Carbon dioxide emission prediction system and method therefor

Abstract

Provided are: a carbon dioxide emission prediction system for predicting, in consideration of damage resulting from a natural disaster such as an earthquake and the process of recovery therefrom, carbon dioxide emissions that are likely to occur when a natural disaster has occurred, as a result of damage due to the natural disaster or in the process of recovery therefrom; and a method for the carbon dioxide emission prediction system. A carbon dioxide emission prediction system 100 comprises: a disaster characteristic data acquisition unit 110 that acquires disaster characteristic data indicating characteristics of a natural disaster based on information relating to the type, scale, and position of the disaster; an impact degree determination unit 120 that determines the degree of impact of the natural disaster on the basis of the disaster characteristic data; an economic data calculation unit 130 that acquires economic data recorded in advance and calculates damage data corresponding to the degree of impact; an economic prediction data acquisition unit 140 that acquires economic prediction data based on the economic data and incorporating the damage data; and a carbon dioxide emission prediction unit 150 that predicts carbon dioxide emissions on the basis of the economic prediction data.

Description

Carbon dioxide emission prediction system and method

[0001] The present invention relates to a carbon dioxide emission prediction system and method.

[0002] In recent years, global warming has become a problem not only in Japan but all over the world, and reducing greenhouse gas emissions is an urgent task. Carbon dioxide is one of the most prominent greenhouse gases, and in Japan, various efforts are being made to reduce carbon dioxide emissions.

[0003] For example, companies are being asked to reduce their carbon dioxide emissions, and further efforts are being made, led by the Ministry of Economy, Trade and Industry, to establish a trading market in which companies can buy and sell carbon dioxide emissions. Patent Document 1 discloses a technology that refers to evaluation information that associates carbon dioxide emission rights with the evaluation of the carbon dioxide emission rights, and effectively selects a supplier of carbon dioxide emission rights according to the evaluation of the carbon dioxide emission rights.

[0004] Incidentally, economic forecasting simulations have traditionally been conducted using a variety of methods, and in recent years, for example, the research community has made great progress in research into macroeconomic forecasting, and the Cabinet Office has announced that economic forecasting simulations are becoming a reality.

[0005] It is also known that carbon dioxide emissions can be estimated by using input-output tables to multiply the production volume in each industry and economic zone by a carbon dioxide emission coefficient (amount of carbon dioxide emissions per unit of production).

[0006] Furthermore, in general, when a natural disaster such as an earthquake occurs, methods and tools are known that estimate the events that will occur under a certain scenario (for example, in the case of an earthquake, the ground shaking and tsunami wave height, etc.) and estimate the damage to structures, etc. In response to the damage to the structures, it is thought that carbon dioxide will be emitted in accordance with the business activities related to the removal, disposal, and reconstruction of the structures to recover from the damage.

[0007] Japanese Patent Application Laid-Open No. 2022-48205

[0008] However, while the conventional systems and methods described above can calculate various economic indicators based on the expected damage that would occur in the event of a natural disaster such as an earthquake, it is difficult to predict the carbon dioxide emissions that would be generated in the damage or reconstruction process that would occur in the event of a natural disaster.

[0009] Therefore, the present invention aims to provide a carbon dioxide emission prediction system and method that takes into account the damage that will occur when a natural disaster such as an earthquake occurs and the process of recovery from it, and predicts the carbon dioxide emissions that will occur during the damage and recovery process when a natural disaster occurs.

[0010] A carbon dioxide emission prediction system according to one embodiment of the present invention is a carbon dioxide emission prediction system that predicts carbon dioxide emissions, and includes a disaster characteristic data acquisition unit that acquires disaster characteristic data that indicates the characteristics of natural disasters based on information about the type, scale, and location of the disaster; an impact determination unit that determines the impact of the natural disaster based on the disaster characteristic data; an economic data calculation unit that acquires at least economic data and calculates damage data according to the impact; an economic forecast data acquisition unit that acquires economic forecast data based on the economic data to which the damage data has been added; and a carbon dioxide emission prediction unit that predicts carbon dioxide emissions based on the economic forecast data.

[0011] According to this aspect, the impact determination unit determines the impact of a natural disaster based on the disaster characteristics data acquired by the disaster characteristics data acquisition unit, the economic data calculation unit acquires at least economic data and calculates damage data according to the impact. The economic forecast data acquisition unit acquires economic forecast data based on the economic data to which the damage data has been added, and the carbon dioxide emission prediction unit predicts carbon dioxide emissions based on this economic forecast data. In this way, the carbon dioxide emission prediction system takes into account the damage that will occur in the event of a natural disaster such as an earthquake and the process of recovery from it, and can predict carbon dioxide emissions that will occur in the event of a natural disaster and during the process of recovery.

[0012] In the above aspect, the impact determination unit may determine the level of the natural disaster, which indicates the degree of damage caused by the natural disaster, based on the disaster characteristic data, and the economic data calculation unit may calculate damage information, which indicates the scale of damage caused by the natural disaster, as damage data, based on the level of the natural disaster.

[0013] According to this aspect, the economic data calculation unit calculates damage information indicating the scale of damage caused by a natural disaster as damage data based on the level of the natural disaster determined by the impact determination unit, thereby making it possible to appropriately grasp damage information caused by a natural disaster. As a result, it is possible to appropriately consider the damage that will occur when a natural disaster such as an earthquake occurs and the process of recovery from that, and to predict carbon dioxide emissions that will occur during the damage and recovery process when a natural disaster occurs.

[0014] In the above aspect, the damage information may include at least one of the number of collapsed buildings, the number of partially collapsed buildings, the number of deaths, the number of injured people, the monetary value of waste, the cost of reconstruction / repair, and the period of reconstruction / repair.

[0015] According to this aspect, various items are taken into account as damage information, and therefore it is possible to more appropriately consider the damage that will occur in the event of a natural disaster such as an earthquake and the process of recovery from that, and to predict the carbon dioxide emissions that will occur in the event of a natural disaster and the process of recovery.

[0016] In the above aspect, the economic forecast data acquisition unit may acquire economic forecast data for a predetermined period in the event of a natural disaster.

[0017] According to this aspect, the economic forecast data acquisition unit acquires economic forecast data for a specified period in the event of a natural disaster, and therefore can predict not temporary and / or actual carbon dioxide amounts, but carbon dioxide emissions over a specified period that will occur during the damage and reconstruction process in the event of a natural disaster.

[0018] In the above aspect, the economic forecast data may include at least one of GDP, production volume, production value, consumption volume, and consumption value of a product.

[0019] According to this aspect, it is possible to appropriately predict the carbon dioxide emissions that will occur during the damage and reconstruction process in the event of a natural disaster, depending on the various items included in the economic forecast data and their combinations.

[0020] In the above aspect, the carbon dioxide emission prediction unit may predict the amount of carbon dioxide emissions based on the economic prediction data, using a pre-recorded carbon dioxide emission coefficient.

[0021] According to this aspect, the carbon dioxide emission prediction unit predicts the amount of carbon dioxide emissions based on economic forecast data using a pre-recorded carbon dioxide emission coefficient, and therefore can appropriately predict the amount of carbon dioxide emissions.

[0022] In the above aspect, the carbon dioxide emission coefficient may be updateable.

[0023] According to this aspect, by appropriately updating the carbon dioxide emission coefficient, which is expected to change in the future, it is possible to calculate carbon dioxide emissions with higher accuracy, leading to future predictions.

[0024] In the above aspect, the economic data calculation unit may include the amount of carbon dioxide emission predicted by the carbon dioxide emission prediction unit in the economic data.

[0025] According to this aspect, the carbon dioxide emission amount predicted by the carbon dioxide emission prediction unit is reflected in the pre-recorded economic data, so that the economic data calculation unit can obtain economic data that is more appropriately reflected.

[0026] In the above aspect, the economic data calculation unit may further include carbon pricing in the economic data.

[0027] According to this aspect, the economic data calculation unit can acquire economic data that more appropriately reflects carbon pricing.

[0028] In the above aspect, the information regarding the type, scale, and location of the disaster may include at least one of the number of buildings, attributes of each building, and attributes of each infrastructure structure in the area affected by the natural disaster.

[0029] According to this aspect, various factors that affect natural disasters are taken into consideration, so that information on damage caused by natural disasters can be grasped with higher accuracy.

[0030] A carbon dioxide emission prediction method according to one aspect of the present invention is a carbon dioxide emission prediction method executed by a computer, and includes a disaster characteristic data acquisition step of acquiring disaster characteristic data indicating the characteristics of a natural disaster based on information regarding the type, scale, and location of the disaster; an impact determination step of determining the impact of the natural disaster based on the disaster characteristic data; an economic data calculation step of acquiring at least economic data and calculating damage data according to the impact; an economic forecast data acquisition step of acquiring economic forecast data based on the economic data to which the damage data has been added; and a carbon dioxide emission prediction step of predicting carbon dioxide emissions based on the economic forecast data.

[0031] According to this aspect, the impact determination step determines the impact of a natural disaster based on the disaster characteristic data acquired in the disaster characteristic data acquisition step, the economic data calculation step acquires at least economic data and calculates damage data according to the impact, the economic forecast data acquisition step acquires economic forecast data based on the economic data to which the damage data has been added, and the carbon dioxide emission prediction step predicts carbon dioxide emissions based on this economic forecast data. In this way, the carbon dioxide emission prediction method takes into account the damage that will occur in the event of a natural disaster such as an earthquake and the process of recovery from it, and can predict carbon dioxide emissions that will occur in the event of a natural disaster and in the process of recovery.

[0032] According to the present invention, it is possible to provide a carbon dioxide emission prediction system and method that takes into account the damage that will occur when a natural disaster such as an earthquake occurs and the process of recovery from that damage, and predicts the carbon dioxide emissions that will occur during the damage and recovery process when a natural disaster occurs.

[0033] 1 is a functional block diagram showing each function of a carbon dioxide emission prediction system 100 according to one embodiment of the present invention. FIG. 1 is a diagram showing an example of setting data related to a hypothetical natural disaster according to one embodiment of the present invention. FIG. 2 is a diagram showing an example of the level and content of the impact of a hypothetical natural disaster according to one embodiment of the present invention. FIG. 3 is a diagram showing an example of damage data corresponding to the impact of a hypothetical natural disaster according to one embodiment of the present invention. FIG. 4 is a diagram showing an example of economic data used in the carbon dioxide emission prediction system 100 according to one embodiment of the present invention. FIG. 5 is a diagram showing an example of economic forecast data used in the carbon dioxide emission prediction system 100 according to one embodiment of the present invention. FIG. 6 is a diagram showing an example of a carbon dioxide emission coefficient. FIG. 7 is a diagram showing an example of carbon dioxide emissions calculated based on the production value of a product included in economic forecast data and the carbon dioxide emission coefficient for that production value. FIG. 8 is a diagram showing an example of carbon dioxide emissions calculated based on the number of employees included in economic forecast data and the carbon dioxide emission coefficient for the employee. FIG. 9 is a diagram showing an example of carbon dioxide emissions calculated based on formed capital included in economic forecast data and the carbon dioxide emission coefficient for the formed capital. FIG. 10 is a diagram showing an example of a carbon dioxide emissions forecast for a predetermined period displayed on a monitor or the like. FIG. 11 is a diagram showing an example of a GDP forecast for a predetermined period displayed on a monitor or the like. 1 is a diagram showing an example of a table displaying the GDP growth rate, economic loss, and additional carbon dioxide emissions due to the impact of an earthquake over a predetermined period. FIG. 2 is a flowchart showing a carbon dioxide emission prediction method M100 executed by a carbon dioxide emission prediction system 100 according to an embodiment of the present invention.

[0034] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Note that the embodiment described below is merely a specific example for carrying out the present invention and is not intended to limit the scope of the present invention. Furthermore, to facilitate understanding of the description, the same components in each drawing will be designated by the same reference numerals wherever possible, and duplicate descriptions may be omitted.

[0035] <One Embodiment> Figure 1 is a functional block diagram showing each function of a carbon dioxide emission prediction system 100 according to one embodiment of the present invention. As shown in Figure 1, the carbon dioxide emission prediction system 100 includes a disaster characteristic data acquisition unit 110, an impact determination unit 120, an economic data calculation unit 130, an economic forecast data acquisition unit 140, and a carbon dioxide emission prediction unit 150. The carbon dioxide emission prediction system 100 is configured to be able to directly or indirectly cooperate with a database unit 10, a natural disaster calculation system 20, and an economic calculation system 30, and predicts carbon dioxide emissions. However, the carbon dioxide emission prediction system 100 is not limited to this configuration. For example, the carbon dioxide emission prediction system 100 may include at least a portion of the database unit 10, the natural disaster calculation system 20, and the economic calculation system 30, and may include these components to form a carbon dioxide emission prediction system.

[0036] In this embodiment, an earthquake is used as an example of a hypothetical natural disaster, but this is not limited to this, and other disasters that affect economic indicators and carbon dioxide emissions, such as strong winds, heavy rain, heavy snow, floods, high tides, tsunamis, and volcanic eruptions, may also be used.

[0037] The disaster characteristic data acquisition unit 110 acquires disaster characteristic data that indicates the characteristics of a virtual natural disaster based on information regarding the type, scale, and location of the disaster.

[0038] For example, for a virtual natural disaster, the user (a) sets the type, scale, location, etc. of the natural disaster. Specifically, the user sets the type of natural disaster as "earthquake," the scale as "magnitude 7," and the location as "XX city."

[0039] The type, scale, and location of the (a) natural disaster set in this manner may be returned as (b) disaster characteristic data using the natural disaster calculation system 20. Specifically, the (b) disaster characteristic data is a response amount indicated by residual deformation, maximum acceleration, maximum velocity, maximum displacement, etc. of a structure caused by a natural disaster (earthquake) estimated based on the type of natural disaster, "earthquake," the scale, "magnitude 7," and the location, "XX city," etc.

[0040] Furthermore, by setting more detailed information about the virtual natural disaster, the disaster characteristics data acquisition unit 110 can acquire disaster characteristics data with higher accuracy.

[0041] FIG. 2 is a diagram illustrating an example of configuration data related to a virtual natural disaster according to one embodiment of the present invention. As shown in FIG. 2 , the configuration items include location, epicenter, magnitude, maximum seismic intensity (not necessary for a detailed simulation, as this information is obtained as an analysis result), and analysis area. Note that, when performing a detailed simulation based on geophysical knowledge, some of these items can also be obtained as an analysis result. Furthermore, including information on the number of buildings, attributes of individual buildings, and attributes of individual infrastructure structures present in or affecting the specified location, epicenter, and analysis area allows for more accurate understanding of earthquake damage information, as described below. Specifically, the amount and type of debris generated by an earthquake and the disruption of logistics due to infrastructure damage can affect economic indicators and carbon dioxide emissions.

[0042] Of the setting items shown in Figure 2, those that can be set by the user are set by the user, and the other items may be set separately based on statistical information or a database that holds statistical information.

[0043] The impact determination unit 120 determines the impact of a virtual natural disaster based on the disaster characteristic data acquired by the disaster characteristic data acquisition unit 110. For example, the impact determination unit 120 determines the level of the virtual natural disaster based on the amount of response of structures caused by an earthquake ((b) disaster characteristic data) calculated by the natural disaster calculation system 20. Here, the level of a natural disaster indicates the degree of damage caused by a natural disaster, and the impact determination unit 120 quantitatively determines the scale of the impact on society caused by a natural disaster.

[0044] FIG. 3 is a diagram showing an example of the impact level and content of a virtual natural disaster according to one embodiment of the present invention. As shown in FIG. 3, the impact assessment unit 120 references thresholds and other data previously set in the database unit 10, etc., and determines the level of the earthquake (Levels 1 to 5) based on physical values ​​((b) disaster characteristics data) indicated by residual deformation, maximum acceleration, maximum velocity, and maximum displacement that will occur in a structure due to the virtual natural disaster (earthquake). The impact assessment unit 120 then determines the impact level (c) (collapse, major damage, moderate damage, minor damage, minor damage) corresponding to the earthquake level (Levels 1 to 5). Note that the assessment may be performed for each individual structure or an average assessment of a range of structures. This depends on the granularity of the data provided by the (b) disaster characteristics data.

[0045] The economic data calculation unit 130 acquires at least (e) economic data and calculates (d) damage data according to the (c) impact level determined by the impact level determination unit 120. For example, the economic data calculation unit 130 calculates, as the (d) damage data, damage information indicating the scale of damage caused by the virtual natural disaster based on the level of the virtual natural disaster determined by the impact level determination unit 120.

[0046] 4 is a diagram showing an example of damage data corresponding to the impact of a virtual natural disaster according to one embodiment of the present invention. As shown in FIG. 4, (d) the damage data includes damage information such as the number of collapsed buildings, the number of partially collapsed buildings, the number of deaths, the number of injured people, the monetary value of disaster waste, the reconstruction and repair costs of each structure, and the reconstruction and repair period of each structure.

[0047] Specifically, it is preferable that each value of this damage information is calculated according to the degree of impact (collapse, major damage, moderate damage, minor damage, minor damage) determined by the impact determination unit 120, but furthermore, each value may be calculated based on the setting items shown in Figure 2 and a database that holds other statistical information.

[0048] Furthermore, the economic data calculation unit 130 acquires, for example, the (e) economic data that is recorded in advance in the database unit 10. The economic data calculation unit 130 may acquire the (e) economic data directly or indirectly, or may acquire the (e) economic data by calculating it using various data such as the value of the economy and infrastructure and a loss function.

[0049] Fig. 5 is a diagram showing an example of economic data used in the carbon dioxide emission prediction system 100 according to one embodiment of the present invention. As shown in Fig. 5, the economic data calculation unit 130 acquires, as (e) economic data, the number of industrial sectors, the number of companies, the number of workers, the total deposits, loans, and funds of each company, the total amount of deposits, loans, and capital of each household, the employment status of each household, borrowing interest rates, taxes (value-added tax rate, income tax, corporate tax, etc.), the cost required for building repairs, and the time required for building repairs.

[0050] The economic data calculation unit 130 may obtain this information based on separate statistical information, a database that holds statistical information, or by user input (setting).

[0051] Note that (e) economic data is not limited to these pieces of information, but includes, for example, data necessary for calculating the economic forecast data (trends in economic indicators including GDP and inflation rate) described below, and if this data is diverse and highly accurate, more accurate economic forecast data can be calculated.

[0052] The economic forecast data acquisition unit 140 acquires (f) economic forecast data based on (e) economic data acquired by the economic data calculation unit 130, to which (d) damage data calculated by the economic data calculation unit 130 has been added. For example, the economic forecast data acquisition unit 140 acquires (f) economic forecast data for a predetermined period in the event of a hypothetical natural disaster (earthquake) using the economic calculation system 30, based on the (d) damage data calculated by the economic data calculation unit 130 and the (e) economic data acquired by the economic data calculation unit 130.

[0053] Specifically, the economic calculation system 30 outputs (f) economic forecast data that takes into account the impact of a hypothetical natural disaster (earthquake) occurring, based on (d) damage data due to the hypothetical natural disaster (earthquake) calculated by the economic data calculation unit 130 and (e) economic data acquired by the economic data calculation unit 130. Note that here, the economic calculation system 30 may output economic forecast data for the case in which the hypothetical natural disaster (earthquake) does not occur, so that economic forecast data can be compared depending on whether or not the hypothetical natural disaster (earthquake) occurs.

[0054] 6 is a diagram showing an example of economic forecast data used in the carbon dioxide emission forecasting system 100 according to one embodiment of the present invention. As shown in FIG. 6 , the (f) economic forecast data output by the economic calculation system 30 includes the inflation rate, economic growth rate, GDP, employment information, product production volume, production value, consumption volume and consumption value, product export volume, export value, import volume and import value, monthly tax collection by the government and local governments, monthly consumption of each household and the government and local governments, earthquake insurance payments to insureds, disaster relief funds from the government and local governments, and government debt. It is preferable that the GDP, employment information, product production volume, production value, consumption volume and consumption value, product export volume, export value, import volume and import value be for each of the above-mentioned industrial sectors.

[0055] The carbon dioxide emission prediction unit 150 predicts (g) carbon dioxide emissions based on the (f) economic forecast data acquired by the economic forecast data acquisition unit 140. For example, the carbon dioxide emission prediction unit 150 predicts (g) carbon dioxide emissions based on the (f) economic forecast data acquired by the economic forecast data acquisition unit 140, using a carbon dioxide emission coefficient set in advance in the database unit 10 or the like. Here, the carbon dioxide emission coefficient is, for example, the carbon dioxide emission amount relative to the production value of a product, the carbon dioxide emission amount per employee, and the carbon dioxide emission amount per formed capital, and may be set in advance in the database unit 10 or the like.

[0056] Fig. 7 is a diagram showing an example of carbon dioxide emission coefficients. As shown in Fig. 7, the carbon dioxide emission coefficients set for each industrial sector are a carbon dioxide emission coefficient for the production value of products, a carbon dioxide emission coefficient for employees, and a carbon dioxide emission coefficient for formed capital. Here, the carbon dioxide emission coefficient for the production value of products is the amount of carbon dioxide emitted per 1 million yen of the production value of products, the carbon dioxide emission coefficient for employees is the amount of carbon dioxide emitted per employee, and the carbon dioxide emission coefficient for formed capital is the amount of carbon dioxide emitted per 1 million yen of formed capital.

[0057] The carbon dioxide emission coefficient is not limited to these, and may be, for example, a carbon dioxide emission coefficient for the production volume, consumption volume, and consumption value of a product, or a carbon dioxide emission coefficient for the export volume, export value, import volume, and import value of a product, or may be a carbon dioxide emission coefficient for other items that affect carbon dioxide emissions (for example, the items shown in FIG. 6). Furthermore, these items and carbon dioxide emission coefficients may be combined.

[0058] The carbon dioxide emission prediction unit 150 uses a carbon dioxide emission coefficient such as that shown in Figure 7, which is stored in advance in the database unit 10, etc., to predict (g) carbon dioxide emissions based on the production value of products included in the (f) economic forecast data acquired by the economic forecast data acquisition unit 140.

[0059] 8A is a diagram showing an example of calculating carbon dioxide emissions based on the production value of a product included in economic forecast data and the carbon dioxide emission coefficient for the production value. As shown in FIG. 8A, the carbon dioxide emission prediction unit 150 calculates the carbon dioxide emissions by multiplying the production value of the product by the carbon dioxide emission coefficient for the production value for each industrial sector ID. Here, the production value of the product for each industrial sector ID is obtained based on the production value of the product included in the (f) economic forecast data output by the economic calculation system 30 as shown in FIG. 6, and the carbon dioxide emission coefficient for the production value may be obtained based on the carbon dioxide emission coefficient previously set in the database unit 10 as shown in FIG. 7.

[0060] 8B is a diagram showing an example of calculating carbon dioxide emissions based on the number of employees included in the economic forecast data and the carbon dioxide emission coefficient for each employee. As shown in FIG. 8B, the carbon dioxide emission prediction unit 150 calculates the carbon dioxide emissions by multiplying the number of employees by the carbon dioxide emission coefficient for each employee for each industry sector ID.

[0061] 8C is a diagram showing an example of calculating carbon dioxide emissions based on the formed capital included in the economic forecast data and the carbon dioxide emission coefficient for the formed capital. As shown in FIG. 8C, the carbon dioxide emission prediction unit 150 calculates the carbon dioxide emissions by multiplying the formed capital by the carbon dioxide emission coefficient for the formed capital for each industry sector ID.

[0062] The number of employees and formed capital in Figures 8B and 8C are obtained based on the information contained in the (f) economic forecast data output by the economic calculation system 30 as shown in Figure 6, and the carbon dioxide emission coefficient for employees and the carbon dioxide emission coefficient for formed capital may be obtained based on the carbon dioxide emission coefficient set in advance in the database unit 10 or the like as shown in Figure 7.

[0063] Note that the carbon dioxide emission coefficients used here, such as those shown in FIG. 7, may be updatable. Recently, as environmental issues such as global warming are addressed not only in Japan but around the world, awareness of carbon dioxide emissions has increased, and technologies related to reducing carbon dioxide emissions have also developed. In other words, it is expected that carbon dioxide emission coefficients will become smaller in the future. By appropriately updating the carbon dioxide emission coefficients previously set in the database unit 10 or the like in accordance with such circumstances, it is possible to calculate carbon dioxide emissions with higher accuracy, leading to future predictions.

[0064] In this way, (g) the carbon dioxide emission amount calculated by the carbon dioxide emission prediction unit 150 may be displayed on a display device such as a monitor, for example.

[0065] 9A is a diagram showing an example of a predicted amount of carbon dioxide emissions for a predetermined period displayed on a monitor or the like. Fig. 9A shows predicted carbon dioxide emissions in the event of a hypothetical natural disaster, an earthquake, and predicted carbon dioxide emissions in the event that no earthquake occurs. Furthermore, predicted carbon dioxide emissions in the event of an earthquake are shown for both a case where infrastructure has been reinforced (infrastructure reinforced) and a case where infrastructure has not been reinforced (infrastructure not reinforced).

[0066] Regarding infrastructure reinforcement, for example, as shown in FIG. 2, the attributes of individual buildings and individual infrastructure structures may be set by the user, based on statistical information, or based on a database containing statistical information. Here, it can be seen that even in the event of an earthquake, if infrastructure has been reinforced, a sudden increase in carbon dioxide emissions immediately after the earthquake can be suppressed. In other words, if infrastructure is severely damaged after an earthquake, logistics may be disrupted and the workforce may be reduced. These effects may lead to a sudden increase in carbon dioxide emissions due to infrastructure restoration.

[0067] 9B is a diagram showing an example of a GDP forecast for a predetermined period displayed on a monitor or the like. Fig. 9B shows a forecast of GDP in the event of a hypothetical natural disaster, such as an earthquake, and a forecast of GDP in the event that no earthquake occurs. Furthermore, the forecast of GDP in the event of an earthquake is shown for both a case where infrastructure has been reinforced (infrastructure reinforced) and a case where infrastructure has not been reinforced (infrastructure not reinforced).

[0068] 9C is a diagram showing an example of a table displaying the GDP growth rate, economic losses, and additional carbon dioxide emissions due to the impact of an earthquake over a predetermined period. In FIG. 9C, the table shows the predicted GDP growth rate, economic losses, and additional carbon dioxide emissions due to the impact of an earthquake over a predetermined period when infrastructure has been reinforced (infrastructure reinforced) and when infrastructure has not been reinforced (infrastructure not reinforced).

[0069] The content displayed on the monitor is not limited to the content and format shown in Figures 9A to 9C, and for example, along with the predicted carbon dioxide emissions for a predetermined period shown in Figure 9A, content related to or comparable to the predicted carbon dioxide emissions may be displayed in a graph or table format. These content and display formats may be selected by the user or may be set in advance, and specific data may be calculated based on the items shown in Figures 2 to 7, 8A to 8C, and 9A to 9C.

[0070] Furthermore, the economic data calculation unit 130 may acquire information on the amount of carbon dioxide emissions (g') calculated by the carbon dioxide emission prediction unit 150 and reflect it as data included in the economic data (e) recorded in advance in the database unit 10. The economic data calculation unit 130 may further include carbon pricing in the economic data (e), and the economic forecast data acquisition unit 140 may acquire economic forecast data (f) using the economic calculation system 30 based on the economic data.

[0071] For example, if carbon dioxide emissions increase, carbon pricing (price in carbon dioxide emission trading) may rise, which may affect not only product prices but also each item of the (f) economic forecast data shown in Figure 6. In other words, by using the (e) economic data including the carbon dioxide emissions calculated by the carbon dioxide emission prediction unit 150 and carbon pricing, the economic forecast data acquisition unit 140 can acquire more accurate economic forecast data. As a result, the carbon dioxide emission prediction unit 150 can predict carbon dioxide emissions with even greater accuracy.

[0072] Carbon pricing is not limited to the price in carbon dioxide emissions trading, but is interpreted broadly to include anything that has economic value related to carbon dioxide emissions, such as government carbon pricing (carbon tax, emissions trading schemes, energy taxes and credit schemes, etc.), internal (intra-company) carbon pricing, and credit trading by the private sector.

[0073] Next, we will consider the damage that would occur if an earthquake were to occur as a hypothetical natural disaster and the process of recovery from it, and provide a detailed explanation of a carbon dioxide emission prediction method that predicts the carbon dioxide emissions that would result from that damage and the recovery process.

[0074] 10 is a flowchart showing a carbon dioxide emission prediction method M100 executed by a carbon dioxide emission prediction system 100 according to one embodiment of the present invention. As shown in FIG. 10, the carbon dioxide emission prediction method M100 includes steps S110 to S150, and each step is executed by a computer included in the carbon dioxide emission prediction system 100.

[0075] In step S110, the disaster characteristic data acquisition unit 110 acquires disaster characteristic data indicating the characteristics of a virtual natural disaster based on information on the type, scale, and location of the disaster (disaster characteristic data acquisition step). As a specific example, the user may set the type of natural disaster as "earthquake," the scale as "magnitude 7," and the location as "XX city," and the natural disaster calculation system 20 may return disaster characteristic data (b) of an earthquake simulated using the natural disaster calculation system 20.

[0076] In step S120, the impact determination unit 120 determines the impact of the virtual natural disaster based on the disaster characteristics data acquired in step S110 (impact determination step). As a specific example, the impact determination unit 120 determines the (c) impact (collapse, major damage, moderate damage, minor damage, slight damage) corresponding to the level of the earthquake (levels 1 to 5) based on the response of the structure caused by the earthquake ((b) disaster characteristics data) calculated by the natural disaster calculation system 20.

[0077] In step S130, the economic data calculation unit 130 acquires at least (e) economic data and calculates (d) damage data according to the impact level determined in step S120 (economic data calculation step). As a specific example, the economic data calculation unit 130 calculates damage information caused by the earthquake as (d) damage data, as shown in Figure 4, based on the earthquake level determined in step S110. The economic data calculation unit 130 also acquires (e) economic data, as shown in Figure 5.

[0078] In step S140, the economic forecast data acquisition unit 140 acquires (f) economic forecast data based on the (e) economic data acquired in step S130, to which the (d) damage data calculated in step S130 has been added (economic forecast data acquisition step). As a specific example, the economic forecast data acquisition unit 140 uses the economic calculation system 30 to output and acquire (f) economic forecast data that takes into account the impact of an earthquake occurring based on the (d) damage data and (e) economic data, as shown in Figure 6.

[0079] In step S150, the carbon dioxide emission prediction unit 150 predicts (g) carbon dioxide emissions based on the (f) economic forecast data acquired in step S140 (carbon dioxide emission prediction step). As a specific example, the carbon dioxide emission prediction unit 150 predicts (g) carbon dioxide emissions based on the (f) economic forecast data acquired in step S140 using a carbon dioxide emission coefficient set in advance in the database unit 10 or the like, as shown in Figure 7. Here, the predicted carbon dioxide emissions may be output to a monitor or the like, for example, as shown in Figures 9A and 9B.

[0080] As described above, according to the carbon dioxide emission prediction system 100 and carbon dioxide emission prediction method M100 of one embodiment of the present invention, the user (a) sets the type, scale, and location of a natural disaster, and the disaster characteristic data acquisition unit 110 acquires (b) disaster characteristic data using the natural disaster calculation system 20. The impact determination unit 120 determines (c) the impact of a hypothetical natural disaster (earthquake) based on the (b) disaster characteristic data, and the economic data calculation unit 130 acquires at least (e) economic data and calculates (d) damage data corresponding to the (c) impact. The economic forecast data acquisition unit 140 then uses the economic calculation system 30 to acquire (f) economic forecast data based on the (e) economic data, which incorporates the (d) damage data. The carbon dioxide emission prediction unit 150 predicts (g) carbon dioxide emissions based on this (f) economic forecast data. In this way, the carbon dioxide emission prediction system 100 takes into account the damage that will occur in the event of a natural disaster such as an earthquake and the subsequent recovery process, and can predict the carbon dioxide emissions that will result from the damage and recovery process in the event of a natural disaster.

[0081] Generally, carbon dioxide emissions are evaluated as values ​​at a single point in time in the past based on the actual values ​​of economic indicators, but according to a carbon dioxide emission prediction system 100 and a carbon dioxide emission prediction method M100 according to one embodiment of the present invention, the impact (damage information) of a natural disaster is grasped, and when a natural disaster occurs, economic prediction data is calculated for a predetermined period of time that will occur during the damage and reconstruction process, and carbon dioxide emissions are predicted based on that data. In other words, when a natural disaster occurs, it is possible to predict the transition of carbon dioxide emissions over a predetermined period of time that will occur during the damage and reconstruction process.

[0082] Furthermore, since the impact (damage information) of a natural disaster can be simulated under various conditions (e.g., whether or not infrastructure reinforcement is performed), it is possible to predict and compare the trends in carbon dioxide emissions under those conditions. Specifically, a natural disaster damages the economy, and the affected structures are reduced to rubble and disposed of as industrial waste, and the structures are then rebuilt. The carbon dioxide emission prediction system 100 and carbon dioxide emission prediction method M100 according to one embodiment of the present invention integrate these intertwined processes (damage / loss estimation, waste disposal, and reconstruction / repair) to appropriately predict the trends in carbon dioxide emissions over a predetermined period of time that occurs during the damage and reconstruction process when a natural disaster occurs.

[0083] In this embodiment, various simulations are performed by setting a virtual natural disaster, but the present invention is not limited to this, and may be applied to a natural disaster that has already occurred (such as an earthquake). For example, it is possible to predict the carbon dioxide emissions that will be caused by the damage and the recovery process from information about a natural disaster (such as an earthquake) that has already occurred (for example, various information about the earthquake is estimated using satellite images after the earthquake).

[0084] The above-described embodiments are intended to facilitate understanding of the present invention and are not intended to limit the present invention. The elements of the embodiments, as well as their arrangement, materials, conditions, shapes, sizes, etc., are not limited to those illustrated and can be modified as appropriate. Furthermore, configurations shown in different embodiments can be partially substituted or combined with each other.

[0085] The present invention can be used for predicting carbon dioxide emissions, economic forecasting, supporting post-disaster recovery plans, carbon pricing policies, and analyzing the costs and benefits of investments in climate change countermeasures.

[0086] 10...database unit, 20...natural disaster calculation system, 30...economic calculation system, 100...carbon dioxide emission prediction system, 110...disaster characteristic data acquisition unit, 120...impact determination unit, 130...economic data calculation unit, 140...economic prediction data acquisition unit, 150...carbon dioxide emission prediction unit, M100...carbon dioxide emission prediction method, S110 to S150...each step of carbon dioxide emission prediction method M100

Claims

1. A carbon dioxide emission prediction system for predicting carbon dioxide emissions, comprising: a disaster characteristic data acquisition unit for acquiring disaster characteristic data indicating characteristics of natural disasters based on information on the type, scale, and location of the disaster; an impact determination unit for determining the impact level of the natural disaster based on the disaster characteristic data; an economic data calculation unit for acquiring pre-recorded economic data and calculating damage data according to the impact level; an economic forecast data acquisition unit for acquiring economic forecast data based on the economic data to which the damage data has been added; and a carbon dioxide emission prediction unit for predicting carbon dioxide emissions based on the economic forecast data.

2. The carbon dioxide emission prediction system of claim 1, wherein the impact determination unit determines the level of the natural disaster indicating the degree of damage caused by the natural disaster based on the disaster characteristic data, and the economic data calculation unit calculates damage information indicating the scale of damage caused by the natural disaster as the damage data based on the level of the natural disaster.

3. The carbon dioxide emission prediction system of claim 2, wherein the damage information includes at least any of the following: the number of collapsed buildings, the number of partially collapsed buildings, the number of deaths, the number of injured, the monetary value of waste, the cost of reconstruction and repair, and the period of reconstruction and repair.

4. The carbon dioxide emission prediction system according to claim 1, wherein the economic forecast data acquisition unit acquires economic forecast data for a predetermined period in the event of the occurrence of the natural disaster.

5. The carbon dioxide emission prediction system according to claim 4, wherein the economic forecast data includes at least one of GDP, production volume, production value, consumption volume and consumption value of a product.

6. The carbon dioxide emission prediction system according to claim 1, wherein the carbon dioxide emission prediction unit predicts the amount of carbon dioxide emissions based on the economic forecast data using a pre-recorded carbon dioxide emission coefficient.

7. The carbon dioxide emission prediction system according to claim 6, wherein the carbon dioxide emission coefficient is updateable.

8. The carbon dioxide emission prediction system according to claim 6 or 7, wherein the economic data calculation unit includes the amount of carbon dioxide emission predicted by the carbon dioxide emission prediction unit in the economic data.

9. The carbon dioxide emission prediction system according to claim 8, wherein the economic data calculation unit further includes carbon pricing in the economic data.

10. The carbon dioxide emission prediction system of claim 1, wherein the information regarding the type, scale and location of the disaster includes at least one of the number of buildings, attributes of individual buildings and attributes of individual infrastructure structures in the area affected by the natural disaster.

11. A carbon dioxide emission prediction method executed by a computer, comprising: a disaster characteristic data acquisition step of acquiring disaster characteristic data indicating characteristics of a natural disaster based on information on the type, scale, and location of the disaster; an impact determination step of determining the impact level of the natural disaster based on the disaster characteristic data; an economic data calculation step of acquiring pre-recorded economic data and calculating damage data according to the impact level; an economic forecast data acquisition step of acquiring economic forecast data based on the economic data to which the damage data has been added; and a carbon dioxide emission prediction step of predicting carbon dioxide emissions based on the economic forecast data.

Images