Introduction

The structure of the food chain, including primary production, food processing, and food consumption, has an important role in determining the economic and biophysical performance of the food systems. The modern food chain mainly follows a so-called linear model [1] where primary production, food processing, and food consumption are operating at and increasingly global scale. This pattern is not only unsustainable in terms of the environment, but it also bypasses economic opportunities for rural regions [2].

One of the main consequences of the current food system has been that primary production has become detached from the land and regions where food is processed and consumed [3, 4]. This detachment has increased dependency on external inputs [5, 6]. For example, livestock production in Europe is heavily dependent on feed imports from outside of Europe [7]. As a result of the increased geographical scale at which food is produced and processed, emissions that are embedded in the products are traded across different spatial scales [8]. This regional specialization in farming coupled with the consolidation of the food industry and the globalization of the production chains have made it increasingly challenging to reach the goals of circularity in food sector because food value chains now typically transcend the spatial scales at which accountability and legislative compliance are administered (O’Sullivan et al., under review).

Nested Circularity

Aiming to address these challenges with food system redesign, previous studies on a circular bioeconomy have called for more localized food production by better cycling of nutrients [9, 10]. However, the desired outcomes of such reintegration of local supply and demand for food must be considered carefully against the benefits of a diversified diet that global trade of food items has allowed.

In response, Koppelmäki et al. [11] introduced the concept of “Nested Circularity,” which considers the interconnected flows over spatial scales of biomasses and products, and plant nutrients, and the benefits from integrating bioenergy production in the food systems. Nested circularity encompasses an optimized food system that maximizes cycling of, and synergies between these components. The result is more local food production systems that also allow for food products to be imported and exported across different spatial scales.

In addition, we must consider with renewed urgency the need for a transition in the role of agriculture from a net consumer of fossil fuels into a producer of bioenergy. The use of agricultural land for energy production is contested because of possible food-fuel competition from the land area that is required to produce feedstock for energy production [12]. However, agricultural biomasses that do not compete with food production provide an untapped potential for bioenergy production which could replace the use of fossil fuels, and to increase the overall economic value created in food systems without the introduction of new external inputs [13,14,15].

Integrated Food and Energy Production

Koppelmäki et al., [14, 16] introduced agroecological symbiosis (AES) as a model that makes the nested circularity concept tangible via a consideration of the spatial scale of food and energy production. In the AES, primary production, food processing, and energy production are re-arranged to function in a spatial proximity that enables efficient nutrient recycling and the multifunctional use of biomass to produce food and energy. In this model, energy is produced from agricultural biomasses such as green manure crops, crop residues and manure, and by-products of food processing. After energy production, the nutrient-rich digestate is returned to the fields as a fertilizer. The resulting enhanced nutrient cycling has been shown to increase the potential primary production of food while simultaneously enhancing nutrient recycling within the farming system [14, 15], thus overcoming food-fuel competition.

While the AES model allows for agriculture to become a net producer of energy, the spatial scale of this energy production is restricted. This is because the long-distance transport of these biomasses or of produce energy is not economically feasible [17,18,19], and local energy demand does not match energy production. This is a challenge, especially in rural areas where biomasses are readily available, but the demand for energy, apart from electricity, is often limited to a farm’s own electricity and heat consumption. In the AES model, food industry partners located in close spatial proximity create a constant demand for the bioenergy.

Knowledge Gaps

In previous studies, we analyzed nested circularity and the AES model primarily from an environmental point of view [11, 14, 15, 20] without considering the role and compatibility of food processing with energy production from locally available biomasses. Partial decentralization of food processing would mean potentially substantial changes to the structure of the current food system and would impact on how economic value is aggregated and distributed across regions.

As such, a food system design aligned with nested circularity and the AES concept would result in food production operations taking place at a smaller spatial scale than that at which the current linear food system operates (Fig. 1). Primary production, energy production, and food processing would take place at local and regional scales allowing for exports and imports of food products from local to global scales. This design would result in the spatial re-distribution of the economic value in the food system.

Fig. 1
figure 1

Value flows in linear (left) and circular (right) food systems. Yellow arrows represent value flows for energy, green arrows are value flows for raw materials, and blue arrows represent economic value flows for processed goods

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The Scope

In this manuscript, we aim to fill the knowledge gap in understanding the economic impacts of such a transformation and to explore the feasibility of the regional integration of primary production with food processing and the integration of these with bioenergy production. To do this, we apply the nested circularity framework [11] to three regions in Finland, to study the accrual and distribution of economic value related to biomass production, nutrients, and energy. First, we assess the compatibility of bioenergy production with the energy consumption of regional food processing, while negating food-fuel competition. Second, we examine how integrated primary production and food processing impact the distribution of economic value across primary producers and food processors in regional food systems.

Material and Methods

Scenario Descriptions

We modeled how economic value is being created in the current food system (CFS) vs. a regionalized food system (RFS) scenario (Fig. 2). In the CFS scenario, we modeled the current system at the regional levels using the year 2019 as the reference year. The RFS scenario represented the concept of AES [14, 20] where farming, food processing, and bioenergy production are integrated at the regional scale. In the RFS scenario, we assumed that food from primary production in a given region was also processed into food products within that same region. This scenario (RFS) was contrasted with the current situation (CFS), where factors other than origin of the primary agricultural products define where food processing industries are located. We included the following agricultural products: food cereals, milk, meat, and agricultural land use related to producing these products (Supplementary Table 1). In both scenarios, produced feed was assumed to be consumed by the livestock in the same regions. Possible feed surpluses and exports were included in the economic value created in a given region. In addition to the value of food production and processing, in the RFS scenario, we included the value of energy production from potential biomasses that did not compete with food or feed production.

Fig. 2
figure 2

Current food systems (CFS) and regional food system (RFS) scenario. Black arrows represent imported inputs to the system and blue arrows represent food exports from the system. Grey arrows represent food exports and imports between the studied system and national/global food system

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Data Collection

We used official statistics about agricultural production and enterprise structure in Finland combined with data based on the literature. Agricultural data used in the study included crop production data and data about inputs used in food production from the years 2016–2020. For livestock production and food processing, we used data from 2019. The data for food processing were obtained by data request from Structural Business and Financial Statement Statistics.

Case Study Regions

We used three contrasting regional food systems in Finland as case study regions (Fig. 3). These regions were administrative areas by the Centres for Economic Development, Transport, and the Environment (ELY Centres). The ELY Centres are responsible for the government’s regional implementation and development tasks including the role of supporting economically, socially, and ecologically sustainable wellbeing [21]. The case study regions were South Savo (GRS-LVS), characterized by grass-based livestock agriculture, South Ostrobothnia (INT-LVS) with intensive livestock production, and Uusimaa (URB-CRP), a more urban region with predominantly arable crop production. The biophysical circularity of these regions was previously analyzed by Koppelmäki et al. [11]. The case study regions have contrasting types of food production and population sizes (Fig. 3). The economic value of food processing was calculated for the 15 ELY-Centre regions and the Åland islands, an autonomous region of Finland.

Fig. 3
figure 3

The location, population, and agricultural land area of three case study regions and ELY-Centre regions in Finland. The data for population year 2020 [22]. The agricultural land area and number of livestock are a 5-year average. More detailed data about livestock is reported in the supplementary material

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Analyses

In order to calculate how economic value is created in primary production and food processing, we analyzed the economic value in absolute values and per hectare of utilized agricultural land within each of the regions. The values of taxes and subsidies were not included. In addition to regional scale calculations, we analyzed how case study regions were connected to the national food system through food exports and imports.

Primary Production

The value of primary production was calculated by multiplying the quantity of produced agricultural food products by the producer prices (Table 1) and the value of produced energy. For agricultural food products, we included cereals that were used for food production, dairy, and meat products and eggs. These products were chosen for two reasons: they require food processing, and they have a high importance in terms of land use corresponding to 92–96% of the cultivation area (fallows excluded) in the case study regions (Fig. 3). We excluded from the calculation the value of horticultural plants, potatoes, and special crops such as caraway. We acknowledge their high economic value per hectare, but these crops were excluded from this study because they require less processing or have a small significance in terms of land use in the case study regions.

Table 1 Producer prices of cereals, dairy, meat and eggs, and feed [23]
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For energy production, we calculated both the economic value and quantity of produced energy. We included the current biogas production in the case study regions in the CFS and the potential energy production from biomasses that do not compete with current food or feed production in the RFS scenario. These biomasses used as feedstock for energy production were livestock manure, grass biomass from green manure, and nature management fields. In addition to energy production from primary production, we also included the quantity and value of food processing-related waste and biowaste. The biomethane potentials for these biomasses as well as the available quantities are provided in Supplementary Table 2.

The current quantity of biogas production was our own estimation based on available information from the current biogas operations and our own estimations [24]. In this study, we assumed that food processors used one-third of the energy produced in the form of electricity and two-thirds in the form of fuel [25, 26]. For electricity generation, we considered 63% conversion loss [27]. The economic value of energy production, 82 MWh−1, was based on the market value of natural gas (50 euros MWh−1) and electricity (147 euros MWh−1) which was our own estimation based on the energy prices in 2019 [28]. We acknowledge the increased energy prices at the time of writing this paper and will discuss the impact this on price volatility in the discussion.

Food Processing

We calculated the value of food processing for all regions in Finland. The current value of food processing was derived directly from the statistics which included data from the year 2019. We used the gross value of production (GV) and value added at factor cost (VA) as indicators for our analysis [29] (Supplementary Table 3). The GV of production measures the actual production output of food processing including production for personal use and production for an enterprise’s other establishments. The VA is the result when the costs of goods and services used in production are deducted from the GV [29]. Thus, these indicators were selected to demonstrate two different economic aspects: the GV to describe the value of total food processing output and the VA to describe the total value added generated in food processing. The current GV of the products included in the study made 83.5% of the total food GV of food processing in GRS-LIV, 95.7% in INT-LIV, and 59.1% in URB-CRP. In URB-CRP, the lower percentage is explained mostly by its large coffee and confectionery industries. The value of egg packing is not included due to a lack of data. We refer to the Supplementary Table 3 for the specific food processing classifications.

In the RFS scenario, we calculated the GV and VA of food processing indirectly by calculating the share of agricultural products (food cereals, milk, meat) produced in each case study region in relation to the total production of these products in Finland. This share was multiplied by the current total GV and VA of food processing for the corresponding product category in Finland. In other words, if a region would produce X% of the total nationwide milk production, the same percentage multiplied by the total GV or VA of dairy processing at the national scale. In addition to the case study regions, we calculated the GV and VA for all ELY-Centre regions in Finland to better understand the role of food processing in the case study regions as a part of the Finnish food system at the national scale. This was calculated in the same way that the GV and VA for the case-study regions were calculated. We refer to Supplementary Table 4 for the total GV and VA of each product category at the national scale.

The Market Value of External Inputs

To calculate biomass and energy costs related to agricultural production, we included the market value of imported feed, nitrogen (N) and phosphorus (P) fertilizers, and energy consumption on the farms and in food processing. The value of imported feed included the market value of industrial feed, 350 euro t−1; and when the regional feed cereal production was not sufficient to cover the feed cereal requirement of livestock, it also included the value of grain cereals at 150 euro t−1 [30]. These values were then multiplied by the feed usage of each region, which is reported in Supplementary Table 5. The number of animals is reported in the Supplementary material and feed use per animal is reported in Koppelmäki et al. [11].

The current quantity of imported mineral N and P was derived from data on regional nutrient balances [31]. These quantities were multiplied by the price of N and P in fertilizers, 0.95 euro kg−1 and 1.7 kg−1, respectively (Natural Resources Institute Finland, 2021). For the RFS scenario, we calculated the reduction in fertilization costs by assuming that, in comparison to CFS, rates of nutrient recycling were increased at the expense of the use of industrial mineral fertilizers. This increased recyclable nutrient quantity, in the RFS, resulted from biogas production using grass biomasses that do not compete with food production. For this, we included biomass from green manure leys and nature management fields.

The value of regional on-farm energy consumption was calculated by multiplying the energy consumption of agriculture and horticulture in GWh in the study regions (Supplementary material) by the energy prices [32, 33]. The value of imported feed and on-farm energy consumption remained the same in both scenarios, as agricultural production remains unchanged in the RFS scenario.

To represent energy consumption in food processing, we used the following processing activities: milling and baking for cereal processing, milk and cheese for dairy processing, and cutting, deboning, and chilling for meat processing. The energy consumption costs were calculated for the RFS scenario by multiplying the energy consumption in food processing (Table 2) with the quantities of potential biomass produced in the region for food processing. Then this result was converted to MWh, and finally multiplied by the same energy price used to calculate the value of energy production. In the CFS, the value of energy consumption was calculated indirectly as we did not have data regarding the quantities of raw material used in food processing. We used ratios for each product group (Supplementary Table 6) which we calculated by dividing the GV of food processing in the RFS by the GV of food processing in the CFS. These ratios were then multiplied by the RFS energy consumption costs.

Table 2 Energy consumption (MJ kg−1) in food processing [34]
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Regarding the quantities of biomass used in food processing, we simulated that 88% of the primary milk production is used for “table” milk production and 12% is used for cheese production. We based these factors on statistics of the current production of milk products in Finland [35]. Furthermore, for baking, we assumed that from 1 kg of grain, 0.6 kg of flour is produced and that from 1 kg of flour, 1.5 kg of bread is produced.

Connection to National and Global Scale Through Food Imports and Exports

In order to understand the role of trade for Finnish food processing, we calculated the quantities of international imports and exports of raw materials, as well as the value of exported and processed food. We assumed that the imports and exports of primary produce and each processed food commodity remained the same in both scenarios. We included corresponding products with primary production and food processing, and we made a distinction between raw materials and processed food. Data about the import and export between Finland and global were derived from the statistics ([36]; Supplementary Table 6).

Results

Economic Value in Primary Production

The current value of primary production in INT-LIV was 32% higher than in GRS-LIV and 241% higher than in URB-CRP when the value was measured per ha of utilized agricultural land (Fig. 4). In each study region, the most value in primary production was created in livestock products which corresponded to 65% of the total value of primary production in URB-CRP, 97% in INT-LIV, and 98% in GRS-LIV. Dairy was the most economically significant line of production in GRS-LIV with 70% share of value generated, and in URB-CRP, this value vas 42%. In INT-LIV, the meat production corresponded 59% of the total value generated.

Fig. 4
figure 4

The value of primary production (food and energy) and gross value in food processing (a), and the value of primary production (food and energy) and added value in food processing (b) in the three case study regions. The arrow between the points shows the change from the current food system (CFS) scenario to the regional food system (RFS) scenario

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In the CFS, the value of energy production was less than 1% in all study regions. In the RFS, the bioenergy production increased the share of the economic value of energy production up to 30% in URB-CRP. The corresponding values for INT-LIV and GRS-LIV were 15% and 17%, respectively. The main sources of energy production were manure in GRS-LIV and INT-LIV, corresponding to 45% and 50% of the total energy production, respectively, in contrast to URB-CRP where the main energy source was plant biomass, corresponding to 64% of the total energy production.

Economic Value in Food Processing

In the CFS, the absolute GV of food processing was highest in INT-LIV and smallest in GRS-LIV (Supplementary Table 7), while when the value was divided by utilized agricultural land, the highest value was created in URB-CRP which was almost sixfold the value for GRS-LIV (Fig. 4). Like in primary production, most of the GV in food processing was generated in livestock products, which corresponded to 62% of the total GV of food processing in URB-CRP, 63% in GRS-LIV, and 98% in INT-LIV. However, VA yielded opposite results for URB-CRP and GRS-LIV where the share of cereal products corresponded 54% in both regions. These contrasting results can be explained by the share of VA per product group which was the highest for cereal products, namely between 34 and 41%, while for livestock products, this was between 12 and 20%.

Compared to the CFS scenario, the GV of food processing in the RFS scenario decreased in INT-LIV and URB-CRP, while in GRS-LIV, the value increased. This increase resulted from increased processing within dairy production, covering 70% of the total GV of food processing. Although in INT-LIV, the GV on cereals had more than quadrupled; the total GV of food processing still decreased due to the halving of the GV on livestock products. In URB-CRP, the GV on all product groups declined, especially on livestock products which decreased by 87%. However, again different results were observed in the VA. The increase in the VA of food processing in GRS-LIV was 8%, while the value decreased in INT-LIV by 14% and in URB-CRP by 70%.

In the CFS, INT-LIV and URB-CRP were the two biggest regions in terms of gross value (Fig. 5; Supplementary Table 7). Together these two regions generated 46% of the total gross value of selected food processing related to the selected product categories in Finland. Four regions out of 16 generated more value than the average gross value (2855 € ha−1) of food processing in Finland. In the RFS, both the gross value and the added value were distributed more evenly across the regions. The biggest increase took place in Kainuu and Southwest Finland, 1106% and 322%, respectively, whereas in Uusimaa (URB-CRP), the gross value decreased 76%.

Fig. 5
figure 5

The gross value (euro ha − 1) in food processing (a) and the added value (euro ha − 1) in food processing (b) relative to region’s cultivated agricultural area in ELY-Centre regions in Finland in the current food system (CFS) scenario and regional food systems (RFS) scenario. The order of regions on the x-axis from left to right is according to the largest absolute gross value of food processing in the regions to the smallest value

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Energy Integration Between Primary Production and Food Processing

In the CFS, energy produced from biomasses originating from farms, food processing, and biowaste was negligible compared to energy production in the RFS (Fig. 6). In the RFS, energy production was 107% higher than consumption in GRS-LIV, 136% in INT-LIV, and 165% in INT-LIV. Dairy processing corresponded to 87.5% of the total energy consumption in INT-LIV and 70% in URB-CRP. In GRS-LIV, nearly all energy consumption in food processing took place in cereal processing.

Fig. 6
figure 6

Energy production potential (GWh) and energy consumption (GWh) in food processing in the current food system (CFS) and regional food system (RFS) scenarios in the three case-study regions (Fig. 1)

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Compared to the CFS, energy consumption in food processing in the RFS scenario decreased by 41% in INT-LIV and 77% in URB-CRP, while it increased with 591% in GRS-LIV (Fig. 6). Moreover, when the value was divided by utilized agricultural land, GRS-LIV had the highest value of energy consumption in food processing (185 euro ha−1), followed by INT-LIV (147 euro ha−1) and URB-CRP (88 euro ha−1).

Value of External Inputs in Primary Production

In the CFS, URB-CRP had the highest costs on N and P fertilizers per ha, followed by GRS-LIV and INT-LIV (Table 3). In the RFS scenario, URB-CRP remained the region with the highest costs on N and P fertilizers per ha, followed by GRS-LIV and INT-LIV, but the cost of fertilizer input per hectare decreased around 15–18% in each region compared to the CFS. The absolute costs of energy consumption in primary production were the highest in INT-LIV, while when the value was measured by utilized agricultural land, the highest costs were found in GRS-LIV (351 euro ha−1), followed by INT-LIV (329 euro ha−1) and URB-CRP (136 euro ha−1).

Table 3 Energy, mineral nitrogen (N) and phosphorus (P), and feed costs (euro ha−1) in primary production. The negative value for feed imports indicates that the value of feed exports from the region is bigger than the value of imports
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Connection to National and Global Scales Through Food Imports and Exports

The economic value of exported raw materials used in food processing was higher than the corresponding value of imported raw materials (Table 4). For processed food, the value of dairy exports was 3% higher than the value of imports, whereas the value of imported cereal products and meat was substantially higher than the value of exports.

Table 4 Average economic value of imports and exports between Finland and Global 2016–2020
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Discussion

In this study, we explored a design for a more circular food system from the economic perspective. We investigated the compatibility of energy production using biomasses from primary production with the energy consumption of food processing, following the concept of AES [14, 20]. We aimed to determine how such an integrated system of primary production, food processing, and bioenergy production would impact on the economic value in regional food systems. Our findings demonstrated that energy production from agricultural biomasses can provide enough energy for food processing at a regional scale, but that this would necessitate integrating food processing with primary production. Such a system design would, however, redistribute and equalize the economic value of the agri-food industry across regional food systems.

Integrated Food and Energy Production

A prominent catalyst for such integrated food-energy systems is the need to replace the use of fossil fuels in food processing to reduce climate emissions, and secure energy-sovereignty. The utilization of energy from agricultural biomasses that do not compete with food production requires the relocation of food processing to be closer to bioenergy suppliers. Our results showed that primary production can indeed provide enough energy for food processing at a regional scale. Results also highlighted the central role of dairy production and processing in this rebalancing of energy production and consumption. Dairy processing is more energy intensive compared to cereal and meat processing [34].

In our study, we compared potential energy production to energy consumption at the regional scale. However, the actual scale at which energy production matches energy consumption is more local. The unit size of the operation in food processing determines the share of energy needs that could be met by locally available biomasses, as transporting biomasses long distances for biogas production is not economically feasible [17,18,19]. It is also important to consider a farms’ own energy consumption. Specifically, electricity or fossil fuels used for heat generation in primary production could be replaced with bioenergy. However, the technology required for fueling farm machinery with biogas, or fueling tractors with electricity has not yet matured. Although no data on energy consumption between different production groups were available, the energy consumption per hectare in the livestock production regions was more than twice that of the crop production region. Dairy farms in particular consume a lot of energy [37]. This suggests that successfully integrating dairy processing with biogas production would necessitate the use of additional biomasses, such as multi-purpose N-fixing, soil conditioning, and nutrient recycling bioenergy leys [15], in energy production in addition to manure, as farms are likely to prioritize their own energy use first.

The biggest energy production potential from agricultural biomasses in Finland lies in grass biomass and crop residues [14, 38]. In our study, we included only grass biomass, but inclusion of other crop residues would significantly increase the energy production. For example, the techno-economical potential of straw is almost 70% compared to grass biomass [38]. The use of grass biomass and crop residues in biogas production enables the multifunctional utilization of biomass. In addition to contributing to energy production, the use of perennial grasses in biogas production would allow the system to fix nitrogen and maintain soil quality [14, 15]. By integrating biogas production into food production, mineral fertilizers can be in part replaced by digestate which also includes nutrients from grass fallows that were not otherwise used in production. Replacing external nutrient inputs to a greater extent than was achieved in our study, would require integrating more nitrogen-fixing plants, such as green manure leys, to biogas production.

Economic Significance of Integrated Primary Production and Food Processing

In our study, we showed how integrating food processing and energy production from agricultural biomasses would require the disaggregation of the current centralized structure of the food processing industry. In the current system, the economic value of primary production and food processing varied between case study regions depending on the structure of these elements. Currently, regional food processing and primary production are not regionally interdependent. For example, in the region with its highest value created in dairy farming, almost all milk was exported to other regions before being processed into dairy products and adding value. As a result, the region with high crop production created, somewhat paradoxically, the highest value in food processing from dairy products. Also, the total value of food processing in relation to the total agricultural land use was the highest in the most densely populated region, but this did not impact the value of primary production which was clearly lower than in other case study regions. Concentration of food processing industries around big cities and in densely populations regions close to big food markets is a well-known and often problematic phenomenon [3]. This phenomenon presents a challenge for rural regions because potential economic benefits are displaced to other regions. Our case study region URB-CRP, which is also the most densely populated region in Finland, is a splendid example of this. The gross value of food processing in this region corresponded to 22% of the total gross value of food processing in Finland but if the processing were based on regionally produced biomass, the corresponding value would be only 5%.

Our results showed how the integration of food processing into regional primary production had a substantial impact on the value of food processing. In most regions, we saw an increase in the economic value of food processing; a decrease in economic value was only observed in the few regions where the food processing sector is currently concentrated. This realignment resulted in a more equitable distribution of economic value among regions. In addition, the economic value of energy production increased extensively in all case study regions as current biogas production is negligible. These results demonstrate the substantial economic potential of food processing and energy production in rural regions.

In our study, the value of food processing was a zero-sum game at the national scale which meant that our regional food production scenario did not impact the overall value of food processing. However, the requirement that food production relies on local resources constrains the maximum potential of biomass throughput in the agri-food system, and therefore, it also constrains the maximum potential value that can be created indigenously within the foodscape at the regional scale. To industry, such constraints as limiting the production to rely on local resources are often seen as a valid reason to call such a change in the system unfeasible; it creates hesitation within companies as this is perceived as an impediment to economic growth, and thus one of main barriers to a transformation towards a circular bioeconomy [5, 39]. At the same time, the increased bioenergy production in the RFS reduced imports, and therefore costs, of fossil fuels at a national scale, resulting in a net economic cost reduction. These results suggest that incentivization, whether monetary or otherwise, of a more circular reconfiguration of the processing industry may be warranted.

Connection to National and Global Scales

Our RFS was connected to the national and global scales through the use of external inputs, and food exports and imports. In the case study regions, the value of food imports was relatively low in relation to the value of regional food processing. This indicates high self-sufficiency in food production. It is, however, important to acknowledge that we only included food types that are important in terms of land use in Finland. According to Sandström et al. [40], the deficit between imports and exports was over 200,000 ha of cropland which corresponds about 10% of the total agricultural area in Finland.

Our redesigned system represented a more local food system as food processing was integrated with regional primary production, and bioenergy production reduced the need for external energy inputs. It is important to note that in this system, food commodities are still exported and imported allowing for diverse diets in food consumption. If all non-processed raw materials (cereals for food, milk, and meat) would be processed in Finland, the value of food processing would increase further.

The Impact of Remarkable Increase of Energy and Fertilizer Prices

In this study, we used energy and fertilizer prices from the year 2019. At the time of writing this article, there is a lot of volatility in these prices. Natural gas prices are at an all-time high as a result of the war in Ukraine at the time of writing this article. For example, the price of natural gas has increased fourfold in a few years, and the price of fertilizers has tripled in less than a year. In fact, currently, there is even a risk of shortages in fertilizers and uncertainties related to the limited availability of natural gas.

In this study, the value of potential energy production from biomasses that did not compete with food production varied from 15 to 30% between the case study regions. The value of energy production depends on the end use of the produced energy. However, any substantial increase in energy prices will make biogas production more attractive option either from perspective of increasing energy self-sufficiency on a farm level or increasing the overall value of primary produce. Increases in fertilizer prices, in turn, will have an impact on which crops are grown and to the share of fallow land, thus having indirect impacts on commodity prices as well. However, the use of recycled nutrients becomes more economic option.

Applicability of the Results and Future Research Questions

Our study included three case study regions representing different agri-food chain structures in the context of the Finnish food systems. It is likely that similar results can be found in other countries and regions where the consolidation of food industry has taken place. However, the role of biomass in energy production is more context specific. It depends on the overall demand for available biomass, and on the local potential to produce biomass that does not compete with food production. For example, in drier climates, other renewable energy production options may provide a more feasible option than producing biogas from crop residues and rotational fallows. In addition, combining biogas production with other renewable energy sources in food processing might provide additional benefits which require further studies.

In nested circularity, the local production of biomass for food, feed, and energy, and the added value of local food processing are based on the availability of local resources [11]. Studying the economic value of food systems from a circular perspective requires separating the total value of food production into the value of food produced from regional resources and the value that is created by using imported inputs that are produced outside of the studied region. Our study included the role of food processing, but a better understanding of circularity would require also studying the changes in food production. This would, for example, mean balancing the intensity of livestock production with the regional feed production, which would likely result in substantial changes to the amounts of food produced.

Finally, a transition towards RFS would not only result in the redistribution of the economic activity across regional food systems; it would also have wider regional economic impacts for other sectors. Multiplier effects of food production on regional output can be almost the same size as the direct affect [41, 42]. In addition, the total regional economic impact of biogas production can also be bigger than the direct impact [43]. These wider economic and employment impacts of a regionalized food system would be valuable for underpinning transitions towards regional hubs for the production and processing of food and energy.

A better understanding of integrated primary production and food processing systems would require applying this study to other types of regional food systems. The possibilities of applying the methodology used in this study in other countries depend largely on the availability of data and the spatial scale at which it is available. Assessing integrated primary production and food processing systems necessitates careful consideration of feasible system boundaries. In some cases, e.g., geographically small countries, it is not necessarily feasible to have a similar study to ours. Instead, a similar comparison between countries may provide an interesting study area.

Conclusions

Our study demonstrated the role of food processing in creating value in regional food systems. This value varies between regions depending on the population of these regions and on their current consolidation of the food industry. We suggest that regionalized food processing is an integral element in circular food systems, given its important role in creating demand for primary production, both in terms of food and energy. RFSs are a contrast to concentrated and globalized food systems that have resulted in many negative environmental and socio-economic challenges. Especially for rural regions, circular food systems could provide new economic opportunities.