70]. 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 [62]. Around the Mediterranean, the processing of citrus fruits generates significant amounts of citrus waste [71]. In the boreal zone, dense forests have a high potential to provide forest residues [60,76]. In addition, the population density or consumption patterns of a region influence the availability of some municipal waste streams [9], whereas the industrial focus of a region influences the availability and types of industrial wastes and by-products [9].
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. [77] 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”. The examples below 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 [77]. The potential environmental impacts of residue removal, such as erosion, nutrient loss and habitat degradation, vary by location [63,77]. The density and condition of a region’s transportation infrastructure affect the biomass supply chain [61,75,81]. Different levels of competition for biomass lead to different economic situations for new utilization paths in different regions [77,81]. A social factor is, for example, personnel trained to operate specific equipment, which is more likely to be available in specialized regions [77]. These dynamic and region-specific supply chain conditions cumulate in temporally and regionally varying residual biomass prices [87]. For example, in 2017, cereal straw prices varied by about 35% between two German states during certain months [87]. 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, technologies also have characteristics that affect supply chain requirements or flexibility. First and foremost, the CBE technology defines what residual biomass is needed. This selected biomass comes with specific characteristics influencing the supply chain, like seasonality [65], spatial dispersion [61,80], or transportation and storage properties [61,64,65,72,74,80]. In addition, CBE technologies differ in their quality requirements for the biomass [61,64,65] and the required biomass amounts [64]. For example, low-capacity, high-value conversion pathways, such as biopharmaceuticals, are likely to require lower volumes of higher quality biomass 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 of biomass. First, the characteristics of a given CBE technology that affect the biomass supply chain can be evaluated using the CBE Technology Evaluation Matrix (Figure 5). In a second step, the Region Evaluation Matrix (Figure 6) can be applied to evaluate characteristics of a given region in terms of a supply chain for the chosen residual biomass type.
From the literature, we derive characteristics that influence the biomass supply chain and indicate whether they support or hinder an adequate biomass supply. To explain the characteristics, we provide examples of how they could be shaped 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; and 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 qualitatively assessing the supply chain characteristics of a CBE technology and then of a region, it is 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 comparing technological and regional characteristics step by step in terms of biomass availability, accessibility, and deliverability. In this way, it is possible to gradually uncover 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, and to prevent installed overcapacities. As said before, it is reasonable to optimize the plant size by considering both the economies of scale and the biomass supply distances [74]. If the minimum supply threshold for economic viable production is relatively low for a given CBE technology, the potential to downshift the 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 a regional biomass supply chain.
Another option for the CBE technology to increase the available feedstock quantity 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 those proposed by Black et al. [62]. The matching process between CBE technology and biomasses can also be supported by tools such as the Bio2Match Tool [88]. They are designed to propose an optimal match between biomass resource and conversion technology and are backed by databases containing extensive information on the specific requirements of a conversion technology for its feedstock and the characteristics of different biomass types.
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 to where the biomass is located. This further allows an increase in the overall biomass supply radius. Commercialized mobile conversion plants exist as palletization [74] and pyrolysis plants [80]. For example, Yazan et al. [80] investigate the economic and environmental sustainability of different supply chain designs for mobile and fixed pyrolysis plants 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.
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, 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 how selected characteristics potentially affect a biomass supply chain and to what extent 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 [9,89]. 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 [90]. In our CBE Region Evaluation Matrix, we reflect regionally varying restrictions for the accessibility of the demanded biomass, i.e., environmental, technical, and social constraints. Regional potential analyses often stop at theoretical or technical potential, neglecting economic, environmental, or social constraints [86,89,91]. 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 [9]. However, Paredes-Sánchez et al. [92] demonstrate that it is possible and relevant to consider region-specific techno-economic and environmental constraints for the extraction of forest residues by applying spatial data on the slope, erosion risk, and carbon content in soil. These are conditions that are typically reflected in environmental residual biomass potentials (see e.g., also [93]). 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., disturbances 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 have the potential to change a region’s agricultural and forestry production patterns [61,73,78]. In addition, the implementation of more efficient production methods in agriculture and forestry can lead to increased yields [62,70,74]. 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 the literature values on yields have limited applicability to other regions or time periods.
In terms of accessibility, the regional competition for biomass plays an important role. Increasing competition can result in increased transportation distances or the need to exploit biomass with limited accessibility. Both result 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 [81]. Zimmer et al. [81] 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 [77], 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 [79], 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. [62] note that comparable to 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.
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 consider regional characteristics such as the availability of specialized equipment and centralized points for collection, storage, and pre-treatment, as well as the availability of infrastructure for transportation and product distribution.
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