Future prediction device, future prediction method, and program

Abstract

In today's rapidly changing world, even when companies set a target once and make a GHG emission reduction plan, social changes due to the promotion of utilization of renewable energy or hydrogen energy have a significant impact on the GHG reduction plans or target achievement of the companies. The purpose of the present invention is to quantitatively predict the impact of future social changes on the GHG emissions of a company.　The present invention is a future prediction device comprising: a base year company emissions calculation means for calculating the GHG emissions of a predetermined company in the base year; a social change prediction means for predicting a future social change in the industry to which the predetermined company belongs, by using a change scenario of an economic model; and future emission calculation means for calculating future GHG emissions of the predetermined company from the GHG emissions of the predetermined company calculated by the base year company emissions calculation means, on the basis of the future social change in the industry to which the predetermined company belongs and which has been predicted by the social change prediction means.

Description

[Technical field]

[0001] The present disclosure relates to a future prediction device, a future prediction method, and a program. [Background technology]

[0002] As climate change progresses, many countries around the world have set mid- to long-term GHG (Greenhouse Gas) emission reduction targets. Against this background, GHG emission reductions are required not only at the national level but also at the industrial and corporate levels, and the number of companies that proactively set GHG emission reduction targets is gradually increasing. For example, SBT (Science Based Targets: setting targets consistent with science) is one representative example of a company's GHG emission reduction target (Non-Patent Document 1), and in recent years, an increasing number of companies are setting SBTs.

[0003] In addition, in recent years, companies have been required to change their GHG emission reduction targets from merely "reducing their own company's emissions" to "reducing emissions throughout the organization's entire supply chain."

[0004] A company's GHG emissions are emissions associated with the use of fuel, electricity, etc., and can be expressed as Scope 1 emissions (direct emissions) and Scope 2 emissions (indirect emissions). Scope 1 (direct emissions) are counted as emissions from the energy conversion sector, which directly emits GHGs. Meanwhile, Scope 2 (indirect emissions) are calculated by allocating GHG emissions to users (companies, households, etc.) who use the fuel, electricity, etc. generated by direct emissions, according to their consumption of fuel, electricity, etc. The Japanese government uses these statistics.

[0005] In addition to Scope 1 and 2 emissions, it is also possible to calculate Scope 3 emissions in order to grasp GHG emissions from the supply chain (Non-Patent Document 2). Scope 1 and 2 emissions are a company's own GHG emissions associated with the use of fuel, electricity, etc., while Scope 3 emissions are indirect emissions other than Scope 1 and 2 (emissions by other companies related to the activities of a specific company (business operator)). [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] SBTi, Internet<URL:https: / / www.wwf.or.jp / activities / basicinfo / 409.html> [Non-Patent Document 2] : "Concepts for calculating supply chain emissions", Ministry of the Environment, Internet <https: / / www.env.go.jp / earth / ondanka / supply_chain / gvc / files / tools / supply_chain_201711_all.pdf> Summary of the Invention [Problem to be solved by the invention]

[0007] However, in today's rapidly changing world, even if a company sets a target and creates a GHG emission reduction plan, social changes such as the promotion of renewable energy and hydrogen energy can often have a significant impact on the company's GHG reduction plan and the degree to which it achieves its target.

[0008] The present invention has been made in consideration of the above points, and has an object to quantitatively predict the impact of future social changes on a company's GHG emissions. [Means for solving the problem]

[0009] In order to solve the above problem, the invention according to claim 1 is a future prediction device for predicting future GHG emissions, Using the formula for calculating corporate GHG emissions based on energy consumption and GHG emission coefficients by energy type, and based on corporate information on companies by industry, Using the base year corporate emission calculation method to calculate the GHG emissions of a specified company in the base year and the change scenario of the economic model 、 The future of the industry to which the specified company belongs including economic changes, weather changes, and changes in relations between nations. Social change Showing change data A means of forecasting social change; a change rate calculation means for calculating, for each year during a prediction period, a rate of change in GHG emissions in each industry for each year based on the change data calculated by the social change prediction means; and multiplying the GHG emissions of the specified company in the base year calculated by the base year company emission calculation means by the rate of change in GHG emissions of the specified company's industry for each year calculated by the change rate calculation means; and a future emission calculation means for calculating the GHG emission amount of the specified company in the future. Effect of the Invention

[0010] As described above, the present invention has the effect of making it possible to quantitatively predict the impact that future social changes will have on a company's GHG emissions. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a schematic diagram of a communication system. [Diagram 2] FIG. 2 is an electrical hardware configuration diagram of the future prediction device. [Diagram 3] FIG. 2 is a diagram illustrating an electrical hardware configuration of a communication terminal. [Figure 4] FIG. 2 is a functional configuration diagram of a future prediction device. [Diagram 5] 1 is a flowchart showing a process for automatically predicting the impact that future social changes, technological advances, etc. will have on a company's GHG emissions. [Figure 6] This is a table showing Company A's energy consumption. [Figure 7] 1 is a table showing purchased product information from a supplier. [Figure 8] This is a graph showing GHG emissions up to 2050 in the base scenario. [Figure 9] This is a graph showing GHG emissions up to 2050 under each scenario. [Figure 10] This is a graph showing the rate of change in GHG emissions for each industry in 2050. [Figure 11] This is a table showing the rate of change in GHG emissions by industry. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0013] [System configuration of the embodiment] First, an outline of the configuration of a communication system according to the present embodiment will be described with reference to Fig. 1. Fig. 1 is a schematic diagram of a communication system according to an embodiment of the present invention.

[0014] 1, a communication system 1 of this embodiment is constructed by a future prediction device 3 and a communication terminal 5. The communication terminal 5 is managed and used by a user Y.

[0015] Furthermore, the future prediction device 3 and the communication terminal 5 can communicate with each other via a communication network 100 such as the Internet. The connection form of the communication network 100 may be either wireless or wired.

[0016] The future prediction device 3 is composed of one or more computers. When the future prediction device 3 is composed of multiple computers, it may be referred to as a "future prediction device" or a "future prediction system."

[0017] The future prediction device 3 is a device that predicts GHG emissions as a future environmental load. For example, the future prediction device 3 predicts GHG emissions of a prediction target company and the company's entire supply chain due to future social changes and technological progress, and outputs result data such as a graph showing the prediction result. Examples of output methods include displaying or printing a graph related to the result data on the communication terminal 5 side by transmitting the result data to the communication terminal 5, displaying the graph on a display connected to the future prediction device 3, and printing the graph on a printer connected to the future prediction device 3.

[0018] The communication terminal 5 is a computer, and a notebook computer is shown as an example in Fig. 1. In Fig. 1, a user Y operates the communication terminal 5.

[0019] [Hardware configuration] <Hardware configuration of the future prediction device> Next, the electrical hardware configuration of the future prediction device 3 will be described with reference to Fig. 2. Fig. 2 is a diagram showing the electrical hardware configuration of the future prediction device.

[0020] As shown in FIG. 2, the future prediction device 3 is a computer and is equipped with a CPU (Central Processing Unit) 301, a ROM (Read Only Memory) 302, a RAM (Random Access Memory) 303, a HD (Hard Disk) 304, a HDD (Hard Disk Drive) controller 305, an external device connection I / F (Interface) 308, a network I / F 309, a bus line 310, and a media I / F 314.

[0021] Of these, the CPU 301 controls the overall operation of the future prediction device 3. The ROM 302 stores programs such as an IPL (Initial Program Loader) that are used to drive the CPU 301. The RAM 303 is used as a work area for the CPU 301.

[0022] The HD 304 stores various data such as programs. The HDD controller 305 controls reading and writing of various data from and to the HD 304 under the control of the CPU 301. Instead of the HD 304 and the HDD controller 305, a solid state drive (SSD) and an SSD controller may be installed.

[0023] The external device connection I / F 308 is an interface for connecting various external devices, such as a display, a speaker, a keyboard, a mouse, a USB (Universal Serial Bus) memory, and a printer.

[0024] The network I / F 309 is an interface for performing data communication via the communication network 100. The bus line 310 is an address bus, a data bus, or the like for electrically connecting each component such as the CPU 301 shown in FIG.

[0025] Furthermore, the media I / F 314 controls reading and writing (storing) of data from and to a recording medium 313 such as a flash memory. The recording medium 313 includes a DVD (Digital Versatile Disc) and a Blu-ray Disc (registered trademark).

[0026] <Hardware configuration of communication terminal> Next, the electrical hardware configuration of the communication terminal 5 will be described with reference to Fig. 3. Fig. 3 is a diagram showing the electrical hardware configuration of the communication terminal.

[0027] As shown in FIG. 3, the communication terminal 5 is a computer and is equipped with a CPU 501, a ROM 502, a RAM 503, a HD 504, a HDD controller 505, a display 506, an external device connection I / F (Interface) 508, a network I / F 509, a bus line 510, a pointing device 512, and a media I / F 514.

[0028] Of these, the CPU 501 controls the overall operation of the communication terminal 5. The ROM 502 stores programs, such as an IPL, used to drive the CPU 501. The RAM 503 is used as a work area for the CPU 501.

[0029] The HD 504 stores various data such as programs. The HDD controller 505 controls reading and writing of various data from and to the HD 504 under the control of the CPU 501. Instead of the HD 504 and the HDD controller 505, an SSD and an SSD controller may be installed.

[0030] The display 506 is a type of display means such as a liquid crystal or organic EL (Electro Luminescence) that displays various images. The external device connection I / F 508 is an interface for connecting various external devices. In this case, the external devices are a display, a speaker, a keyboard, a mouse, a USB memory, a printer, etc.

[0031] The network I / F 509 is an interface for performing data communication via the communication network 100. The bus line 510 is an address bus, a data bus, or the like for electrically connecting each component such as the CPU 501 shown in FIG.

[0032] The pointing device 512 is a type of input means for selecting and executing various instructions, selecting a processing target, moving a cursor, etc. When user Y uses a keyboard, the function of the pointing device 512 may be turned off. The media I / F 514 controls reading and writing (storing) data from and to a recording medium 513 such as a flash memory. The recording medium 513 includes DVDs, Blu-ray Discs (registered trademarks), and the like.

[0033] [Functional configuration of the future prediction device] Next, the functional configuration of the future prediction device will be described with reference to Fig. 4. Fig. 4 is a functional configuration diagram of the future prediction device in the embodiment of the present invention.

[0034] 4, the future prediction device 3 has a processing unit 20, an input / output unit 21, and a data storage unit 29. These units are functions realized by instructions from the CPU 301 in FIG. 2 based on a program. The processing unit 20 also includes a calculation unit 30, a calculation unit 40, and an alert information generation unit 50.

[0035] 2, a numerical value DB (Data Base) 3000, a numerical value DB 3001, a numerical value DB 3002, an evaluation formula DB 4000, and an evaluation formula DB 4001 are constructed.

[0036] <DB Configuration> (Numerical Value DB) In the numerical value DB3000, each piece of information indicating the input - output table for a certain base year and various evaluation condition values such as the prediction year (also referred to as the "evaluation year") is stored and managed. The input - output table is a table (described in matrix form) that represents the inter - industry transactions of goods and services conducted in a certain region (such as a country, prefecture, etc.) over a certain period (usually one year) in terms of amount. Taking a simplified example, the financial industry receives supplies of 100 yen from the information and communication industry and 200 yen from the power industry and produces 500 yen (the added value is 200 yen), which is expressed in a matrix. Note that the demand and supply of each industry match. The Ministry of Internal Affairs and Communications of Japan creates the input - output table every five years and publishes it as statistical information.

[0037] Also, in the numerical value DB3001, news information and statistical information for each industry are stored and managed.

[0038] Furthermore, in the numerical value DB3002, for each industry, corporate information about companies and information about other companies as suppliers and customers of the said companies are stored and managed. A supplier is a provider of products (goods) and services to the company to be predicted, and a customer is a customer of the company to be predicted.

[0039] The above - mentioned news information, statistical information, corporate information, and information about other companies (suppliers, customers) are indicators representing the status and development of each industry, and are regularly collected and accumulated from various information sources such as the media and government agencies.

[0040] (Evaluation Formula DB) In the evaluation formula DB4000, data of the applied general equilibrium model (base scenario) and data of the applied general equilibrium model (changed scenario) are stored and managed. The applied general equilibrium model (base scenario) is a model (simultaneous equations) corresponding to the reference scenario. The applied general equilibrium model (changed scenario) is a model corresponding to, for example, the situation where a specific industry (such as the agriculture, forestry, and fisheries industry) has developed.

[0041] The applied general equilibrium model is disclosed, for example, in reference material (Matsumoto Mitsutaka, "Analysis of the impact of ubiquitous computing on Japan's energy demand," IEEJ Trans. EIS, Vol. 125, No. 10, 2005), so a detailed explanation will be omitted here.

[0042] Moreover, the evaluation formula DB 4001 stores and manages data on the company GHG emission calculation formula (Formula 1) and the other company GHG emission calculation formula (Formula 2).

[0043] The corporate GHG emissions calculation formula (Formula 1) is used to calculate the GHG emissions of the company being forecast.

[0044]

number

[0045] The formula for calculating GHG emissions of other companies (Formula 2) is a formula for calculating GHG emissions of the entire supply chain for the company that is the subject of the prediction in (Formula 1).

[0046]

number

[0047] In addition, for Scope 3 Category 1 (purchased products and services), the GHG emissions attributable to products purchased by the company being forecast from its major suppliers are calculated using (Equation 3).

[0048]

number

[0049] The input / output unit 21 inputs each piece of information on the base year and the forecast period to the processing unit 20 via the external device connection I / F 308, the network I / F 309, or the media I / F 314 in Fig. 2. When inputting via the network I / F 309, each piece of information on the base year and the forecast period is sent from the communication terminal 5 via the communication network 100.

[0050] Furthermore, the input / output unit 21 outputs result data obtained by the processing unit 20 calculating the GHG emissions, and when alert information is generated, it shows the alert information to user Y, etc. The result data is the GHG emissions of the company that is the subject of the prediction in a specific predicted year, and the GHG emissions of other companies, such as suppliers and customers of the company that is the subject of the prediction in the specific predicted year. Examples of output include output by a display, printer, etc. connected to the external device connection I / F 308, or output by transmitting the result data from the network I / F 309 to the communication terminal 5 via the communication network 100.

[0051] The data storage unit 29 is realized by the RAM 303, the HD 304, or the medium 313 in FIG. 2, and stores various data (information).

[0052] Furthermore, the calculation unit 30 of the processing unit 20 includes a social change prediction unit 31 and a change rate calculation unit 32 .

[0053] Among these, the social change prediction unit 31 predicts future social changes in the industry to which a given company belongs and in the industries to which other companies related to the activities of the given company belong, using change scenarios of the economic model. Social changes include economic changes, weather changes, changes in relations between countries, etc.

[0054] For example, in the initial state, the social change prediction unit 31 obtains an input-output table and evaluation condition values ​​from the numerical DB 3000, and obtains data of an economic model (for example, an applied general equilibrium model (base scenario)) from the evaluation formula DB 4000, and calculates base data indicating the state of society and the economy (production value of each industry, GHG emission amount, etc.) in the prediction period, thereby generating a base scenario. In this case, the social change prediction unit 31 converts the industrial relationship table and the evaluation condition values ​​into a form that can be expressed in the applied general equilibrium model, and inputs them into the applied general equilibrium model. In addition, in order to catch predictions of social changes, the social change prediction unit 31 obtains news information and statistical information from the numerical DB 3001, and obtains data of an economic model (for example, an applied general equilibrium model (change scenario)) from the evaluation formula DB 4000, and calculates change data indicating the changing state of society and the economy (production value of each industry, GHG emission amount, etc.) in the prediction period, thereby predicting and generating a change scenario. In this case, the social change forecasting unit 31 converts the news information and statistical information into a form that can be expressed in the applied general equilibrium model, and inputs the converted information into the applied general equilibrium model.

[0055] The change rate calculation unit 32 calculates the change rate of GHG emissions for each year in each industry for each year during the prediction period, based on the change data calculated by the social change prediction unit 31. In addition, the change rate calculation unit 32 stores the calculated data of the change rate of GHG emissions in the data storage unit 29.

[0056] Next, a description will be given of the calculation unit 40 of the processing unit 20. The calculation unit 40 includes a base year corporate emission calculation unit 41, a base year other company emission calculation unit 42, an industry determination unit 43, and a future emission calculation unit 44.

[0057] Of these, the base year corporate emission calculation unit 41 calculates the GHG emission amount of a specified company in a base year.

[0058] To explain in more detail, the base year corporate emission calculation unit 41 acquires corporate information from the numerical DB 3002, and acquires the corporate GHG emission calculation formula (Formula 1) from the evaluation formula DB 4001 to calculate the GHG emission (Scope 1, 2) of the company that is the target of the prediction. If the corporate information does not include a GHG emission reduction target value of the company that is the target of the prediction, the base year corporate emission calculation unit 41 sets a GHG emission reduction target value for the prediction period and stores it in the data storage unit 29. Similarly, if the corporate information does not include an allowable deviation range (threshold) for the GHG emission reduction target value, the base year corporate emission calculation unit 41 sets an allowable deviation range (threshold) for the prediction period and stores it in the data storage unit 29.

[0059] The base year other company emissions calculation unit 42 calculates the GHG emissions of other companies related to the activities of a specified company in the base year. The GHG emissions of other companies related to the activities of a specified company include GHG emissions resulting from transactions or contracts with other companies such as suppliers or customers of the specified company. Examples of GHG emissions resulting from transactions or contracts include GHG emissions resulting from products purchased by the specified company from suppliers.

[0060] More specifically, the base year other company emission calculation unit 42 obtains other company (supplier, customer) information related to the prediction target company from the numerical DB 3002, and obtains the other company GHG emission calculation formula (Formula 2) from the evaluation formula DB 4001 to calculate the GHG emission (Scope 3) of the supply chain (excluding the prediction target company) related to the prediction target company. In addition, if the other company (supplier, customer) information does not include the GHG emission reduction target values ​​of the suppliers and customers of the prediction target company, the base year other company emission calculation unit 42 sets the GHG emission reduction target values ​​of the suppliers and customers during the prediction period and stores them in the data storage unit 29. Similarly, if the other company (supplier, customer) information does not include the deviation tolerance range (threshold value) for the GHG emission reduction target values ​​of the suppliers and customers, the base year other company emission calculation unit 41 sets the deviation tolerance range (threshold value) during the prediction period and stores it in the data storage unit 29.

[0061] The industry determining unit 43 obtains, from the numerical DB 3001, corporate information on the company to be predicted and information on other companies (suppliers, customers) related to the company to be predicted, and determines the industry to which each company belongs.

[0062] The future emission calculation unit 44 calculates the future GHG emissions of a specified company from the GHG emissions of the company calculated by the base year company emission calculation unit 41, based on future social changes in the industry to which the specified company belongs predicted by the social change prediction unit 31. In addition, the future emission calculation unit 44 calculates the future GHG emissions of other companies from the GHG emissions of other companies calculated by the base year other company emission calculation unit 42, based on future social changes in the industry to which the specified company belongs predicted by the social change prediction unit 31.

[0063] In more detail, the future emission calculation unit 44 calculates the changed GHG emission amount of the prediction target company in each prediction year by multiplying (multiplying) the GHG emission amount (Scope 1, 2) of the prediction target company in the base year of the prediction calculated by the base year company emission calculation unit 41 by the change rate of the GHG emission amount of the industry of the prediction target company in each prediction year calculated by the change rate calculation unit 32. In addition, the future emission calculation unit 44 calculates the changed GHG emission amount of each other company (supplier and customer) in each prediction year by multiplying each GHG emission amount (Scope 3) of other companies (suppliers and customers) related to the prediction target company in the base year of the prediction calculated by the base year other company emission calculation unit 42 by the change rate of the GHG emission amount of each industry of the supplier and customer in each prediction year calculated by the change rate calculation unit 32. In this way, the future emission calculation unit 44 can calculate the GHG emission amount (Scope 1, 2, 3) of the entire supply chain including the prediction target company in each prediction year.

[0064] Next, the alert information generating unit 50 of the processing unit 20 will be described. The alert information generating unit 50 includes an allowable range determining unit 51. The allowable range determining unit 51 acquires company information (in this case, GHG emission reduction target information of the company to be predicted, each GHG emission reduction target information of other companies (suppliers and customers) related to the activities of the company, and each allowable deviation range information) from the numerical DB 3002, and determines whether each of the GHG emission amounts (Scope 1, 2) and GHG emission amounts (Scope 3) calculated by the future emission calculation unit 44 exceeds the allowable deviation threshold value with respect to the reduction target value indicated by each GHG emission reduction target information. If exceeded, the alert information generating unit 50 automatically generates alert information.

[0065] [Processing or Action] Next, the processing or operation of this embodiment will be described in detail with reference to FIGS.

[0066] 5 is a flowchart showing a process for automatically predicting the impact of future social changes (technological changes, meteorological changes, changes in relations between nations, etc.) on a company's GHG emissions. In this embodiment, an example is shown in which the impact on GHG emissions of the entire supply chain, including Company A (a telecommunications company), is predicted when the utilization of hydrogen energy (hydrogen society) develops in the future and hydrogen power generation accounts for 10% of the total by 2050.

[0067] 5, the input / output unit 21 inputs information on the base year and the prediction period as information on the prediction target (S11). For example, a user Y sets the base year and the prediction period to 2015 to 2050.

[0068] Next, the social change prediction unit 31 acquires an input-output table and evaluation condition values ​​from the numerical DB 3000, and acquires data of an economic model (for example, an applied general equilibrium model (base scenario)) from the evaluation formula DB 4000, and calculates base data (production value and GHG emissions of each industry, etc.) showing the economic performance of each industry in the base scenario (S11). Figure 8 is a graph showing GHG emissions up to 2050 in the base scenario. As shown in Figure 8, the social change prediction unit 31 calculates GHG emissions as base data.

[0069] Next, the base year corporate emission calculation unit 41 obtains corporate information from the numerical DB 3002 and obtains the corporate GHG emission calculation formula (Formula 1) from the evaluation formula DB 4001 to calculate the GHG emissions (Scope 1, 2) of the company to be predicted (S12).

[0070] For example, the base year corporate emission calculation unit 41 uses (Formula 1) and corporate information (for example, values ​​in FIG. 6) to calculate the GHG emissions (Scope 1, 2) of a company (Company A) in 2015 as shown below. Note that FIG. 6 is a table showing the energy consumption of Company A. The values ​​in the table are fictitious.

[0071]

number

[0072] Similarly, if the corporate information does not include the allowable deviation range (threshold) for the GHG emission reduction target value of the company to be predicted, the base year corporate emission calculation unit 41 sets the allowable deviation range (threshold) for the company to be predicted during the prediction period, and stores it in the data storage unit 29 (S14). For example, the base year corporate emission calculation unit 41 sets "±5%" as the allowable deviation range.

[0073] Next, the base year other company emission calculation unit 42 obtains other company (supplier, customer) information related to the company being predicted from the numerical DB 3002, and obtains the other company GHG emission calculation formula (Formula 2) from the evaluation formula DB 4001, thereby calculating each GHG emission (Scope 3) of suppliers and customers related to the company being predicted (S15).

[0074] At this time, the base year other company emission calculation unit 42 uses (Formula 3) in advance to calculate, for example, GHG emissions attributable to products purchased from major suppliers in category 1 (purchased products, services) of GHG emissions (Scope 3). Here, the base year other company emission calculation unit 42 calculates GHG emissions attributable to products purchased from two major suppliers (Company B, Company C) in category 1 (purchased products, services) of Scope 3 using the values ​​shown in FIG. 7 as shown below. Note that FIG. 7 is a table showing purchased product information from suppliers. The values ​​in the table are fictitious.

[0075]

number

[0076] Next, if the corporate information does not include the allowable deviation ranges (thresholds) for the GHG emission reduction target values ​​of the suppliers and customers of the company to be forecasted, the base year other company emission calculation unit 42 sets the allowable deviation ranges (thresholds) for each supplier and customer during the forecast period and stores them in the data storage unit 29 (S17). Note that even if the corporate information does not include the allowable deviation ranges (thresholds) for at least one of the suppliers and customers, the base year other company emission calculation unit 42 sets the allowable deviation ranges (thresholds) and stores them in the data storage unit 29. Furthermore, if there are multiple suppliers and multiple customers, the base year other company emission calculation unit 42 sets a predetermined allowable deviation range (threshold) for any of these that is not included in the corporate information and stores it in the data storage unit 29.

[0077] Next, the social change prediction unit 31 obtains news information and statistical information from the numerical DB 3001, and obtains data on an economic model (e.g., an applied general equilibrium model (change scenario)) from the evaluation formula DB 4000, thereby capturing predictions of social change, and calculates change data (such as the production value and GHG emissions of each industry) showing economic predictions in the future society for each industry in the change scenario (S18).

[0078] For example, the social change prediction unit 31 picks up on news information that hydrogen power generation will be introduced at 10% by 2050, and uses an economic model to predict social changes (such as GHG emissions from each industry) due to this change for each year during the prediction period. The change data calculated by this prediction is shown as hydrogen scenarios in FIG. 9. FIG. 9 is a graph showing GHG emissions up to 2050 in each scenario. FIG. 9 shows GHG emissions due to the development of a hydrogen society when the base data shown in FIG. 8 is set to BAU (Business as usual).

[0079] Next, the change rate calculation unit 32 calculates the change rate of GHG emissions in each industry indicated by the change data calculated by the social change prediction unit 31, using the following (Equation 4) (S19).

[0080] For example, in the case of the above-mentioned hydrogen scenario, the change rate calculation unit 32 calculates the change rate of GHG emissions for each industry for each year during the prediction period in the hydrogen scenario, as shown below.

[0081]

number

[0082] Next, the change rate calculation unit 32 stores the calculated data of the change rate of the GHG emission amount in the data storage unit 29 (S20).

[0083] Next, the industry determining unit 43 obtains, from the numerical DB 3001, the company information of the company to be predicted and information of other companies (suppliers, customers) related to the company to be predicted, and determines the industry to which each company belongs (S21).

[0084] For example, the industries to which Company A and its suppliers, Company B and Company C, belong are determined (identified). Figure 11 is a table showing the rate of change in GHG emissions by industry. Figure 11 shows a case in which Company A is determined to belong to the information and communications industry, supplier Company B to the information and communications equipment industry, and supplier Company C to the industrial machinery industry. The rate of change in GHG emissions for each industry of Company A, Company B, and Company C is calculated in step S19 above.

[0085] Next, the future emission calculation unit 44 calculates the GHG emissions in the base year of the forecast of the target company and each of its other companies (suppliers and customers) by using the GHG emissions (Scope 1, 2) of the target company in the base year of the forecast calculated by the base year company emission calculation unit 41, the GHG emissions (Scope 3) of other companies (suppliers and customers) related to the target company in the base year of the forecast calculated by the base year other company emission calculation unit 42, and the change rates of the GHG emissions of the industry of the target company and the industry of other companies (suppliers and customers) related to the target company in the base year of the forecast calculated by the change rate calculation unit 32 (S22). As a result, the future emission calculation unit 44 can calculate the GHG emissions (Scope 1, 2, 3) of the entire supply chain including the target company in the base year of the forecast.

[0086] For example, the future emission calculation unit 44 calculates the GHG emissions of A company and its suppliers B and C companies in the forecast year by multiplying the GHG emissions of A company and A company's suppliers B and C companies in the base year (2015) by the rate of change in GHG emissions of the industry to which they belong. Note that if detailed information on the GHG emissions of the companies to be forecasted exists, the future emission calculation unit 44 can also calculate using a method different from the above-mentioned process.

[0087] We now discuss the hydrogen scenario in more detail.

[0088] Regarding the predicted GHG emissions (Scope 1, 2) of Company A in the year 2050 in the hydrogen scenario, the future emissions calculation unit 44 calculates the values ​​shown below.

[0089]

number

[0090]

number

[0091]

number

[0092] For example, when the GHG emission deviation K for the forecast year (2050) calculated in step S22 above with reference to the set GHG emission reduction target of company A exceeds the deviation tolerance threshold (e.g., ±5%), alert information is generated. In this case, as shown below, the GHG emissions of company A itself in Scope 1 and 2 deviate by only 1% (=1.01-1.00) due to the introduction of 10% hydrogen, but the GHG emissions of suppliers B and C in Scope 3 of company A deviate by -7% (=0.93-1.00) due to the introduction of 10% hydrogen, so the alert information generation unit 50 generates alert information.

[0093]

number

[0094]

number

[0095] [Effects of the embodiment] As described above, according to this embodiment, it is possible to quantitatively predict the impact that future social changes will have on the GHG emissions of a given company.

[0096] In addition, by quantitatively predicting the impact on GHG emissions not only of a specific company but also of other companies (suppliers, customers) related to the activities of that company, it is possible to quantitatively predict the impact on GHG emissions throughout the entire supply chain, including the specific company. This makes it possible to more accurately predict the future GHG emissions of a specific company, solving the issue of having to drastically revise GHG emission reduction plans. In addition, company managers and responsible departments can use the prediction results to help them develop proactive management strategies.

[0097] Furthermore, if the forecast results deviate from the company's GHG emission reduction target, User Y can be notified of this fact to the management or the relevant department via User Y, which can be used to develop more flexible management strategies.

[0098] 〔supplement〕 The present invention is not limited to the above-described embodiment, and may have the following configurations or processes (operations). (1) The future prediction device 3 of the present invention can be realized by a computer and a program, and this program can be recorded on a recording medium or provided via a communication network. (2) The acceptable range determination unit 51 determines whether the GHG emissions in the base year of the forecast of the company to be forecasted "exceed" the deviation tolerance threshold with respect to the set target indicated in the GHG emission reduction target information of the company to be forecasted, but is not limited to this. For example, the acceptable range determination unit 51 may determine whether the GHG emissions are "equal to or greater than" the deviation tolerance threshold with respect to the set target. Furthermore, instead of determining whether the GHG emissions exceed the deviation tolerance threshold or are equal to or greater than the threshold, the acceptable range determination unit 51 may determine only whether the emissions exceed the deviation tolerance threshold or do not exceed the deviation tolerance threshold, or only whether the emissions are equal to or greater than the deviation tolerance threshold or are not equal to or greater than the deviation tolerance threshold (below the deviation tolerance threshold). (3) In the communication between the future prediction device 3 and the communication terminal 5, other devices (servers, routers, etc.) may relay data. For example, for the sake of simplicity, this specification describes that the input / output unit 21 of the future prediction device 3 transmits change data to the communication terminal 5, but this transmission process is intended to include cases where other devices relay the change data. (4) In the above embodiment, a notebook computer is shown as an example of the communications terminal 5, but this is not limited to this and may be, for example, a desktop computer, a tablet terminal, a smartphone, a smart watch, a car navigation device, a refrigerator, a microwave oven, etc. (5) Each of the CPUs 301 and 501 may be multiple, rather than just single. (6) At least one of the units 31, 32, 41, 42, 43, 44, and 51 may use a neural network in its processing. [Explanation of symbols]

[0099] 1. Communication Systems 3 Future Prediction Device 5. Communication terminals 21 Input / output unit (an example of an output means) 29 Data Storage Section 30 Arithmetic section 31 Social change prediction unit (an example of a social change prediction means) 32 Change rate calculation unit (an example of a change rate calculation means) 40 Arithmetic section 41 Base year corporate emissions calculation section (an example of a means for calculating base year corporate emissions) 42 Base year other company emissions calculation section (an example of a method for calculating base year other company emissions) 43 Industry Determination Department 44 Future emission calculation unit (an example of a future emission calculation means) 50 Alert information generating unit (an example of an alert information generating means) 51 Tolerance range determination section 3000 Numerical Database 3001 Numerical Database 3002 Numerical Database 4000 Evaluation Formula DB 4001 Evaluation Formula DB

Claims

1. A future prediction device for predicting future GHG emissions, a base year corporate emission calculation means for calculating a GHG emission amount of a specified company in a base year based on corporate information on companies in each industry, using a corporate GHG emission calculation formula based on energy consumption and GHG emission coefficients by energy type; A social change prediction means for predicting change data showing social changes including economic changes, weather changes, and changes in relations between countries in the future of the industry to which the specified company belongs, using a change scenario of an economic model; A change rate calculation means for calculating, for each year during a prediction period, a change rate of GHG emissions in each industry for each year based on the change data calculated by the social change prediction means; a future emission calculation means for calculating the GHG emission amount of the specified company in the future by multiplying the GHG emission amount of the specified company in the base year calculated by the base year corporate emission calculation means by the change rate of the GHG emission amount of the specified company in each year calculated by the change rate calculation means; A future prediction device comprising:

2. 2. The future prediction device according to claim 1, a base year other company emission calculation means for calculating other company GHG emissions related to the activities of the specified company in the base year based on company information on companies in each industry, using a other company GHG emission calculation formula for calculating GHG emissions of an entire supply chain related to the specified company in the company GHG emission calculation formula; The social change prediction means predicts change data of other companies indicating the social changes in the future of the industry to which the other companies belong, using a change scenario of the economic model; The future emission calculation means calculates the other company's future GHG emissions by multiplying the other company's GHG emissions in the base year calculated by the base year other company emission calculation means by the rate of change in GHG emissions of the other company's industry in each year calculated by the change rate calculation means.

3. 2. The future prediction device according to claim 1, A future prediction device characterized by having an output means for outputting alert information when the future GHG emissions of the specified company calculated by the future emissions calculation means exceed or are equal to or greater than the allowable deviation range from the GHG emission reduction target value.

4. 3. The future prediction device according to claim 2, A future prediction device characterized by having an output means for outputting alert information when the future GHG emissions of the other companies calculated by the future emission calculation means exceed or are equal to or greater than the allowable deviation range from the GHG emission reduction target value.

5. 5. The future prediction device according to claim 1, wherein the economic model is an applied general equilibrium model.

6. 2. The future prediction device according to claim 1, wherein at least one of said means uses a neural network.

7. A future prediction method executed by a future prediction device that predicts future GHG emissions, comprising: A base year corporate emission calculation step of calculating the GHG emissions of a specified company in a base year based on corporate information on the company for each industry using a corporate GHG emission calculation formula based on the energy consumption amount and the GHG emission coefficient for each energy type; A social change prediction step of predicting change data indicating social changes including economic changes, weather changes, and changes in relations between countries in the future of the industry to which the specified company belongs, using a change scenario of an economic model; A change rate calculation step of calculating a change rate of GHG emissions in each industry for each year based on the change data calculated by the social change prediction step for each year during the prediction period; a future emission calculation step of calculating the GHG emission amount of the specified company in the future by multiplying the GHG emission amount of the specified company in the base year calculated in the base year company emission calculation step by the change rate of the GHG emission amount of the specified company's industry in each year calculated in the change rate calculation step; A future prediction method comprising the steps of:

8. A program causing a computer to execute the method according to claim 7.

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