Biomass utilization assistance device, method, and program

Abstract

A biomass utilization support device that acquires biomass information relating to the bio-based material and product information relating to each of the plurality of products, the product information including information of the material constituting the product; estimating an appropriate value for each of the plurality of products using a machine learning model trained to estimate an appropriate value for the amount of replacement when a portion of the material constituting the product is replaced with the bio-based material, and the acquired biomass information and product information; an environmental load index calculation unit that calculates, for each of the plurality of products, an environmental load index when a portion of the material constituting the product is replaced with the bio-based material by a replacement amount represented by the estimated appropriate value; and outputting support information in which the estimated appropriate value and the calculated environmental load index are listed for each of the plurality of products.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to a biomass utilization support device, a biomass utilization support method, and a biomass utilization support program. BACKGROUND

[0002] In view of the global warming problem in recent years, it is required to cope with carbon neutrality in production of products. For example, it is promoted to use resources from living things (biomass) as materials of products.

[0003] As a technology related to utilization of biomass, a biomass effective utilization support system capable of efficiently processing biomass is proposed. The system inputs a kind and an input amount of input biomass selected from a group consisting of sewage sludge, livestock manure, waste wood, kitchen garbage, and other waste. In addition, the system registers, in advance, inherent characteristic data possessed by equipment classes including pretreatment devices, anaerobic digesters, dewatering machines, heat exchangers, incinerators, and power generators, selects at least one from among the registered equipment classes, and constructs a processing flow of biomass. Furthermore, the system calculates at least one of a set equipment structure, a water quality of wastewater generated when processing biomass in the processing flow and an amount of waste generated, a generation amount of biogas, and an energy that can be recovered from the biogas or a power generation energy that can generate power, and an operation cost required when operating a processing facility.

[0004] [Related Art Documents] Patent Literature Patent Literature 1: Japanese Patent Application Publication No. 2021-149905 SUMMARY

[0005] Problems to be Solved by the Invention The obtained bio-based material has a large deviation in physical properties such as the degree of impurities, and thus it is difficult to determine an appropriate utilization destination each time.

[0006] An object of the present disclosure is to provide a biomass utilization support device, method, and program capable of supporting determination of an appropriate utilization destination of a bio-based material.

[0007] Means for Solving the Problems To achieve the above object, a biomass utilization support device of the present disclosure includes: an acquisition unit that acquires biomass information related to a bio-based material and product information related to each of a plurality of products, the product information including information on materials that make up the product; an estimation unit that estimates, using a machine learning model trained to estimate the appropriate value of the replacement amount in a case where a part of the material that makes up a product is replaced with a bio-based material, and the biomass information and the product information acquired by the acquisition unit, an appropriate value related to each of the plurality of products; a calculation unit that calculates, for each of the plurality of products, an environmental load index in a case where a part of the material that makes up the product is replaced with the bio-based material in an amount indicated by the appropriate value estimated by the estimation unit; and an output unit that outputs, for each of the plurality of products, support information in which the appropriate value estimated by the estimation unit and the environmental load index calculated by the calculation unit are tabulated. Thereby, it is possible to support the determination of an appropriate utilization destination of a bio-based material.

[0008] In addition, the estimation unit can estimate, for each of the plurality of products, a replacement amount for which the characteristic value becomes a threshold value or more in a case where the replacement amount is varied by a plurality of values, or a replacement amount corresponding to the characteristic value of a higher-order regulation, using the machine learning model trained using a plurality of training data in which the characteristic value representing the characteristics of the product in a case where a part of the material that makes up the product is replaced with a bio-based material and the replacement amount are varied by a plurality of values. In addition, the estimation unit can estimate, for each of the plurality of products, a replacement amount for which the characteristic value becomes optimal in a case where the replacement amount is varied by a plurality of values. Thereby, for a bio-based material whose quality is unstable, it is possible to easily acquire support information.

[0009] In addition, the biomass information includes a physical property value of the bio-based material and a biomass degree that is a proportion of biomass with respect to the entire bio-based material, and the product information includes a composition ratio of the material that makes up the product.

[0010] In addition, the calculation unit can calculate, as the environmental load index, a carbon dioxide emission amount that is reduced in a case where the bio-based material is used. Thereby, as a utilization destination of a bio-based material, it is possible to select a product for which the reduction effect of carbon dioxide emission amount is high.

[0011] Further, the biomass utilization support device of the present disclosure can also be one that includes a collection section that collects, from the Internet, associated information for each of the plurality of products based on a keyword extracted from the biomass information and the product information acquired by the acquisition section, and the output section outputs the support information relating to each of the plurality of products with the associated information collected by the collection section added thereto. Alternatively, the associated information can be information related to environmental load included in patent literature or policy. Thus, it is also possible to select a product that is a utilization destination of a bio-based material with reference to the associated information.

[0012] Further, the biomass utilization support method of the present disclosure, which is executed by a biomass utilization support device including an acquisition section, an estimation section, a calculation section, and an output section, includes the following steps: the acquisition section acquires biomass information related to a bio-based material and product information relating to each of a plurality of products, the product information including information on materials that constitute the product; the estimation section estimates, using a machine learning model trained to estimate an appropriate value of a replacement amount in a case where a part of a material that constitutes a product is replaced with a bio-based material, the appropriate value relating to each of the plurality of products, using the biomass information and the product information acquired by the acquisition section; the calculation section calculates, for each of the plurality of products, an environmental load index in a case where a part of a material that constitutes the product is replaced with the bio-based material in an amount indicated by the appropriate value estimated by the estimation section; and the output section outputs, for each of the plurality of products, support information in which the appropriate value estimated by the estimation section and the environmental load index calculated by the calculation section are tabulated.

[0013] Further, the biomass utilization support program of the present disclosure is for causing a computer to function as an acquisition section that acquires biomass information related to a bio-based material and product information relating to each of a plurality of products, the product information including information on materials that constitute the product; an estimation section that estimates, using a machine learning model trained to estimate an appropriate value of a replacement amount in a case where a part of a material that constitutes a product is replaced with a bio-based material, the appropriate value relating to each of the plurality of products, using the biomass information and the product information acquired by the acquisition section; a calculation section that calculates, for each of the plurality of products, an environmental load index in a case where a part of a material that constitutes the product is replaced with the bio-based material in an amount indicated by the appropriate value estimated by the estimation section; and an output section that outputs, for each of the plurality of products, support information in which the appropriate value estimated by the estimation section and the environmental load index calculated by the calculation section are tabulated.

[0014] [Inventive Effects] According to the biomass utilization support device, method, and program of the present disclosure, it is possible to support the determination of an appropriate utilization destination of a bio-based material. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a block diagram showing a hardware structure of the biomass utilization support device.

[0016] Figure 2 is a block diagram showing an example of a functional structure of the biomass utilization support device.

[0017] Figure 3 is a diagram showing an example of the material DB.

[0018] Figure 4 is a diagram showing an example of the product DB.

[0019] Figure 5 is a diagram showing an example of the output support information.

[0020] Figure 6 is a flowchart showing an example of the biomass utilization support processing. DETAILED DESCRIPTION

[0021] Hereinafter, an example of the present embodiment will be described with reference to the drawings.

[0022] Figure 1 is a block diagram showing a hardware structure of the biomass utilization support device 10. As shown in Figure 1 , the biomass utilization support device 10 has a CPU (Central Processing Unit) 12, a memory 14, a storage device 16, an input device 18, an output device 20, a storage medium reading device 22, and a communication I / F (Interface) 24. Each structure is connected in a manner capable of communicating with each other via a bus 26.

[0023] The biomass utilization support program for executing each processing related to the biomass utilization support method described later is stored in the storage device 16. The CPU 12 is a central arithmetic processing unit that executes various programs or controls each structure. That is, the CPU 12 reads out a program from the storage device 16 and executes the program using the memory 14 as a work area. The CPU 12 performs the control of each structure and various arithmetic processing according to the program stored in the storage device 16.

[0024] The storage 14 is constituted by a RAM (Random Access Memory), and temporarily stores programs and data as a work area. The storage device 16 is constituted by a ROM (Read Only Memory), an HDD (Hard Disk Drive), an SSD (Solid State Drive), or the like, and stores various programs including an operating system and various data.

[0025] The input device 18 is, for example, a keyboard, a mouse, or the like, and is a device for performing various inputs. The output device 20 is, for example, a display, a printer, or the like, and is a device for outputting various information. The output device 20 can also function as the input device 18 by employing a touch panel display.

[0026] The storage medium reading device 22 performs reading of data stored in various storage media such as a CD (Compact Disc)-ROM, a DVD (Digital Versatile Disc)-ROM, a Blu-ray disc, a USB (Universal Serial Bus) memory, writing of data to the storage medium, and the like. The communication I / F 24 is an interface for communication with other devices, and uses standards such as Ethernet (registered trademark), FDDI, or Wi-Fi (registered trademark).

[0027] Next, the functional structure of the biomass utilization support device 10 will be described. Figure 2 is a block diagram showing an example of the functional structure of the biomass utilization support device 10. As shown in Figure 2 the biomass utilization support device 10 includes a acquisition unit 30, an estimation unit 32, a calculation unit 34, a collection unit 36, and an output unit 38 as the functional structure. In addition, a material DB (database) 40, a product DB 42, an estimation model 44 are stored in a prescribed storage area of the biomass utilization support device 10. Each of the functional structures is realized by the CPU 12 reading out the biomass utilization support program stored in the storage device 16, expanding and executing in the storage 14.

[0028] The material information relating to various materials including the bio-based material is stored in the material DB 40. In the case where the material is a bio-based material, the material information is an example of the biomass information of the present disclosure. The material information of the bio-based material includes the functional group equivalent, the physical property values of the bio-based material such as the structure, and the proportion of the biomass with respect to the entire bio-based material, that is, the biomass degree. In the material information, in addition to these, for example, the purity, the molecular weight, the dielectric constant, the length of the main chain, the length of the side chain, the glass transition temperature (Tg), and the like are included. In addition, the material information also includes impurity information indicating information of impurities included in the material. In the impurity information, in addition to the ratio of the impurities included in the material, the same information as the above-described material information is included. Figure 3 An example of the material DB 40 is shown.

[0029] In the product DB 42, the product information including the information of the materials constituting the product, specifically, the composition ratio, relating to each of a plurality of products is stored. In addition, the product information also includes the characteristics of the product such as the dielectric constant, the Tg, the viscosity, the flowability, and the like. Figure 4 An example of the product DB 42 is shown.

[0030] The acquisition unit 30 receives the designation of the bio-based material to be utilized, acquires the material information of the designated bio-based material from the material DB 40. In addition, the acquisition unit 30 acquires the product information of each product from the product DB 42, and acquires the material information of the materials constituting the product from the material DB 40.

[0031] In addition, the material DB 40 and the product DB 42 are not limited to the case where they are stored in the biomass utilization support device 10, and can be stored in an external storage device or the like. In this case, the acquisition unit 30 can access the external storage device or the like to acquire the material information and the product information.

[0032] The estimation unit 32 uses the estimation model 44 and the material information and the product information acquired by the acquisition unit 30 to estimate, for each of a plurality of products, an appropriate value of the replacement amount in the case where a part of the materials constituting the product is replaced with the bio-based material. The estimation model 44 is, for example, a machine learning model constituted by a neural network or the like. The estimation model 44 is trained to estimate the above-described appropriate value based on the material information and the product information.

[0033] Specifically, the estimation model 44 is trained using training data including a characteristic value representing a characteristic of a product in a case where a part of a material constituting the product is replaced with a bio-based material and a replacement amount, and a plurality of training data in which a plurality of values are varied as the replacement amount. The training data is prepared in advance through experiments. Also, the estimation unit 32 uses the material information and the product information, creates input data including a composition ratio of the product in a case where a plurality of values are varied as the replacement amount for each of a plurality of products, and inputs to the estimation model 44, thereby estimating a characteristic value for each replacement amount. The estimation unit 32 estimates a replacement amount for which the estimated characteristic value is equal to or greater than a threshold value, or a replacement amount corresponding to a predetermined number of characteristic values as an appropriate value. In a case where the predetermined number is one, the estimation unit 32 estimates a replacement amount for which the characteristic value is the best as an appropriate value.

[0034] The calculation unit 34 calculates, for each of a plurality of products, an LCA (Life Cycle Assessment; environmental load index) value in a case where a part of a material constituting the product is replaced with a bio-based material in an amount represented by the appropriate value estimated by the estimation unit 32 using the material information and the product information. The LCA value is an index that quantitatively represents an environmental load in a life cycle of a product. The calculation unit 34, for example, calculates a carbon dioxide emission amount reduced in a case where it is replaced with a bio-based material as the LCA value. More specifically, the calculation unit 34 calculates a carbon dioxide emission amount before replacement based on the product information and the material information of the product before replacement with a bio-based material. In addition, the calculation unit 34 calculates a carbon dioxide emission amount in a case where a part of the material of the product is replaced with a bio-based material in an amount represented by the appropriate value. Then, the calculation unit 34 calculates a reduction amount by subtracting the carbon dioxide emission amount after replacement from the carbon dioxide emission amount before replacement.

[0035] The collection unit 36 collects, for each of a plurality of products, associated information from the Internet based on a keyword extracted from the material information and the product information acquired by the acquisition unit 30. The associated information is, for example, information related to an environmental load included in a patent document or a policy. More specifically, the information related to the environmental load is information disclosed in a patent document regarding an effect on LCA achieved by a product of a specific composition, appropriateness in a case where a specific material is applied to a product, and the like, information disclosed in a policy regarding an effect on LCA required for a product, information on a kind of material restricted by a regulation, and the like.

[0036] For example, the collection section 36 extracts product names, material names, and the like as keywords from the material information and the product information, and searches the Internet for documents containing the extracted keywords. The collection section 36 collects sentences containing predetermined expressions such as effects, LCA, and the like, and sentences before and after the sentences, from the searched documents as the association information. In addition, the collection section 36 can collect sentences described in specific item columns as the association information with respect to documents in which formats are predetermined such as patent documents, policies, and the like. In addition, the collection section 36 can collect the association information by inputting the searched documents to a machine learning model trained to extract appropriate portions from input documents as the association information and output. In addition, the collection section 36 can attach information such as document names of the searched documents to the association information.

[0037] The output section 38 outputs support information in which the appropriate value estimated by the estimation section 32, the LCA value calculated by the calculation section 34, and the association information collected by the collection section 36 are listed. Figure 5 An example of the output support information is shown in Table 1.

[0038] Next, the action of the biomass utilization support device 10 of the present embodiment will be described.

[0039] The material information related to various materials containing bio-based materials is stored in the material DB 40, and the product information including information of materials constituting products is stored in the product DB 42 for each of a plurality of products. In addition, a estimation model 44 trained to estimate an appropriate value of a replacement amount using training data containing a characteristic value representing a characteristic of a product in a case where a part of a material constituting the product is replaced with a bio-based material and a plurality of training data in which the replacement amount is varied by a plurality of values is stored in a prescribed storage area of the biomass utilization support device 10. In this state, if output of support information is instructed, the biomass utilization support device 10 executes the biomass utilization support processing shown in Fig. 2. Figure 6

[0040] In step S10, the acquisition section 30 receives designation of a bio-based material to be utilized, and acquires material information of the designated bio-based material from the material DB 40. Next, in step S12, the acquisition section 30 selects a product for which the processing of steps S14 to S20 described later is not processed as a processing target product from the product DB 42, and acquires product information of the processing target product. Further, the acquisition section 30 determines a material constituting the product from a composition ratio contained in the acquired product information, and acquires material information of the determined material from the material DB 40.

[0041] ​Next, in step S14, the estimation section 32 creates input data containing the composition ratio of the product in the case where the plurality of values of the substitution amount are varied, using the material information and the product information acquired in the above steps S10 and S12, for the product of the processing target. Also, the estimation section 32 estimates the characteristic value for each substitution amount by inputting the created input data to the estimation model 44, thereby estimating the substitution amount for which the characteristic value is optimal as the appropriate value.

[0042] Next, in step S16, the calculation section 34 calculates the LCA value in the case where a part of the material constituting the product of the processing target is substituted for the bio-based material with the substitution amount indicated by the appropriate value estimated in the above step S14, using the acquired material information and product information. Next, in step S18, the collection section 36 collects the associated information from the Internet based on the keywords extracted from the acquired material information and product information, for the product of the processing target.

[0043] Next, in step S20, the output section 38 temporarily stores the appropriate value of the estimated substitution amount, the calculated LCA value, and the collected associated information in correspondence with the identification information of the product of the processing target in a prescribed storage area.

[0044] Next, in step S22, it is determined whether or not the processing of the above steps S14 to S20 is completed for all the products for which the product information is stored in the product DB 42. In the case where there is a product which is not processed, the processing returns to step S12, and in the case where the processing of all the products is completed, the processing proceeds to step S24. Note that, the case where all the products for which the product information is stored in the product DB 42 are taken as the object is not restrictive, and a product designated in advance can be selected as the processing target.

[0045] In step S24, the output section 38 creates and outputs the support information in which the identification information of the product, the appropriate value of the substitution amount, the LCA value, and the associated information are listed, which are temporarily stored in the prescribed storage area, and the biomass utilization support processing is completed.

[0046] As explained above, the biomass utilization support device of the present embodiment acquires biomass information related to a bio-based material and product information related to each of a plurality of products, the product information including information of materials constituting the product. Further, the biomass utilization support device estimates an appropriate value related to each of the plurality of products using a machine learning model trained to estimate the appropriate value of a replacement amount in a case where a part of the materials constituting the product is replaced with the bio-based material and the acquired biomass information and product information. In addition, the biomass utilization support device calculates an environmental load index in a case where a part of the materials constituting the product is replaced with the bio-based material in an amount indicated by the estimated appropriate value for each of the plurality of products. Then, the biomass utilization support device outputs support information in which the estimated appropriate value and the calculated environmental load index are listed for each product. Thereby, it is possible to support the judgment of an appropriate utilization destination of the bio-based material. For example, based on the output support information, a product in which the balance between the replacement amount of the bio-based material and the contribution to the LCA effect is the best is selected, and replacement with the bio-based material is performed, whereby it is possible to achieve a balance between the realization of the LCA effect such as reduction in the amount of carbon dioxide emitted and the maintenance of the performance of the product.

[0047] In addition, the processing performed by the CPU to read in and execute the software (program) in the above-described embodiments can also be performed by various processors other than the CPU. As the processor in this case, a PLD (Programmable Logic Device) such as an FPGA (Field-Programmable Gate Array) in which the circuit structure can be changed after manufacture, an ASIC (Application Specific Integrated Circuit) having a circuit structure designed specifically to perform a certain processing, and the like, that is, a dedicated circuit, can be exemplified. In addition, the processing can be performed by one of these various processors, or can be performed by a combination of two or more processors of the same kind or different kinds (for example, a combination of a plurality of FPGAs and a CPU and an FPGA). In addition, more specifically, the hardware structure of these various processors is a circuit in which circuit elements such as semiconductor elements are combined.

[0048] Further, in the above-described embodiments, the case where the biomass utilization support program is stored (installed) in the storage device in advance is explained, but the present application is not limited thereto. The program can also be provided in a manner of being stored in a storage medium such as a CD-ROM, a DVD-ROM, a USB memory, and the like. In addition, the program can also be provided in a manner of being downloaded from an external device via a network.

[0049] Hereinafter, the supplementary items are described.

[0050] (Paragraph 1) A biomass utilization support device includes: an acquisition unit that acquires biomass information related to a bio-based material and product information related to each of a plurality of products, the product information including information of materials that constitute the product; a presumption unit that presumes, using a machine learning model trained to presume the appropriate value of a replacement amount in a case where a part of a material that constitutes a product is replaced with a bio-based material, and the biomass information and the product information acquired by the acquisition unit, an appropriate value related to each of the plurality of products; a calculation unit that calculates, for each of the plurality of products, an environmental load index in a case where a part of a material that constitutes the product is replaced with the bio-based material in an amount indicated by the appropriate value presumed by the presumption unit; and an output unit that outputs, for each of the plurality of products, support information in which the appropriate value presumed by the presumption unit and the environmental load index calculated by the calculation unit are tabulated.

[0051] (Paragraph 2) The biomass utilization support device according to Paragraph 1, wherein the presumption unit presumes, for each of the plurality of products, as the appropriate value, a replacement amount in which the characteristic value becomes a threshold value or more or a replacement amount corresponding to an upper limit of a predetermined number of characteristic values, using the machine learning model trained using a plurality of training data in which a characteristic value representing a characteristic of the product in a case where a part of a material that constitutes the product is replaced with a bio-based material and a replacement amount are varied.

[0052] (Paragraph 3) The biomass utilization support device according to Paragraph 2, wherein the presumption unit presumes, as the appropriate value, a replacement amount in which the characteristic value becomes the best, in a case where the characteristic value is varied.

[0053] (Paragraph 4) The biomass utilization support device according to any one of Paragraphs 1 to 3, wherein the biomass information includes a physical property value of the bio-based material and a biomass degree that is a proportion of biomass with respect to the entire bio-based material, the product information includes a composition ratio of the material that constitutes the product.

[0054] (Note 5) The biomass utilization support device according to any one of Note 1 to Note 4, wherein the calculation section calculates a carbon dioxide emission amount reduced in the case of being replaced with the bio-based material as the environmental load index.

[0055] (Note 6) The biomass utilization support device according to any one of Note 1 to Note 5, wherein includes a collection section that collects, from the Internet, for each of the plurality of products, associated information based on a keyword extracted from the biomass information and the product information acquired by the acquisition section, the output section imparts the support information related to each of the plurality of products with the associated information collected by the collection section and outputs.

[0056] (Note 7) The biomass utilization support device according to Note 6, wherein the associated information is information related to environmental load included in a patent document or a policy.

[0057] [Legend] 10: biomass utilization support device 12: CPU 14: memory 16: storage device 18: input device 20: output device 22: storage medium reading device 24: communication I / F 26: bus 30: acquisition section 32: estimation section 34: calculation section 36: collection section 38: output section 40: material DB 42: product DB 44: estimation model

Claims

1.A biomass utilization support device comprising: an acquisition unit that acquires biomass information related to a bio-based material and product information related to each of a plurality of products, the product information including information on materials that constitute the product; an estimation unit that estimates, using a machine learning model trained to estimate an appropriate value of a replacement amount of a part of a material that constitutes a product to a bio-based material, and the biomass information and the product information acquired by the acquisition unit, the appropriate value related to each of the plurality of products; a calculation unit that calculates, for each of the plurality of products, an environmental load index in a case where a part of a material that constitutes the product is replaced with the bio-based material in an amount indicated by the appropriate value estimated by the estimation unit; an output unit that outputs, for each of the plurality of products, support information in which the appropriate value estimated by the estimation unit and the environmental load index calculated by the calculation unit are tabulated. 2.The biomass utilization support device according to claim 1, wherein the estimation unit estimates, for each of the plurality of products, as the appropriate value, a replacement amount in which the characteristic value becomes a threshold value or more or a replacement amount corresponding to an upper-level prescribed characteristic value, using the machine learning model trained using a plurality of training data in which a characteristic value indicating a characteristic of the product in a case where a part of a material that constitutes the product is replaced with a bio-based material and the replacement amount are varied. 3.The biomass utilization support device according to claim 2, wherein the estimation unit estimates, as the appropriate value, a replacement amount in which the characteristic value becomes the best. 4.The biomass utilization support device according to any one of claims 1 to 3, wherein the biomass information includes a physical property value of the bio-based material and a biomass degree that is a proportion of biomass with respect to the entire bio-based material, the product information includes a composition ratio of the material that constitutes the product. 5.The biomass utilization support device according to any one of claims 1 to 3, wherein the calculation unit calculates, as the environmental load index, a carbon dioxide emission amount that is reduced in a case where the bio-based material is replaced. 6.The biomass utilization support device according to any one of claims 1 to 3, comprising a collection unit that collects, for each of the plurality of products, associated information from the Internet based on a keyword extracted from the biomass information and the product information acquired by the acquisition unit, the output unit outputs the support information related to each of the plurality of products to which the associated information collected by the collection unit is added. 7.The biomass utilization support device according to claim 6, wherein ​ The association information is information related to environmental load included in patent literature or policy. 8.A biomass utilization support method executed by a biomass utilization support device including an acquisition unit, an estimation unit, a calculation unit, and an output unit, the biomass utilization support method comprising: the acquisition unit acquires biomass information related to a bio-based material, and product information related to each of a plurality of products, the product information including information of materials constituting the product; the estimation unit estimates, using a machine learning model trained to estimate the appropriate value of a replacement amount in a case where a part of a material constituting a product is replaced with a bio-based material, and the biomass information and the product information acquired by the acquisition unit, an appropriate value related to each of the plurality of products; the calculation unit calculates, for each of the plurality of products, an environmental load index in a case where a part of a material constituting the product is replaced with the bio-based material in a replacement amount represented by the appropriate value estimated by the estimation unit; and the output unit outputs, for each of the plurality of products, support information in which the appropriate value estimated by the estimation unit and the environmental load index calculated by the calculation unit are tabulated. 9.A biomass utilization support program for causing a computer to function as: an acquisition unit that acquires biomass information related to a bio-based material, and product information related to each of a plurality of products, the product information including information of materials constituting the product; an estimation unit that estimates, using a machine learning model trained to estimate the appropriate value of a replacement amount in a case where a part of a material constituting a product is replaced with a bio-based material, and the biomass information and the product information acquired by the acquisition unit, an appropriate value related to each of the plurality of products; a calculation unit that calculates, for each of the plurality of products, an environmental load index in a case where a part of a material constituting the product is replaced with the bio-based material in a replacement amount represented by the appropriate value estimated by the estimation unit; and an output unit that outputs, for each of the plurality of products, support information in which the appropriate value estimated by the estimation unit and the environmental load index calculated by the calculation unit are tabulated.

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