Co2 emissions estimation method

Abstract

To estimate CO2 emission of a building with less effort and cost.SOLUTION: A CO2 emissions estimation method for estimating CO2 emissions, for a building, derived from at least one of fuel and electric power includes: a building information acquisition step of acquiring building information including building specifications of the building and construction information; and a building type specifying step of specifying a building type of the building, using a first specification of the building specifications. By use of a CO2 emissions estimation formula, which has been constructed in advance based on past result data, CO2 emissions are estimated on the basis of information on contract price in the construction information, a second specification in the building specifications, and the building type.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a method for predicting CO2 emissions. [Background technology]

[0002] Recently, interest in environmental issues has been growing, and the construction industry is also being called upon to reduce carbon dioxide (CO2) emissions. In this context, technology for predicting the amount of CO2 emissions during the construction and operation of a building has been attracting attention. For example, Patent Document 1 discloses a technology for accurately predicting the total carbon dioxide emissions of a building by accumulating and calculating the carbon dioxide emissions of construction materials used in the building. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2022-91900 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventionally, carbon dioxide (CO2) emissions were generally predicted by multiplying each planned quantity of a building by its emission unit (for example, the amount of emissions related to construction per cubic meter of concrete) and adding them up. These planned quantities were calculated by multiplying them from design drawings or accumulating them using BIM, but the scope of the calculation was wide-ranging, and calculations had to be redone if any design changes were made, resulting in a lot of work and cost.

[0005] The present invention has been made in consideration of such problems, and an object of the present invention is to predict the CO2 emissions of a building with little effort and cost. [Means for solving the problem]

[0006] The main invention for achieving the above-mentioned object is a CO2 emissions prediction method for predicting CO2 emissions from a building that originate from at least one of fuel and electricity, comprising a building information acquisition step for acquiring building information including building specifications and construction information of the building, and a building type identification step for identifying the building type of the building using a first specification among the building specifications, characterized in that the method predicts CO2 emissions based on information regarding the contract fee from the construction information, a second specification from the building specifications, and the building type, using a CO2 emissions prediction formula previously constructed based on performance data.

[0007] Other features of the present invention will become apparent from the following detailed description of the present invention and the accompanying drawings. Effect of the Invention

[0008] According to the present invention, the CO2 emissions from a building can be predicted with little effort and cost. [Brief description of the drawings]

[0009] [Figure 1] 1 is a table showing an example of details of CO2 emissions at a building construction site. [Diagram 2] FIG. 1 is a diagram illustrating an example of a conventional method for predicting CO2 emissions. [Diagram 3] FIG. 2 is a flow diagram of a method for predicting CO2 emissions in the present embodiment. [Figure 4] FIG. 11 is a diagram illustrating an example of information acquired in a building information acquisition step. [Diagram 5] FIG. 13 is a diagram illustrating an example of information confirmed in a prediction formula application range confirmation step. [Figure 6] FIG. 13 is a diagram illustrating a method for identifying a building type. [Figure 7] FIG. 2 is a diagram for explaining a prediction formula for CO2 emission used to calculate the amount of CO2 emission. [Figure 8]1 is a table illustrating examples of coefficients A to C and a constant term D that are applied to the prediction equation for CO2 emissions. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] At least the following matters will become apparent from the description of this specification and the accompanying drawings. A CO2 emissions prediction method for predicting CO2 emissions from a building that are derived from at least one of fuel and electricity, the method comprising: a building information acquisition step for acquiring building information including building specifications and construction information of the building; and a building type identification step for identifying the building type of the building using a first specification among the building specifications, the method predicting CO2 emissions based on information regarding the contract fee from the construction information, a second specification from the building specifications, and the building type, using a CO2 emissions prediction formula previously constructed based on performance data.

[0011] According to this method of predicting CO2 emissions, it is possible to calculate CO2 emissions without much effort or cost using only certain basic information. For example, it is possible to reduce the cost of predicting CO2 emissions without the effort of tallying up and accumulating planned quantities one by one, as was previously done. In addition, if a change in the plan occurs, there is no need to re-tally up and re-estimate the construction quantities, and predictions can be simplified by comprehensively evaluating the necessary building information as a building type, making it easier to flexibly respond to changes in the plan.

[0012] In such a CO2 emission prediction method, it is desirable that the CO2 emission is calculated by A x the contract amount + B x the second parameter + C x a numerical value corresponding to the building type + a constant term derived from at least one of fuel and electricity.

[0013] According to this method for predicting CO2 emissions, once a prediction formula is constructed, CO2 emissions can be easily calculated if there is data on the building's "contract fee," "secondary specifications (number of basement floors)," and "building type." Therefore, compared to conventional methods, the types of data required to calculate CO2 emissions are limited, making it less time-consuming and cost-intensive.

[0014] In such a CO2 emission prediction method, it is desirable that the prediction formula for calculating the CO2 emissions derived from fuel differs from the prediction formula for calculating the CO2 emissions derived from electricity in at least any of A, B, C, and the constant term.

[0015] According to this method of predicting CO2 emissions, because the coefficients A to C and the constant terms are different for fuel-derived and electricity-derived emissions, it becomes easier to visualize the difference in the impact that data such as "contract fee," "number of basement floors," and "building type" have on calculating CO2 emissions for fuel-derived and electricity-derived emissions. Therefore, in the planning stage, it becomes easier to predict how fuel-derived CO2 emissions and electricity-derived CO2 emissions may differ depending on the type and model of the building.

[0016] It is desirable that such a CO2 emission prediction method further includes, between the building information acquisition step and the building type identification step, a prediction formula application range confirmation step for confirming that the building information is within the application range of the prediction formula.

[0017] This CO2 emission prediction method prevents building information that deviates significantly from past performance data from being applied to the CO2 emission prediction formula, making it easier to calculate accurate CO2 emissions based on the prediction formula.

[0018] It is preferable that the method for predicting the amount of CO2 emissions predicts the amount of CO2 emissions emitted during the construction of the building.

[0019] According to this method for predicting CO2 emissions, the amount of CO2 emissions emitted during construction can be calculated simply by applying predetermined building information to the prediction formula. Even if changes to the plan occur, the CO2 emissions can be easily recalculated simply by applying the changed information to the prediction formula. In particular, even if changes to the plan occur in the early stages of building construction when the plan has not yet been completely determined, the effort and cost are unlikely to become excessive. Therefore, this method is suitable for calculating the amount of CO2 emissions during the construction of a building.

[0020] It is desirable for such a method for predicting CO2 emissions to predict the amount of CO2 emissions emitted during operation of the building.

[0021] According to this method for predicting CO2 emissions, it is possible to calculate the amount of CO2 emissions emitted during operation simply by applying certain building information to the prediction formula. In addition, by comprehensively evaluating the type of building, it is possible to predict CO2 emissions based on the actual usage of the heat source for air conditioning, lighting, outlets, etc. Therefore, it is possible to predict the amount of CO2 emissions during the operation of a building without significant effort or cost.

[0022] In such a method for predicting CO2 emissions, it is desirable that the building specifications include information on at least the total floor area, the number of above-ground floors, the number of underground floors, and building use.

[0023] According to these CO2 emission prediction methods, the amount of CO2 emissions can be calculated based on information that can be easily obtained and confirmed. Therefore, the amount of CO2 emissions can be predicted without much effort.

[0024] In such a CO2 emission prediction method, it is desirable that the first specification is information relating to the total floor area, the number of above-ground floors, and the building use, and the second specification is information relating to the number of underground floors.

[0025] According to this method for predicting CO2 emissions, the amount of CO2 emissions can be calculated based on information that is unlikely to change significantly during the construction or operation of a building. Therefore, the amount of CO2 emissions can be predicted stably.

[0026] === Implementation form === <About conventional CO2 emissions forecasts> First, we will provide a brief overview of the CO2 emissions forecast for buildings. Below, we will explain the case of forecasting fuel-derived and / or electricity-derived CO2 emissions at a building construction site as an example.

[0027] FIG. 1 is a table showing an example of the main items of CO2 emissions at a building construction site. At a building construction site, the CO2 emitted from fuel (scope 1) mainly includes CO2 generated based on the amount of diesel consumed for lifting, excavation, transportation, etc., and kerosene consumed for heating. In addition, the CO2 emitted from electricity (scope 2) mainly includes CO2 generated based on the amount of electricity used to operate lighting, temporary elevators, tower cranes, etc. Then, by calculating and accumulating the CO2 generated for each of these items, it is possible to predict the CO2 emissions from fuel (scope 1) and / or electricity (scope 2) for the entire building. Note that the main items of CO2 emissions shown in FIG. 1 are only an example, and targets other than those shown in FIG. 1 may be considered.

[0028] FIG. 2 is a diagram for explaining an example of a conventional method for predicting CO2 emissions. In general, when predicting the CO2 emissions of a building, first, the construction quantity for each construction work is calculated. For example, the number of machines and the number of operation days for each construction work are planned and calculated for the machinery and equipment and the labor required for civil engineering work and structural work when constructing a building. Next, the fuel and power amount planned to be used to operate the calculated machinery and equipment are calculated. Then, the amount of CO2 emitted when the calculated fuel and power are used is calculated. In this way, the CO2 emissions for each construction work are calculated and accumulated for all construction works, so that the CO2 emissions for the entire building can be predicted. In addition to the method shown in FIG. 2, there is also a method for simply calculating CO2 emissions by multiplying the construction quantity by a specified coefficient (emission coefficient).

[0029] However, in the conventional CO2 emission forecasting method, in either case, it was necessary to calculate the construction quantity (planned quantity). Specifically, it was necessary to calculate the construction quantity as accurately as possible by calculating the construction quantity from the building design drawings or using BIM (Building Information Modeling). With such a method, since the scope of the calculation target was wide, it took a lot of time and cost to tally and calculate the construction quantity. In addition, if the construction quantity changed due to design changes, etc., it was necessary to recalculate the construction quantity each time, which was not cost-effective. Furthermore, in the conventional method, it was common to calculate CO2 emissions using public values ​​as emission coefficients, etc., so it was difficult to reflect the construction capabilities of construction companies, and it was easy for variations to occur between construction companies.

[0030] <CO2 Emissions Prediction of This Embodiment> In contrast, the method for predicting CO2 emissions according to this embodiment makes it possible to predict the amount of CO2 emissions from a building with less effort and time than in the past. FIG. 3 is a flow diagram of the method for predicting CO2 emissions according to this embodiment. In this embodiment, the amount of CO2 emissions originating from at least one of fuel and electricity is predicted simply and at low cost through four steps S001 to S004 shown in FIG. 3. The method for predicting the amount of CO2 emissions will be specifically described below.

[0031] First, a building information acquisition step is performed to acquire predetermined information related to a building (S001). FIG. 4 is a diagram for explaining an example of information acquired in the building information acquisition step. In the building information acquisition step, "building specifications" and "construction information" are acquired as "building information" related to a building to be constructed. The "building specifications" include information related to at least the "total floor area", "number of above-ground floors", "number of underground floors", and "building use". The building use is information indicating what purpose the building will be used for, and is classified into, for example, hospitals, offices, schools, etc. (see FIG. 6 described later). Furthermore, the "building specifications" may include the "structural type" of the building and other information. Moreover, the "construction information" includes information related to at least the "contract money" of the building construction, and may further include the "construction period" and other information.

[0032] Next, a prediction formula application range confirmation step is performed to confirm that each piece of the building information acquired in S001 is within the application range of a prediction formula for CO2 emissions (see FIG. 7 described later) that has been constructed in advance based on performance data (S002). FIG. 5 is a diagram illustrating an example of information confirmed in the prediction formula application range confirmation step. Although details will be described later, in this embodiment, a prediction formula for CO2 emissions is constructed based on past performance data, and the CO2 emissions are predicted by applying the prediction formula to the various pieces of information acquired in S001. Therefore, if the building information on the building to be constructed is significantly different from past performance values, there is a risk that the CO2 emissions cannot be accurately calculated.

[0033] Therefore, it is confirmed that each of the various pieces of information included in the building information is included within the application range of the prediction formula for CO2 emissions (see FIG. 7 described later) and is applicable to the prediction formula. FIG. 5 shows an example of a case where it is confirmed whether or not the "total floor area" of the building information (building specifications) is included within the application range of the prediction formula. In this case, it is confirmed that the "total floor area" of the building to be constructed is larger than the case with the smallest total floor area (lower limit of application range) and smaller than the case with the largest total floor area (upper limit of application range) among the building information (actual values) of multiple buildings used when constructing the prediction formula for CO2 emissions. Note that the upper and lower limits of the application range may be values ​​determined based on past results rather than the past actual values ​​themselves. For example, a value larger than the maximum value of the past actual values ​​may be set as the upper limit of the application range, and a value smaller than the minimum value of the past actual values ​​may be set as the lower limit of the application range.

[0034] This operation is performed for each type of information (building specifications, construction information) acquired as building information, and it is confirmed that it can be applied to the CO2 emission prediction formula according to this embodiment. If any of the building information is outside the scope of application of the CO2 emission prediction formula according to this embodiment, the CO2 emission is predicted according to the conventional method described in FIG. 2, for example.

[0035] Next, a building type identification step is performed (S003) in which a building type of the building to be constructed is identified using predetermined information from the building specifications acquired in S001. FIG. 6 is a diagram explaining a method for identifying a building type. In the building type identification step, a scatter diagram as shown in FIG. 6 is created in advance based on past data of multiple types of buildings. The scatter diagram in FIG. 6 shows the relationship between the total floor area and the number of above-ground floors for each building use.

[0036] In the case of Figure 6, building uses are classified into nine types (retail and food and beverage, logistics, hotels, housing, offices, factories, schools, hospitals, and others), and the average values ​​of the total floor area and number of above-ground floors (corresponding to the "first attribute" of the building attributes) are calculated for each building type, and the total floor area and number of above-ground floors are normalized to create a scatter plot. For example, if there are 20 pieces of actual data for buildings whose building use is "logistics," the average total floor area and the average number of above-ground floors are calculated for each of the 20 cases. This process is performed for all building uses, and the average total floor area and the average number of above-ground floors are calculated for each of the nine building uses mentioned above.

[0037] Then, among the nine types of building uses, the largest average value of the total floor area is normalized to "10" and the smallest to "0". In the example of FIG. 6, the average value of the total floor area of ​​buildings belonging to "Logistics" is the largest and the average value of the total floor area of ​​buildings belonging to "Others" is the smallest. In this case, the total floor area of ​​buildings belonging to "Logistics" is normalized to "10 (maximum average value)" and the total floor area of ​​buildings belonging to "Others" is normalized to "0 (minimum average value)". Similarly, among the nine types of building uses, the largest average value of the number of aboveground floors is normalized to "10" and the smallest to "0". In the example of FIG. 6, the number of aboveground floors of buildings belonging to "Residential" is normalized to "10 (maximum average value)" and the number of aboveground floors of buildings belonging to "Factory" is normalized to "0 (minimum average value)". In this way, a scatter diagram showing the relationship between the normalized total floor area and the normalized number of aboveground floors is obtained for the nine types of building uses. However, the classification of building uses may be more or less than the above-mentioned nine types.

[0038] Next, the scatter diagram is classified into four regions, and a building type is defined for each region. In this embodiment, a region with a normalized number of above-ground floors ≧5 and a normalized total floor area <5 is defined as Type 1. That is, a building type of Type 1 is classified into the upper left region of FIG. 6, and represents a relatively small area and high-rise building. In FIG. 6, buildings used as "residential", "hotel", and "office" are included in the building type of Type 1.

[0039] Similarly, the area where the normalized number of above-ground floors is <5 and the normalized total floor area is <5 is defined as Type 2. Type 2 building types are classified in the lower left area of ​​FIG. 6 and represent buildings with relatively small areas and low rise. In FIG. 6, buildings with uses such as "hospital", "school", "factory", and "other" are included in Type 2 building types. In addition, the area where the normalized number of above-ground floors is <5 and the normalized total floor area is ≧5 is defined as Type 3. Type 3 building types are classified in the lower right area of ​​FIG. 6 and represent buildings with relatively large areas and low rise. In FIG. 6, buildings with uses such as "logistics" and "retail and food service" are included in Type 3 building types.

[0040] In addition, the area where the normalized number of above-ground floors is ≧5 and the normalized total floor area is ≧5 is defined as Type 4. Type 4 building types are classified in the upper right area of ​​Figure 6, and represent relatively large areas and high-rise buildings. Such building types are buildings with special uses, such as large tower-type commercial facilities, and are often specially designed according to their uses, making them less versatile. For this reason, buildings with any uses are not included in Type 4 building types in Figure 6. In the following, Type 4 building types will not be considered.

[0041] Once a scatter diagram like that shown in Fig. 6 has been created, the normalized values ​​of "total floor area" and "number of above-ground floors" among the building specifications of the building information acquired in S001 are plotted on the scatter diagram to identify which type of building model the building to be constructed corresponds to. For example, if the normalized total floor area of ​​the building to be constructed is 3 and the normalized number of above-ground floors is 4, the building model of the building to be constructed is identified as Type 2.

[0042] The normalized values ​​of "total floor area" and "number of above-ground floors" can be calculated as follows. For example, if the total floor area of ​​a building to be constructed is Sn, the maximum total floor area in the performance data is S1 (in the above example, the average total floor area of ​​buildings belonging to "Logistics"), and the minimum total floor area in the performance data is S2 (in the above example, the average total floor area of ​​buildings belonging to "Other"), the normalized total floor area of ​​the building to be constructed is expressed as Sn / (S1-S2)×(10-0).

[0043] Next, the various building information acquired in S001 and the building type identified in S003 are applied to a prediction formula for the amount of CO2 emissions to calculate the amount of CO2 emissions (S004). Fig. 7 is a diagram for explaining the prediction formula for the amount of CO2 emissions used to calculate the amount of CO2 emissions.

[0044] The prediction formula shown in FIG. 7 calculates predicted CO2 emissions using the "contract amount (billion yen)" from the construction information, the "number of basement floors" (corresponding to the second specification) from the building specifications, and the "building type" as parameters (explanatory variables). Specifically, as shown in FIG. 7, the value of A x "contract amount" + B x "number of basement floors" + C x "building type" + D is calculated as the CO2 emissions. Here, A, B, and C are coefficients by which each parameter is multiplied, and D is a constant term. In this embodiment, the coefficients A, B, and C, and the constant term D are calculated for each of the CO2 emissions derived from fuel and the CO2 emissions derived from electricity. In other words, the prediction formula for CO2 emissions is constructed for two types of CO2 emissions, namely, the CO2 emissions derived from fuel and the CO2 emissions derived from electricity.

[0045] The coefficients A, B, C, and constant term D are found using past performance data. For example, assume that the known performance data for a certain "house" constructed in the past includes the contract amount X1 (billion yen), the number of basement floors Y1 (floors), the building model Type 1, and the performance value of CO2 emissions (fuel-derived or electricity-derived) E1 (tons). For the performance data, the theoretical value E' is calculated using the formula E'=A×X1+B×Y1+C×Type 1+D, and compared with the performance value E1. This comparison is then made for multiple samples (performance data), and A, B, C, and D that minimize the square of the difference between the performance value E1 and the theoretical value E' are determined.

[0046] The coefficient C is a coefficient determined for each building type, and in this embodiment, three types of coefficients are defined for each of the three types of building types. For example, if C=(C1×Type 1)+(C2×Type 2)+(C3×Type 3), then if the building to be constructed is Type 1, then Type 1=1, Type 2=0, and Type 3=0, and C=(C1×1)+(C2×0)+(C3×0)=C1. Similarly, if the building to be constructed is Type 2, then C=(C1×0)+(C2×1)+(C3×0)=C2, and if the building to be constructed is Type 3, then C=(C1×0)+(C2×0)+(C3×1)=C3.

[0047] In this way, by applying past performance data, coefficients A, B, C (C1, C2, C3) that minimize the square of the difference between the theoretical value and the performance value, and constant term D are obtained, and a prediction formula (multiple regression formula) shown in Figure 7 is constructed. Then, by using the constructed prediction formula, CO2 emissions can be predicted.

[0048] Fig. 8 is a table explaining examples of coefficients A to C and constant term D applied to the prediction formula for CO2 emissions. In Fig. 8, if the coefficients of the prediction formula for calculating fuel-derived CO2 emissions are A=a1, B=b1, C=c11 (type 1), c12 (type 2), c13 (type 3), and D=d1, for example, if the building to be constructed is a "residence", the contract amount is Xj, the number of basement floors is Yj, and the building type is type 1, the predicted value Ej of fuel-derived CO2 emissions is calculated as Ej=a1×Xj+b1×Yj-c11×1+d1.

[0049] Similarly, in Figure 8, if the coefficients of the prediction formula for calculating electricity-derived CO2 emissions are A = a2, B = b2, C = c21 (Type 1), c22 (Type 2), c23 (Type 3), D = d2, for example, if the building to be constructed is a "hospital", the contract amount is Xb, the number of basement floors is Yb, and the building type is Type 2, the predicted value Eb of electricity-derived CO2 emissions is calculated as Eb = a2 × Xb + b2 × Yb + c22 × 1 + d2.

[0050] In this way, by using the CO2 emission prediction method of this embodiment, it is possible to calculate the CO2 emission amount without much effort or cost using only predetermined basic information. That is, based on the total floor area, the number of above-ground floors, the number of underground floors, and the building use as building specifications, and on the contract money as construction information, the CO2 emission amount based on the actual results can be predicted. Therefore, it is possible to significantly reduce the cost of calculating the CO2 emission amount without the effort of tallying up and accumulating the construction quantity (planned quantity) related to the building construction work one by one, as was done in the past. In addition, even if the plan is changed during the construction work, the CO2 emission amount can be easily recalculated by applying the changed value to the prediction formula. In other words, there is no need to re-tally up and re-accumulate the construction quantity in response to the plan change, and it is possible to flexibly respond to the plan change.

[0051] Furthermore, by evaluating uses such as hospitals and factories as "building types (Types 1-3)," CO2 predictions can be simplified and made more accurate. In other words, by integrating information on "total floor area" and "number of above-ground floors" as building types rather than simply multiplying each item by a coefficient, it becomes easier to reflect differences that arise between building types, making it possible to predict CO2 emissions more accurately. Furthermore, by comprehensively evaluating the necessary building information as building types, predictions can be simplified and plans can be more flexibly accommodated.

[0052] In addition, because the prediction formula is constructed based on the past performance values ​​of the contractor in charge of constructing the building, the calculated CO2 emissions reflect the construction capabilities of the contractor, making it possible to predict CO2 emissions that are in line with actual conditions.

[0053] As described in FIG. 7, the CO2 emission prediction formula of this embodiment is composed of a value obtained by multiplying each parameter of the building information by a predetermined coefficient (A to C) and a constant term. In other words, once the prediction formula is constructed, it is possible to easily calculate the CO2 emission amount if there is data on the "contract fee" as the construction information, the "number of basement floors" as the building specifications (second specifications), and the "building type" as the building use. Therefore, compared to the conventional method, the type of data required to calculate the CO2 emission amount is limited, and the amount of data itself is small, so that it is less time-consuming and cost-intensive.

[0054] In addition, the values ​​of coefficients A to C and constant term D are calculated separately for the formula predicting fuel-derived CO2 emissions and the formula predicting electricity-derived CO2 emissions. Therefore, as shown in FIG. 8, it is highly likely that coefficients A to C and constant term D applied to the formula predicting fuel-derived CO2 emissions are different from coefficients A to C and constant term D applied to the formula predicting electricity-derived CO2 emissions. With this configuration, it becomes easier to understand the difference in the influence of data such as "contract fee", "number of basement floors" and "building type" on the calculation of CO2 emissions between fuel-derived and electricity-derived, and the difference in fuel and electricity consumed during construction depending on the type and type of building becomes clearer. For example, it becomes easier to visualize which parts of a building should be planned and how to reduce CO2 emissions.

[0055] In addition, the prediction formula according to this embodiment (see FIG. 7) can predict the amount of CO2 emitted during the construction of a building. As described above, conventionally, a method of predicting the amount of CO2 emitted during the construction of a building has been generally used in which each planned quantity is multiplied by an emission unit to accumulate the CO2 emissions. For example, in order to multiply each amount of concrete in the framework by the amount of CO2 emissions related to the construction per cubic meter of concrete, it is necessary to use design drawings and BIM to tabulate the planned quantities in detail, which requires a huge amount of effort and cost. In particular, in the early stages of construction, there is a high possibility that the plan is not completely determined, and there is a risk of a large impact if the plan is changed. In contrast, in this embodiment, the amount of CO2 emitted during construction can be calculated without significant effort or cost by simply applying predetermined building information to the prediction formula. And even if the plan is changed, the CO2 emissions can be easily recalculated by simply applying the changed information to the prediction formula. Therefore, it is suitable for calculating the CO2 emitted during the construction of a building.

[0056] The information used to predict CO2 emissions includes "total floor area," "number of above-ground floors," and "building use" as the first specifications in the building information, and "number of underground floors" as the second specifications in the building information. All of this information can be easily acquired and confirmed, and is unlikely to change significantly during the construction of the building. Therefore, in this embodiment, CO2 emissions can be predicted stably without much effort.

[0057] ===Other embodiments=== The above-mentioned embodiment is for facilitating understanding of the present invention, and is not intended to limit the present invention. The present invention may be modified or improved without departing from the spirit of the present invention, and it goes without saying that the present invention includes equivalents. In particular, the following embodiments are also included in the present invention.

[0058] In the above embodiment, a method for predicting the amount of CO2 emitted when constructing a building using a CO2 emission prediction formula has been described, but it is also possible to predict the amount of CO2 emitted when operating a building using the CO2 emission prediction formula. That is, by constructing a prediction formula corresponding to Fig. 7 based on the operational performance of the building and performing each step (S001 to S004) described in Fig. 3, it is possible to predict the amount of CO2 emitted during the operation of the building.

[0059] For example, a building type such as a "hotel (type 1)" that is long vertically and a "retail and food service building (type 3)" that is wide horizontally will have significantly different heat sources for air conditioning, lighting and outlet usage, elevator operation, etc. Therefore, as in the above-mentioned embodiment, by comprehensively evaluating the building type, it is possible to predict CO2 emissions that are in line with the actual situation. In this way, by using the CO2 emission prediction formula according to this embodiment, it is possible to predict CO2 emissions during building operation without significant effort or cost. [Explanation of symbols]

[0060] S001: Building information acquisition step; S002: Step for checking whether prediction formula is within the applicable range; S003 Building type identification step, S004 CO2 emission calculation step

Claims

1. A method for predicting CO2 emissions from a building that are derived from at least one of fuel and electricity, comprising: A building information acquisition step of acquiring building information including building specifications and construction information of the building; A building type identification step of identifying a building type of the building using a first parameter among the building parameters; having A method for predicting CO2 emissions, characterized in that a prediction formula for CO2 emissions previously constructed based on actual data is used to predict CO2 emissions based on information regarding the contract fee from the construction information, a second specification from the building specifications, and the building type.

2. 2. The method for predicting CO2 emissions according to claim 1, A method for predicting CO2 emissions, characterized in that the CO2 emissions are calculated by A x the contract amount + B x the second parameter + C x a numerical value corresponding to the building type + a constant term derived from at least one of fuel and electricity.

3. The method for predicting CO2 emissions according to claim 2, A method for predicting CO2 emissions, characterized in that a prediction formula for calculating the CO2 emissions derived from fuel and a prediction formula for calculating the CO2 emissions derived from electricity differ in at least any of A, B, C, and the constant term.

4. The method for predicting CO2 emissions according to any one of claims 1 to 3, Between the building information acquisition step and the building type identification step, A method for predicting CO2 emissions, further comprising a prediction formula application range confirmation step of confirming that the building information is within an application range of the prediction formula.

5. The method for predicting CO2 emissions according to any one of claims 1 to 3, A method for predicting CO2 emissions, comprising predicting the amount of CO2 emitted during the construction of the building.

6. The method for predicting CO2 emissions according to any one of claims 1 to 3, A method for predicting CO2 emissions, comprising predicting the amount of CO2 emitted during operation of the building.

7. The method for predicting CO2 emissions according to any one of claims 1 to 3, The method for predicting CO2 emissions, wherein the building specifications include information regarding at least total floor area, number of above-ground floors, number of underground floors, and building use.

8. The method for predicting CO2 emissions according to claim 7, The first specifications are information regarding the total floor area, the number of above-ground floors, and the building use, The method for predicting CO2 emissions, wherein the second parameter is information relating to the number of underground floors.

Images