GHG emissions derivation apparatus, GHG emissions derivation method, and program

Abstract

To provide a greenhouse gas (GHG) emissions derivation apparatus, method and a program for deriving the amount of greenhouse gas emitted with respect to the amount of activity of activities.SOLUTION: A GHG emissions derivation apparatus includes a derivation unit which derives, on the basis of activity information indicating activities and the amount of activity of the activities, and ratio specifying information that specifies a ratio for each of categories and scopes 1, 2 and 3 for allocating the activities and the amount of activity, the amount of GHG emitted with respect to the amount of activity of the activities for each of the categories and the scopes 1, 2 and 3, the activities indicating the use of electricity, heat, or vapor including a treatment of waste, the amount of activity indicating the amount of electricity, heat or vapor used including the amount of waste disposal.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a GHG emission amount derivation device, a GHG emission amount derivation method, and a program. [Background technology]

[0002] Patent Document 1 describes that "for each asset, the value corresponding to the asset is multiplied by an emission coefficient to calculate the amount of emissions of environmentally hazardous substances for each asset." [Prior art document] [Patent documents]

[0003] [Patent Document 1] Patent No. 7043691 Summary of the Invention [Problem to be solved by the invention]

[0004] A greenhouse gas (GHG) emission derivation device in a first aspect of the present invention includes a derivation unit that derives GHG emissions for the activity amount of the activity content for each scope 1, scope 2, scope 3, and category based on activity information indicating the activity content and the activity amount of the activity content, and ratio identification information for identifying ratios for each scope 1, scope 2, scope 3, and category to which the activity content and the activity amount are assigned.

[0005] In the GHG emission deriving device, the activity content may be the use of electricity, heat, or steam. The amount of activity may be the amount of electricity, heat, or steam used.

[0006] In any of the GHG emission derivation devices, the activity information may include information indicating an amount of electricity used in real estate. The proportion specifying information may indicate, among the amounts of electricity used in the activity information, a proportion of electricity used in the real estate by an owner of the real estate that corresponds to Scope 2 and a proportion of electricity used in the real estate by a tenant of the real estate that corresponds to Category 13 of Scope 3.

[0007] In any of the GHG emission derivation devices, the activity information may include information indicating an amount of electricity used in real estate. The proportion identification information may indicate a measurement result from a meter that measures an amount of electricity used in the real estate by a tenant of the real estate. The derivation unit may refer to the proportion identification information and, based on the amount of electricity usage indicated in the activity information and the measurement result from a meter that measures an amount of electricity usage used in the real estate by the tenant, identify a proportion of the amount of electricity usage used in the real estate by the owner of the real estate and a proportion of the amount of electricity usage used in the real estate by the tenant.

[0008] In any of the GHG emission derivation devices, the activity information may include information indicating the amount of electricity used in real estate. The proportion identification information may indicate, among the amount of electricity used in the activity information, the proportion of electricity used in the real estate by each of the owner and condominium owner of the real estate that corresponds to Scope 2, and the proportion of electricity used in the real estate by a tenant of the real estate that corresponds to Category 13 of Scope 3.

[0009] In any of the GHG emission derivation devices, the activity information may include information indicating the amount of electricity used in real estate. The proportion identification information may indicate measurement results from meters that measure the amount of electricity used in the real estate by each of the tenant and condominium owner of the real estate. The derivation unit may refer to the proportion identification information and, based on the amount of electricity used in the real estate by the owner of the real estate that corresponds to Scope 2, the proportion of electricity used in the real estate by the tenant that corresponds to Category 13 of Scope 3, and the proportion of electricity used in the real estate by the condominium owner that corresponds to Scope 2, based on the amount of electricity used in the real estate by the tenant that corresponds to Category 13 of Scope 3 and the measurement results from the meters that measure the amount of electricity used in the real estate by each of the tenant and the condominium owner, identify the proportion of electricity used in the real estate by the owner of the real estate that corresponds to Scope 2, based on the amount of electricity used in the real estate by the tenant that corresponds to Category 13 of Scope 3, and based on the measurement results from the meters that measure the amount of electricity used in the real estate by each of the tenant and the condominium owner.

[0010] In any of the GHG emission derivation devices, the activity information may include information indicating the amount of electricity used in real estate. The proportion identification information may indicate, among the amount of electricity used in the activity information, a proportion of electricity used in the real estate by the owner of the real estate that corresponds to Scope 2, and a proportion of electricity used by a non-owner other than the owner that corresponds to Category 13 of Scope 3, associated with the use of movable property installed in the real estate.

[0011] In any of the GHG emission derivation devices, the activity information may include information indicating the amount of electricity used in real estate. The proportion identification information may indicate measurement results from meters that measure the amount of electricity used in the real estate by each of the non-owners who are persons other than the owner of the real estate. The derivation unit may refer to the proportion identification information and, based on the amount of electricity used in the real estate by the owner of the real estate that falls under Scope 2 and the amount of electricity used in the real estate by each of the non-owners that falls under Category 13 of Scope 3, specify the proportion of electricity used in the real estate by the owner of the real estate that falls under Scope 2 and the proportion of electricity used in the real estate by each of the non-owners that falls under Category 13 of Scope 3,

[0012] In any of the GHG emission derivation devices, the activity information may include information indicating an amount of electricity used in real estate. The proportion identification information may indicate a proportion of floor area allocated to each user of the real estate for each floor area of ​​the real estate. The derivation unit may identify a proportion of electricity usage used in the real estate by an owner of the real estate that falls under Scope 2 and a proportion of electricity usage used in the real estate by each of the users that falls under Category 13 of Scope 3, based on the electricity usage indicated in the activity information and the proportion of floor area allocated to the user for each floor area of ​​the real estate that is indicated in the proportion identification information.

[0013] In any of the GHG emission derivation devices, the information indicating the amount of electricity used in the real estate may be information shown on an electricity bill.

[0014] In the GHG emission deriving device, the activity content may include waste disposal. The activity amount may include the amount of waste disposed. The proportion identification information may indicate at least one of the following, among the amount of waste disposed: a proportion disposed of in-house, which corresponds to Scope 1; a proportion recycled in-house, which corresponds to Scope 2; a proportion purchased by the company of materials recycled by other companies, which corresponds to Category 1 of Scope 3; a proportion disposed of by other companies, which corresponds to Category 5 of Scope 3; and a proportion purchased by the company of products recycled by other companies, which corresponds to Category 2 of Scope 3, by requesting recycling to other companies.

[0015] A second aspect of the present invention provides a method for deriving GHG emissions, comprising the steps of: deriving GHG emissions for the activity amount of the activity content for each scope 1, scope 2, scope 3, and category, based on activity information indicating the activity content and the activity amount of the activity content, and ratio identification information for identifying ratios for each scope 1, scope 2, scope 3, and category to which the activity content and the activity amount are assigned.

[0016] A program in a third aspect of the present invention causes a computer to function as a derivation unit that derives GHG emissions for the activity amount of the activity content for each scope 1, scope 2, scope 3, and category, based on activity information indicating the activity content and the activity amount of the activity content, and ratio identification information for identifying ratios for each scope 1, scope 2, scope 3, and category to which the activity content and the activity amount are assigned.

[0017] The above summary of the invention does not list all of the features of the present invention. Also, subcombinations of these features may also be inventions. [Brief description of the drawings]

[0018] [Figure 1] 1 is an example of an overall configuration of a system including a GHG emission derivation device 100. [Diagram 2] 1 is an example of a functional block diagram of a GHG emission derivation device 100. FIG. [Diagram 3] 1 is an example table showing the percentage of owners and tenants by scope and category within a facility 50 and electricity usage. [Figure 4] 4 is a first example of a flow diagram showing the operation of the GHG emission derivation device 100. [Diagram 5] 1 shows another example of the overall configuration of a system including a GHG emission amount deriving device 100. [Figure 6] 4 is a second example of a flow diagram showing the operation of the GHG emission derivation device 100. [Figure 7] 11 is a third example of a flow diagram showing the operation of the GHG emission derivation device 100. [Figure 8] 1 is an example table showing the floor area of ​​business premises operated by owners and tenants within facility 50 and the percentage by scope and category. [Figure 9] 4 is a fourth example of a flow diagram showing the operation of the GHG emission derivation device 100. [Figure 10] 1 is an example of a table showing the scope and percentage of each category in waste disposal by a business operator. [Figure 11] FIG. 1 is an example diagram illustrating a computer in which aspects of the present embodiments may be embodied in whole or in part. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention according to the claims. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0020] In order to mitigate the effects of large-scale climate change and realize a sustainable society, it is necessary to reduce greenhouse gas (GHG) emissions. Therefore, it is required to classify GHG emissions from each business into scopes and categories in accordance with the GHG Protocol, and to take measures to reduce emissions based on analysis of each category.

[0021] The GHG emission deriving device described in this specification makes it possible to automatically identify which of each scope and each category the GHG emissions in each facility, business, etc. originate from, based on activity information of each business, etc. and ratio identification information for identifying the ratio. Hereinafter, an exemplary embodiment of the GHG emission deriving device of the present invention will be described with reference to each drawing.

[0022] 1 shows an example of the overall configuration of a system including a greenhouse gas (GHG) emission deriving device 100. The system includes a facility 50, a system 500 that supplies power to the facility 50, and a main power meter 82.

[0023] The facility 50 is a structure or building, such as a building, a commercial facility, an apartment building, etc., that can be used by a contracted natural person or legal person, and is real property fixed to land. The tenant 60 is a natural person or legal person who has entered into a lease agreement with the owner of the facility 50 for the facility's tenant facility, etc. The facility 50 is provided with a main distribution board 55, and for each tenant 60, a distribution board 62, a power meter 64, a load 66, and a GHG emission derivation device 100.

[0024] The main distribution board 55 distributes the power supplied from the grid 500 to the distribution boards 62 of each tenant 60. Power in shared spaces within the facility 50, power shared within the facility 50, and power used by the owner of the facility 50 for his / her own use are supplied from the main distribution board 55 to a distribution board (not shown) that manages the power used by the owner. However, the main distribution board 55 itself may manage the power used by the owner. Power in shared spaces within the facility 50 includes power used by electrical equipment in the shared spaces. Power shared within the facility 50 includes power used for transportation equipment within the facility such as elevators, power to operate security equipment of the facility 50, etc.

[0025] The tenant 60 performs activities in each tenant facility by driving loads 66 with power supplied from a distribution board 62. The loads 66 are electrical appliances that consume power. The electrical appliances may be placed in the tenant space. The electrical appliances include air conditioners, lighting appliances, and electronic appliances. The distribution board 62 includes a power meter 64.

[0026] The power meter 64 measures the power used to drive the load 66 supplied from the distribution board 62. The power meter 64 may be a smart meter. The power meter 64 of each tenant 60 is connected to the GHG emission derivation device 100. However, the power meter 64 may communicate wirelessly with the GHG emission derivation device 100. The power meter 64 is an example of a "meter that measures the amount of electricity used in real estate."

[0027] In billing for electricity, the amount of electricity used is generally measured based on the amount of power used (kWh), so the amount of electricity used may be measured by measuring the amount of power. However, the electrical indicator to be measured is not limited to the amount of power, and the current, or both the current and the voltage, may be continuously measured over time.

[0028] 1, in addition to the tenant 60, there may be a condominium owner (not shown) who is a natural person or a legal entity that has purchased a plot in real estate in the facility 50. A distribution board and load similar to those for the tenant 60 may be provided for such a condominium owner, and an electric meter on the distribution board for the condominium owner may be connected to the GHG emission derivation device 100.

[0029] The main power meter 82 measures the power supplied from the system 500 to the main distribution board 55, i.e., the power supplied from the system 500 to the entire facility 50. Therefore, the main power meter 82, which bills the facility 50 from the system 500, is provided on the transmission line between the main distribution board 55 and the system 500. The main power meter 82 may be a smart meter.

[0030] The GHG emission amount derivation device 100 derives the proportion of electricity usage for each scope and category emitted by each lessee 60 and owner based on the proportion identifying information of the electricity used by each lessee 60 and owner. Furthermore, the GHG emission amount derivation device 100 may derive GHG emissions based on an emission coefficient (kg-CO2 / kWh) for the electricity usage. As the proportion identifying information for the GHG emission amount derivation device 100, information on the electricity usage of each lessee 60 is obtained from the power meter 64 of each lessee 60. In this embodiment, the GHG emission amount derivation device 100 is provided within the facility 50, but the GHG emission amount derivation device 100 may be provided outside the facility 50.

[0031] A specific configuration of the GHG emission amount deriving device 100 will be described later with reference to Fig. 2. A specific operation of the GHG emission amount deriving device 100 will be described later with reference to Figs.

[0032] 2 is an example of a functional block diagram of the GHG emission amount deriving device 100. The GHG emission amount deriving device 100 includes an acquisition unit 102, a derivation unit 104, and a storage unit 106.

[0033] The acquisition unit 102 acquires activity information indicating the activity content and the activity amount of the target business entity, etc., and ratio specification information for specifying scope 1, scope 2, and scope 3 of the GHG Protocol and the ratio for each category to which the activity content and activity amount are assigned. In the example of FIG. 1, the acquisition unit 102 acquires information indicating the electricity usage amount of electricity used in the real estate and the measurement result acquired from the power meter 64.

[0034] Here, scope 1 refers to direct emissions, which indicate greenhouse gas emissions emitted directly by a business. Scope 2 refers to indirect emissions, which indicate greenhouse gas emissions emitted indirectly through the purchase of energy by a business. Scope 3 refers to other indirect emissions, which indicate greenhouse gas emissions emitted through the activities of a business that are not included in scope 1 direct emissions and scope 2 indirect emissions.

[0035] Scope 3 is further divided into 15 categories based on the activities. Category 1 refers to "purchased products and services." Category 2 refers to "capital goods." Category 3 refers to "fuel- and energy-related activities not included in Scope 1 and Scope 2." Category 4 refers to "upstream transportation and handling." Category 5 refers to "waste generated from business activities." Category 6 refers to "business trips." Category 7 refers to "employee commuting." Category 8 refers to "upstream leased assets." Category 9 refers to "downstream transportation and distribution." Category 10 refers to "processing of sold products." Category 11 refers to "use of sold products." Category 12 refers to "disposal of sold products." Category 13 refers to "downstream leased assets." Category 14 refers to "franchises." Category 15 refers to "investments." Scope 3 further includes "other," which indicates indirect GHG emissions not included in the 15 categories. "Other" GHG emissions include, for example, GHG emissions related to the daily lives of employees or consumers.

[0036] An example of the activities of business operators is the use of energy such as electricity, heat, or steam. For example, in the example of Figure 1, this corresponds to an example where business operators use electric energy. In this example, when the lessee and owner carry out electric energy activities, GHG is emitted in an amount according to the emission factor determined according to the facilities of the electric power company that operates the power system 500.

[0037] These emissions can be allocated to GHG Protocol scopes 1 to 3, and particularly categories 1 to 15 in scope 3, depending on the activities of the business operator. In the case of electricity use, if it is used by the owner, it is classified as scope 2 for the owner, and if it is used by a tenant, it is classified as category 13 of the owner's scope 3, since it is associated with the operation of leased assets that the owner rents to a tenant (other person). Other examples of the activities of business operators, etc. will be explained with reference to Figures 5 and 6.

[0038] As an example, if the activity of the business operator is an activity using energy such as electricity, heat, or steam, the amount of activity is the amount of electricity, heat, or steam used. The amount of GHG emissions is calculated by multiplying the amount of use by an emission factor according to the amount of use. For example, regarding the emission factor for electricity use, in Japan, each electric power company submits an emission factor (kg-CO2 / kWh) according to the amount of electricity used (kWh) to the Ministry of the Environment, and the emission factor is summarized in the Ministry of the Environment's "List of Calculation Methods and Emission Factors." Note that CO2 is an example of GHG, and is not limited to this, and GHG also includes methane, etc. However, in the GHG protocol, greenhouse gases other than CO2 can also be converted to CO2 equivalents based on their respective global warming coefficients. The GHG emission derivation device 100 can derive GHG emissions by multiplying the amount of electricity used by an emission factor.

[0039] 1, the activity information of the business operator or the like is an electricity bill billed by the power company or the like that operates the grid 500 according to the amount of electricity used throughout the facility 50. The billing information in the electricity bill is, for example, the amount of electricity used based on the measurement information of the main power meter 82, and includes information indicating the amount of electricity used throughout the facility 50.

[0040] In the example of Fig. 1, the ratio-specific information of the GHG emission derivation device 100 is the measurement result of the electric power meter 64 obtained from the electric power meter 64 of each tenant 60. The amount of electricity used in the entire facility 50 can be read from the electricity bill, and the amount of electricity used by each tenant 60 can be read from the measurement result of the electric power meter 64.

[0041] Therefore, if the only electricity users in the facility 50 are the owner and each tenant 60, the owner's electricity usage ratio can also be determined by subtracting the total electricity usage of the tenants 60 from the electricity usage of the entire facility 50. However, the owner's electricity usage ratio may also be determined directly from the electricity meter by installing an electricity meter on the owner's distribution board and connecting this electricity meter to the GHG emission derivation device 100.

[0042] In cases where the only users of electricity within facility 50 are the owner and each tenant 60, GHG emissions from the owner's electricity use can be classified as Scope 2 in the GHG Protocol, and GHG emissions from the tenant's electricity use can be classified as Scope 3, Category 13. In this way, the proportion identification information indicates the proportion of electricity usage used in the real estate by the owner of facility 50 that falls under Scope 2, and the proportion of electricity usage used in the real estate by tenants, etc. 60 of facility 50 that falls under Scope 3, Category 13.

[0043] Here, when there are condominium owners, etc. other than the owner and tenant 60, the electricity usage of the condominium owners, etc. becomes the condominium owner's Scope 2. In this case, unlike when the electricity users are only the owner and each tenant 60, it is not possible to classify all of the proportion of electricity usage read from the electricity meter into category 13 of the owner's Scope 3. Therefore, in such a case, the derivation by derivation unit 104 described below will be based on the data stored in memory unit 106, which will be described later.

[0044] The derivation unit 104 derives the GHG emission amount for the activity amount of the activity content for each of scope 1, scope 2, and scope 3 and category, based on the activity information and the ratio identification information. In the example of Fig. 1, the derivation unit 104 refers to the measurement result acquired from the power meter 64, and identifies the ratio of the electricity usage amount used by the owner in the facility 50 and the ratio of the electricity usage amount used by the tenant 60 in the facility 50, based on the electricity usage amount indicated in the activity information and the measurement result. In addition, the derivation of the GHG emission amount by the derivation unit 104 is based on the data stored in the storage unit 106.

[0045] The storage unit 106 stores the correspondence between the power meter 64 etc. and the scope and category of the GHG protocol. This allows the GHG emission amount derivation device 100 to determine into which scope and category the proportion of electricity usage should be classified even when there is a condominium owner other than the owner and the tenant 60, or when proportion identification information is obtained from the owner's power meter.

[0046] In addition, when the GHG emission derivation device 100 is used for relationships other than the owner, tenant, and condominium owner in the facility 50, the correspondence relationship between the classification target and the scope and category may be more complicated. In particular, this is the case when the classification of the GHG emissions emitted by the business operator into which category of Scope 3 in the GHG Protocol corresponds is complicated. The storage unit 106 may store data generated by machine learning of the past classification of the GHG emission derivation device 100 as the correspondence data for such a case. The GHG emission derivation device 100 may generate a prediction model according to an algorithm predetermined by machine learning using data in which the total floor area of ​​the facility 50, the occupied floor area of ​​each tenant 60, the business type of each tenant 60, the number of employees of each tenant 60, etc. are associated as explanatory variables with the electricity usage of the owner and each tenant 60 for each month or year as an objective variable as teacher data. As the supervised machine learning algorithm, for example, a support vector machine (SVM) can be used.

[0047] Furthermore, the storage unit 106 may store an emission coefficient (kg-CO2 / kWh) of the electric power company that operates the grid 500. This allows the derivation unit 104 to derive the GHG emission amount based on the emission coefficient (kg-CO2 / kWh) and the amount of electricity used by the lessee 60.

[0048] Furthermore, the storage unit 106 may store data combining each company's emission coefficient (kg-CO2 / kWh) and the electricity rate for each amount of electricity used (khW) based on, for example, the Ministry of the Environment's "List of Calculation Methods and Emission Coefficients." The owner or lessee 60 of the facility 50 may refer to the emission coefficient (kg-CO2 / kWh) and the electricity rate stored in the storage unit 106 to select the electric power company that operates the grid 500 and how to make a contract for that combination.

[0049] In this way, even if the scope and category of activities performed by the lessee 60 are not specified on the electricity bill, the GHG emission derivation device 100 can identify the electricity usage for each scope and category based on the information from the power meter 64. In the inventions in the prior art documents, the scope and category are previously associated with one or more combinations of items such as asset classification, asset name, product / service name, and payee of the accounting data. In the GHG emission derivation device 100 of this embodiment, such association is not required in advance for the electricity bill data.

[0050] In addition, the GHG emission derivation device 100 improves the accuracy of allocation of scopes and categories by using both activity information of businesses, etc., such as electricity bills, and ratio specification information from the power meter 64. Furthermore, the GHG emission derivation device 100 can calculate GHG emissions (kg) for each scope and category based on the emission coefficient (kg-CO2 / kWh). This allows data on the calculated GHG emissions (kg) for each scope and category to be aggregated and used for efforts to reduce GHG emissions (kg) for each scope and category.

[0051] 3 is an example of a table showing the proportion of each scope and category of owners and tenants and the amount of electricity used within the facility 50. In this example, the annual electricity usage of the entire facility 50 is 620,000 kWh.

[0052] The GHG emission amount derivation device 100 assigns the GHG Protocol scope and category and the amount of electricity usage to each electricity user. In this embodiment, when the electricity user is the owner of the facility 50, the GHG emission amount derivation device 100 derives that the proportion of the amount of electricity usage is 18.1% of the amount of electricity consumed in the facility 50. The amount of electricity equivalent to the proportion of 18.1% of the total amount of 620,000 kWh is 112,220 kWh.

[0053] The GHG emission derivation device 100 derives that the percentage of electricity usage for Lessee 1 is 14.3%. The amount of electricity equivalent to 14.3% of the total amount of 620,000 kWh is 88,660 kWh. Furthermore, the GHG emission derivation device 100 derives that the percentage of electricity usage for Lessee 2 is 9.3%. The amount of electricity equivalent to 14.3% of the total amount of 620,000 kWh is 57,600 kWh.

[0054] For example, Lessee 1 is a business owner who operates the same business as Lessee 2, but occupies a larger area of ​​floor space in a section of facility 50 than Lessee 2. Because Lessee 1 has a larger occupied area and business scale than Lessee 1, Lessee 1 uses more electricity than Lessee 2. In another example, Lessee 1 occupies the same area of ​​floor space as Lessee 2, but is a business owner whose business is different. Because Lessee 1's business differs, Lessee 1 operates for longer hours than Lessee 2, and because of the type of business, Lessee 1 may incur higher expenses for electrical equipment.

[0055] Furthermore, the GHG emission derivation device 100 derives that the ratio of electricity usage for the lessee 3 is 21.0%. The amount of electricity equivalent to 21.0% of the total amount of 620,000 kWh is 130,200 kWh. For example, the lessee 3 is a business owner who has a large number of employees in the facility 50 and occupies a large floor area in a section within the facility 50.

[0056] In addition, if there is a condominium owner (not shown) who has ownership of a certain section within facility 50, GHG emission derivation device 100 derives the amount of electricity usage based on the proportion of the condominium owner's electricity usage. The condominium owner's electricity usage is classified as Scope 2, similar to the owner of facility 50. GHG emission derivation device 100 may also derive the condominium owner's GHG emissions based on an emission coefficient.

[0057] 4 is a first example of a flow diagram showing the operation of the GHG emission amount deriving device 100. The operation of the GHG emission amount deriving device 100 implements a GHG emission amount deriving method including steps S100 to S102.

[0058] The acquiring unit 102 acquires activity information indicating the activity content of the target business entity or the like and the activity amount of the activity content, and ratio identification information for identifying the scope 1, scope 2, and scope 3 and the ratio for each category to which the activity content and activity amount are assigned (S100). In the example of Fig. 1, the acquiring unit 102 acquires an electricity bill based on the amount of electricity used throughout the facility 50, and measurement results acquired from each power meter 64, etc. The amount of electricity used throughout the facility 50 may be an amount based on the measurement value of the main power meter 82.

[0059] The derivation unit 104 derives the GHG emission amount for the activity amount of the activity content for each of scope 1, scope 2, and scope 3 and category based on the activity information and the ratio identification information (S102). The derivation of the GHG emission amount by the derivation unit 104 is based on the data stored in the storage unit 106.

[0060] 5 shows another example of the overall configuration of a system including the GHG emission amount deriving device 100. The system includes a data center 200, a system 500 that supplies power to the data center 200, and a main power meter 82.

[0061] The data center 200 is a robust building having a large number of ICT (information and computer technology) devices such as servers. The data center 200 is managed by a data center administrator, and provides resources for users to execute various information processes and store various data. The data center 200 includes one or more racks 250, an uninterruptible power supply 210, a power meter 220, and a GHG emission derivation device 100. Note that, although only one rack is shown in FIG. 5 for illustrative purposes, the data center 200 may include multiple racks 250.

[0062] The rack 250 is a movable property that is not fixed to a land. One or more spaces 252 are assigned to one rack 250. Power is provided to each space 252 of the rack 250 from a system 500 via an uninterruptible power supply 210. Although the term "rack" is used for the rack 250, it is not limited to a rack server arranged in the data center 200, and a chassis of a blade server may be used instead of the rack 250.

[0063] The right to use space 252 is assigned to a user of data center 200. The user of data center 200 performs desired information processing, etc. by placing his / her own server in space 252 or by using a server provided by the administrator. Since space 252 is rented by the administrator, the electricity consumed by the server placed in space 252 falls under category 13 of scope 3 of the administrator in the GHG Protocol.

[0064] The uninterruptible power system (UPS) 210 is a power source for supplying a substantially constant amount of power to the space 252 even in the event of a power supply trouble, such as a temporary stop of power supply from the power grid 500 due to a natural disaster or the like. An uninterruptible power supply 210 may be provided for each space 252. The uninterruptible power supply 210 has a switch SW and a battery 212. A power meter 220 for measuring the power supplied by the uninterruptible power supply 210 to the space 252 is provided in addition to the uninterruptible power supply 210.

[0065] The switch SW switches on and off the power supplied to each space 252. There may be cases where there is no user who has signed a usage contract in each space 252 at a certain point in time, in which case power is not supplied. In addition, when a current accompanied by an overvoltage that may exceed the withstand voltage of the equipment connected to the space 252 flows due to a natural disaster such as lightning, the switch SW may cut off the supply of power to the space 252 to protect the equipment connected to the space 252.

[0066] The battery 212 is charged when the power supply state from the grid 500 is stable, and supplies power to the space 252 so as to prevent fluctuations in the power to the space 252 when a power supply trouble occurs in the power supplied from the grid 500. The operations of the switch SW and the battery 212 are controlled by a power meter 220 described below and a power management device provided together with the power meter 220, but are not limited to this, and a control device (not shown) for controlling them may be provided.

[0067] The power meter 220 measures the power supplied by the uninterruptible power supply 210 to the space 252. Since the amount of electricity used is generally based on power, the power meter 220 may measure the amount of electricity used that the uninterruptible power supply 210 supplies to the space 252. The power meter 220 may also measure other electrical indicators, such as the voltage and current, supplied by the uninterruptible power supply 210 to the space 252, in order to observe the power status of the uninterruptible power supply 210, etc. In particular, since the required voltage and current differ depending on the performance of a server or the like connected to the space 252, measurements of other electrical indicators may also be performed.

[0068] The power meter 220 is connected to the GHG emission amount derivation device 100. However, the power meter 220 may perform wireless communication with the GHG emission amount derivation device 100. The power meter 220 may be a smart meter. Furthermore, a power management device supplied by the uninterruptible power supply device 210 may be provided together with the power meter 220.

[0069] A cooling device (not shown) is built into the rack or the server, or is provided together with the cooling device. As an example, the power consumption of the cooling device (not shown) built into the server is measured by the power meter 220 together with the space 252. The cooling device also includes a data center air conditioner that is provided together with the rack. The power used by the cooling device of the rack or the server may be measured by a power meter separate from the power meter 220. In this case, according to the amount of power of each space 252 measured by the power meter 220, the GHG emission derivation device 100 may apportion the power used by the cooling device to each user, assuming that the power is the power used by each user for each space 252.

[0070] The main power meter 82 measures the power supplied from the system 500 to the main distribution board 55, i.e., the power supplied from the system 500 to the entire facility 50. Therefore, the main power meter 82, which bills the facility 50 from the system 500, is provided on the transmission line between the main distribution board 55 and the system 500. The main power meter 82 may be a smart meter.

[0071] The GHG emission emission deriving device 100 derives the ratio of electricity usage for each scope and category emitted by the manager and each user, based on the ratio specifying information of electricity used by the manager and each user of the data center 200. Furthermore, the GHG emission emission deriving device 100 may derive GHG emissions based on an emission coefficient (kg-CO2 / kWh) for the electricity usage. As the ratio specifying information for the GHG emission emission deriving device 100, information on the electricity usage of each user is obtained from the power meter 220 of each user.

[0072] 5, the GHG emission derivation device 100 derives the ratio of the electricity usage amount for each scope and category emitted by the manager and each user based on the measurement result of the power meter 220 installed in each space 252 of the rack 250. However, if the average power consumption of devices such as rack servers installed in each space 252 of the rack 250 can be considered to be the same, one power meter 220 may be installed in the rack 250. In this case, the GHG emission derivation device 100 may derive the ratio of the electricity usage amount emitted by each user from the number of spaces 252 used by each user and the measurement result of one power meter 220 installed in the rack 250. In other words, the GHG emission derivation device 100 may derive the ratio of the electricity usage amount emitted by each user by dividing the electricity usage amount of the rack 250 based on the measurement result of one power meter 220 installed in the rack 250 by the number of spaces 252 used by each user.

[0073] Here, the manager of data center 200 corresponds to the "owner" of the "real estate" called data center 200, and the users of data center 200 correspond to the "non-owners" of the movable property called rack 250 installed within the "real estate" called data center 200. Power meter 220 corresponds to "each measuring device that measures the amount of electricity used by each of the non-owners in use of the movable property."

[0074] 6 is a second example of a flow diagram showing the operation of the GHG emission amount deriving device 100. The operation of the GHG emission amount deriving device 100 implements a GHG emission amount deriving method including steps S200 to S202.

[0075] The acquisition unit 102 acquires activity information indicating the electricity usage in the data center 200, and ratio specification information for allocating the electricity usage to the manager and the users (S200). The ratio specification information is information for specifying the ratio of the scope 2 of the manager's usage and the scope 3 of the user's specifications, category 13.

[0076] The derivation unit 104 derives the GHG emission amount for the electricity usage allocated to each of the scope 2 of the manager's usage and the scope 3 of the user's usage, category 13, based on the activity information and the ratio identification information (S202). The derivation of the GHG emission amount by the derivation unit 104 is based on the data stored in the storage unit 106.

[0077] Fig. 7 is a third example of a flow diagram showing the operation of the GHG emission amount derivation device 100. A GHG emission amount derivation method including steps S300 to S302 is implemented by the operation of the GHG emission amount derivation device 100. The embodiment of Fig. 7 differs from the embodiments of Figs. 1 to 4 in that information on the floor area of ​​each lessee 60 such as each tenant is acquired as the ratio specification information, but other configurations of the system are similar to those of the embodiment of Fig. 1.

[0078] The acquiring unit 102 acquires activity information and ratio specifying information that assigns activity details and activity amounts (S300). In this embodiment, the activity information indicates activity details, which are electricity usage, and activity amounts, which are electricity usage amounts.

[0079] In particular, in buildings used for commercial purposes, GHG emissions have a strong linear correlation with floor area. There is an advantage in using a value with floor area as the denominator for GHG emission intensity because of the ease of calculation when an extension is made to a building, the convenience of comparison with other facilities of the same type, and the fact that floor area has traditionally been used as the denominator in the calculation of energy intensity at business establishments, etc. In this embodiment, the allocation of electricity is described as an example, but electrical energy is merely an example, and the allocation of GHG emission sources based on energy use for the calculation of GHG emissions may be performed for other energies such as heat or steam in addition to electricity.

[0080] In this embodiment, the owner's floor area is based on, as an example, the floor area of ​​the office where the owner actually operates in the building. Unlike the embodiment of FIG. 1, the electricity usage per floor area of ​​the common area may differ from the electricity usage per floor area used by each tenant 60 in the office area, and may not be apportioned based on the floor area ratio alone. In this example, the apportionment of the electricity usage used in the common area in the facility 50 is based on the floor area of ​​the office operated by the owner in the facility 50 and the floor area of ​​the office where each tenant 60 actually operates. However, when the entire floor area of ​​the office area in the facility 50 is occupied by the owner and the tenant 60, the owner's floor area may be derived by subtracting the sum of the floor areas occupied by the tenants 60 from the total area of ​​the office area.

[0081] Next, the derivation unit 104 derives GHG emissions for the activity amounts of the activity contents assigned to each of the owner's scope 2 and the owner's scope 3 category 13, which is the usage by non-users, based on the activity information and the ratio identification information (S302). In this step, as in S102 and S202, the GHG emission derivation device 100 may derive the electricity usage of the owner and each lessee 60 based on the ratio identification information, and then derive the GHG emissions using the emission intensity (kg-CO2 / kWh) for the electricity usage.

[0082] For example, due to mergers and acquisitions (M&A), spin-offs, consolidations, and the like of the companies that are the lessees 60 of the facility 50, the floor space occupied by each organization, including both the owner and lessee 60, may change within the facility 50. In such cases, it is useful to identify which business activities are attributable to GHG emissions resulting from the use of energy resources such as electricity used within the facility 50.

[0083] There are cases where a local government or the like requests a report for a certain period (e.g., annually) regarding GHG emissions from the facility 50. For example, even if the amount of electricity usage on each floor of the facility 50 can be obtained, data on the amount of electricity usage for each tenant cannot be obtained, or there are cases where the occupancy rate of floor space of each tenant 60 within the facility 50 fluctuates frequently. Even in such cases, the GHG emission derivation device 100 can automatically calculate the GHG emissions for each scope and category according to the floor space.

[0084] Fig. 8 is an example of a table showing the floor area of ​​business premises operated by the owner and tenant within the facility 50 and the ratio for each scope and category. Fig. 8 is a specific example in which the GHG emission amount derivation device 100 apportions the ratio of electricity usage and GHG emissions in an embodiment in which the GHG emission amount derivation device 100 according to the example of Fig. 7 is used.

[0085] Figure 8 shows a building with a total floor area of ​​approximately 10,000 m 2 The building has eight floors, with a basement parking lot and a total office area of ​​approximately 7,440 m on each floor. 2 This is an example of an office building. In this example, the floor area of ​​the office space on the standard floor is 930 m. 2 It is.

[0086] As an example, the Owner is a legal entity that operates a property management company and occupies half of the office space on the first floor of the building. Lessee A is a legal entity that leases one entire floor of the building, Lessee B is a legal entity that leases two entire floors of the building, and Lessee C is a legal entity that leases half of the floor space on one floor of the building.

[0087] The GHG emission derivation device 100 apportions the electricity usage and GHG emissions in accordance with the proportion of floor area occupied by the owner and each tenant 60. In this embodiment, the electricity usage and GHG emissions are apportioned as follows: 6.3% to the owner, 12.6% to tenant A, 25.2% to tenant B, and 6.3% to tenant C. The GHG emission derivation device 100 may also be configured to take into account the maximum power demand and contract power of the owner and each tenant A to C when making the calculation, and to apportion the GHG usage weighted toward users with larger demands and contract power.

[0088] In calculating the amount of emissions, the GHG emission derivation device 100 may use the emission intensity per unit of electricity published by the electric power company or the like that operates the system 500. For example, the GHG emission derivation device 100 may store data on the emission intensity per floor area for each business type in the storage unit 106, and provide the owner and the lessees A to C with comparative data with the emission intensity per floor area obtained from the electricity actually used by the owner and the lessees A to C. This allows the owner and the lessees A to C to grasp in detail the data on the GHG emissions and intensity due to their own activities.

[0089] Fig. 9 is a fourth example of a flow diagram showing the operation of the GHG emission amount derivation device 100. In this embodiment, the GHG emission amount derivation device 100 has an acquisition unit 102, a derivation unit 104, and a storage unit 106, similar to Fig. 2. The GHG emission amount derivation device 100 is connected to a terminal, a computer, a server, a database, or the like that stores data on how waste generated in association with a business carried out by a business operator was treated.

[0090] The acquiring unit 102 acquires the activity details and activity information of the target business operator (S400). In this embodiment, the activity details include details of waste disposal, and the activity information includes the amount of waste discharged as the amount of activity.

[0091] The acquisition unit 102 acquires ratio specification information that specifies the ratio of each processing entity and processing method in the waste amount of the target business (S402). The ratio specification information includes information for specifying the ratio of waste processed by the business itself (in-house), the ratio of recycled waste processed by the business itself (in-house), the ratio of materials or products that have been recycled by other companies that the business itself purchased, and the ratio of waste processed by other companies.

[0092] Here, in the GHG Protocol, emissions resulting from in-house waste treatment fall under Scope 1 or Scope 2. Direct emissions from industrial processes using fuels within a company, such as GHG emissions from physical or chemical processes for waste treatment, fall under Scope 1, while emissions from the use of energy resources for waste treatment fall under Scope 2. In this embodiment, as an example, the GHG emission derivation device 100 calculates the proportion of in-house waste treatment that falls under Scope 1. However, the scope classification in this embodiment is an example, and the GHG emission derivation device 100 may further subdivide the scope of in-house waste treatment.

[0093] Similarly, emissions generated from in-house recycling processing fall under Scope 1 or Scope 2. For example, GHG emissions generated from the consumption of electricity to operate a recycling device fall under Scope 2. In the present embodiment, as an example, the GHG emission derivation device 100 calculates the proportion of in-house recycling that falls under Scope 2. However, the scope classification in the present embodiment is an example, and the GHG emission derivation device 100 may further subdivide the scope classification of in-house recycling processing.

[0094] Emissions resulting from requesting recycling from another company and then purchasing the recycled materials from that company are emissions from purchased goods and services, so they fall under Scope 3, Category 1. Emissions resulting from requesting recycling from another company and then purchasing products (which fall under capital goods) from that company are emissions from capital goods, so they fall under Scope 3, Category 2. Emissions resulting from waste processing by another company correspond to emissions from the disposal and processing by a third party of waste generated from business, so they fall under Scope 3, Category 5.

[0095] Furthermore, the derivation unit 104 derives greenhouse gas (GHG) emissions for the amount of activity of the activity content for each of scope 1, scope 2, and scope 3 and category based on the activity information and the ratio identification information (S404). The derivation of the GHG emissions by the derivation unit 104 is based on the emission coefficient stored in the storage unit 106.

[0096] The memory unit 106 of this embodiment stores emission coefficients for waste disposal for each scope and category. The emission coefficients stored in the memory unit 106 may be based on data published in "Emissions Unit by Waste Type and Treatment Method" in the "Emissions Unit Database for Calculating Greenhouse Gas Emissions, etc. of Organizations Through the Supply Chain" provided by the Ministry of the Environment. Alternatively, the emission coefficients may be based on emission coefficients published by waste treatment companies contracted by businesses.

[0097] Furthermore, the emission factor may be based on an emission factor calculated as an average value from the emissions if the waste is disposed of in-house in the case of Scope 1. Similarly, the emission factor may be based on an emission factor calculated as an average value from the emissions if the waste is recycled in-house in the case of Scope 2.

[0098] As already explained with reference to FIG. 2, the GHG emission amount derivation device 100 can automatically calculate which scope and category of waste treatment each business carried out and the associated GHG emissions. Machine learning of such data may be used to learn about optimizing future waste treatment methods for businesses. This allows data center users to optimize future waste treatment methods with low GHG emissions in their own businesses. Data from the GHG emission amount derivation device 100 can also be collected and used to promote GHG emission efforts by the data providers as a whole.

[0099] 10 is an example of a table showing the proportion of each scope and category in waste treatment by a business operator. The GHG emission amount deriving device 100 identifies the scope and category for each waste treatment carried out by the business operator.

[0100] The proportion of waste disposal by the business operator itself is 26.2%, which is classified as Scope 1. The derivation unit 104 calculates the GHG emissions by multiplying the amount of waste disposal in Scope 1, calculated by multiplying the total amount of waste disposal by the proportion, by the emission coefficient stored in the storage unit 106. The emission coefficient may be based on the average GHG emissions from the waste disposal of the target object by the business operator.

[0101] The company recycles 28.4% of its waste in-house, which is classified as Scope 2. The derivation unit 104 calculates the GHG emissions by multiplying the amount of waste processed in Scope 2, calculated by multiplying the total amount of waste processed by the ratio, by the emission coefficient stored in the storage unit 106. The emission coefficient may be based on the average GHG emissions from the recycling of waste in-house.

[0102] The percentage of businesses that requested recycling processing in-house was 14.4%. This is classified as category 1 of scope 3. The derivation unit 104 calculates the GHG emissions by multiplying the amount of processing in category 1 of scope 3, calculated by multiplying the total amount of processing of the target object by the percentage, by the emission factor stored in the storage unit 106. The emission factor may be an emission factor provided by the requesting business (another company), or may be an emission factor based on data that is publicly available as the emission intensity of the target object.

[0103] The business outsourced recycling to other companies for 31.1% of the total. This is classified as Scope 3, Category 5. The derivation unit 104 calculates the GHG emissions by multiplying the amount of processing in Scope 3, Category 5, obtained by multiplying the total amount of processing of the target object by the percentage, by the emission factor stored in the storage unit 106. The emission factor may be an emission factor provided by the requesting business (other company), or may be an emission factor based on data publicly available as the emission intensity of the target object.

[0104] 11 shows an example of a computer 1200 that may embody aspects of the present embodiment in whole or in part. A program installed on the computer 1200 may cause the computer 1200 to perform operations associated with an apparatus according to an embodiment of the present invention or to function as one or more "parts" of the apparatus. Alternatively, the program may cause the computer 1200 to execute the operations or one or more "parts". The program may cause the computer 1200 to execute a process or steps of the process according to an embodiment of the present invention. Such a program may be executed by the CPU 1212 to cause the computer 1200 to execute specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

[0105] The computer 1200 according to this embodiment includes a CPU 1212 and a RAM 1214, which are connected to each other by a host controller 1210. The computer 1200 also includes a communication interface 1222 and an input / output unit, which are connected to the host controller 1210 via an input / output controller 1220. The computer 1200 also includes a ROM 1230. The CPU 1212 operates according to programs stored in the ROM 1230 and the RAM 1214, thereby controlling each unit.

[0106] The communication interface 1222 communicates with other electronic devices via a network. The hard disk drive may store programs and data used by the CPU 1212 in the computer 1200. The ROM 1230 stores a boot program executed by the computer 1200 when activated and / or a program that depends on the hardware of the computer 1200. The programs are provided via a computer-readable recording medium such as a CR-ROM, a USB memory, or an IC card, or a network. The programs are installed in the RAM 1214, which is also an example of a computer-readable recording medium, or the ROM 1230, and executed by the CPU 1212. The information processing described in these programs is read by the computer 1200, and brings about cooperation between the programs and the various types of hardware resources. An apparatus or method may be configured by implementing an operation or processing of information according to the use of the computer 1200.

[0107] For example, when communication is performed between the computer 1200 and an external device, the CPU 1212 may execute a communication program loaded in the RAM 1214 and instruct the communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 1212, the communication interface 1222 reads transmission data stored in a transmission buffer area provided in the RAM 1214 or a recording medium such as a USB memory, transmits the read transmission data to a network, or writes reception data received from the network to a reception buffer area or the like provided on the recording medium.

[0108] Furthermore, the CPU 1212 may cause all or a necessary portion of a file or database stored in an external recording medium such as a USB memory to be read into the RAM 1214, and may perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external recording medium.

[0109] Various types of information, such as various types of programs, data, tables, and databases, may be stored in the recording medium and undergo information processing. The CPU 1212 may perform various types of processing on the data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequence of the program, and write back the results to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. in the recording medium. For example, when a plurality of entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the recording medium, the CPU 1212 may search for an entry that matches a condition, in which the attribute value of the first attribute is specified, from among the plurality of entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0110] The above-described programs or software modules may be stored in a computer-readable storage medium on the computer 1200 or in the vicinity of the computer 1200. In addition, a recording medium such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the Internet can be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

[0111] A computer-readable medium may include any tangible device capable of storing instructions that are executed by a suitable device. As a result, a computer-readable medium having instructions stored thereon comprises an article of manufacture that includes instructions that can be executed to create means for performing the operations specified in the flowchart or block diagram. Examples of computer-readable media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, and the like. More specific examples of computer-readable media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disk read-only memories (CD-ROMs), digital versatile disks (DVDs), Blu-ray (RTM) disks, memory sticks, integrated circuit cards, and the like.

[0112] The computer readable instructions may include either source code or object code written in any combination of one or more programming languages. The source code or object code includes conventional procedural programming languages. The conventional procedural programming languages ​​may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, or object oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and the “C” programming language or similar programming languages. The computer readable instructions may be provided to a processor or programmable circuitry of a general purpose computer, special purpose computer, or other programmable data processing apparatus locally or over a wide area network (WAN) such as a local area network (LAN), the Internet, etc. The processor or programmable circuitry may execute the computer readable instructions to create means for performing the operations specified in the flowcharts or block diagrams. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0113] Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It is clear to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the description of the claims that such modifications and improvements can also be included in the technical scope of the present invention.

[0114] It should be noted that the order of execution of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and may be realized in any order unless the output of a previous process is used in a later process. Even if the operational flow in the claims, specifications, and drawings is explained using "first," "next," etc. for convenience, it does not mean that it is essential to perform the process in this order. [Explanation of symbols]

[0115] 50 Facilities 55 Main distribution board 60 Tenant 62 Distribution Board 64 Power Meter 66 Load 82 Main power meter 100 GHG emissions derivation device 102 Acquisition Department 104 Derivation part 106 Storage section 200 Data Centers 210 Uninterruptible power supply 212 Battery 220 Power Meter 250 racks 252 Space 500 lines 1200 Computer 1210 Host Controller 1212 CPU 1214 RAM 1220 Input / Output Controller 1222 Communication Interface 1230 ROM

Claims

1. A GHG emissions derivation device comprising a derivation unit that derives the proportion of electricity usage for each of Scope 1, Scope 2, and Scope 3 and category based on information indicating the amount of electricity usage used in a data center and proportion identification information for identifying the proportion for each of Scope 1, Scope 2, and Scope 3 and category to which the amount of electricity usage is to be allocated, and derives greenhouse gas (GHG) emissions by multiplying the proportion by an emission coefficient corresponding to the amount of electricity usage, The proportion identification information indicates, of the electricity usage, the proportion of electricity usage used in the data center by the owner of the data center, which falls under Scope 2, and the proportion of electricity usage by equipment mounted in racks installed in the data center, which is used by a non-owner other than the owner, which falls under Category 13 of Scope 3.

2. The amount of electricity used by the equipment mounted on the rack is based on the measurement results of a power meter installed in each space of the rack. The GHG emission deriving device according to claim 1 .

3. The proportion of the electricity consumption of the equipment mounted on the racks installed in the data center used by each of the non-owners is derived from the number of spaces used by each of the non-owners and the measurement results of one power meter installed in the racks. The GHG emission deriving device according to claim 1 .

4. The method comprises a step of deriving the proportion of the electricity usage for each of Scope 1, Scope 2, and Scope 3 and category based on activity information indicating the amount of electricity used in the data center and proportion identification information for identifying the proportion for each of Scope 1, Scope 2, and Scope 3 and category to which the electricity usage is allocated, and deriving greenhouse gas (GHG) emissions by multiplying the proportion by an emission coefficient corresponding to the amount of electricity usage; A GHG emission derivation method, wherein the proportion identification information indicates, of the electricity usage, the proportion of electricity usage used in the data center by the owner of the data center, which falls under Scope 2, and the proportion of electricity usage by equipment mounted in racks installed in the data center, which is used by a non-owner other than the owner, which falls under Category 13 of Scope 3.

5. A computer is made to function as a derivation unit that derives the proportion of electricity usage for each of Scope 1, Scope 2, Scope 3 and category based on activity information indicating the amount of electricity usage used in a data center and proportion identification information for identifying the proportion for each of Scope 1, Scope 2, Scope 3 and category to which the amount of electricity usage is allocated, and derives greenhouse gas (GHG) emissions by multiplying the proportion by an emission coefficient corresponding to the amount of electricity usage; The program, wherein the proportion identification information indicates the proportion of the electricity usage that is used in the data center by the owner of the data center, which falls under Scope 2, and the proportion of the electricity usage that is used by equipment mounted in racks installed in the data center, which is used by a non-owner other than the owner, which falls under Category 13 of Scope 3.

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