Carbon label-driven carbon emission reduction grading method

Abstract

The invention discloses a carbon label-driven carbon emission reduction grading method, relates to the technical field of carbon emission reduction, and solves the technical problem that product data, enterprise operation and industry emission reduction requirements cannot be effectively connected in series in the prior art. The method comprises the steps of 1, selecting a reference product for a to-be-estimated enterprise to obtain a reference carbon footprint model, and then calculating carbon footprints of other products through differences between the other products and the reference product so as to determine carbon labels of all the products; 2, determining a corresponding enterprise carbon label; 3, determining carbon emission reduction requirements of different industries; 4, determining an enterprise needing carbon emission reduction planning; 5, determining an optimal carbon emission reduction strategy of the enterprise; step 6, performing hierarchical management and control on the enterprise according to a carbon emission reduction target involved in the optimal carbon emission reduction strategy of the enterprise, and determining that the carbon emission reduction requirement is met; according to the method, the carbon footprint evaluation efficiency is effectively improved by introducing an innovative calculation method of combining a reference product with a difference threshold value.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon emission reduction, in particular to a carbon label driven carbon emission reduction grading method. BACKGROUND

[0002] Currently, the technical path in the field of carbon emission reduction mainly focuses on energy substitution, energy efficiency improvement, process innovation and carbon management. In terms of energy substitution, although renewable energy technologies such as photovoltaic and wind power have been applied on a large scale, their output is intermittent and volatile, which poses a challenge to the stable operation of the power grid. Hydrogen energy and sustainable aviation fuel, as important clean energy carriers, still need to improve the economy and technical maturity of the whole chain of preparation, storage, transportation and terminal application. In terms of industrial process emission reduction, carbon capture, utilization and storage technology is considered as a key path to deeply decarbonize industries with difficult emission reduction, but large-scale deployment currently faces core technical bottlenecks such as high energy consumption, high cost, and long-term storage safety and monitoring reliability.

[0003] In terms of accounting and management, the quantification methodology of product carbon footprint has been initially established, but there are still significant obstacles in practical application. Many existing technical methods often rely on idealized calculation models, assuming that enterprises are at a uniform operating level and technical condition, which deviates from reality and leads to deviations between carbon footprint accounting results and actual enterprise conditions. The proposed emission reduction path is also difficult to implement due to lack of feasibility. In addition, traditional carbon footprint assessment usually requires independent and complete life cycle assessment for each product, which is time-consuming and labor-intensive. When faced with a variety of products in an enterprise, the calculation cost is high and the efficiency is low, which constitutes a significant bottleneck in large-scale application. More importantly, existing solutions generally lack a systematic perspective and fail to effectively link product data, enterprise operations and industry emission reduction needs, resulting in emission reduction strategies that are often disconnected from enterprise actual capabilities, technical reserves and industry overall effort direction, making it difficult to form a scientific grading control system. SUMMARY

[0004] To solve the problems existing in the prior art, the present application provides a carbon label driven carbon emission reduction grading method, which solves the problem that the prior art fails to effectively link product data, enterprise operations and industry emission reduction needs, resulting in emission reduction strategies that are often disconnected from enterprise actual capabilities, technical reserves and industry overall effort direction, making it difficult to form a scientific grading control system.

[0005] A carbon label driven carbon emission reduction grading method, comprising the following steps:

[0006] Step 1, select an enterprise to be estimated, select a benchmark product for the enterprise to be estimated, calculate the carbon footprint of the benchmark product, establish a benchmark carbon footprint model, compare the product to be estimated with the benchmark product, obtain the difference points, import the difference points into the benchmark carbon footprint model to obtain the carbon footprint of the product to be estimated, and generate the corresponding carbon label;

[0007] Step 2, repeat step 1 until all product carbon labels of all enterprises to be estimated are obtained, based on the data collected during the calculation of the carbon footprint of all products of the enterprise to be estimated and other carbon emission related data, comb the calculation of the carbon footprint of the enterprise to be estimated, and determine the corresponding carbon label of the enterprise to be estimated according to the carbon footprint of the enterprise to be estimated;

[0008] Step 3, repeat step 2 until the carbon labels of all enterprises to be estimated are obtained, divide all enterprises to be estimated according to industry, analyze the distribution of carbon labels of enterprises in different industries, and determine the carbon emission reduction demand of the industry combined with the characteristics of the industry;

[0009] Step 4, according to the carbon emission reduction demand of the industry and the carbon label of all enterprises to be estimated, the carbon emission reduction planning enterprise is preliminarily determined;

[0010] Step 5, the product carbon emission reduction level of each carbon emission reduction planning enterprise is determined by comprehensively determining the product carbon emission reduction level of the carbon emission reduction planning enterprise, the carbon emission reduction demand of the corresponding industry, the optimization cost and optimization return of the available carbon emission reduction technology. Based on the product carbon emission reduction level, technical reserve, fund, energy price, the optimal carbon emission reduction strategy of the carbon emission reduction planning enterprise is determined based on reinforcement learning;

[0011] Step 6, according to the carbon emission reduction target involved in the optimal carbon emission reduction strategy of the enterprise, the enterprise is classified and controlled, and the enterprise meeting the carbon emission reduction requirement is determined.

[0012] Further, the step 1 comprises:

[0013] Step 1.1: calculating the product carbon footprint of the benchmark product, establishing a benchmark carbon footprint model according to the calculation result, the benchmark carbon footprint model comprising carbon footprints of different life cycle stages and total carbon footprint, the different life cycle stages comprising material preparation stage, production stage, transportation stage and use stage;

[0014] Step 1.2: comparing the product to be evaluated with the benchmark product to obtain the difference points of the product to be evaluated in different stages from the benchmark product, the difference points comprising material difference in material preparation stage, process difference in production stage, transportation difference in transportation stage and energy efficiency difference in use stage;

[0015] Step 1.3: importing the difference points into the benchmark carbon footprint model, calling the emission factor in the database to calculate the carbon footprint of the product to be evaluated, and generating the corresponding product carbon label according to the carbon footprint of the product to be evaluated.

[0016] Further, the step 1.3 comprises: calling the emission factor quick estimation difference point carbon footprint in the emission factor database, if the difference point carbon footprint reaches the threshold value, importing the benchmark carbon footprint model to calculate the carbon footprint of the product to be evaluated by the standard calculation method; thereby further improving the calculation efficiency, and the threshold value is set according to the industry standard.

[0017] Further, the difference point carbon footprint threshold value comprises a plurality of threshold values, different threshold value ranges correspond to different processing methods, and a% or b% (b>a) of the benchmark product carbon footprint is taken as the threshold base point to set the threshold interval and the corresponding processing method as follows:

[0018] The threshold value less than a% of the benchmark carbon footprint is set as a low impact threshold interval, if the difference point carbon footprint is in this interval, it can be directly ignored or qualitatively noted without adjusting the value; the threshold value greater than or equal to a% and less than b% of the benchmark carbon footprint is set as a concern threshold interval, if the difference point carbon footprint is in this interval, the quick estimation value is taken as the final difference point carbon footprint to calculate the carbon footprint of the product to be evaluated without further detailed data collection, and at the same time, the data is recorded as a quick estimation value; the threshold value greater than or equal to b% of the benchmark carbon footprint is set as an action threshold, if the difference point carbon footprint is in this interval, the standard calculation method is adopted: collecting specific data and performing accurate calculation.

[0019] Further, step 2 comprises: entering all activity data, emission factors and calculation formulas involved in the carbon footprint calculation process of all products in the carbon footprint database, and when calculating the carbon footprint of the enterprise, the corresponding data is integrated and calculated to generate a report to obtain the carbon footprint of the enterprise by using professional carbon accounting software or an automatic calculation template based on Excel / database development, and the corresponding enterprise carbon label is generated according to the carbon footprint of the enterprise to be evaluated.

[0020] Further, the different industries in step 3 comprise high energy consumption industries, clean energy industries, consumer product industries, transportation industries, and emerging industries.

[0021] Further, step 4 comprises: after determining the carbon emission reduction demand of different industries in step 3, combining the technical status and implementation cost estimation of the industry to determine the priority of the carbon emission reduction demand, and then combining the enterprise carbon label obtained in step 2 to sort the enterprises for carbon emission reduction, and selecting the carbon emission reduction planning enterprise from the sorted enterprises to be evaluated. The specific selection method is to take the top n% in the ranking as the carbon emission reduction planning object.

[0022] Further, step 4 comprises:

[0023] Step 4.1: Conduct a technology status assessment, investigate the current applicable carbon reduction technologies for each target industry, obtain the technology maturity level, existing popularity, and future improvement potential of each technology, and establish an industry-level carbon reduction technology database;

[0024] Step 4.2: Perform cost estimation, collect and calculate the initial investment cost, operation and maintenance cost, and financing related cost required for each carbon reduction technology, based on the cost data, quantify the comprehensive implementation cost corresponding to the unit carbon dioxide equivalent (tCO2e) reduction;

[0025] Step 4.3: Determine the industry reduction priority, use multi-criteria decision analysis method, combine the technology status information obtained in step 4.1 and the cost estimation results in step 4.2, score and sort the carbon reduction demand urgency of each industry, generate the industry carbon reduction priority sequence;

[0026] Step 4.4: Implement enterprise sorting, first sort the enterprises according to the carbon emission level marked in the carbon label corresponding to each enterprise in the same industry, where the enterprises with lower carbon emission level are given priority; then adjust the preliminary sorting result according to the industry carbon reduction priority sequence and the main carbon emission source category identified in the enterprise carbon label, output the final enterprise carbon reduction action priority ranking, the specific formula for dynamic adjustment is:

[0027]

[0028] The comprehensive score of the i-th enterprise is, The carbon emission level value of the i-th enterprise is, The industry reduction demand priority weight corresponding to the main carbon emission source of the i-th enterprise is;

[0029] The calculation process of the industry reduction demand priority weight includes: determining the industry carbon reduction demand closest to the main carbon emission source in the enterprise carbon label, and determining its corresponding priority, and determining the corresponding weight according to the priority;

[0030] Then generate a comprehensive ranking list of all enterprises according to the enterprise comprehensive score, from high to low, indicating the reduction urgency.

[0031] Step 4.5: Confirm the planning object, extract the top n% enterprises from the ranking list to form the carbon reduction planning object list.

[0032] Further, the determination of the product carbon reduction level in step 5 includes: using comprehensive scoring method to calculate the carbon reduction potential score of each product, the formula is as follows:

[0033]

[0034] wherein, is the carbon emission reduction potential score of the jth product of the ith enterprise, is the industry emission reduction demand priority weight corresponding to the jth product of the ith enterprise, is the product carbon label value corresponding to the jth product of the ith enterprise, is the return cost ratio corresponding to the jth product of the ith enterprise, and the formula is as follows:

[0035]

[0036] wherein, is the optimal return corresponding to the jth product of the ith enterprise, is the optimal cost corresponding to the jth product of the ith enterprise;

[0037] According to the emission reduction potential scores of all products, a grading threshold is determined to further determine the carbon emission reduction grade of each product.

[0038] Further, the determination of the optimal carbon emission reduction strategy of the enterprise in step 5 includes:

[0039] Setting a state space: defining environmental state variables, including: product carbon emission reduction grade, technology reserve, fund, energy price and other factors;

[0040] Setting an action space: defining the emission reduction actions that can be taken by the enterprise, including: investing in new technology, process optimization, carbon offset, product adjustment;

[0041] Setting a reward function: designing to maximize long-term net income or minimize total cost;

[0042] According to the set state space, action space and reward function, reinforcement learning optimization is performed to determine the output of the optimal carbon emission reduction strategy of the enterprise.

[0043] The beneficial effects of the present application include:

[0044] Firstly, by introducing the innovative calculation method of benchmark product combined with difference threshold, the efficiency of carbon footprint assessment is effectively improved. The repetitive and tedious calculation for a large number of products is avoided, and the product carbon label can be quickly generated under the premise of ensuring data accuracy and comparability, and the enterprise carbon label is obtained, which provides an efficient data basis for subsequent analysis, making it possible to conduct large-scale and full-industry carbon footprint investigation.

[0045] Secondly, the application constructs a closed-loop decision mechanism from micro-product to enterprise to macro-industry carbon emission reduction demand, and then from macro-industry carbon emission reduction demand to determine the micro-product adjustment priority feedback macro. Both the overall emission reduction demand at the industry level and the specific product structure, financial situation, technical ability and even external energy price of the enterprise are considered, and the reinforcement learning algorithm is used to optimize under multiple constraints, so as to tailor the optimal emission reduction strategy with ambition and reality for the enterprise, greatly improving the acceptance and executability of the strategy.

[0046] Finally, the application links the final carbon emission reduction target with enterprise grading management, and establishes a dynamic and scientific management system. This not only ensures that the emission reduction pressure can be accurately transmitted to the enterprises that need to take measures the most, but also gives greater development space to the enterprises that meet the standards, thereby systematically promoting the green and low-carbon transformation of the entire industry in the most cost-effective way, and contributing to the actual value of achieving broader climate goals. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 A carbon label driven carbon emission reduction grading method related to an embodiment of the application is shown in the flowchart. DETAILED DESCRIPTION

[0048] To make the purpose, technical solutions and advantages of the embodiments of the application clearer, the technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all embodiments of the application. Therefore, the detailed description of the embodiments of the application provided in the following drawings is not intended to limit the scope of the claimed application, but only to represent selected embodiments of the application. Based on the embodiments of the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0049] Embodiment 1

[0050] The following will be described in conjunction with the drawings Figure 1 The specific embodiments of the application will be described in detail;

[0051] A carbon label driven carbon emission reduction grading method, comprising the following steps:

[0052] Step 1, selecting a to-be-evaluated enterprise, selecting a benchmark product for the to-be-evaluated enterprise, calculating the carbon footprint of the benchmark product, establishing a benchmark carbon footprint model, comparing the to-be-evaluated product with the benchmark product, obtaining the difference points, importing the difference points into the benchmark carbon footprint model to obtain the carbon footprint of the to-be-evaluated product, and generating a corresponding carbon label;

[0053] The specific to-be-evaluated enterprise determination method comprises: setting a carbon emission level value according to a national carbon emission standard, and determining an enterprise with a carbon emission level greater than or equal to a carbon emission level threshold as a to-be-evaluated enterprise that needs to be optimized for carbon emission reduction;

[0054] Step 2, repeat step 1 until all product carbon labels of all to-be-evaluated enterprises are obtained, comb the carbon footprint of the to-be-evaluated enterprise based on the data collected in the calculation process of the carbon footprint of the to-be-evaluated enterprise and other carbon emission related data, and determine the carbon label of the to-be-evaluated enterprise according to the carbon footprint of the to-be-evaluated enterprise;

[0055] Step 3, repeat step 2 until the carbon labels of all to-be-evaluated enterprises are obtained, divide all to-be-evaluated enterprises according to industries, analyze the distribution of carbon labels of enterprises in different industries, and determine the carbon emission reduction demand of the industry in combination with the characteristics of the industry;

[0056] Step 4, determine the carbon emission reduction planning enterprise according to the carbon emission reduction demand of the industry and the carbon labels of all to-be-evaluated enterprises;

[0057] Step 5, determine the product carbon emission reduction level of each carbon emission reduction planning enterprise by comprehensively determining the product carbon emission reduction level of each carbon emission reduction planning enterprise according to the product carbon emission reduction level of the carbon emission reduction planning enterprise, the carbon emission reduction demand of the corresponding industry, the optimization cost and the optimization return of the available carbon emission reduction technology, and determine the current optimal carbon emission reduction strategy of the carbon emission reduction planning enterprise based on reinforcement learning according to the product carbon emission reduction level, the technical reserve, the fund and the energy price;

[0058] Step 6, grade and control the enterprise according to the carbon emission reduction target involved in the optimal carbon emission reduction strategy of the enterprise, and determine whether the carbon emission reduction requirement is met.

[0059] In another embodiment, the step 1 comprises:

[0060] Step 1.1: The reference product is a product with the largest carbon footprint in the to-be-evaluated enterprise after being estimated by using the available carbon footprint data and enterprise production and sales data, a detailed product carbon footprint calculation is performed on the reference product according to the international standard “PAS2050-2011 Specification for the Assessment of Greenhouse Gas Emissions from Goods and Services”, a reference carbon footprint model is obtained, the reference carbon footprint model comprises carbon footprints in different life cycle stages and a total carbon footprint, and the different life cycle stages comprise a material preparation stage, a production stage, a transportation stage and a use stage.

[0061] Step 1.2: Compare the to-be-evaluated product with the reference product, and obtain difference points in different stages of the life cycle of the to-be-evaluated product from the reference product, the difference points comprise material differences in the material preparation stage, process differences in the production stage, transportation differences in the transportation stage and energy efficiency differences in the use stage.

[0062] Specifically, taking manufacturing as an example, material difference, which may be increased by a certain component, reduced weight, replaced material; process difference, which may be increased or decreased by a processing procedure; transportation difference, which may be caused by the change of transportation distance and mode due to different sales destinations; energy efficiency difference, which may be caused by the change of energy consumption in the product use stage.

[0063] Taking service industry as an example, material difference, which may be caused by the need for more delicate services to increase additional consumables; process difference, which may be caused by the need for additional value-added services to increase the use of certain tools or electronic equipment; transportation difference, which may be caused by the transportation of service customers or additional materials required by the service.

[0064] Step 1.3: Introducing the difference point into the reference carbon footprint model, calling the emission factor in the database to calculate the carbon footprint of the difference point to obtain the carbon footprint of the product to be evaluated, and generating the corresponding product carbon label according to the carbon footprint of the product to be evaluated.

[0065] In another embodiment, the step 1.3 includes: calling the emission factor in the emission factor database to quickly estimate the carbon footprint of the difference point, and if the carbon footprint of the difference point reaches a threshold, introducing the reference carbon footprint model to accurately calculate the carbon footprint of the product to be evaluated by a standard calculation method; thereby further improving the calculation efficiency.

[0066] Specifically, the emission factor database finds the corresponding emission factor for various energy and materials collected and preprocessed in advance.

[0067] Specifically, the quick estimation refers to direct calculation based on the difference point value and the corresponding emission factor.

[0068] For example, taking product A as the reference product, the full life cycle carbon footprint is 100 kg CO2e, and product B as the product to be evaluated; the difference between the two is as follows:

[0069] Difference 1: product B is 0.5 kg heavier than product A, which increases 0.5 kg of steel; calling the steel emission factor (2.5 kg CO2e / kg) in the database, the increment is calculated as: 0.5 kg * 2.5 kg CO2e / kg = 1.25 kg CO2e.

[0070] Difference 2: product B has energy efficiency improvement, and the annual power consumption is reduced by 10 kWh; calling the grid power emission factor (0.5 kg CO2e / kWh), the decrement is calculated as: -10 kWh * 0.5 kg CO2e / kWh = -5 kg CO2e.

[0071] The carbon footprint of new product B = 100 + 1.25 - 5 = 96.25 kg CO2e.

[0072] This method avoids repeated calculation of all unchanged parts, reduces the amount of calculation, and is more conducive to application and promotion.

[0073] In another embodiment, the difference point carbon footprint threshold includes multiple thresholds, different threshold ranges correspond to different processing methods, so as to ensure that resources are invested in the most influential places while ensuring that moderate changes are quantitatively considered rather than simply discarded.

[0074] Based on the international standard "PAS2050-2011 Life Cycle Assessment of Greenhouse Gas Emissions from Products and Services", 1% or 5% of the baseline product carbon footprint is taken as the threshold point, and the threshold interval and the corresponding processing method are set as follows:

[0075] Set less than 1% of the baseline carbon footprint as the low-impact threshold interval. If the difference point carbon footprint is in this interval, it can be directly ignored or qualitatively noted without adjusting the value; set greater than or equal to 1% and less than 5% of the baseline carbon footprint as the attention threshold interval. If the difference point carbon footprint is in this interval, the quick estimate value is taken as the final difference point carbon footprint for calculating the carbon footprint of the product to be evaluated without further detailed data collection. At the same time, record the quick estimate value; set greater than or equal to 5% of the baseline carbon footprint as the action threshold. If the difference point carbon footprint is in this interval, the standard calculation method is used: collect specific data and perform accurate accounting.

[0076] Specifically, the baseline product carbon footprint of the baseline product A is 100 kg CO2e, so 1% of the baseline product carbon footprint is 1 kg CO2e and 5% is 5 kg CO2e. At this time, if product B replaces a small screw compared to product A, it only causes a change of 0.2 kg CO2e. 0.2 < 1, i.e. in the low-impact threshold interval, the difference is not significant and can be ignored.

[0077] If the increment of product B compared to product A is 1.25 kg CO2e, 1 < 1.25 < 5, there is a certain difference, and the difference point carbon footprint obtained by preliminary estimation can be taken as the final difference point carbon footprint for calculating the carbon footprint of the product to be evaluated.

[0078] If the increment of product B compared to product A is 6 kg CO2e): 6 > 5, the difference is significant, and the difference point needs to be introduced into the baseline carbon footprint model for accurate accounting of the carbon footprint of the product to be evaluated by the standard calculation method.

[0079] The setting of multiple thresholds ensures that resources are invested in the most influential places while ensuring that moderate changes are quantitatively considered rather than simply discarded.

[0080] In another embodiment, step 2 comprises: inputting the activity data, emission factors, calculation formula involved in the process of calculating the carbon footprint of all products in the enterprise to be evaluated into the carbon footprint database, when calculating the carbon footprint of the enterprise, automatically calling the corresponding data for integration and calculation to generate a report to obtain the carbon footprint of the enterprise by professional carbon accounting software or an automatic calculation template based on Excel / database development, and generating the corresponding enterprise carbon label according to the carbon footprint of the enterprise to be evaluated.

[0081] The specific integration calculation process includes:

[0082] Integration range 1 includes: checking the fuel purchase records and inventory records of the entire enterprise's financial or energy department, and integrating and calculating the fuel combustion, industrial production process and fugitive emissions of the enterprise's own facilities; for example, how many liters of diesel and how many cubic meters of natural gas are consumed by the enterprise in a year;

[0083] The integration formula is: Σ (fuel or material consumption × corresponding emission factor)

[0084] Integration range 2 includes: obtaining the electricity consumption (kWh) on the total electricity bill of the enterprise in a year, and the data on the total steam / heat purchase documents to determine the consumption of purchased electricity, heat and steam by the enterprise.

[0085] The integration formula is: Σ (purchased electricity / heat quantity × corresponding emission factor)

[0086] Integration range 3 includes: obtaining the emissions of upstream and downstream, such as purchased raw materials, outsourcing processing, employee travel, waste disposal, etc. For the carbon emissions of upstream raw materials, obtain the upstream emission part of raw materials in the carbon footprint of all products from the carbon footprint database, and then scale up and adjust according to the total annual procurement amount or total procurement quantity of the enterprise, such as using the expenditure method: total expenditure of the enterprise in a year in a certain category (such as raw materials, travel) × average carbon emission factor of the industry (yuan / ton CO2e). Other categories, such as employee commuting and waste disposal, are obtained from the corresponding data sources.

[0087] Finally, the enterprise carbon label includes the carbon emission level and the main source of carbon emissions of the enterprise. The carbon emission level is usually represented by a numerical value or a level, such as A-J level, where A level represents low carbon and J level represents high carbon, with each level increasing.

[0088] In another embodiment, the different industries in step 3 are classified according to China's industry classification standard, i.e. "Classification of National Economic Industries" (GB / T 4754-2017), which systematically classifies and codes all social economic activities. Based on the carbon emissions and characteristics of different industries, different industries are classified into high energy consumption industries, clean energy industries, consumer goods industries, transportation industries, and emerging industries. Specifically:

[0089] 1. High energy consumption industries refer to industries with intensive energy consumption and high carbon emissions, mainly involving mining, raw material processing and heavy industry. For example, ferrous metal smelting and rolling processing industry, chemical raw material and chemical product manufacturing industry, the corresponding carbon label may tend to disclose the energy structure, such as the proportion of coal power or green energy, CCUS project emission reduction, such as the annual CO2 storage of ten thousand tons, process substitution progress, such as the proportion of hydrogen reduction.

[0090] The corresponding carbon emission reduction demand may involve: process innovation, such as popularizing hydrogen metallurgy and CCUS (carbon capture and storage) technology, with the goal of reducing carbon emissions per ton of steel; energy substitution, such as increasing the proportion of green electricity, building wind and solar power stations or participating in green electricity transactions.

[0091] 2. Clean energy industry refers to industries engaged in renewable energy, nuclear energy and clean energy production and supply, with low or zero carbon emissions. For example, solar power generation, wind power generation, the corresponding carbon label may tend to quantify energy recovery period, material recycling rate, such as glass, aluminum frame recycling rate, emission reduction brought by technology iteration, such as GW components reducing CO2 emission by 1 million tons per year.

[0092] The corresponding carbon emission reduction demand may involve: low carbonization of the whole industry chain, such as reducing the power consumption of polycrystalline silicon production and improving the coverage rate of component recycling system; technology upgrading.

[0093] 3. Consumer goods industry refers to industries that directly provide goods and services to consumers, involving daily life product manufacturing and sales. For example, food manufacturing industry, textile industry, the corresponding carbon label may tend to disclose transportation carbon emissions, packaging material carbon footprint, consumer behavior influence.

[0094] The corresponding carbon emission reduction demand may involve: supply chain optimization, such as shortening the transportation range of dairy cold chain or adopting bio-based packaging; consumer end guidance: promoting low-carbon consumer behavior, such as encouraging old clothes recycling and reducing food waste, etc.

[0095] 4. Transportation industry refers to industries engaged in freight and passenger transportation, warehousing and postal services. For example, air transportation industry, water transportation industry, the corresponding carbon label may tend to disclose fuel type, operation efficiency improvement, such as unit freight turnover emission reduction ratio, alternative fuel research and development progress.

[0096] Corresponding carbon reduction requirements may involve: fuel transformation, such as increasing the proportion of sustainable aviation fuel blending in the aviation industry, promoting green methanol and ammonia fuel in the shipping industry; operation optimization, such as reducing the speed of ships to reduce fuel consumption, and optimizing the flight path of aircraft.

[0097] 5. Emerging industries refer to high-tech industries and modern service industries with new technologies and new formats as the core, with innovation and growth potential. For example, Internet and related services, computer, communication and other electronic equipment manufacturing industries, the corresponding carbon labels may tend to: raw material sources such as green electricity smelting aluminum, product energy efficiency levels such as ENERGY STAR certification, circular economy contribution such as old equipment renovation and recycling rate;

[0098] Corresponding carbon reduction requirements may involve: material innovation, such as developing rare earth-free permanent magnets and biodegradable electronic packaging materials to reduce dependence on high-carbon raw materials; energy efficiency improvement, such as reducing data center PUE and improving AI chip power consumption ratio.

[0099] In another embodiment, step 4 includes: after determining the carbon reduction requirements of different industries in step 3, combining the technical status and implementation cost estimation of the industry to determine the priority of carbon reduction requirements, and then combining the enterprise carbon labels obtained in step 2 to sort the enterprises for carbon reduction. The top n% in the ranking are the carbon reduction planning objects.

[0100] Specifically, the technical status evaluation: for each industry, investigate available carbon reduction technologies, evaluate their technical maturity, popularity and improvement potential. For example, renewable energy technologies are relatively mature in the power industry, while CCUS is still in the demonstration stage in the industrial industry. Analyze the barriers to technology diffusion, such as infrastructure requirements, technology transfer difficulties, etc.

[0101] Among them, the technical maturity is evaluated by the technology readiness level (TRL), and the technical maturity is divided into 1-9 levels;

[0102] The evaluation dimensions of popularity include market penetration indicators, regional distribution analysis, and industry chain maturity;

[0103] The evaluation dimensions of improvement potential include performance improvement potential, cost reduction potential, iteration and integration potential, and resource and environmental constraints;

[0104] Implementation cost estimation: calculate the cost of implementing emission reduction technologies, including initial investment, operation and maintenance cost, financing cost, etc. Use cost-benefit analysis (CBA) or levelized carbon abatement cost (LCOA) to quantify the cost of reducing one ton of CO2. Consider external costs such as environmental benefits and social costs, which can also be converted using carbon pricing (carbon tax or carbon trading price).

[0105] The estimation process includes: listing all cost items of initial investment, operation and maintenance, and financing, assigning values to each cost item through channels such as supplier quotes, historical data, industry databases, etc., building a life cycle cost model in a spreadsheet, incorporating time factors and discount rates, and deriving LCOA, NPV, payback period, etc., testing the impact of changes in key variables (such as energy prices, carbon prices, interest rates) on the results.

[0106] Determine industry emission reduction priority: use multi-criteria decision analysis method, combined with technology status information and cost estimation results, score and sort the carbon emission reduction demand urgency of each industry, generate industry carbon emission reduction priority sequence;

[0107] Implement enterprise ranking, first according to the carbon emission level marked in the carbon label corresponding to each enterprise in the same industry, preliminarily sort the enterprises, and the enterprises with lower carbon emission level are ranked first; then according to the industry carbon emission reduction priority sequence and combined with the main carbon emission source category identified in the enterprise carbon label, dynamically adjust the preliminary sorting result, output the final enterprise carbon emission reduction action priority ranking, and the specific formula for dynamic adjustment is:

[0108]

[0109] The comprehensive score of the i-th enterprise is, The carbon emission level value of the i-th enterprise is, The industry emission reduction demand priority weight corresponding to the main carbon emission source of the i-th enterprise; the carbon emission level value is determined according to the carbon emission level, and in this embodiment, the And The integer is 1-10.

[0110] The calculation process of the industry emission reduction demand priority weight includes: determining the industry carbon emission reduction demand closest to the main carbon emission source in the enterprise carbon label, and determining its corresponding priority, and determining the corresponding weight according to the priority, such as the high priority weight interval is 8-10, the general priority weight interval is 4-7, and the low priority weight interval is 1-3, and the specific value is determined according to the division granularity of the corresponding priority.

[0111] Then generate a comprehensive ranking list of all enterprises according to the enterprise comprehensive score, from high to low, indicating the urgency of emission reduction.

[0112] Select threshold n%: determine n value according to resource constraints (such as funds, regulatory capacity). For example, n=10% means selecting the top 10% of enterprises as the focus. The n value can be determined by stakeholder consultation or optimization model.

[0113] Confirm the planning object: Extract the top n% enterprises from the ranking list to form the carbon emission reduction planning object list.

[0114] In another embodiment, the step 5 comprises:

[0115] Step 5.1: Determine the product carbon emission reduction level based on industry carbon emission reduction demand, product carbon label, optimization cost, and return.

[0116] The input data includes industry carbon emission reduction demand, product carbon label, optimization cost, and optimization return.

[0117] The industry carbon emission reduction demand includes industry emission reduction targets and priorities; the optimization cost is the optimization cost required to reduce product carbon footprint, including technology improvement cost, material substitution cost, certification cost, etc., calculated using life cycle cost analysis (LCCA); the optimization return includes the benefits brought by reducing product carbon footprint, such as energy saving, carbon credit income, market competitiveness improvement, etc., quantified as financial return or non-financial benefits.

[0118] The determination of product carbon emission reduction level includes: using comprehensive scoring method to calculate the carbon emission reduction potential score of each product, the formula is as follows:

[0119]

[0120] Wherein, is the carbon emission reduction potential score of the jth product of the ith enterprise, is the industry emission reduction demand priority weight corresponding to the jth product of the ith enterprise, is the product carbon label value corresponding to the jth product of the ith enterprise, is the return cost ratio corresponding to the jth product of the ith enterprise, the formula is as follows:

[0121]

[0122] Wherein, is the optimization return corresponding to the jth product of the ith enterprise, is the optimization cost corresponding to the jth product of the ith enterprise.

[0123] According to the emission reduction potential scores of all products, determine the grading threshold to further determine the carbon emission reduction level of each product.

[0124] According to the scores, products are divided into different levels (such as 1-5 levels, 1 level indicating the most urgent emission reduction). Products with high level indicate high urgency and high economic efficiency.

[0125] Output the product carbon emission reduction level list to guide the emission reduction decision-making within the enterprise.

[0126] Step 5.2: Determine the optimal carbon reduction strategy for the enterprise based on product carbon reduction levels, technology reserves, funding, energy prices, and other factors using reinforcement learning. Specifically:

[0127] Set state space: Define environmental state variables, including product carbon reduction levels, technology reserves, funding, energy prices, and other factors. Among them, product carbon reduction levels represent internal reduction demand; technology reserves refer to existing technical capabilities, such as energy efficiency technology and renewable energy equipment, represented by numerical values or levels; funding refers to the level of available funds, including cash flow and financing capacity; energy prices include electricity and fossil fuel prices, affecting operating costs; other factors include market demand, competitor actions, etc.

[0128] Set action space: Define the actions the enterprise can take to reduce emissions, including investing in new technology, purchasing energy-efficient equipment, introducing clean energy, installing solar panels, optimizing processes, reducing waste, purchasing carbon credits, participating in carbon trading, adjusting products, switching to low-carbon raw materials, and developing low-carbon products.

[0129] Set reward function: Design to maximize long-term net income or minimize total cost. The reward function is:

[0130] Reward = (Carbon reduction revenue + cost savings + policy rewards) - (investment costs + operating costs)

[0131] Where carbon reduction revenue includes carbon trading income and avoided carbon tax; cost savings include energy efficiency improvements; policy rewards include subsidies or tax deductions.

[0132] Consider a time discount factor to reflect the present value of future income.

[0133] Reinforcement learning process:

[0134] Choose a deep Q network (DQN) suitable for continuous state and action space, and the training process includes:

[0135] Initialization: Random policy or based on historical data.

[0136] Interaction: Simulate the interaction between the enterprise and the environment (policy, market), execute actions, observe new states and rewards.

[0137] Update: Through trial and error learning, adjust the strategy to maximize cumulative rewards. Training data can come from historical cases or simulation generation.

[0138] Convergence: Stop when the strategy is stable or the maximum number of iterations is reached.

[0139] Output optimal strategy: Reinforcement learning model recommends a series of actions, such as investing in energy efficiency technology in the first year, participating in carbon trading in the second year, and considering dynamic factors such as policy changes and energy price fluctuations. The specific strategy output is in the form of a timeline and corresponding resource allocation plan.

[0140] In another embodiment, step 6 includes setting carbon reduction targets for different periods according to the enterprise's optimal carbon reduction strategy, grading and controlling the enterprise according to the carbon reduction targets, and determining whether it meets the carbon reduction requirements.

[0141] The enterprise formulates detailed plans according to the recommended strategy and sets KPIs (such as emission reduction and cost); continuously monitors environmental changes and adjusts the strategy using the reinforcement learning model to achieve adaptive management. Through industry demand analysis and technical and economic evaluation, the key enterprises for carbon reduction are systematically identified, ensuring that the focus is on enterprises with large potential for emission reduction and low cost.

[0142] Specifically, the grading management of enterprises in different industries is shown in Table 1:

[0143] Table 1 Grading management example 1

[0144]

[0145] Among them, enterprise A, as a steel enterprise in the black metal smelting and rolling industry, upgrades the blast furnace coal gas recovery system in the first year, sets a carbon reduction target of 50.6 tons of CO2e / year, adopts intelligent scheduling optimization strategy in the second year, sets a carbon reduction target of 32.5 tons of CO2e / year, and adopts carbon market quota trading in the third year, sets a carbon reduction target of 23.1 tons of CO2e / year;

[0146] Enterprise B, as an aviation transportation enterprise in the transportation industry, optimizes the flight operation plan in the first year, sets a carbon reduction target of 18.8 tons of CO2e / year, promotes the use of sustainable aviation fuel in the second year, sets a carbon reduction target of 35.2 tons of CO2e / year, and adopts a more efficient engine in the third year, sets a carbon reduction target of 40.4 tons of CO2e / year;

[0147] Enterprise C, as a solar power generation enterprise in the clean energy industry, upgrades photovoltaic cell technology in the first year, sets a carbon reduction target of 34.2 tons of CO2e / year, optimizes operation and maintenance management and equipment upgrade in the second year, sets a carbon reduction target of 22.1 tons of CO2e / year, and increases the installed capacity in the third year, sets a carbon reduction target of 16.4 tons of CO2e / year;

[0148] Based on the relative situation of the carbon emission reduction target of each enterprise, the classification is adjusted in real time. In the first year, the carbon emission reduction target of enterprise A accounts for the top 30% of all carbon emission reduction targets in the year, so it is classified as level 1 management, the carbon emission reduction target of enterprise C accounts for 30%-70% of all carbon emission reduction targets in the year, so it is classified as level 2 management, and the carbon emission reduction target of enterprise B accounts for the last 30% of all carbon emission reduction targets in the year, so it is classified as level 3 management. Similarly, in the second year, enterprise B is classified as level 1 management, enterprise A is classified as level 2 management, and enterprise C is classified as level 3 management. In the third year, enterprise B is classified as level 1 management, enterprise A is classified as level 2 management, and enterprise C is classified as level 3 management.

[0149] In another embodiment, the difference from the previous embodiment is that the classification of the carbon emission reduction target of the enterprise is different, as shown in Table 2.

[0150] Table 2: Classification management example 2

[0151]

[0152] Based on the threshold interval in which the carbon emission reduction target of each enterprise is located, the classification is adjusted in real time. In the first year, the carbon emission reduction target of enterprise A is in the first interval [4-6], so it is classified as level 1 management, the carbon emission reduction target of enterprise B is in the third interval [0-2), so it is classified as level 3 management, and the carbon emission reduction target of enterprise C is in the second interval [2-4), so it is classified as level 2 management. Similarly, in the second year, enterprise A is classified as level 2 management, enterprise B is classified as level 2 management, and enterprise C is classified as level 2 management. In the third year, enterprise A is classified as level 2 management, enterprise B is classified as level 1 management, and enterprise C is classified as level 3 management.

[0153] The above two embodiments mainly illustrate a dynamic classification idea, and the specific classification method and classification parameter value can be determined according to the supervision ability, the number of enterprises participating in classification, and the distribution of carbon emission reduction targets.

[0154] The above-described embodiments only express the specific implementation of the present application, and the description is more specific and detailed, but it cannot be understood as a limitation on the protection scope of the present application. It should be noted that for ordinary skilled persons in the art, without departing from the technical concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application.

Claims

1. A carbon label driven carbon emission reduction grading method, characterized in that, The method comprises the following steps: Step 1: selecting an enterprise to be evaluated, selecting a benchmark product for the enterprise to be evaluated, calculating the carbon footprint of the benchmark product, establishing a benchmark carbon footprint model, comparing the product to be evaluated with the benchmark product, obtaining the difference points, importing the difference points into the benchmark carbon footprint model to obtain the carbon footprint of the product to be evaluated, and generating the corresponding carbon label; Step 2: repeating step 1 until all product carbon labels of all enterprises to be evaluated are obtained, combing the data collected during the calculation of the carbon footprint of the enterprise to be evaluated and other carbon emission related data to calculate the carbon footprint of the enterprise to be evaluated, and determining the corresponding carbon label of the enterprise to be evaluated according to the carbon footprint of the enterprise to be evaluated; Step 3: repeating step 2 until the carbon labels of all enterprises to be evaluated are obtained, dividing all enterprises to be evaluated according to industries, analyzing the distribution of carbon labels of enterprises in different industries, and combining with the characteristics of the industries to determine the carbon emission reduction demand of the industries; Step 4: preliminarily determining the carbon emission reduction planning enterprises according to the carbon emission reduction demand of the industries and the carbon labels of all enterprises to be evaluated; Step 5: determining the product carbon emission reduction level of each carbon emission reduction planning enterprise by comprehensively determining the product carbon label of the carbon emission reduction planning enterprise, the carbon emission reduction demand of the corresponding industry, the optimization cost and optimization return of the available carbon emission reduction technology, and determining the current optimal carbon emission reduction strategy of the carbon emission reduction planning enterprise based on reinforcement learning according to the product carbon emission reduction level, technical reserves, funds and energy prices; Step 6: classifying and controlling the enterprises according to the carbon emission reduction targets involved in the optimal carbon emission reduction strategy of the enterprises, and determining the enterprises meeting the carbon emission reduction requirements.

2. A carbon label driven carbon abatement grading method according to claim 1, characterized in that, The step 1 comprises: Step 1.1: calculating the product carbon footprint of the benchmark product, establishing a benchmark carbon footprint model according to the calculation results, wherein the benchmark carbon footprint model comprises carbon footprints of different life cycle stages and total carbon footprint, and the different life cycle stages comprise a material preparation stage, a production stage, a transportation stage and a use stage; Step 1.2: comparing the product to be evaluated with the benchmark product to obtain the difference points of the product to be evaluated in different stages from the benchmark product, wherein the difference points comprise material differences in the material preparation stage, process differences in the production stage, transportation differences in the transportation stage and energy efficiency differences in the use stage; Step 1.3: importing the difference points into the benchmark carbon footprint model, calling the emission factors in the database to calculate the carbon footprint of the product to be evaluated, and generating the corresponding product carbon label according to the carbon footprint of the product to be evaluated.

3. A carbon label driven carbon abatement grading method according to claim 2, wherein, The step 1.3 comprises: calling the emission factors in the emission factor database to quickly estimate the carbon footprint of the difference points, and if the carbon footprint of the difference points reaches a threshold, importing the benchmark carbon footprint model to calculate the carbon footprint of the product to be evaluated by a standard calculation method.

4. A carbon label driven carbon abatement grading method according to claim 3, wherein, The threshold values of the carbon footprint of the difference points comprise a plurality of threshold value ranges, different threshold value ranges correspond to different processing methods, and a% or b%(b>a) of the carbon footprint of the benchmark product is taken as a threshold base point, and the threshold value range and the corresponding processing method are set as follows: Setting less than a% baseline carbon footprint as a low impact threshold interval, if the difference point carbon footprint is in this interval, it is directly ignored or made a qualitative note without adjusting the value; setting greater than or equal to a% and less than b% baseline carbon footprint as a threshold interval of concern, if the difference point carbon footprint is in this interval, it is not directly ignored, but the quick estimate value is taken as the final difference point carbon footprint to calculate the carbon footprint of the product to be evaluated, at the same time, the data is recorded as a quick estimate value; setting greater than or equal to b% baseline carbon footprint as an action threshold, if the difference point carbon footprint is in this interval, the standard calculation method is adopted: collecting data and accounting.

5. The carbon label driven carbon emission reduction classification method according to claim 1, wherein, Step 2 includes: entering the activity data, emission factors and calculation formula involved in the carbon footprint calculation process of all products in the enterprise to be estimated into the carbon footprint database, calling the corresponding data to integrate and calculate to generate a report to obtain the carbon footprint of the enterprise according to the organization boundary and accounting boundary, and generating the corresponding enterprise carbon label according to the carbon footprint of the enterprise to be estimated.

6. A carbon label driven carbon abatement grading method according to claim 1, wherein, The different industries in step 3 are high energy consumption industries, clean energy industries, consumer product industries, transportation industries, and emerging industries.

7. A carbon label driven carbon abatement grading method according to claim 1, wherein, Step 4 includes: after determining the carbon emission reduction demand of different industries in step 3, combining the technical status and implementation cost estimation of the industry to determine the priority of the carbon emission reduction demand, and then sorting the carbon emission reduction of the enterprise to be estimated according to the enterprise carbon label obtained in step 2, and selecting a carbon emission reduction planning enterprise from the sorted enterprise to be estimated.

8. The carbon label driven carbon emission reduction classification method of claim 1, wherein, Step 4 includes: Step 4.1: technical status evaluation, for each target industry, research the currently applicable carbon emission reduction technologies, obtain the technical maturity level, existing popularity and future improvement potential of each technology, and establish an industry-level carbon emission reduction technology database; Step 4.2: cost estimation, for each carbon emission reduction technology, collect and calculate the initial investment cost, operation and maintenance cost and financing related cost required for its implementation, and based on the cost data, quantify the comprehensive implementation cost corresponding to the unit carbon dioxide equivalent (tCO2e) emission reduction; Step 4.3: determine the industry emission reduction priority, use multi-criteria decision analysis method, combine the technical status information obtained in step 4.1 and the cost estimation results obtained in step 4.2, score and sort the carbon emission reduction demand urgency of each industry, and generate an industry carbon emission reduction priority sequence; Step 4.4: enterprise sorting, first, according to the carbon emission level marked in the carbon label corresponding to each enterprise to be estimated in the same industry, the enterprises are preliminarily sorted, and the enterprises with lower carbon emission level are given priority; then, according to the industry carbon emission reduction priority sequence and combining the main carbon emission source category identified in the carbon label of the enterprise to be estimated, the preliminary sorting result is dynamically adjusted, and the final carbon emission reduction action priority of the enterprise to be estimated is output, and the specific formula for dynamic adjustment is: a composite score for the i-th enterprise, a carbon emission rating value for the i-th enterprise, a priority weight of the industry emission reduction demand corresponding to the main source of carbon emission of the i-th enterprise; The calculation process of the industry emission reduction demand priority weight includes: determining the industry carbon emission reduction demand closest to the main carbon emission source in the carbon label of the enterprise to be estimated, and determining the corresponding priority, and determining the corresponding weight according to the priority; According to the comprehensive score of the enterprise to be estimated, a comprehensive ranking list of all enterprises to be estimated is generated, from high to low, indicating the urgency of emission reduction; Step 4.5: Confirm the planning object, extract the enterprise from the ranking list, and form a list of carbon emission reduction planning objects.

9. The carbon label driven carbon emission reduction rating method of claim 1, wherein, The determination of the product carbon emission reduction level in step 5 includes: using the comprehensive scoring method to calculate the carbon emission reduction potential score of each product, and the formula is as follows: wherein, is the carbon emission reduction potential score of the jth product of the ith enterprise, is the industry emission reduction demand priority weight corresponding to the jth product of the ith enterprise, is the product carbon label value corresponding to the jth product of the ith enterprise, is the return cost ratio corresponding to the jth product of the ith enterprise, and the formula is as follows: wherein, is the optimized return corresponding to the jth product of the ith enterprise, is the optimized cost corresponding to the jth product of the ith enterprise; According to the emission reduction potential score of all products, determine the classification threshold to further determine the carbon emission reduction level of each product.

10. A carbon label driven carbon abatement grading method according to claim 9, wherein, The determination of the optimal carbon emission reduction strategy of the enterprise in step 5 includes: Set the state space: define the environmental state variables, including: product carbon emission reduction level, technology reserve, fund, energy price and other factors; Set the action space: define the emission reduction actions that the enterprise can take, including: investment in new technology, process optimization, carbon offset, product adjustment; Set the reward function: design to maximize long-term net income or minimize total cost; According to the set state space, action space and reward function, reinforcement learning optimization is carried out to determine the output enterprise optimal carbon emission reduction strategy.

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