Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
DETAILED ACTION
The following NON-FINAL Office Action is in response to Application 18/953,660 - filed on 11/20/2024.
Priority
Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
The Examiner has noted the Applicant claiming Foreign priority from Application CN202311551416.8 filed 11/20/2023.
Status of Claims
Claims 1-20 are currently pending.
Claims 1-20 are currently under examination and have been rejected as follows.
IDS
The information disclosure statement filed on 12/23/2024 complies with the provisions of 37 CFR 1.97, 1.98 and MPEP § 609 and is considered by the Examiner.
Claim Objections
Claim 10 is objected to because of the following informalities:
Claim 10 recites: “The carbon quota processing method according to claim 4, wherein calculating the decoupling factor comprises:
“obtain a first parameter… ;
“obtain a second parameter….”
Claim 10 is recommended to recite, as an example only: “The carbon quota processing method according to claim 4, wherein calculating the decoupling factor comprises:
“ obtaining a first parameter… ;
“ obtaining a second parameter….”
Appropriate correction is required.
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Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 3, 7, 17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 3, 17 recite: [..] “calculating the influencing factors that influence the balance between environmental protection and development of the target manufacturing entity based on…, the category of the target manufacturing entity, and the carbon emission planning parameter.”
Claims 3, 17 are rendered vague and indefinite because there is insufficient antecedent basis for “the category of the target manufacturing entity” in the claim.
Claim 3, 17 are recommended to recite, as an example only, [..] “calculating the influencing factors that influence the balance between environmental protection and development of the target manufacturing entity based on…, a category of the target manufacturing entity, and the carbon emission planning parameter.
*** OR ***
Claims 3, 17 is recommended to recite, as an example only, [..] “calculating the influencing factors that influence the balance between environmental protection and development of the target manufacturing entity based on…, the type of the target manufacturing entity, and the carbon emission planning parameter”, in a manner consistent with antecedently recited claim 3 language “a type of the target manufacturing entity, based on the historical carbon inventory data”.
Claim 7 recites: [..] “wherein the carbon emission reduction capacity of the first type entity is greater than that of the second type entity, and the carbon emission reduction capacity of the second type entity is greater than that of the third type entity.”
Claim 7 is rendered vague and indefinite because there is insufficient antecedent basis for “the carbon emission reduction capacity”, “that of the second type entity”, or “that of the third type entity”.
Claim 7 is recommended to recite, as an example only, [..] “wherein a carbon emission reduction capacity of the first type entity is greater than a carbon emission reduction capacity of the second type entity, and the carbon emission reduction capacity of the second type entity is greater than a carbon emission reduction capacity of the third type entity.”
Appropriate correction is required.
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Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-14 are directed to a method or process which is a statutory category.
Claims 15-17 are directed to a system or machine which is a statutory category.
Claims 18-20 are directed to a non-transitory computer-readable storage medium or article of manufacture which is a statutory category.
Step 2A Prong One: The claims recite, describe, or set forth a judicial exception of an abstract idea (see MPEP 2106.04(a)). Specifically, the claims recite, describe or set forth mitigating risk, legal obligations, and/or mathematical relationships, formulas, equations, or calculations, including: “determining a target manufacturing entity and searching for historical carbon inventory data of manufacturing entities within a manufacturing entity set to which the target manufacturing entity belongs”, “obtaining a carbon emission planning parameter of the target manufacturing entity during a target time period”, “calculating influencing factors that influence the balance between environmental protection and development of the target manufacturing entity based on the historical carbon inventory data and the carbon emission planning parameter”, “building a carbon quota allocation model based on the influencing factors”, and “allocating a carbon quota during the target time period to the target manufacturing entity based on the carbon quota allocation model”. Allocating carbon quotas for manufacturing entities within industrial groupings falls within mitigating risk as it pertains to fundamental economic principles or practices as well as legal obligations as they pertain to commercial or legal interactions, each within the larger subgrouping of Certain Methods of Organizing Human Activity (MPEP 2106.04(a)(2) II). Determining the quotas for manufacturing entities based on quantitative environmental and production data falls within mathematical relationships, formulas, equations, or calculations under the larger subgrouping of Mathematical Concepts1 (MPEP 2106.04(a)(2) I). Accordingly, the claims recite an abstract idea.
Step 2A Prong Two: Independent claim 1 (along with its dependent claims 2-14) does not appear to provide any further additional computer-based elements, let alone for such additional computer-based elements to integrate the abstract idea into practical application. Independent claims 15, 18 recite the following additional elements: “memory”, “processor”, and “non-transitory computer-readable storage medium”. The functions of these additional elements include examples such as “determining a target manufacturing entity and searching for historical carbon inventory data”, “obtaining a carbon emission planning parameter”, “calculating influencing factors that influence the balance between environmental protection and development of the target manufacturing entity”, “building a carbon quota allocation model based on the influencing factors”, and “allocating a carbon quota during the target time period”. The additional elements are recited at a high level of generality (i.e. as a generic computer performing functions of querying for and obtaining data, performing calculations, organizing and communicating data, etc.) such that they amount to no more than mere instructions to apply the exception using generic computer components. Therefore, these functions can be viewed as not meaningfully different than a business method or mathematical algorithm being applied on a general-purpose computer as tested per MPEP 2106.05(f)(2)(i). The claims are directed to an abstract idea and the judicial exception does not integrate the abstract idea into a practical application.
Step 2B: According to MPEP 2106.05(f)(1), considering whether the claim recites only the idea of a solution or outcome i.e., the claims fail to recite the technological details of how the actual technological solution to the actual technological problem is accomplished. The recitation of claim limitations that attempt to cover an entrepreneurial and thus abstract solution to an entrepreneurial problem with no technological details on how the technological result is accomplished and no description of the mechanism for accomplishing the result do not provide significantly more than the judicial exception.
Dependent claims 2-14, 16-17, 19-20 do not appear to provide any further additional computer-based elements, let alone for such additional computer-based elements to integrate the abstract idea into practical application.
Further, dependent claims 2-14, 16-17, 19-20 merely incorporate the additional elements recited in claims 15, 18 along with further narrowing of the abstract idea of claims 15, 18 and their execution of the abstract idea. Specifically, the dependent claims narrow the “memory”, “processor”, and “non-transitory computer-readable storage medium” to capabilities such as obtaining, sending, and calculating various forms of data such as carbon emissions, manufacturing entities, time periods, prompt messages, carbon emission intensity mean values, carbon emission changes, gross industrial production changes, influence factors, etc. which, when evaluated per MPEP 2106.05(f)(2) represent mere invocation of computers to perform existing processes. Therefore, the additional elements recited in the claimed invention individually and in combination fail to integrate a judicial exception into a practical application (Step 2A prong two) and for the same reasons they also fail to provide significantly more (Step 2B). Thus, claims 1-20 are reasoned to be patent ineligible.
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REJECTIONS BASED ON PRIOR ART
Examiner Note: Some rejections will contain bracketed comments preceded by an “EN” that will denote an examiner note. This will be placed to further explain a rejection.
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Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-3, 15-20 is/are rejected under 35 U.S.C. 102(a)(1) & 102(a)(2) as being anticipated by
Zhang et al. US 20240296409 A1, hereinafter Zhang. As per,
Regarding claims 1, 15, 18: Zhang teaches:
A carbon quota processing method, comprising:
determining a target manufacturing entity and searching for historical carbon inventory data of manufacturing entities within a manufacturing entity set to which the target manufacturing entity belongs (Zhang ¶ [0010]: In order to solve the above problem, according to the invention of claim 1, there is provided a future prediction device that predicts future GHG emissions, the future prediction device including: base year company emissions calculation means for calculating GHG emissions of a predetermined company in a base year; social change prediction means for predicting a future social change of an industry to which the predetermined company belongs [EN: manufacturing entity set] by using a change scenario of an economic model; and future emissions calculation means for calculating future GHG emissions of the predetermined company from the GHG emissions of the predetermined company calculated by the base year [EN: historical data] company emissions calculation means on the basis of the future social change of the industry to which the predetermined company belongs predicted by the social change prediction means);
obtaining a carbon emission planning parameter of the target manufacturing entity during a target time period (See Zhang Fig. 5 S10: Input base year and prediction period [EN: target time period]; S13: Set GHG emission reduction target value [EN: carbon emission planning parameter] of company. ¶ [0089]: First, as shown in FIG. 5, the input/output unit 21 inputs each piece of information about the base year of prediction and the prediction period as information about the prediction object (S11). For example, the user Y sets the base year of prediction as 2015 and the prediction period as 2015 to 2050);
calculating influencing factors that influence the balance between environmental protection and development of the target manufacturing entity based on the historical carbon inventory data and the carbon emission planning parameter (Zhang ¶ [0076]: …the social change prediction unit 31 acquires an industry-related table and evaluation condition values from the numerical value DB 3000, acquires data of an economic model (for example, an applied general equilibrium model (base scenario)) from the evaluation formula DB 4000, and calculates base data showing the state of society and the economy (production value, GHG emissions, etc. of each industry) during the prediction period, thereby generating a base scenario);
building a carbon quota allocation model based on the influencing factors Zhang continued at ¶ [0076]: In this case, the social change prediction unit 31 converts the industry related table and evaluation condition values into a form that can be expressed in the applied general equilibrium [EN: carbon quota allocation] model, and inputs the converted information to the applied general equilibrium model); and
allocating a carbon quota during the target time period to the target manufacturing entity based on the carbon quota allocation model (Zhang ¶ [0080]: More specifically, the base year company emissions calculation unit 41 acquires company information from the numerical value DB 3002, acquires the company GHG emissions calculation formula (Formula 1) from the evaluation formula DB 4001, and calculates the GHG emissions (Scope 1, 2) of the company to be predicted… the base year company emissions calculation unit 41 sets the GHG emission reduction target value [EN: carbon quota] for the prediction period and stores the set value in the data storage unit… the base year company emissions calculation unit 41 sets an allowable deviation range (threshold value) [EN: carbon quota] during the prediction period and stores the set value in the data storage unit 29).
Regarding claims 2, 16, 19: Zhang teaches:
The carbon quota processing method according to claim 1, further comprising:
obtaining a carbon emission of the target manufacturing entity during the target time period (Zhang ¶ [0080]: More specifically, the base year company emissions calculation unit 41 acquires company information from the numerical value DB 3002, acquires the company GHG emissions calculation formula (Formula 1) from the evaluation formula DB 4001, and calculates the GHG emissions (Scope 1, 2) of the company to be predicted); and
sending a prompt message to a client of the target manufacturing entity, in a case where the carbon emission of the target manufacturing entity during the target time period does not match the allocated carbon quota (Zhang ¶ [0086]: The alert information generation unit 50 includes an allowable range determination unit 51. The allowable range determination unit 51… determines whether or not each of the GHG emissions (Scope 1, 2) and the GHG emissions (Scope 3) calculated by the future emissions calculation unit 44 exceed an allowable deviation threshold value with respect to a reduction target value indicated by each of pieces of GHG emission reduction target information. When the result exceeds the threshold value, the alert information generation unit 50 automatically generates alert information).
Regarding claims 3, 17, 20: Zhang teaches:
The carbon quota processing method according to claim 1, wherein calculating influencing factors that influence the balance between environmental protection and development of the target manufacturing entity comprises:
calculating
a first carbon emission intensity mean value of the manufacturing entity set corresponding to a historical time period (Zhang ¶ [0081]: The base year other company emissions calculation unit 42 calculates GHG emissions of other companies [EN: entity set] related to the activities of a predetermined company in the base year [EN: historical time period]. GHG emissions of other companies related to the activities of a predetermined company includes GHG emissions resulting from transactions or contracts with other companies such as suppliers and customers of the company. GHG emissions resulting from the transaction or contract include GHG emissions resulting from products purchased by the company from its suppliers. [Also see Fig. 5 and related text]),
a second carbon emission intensity mean value of the target manufacturing entity corresponding to the historical time period (Zhang ¶ [0079]: Among them, the base year company emissions calculation unit 41 calculates GHG emissions of a predetermined company [EN: target entity] in a base year [EN: historical time period]),
a carbon emission change and a gross industrial production change of the target manufacturing entity during a first time period within the historical time period relative to a second time period prior to the first time period (See Zhang Fig. 5, S18: Calculate change data (production value, GHG emissions. etc. of each industry) showing result of predicting future social change of each industry in economic model; S22: Calculate changes in GHG emissions of each company. Zhang ¶ [0077]: The rate-of-change calculation unit 32 calculates a rate of change in GHG emissions of each year in each industry on the basis of the change data calculated by the social change prediction unit 31 for each year [EN: multiple time periods] during the prediction period. In addition, the rate-of-change calculation unit 32 stores data on the calculated rate of change in GHG emissions in the data storage unit 29), and
a type of the target manufacturing entity, based on the historical carbon inventory data (Zhang ¶ [0083]: The belonging industry determination unit 43 acquires company information of a company to be predicted and information on another company (supplier, customer) related to the company to be predicted from the numerical value DB 3001, and determines the industry [EN: type] to which each company belongs); and
calculating the influencing factors that influence the balance between environmental protection and development of the target manufacturing entity based on the first carbon emission intensity mean value, the second carbon emission intensity mean value, the carbon emission change, the gross industrial production change, the category of the target manufacturing entity, and the carbon emission planning parameter (See Zhang breakdown of citations for summarized limitations above in Fig. 5, ¶ [0071], [0077], [0079], [0081], [0083]).
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Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 4-10, 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over:
Zhang in view of
Zou et al. US 20230410127 A1, hereinafter Zou. As per,
Regarding claim 4: Zhang teaches all the limitations of claim 3 above.
Zhang further teaches:
wherein the influencing factors comprise a development growth factor (Zhang ¶ [0100]: For example, the social change prediction unit 31 catches information that 10% of hydrogen power generation will be introduced by 2050 from news information, and uses an economic model to predict social changes (GHG emissions for each industry, etc.) for each year during the prediction period due to the changes. The change data calculated by this prediction is shown as a hydrogen scenario in FIG. 9. FIG. 9 is a graph showing GHG emissions up to 2050 in each scenario. FIG. 9 shows GHG emissions due to the development of a hydrogen society when the base data shown in FIG. 8 is Business as usual (BAU)) and
at least two of an intensity factor, a type factor, a decoupling factor and a policy factor, wherein building the carbon quota allocation model comprises: determining a periodic decline coefficient based on a product of at least two of the intensity factor, the type factor, the decoupling factor, and the policy factor (Zhang ¶ [0093]: the base year company emissions calculation unit 41 sets the GHG emission reduction target value of the company [EN: policy factor] to be predicted during the prediction period, and stores the set value in the data storage unit 29 (513). ¶ [0112]: For example, the future emissions calculation unit 44 multiplies the GHG emissions [EN: intensity factor] of company A and companies B and C which are suppliers of company A in the base year (2015) by the rate of change in GHG emissions in the industry to which they belong [EN: type factor], and thereby calculates the GHG emissions of company A and companies B and C which are suppliers of company A in the prediction year. ¶ [0102]: For example, in the case of the above-mentioned hydrogen scenario, the rate-of-change calculation unit 32 calculates the rate of change in GHG emissions [EN: periodic decline coefficient] for each industry for each year during the prediction period in the hydrogen scenario, as shown below. [Math. 6] R(s,t) = EMS(s,t)/EMS(s,t0));
determining a [..] value [..] during the target time period based on a product of a[n] [..] value [..] corresponding to the historical time period and the development growth factor (Zhang ¶ [0054]: The company GHG emissions calculation formula (Formula 1) is a formula for calculating GHG emissions in a company to be predicted. [Math. 1] EMs12(t0) = Σ Energy(i,t0) * EF(i,t0). ¶ [0114]: For the GHG emissions (Scope 1, 2) in the prediction year 2050 of company A in the hydrogen scenario, the future emissions calculation unit 44 calculates the values shown below. [Math. 7] EM(s12_h,2050) = 3,598,000 • 1.01 = 3,633,980 (kg)); and
obtaining the carbon quota allocation model by multiplying the periodic decline coefficient, the gross industrial production value during the target time period, and the second carbon emission intensity mean value (Zhang ¶ [0115]: In addition, regarding the amount of change in GHG emissions of companies B and C which are suppliers of company A in the prediction year 2050 in the hydrogen scenario, the future emissions calculation unit 44 regards the rate of fluctuation of the industry to which each of companies B and C which are suppliers belongs as the rate of change of the GHG emission intensity of purchased products, and calculates the GHG emissions of Category 1 (purchased products and services) of Scope 3 in the prediction year 2050 using (Formula 5) as shown below. [Math. 8] EC(c1,t) = Σ Sup(r,t) * Emp(r,t0) * R(s,t)).
Although Zhang teaches policy factors, carbon emission intensity factors, declining emissions coefficients influencing the carbon quota allocation model, Zhang does not specifically teach gross industrial production of the manufacturing entity set being a factor.
However, Zou in analogous art of industrial carbon emission data management teaches or suggests:
determining a gross industrial production value of [..] an average gross industrial production value of the manufacturing entity set corresponding to the historical time period and the development growth factor (Zou ¶ [0009]: S2, the data center control substitutes the operation data into the intelligent production accounting model to obtain enterprise-level production indicators, accumulates all the enterprise-level production indicators in the region to obtain regional production indicators, and substitutes the regional production indicators into the prediction algorithm to obtain regional prediction data, wherein the production indicators comprise carbon emission indicators, energy consumption indicators and economic indicators; and region refers to a collection of all enterprise ports within a certain geo graphical range).
Zou and Zhang are found as analogous art of industrial carbon emission data management. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified Zhang’s future greenhouse gas emission prediction system and method to have included Zou’s teachings around gross industrial production of the manufacturing entity set being a factor in a carbon allocation model. The benefit of these additional features would have achieved the effect of data interconnection among industrial entities the work efficiency of carbon allocation data modeling is improved. (Zou ¶ [0036]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by Zhang in view of Zou (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of industrial carbon emission data management. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by Zhang in view of Zou above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claim 5: Zhang / Zou teaches all the limitations of claim 4 above.
Zhang further teaches:
calculating a regulation of total carbon emissions factor for the manufacturing entity set, wherein obtaining the carbon quota allocation model further comprises: obtaining the carbon quota allocation model [by multiplying] the periodic decline coefficient, the gross industrial production value during the target time period, the second carbon emission intensity mean value, and the regulation of total carbon emissions factor (Zhang mid-¶ [0076]: In addition, the social change prediction unit 31 acquires news information and statistical information from the numerical value DB 3001 and acquires data of an economic model (for example, an applied general equilibrium model (change scenario)) from the evaluation formula DB 4000 in order to catch predictions of social changes, and calculates change data showing the changing state of society and the economy (production value, GHG emissions, etc. of each industry) during the prediction period, thereby predicting and generating a change scenario [EN: regulation of total carbon emissions factor]. In this case, the social change prediction unit 31 converts the news information and statistical information into a form that can be expressed in the applied general equilibrium model, and inputs the converted information to the applied general equilibrium model ¶ [0077]: The rate-of-change [EN: periodic decline] calculation unit 32 calculates a rate of change in GHG emissions of each year in each industry on the basis of the change data [EN: second value] calculated by the social change prediction unit 31 for each year during the prediction period. In addition, the rate-of-change calculation unit 32 stores data on the calculated rate of change in GHG emissions in the data storage unit 29. ¶ [0100]: For example, the social change prediction unit 31 catches information that 10% of hydrogen power generation will be introduced by 2050 from news information, and uses an economic model to predict social changes (GHG emissions for each industry, etc.) for each year during the prediction period due to the changes).
Although Zhang teaches calculating a regulation of total carbon emissions factor wherein obtaining the carbon quota allocation model further comprises the periodic decline coefficients, the gross industrial production values, carbon emission intensity mean values, and the regulation of total carbon emissions factors, Zhang does not specifically teach the multiplication of all the factors in achieving the carbon quota allocation model.
However, Zou in analogous art of industrial carbon emission data management teaches or suggests:
[..] wherein obtaining the carbon quota allocation model further comprises: obtaining the carbon quota allocation model by multiplying the [various factors] (See Zou description of carbon emissions factor formula at ¶ [0066] involving multiplication of several other factors at ¶ [0077]).
Zou and Zhang are found as analogous art of industrial carbon emission data management. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified Zhang’s future greenhouse gas emission prediction system and method to have included Zou’s teachings around the multiplication of all the factors in achieving the carbon quota allocation model. The benefit of these additional features would have achieved the effect of data interconnection among industrial entities the work efficiency of carbon allocation data modeling is improved. (Zou ¶ [0036]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by Zhang in view of Zou (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of industrial carbon emission data management. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by Zhang in view of Zou above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claim 6: Zhang / Zou teaches all the limitations of claim 5 above.
Although Zhang teaches calculating the regulation of total carbon emissions factor for the manufacturing entity set, Zhang does not specifically teach calculating a sum of carbon quotas for each entity, or comparing total emissions target values for the entity set to the total carbon quota allocation for the entity set.
However, Zou in analogous art of industrial carbon emission data management teaches or suggests:
calculating a sum of carbon quotas of the multiple manufacturing entities during the target time period to obtain a total carbon quota allocation of the manufacturing entity set (Zou end-¶ [0046]: Regional production indicators represent the sum of production indicators of all enterprises in the specific geographical range. Regional prediction data refers to the carbon emission indicators, energy consumption indicators and economic indicators predicted to reach in the region in a certain time in future); and
obtaining the regulation of total carbon emissions factor based on a ratio of a total carbon emission target value of the manufacturing entity set during the target time period to the total carbon quota allocation of the manufacturing entity set (Zou ¶ [0047]: S3, the data center control is pre-set with regional target data, and determines whether the regional prediction data exceeds the target data, and if so, obtains the regional energy consumption reduction task and the regional carbon emission reduction task according to the difference between the regional production data and the regional prediction data).
Zou and Zhang are found as analogous art of industrial carbon emission data management. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified Zhang’s future greenhouse gas emission prediction system and method to have included Zou’s teachings around calculating a sum of carbon quotas for each entity and comparing total emissions target values for the entity set to the total carbon quota allocation for the entity set. The benefit of these additional features would have achieved the effect of data interconnection among industrial entities the work efficiency of carbon allocation data modeling is improved. (Zou ¶ [0036]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by Zhang in view of Zou (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of industrial carbon emission data management. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by Zhang in view of Zou above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claim 7: Zhang / Zou teaches all the limitations of claim 4 above.
Zhang further teaches:
wherein the type of the target manufacturing entity comprises a first type entity, a second type entity, or a third type entity, wherein the carbon emission reduction capacity of the first type entity is greater than that of the second type entity, and the carbon emission reduction capacity of the second type entity is greater than that of the third type entity (See Zhang FIG. 10 manufacturing entity types, such as metal product, chemical product, fiber product, food and drink, etc., each with different rates of change of emissions by 2050 (i.e. reduction capacities), and related text).
Regarding claim 8: Zhang / Zou teaches all the limitations of claim 7 above.
Zhang further teaches:
wherein calculating the intensity factor comprises:
setting the intensity factor to a first value in a case where the target manufacturing entity is the first type entity or the second type entity, and the second carbon emission intensity mean value of the target manufacturing entity is greater than the first carbon emission intensity mean value (Zhang mid-¶ [0093]: For example, the base year company emissions calculation unit 41 sets the GHG emission reduction target value to 3,598,000 kg by 2030 on the basis of the emission reduction target value of 4.2% every year. ¶ [0095] Next, the base year other company emissions calculation unit 42 acquires information on another company (supplier, customer) related to the company to be predicted from the numerical value DB 3002, acquires the other company GHG emissions calculation formula (Formula 2) from the evaluation formula DB 4001, and thereby calculates each GHG emissions (Scope 3) of the supplier and customer related to the company to be predicted (Sl5). [Also see Figs. 10-11 showing different emission values for different manufacturing entity types]);
setting the intensity factor to a second value greater than the first value in a case where the target manufacturing entity is the first type entity or the second type entity, and the second carbon emission intensity mean value of the target manufacturing entity is less than or equal to the first carbon emission intensity mean value (Zhang mid-¶ [0093]: For example, the base year company emissions calculation unit 41 sets the GHG emission reduction target value to 3,598,000 kg by 2030 on the basis of the emission reduction target value of 4.2% every year. ¶ [0095] Next, the base year other company emissions calculation unit 42 acquires information on another company (supplier, customer) related to the company to be predicted from the numerical value DB 3002, acquires the other company GHG emissions calculation formula (Formula 2) from the evaluation formula DB 4001, and thereby calculates each GHG emissions (Scope 3) of the supplier and customer related to the company to be predicted (Sl5). [Also see Figs. 10-11 showing different emission values for different manufacturing entity types]); and
setting the intensity factor to a third value greater than the second value in a case where the target manufacturing entity is the third type entity (Zhang mid-¶ [0093]: For example, the base year company emissions calculation unit 41 sets the GHG emission reduction target value to 3,598,000 kg by 2030 on the basis of the emission reduction target value of 4.2% every year. ¶ [0095] Next, the base year other company emissions calculation unit 42 acquires information on another company (supplier, customer) related to the company to be predicted from the numerical value DB 3002, acquires the other company GHG emissions calculation formula (Formula 2) from the evaluation formula DB 4001, and thereby calculates each GHG emissions (Scope 3) of the supplier and customer related to the company to be predicted (Sl5). [Also see Figs. 10-11 showing different emission values for different manufacturing entity types]).
Regarding claim 9: Zhang / Zou teaches all the limitations of claim 7 above.
Zhang further teaches:
wherein calculating the type factor comprises: setting the type factor to a fourth value in a case where the target manufacturing entity is the first type entity; setting the type factor to a fifth value greater than the fourth value in a case where the target manufacturing entity is the second type entity; and setting the type factor to a sixth value greater than the fifth value in a case where the target manufacturing entity is the third type entity (See Zhang Formula 1 at ¶ [0054] and definitions for EF: GHG emission factor of energy type, and i: Type of energy. ¶ [0060]: Scope 1 (direct emissions) counts emissions from the energy conversion sector that directly emits GHG. Scope 2 (indirect emissions) is calculated by assigning GHG emissions to users (companies, households, etc.) who use fuel and electric power generated by direct emissions, according to the consumption of fuel and electric power. The Japanese government uses these statistics).
Regarding claim 10: Zhang / Zou teaches all the limitations of claim 4 above.
Zhang further teaches:
wherein calculating the decoupling factor comprises:
obtain a first parameter by calculating a ratio of the carbon emission change of the target manufacturing entity during the first time period relative to the second time period to a carbon emission during the second time period (See Zhang FIG. 10, S22: Calculate changes in GHG emissions [EN: first parameter] of each company [EN: target manufacturing entity];
obtain a second parameter by calculating a ratio of a gross industrial production change of the target manufacturing entity during the first time period relative to the second time period to a gross industrial production change during the second time period (Zhang ¶ [0066]: In addition, for Category 1 (purchased products and services [EN: gross industrial production]) of Scope 3, (Formula 3) is used to calculate GHG emissions resulting from products purchased by the company to be predicted from major suppliers. [Math. 3] EC(c1,t0) = Σ Sup(r,t0) * Emp(r,t0). ¶ [0071]: The input/output unit 2 inputs each piece of information on the base year and the prediction period of prediction to the processing unit 20 [EN: to calculate change or ratio between them]);
[..].
Although Zhang teaches obtaining carbon emission change and industrial production change parameters , Zhang does not specifically teach determining a ratio for a decoupling coefficient [correlation measure] between the parameters.
However, Zou in analogous art of industrial carbon emission data management teaches or suggests:
determining a decoupling coefficient based on a ratio of the first parameter to the second parameter; and setting the decoupling factor based on the decoupling coefficient (Zou ¶ [0047]: In the above steps, the enterprise-level energy reduction potential value is positively correlated [EN: decoupling factor] with the ratio of enterprise energy consumption indicators to regional energy consumption indicators, and the enterprise-level carbon emission potential value is positively correlated [EN: decoupling factor] with the ratio of enterprise carbon emission indicators to regional carbon emission indicators. The higher the enterprise-level energy reduction potential value, the larger energy reduction task assigned to the enterprise. The higher the enterprise level carbon emission reduction potential value, the larger carbon emission reduction task assigned to the enterprise. The enterprise-level assessment indicators are positively correlated to the enterprise-level energy reduction potential value).
Zou and Zhang are found as analogous art of industrial carbon emission data management. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified Zhang’s future greenhouse gas emission prediction system and method to have included Zou’s teachings around determining a ratio for a decoupling coefficient [correlation measure] between emission and production parameters. The benefit of these additional features would have achieved the effect of data interconnection among industrial entities the work efficiency of carbon allocation data modeling is improved. (Zou ¶ [0036]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by Zhang in view of Zou (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of industrial carbon emission data management. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by Zhang in view of Zou above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claim 12: Zhang / Zou teaches all the limitations of claim 4 above.
Zhang further teaches:
wherein calculating the policy factor comprises:
determining the policy factor based on a ratio of a carbon emission intensity of the target manufacturing entity during the target time period to a carbon emission intensity during the second time period, in a case that the target manufacturing entity is determined to have a carbon emission goal based on the carbon emission planning parameter (Zhang ¶ [0102]: For example, in the case of the above-mentioned hydrogen scenario, the rate-of-change calculation unit 32 calculates the rate of change in GHG emissions [EN: carbon emission intensity ratio] for each industry for each year during the prediction period in the hydrogen scenario, as shown below. [Math. 6] R(s,t) = EMS(s,t)/EMS(s,t0) [EN: policy factor]); and
setting the policy factor to 1, in a case that the target manufacturing entity is determined to not have a carbon emission goal (Zhang ¶ [0107]: FIG. 10 is a graph showing the rate of change in the GHG emissions for each industry in 2050. FIG. 10 shows, by way of example, the rate of change in GHG emissions for each industry in 2050 (value =1 in the base scenario [EN: no carbon emission goal])).
Regarding claim 13: Zhang / Zou teaches all the limitations of claim 3 above.
Zhang further teaches:
wherein calculating the first carbon emission intensity mean value of the manufacturing entity set corresponding to the historical time period comprises:
determining the first carbon emission intensity mean value based on a ratio of a sum of carbon emissions of multiple manufacturing entities in the historical carbon inventory data (Zhang ¶ [0055]: EMsl2: Total value of GHG emissions of Scope 1 (direct emissions) and Scope 2 (indirect emissions) of the company to be predicted. ¶ [0065]: Scope 1 and 2 emissions are the company's GHG emissions associated with the use of fuel, electric power, etc., while Scope 3 emissions are indirect emissions other than those of Scope 1 and 2 (emissions by other companies related to the activities of specific companies (operators)))
to a sum of [..] values of the multiple manufacturing entities during the historical time period (See Zhang Fig. 5, S18: Calculate change data (production value, GHG emissions. etc. of each industry) showing result of predicting future social change of each industry in economic model; S22: Calculate changes [EN ratios] in GHG emissions of each company [EN: target entity]. Zhang ¶ [0077]: The rate-of-change calculation unit 32 calculates a rate of change in GHG emissions of each year in each industry on the basis of the change data calculated by the social change prediction unit 31 for each year [EN: multiple time periods] during the prediction period. In addition, the rate-of-change [EN: ratio] calculation unit 32 stores data on the calculated rate of change in GHG emissions in the data storage unit 29)
Although Zhang teaches determining carbon emissions by comparing company emissions to those of other companies and summing the values, Zhang does not specifically teach summing industrial production values of the various companies.
However, Zou in analogous art of industrial carbon emission data management teaches or suggests:
[..] a sum of gross industrial production values of the multiple manufacturing entities [..] (Zou end-¶ [0046]: Regional production indicators represent the sum of production indicators of all enterprises in the specific geographical range. Regional prediction data refers to the carbon emission indicators, energy consumption indicators and economic indicators predicted to reach in the region in a certain time in future).
Zou and Zhang are found as analogous art of industrial carbon emission data management. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified Zhang’s future greenhouse gas emission prediction system and method to have included Zou’s teachings around summing industrial production values of various manufacturing companies. The benefit of these additional features would have achieved the effect of data interconnection among industrial entities the work efficiency of carbon allocation data modeling is improved. (Zou ¶ [0036]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by Zhang in view of Zou (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of industrial carbon emission data management. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by Zhang in view of Zou above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claim 14: Zhang / Zou teaches all the limitations of claim 3 above.
Zhang further teaches:
wherein calculating the second carbon emission intensity mean value of the target manufacturing entity corresponding to the historical time period comprises:
determining the second carbon emission intensity mean value based on a ratio of a sum of carbon emissions of the target manufacturing entity during the historical time period in the historical carbon inventory data (Zhang ¶ [0079]: Among them, the base year company emissions calculation unit 41 calculates GHG emissions of a predetermined company [EN: target entity] in a base year [EN: historical time period])
to a sum of [..] values of the target manufacturing entity during the historical time period (See Zhang Fig. 5, S18: Calculate change data (production value, GHG emissions. etc. of each industry) showing result of predicting future social change of each industry in economic model; S22: Calculate changes [EN ratios] in GHG emissions of each company [EN: target entity]. Zhang ¶ [0077]: The rate-of-change calculation unit 32 calculates a rate of change in GHG emissions of each year in each industry on the basis of the change data calculated by the social change prediction unit 31 for each year [EN: multiple time periods] during the prediction period. In addition, the rate-of-change [EN: ratio] calculation unit 32 stores data on the calculated rate of change in GHG emissions in the data storage unit 29).
Although Zhang teaches determining carbon emissions by comparing company emissions to other emissions of the same company summing the values, Zhang does not specifically teach summing industrial production values of the target companies.
However, Zou in analogous art of industrial carbon emission data management teaches or suggests:
[..] a sum of gross industrial production values of the target manufacturing entity [..]
(Zou end-¶ [0046]: Regional production indicators represent the sum of production indicators of all enterprises in the specific geographical range. Regional prediction data refers to the carbon emission indicators, energy consumption indicators and economic indicators predicted to reach in the region in a certain time in future).
Zou and Zhang are found as analogous art of industrial carbon emission data management. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified Zhang’s future greenhouse gas emission prediction system and method to have included Zou’s teachings around summing industrial production values of a target company. The benefit of these additional features would have achieved the effect of data interconnection among industrial entities the work efficiency of carbon allocation data modeling is improved. (Zou ¶ [0036]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by Zhang in view of Zou (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of industrial carbon emission data management. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by Zhang in view of Zou above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
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Potentially allowable subject matter
Claim 11 is dependent and overcomes prior art, with the following being Examiner’s statement of reasons for overcoming the prior art: The closest prior art is Zhang et al. US 20240296409 A1 and Zou et al. US 20230410127 A1 as mapped above. Yet, neither of Zhang, Zou, nor any other prior art on record teaches either alone or, in combination with adequate rationale, teach the mathematical relationships and numerical equivalencies as recited in dependent claim 11. Thus, dependent claim 11 is objected to as being dependent upon a rejected base claim 1 and intervening dependent claims, but would be allowable if rewritten in independent form including all of the limitations of the base claim 1 and any intervening claims.
Last but not least, the Examiner reminds Applicant that novelty (35 USC 102) and non-obviousness (35 USC 103) still pertain to features that are mostly abstract that do not render the claims patent eligible (35 USC 101). Simply said the novel and non-obviousness rationale above do not necessarily render the claims patent eligible. See for example MPEP 2106.04 I ¶5, 3rd sentence citing Mayo, 566 U.S. 71, 101 USPQ2d at 1965); Flook, 437 U.S. at 591-92, 198 USPQ2d at 198 "the novelty of the mathematical algorithm is not a determining factor at all”.
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Conclusion
The following art is made of record and considered pertinent to Applicant’s disclosure:
SAKAINO; Akira et al. US 20230081485 A1, Information processing device, information processing method and non-transitory computer-readable medium.
KOBAYASHI; Yumi et al. US 20230177536 A1, Manufacturing and sales planning support apparatus and manufacturing and sales planning support method.
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Graeber; Astrid et al. US 20220101212 A1, System and methods for greenhouse gas emission modeling and calculation to estimate the product carbon footprint.
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King; William Paul et al. US 20220214668 A1, Manufacturing and development platform.
Boardman; Paul et al. US 20230289820 A1, System and method for generating certification of greenhouse gas reduction in efficiency-optimized processes.
Davis; Robbie G. et al. US 20230350387 A1, Building management system with sustainability improvement.
Yu; Yanghao et al. US 12511660 B2, Method and apparatus for calculating carbon emission response based on carbon emission flows.
Yu; Zhi et al. CN 113095678 A. Data quality evaluation method of carbon emission quota allocation technology.
Shojaei, Tahereh, and Alireza Mokhtar. "Carbon mitigation by quota allocation." Journal of Environmental Management 304 (2022): 114097. https://www.sciencedirect.com/science/article/pii/S0301479721021599
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/REED M. BOND/Examiner, Art Unit 3624 February 26, 2026
/HAMZEH OBAID/Primary Examiner, Art Unit 3624 March 2, 2026
1 MPEP 2106.04(a): “examiners should identify at least one abstract idea grouping, but preferably identify all groupings to the extent possible”.