A method and system for evaluating the life cycle of steel products

Abstract

This invention discloses a method and system for evaluating the life cycle of steel products. By acquiring a target life cycle impact assessment method, a target modeling method, and a target background database suitable for this evaluation, and organically integrating these with the product type, production process, and actual production data of the steel product to be evaluated, a life cycle model instance with both rule constraints and factual input is constructed. Based on this, the generation of an emissions inventory, inventory processing according to the allocation and cutoff rules applied in the target modeling method, and conversion of environmental impact indicators based on a set of characteristic factors are executed sequentially. This entire process achieves dynamic linkage and integrated execution of evaluation standards, modeling logic, and data sources, eliminating the tedious manual configuration and repetitive modeling operations between different methodologies. It fundamentally eliminates logical conflicts caused by mismatched parameter combinations, significantly improving the efficiency of steel product life cycle evaluation.

Description

Technical Field

[0001] This invention relates to the field of steel technology, and in particular to a method and system for evaluating the life cycle of steel products. Background Technology

[0002] Life cycle assessments of steel products require different life cycle impact assessment methods, such as CML, EF, EN15804, and TRACI, each with its own specific system modeling rules and background database. Existing tools often require users to manually select assessment methods, configure corresponding modeling rules, and manually match compliant data, resulting in cumbersome and fragmented processes. This leads to inefficiency in the assessment preparation process and makes it difficult to ensure the logical consistency of assessment parameter combinations. Therefore, how to achieve efficient integration and dynamic invocation of multiple life cycle impact assessment methods in steel product assessment is an urgent problem to be solved. Summary of the Invention

[0003] This application provides a method and system for evaluating the life cycle of steel products. It solves the technical problem in the prior art that multiple life cycle impact assessment methods and system modeling rules and background databases need to be manually matched and configured one by one, resulting in low evaluation preparation efficiency and difficulty in ensuring the consistency of parameter combination logic. It realizes the automatic association of corresponding modeling rules and background databases based on the target life cycle impact assessment method selected by the user, and completes model construction, emission inventory processing and impact index calculation in an integrated manner, thereby improving the efficiency and reliability of steel product life cycle assessment results.

[0004] In a first aspect, this application provides a method for evaluating the life cycle of steel products, the method comprising: Obtain the target life cycle impact assessment method, target modeling method, target background database, product type of the target steel product to be evaluated, and corresponding production process flow and actual production data applicable to the life cycle of steel products in this evaluation; Based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process flow, and the actual production data, a target life cycle model instance is constructed, which includes a first emission inventory to be allocated. The first emission inventory is processed according to the application allocation and cutoff rules in the target modeling method to obtain a second emission inventory with a clear environmental burden attribution. Based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, a corresponding environmental impact index set is obtained, which is used to evaluate the life cycle of steel products.

[0005] Secondly, this application provides a system for evaluating the life cycle of steel products, corresponding to the method for evaluating the life cycle of steel products provided in the first aspect, the system comprising: The user interaction layer is used to obtain the target life cycle impact assessment method, target modeling method, target background database, product type of the target steel product to be evaluated, and corresponding production process and actual production data applicable to the life cycle of the steel product being evaluated in this evaluation. The core algorithm layer is used to construct a target life cycle model instance based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process, and the actual production data. The target life cycle model instance includes a first emission inventory to be allocated. The first emission inventory is processed according to the application allocation and cutoff rules in the target modeling method to obtain a second emission inventory with a clear environmental burden attribution. Based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, a corresponding environmental impact index set is obtained. The environmental impact index set is used to evaluate the life cycle of steel products.

[0006] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: This application embodiment acquires the target life cycle impact assessment method, target modeling method, and target background database applicable to this evaluation, and organically integrates them with the product type, production process, and actual production data of the steel product to be evaluated, constructing a life cycle model instance that combines rule constraints and factual input. Based on this, the generation of the emission inventory, inventory processing according to the allocation and cutoff rules applied in the target modeling method, and conversion of environmental impact indicators based on the characteristic factor set are executed sequentially. This entire process achieves dynamic linkage and integrated execution of evaluation standards, modeling logic, and data sources, eliminating the tedious manual configuration and repetitive modeling operations between different methodologies. It fundamentally eliminates logical conflicts caused by mismatched parameter combinations, significantly improving the efficiency, credibility, and comparability of the steel product life cycle assessment results. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1A flowchart illustrating a method for evaluating the life cycle of steel products, provided as an embodiment of this application; Figure 2 This is a schematic diagram of a system for evaluating the life cycle of steel products, provided as an embodiment of this application. Detailed Implementation

[0009] This application provides a method and system for evaluating the life cycle of steel products. It solves the technical problem in the prior art that multiple life cycle impact assessment methods and system modeling rules and background databases need to be manually matched and configured one by one, resulting in low evaluation preparation efficiency and difficulty in ensuring the consistency of parameter combination logic. It realizes the automatic association of corresponding modeling rules and background databases based on the target life cycle impact assessment method selected by the user, and completes model construction, emission inventory processing and impact index calculation in an integrated manner, thereby improving the efficiency and reliability of steel product life cycle assessment results.

[0010] The technical solution of this application embodiment is to solve the above-mentioned technical problems, and the general idea is as follows: This application embodiment acquires the target life cycle impact assessment method, target modeling method, and target background database applicable to this evaluation, and organically integrates them with the product type, production process, and actual production data of the steel product to be evaluated, constructing a life cycle model instance that combines rule constraints and factual input. Based on this, the generation of the emission inventory, inventory processing according to the allocation and cutoff rules applied in the target modeling method, and conversion of environmental impact indicators based on the characteristic factor set are executed sequentially. This entire process achieves dynamic linkage and integrated execution of evaluation standards, modeling logic, and data sources, eliminating the tedious manual configuration and repetitive modeling operations between different methodologies. It fundamentally eliminates logical conflicts caused by mismatched parameter combinations, significantly improving the efficiency, credibility, and comparability of the steel product life cycle assessment results.

[0011] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0012] First, it should be clarified that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0013] Life Cycle Assessment (LCA) is an important tool for systematically assessing the environmental impact of a product throughout its entire lifecycle, from raw materials, production, use to disposal, and is of great significance for promoting the green transformation of industries.

[0014] Currently, the application and promotion of life cycle assessment (LCIA) faces bottlenecks such as fragmented methods and poor model compatibility. On the one hand, there are various mainstream LCIA methods, including the CML (Institute of Environmental Sciences, Leiden University) developed by the Leiden University Environmental Science Centre in the Netherlands, the Environmental Footprint (EF) developed by the European Commission, the core rules for the product category of construction products (EN 15804) of the European Building Products Environmental Declarations Standard, and the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI) developed by the US Environmental Protection Agency. These methods suffer from inconsistent evaluation standards due to regional and industry differences, requiring companies to repeatedly model and adapt to different international standards, resulting in low efficiency. On the other hand, the system modeling methods are diverse. Attribution methods (including classification cutoff method, EN15804 cutoff method, and alternative point cutoff method) and result methods (such as system extension method) have logical conflicts in the allocation rules. Furthermore, rules such as EN15804 cutoff method depend on specific application scenarios, and existing tools are difficult to dynamically switch models, resulting in poor comparability of evaluation results.

[0015] To address the aforementioned problems, this application provides a method for evaluating the life cycle of steel products. The method includes steps S11-S14, which can be found in detail elsewhere. Figure 1 As shown.

[0016] Step S11: Obtain the target life cycle impact assessment method, target modeling method, target background database, product type of the target steel product to be evaluated, and corresponding production process flow and actual production data applicable to the life cycle of steel products in this evaluation. Step S12: Based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process flow, and the actual production data, construct a target life cycle model instance, which includes a first emission inventory to be allocated. Step S13: Process the first emission inventory according to the application allocation and cutoff rules in the target modeling method to obtain a second emission inventory with clear environmental burden attribution. Step S14: Based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, a corresponding environmental impact index set is obtained. The environmental impact index set is used to evaluate the life cycle of steel products.

[0017] This application provides a method for evaluating the life cycle of steel products, which can rely on a system implementation for evaluating the life cycle of steel products. Specifically, the system for evaluating the life cycle of steel products adopts a layered architecture, including a user interaction layer, a core algorithm layer, and an output optimization layer.

[0018] The user interaction layer provides a standard selection interface, industry templates, and data input interfaces.

[0019] The standard selection interface supports the selection of mainstream LCIA methods, including CML, EF, TRACI, and EN15804, and displays the applicable scenarios for each method. CML is suitable for global warming potential assessment, while TRACI is suitable for North American market assessment. The standard selection interface also provides a method comparison function, allowing users to preview the differences in indicators between different methods. CML includes 10 impact categories, and EF includes 16 impact categories.

[0020] The industry templates are pre-set with typical process chains in the steel industry, including blast furnace-converter process, electric furnace process, hydrogen-based shaft furnace-electric furnace process, and steel solutions for the construction industry. The industry templates have built-in default parameters for direct emission factors, power emission factors, background data, and industry average energy consumption levels, and support users to adjust them according to the actual process.

[0021] The data input interface supports importing data in the ILCD standard data format or filling in data using customized input templates. The data list covers data on raw materials, energy media, by-product recycling, water, solid and gas emissions, etc. The data input interface also provides a data verification function, which automatically detects and identifies missing fields or inconsistent units, and verifies the accuracy and rationality of imported activity data based on industry average data.

[0022] The core algorithm layer includes a method library management module, a dynamic modeling module, and a data adaptation module.

[0023] The method library management module stores mainstream LCIA methods, including CML, EF, EN 15804, and TRACI. It also includes pre-built characteristic models for each method, such as the Global Warming Potential (GWP) index for CML and the ecotoxicity index for EF. After a user selects a target standard, the system automatically loads the corresponding indicator set. The module also provides a method comparison function, allowing users to preview the differences in indicators between different methods. Based on the user's selected industry and standard, the system automatically loads the corresponding characteristic models, background data, and allocation rules. Specifically, when a user selects the building industry and the EN 15804 standard, the system automatically loads the corresponding characteristic models, background data, and allocation rules.

[0024] The dynamic modeling module includes attribution adaptation units and result adaptation units.

[0025] The attribution method adaptation unit integrates the classification cutoff method, the EN15804 cutoff method, and the substitution point cutoff method. It automatically selects the allocation strategy based on physical or economic allocation rules. The allocation methods are shown in Table 1, and the implementation logic of the cutoff method is shown in Table 2. Specifically, the physical allocation rules support setting allocation coefficients for physical zoning based on energy and reaction processes; the economic allocation rules allocate based on the economic value proportion of symbiotic products over three years; the classification cutoff method excludes the load of by-products by default, including slag; the EN15804 cutoff method only includes streams with a mass proportion greater than one percent; and the substitution point cutoff method allows users to manually set substitution points, including the substitution ratio of recycled scrap steel.

[0026] Table 1 Allocation Method

[0027] Table 2 Implementation Logic of the Cutoff Method

[0028] substitution coefficient ( The determination of ) =1: Assuming 1kg of recycled material completely replaces 1kg of virgin material (ideal situation, data support required); <1: Consider the performance loss of recycled materials or the market substitution rate (e.g., the strength of scrap steel may be lower than that of virgin steel). Take 0.8); =0: Equivalent to the traditional cutoff method (ignoring the carbon reduction contribution of recycled materials).

[0029] The result-oriented adaptation unit realizes system extension modeling, incorporates the influence of alternative products, and supports dynamic adjustment of multiple system boundaries.

[0030] The data adaptation module automatically matches the background database based on the same LCIA method and system modeling method according to the selected method, and calibrates the regional difference data.

[0031] The output optimization layer compares the results of different methods through sensitivity analysis and generates a standardized report, which includes the Environmental Product Declaration (EPD) and the Carbon Footprint Declaration.

[0032] The following description will continue to illustrate a method for evaluating the life cycle of steel products provided in the embodiments of this application.

[0033] Regarding step S11, obtain the target life cycle impact assessment method, target modeling method, target background database, product type of the target steel product to be evaluated, and corresponding production process flow and actual production data applicable to the life cycle of steel products evaluated in this assessment.

[0034] The target life cycle impact assessment method refers to the specific calculation rule system selected by the user in this assessment to convert the emissions inventory into various environmental impact indicators. The determination of this method depends on the compliance requirements of the target market and the acceptance preferences of downstream customers. For example, when steel products are planned to enter the EU construction market, the user needs to select the Environmental Footprint (EF) method referenced in the EU standard EN 15804 as the target life cycle impact assessment method; when the products are targeted at the North American market, the user can select the TRACI method as the target life cycle impact assessment method based on local green building standards.

[0035] The target modeling method refers to the rule system selected by the user in this assessment to address the allocation of environmental burdens of symbiotic products in steel production and the delineation of system boundaries. The determination of this method depends on the inherent logical requirements of the selected life cycle impact assessment method, and the two have a pre-defined correlation. For example, when the user selects the assessment method corresponding to the EN 15804 standard, the system will automatically match the EN 15804 cutoff method under the attribution approach as the target modeling method. This method stipulates that environmental burdens are allocated only to material flows with a mass percentage greater than one percent. However, when the user conducts decision analysis oriented towards substitution effects, they can select the system extension method under the attribution approach as the target modeling method to incorporate the environmental impact of the substituted products.

[0036] The target background database refers to the database resource selected by the user in this assessment to provide standardized environmental data for the upstream of the industrial chain. This database provides lifecycle inventory data for background processes such as iron ore mining, power generation, and transportation in the model, consistent with the assessment methodology. Its determination depends on the combined requirements of the target lifecycle impact assessment method and the target modeling method, ensuring that the data in the database maintains consistency with the selected method in terms of calculation rules and allocation logic. For example, when the user selects the EN 15804 standard and its corresponding attribution modeling rules, the system will automatically match the Ecoinvent background database, which conforms to the EN 15804 attribution framework, rather than using a database based on the attribution framework, to ensure logical consistency of the data source.

[0037] The product type of the target steel product to be evaluated refers to the application scenario category of the specific steel product being evaluated by the user, such as steel for construction or steel for automobiles. The corresponding production process refers to the core technology route used to manufacture the product, such as the traditional blast furnace-converter process, electric arc furnace process, or hydrogen-based shaft furnace-electric furnace process. Users can adjust these parameters according to their actual processes. Actual production data refers to the activity data actually collected by the user during the production of the target steel product, covering the consumption of raw and auxiliary materials, energy media consumption, by-product recovery, and emissions of various air, water, and solid wastes. For example, the user selects the product type as construction steel, the production process as a blast furnace-converter process, and enters actual data such as the iron ore consumption, blast furnace gas consumption, and converter slag recovery for a specific production batch at a steel plant.

[0038] The above elements together constitute a logically consistent set of initialization parameters for the evaluation task. Among them, the target life cycle impact assessment method, the target modeling method, and the target background database have a pre-defined relationship, jointly defining the boundaries of the "calculation rules" for this evaluation; product type and production process define the boundaries of the "physical system" for this evaluation; and actual production data provide specific activity inputs for each process unit within the boundaries of this physical system. For example, when evaluating construction steel exported to the EU, the user selects the EF method corresponding to the EN 15804 standard as the target life cycle impact assessment method. The system automatically locks the attribution method—EN 15804 cutoff method—as the target modeling method and the corresponding Ecoinvent database as the target background database. Simultaneously, the user specifies the product type as construction steel, the production process as blast furnace-converter process, and imports the actual production data for this batch of steel. These five elements together constitute a complete evaluation task initialization configuration with unified calculation rules, clear physical boundaries, and explicit data sources, ensuring logical consistency and comparability of results in subsequent model construction and impact calculation.

[0039] Further, step S11 includes: Receive a first selection instruction from the user, the first selection instruction including a target life cycle impact assessment method applicable to the life cycle of steel products in this evaluation; The target modeling method and target background database corresponding to the target life cycle impact assessment method are determined from the pre-defined relationships between the life cycle impact assessment method, modeling method, and background database. Receive a second selection instruction input by the user, the second selection instruction including the product type of the target steel product to be evaluated and the corresponding production process flow and production process parameters; Receive the actual production data of the target steel product.

[0040] Users input their initial selection command through a standard selection interface provided by the user interaction layer. This standard selection interface can be presented as a graphical interface such as a drop-down menu, an option list, or an icon array, displaying the mainstream life cycle impact assessment methods supported by the system as options for the user. For example, when a steel company plans to apply for an EU Environmental Product Declaration (EPD) for its construction steel reinforcement products, the user can select the "EN 15804" option from the drop-down menu on the standard selection interface; when the company needs to assess the carbon footprint of its hot-rolled coils exported to the North American market, it can select the "TRACI" option on the interface. After the user completes the selection, the system receives the initial selection command containing the target life cycle impact assessment method.

[0041] The aforementioned correlation refers to the pre-defined mapping relationship between the life cycle impact assessment method, the modeling method, and the background database. This correlation is pre-established based on the following rules: each life cycle impact assessment method, due to its specific computational logic and indicator framework requirements, must be used in conjunction with a specific type of system modeling method. Simultaneously, it must call upon a background database that maintains consistency with the modeling method in terms of allocation rules and system boundary handling to avoid computational logic conflicts. For example, when the system pre-defines the correlation, it maps the assessment method corresponding to the "EN 15804" standard to the "EN15804 cutoff method" modeling method under the attribution approach, and associates the "Ecoinvent" background database, which conforms to the EN 15804 attribution framework, with it; it maps the "TRACI" method to attribution modeling rules applicable to the North American market, and associates a background database containing localized data such as North American regional electricity emission factors with it. When the user selects a target life cycle impact assessment method, the system automatically retrieves and determines the corresponding target modeling method and target background database from this pre-defined correlation.

[0042] The user inputs the second selection command through the industry template selection interface provided by the user interaction layer. This interface can be presented as a hierarchical selector or a wizard-style dialog box. It first displays the available product types (application scenarios). After the user selects a product type, it further displays the preset typical production process flow options under that product type. For example, the user first selects "Construction Steel Solution" as the product type in the industry template interface. The system then displays the preset typical process chain options under the construction steel scenario, including "Traditional Blast Furnace-Converter Process," "Electric Arc Furnace Process," and "Hydrogen-Based Shaft Furnace-Electric Furnace Process." The user selects "Traditional Blast Furnace-Converter Process" as the production process flow for this evaluation and adjusts and confirms the sintering temperature, continuous casting speed, and other production process parameters according to the actual process. After the user completes the above operations, the system receives the second selection command containing the product type, production process flow, and production process parameters.

[0043] Actual production data refers to the on-site activity data collected by users during the actual production process of the target steel product to be evaluated, through production execution systems, energy management systems, or environmental monitoring systems. This actual production data covers the following categories: raw material consumption data, such as the input of raw materials like iron ore, scrap steel, limestone, dolomite, and alloy additives; energy medium consumption data, such as the consumption of energy media like electricity, coke oven gas, blast furnace gas, converter gas, oxygen, nitrogen, and steam; by-product recovery data, such as the output and recycling of by-products like blast furnace slag, converter slag, coke oven gas, and recycled scrap steel; and emission data, including atmospheric emissions (such as emissions of carbon dioxide, sulfur dioxide, nitrogen oxides, and particulate matter), water emissions (such as emissions of chemical oxygen demand and ammonia nitrogen), and solid waste data (such as the generation of dust collector ash and waste refractory materials). For example, when a steel plant enters actual production data, it can import data such as the iron ore consumption of a certain batch of iron produced in its ironmaking process as 1.6 tons / ton of molten iron, the coke consumption as 0.35 tons / ton of molten iron, the blast furnace gas production as 1500 cubic meters / ton of molten iron, as well as the corresponding dust generation data and flue gas desulfurization emission data.

[0044] In addition to the interactive method of completing the selection instructions sequentially through a step-by-step wizard interface, the acquisition of various data in step S11 can also be achieved using the following alternative methods: The first method is a one-click import method based on configuration files.

[0045] The system provides a configuration file parsing interface, allowing users to directly import pre-prepared evaluation task configuration files. This configuration file uses a structured data format (such as XML, JSON, or YAML), fully declaring the target life cycle impact assessment method, target modeling method, target background database, product type, production process flow, and the storage path or embedded data of actual production data required for this evaluation. After the user uploads the configuration file through the system interface, the system automatically parses the file content and completes the loading and verification of all parameters in one go, eliminating the need for the user to perform item-by-item operations across multiple interfaces. For example, a steel company has established a standardized evaluation task template in its internal digital platform. After the user exports the template as a JSON file, they can upload it through the system's configuration file import portal. The system can then automatically identify the declared "EN15804" target standard, the corresponding attribution modeling rules, the type of steel for construction, and the blast furnace-converter process, and associate it with the actual production data tables embedded in the file or pointed to by the path, completing the evaluation task initialization.

[0046] The second method is barcode or QR code recognition.

[0047] The system can integrate a barcode scanning module, allowing users to obtain the data needed for evaluation by scanning barcodes or QR codes associated with specific product batches. These barcodes or QR codes are generated by the enterprise's production information system and encode the product type, production process route identifier, and corresponding activity data storage address for that batch. After scanning, the system automatically parses the encoded information, retrieves the corresponding actual production data from the associated enterprise database, and matches the corresponding target standards and modeling methods from a preset rule base based on the product type and process route. For example, a steel mill generates a unique batch QR code for each batch of hot-rolled steel coils for construction. After a user scans the QR code using the system's barcode scanning function, the system automatically identifies the product type as construction steel and the process as a blast furnace-converter process. It then retrieves the actual production data for that batch, including iron ore consumption, energy consumption, and emissions, from the enterprise's MES system. Simultaneously, it automatically matches the EN 15804 standard and corresponding parameter combinations based on preset EU export business rules.

[0048] The third method is the external system call method based on API interfaces.

[0049] The system provides an Application Programming Interface (API) that allows external systems (such as Enterprise Resource Planning (ERP) systems, Manufacturing Execution Systems (MES) or Supply Chain Carbon Management (SCH) platforms) to directly pass the parameters required for the evaluation task via API calls. External systems construct request messages according to the interface specifications. The message body includes the target standard code, product type code, process route code, and a list of actual production data or data source identifier. Upon receiving the request, the system can complete the evaluation task initialization. For example, a large steel group's supply chain carbon management platform needs to calculate the carbon footprint of multiple batches of construction steel in batches. This platform calls the system's API, passing in the target standard code, product type, and process route parameters batch by batch, along with the corresponding batch's actual production data extracted from the group's data lake, thus achieving fully automated batch startup of the evaluation task.

[0050] Regarding step S12, based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process flow, and the actual production data, a target life cycle model instance is constructed, and the target life cycle model instance contains a first emission inventory to be allocated.

[0051] The target lifecycle model instance refers to a calculable product environmental load analysis object constructed by the system in the background during this evaluation process, based on the user-selected target lifecycle impact assessment method, target modeling method, target background database, product type, production process flow, and actual production data. This model instance uses process units as basic nodes, connecting each production process into a complete supply chain network according to material and energy flows based on the selected production process flow, and populating the corresponding process unit inputs with the user-entered actual production data. Simultaneously, this model instance has pre-loaded the allocation rule preset items specified by the target modeling method onto each process unit, and has parsed and linked all upstream background data based on the target background database.

[0052] The first emissions inventory to be allocated refers to a preliminary, original inventory formed after the target lifecycle model instance has completed data population and background data linking. This inventory is generated by initially traversing all process units' foreground data and linked background data, converting various activity data into environmental emissions and resource consumption. This inventory is a preliminary list of environmental burdens from co-produced products that has not yet been allocated. In this first emissions inventory, all environmental outputs such as carbon dioxide and sulfur dioxide emissions from a blast furnace process that simultaneously produces molten iron and slag are recorded as a whole at that process node, without being allocated between molten iron products and slag by-products.

[0053] The core of step S12 is to integrate the calculation rules used in this evaluation with the collected physical facts into a unified calculation carrier. Based on the user-specified parameter combination, the system integrates the abstract evaluation criteria (target life cycle impact assessment method), modeling logic (target modeling method), data support (target background database), and concrete physical objects (product type, production process, actual production data) into a unified whole, constructing a target life cycle model instance in the background that can perform subsequent calculations. This model instance not only solidifies the selected criteria and rules, but also fully links and quantifies the actual production activity data with the upstream supply chain background data, generating a raw data set reflecting all environmental emissions of the steel product throughout its entire life cycle, namely the first emission list to be allocated, providing a unified data foundation for subsequent allocation of symbiotic products and characteristic calculation of environmental impact.

[0054] Specifically, step S12 may include: Based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process flow, and the actual production data, a basic life cycle model instance is constructed. Determine whether the source tags of all upstream background data requests in the basic lifecycle model instance are consistent with the target background database to obtain the data source verification result; If the data source verification result is inconsistent, the upstream background data request will be redirected to the target background database until the source tags of all upstream background data requests in the obtained basic lifecycle model instance are consistent with the target background database. The target lifecycle model instance is obtained by replacing the general default data in the basic lifecycle model instance with the regional dataset in the target background database.

[0055] The process of constructing a basic lifecycle model instance involves the structured integration of various evaluation parameters provided by the user. The system first uses the user-selected product type and production process as a framework, retrieving the corresponding process unit chain from the industry template library. For example, when the user selects "construction steel" as the product type and "traditional blast furnace-converter process" as the production process, the system sequentially loads the sintering process unit, blast furnace ironmaking process unit, converter steelmaking process unit, continuous casting process unit, and rolling process unit, connecting each process unit in series according to the direction of material and energy flow. Subsequently, the system fills the foreground data ports of each process unit with the actual production data entered by the user. For example, the iron ore consumption of 1.6 tons provided by a steel plant is filled into the raw material input port of the blast furnace ironmaking process unit, the coke oven gas consumption is filled into the corresponding energy medium input port, and the sulfur dioxide emissions are filled into the emission output port of this process. Simultaneously, based on the input port declarations of each process unit, the system sends data requests to the target background database, linking the corresponding upstream background dataset for each material and energy input. For example, it links the "Iron Ore Mining and Beneficiation" dataset in the target background database for the iron ore input and the "Electricity Production" dataset for the electricity input, thereby forming a basic lifecycle model instance with complete process nodes, filled data ports, and interconnected upstream and downstream processes.

[0056] Upstream background data requests refer to calls initiated by each process unit in a basic lifecycle model instance to a background database to obtain environmental load data from the upstream supply chain in order to ensure the integrity of its material or energy input ports. For example, the iron ore input port of the blast furnace ironmaking process unit initiates an upstream background data request to obtain all environmental emissions and resource consumption data generated during the process of "mining and beneficiating 1.6 tons of iron ore". The role of upstream background data requests is to extend the evaluation system boundary from the internal production processes of the steel plant upstream to the industrial chain links such as raw material mining and energy production, thereby forming a complete lifecycle perspective. A source tag refers to the metadata tag carried by each upstream background data request, used to identify the database source it points to. This tag records information such as the database name, version number, and data publishing organization to which the dataset belongs. The system can determine which database the background data is retrieved from by reading this tag.

[0057] If, after a full-link scan, the system determines that the source tags of all upstream background data requests in the basic lifecycle model instance are consistent with the target background database, the system generates a marker indicating that the data source verification has passed. It does not modify any background data request links in the current basic lifecycle model instance and directly sends the basic lifecycle model instance to the next processing stage, i.e., the stage of replacing general default data based on regional datasets. For example, in an evaluation task, the actual production data imported by the user and the background data it references both come from the Ecoinvent database corresponding to the EN 15804 standard, and the system scan confirms that all source tags point to the target database. In this case, the verification results are consistent, the system retains all link relationships of the current model instance, and continues to perform subsequent regional calibration operations.

[0058] When the system detects that the source label of an upstream background data request is inconsistent with the target background database, the system redirects the request by modifying its link pointer. Specifically, the system retains the material or energy demand type declared in the original data request (e.g., "electricity production"), but switches the database path it points to from the database identified by the original source label to the storage address of the corresponding dataset in the target background database. For example, an upstream background data request might originally point to the "electricity production" dataset in a steel plant's locally built database, with its source label showing "local database A," which is inconsistent with the target background database "Ecoinvent." The system automatically rewrites the link pointer of this data request from the storage path of local database A to the "China Power Grid Electricity" dataset path in the Ecoinvent database, keeping the request type unchanged and only changing the data source, thus completing the redirection operation.

[0059] After confirming that the basic lifecycle model instance passes the data source consistency check, the system replaces the previously preset general default background data in the model instance with the regionalized datasets provided in the target background database. This replacement process involves the system traversing the background datasets linked to each process unit, identifying data nodes using general average values, and replacing them with refined datasets in the target background database that match the regional information of this evaluation. For example, when constructing the basic lifecycle model instance, the power input of the blast furnace ironmaking process is linked by default to the "Global Average Grid Electricity" dataset in the target background database, which uses the global average emission factor. When the regional information for this evaluation is "China," the system retrieves the "China Specific Regional Grid Electricity" dataset from the target background database. This dataset calculates the emission factor based on the actual power generation structure of the Chinese power grid. The system replaces the original default global average dataset with this regional dataset, thus calibrating the steel plant's power consumption background data to reflect the actual situation of the Chinese power grid.

[0060] Through the execution of step S12 above, the system integrates the user-selected evaluation criteria, modeling rules, physical objects, and measured data into a computable model that is internally consistent, has a unified data source, and is regionally representative. In this process, the system first structurally integrates abstract standards with specific production facts to form a preliminary model framework; then, through a full-chain data source scan, it identifies and corrects potential biases in the background data source within the model, ensuring that all supply chain data relied upon by the model originates from the same compliant database; based on this, the system further replaces general default values ​​with regionalized parameters, making the supply chain environmental load reflected by the model more closely reflect the objective conditions of the actual production location. The resulting target lifecycle model instance provides a reliable input with consistent data foundation and accurate regional characteristics for subsequent emission inventory allocation and impact indicator conversion.

[0061] Furthermore, the first emission inventory is obtained through the following steps: Traverse the foreground data and linked background data of all process units in the target life cycle model instance, convert the foreground data and background data into the mass of various environmental emissions and the amount of resources consumed, and obtain the first emission inventory based on the mass of various environmental emissions and the amount of resources consumed.

[0062] A process unit refers to a basic modeling node in a target lifecycle model instance, representing a single, independent production stage in the steel product manufacturing process. Each process unit encapsulates the input and output ends of that production stage. The input ends include the raw materials, auxiliary materials, and energy media required for that stage, while the output ends include intermediate products, by-products, and various substances emitted into the environment. For example, sintering, blast furnace ironmaking, converter steelmaking, continuous casting, and rolling are all independent process units. The relationship between process units and the target lifecycle model instance can be understood as follows: the target lifecycle model instance is a complete model network composed of multiple process units connected sequentially according to the production process flow, through the input and output relationships of material and energy flows. The process unit is the basic structural unit constituting the target lifecycle model instance.

[0063] Foreground data refers to activity data collected on-site at each process unit during the actual production of the steel product to be evaluated, entered by users through the data input interface. Its data boundaries are limited to the direct production activities within the steel plant. For example, the iron ore consumption, coke consumption, blast furnace gas consumption, and sulfur dioxide emissions monitored on-site for the blast furnace ironmaking process unit are all considered foreground data for that process unit. Linked background data refers to upstream supply chain datasets in the target background database accessed by the input terminals of each process unit. These datasets provide data on environmental emissions and resource consumption generated in the upstream links of the industrial chain before the materials or energy required by the input terminal enter the steel plant. For example, the "Iron Ore Mining and Beneficiation" dataset linked to the iron ore input terminal of the blast furnace ironmaking process unit, and the "Electricity Production" dataset linked to the electricity input terminal, are both considered linked background data. These datasets were linked to their corresponding input ports when constructing the target lifecycle model instance.

[0064] The system iterates through each process unit in the target lifecycle model instance, converting the foreground data and linked background data for that process unit. For foreground data, the system directly converts the activity data into the corresponding environmental emissions and resource consumption based on the emission factor calculation rules built into that process unit. For example, for the foreground data of coke consumption in the blast furnace ironmaking process unit, the system converts the coke consumption into carbon dioxide emissions (e.g., 0.35 tons of coke is converted into approximately 1.1 tons of carbon dioxide) and sulfur dioxide emissions based on the carbon content and oxidation rate parameters of coke combustion; for the foreground data of scrap steel consumption in the converter steelmaking process unit, the system converts the scrap steel consumption into the corresponding electricity or fuel consumption based on the heat balance model of scrap steel preheating and smelting, and further converts it into emissions. For linked background data, the system directly extracts the pre-calculated environmental emissions and resource consumption from that dataset. For example, the background dataset of "Iron Ore Mining and Beneficiation" linked to the iron ore input terminal of the blast furnace ironmaking process unit has recorded data such as carbon dioxide emissions, water consumption, and diesel consumption generated from mining and beneficiating 1.6 tons of iron ore. The system directly reads these values ​​and includes them in the total amount calculated in this conversion.

[0065] After completing the conversion of foreground and background data in all process units, the system aggregates the environmental emissions and resource consumption data produced by each process unit, categorized by emission type and resource type, to form a structured first emission list covering the entire process scope of the target lifecycle model instance. This first emission list uses the identifier of the emission type or resource type as the primary key, and the aggregated total amount as the corresponding value. For example, the system accumulates the carbon dioxide emissions converted from the blast furnace ironmaking process unit, the converter steelmaking process unit, and the sintering process unit, along with the carbon dioxide emissions recorded in the upstream background data linked to each process unit, across processes to obtain the total carbon dioxide emissions for the entire lifecycle of the target steel product, which is then recorded in the first emission list. Similarly, the system summarizes the atmospheric emissions (sulfur dioxide, nitrogen oxides, methane, etc.) converted from each process unit, the water emissions (chemical oxygen demand, ammonia nitrogen, etc.), and the resource consumption (iron ore, manganese ore, limestone, etc.) into total data for each corresponding category, ultimately forming a complete first emission list, but without environmental burden allocation among co-produced products. In this list, the total emission burden of molten iron and slag produced simultaneously by the same blast furnace is still recorded as a whole, without distinguishing between the portion belonging to molten iron products and the portion belonging to slag by-products.

[0066] Regarding step S13, the first emission inventory is processed according to the application allocation and cutoff rules in the target modeling method to obtain a second emission inventory with a clear environmental burden attribution.

[0067] Application allocation and cutoff rules refer to a set of systematic rules specified in the objective modeling method for handling the environmental burden attribution problem of multiple outputs and micro-logistics in the steel production process. These rules consist of two parts: co-product allocation rules and application cutoff rules.

[0068] The coexisting product allocation rule refers to the rule for distributing the total environmental burden of a steel production unit among its coexisting products according to a pre-defined allocation logic when a certain process unit simultaneously produces two or more economically valuable coexisting products. This rule can establish allocation ratios based on physical attributes or economic value. Physical allocation rules allocate the burden based on the mass, energy, or calorific value proportion of each coexisting product, while economic allocation rules allocate the burden based on the economic value proportion reflected by the average market price of each coexisting product over a specific time period. For example, in the blast furnace ironmaking process, a blast furnace simultaneously produces molten iron and blast furnace slag, where molten iron is the main product and blast furnace slag can be sold as a cement raw material, belonging to an economically valuable by-product. In this case, according to the physical allocation rule, the total carbon dioxide and sulfur dioxide emissions generated by the blast furnace process can be proportionally allocated to the two products—molten iron and blast furnace slag—based on their respective mass proportions in the total output mass.

[0069] Application cutoff rules refer to rules that filter and screen specific material or energy flows in the first emission inventory to determine whether they should be included in the environmental burden allocation. These rules exclude minute flows below a preset threshold from environmental burden allocation, or cut the environmental burden of recyclable materials according to specific boundaries. For example, the classification cutoff method under the attribution framework by default excludes flows marked as by-products from environmental burden calculation, meaning by-products do not bear any environmental emissions from their upstream processes; the EN 15804 cutoff rule stipulates that only material flows with a mass percentage greater than one percent or an energy percentage greater than one percent are allocated environmental burden, and minute flows below this threshold are considered to have negligible contribution to the environmental burden and are not included in the allocation.

[0070] Step S13 specifically involves allocating the environmental burden of each process among the symbiotic products in the target steel production process according to the symbiotic product allocation rules, filtering the first emission list based on the application cutoff rules, and obtaining a second emission list with a clear environmental burden attribution.

[0071] First, the system identifies the co-product nodes in each process unit of the first emission list. For example, after traversing the list, the system identifies that the blast furnace ironmaking process unit produces two co-products: molten iron and blast furnace slag, and the converter steelmaking process unit produces two co-products: molten steel and converter slag. For each identified co-product node, the system establishes an allocation coefficient according to a preset co-product allocation rule. Taking the blast furnace ironmaking process as an example, if the physical allocation rule is used in this evaluation, the system extracts the molten iron quality data and slag quality data output from this process in the first emission list, calculates the ratio of molten iron quality to the total mass of molten iron and slag, uses this ratio as the burden allocation coefficient for molten iron products, and multiplies the total carbon dioxide emissions of this process (e.g., a total of 1850 kg) by this allocation coefficient to obtain the carbon dioxide emissions attributed to molten iron products. The remaining portion is attributed to slag by-products. If the economic allocation rule is adopted in this evaluation, the system will retrieve the average market prices of molten iron and slag in the past three years, calculate the economic value ratio of the two as the allocation coefficient, and complete the burden allocation according to the economic value ratio.

[0072] After the allocation of co-existing products is completed, the system further filters the allocated emission items according to the application cutoff rules. For example, if the EN 15804 cutoff method is used in this assessment, the system scans the mass percentage of the data allocated to each material flow in the converter steelmaking process, identifying trace emission flows with a mass percentage of less than one percent. For instance, if the amount of foundry slag recovered in a certain batch in this process accounts for only three-thousandths of the total output mass, the system removes the environmental burden item corresponding to this trace flow from the list according to the cutoff rules and does not include it in the final assessment. After the complete processing of the above allocation and filtering operations, the system finally produces a second emission list in which the environmental burden is clearly assigned among each product and the trace flows that do not meet the threshold have been removed. In this second emission list, each environmental emission and resource consumption data has a clear attribution object. The environmental burden of carbon dioxide emissions, sulfur dioxide emissions, etc., corresponding to the main product, construction steel, is clearly separated from the respective shares that by-products such as blast furnace slag and converter slag should bear.

[0073] Regarding step S14, a corresponding environmental impact indicator set is obtained based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory. This environmental impact indicator set is used to evaluate the life cycle of steel products. Specifically, each emission substance in the second emission inventory is multiplied by its corresponding relative contribution value to obtain the corresponding environmental impact indicator set.

[0074] A characteristic factor set refers to a set of conversion coefficients provided by the target life cycle impact assessment method to quantify the relative contribution potential of different emission substances to a specific type of environmental problem. The characteristic factor set includes the relative contribution values ​​of different emission substances to a specific type of environmental problem. This factor set stores the equivalent conversion coefficients of various emission substances relative to the benchmark substance for that environmental problem type, indexed by the specific environmental problem type.

[0075] Taking global warming as an example, the characteristic factors include those corresponding to the global warming potential of dozens of greenhouse gases, such as carbon dioxide, methane, nitrous oxide, and fluorine-containing gases in blast furnace gas. The factor value for carbon dioxide is 1 kg CO2 equivalent, and the factor value for methane is 28 kg CO2 equivalent, meaning that the relative contribution of 1 kg methane emission to global warming is equivalent to the emission of 28 kg CO2. Taking acidification as another example, the characteristic factors include those corresponding to the acidification potential of acidic gases such as sulfur dioxide, nitrogen oxides, and ammonia. The factor value for sulfur dioxide is 1 kg sulfur dioxide equivalent, and the factor value for nitrogen oxides is 0.7 kg sulfur dioxide equivalent, meaning that the relative contribution of 1 kg nitrogen oxide emission to acidification is equivalent to the emission of 0.7 kg sulfur dioxide. Taking eutrophication as an example of an environmental problem, the characteristic factors include the characteristic factors of eutrophication potential corresponding to nutrients such as phosphorus compounds and nitrogen compounds. Among them, the factor value of phosphate is 1 kg phosphate equivalent, and the factor value of ammonia nitrogen is 0.35 kg phosphate equivalent.

[0076] The environmental impact indicator set refers to a set of evaluation results obtained by multiplying each emission substance in the second emission inventory by the corresponding characteristic factor in the characteristic factor set and summing them, and then quantitatively representing each environmental problem type. Each indicator in this indicator set represents the comprehensive impact value of the steel product on the corresponding environmental problem type, expressed in the reference material equivalent unit defined for that environmental problem type.

[0077] The specific content of the environmental impact indicator set depends on the indicator framework of the target life cycle impact assessment method selected for this assessment. Taking the EF method for steel products as an example, this environmental impact indicator set includes sixteen indicators, reflecting the environmental performance of the steel products from different dimensions: global warming potential indicators in the climate dimension, expressed in kilograms of carbon dioxide equivalent; acidification potential indicators in the atmosphere dimension, expressed in molar hydrogen ion equivalent; eutrophication potential indicators in the water body dimension, including freshwater eutrophication (expressed in kilograms of phosphorus equivalent) and seawater eutrophication (expressed in kilograms of nitrogen equivalent); ecotoxicity indicators in the ecological dimension, expressed in comparative toxicity units; abiotic resource depletion potential indicators in the resource dimension, expressed in kilograms of antimony equivalent, and water resource depletion potential indicators, expressed in cubic meters of water equivalent; in addition, it also includes ozone layer depletion potential, photochemical ozone formation potential, particulate matter emission impact, and human toxicity indicators.

[0078] The system first retrieves the characteristic factor set corresponding to the target life cycle impact assessment method determined in step S11 from the method library management module. Then, the system iterates through each emission substance entry in the second emission inventory, reads the type identifier of the emission substance and the emission amount value attributed to the target product after allocation, and retrieves the characteristic factor corresponding to the emission substance under each environmental problem type in the characteristic factor set.

[0079] The specific conversion process is illustrated using the Global Warming Potential Index as an example. The second emissions inventory records greenhouse gas emissions attributable solely to the main product, construction steel, including 1850 kg of carbon dioxide, 0.5 kg of methane, and 0.02 kg of nitrous oxide. The system multiplies these emissions by the corresponding global warming characteristic factors from the characteristic factor set: 1850 kg of carbon dioxide multiplied by 1 yields 1850 kg of carbon dioxide equivalent; 0.5 kg of methane multiplied by 28 yields 14 kg of carbon dioxide equivalent; and 0.02 kg of nitrous oxide multiplied by 265 yields 5.3 kg of carbon dioxide equivalent. The system then sums these three converted values ​​along with the converted values ​​for other greenhouse gases in the second emissions inventory to obtain the global warming potential index value for this construction steel product. Simultaneously, the system multiplies the emissions of acidic gases such as sulfur dioxide and nitrogen oxides in the second emission inventory by their respective acidification characteristic factors and sums them to obtain acidification potential index values; it also multiplies phosphorus-containing and nitrogen-containing emissions by their respective eutrophication characteristic factors and sums them to obtain eutrophication potential index values. This process is executed synchronously for all environmental problem types required by the target LCIA method, ultimately producing a set of environmental impact indicators covering all preset indicator dimensions and expressed in their respective benchmark equivalent units.

[0080] The environmental impact indicator set, through multi-dimensional quantitative values, comprehensively reflects the overall environmental performance of a steel product throughout its life cycle from the perspective of different environmental issues. The application analysis of the environmental impact indicator set can be carried out at three levels. The first level is absolute numerical assessment, directly reading the equivalent values ​​of each indicator to identify the main types of environmental impacts of the product. For example, the global warming potential indicator for a certain construction steel product is 1980 kg CO2 equivalent, indicating that this type of emission is one of the most prominent types of environmental impacts of the product. The second level is process contribution decomposition, tracing the source of each indicator value by process unit to identify the main contributing processes. For example, after decomposing the 1980 kg CO2 equivalent of the global warming potential indicator by process, the blast furnace ironmaking process contributes 65% and the sintering process contributes 15%, indicating that blast furnace ironmaking is the primary control point for carbon emissions of this product. The third level is scheme comparison assessment, comparing the environmental impact indicator sets under different process routes, different raw material and fuel ratios, or different recycling schemes to provide data support for process optimization decisions. For example, comparing the environmental impact indicators of the same specification of building steel produced by the blast furnace-converter long process and the electric arc furnace short process, the former has a global warming potential of about 1980 kg CO2 equivalent, while the latter has about 520 kg CO2 equivalent. However, the latter has a lower value in the non-biological resource consumption indicator due to the ore-saving effect of scrap steel. The comprehensive comparison can provide a scientific basis for the selection of low-carbon metallurgical process routes.

[0081] Furthermore, after obtaining the corresponding environmental impact indicator set based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, the method further includes: An environmental product declaration report in a preset format is generated based on the set of environmental impact indicators.

[0082] The preset format refers to the report structure template pre-configured by the system based on the target standards selected for this evaluation. This report structure template follows internationally standardized environmental product declaration preparation specifications and specifically includes the following components: a report cover area, which specifies the product name, manufacturer information, report number, and publication date; a product description area, which specifies product definition information such as functional units, system boundaries, reference service life, and technical performance parameters; a life cycle assessment methodology information area, which specifies the life cycle impact assessment methodology, system modeling methodology, allocation rule type, cutoff rule type, and background database source used in this evaluation; a full life cycle stage results area, which presents the indicator values ​​for each type of environmental problem in a modular structure, from raw material acquisition, transportation, manufacturing, use and maintenance to end-of-life disposal or recycling; a data quality description area, which specifies the data source, temporal representativeness, geographical representativeness, technical representativeness, and uncertainty analysis or sensitivity analysis conclusions; a third-party verification information area, reserved for specifying the name of the verification agency, verification conclusions, and signature information; and an appendix area, which contains supplementary information, references, or terminology explanations.

[0083] The Environmental Product Declaration Report is a complete document containing the specific data and information for this evaluation that has been filled in the aforementioned areas. Taking an Environmental Product Declaration Report for construction steel products as an example, the product description area of ​​this report records the functional unit as "1 ton of hot-rolled ribbed steel bars for construction," and the system boundary as "from cradle to gate (modules A1 to A3)." The A1 raw material acquisition module in the full life cycle stage results area records the contribution values ​​of upstream processes such as iron ore mining and limestone mining to various indicators; the A2 transportation module records the contribution values ​​of raw material transportation processes; and the A3 production and manufacturing module records the contribution values ​​of core processes such as sintering, blast furnace ironmaking, converter steelmaking, continuous casting, and rolling. The data quality description area records that the data collection period for this report is the monthly average of the steel plant over the past year, the geographical representative region is East China, and includes a sensitivity analysis comparison of the main indicators under two allocation rules: physical allocation and economic allocation.

[0084] After completing the calculation of the environmental impact indicator set, the system calls a preset report structure template that matches the target standard type determined in step S11 from the output optimization layer. The system establishes a mapping relationship between the data placeholders of each module in the template and the calculated environmental impact indicator set, and automatically extracts the values ​​of each indicator and writes them into the corresponding report fields.

[0085] The specific generation process is as follows: The system first reads the values ​​of sixteen indicators from the environmental impact indicator set, extracts the global warming potential indicator value, and breaks it down into sub-values ​​for each module (A1 raw material acquisition, A2 transportation, A3 production and manufacturing) according to the contribution rate of each process. These sub-values ​​are then written into the "Climate Change" row of the corresponding module in the full life cycle stage results area. The acidification potential indicator value is also broken down and written into the "Acidification" row of the corresponding module. This process is repeated to complete the data entry for all indicators at each life cycle stage. Simultaneously, the system extracts product description fields such as product name, functional unit, and manufacturer name from the evaluation task configuration information. It also extracts the target life cycle impact assessment method name, target modeling method name, target background database name, and version number from the data in step S11 and writes them into the life cycle assessment method information area. The system also extracts the contribution percentage of each process unit to the main indicators, the data collection time range, and the geographical range from the calculation process of this evaluation, automatically generating the content of the data quality description area. When it detects that the user has selected multiple allocation rules for comparison during the evaluation process, the system automatically organizes the comparison data into a sensitivity analysis summary and includes it in the data quality description area.

[0086] The presentation of Environmental Product Declaration (EPD) reports can take at least one of the following forms: First, the system provides an interactive preview window on the output optimization layer interface, allowing users to view the full report online and zoom in and out on charts and graphs. Second, the system supports exporting the report as a portable document format, such as a PDF file, which includes embedded data tables and stacked bar charts of impact indicators. Third, the system supports outputting in machine-readable formats required by the international EPD platform, such as ILCD or XML data packets, which can interact with third-party verification platforms or the EPD database. For example, after completing the evaluation of steel for construction, a steel company can preview and confirm the report content through the output optimization layer interface, export the report as a PDF file for submission to a third-party verification agency, and simultaneously export an XML data packet to the international EPD system platform for registration and publication.

[0087] Furthermore, after obtaining a second emission inventory with clearly defined environmental burden attribution, the method further includes: In response to the user's input of a horizontal comparison command, a corresponding set of environmental impact indicators is obtained based on the characteristic factor set in at least one other life cycle impact assessment method besides the target life cycle impact assessment method and the second emission inventory; Identify common indicators in the environmental impact indicator sets corresponding to various life cycle impact assessment methods, including the target life cycle impact assessment method, and determine the differences between various common indicators.

[0088] A horizontal comparison command refers to an interactive command issued by a user through the system interface after the current evaluation calculation is completed, requesting the system to run at least one other life cycle impact assessment method in parallel based on the same second emission inventory and produce comparison results. This command can be triggered by selecting a method through the "Method Comparison" button or drop-down menu provided on the output optimization layer interface. When viewing the current results, the user can select one or more other methods from the system's preset method list. After receiving the command, the system initiates the background parallel calculation process.

[0089] At least one other life cycle impact assessment method besides the target life cycle impact assessment method refers to other mainstream methods pre-set in the system method library, besides the target method used in the current assessment task determined in step S11. For example, if the target method selected by the user in step S11 is the EF method referenced in the EN 15804 standard, then other methods besides the target method include at least one or more of the CML method and the TRACI method. These other methods differ from the target method in the coverage of the characteristic model, the setting of indicator categories, and the numerical values ​​of the characteristic factors for each emission substance. Therefore, the environmental impact indicator set calculated based on the same second emission inventory will also present different result characteristics. This horizontal comparison function allows users to obtain environmental impact assessment conclusions from multiple methodological perspectives simultaneously in a single assessment task without having to re-execute the complete modeling and data entry process.

[0090] After completing the feature calculations for the target method and at least one other method selected by the user, the system obtains multiple sets of environmental impact indicators, each corresponding to a life cycle impact assessment method. The system first needs to identify common indicators with the same meaning or those that can be correlated across the multiple sets of indicators, i.e., indicators targeting the same type of environmental problem.

[0091] The specific method for identifying common indicators is as follows: the system uses the scientific definition of environmental problem types as the mapping basis and establishes matching relationships between the indicator dictionaries of different methods. For example, the indicator set of the target method EF includes the indicator "global warming potential," and the indicator set of the user-selected comparison method CML also includes the indicator "global warming potential." The system identifies them as a pair of common indicators because both point to the environmental problem type of "climate change caused by greenhouse gas emissions." Similarly, EF's "acidification potential" and TRACI's "acidification potential" are identified as common indicators because they both point to the environmental problem type of "environmental acidification caused by acidic substance emissions." EF's "eutrophication potential - freshwater" and CML's "eutrophication potential" are identified as common indicators because they both point to the environmental problem type of "eutrophication of water bodies caused by nutrient emissions." For indicators that are unique to certain methods but do not have corresponding environmental problem types in other methods, such as the "water resource consumption potential" indicator in the EF method which lacks a direct corresponding indicator category in the CML method, such indicators are not included in the common indicator identification scope. The system marks them as "indicators unique to a certain method" and presents them separately in the comparison report.

[0092] The process of determining the differences between various common indicators is as follows: For each pair of identified common indicators, the system reads their respective equivalent values ​​from the environmental impact indicator set corresponding to the target method and the environmental impact indicator set corresponding to other methods, and calculates the absolute difference and relative percentage change. Taking the acidification potential indicator as an example, based on the same second emission inventory, the acidification potential indicator calculated by the target method EF is 3.2 molar hydrogen ion equivalents, while the acidification potential indicator calculated by the comparative method TRACI is 4.1 kg sulfur dioxide equivalents. Considering that the two indicators have different reference material units, the system decomposes their respective results to the emission material level according to a unified percentage contribution for attribution comparison. The system found that the main source of the difference is that the acidification characteristic factor value of nitrogen oxides by the TRACI method is higher than the corresponding factor value of nitrogen oxides by the EF method. The system marks the reason for this difference in the comparison results. Finally, the system compiles the comparison relationships of all common indicators into a comparison matrix table. The row headers are the names of the common indicators, the column headers are the names of the comparison methods, the cells contain the equivalent values ​​of the indicators corresponding to each method, and the difference column indicates the percentage of relative difference between the indicators and the main substances causing the difference, so as to provide users with cross-standard evaluation and decision-making.

[0093] In summary, this application's embodiments acquire the target life cycle impact assessment method, target modeling method, and target background database applicable to this evaluation, and organically integrate them with the product type, production process, and actual production data of the steel product to be evaluated, constructing a life cycle model instance that combines rule constraints and factual input. Based on this, the generation of the emission inventory, inventory processing according to the allocation and cutoff rules applied in the target modeling method, and conversion of environmental impact indicators based on the characteristic factor set are executed sequentially. This entire process achieves dynamic linkage and integrated execution of evaluation standards, modeling logic, and data sources, eliminating the tedious manual configuration and repetitive modeling operations between different methodologies. It fundamentally eliminates logical conflicts caused by mismatched parameter combinations, significantly improving the efficiency, credibility, and comparability of the steel product life cycle assessment results.

[0094] This application embodiment, through preset association relationships, enables the system to automatically determine logically compatible target modeling methods and target background databases based on the user-selected target life cycle impact assessment method. This avoids the mismatch risks that may be introduced during manual matching and ensures the inherent self-consistency of the evaluation parameter system. In the model building stage, full-link verification is performed on the source tags of all upstream background data requests, and inconsistencies are automatically redirected to the target database, forcing the unification of background data sources and eliminating calculation biases caused by the mixing of multiple data sources. Furthermore, the system replaces the general default values ​​with regional datasets from the target background database, making the supply chain environmental load on which the evaluation is based more closely aligned with the actual geographical and energy structure characteristics of production, thus enhancing the representativeness and relevance of the results. When processing symbiotic products, the environmental burden of the process is reasonably allocated among various products according to physical or economic allocation rules, and cutoff rules are used to filter out logistics with minimal contributions, resulting in a clear and well-defined environmental burden attribution and boundary in the final emission inventory. The characteristic factor set scientifically converts various emission substances in the inventory into a set of environmental impact indicators covering multiple dimensions such as global warming, acidification, and eutrophication, comprehensively reflecting the overall performance of steel products in different types of environmental problems. After producing the indicator set, the system can automatically generate an Environmental Product Declaration Report conforming to a preset format of international standards, outputting standardized documents that can be directly used for green certification and supply chain information disclosure. Furthermore, while maintaining the same emissions inventory, the system can perform characteristic calculations for multiple life cycle impact assessment methods in parallel, identifying common indicators under different methods and quantifying differences. This provides a cross-standard comparative perspective within a single assessment task, effectively supporting enterprises' compliance strategy decisions and low-carbon process path selection for different target markets.

[0095] The implementation method is described using life cycle assessment of steel used in construction as an example.

[0096] By selecting building steel, EN 15804LCIA method, and traditional blast furnace-converter process in the above user interaction layer, modular modeling can be achieved. After importing the activity data list and performing data verification, you can proceed to the next stage.

[0097] When a user selects building steel as the research object in the interaction layer and specifies EN 15804 as the LCIA method, the system will automatically execute the following matching logic: The method library management module loads EN 15804 characteristic models (such as Global Warming Potential (GWP) and Acidification Potential (AP)) and their corresponding 16 impact categories. The dynamic modeling module uses the EN 15804 cutoff method by default (only including flows with a mass / energy percentage > 1%), but can also match physical or economic allocation rules (allocation coefficients based on different allocation methods need to be input). The data adaptation module automatically associates with a background database conforming to the EN 15804 standard (such as the Ecoinvent building industry dataset) and calibrates regional difference data. Through the above process, the system ensures that the LCIA method, modeling method, and background database are logically consistent, avoiding result deviations caused by cross-standard calculations.

[0098] Based on the EN 15804 standard, the EPD (Environmental Product Declaration) report output by the output optimization layer must disclose the following core information: Product description and functional units (clearly defining system boundaries and reference flows), Life Cycle Assessment (LCA) methodology (including data sources, allocation rules, and LCIA impact categories, such as GWP, AP, etc.), full life cycle stage results (divided into A1-C4 modules, such as raw material production, construction, use, and disposal stages), key data quality descriptions (such as uncertainty analysis or sensitivity analysis), and third-party verification information (ensuring compliance with ISO 14025 and EN 15804 compliance markings). The report must present data in a standardized manner to ensure comparability and transparency.

[0099] Based on the same inventive concept, this application provides a system for evaluating the life cycle of steel products, corresponding to the aforementioned method for evaluating the life cycle of steel products. The system includes: The user interaction layer is used to obtain the target life cycle impact assessment method, target modeling method, target background database, product type of the target steel product to be evaluated, and corresponding production process and actual production data applicable to the life cycle of the steel product being evaluated in this evaluation. The core algorithm layer is used to construct a target life cycle model instance based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process, and the actual production data. The target life cycle model instance includes a first emission inventory to be allocated. The first emission inventory is processed according to the application allocation and cutoff rules in the target modeling method to obtain a second emission inventory with a clear environmental burden attribution. Based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, a corresponding environmental impact index set is obtained. The environmental impact index set is used to evaluate the life cycle of steel products.

[0100] Furthermore, the system also includes: The output optimization layer, in response to the user's input of a horizontal comparison command, obtains the corresponding environmental impact indicator set based on the characteristic factor set in at least one other life cycle impact assessment method besides the target life cycle impact assessment method and the second emission inventory; identifies common indicators in the environmental impact indicator sets corresponding to various life cycle impact assessment methods, including the target life cycle impact assessment method, and determines the difference values ​​between various common indicators.

[0101] Since the electronic device described in this embodiment is an electronic device used to implement the information processing method in the embodiments of this application, those skilled in the art can understand the specific implementation methods and various variations of the electronic device in this embodiment based on the information processing method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any electronic device used by those skilled in the art to implement the information processing method in the embodiments of this application falls within the scope of protection of this application.

[0102] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0106] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0107] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for evaluating the life cycle of steel products, characterized in that, The method includes: Obtain the target life cycle impact assessment method, target modeling method, target background database, product type of the target steel product to be evaluated, and corresponding production process flow and actual production data applicable to the life cycle of steel products in this evaluation; Based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process flow, and the actual production data, a target life cycle model instance is constructed, which includes a first emission inventory to be allocated. The first emission inventory is processed according to the application allocation and cutoff rules in the target modeling method to obtain a second emission inventory with a clear environmental burden attribution. Based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, a corresponding environmental impact index set is obtained, which is used to evaluate the life cycle of steel products.

2. The method for evaluating the life cycle of steel products as described in claim 1, characterized in that, Obtain the target life cycle impact assessment method, target modeling method, target background database, product type of the target steel product to be evaluated, and corresponding production process flow and actual production data applicable to this evaluation of the steel product life cycle, including: Receive a first selection instruction from the user, the first selection instruction including a target life cycle impact assessment method applicable to the life cycle of steel products in this evaluation; The target modeling method and target background database corresponding to the target life cycle impact assessment method are determined from the pre-defined relationships between the life cycle impact assessment method, modeling method, and background database. Receive a second selection instruction input by the user, the second selection instruction including the product type of the target steel product to be evaluated and the corresponding production process flow and production process parameters; Receive the actual production data of the target steel product.

3. The method for evaluating the life cycle of steel products as described in claim 1, characterized in that, Based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process flow, and the actual production data, a target life cycle model instance is constructed, including: Based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process flow, and the actual production data, a basic life cycle model instance is constructed. Determine whether the source tags of all upstream background data requests in the basic lifecycle model instance are consistent with the target background database to obtain the data source verification result; If the data source verification result is inconsistent, the upstream background data request will be redirected to the target background database until the source tags of all upstream background data requests in the obtained basic lifecycle model instance are consistent with the target background database. The target lifecycle model instance is obtained by replacing the general default data in the basic lifecycle model instance with the regional dataset in the target background database.

4. A method for evaluating the life cycle of steel products as described in claim 1 or 3, characterized in that, The first emissions inventory was obtained through the following steps: Traverse the foreground data and linked background data of all process units in the target life cycle model instance, convert the foreground data and background data into the mass of various environmental emissions and the amount of resources consumed, and obtain the first emission inventory based on the mass of various environmental emissions and the amount of resources consumed.

5. The method for evaluating the life cycle of steel products as described in claim 1, characterized in that, Application allocation and expiration rules include symbiotic product allocation rules and application expiration rules; The first emission inventory is processed according to the application allocation and cutoff rules in the target modeling method to obtain a second emission inventory with a clear environmental burden attribution, including: For the symbiotic products in the target steel production, the environmental burden of each process is allocated among the symbiotic products according to the symbiotic product allocation rules. Based on the application cutoff rules, the first emission list is filtered to obtain a second emission list with a clear environmental burden attribution.

6. The method for evaluating the life cycle of steel products as described in claim 1, characterized in that, The characteristic factor set includes the relative contribution values ​​of different emission substances to a specific type of environmental problem; Based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, a corresponding environmental impact indicator set is obtained, including: Multiply each emission substance in the second emission inventory by its corresponding relative contribution value to obtain the corresponding set of environmental impact indicators.

7. The method for evaluating the life cycle of steel products as described in claim 1, characterized in that, After obtaining the corresponding environmental impact indicator set based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, the method further includes: An environmental product declaration report in a preset format is generated based on the set of environmental impact indicators.

8. The method for evaluating the life cycle of steel products as described in claim 1, characterized in that, After obtaining a second emissions inventory with clearly defined environmental burden attribution, the method further includes: In response to the user's input of a horizontal comparison command, a corresponding set of environmental impact indicators is obtained based on the characteristic factor set in at least one other life cycle impact assessment method besides the target life cycle impact assessment method and the second emission inventory; Identify common indicators in the environmental impact indicator sets corresponding to various life cycle impact assessment methods, including the target life cycle impact assessment method, and determine the differences between various common indicators.

9. A system for evaluating the life cycle of steel products, characterized in that, Corresponding to the method for evaluating the life cycle of steel products according to any one of claims 1-8, the system comprises: The user interaction layer is used to obtain the target life cycle impact assessment method, target modeling method, target background database, product type of the target steel product to be evaluated, and corresponding production process and actual production data applicable to the life cycle of the steel product being evaluated in this evaluation. The core algorithm layer is used to construct a target life cycle model instance based on the target life cycle impact assessment method, the target modeling method, the target background database, the product type, the production process, and the actual production data. The target life cycle model instance includes a first emission inventory to be allocated. The first emission inventory is processed according to the application allocation and cutoff rules in the target modeling method to obtain a second emission inventory with a clear environmental burden attribution. Based on the characteristic factor set in the target life cycle impact assessment method and the second emission inventory, a corresponding environmental impact index set is obtained. The environmental impact index set is used to evaluate the life cycle of steel products.

10. A system for evaluating the life cycle of steel products as described in claim 9, characterized in that, The system also includes: The output optimization layer, in response to the user's input of a horizontal comparison command, obtains the corresponding environmental impact indicator set based on the characteristic factor set in at least one other life cycle impact assessment method besides the target life cycle impact assessment method and the second emission inventory; identifies common indicators in the environmental impact indicator sets corresponding to various life cycle impact assessment methods, including the target life cycle impact assessment method, and determines the difference values ​​between various common indicators.

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