Industrial furnace oxygen-enriched combustion full life cycle carbon footprint evaluation regulation and control method and system

Abstract

The invention discloses an industrial furnace oxygen-enriched combustion full-life-cycle carbon footprint evaluation regulation and control method and system, and the method comprises the steps: constructing an industrial furnace oxygen-enriched combustion system full-life-cycle carbon footprint data model, and the full life cycle comprises an equipment manufacturing stage, a transportation and installation stage, an operation stage, a maintenance stage and a scrapping stage; establishing a unique carbon footprint identification code for each physical component of the oxygen-enriched combustion system of the industrial furnace, and recording and accumulating corresponding carbon footprint increments in each stage of a full life cycle through the unique carbon footprint identification code to form a complete carbon footprint life track of the physical component; and for each physical component, establishing a refined accounting model based on emission, dynamically calculating and accumulating carbon footprints according to corresponding source data, monitoring data and consumption records in each stage of a full life cycle, and forming a complete emission data chain of the physical component. According to the invention, the whole-process transparency, precision and traceability of carbon emission data can be realized.

Description

Technical Field

[0001] This invention relates to the field of carbon footprint management technology, and in particular to a method and system for assessing and controlling the carbon footprint of oxygen-enriched combustion in industrial furnaces throughout its entire life cycle. Background Technology

[0002] As typical high-energy-consuming and high-emission industrial equipment, the carbon footprint management of industrial furnaces and kilns is directly related to the accuracy of corporate carbon accounting and the achievement of emission reduction targets, and is of critical significance in the context of carbon peaking and carbon neutrality. Carbon emissions run through the entire life cycle of equipment, from raw material procurement, component manufacturing, transportation and installation, long-term operation, routine maintenance to final scrapping, involving numerous links and stakeholders. Current management methods mainly rely on periodic reporting or manual statistics, resulting in emission data scattered across different enterprises, systems, and time points, with highly heterogeneous sources. Equipment manufacturers provide emissions during the manufacturing stage, construction units record emissions during transportation and installation, operating companies collect emissions from fuel and electricity consumption through control systems, maintenance records are scattered on paper or in separate forms, and scrapping data is often missing. This fragmentation makes it difficult for subsequent stages to directly obtain and continue the emissions generated in the previous stage, and data is prone to breakage or double counting at the stage transition.

[0003] Currently, it is difficult to continuously track and accumulate component-level emissions. Taking steel and refractory materials as examples, a refractory brick has initial emissions when it is produced from the smelter. During transportation to the furnace site and installation, new emissions are added. After being put into operation, due to the high-temperature environment, it gradually wears down, and the performance degradation will increase fuel consumption under the same operating conditions, thus generating additional emissions. Subsequent replacement and maintenance will release residual emissions when the old bricks are scrapped. These emission increments generated by the same component at different stages cannot be continuously accumulated along the actual flow path of the component because of the lack of a unified identification and transmission mechanism. Ultimately, the carbon footprint of the entire furnace can only be estimated at a rough system level, and the emission changes and degradation effects within the component's life cycle are completely ignored.

[0004] How to establish a continuous transmission and accumulation mechanism for emission data throughout the entire flow of components from manufacturing to scrapping, so as to achieve accurate tracking of carbon footprint throughout the entire life cycle, has become a key issue facing carbon management of oxygen-enriched combustion systems in industrial furnaces. Summary of the Invention

[0005] This invention provides a method and system for assessing and controlling the carbon footprint of oxygen-enriched combustion in industrial furnaces throughout its entire life cycle, aiming to achieve full transparency, accuracy, and traceability of carbon emission data.

[0006] In a first aspect, the method for assessing and controlling the carbon footprint of oxygen-enriched combustion throughout the entire life cycle of industrial furnaces provided by this invention mainly includes: Construct a full life cycle carbon footprint data model for industrial furnace oxygen-enriched combustion systems, and establish standardized data acquisition interfaces and data formats. The full life cycle includes the equipment manufacturing stage, transportation and installation stage, operation stage, maintenance stage, and scrapping stage. A unique carbon footprint identifier is established for each physical component of the oxygen-enriched combustion system of the industrial furnace. The corresponding carbon footprint increment is recorded and accumulated at each stage of the entire life cycle through the unique carbon footprint identifier, forming the complete carbon footprint life trajectory of the physical component. A unified carbon footprint data integration platform is built to obtain scattered carbon footprint-related data from multiple heterogeneous data sources and integrate them into a unified data model through data cleaning, format conversion, timestamp alignment, and unit standardization. For each physical component, a refined accounting model based on emissions is established. The carbon footprint is dynamically calculated and accumulated at each stage of the entire life cycle based on corresponding source data, monitoring data, and consumption records, forming a complete emissions data chain for the physical component.

[0007] Furthermore, a unique carbon footprint identifier is established for each physical component of the oxygen-enriched combustion system of the industrial furnace. The corresponding carbon footprint increments are recorded and accumulated at each stage of the entire life cycle using this unique carbon footprint identifier, forming a complete carbon footprint lifecycle for the physical component, including: During the equipment manufacturing stage, the material procurement list and supplier carbon emission declaration data are extracted from the ERP system. The initial carbon footprint value is calculated by multiplying the material quality by the unit emission intensity and recorded to the unique carbon footprint identifier. During the transportation and installation phase, electricity consumption and diesel usage records are obtained from the construction management system. The incremental carbon emissions of logistics are calculated based on transportation distance, load capacity, and type of transportation vehicle, and then added to the unique carbon footprint identifier. During operation, the oxygen concentration and power consumption data of the air separation oxygen production unit, the fuel consumption, flue gas composition and flue gas flow data of the oxygen-enriched combustion industrial kiln are read in real time from the DCS system. The direct carbon emissions generated by fuel combustion and power consumption are calculated and uploaded to the control center. The operation carbon footprint is accumulated to the unique carbon footprint identifier code to form dynamic tracking of the carbon footprint during operation. During the maintenance phase, spare parts replacement ledgers and consumables requisition records are imported from the maintenance system to quantify the frequency of spare parts replacement and the additional emissions caused by energy efficiency decline due to performance degradation, and these are accumulated to the unique carbon footprint identifier. During the end-of-life phase, the energy consumed by dismantling equipment and the carbon emissions reduced by recycling materials are calculated and recorded in the unique carbon footprint identifier.

[0008] Furthermore, the construction of a unified carbon footprint data integration platform acquires scattered carbon footprint-related data from multiple heterogeneous data sources, and integrates it into a unified data model through data cleaning, format conversion, timestamp alignment, and unit standardization, including: During the equipment manufacturing stage, material procurement lists and supplier carbon emission declaration data are extracted from the ERP system; During the transportation and installation phase, records of electricity consumption and diesel usage are obtained from the construction management system. During the operation phase, by using the oxygen concentration and power consumption data in the air separation oxygen production unit, and simultaneously acquiring the fuel consumption, flue gas composition and flue gas flow data in the oxygen-enriched combustion industrial kiln, the direct carbon emissions generated by fuel combustion and power consumption are calculated, and the direct carbon emissions are uploaded to the control center. The operation carbon footprint is accumulated to the unique carbon footprint identifier code to form dynamic tracking of the carbon footprint during the operation phase. During the maintenance phase, import spare parts replacement logs and consumable requisition records from the maintenance system; Redundant and abnormal data are removed through data cleaning, data structure is unified through format conversion, cross-stage data synchronization is achieved through timestamp alignment, and emission units are standardized to unify the emission dimensions, thus integrating the scattered carbon footprint-related data into a unified data model.

[0009] Furthermore, a refined emission accounting model is established for each physical component. This model dynamically calculates and accumulates the carbon footprint at each stage of the entire life cycle based on corresponding source data, monitoring data, and consumption records, forming a complete emission data chain for the physical component, including: Source data is obtained from the blast furnace carbon emission coefficient in the steel smelting stage, the fuel consumption in the refractory material sintering process, and the carbon emission factor of electricity generated from the manufacture of oxygen-enriched equipment. During the equipment manufacturing stage, the initial carbon footprint value is calculated by multiplying the material mass by the unit emission intensity. During the transportation and installation phase, the carbon emission increment is calculated based on the transportation distance, load capacity, and type of transportation vehicle, combined with construction energy consumption records. During the operation phase, the direct carbon emissions are accumulated to calculate the operating carbon footprint by real-time monitoring of oxygen concentration and power consumption data in the air separation oxygen production unit, fuel consumption in the oxygen-enriched combustion industrial kiln, and flue gas emission concentration. During the maintenance phase, quantify the frequency of spare parts replacement and the additional emissions caused by performance degradation; During the disposal phase, the energy consumed in dismantling and the carbon emissions reduced by recycling materials are calculated, forming a complete data chain of emissions from raw materials to final dismantling of the physical components.

[0010] Furthermore, the unique carbon footprint identifier is recorded and accumulated at each stage of the entire life cycle, including: The unique carbon footprint identifier is associated with the origin of the physical component materials and the processing technology, and the initial carbon footprint value is recorded during the equipment manufacturing stage; The unique carbon footprint identifier is associated with the incremental carbon footprint generated during the transportation and installation phases of logistics and construction. The unique carbon footprint identifier continuously records the carbon footprint of energy consumption associated with the operation phase. The unique carbon footprint identifier tracking and maintenance phase leads to component performance degradation, resulting in additional carbon emissions; The unique carbon footprint identifier records the carbon footprint of the dismantling and recycling process during the end-of-life stage.

[0011] Furthermore, the unified carbon footprint data integration platform acquires dispersed carbon footprint-related data from multiple heterogeneous data sources, including: Obtain material procurement and supplier carbon emission declaration data from the materials management system; To acquire electricity consumption and fuel usage records for energy metering systems; Acquire combustion parameters and energy consumption data for the production execution system; The equipment monitoring system reads real-time data on flue gas composition and oxygen concentration. Import spare parts replacement and consumables requisition records into the maintenance management system.

[0012] Furthermore, the dynamic calculation and accumulation of the carbon footprint at each stage of the entire life cycle based on corresponding source data, monitoring data, and consumption records includes: Calculate the initial carbon footprint value during the equipment manufacturing stage based on source data; The carbon emission increment during the transportation and installation phase is calculated based on transportation distance, load capacity, type of transportation vehicle, and construction records. The carbon footprint during operation is calculated based on real-time monitoring data of oxygen concentration and power consumption in the air separation oxygen production unit, fuel consumption, flue gas composition and flue gas flow rate data in the oxygen-enriched combustion industrial kiln. Quantify the additional emissions during the maintenance phase based on the performance degradation caused by spare parts replacement frequency; The carbon footprint at the end-of-life stage is calculated based on energy consumption from dismantling and emission reduction from material recycling.

[0013] Secondly, the industrial furnace oxygen-enriched combustion full life cycle carbon footprint assessment and control system provided by the present invention includes: The first construction module is used to build a full life cycle carbon footprint data model of an industrial furnace oxygen-enriched combustion system. The full life cycle includes the equipment manufacturing stage, transportation and installation stage, operation stage, maintenance stage, and scrapping stage. The identification code establishment module is used to establish a unique carbon footprint identification code for each physical component of the industrial furnace oxygen-enriched combustion system. The module records and accumulates the corresponding carbon footprint increments at each stage of the entire life cycle through the unique carbon footprint identification code, forming the complete carbon footprint life trajectory of the physical component. The second building module is used to build a unified carbon footprint data integration platform. It obtains scattered carbon footprint-related data from multiple heterogeneous data sources and integrates them into a unified data model through data cleaning, format conversion, timestamp alignment and unit standardization. The refined accounting module is used to establish a refined accounting model based on emissions for each physical component. It dynamically calculates and accumulates the carbon footprint at each stage of the entire life cycle based on the corresponding source data, monitoring data and consumption records, forming a complete emissions data chain for the physical component.

[0014] Furthermore, the identifier code establishment module includes: The extraction unit is used to calculate the initial carbon footprint value by multiplying the material mass by the unit emission intensity. The acquisition unit is used to calculate the incremental carbon emissions of logistics based on the transportation distance, load capacity and transportation vehicle type, and accumulate it to the unique carbon footprint identifier. The reading unit is used to obtain the direct carbon emissions generated by fuel combustion and electricity consumption through the calculation module, and accumulate the operating carbon footprint to the unique carbon footprint identifier code; An import unit is used to quantify the frequency of spare parts replacement and the additional emissions caused by energy efficiency decline due to performance degradation, and to accumulate them into the unique carbon footprint identifier. The calculation unit is used to calculate the energy consumption of the dismantling equipment and the carbon emission reduction of recycled materials, and record it to the unique carbon footprint identifier.

[0015] Furthermore, the refined accounting module includes: The initial carbon footprint calculation unit is used to calculate the initial carbon footprint value by multiplying the material mass by the unit emission intensity. The carbon emission increment calculation unit is used to calculate the carbon emission increment based on transportation distance, load capacity, and transportation vehicle type, combined with construction energy consumption records. The carbon footprint operation unit is used to read oxygen concentration and power consumption data from the air separation oxygen production unit, fuel consumption, flue gas composition and flue gas flow data from the oxygen-enriched combustion industrial kiln in real time from the DCS system. It calculates the direct carbon emissions generated by fuel combustion and power consumption, uploads the direct carbon emissions to the control center, and accumulates the operation carbon footprint to the unique carbon footprint identifier code to form dynamic tracking of carbon footprint during the operation phase. Additional emissions calculation unit, used during maintenance phases to quantify the frequency of spare parts replacement and additional emissions caused by performance degradation; The emission data chain forming unit is used to calculate the energy consumed in dismantling and the reduction of carbon emissions by recycling materials during the scrapping stage, forming a complete emission data chain of the physical component from raw materials to final dismantling.

[0016] The technical solutions provided by the embodiments of the present invention have the following beneficial effects: This invention addresses the unique business scenario of carbon emission data in industrial furnace oxy-fuel combustion systems, which is scattered across different stages such as equipment manufacturing, transportation and installation, operation, maintenance, and scrapping, with heterogeneous source systems and difficulties in finely tracking component-level emissions. It achieves continuous cumulative tracking of carbon footprints throughout the entire lifecycle by assigning a unique carbon footprint identifier to each steel, refractory material, and oxy-fuel equipment component. Simultaneously, it constructs a unified carbon footprint data integration platform that automatically extracts, cleans, and integrates multi-source heterogeneous data from ERP, construction management, DCS, and maintenance systems. Standardized acquisition interfaces and refined accounting models are established to dynamically calculate emission increments at each stage and additional emissions caused by performance degradation, ultimately forming a complete carbon footprint lifecycle map of the component. This invention achieves full-process transparency, accuracy, and traceability of carbon emission data, providing reliable technical support for low-carbon operation, carbon emission accounting, and emission reduction optimization of industrial furnace oxy-fuel combustion systems. Attached Figure Description

[0017] Figure 1 A flowchart of the method for assessing and controlling the carbon footprint of oxygen-enriched combustion throughout the entire life cycle of industrial furnaces provided in this embodiment of the invention.

[0018] Figure 2 The flowchart illustrates the method for assessing and controlling the carbon footprint of oxygen-enriched combustion throughout the entire life cycle of industrial furnaces, as provided in this embodiment of the invention.

[0019] Figure 3 This is a schematic diagram of the functional modules of the industrial furnace oxygen-enriched combustion full life cycle carbon footprint assessment and control system according to an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and thoroughly described below with reference to the accompanying drawings. The described embodiments are merely some embodiments of the present invention.

[0021] like Figures 1-3 As shown in the embodiments of the present invention, the method for assessing and controlling the carbon footprint of oxygen-enriched combustion in industrial furnaces throughout its entire life cycle may specifically include the following steps: Step S100: Construct a full life-cycle carbon footprint data model for industrial furnace oxygen-enriched combustion systems and establish standardized data acquisition interfaces and data formats.

[0022] In this embodiment, a full life-cycle carbon footprint data model is constructed, covering equipment manufacturing, operation and maintenance, and dismantling and recycling. This includes material carbon footprint data collection during the equipment manufacturing stage, energy consumption data collection during the oxygen-enriched equipment installation and commissioning stage, real-time combustion data collection during daily operation, and maintenance material consumption data collection during periodic maintenance. A standardized data collection interface and storage format covering both time and space dimensions are established.

[0023] For the collection of carbon footprint data for the entire lifecycle of oxy-fuel combustion in industrial furnaces, the process begins with acquiring carbon emission data related to materials during the equipment manufacturing stage. This involves recording the purchase quantity of each raw material and the unit emission intensity data provided by the supplier. Simultaneously, during the installation and commissioning phase of the oxy-fuel equipment, electricity consumption and fuel usage records are collected to form an initial energy consumption data list. This data is then categorized and organized according to pre-established time and spatial dimensions to generate a preliminary carbon footprint dataset. Based on this preliminary carbon footprint dataset, during the daily operation phase, combustion-related data such as fuel flow rate, oxygen concentration, and flue gas composition are acquired through real-time monitoring devices. This real-time data undergoes timestamp alignment and unit standardization to ensure data format consistency. The processed operational data is then integrated with the data sets from the manufacturing and installation phases to construct a comprehensive carbon footprint data record covering multiple stages. Finally, during the periodic maintenance phase, detailed data on spare parts replacement and consumable requisition are obtained from maintenance records. Combined with maintenance frequency and material consumption, the additional carbon emissions from maintenance are calculated. This data is then added to the previous comprehensive records, forming a complete carbon footprint data chain encompassing the entire process of manufacturing, installation, operation, and maintenance. For the complete carbon footprint data chain, a standardized data acquisition interface and storage format are established to ensure data traceability and consistency. Data is classified and saved through a unified storage structure to cover information needs in both time and space dimensions, ultimately realizing the construction of a carbon footprint data model for the entire life cycle of oxygen-enriched combustion in industrial furnaces.

[0024] For the collection of carbon footprint data throughout the entire lifecycle of oxygen-enriched combustion in industrial furnaces, carbon emission data related to materials is obtained from the equipment manufacturing stage. By recording the purchase quantity of each raw material and the unit emission intensity data provided by the supplier, the source of emissions can be effectively traced, thus providing a reliable foundation for subsequent integration. This approach improves data accuracy and avoids errors caused by later corrections.

[0025] Specifically, during the installation and commissioning phase of oxygen-enriched equipment, electricity consumption and fuel usage records are collected to form an initial energy consumption data list. This data is then categorized and organized according to pre-established time and spatial dimensions to generate a preliminary carbon footprint dataset. This is beneficial for identifying early-stage emission hotspots and promoting overall process optimization. For example, in practical operation, for the manufacturing of steel components, recording the emission intensity data per ton of steel purchased directly quantifies the initial carbon footprint, ensuring seamless integration with electricity records from the installation phase, thereby supporting full-chain traceability.

[0026] Based on the initial carbon footprint dataset, combustion-related data such as fuel flow, oxygen concentration, and flue gas composition are acquired through real-time monitoring devices during routine operation. Timestamp alignment and unit standardization of this real-time data ensure data format consistency. The processed operational data is then integrated with the datasets from the previous manufacturing and installation phases. This construction of a comprehensive carbon footprint data record covering multiple phases is beneficial for dynamically monitoring emission changes and improving the speed of regulatory response.

[0027] The timestamp alignment process involves unifying time records from different systems to the same time zone standard to avoid data discrepancies, while unit standardization converts various units of measurement into a unified format, such as standard coal equivalent for fuel consumption. This integration creates a continuous data stream, supporting accurate assessments. For example, in real-time monitoring of oxygen concentration, if processed data shows that concentration fluctuations lead to increased emissions, it can be promptly correlated with material data from the manufacturing stage to reveal potential efficiency issues, thereby enhancing the consistency of lifecycle management.

[0028] For comprehensive carbon footprint data recording, detailed data on spare parts replacement and consumables usage are obtained from maintenance records during periodic overhauls. Combined with maintenance frequency and material consumption, the additional carbon emissions from overhauls are calculated. Adding this data to previous comprehensive records creates a complete carbon footprint data chain encompassing the entire process of manufacturing, installation, operation, and overhaul. This approach helps quantify the impact of maintenance on total emissions and avoids overlooking hidden carbon sources. Specifically, calculating additional emissions considers spare parts replacements, such as the consumption of refractory materials, and estimates the cumulative impact using frequency data. This ensures that the supplementary data matches previous records, improving the model's completeness. For instance, replacing burner components during overhauls and recording the emission intensity of consumables such as new materials can supplement operational data, revealing how maintenance affects overall efficiency and strengthening the continuity of the data chain.

[0029] Step S200: Establish a unique carbon footprint identifier for each physical component of the industrial furnace oxygen-enriched combustion system, and record and accumulate the corresponding carbon footprint increments at each stage of the entire life cycle through the unique carbon footprint identifier to form the complete carbon footprint life trajectory of the physical component.

[0030] The oxygen-enriched combustion system of the industrial furnace establishes a unique carbon footprint identification code for each batch of steel and refractory oxygen-enriched equipment components. During the equipment manufacturing stage, it records the material source, processing technology and initial carbon footprint value of each component. During the transportation and installation stage, it accumulates the carbon footprint increment generated by logistics and construction. During the operation stage, it continuously records the carbon footprint of energy consumption associated with the component. During the maintenance stage, it tracks the additional carbon emissions caused by the performance degradation of the component. During the scrapping stage, it records the carbon footprint of the dismantling and recycling process, forming a complete carbon footprint life trajectory map for each physical entity.

[0031] A unique carbon footprint identifier is generated for each batch of steel, refractory materials, and oxygen-enriched equipment components. This identifier is associated with the component's material origin and processing technology. During the manufacturing phase, initial carbon emission coefficients and processing technology data are obtained from the material origin and recorded to form an initial carbon footprint value. During the transportation and installation phase, the carbon emission increments generated by logistics distance and construction energy consumption are added to the initial carbon footprint value, updating the carbon footprint data corresponding to the unique carbon footprint identifier to form a cumulative carbon footprint value after transportation and installation. During the operation phase, carbon emissions generated by fuel consumption and oxygen enrichment energy consumption associated with the component are continuously recorded based on the cumulative carbon footprint value, and the operational carbon footprint data corresponding to the unique carbon footprint identifier is updated in real time to form a dynamic carbon footprint value for the operation phase. During the maintenance and scrapping phases, additional carbon emissions caused by component performance degradation and carbon emissions and emission reductions during dismantling and recycling are tracked based on the dynamic carbon footprint value, and fully recorded to the unique carbon footprint identifier to form a complete carbon footprint lifecycle map for each component from manufacturing to scrapping.

[0032] For example, in an oxygen-enriched combustion system for industrial furnaces, when generating a unique carbon footprint identifier for steel components, the source data of iron ore and the processing parameters of the electric arc furnace are first obtained from the smelter. The initial value is calculated by multiplying it by the corresponding carbon emission coefficient. The benefit of doing so is to ensure the accuracy of the source data and provide a reliable basis for subsequent accumulation.

[0033] In one possible implementation, for refractory components, the identification code is linked to the origin of the silicate raw materials and the tunnel kiln sintering process, recording the initial carbon footprint value converted from fuel gas consumption. This method can accurately capture emission differences during material processing and avoid the accumulation of deviations later. Specifically, the identification code of oxygen-enriched equipment components, such as oxygen nozzles, is linked to the source of the aluminum alloy and the casting process to obtain the initial value of the carbon factor formed by electricity consumption, which is helpful in distinguishing the environmental protection levels of different suppliers.

[0034] In one possible implementation, the transportation and installation phase adds a logistical increment to the initial carbon footprint value. For example, the distance of trucking steel from Shanghai to Beijing is multiplied by a diesel emission factor, and this is combined with an updated cumulative value of electricity consumption for on-site welding. This accumulation mechanism helps reflect the carbon impact of the supply chain and promotes optimized transportation route selection. For instance, for refractory material transportation, the ocean freight distance and cement mixing energy during installation are considered, and the accumulated value forms a new value. The beneficial effect is that it visualizes the carbon contribution of the installation process and promotes the adoption of low-carbon construction technologies.

[0035] During operation, the oxygen concentration and power consumption data of the air separation oxygen production unit are read in real time from the DCS system. Simultaneously, data on fuel consumption, flue gas composition, and flue gas flow rate in the oxygen-enriched combustion industrial kiln are acquired. The direct carbon emissions generated by fuel combustion and power consumption are calculated by the calculation module and uploaded to the control center. The operational carbon footprint is accumulated and added to the unique carbon footprint identifier, forming a dynamic carbon footprint tracking system during operation. Based on the direct carbon emission data and the accumulated carbon footprint, kiln operating parameters, including oxygen partial pressure, fuel ratio, and flue gas recirculation ratio, are dynamically adjusted to reduce fuel consumption and lower direct carbon emissions.

[0036] Continuously recording fuel consumption data by accumulating carbon footprint values, such as real-time updates of carbon emissions associated with heat loss from steel linings during gasifier operation, allows for timely adjustments to combustion parameters to reduce emissions. Specifically, recording the carbon emissions generated by oxygen-enriched membranes at high temperatures is beneficial for capturing real-time fluctuations and achieving precise energy savings. For example, accumulating data on fuel natural gas consumption and flue gas concentration in oxygen-enriched equipment such as burners helps analyze operational efficiency and reduce ineffective carbon emissions.

[0037] Tracking performance degradation during maintenance, such as the additional fuel consumption and carbon emissions caused by decreased heat conduction due to steel corrosion, is recorded as dynamic values. This tracking helps predict maintenance timing and extend component life. Specifically, quantifying additional emissions from refractory material crack decay quantifies the carbon cost of spare parts replacement, promoting sustainable maintenance strategies. For example, recording additional energy consumption carbon values ​​for membrane module efficiency degradation in oxygen-enriched equipment helps optimize replacement frequency and reduce the overall footprint.

[0038] Recording the dismantling process during the end-of-life stage, such as the energy consumption from steel cutting and recycling minus the emission reduction from recycled steel, down to the identification code, is beneficial for closed-loop assessment of the entire life cycle carbon balance. Specifically, calculating carbon emissions from refractory material crushing and recycling and emission reductions from reuse incentivizes innovation in recycling technologies to enhance environmental value. For example, integrating the carbon value of metal separation from oxygen-enriched equipment dismantling with emission reductions from recycling creates a life cycle map, providing a valuable reference for full-chain carbon management in industrial furnaces.

[0039] Step S300: Build a unified carbon footprint data integration platform to obtain scattered carbon footprint-related data from multiple heterogeneous data sources, and integrate them into a unified data model through data cleaning, format conversion, timestamp alignment and unit standardization.

[0040] The industrial furnace oxygen-enriched combustion system establishes a unified carbon footprint data integration platform. It extracts material procurement lists and supplier carbon emission declarations from the ERP system during the equipment manufacturing phase. It obtains electricity consumption and diesel usage records from the construction management system during the installation and commissioning phase. It reads combustion data such as fuel flow, oxygen concentration, and flue gas composition in real time from the DCS system during daily operation. It imports spare parts replacement ledgers and consumable requisition records from the maintenance system during periodic maintenance. Through data cleaning, format conversion, timestamp alignment, and unit standardization, the dispersed carbon footprint information is integrated into a unified data model.

[0041] Material procurement lists and supplier carbon emission declarations are extracted from the Enterprise Resource Planning (ERP) system during the equipment manufacturing phase. Electricity consumption and diesel usage records are obtained from the construction management system during the installation and commissioning phase. Simultaneously, fuel flow, oxygen concentration, and flue gas composition data are read in real-time from the distributed control system during daily operation. Spare parts replacement ledgers and consumable requisition records are imported from the maintenance system during periodic maintenance. Data cleaning and format conversion are performed on the acquired material procurement lists, supplier carbon emission declarations, electricity consumption records, diesel usage records, fuel flow data, oxygen concentration data, flue gas composition data, spare parts replacement ledgers, and consumable requisition records to unify heterogeneous formats into a pre-established standardized data structure. Based on the standardized data structure after format conversion, timestamp alignment is performed to correlate related records of the same equipment or production batch in the time dimension, forming a continuous time-series data set. Unit standardization is then performed on the timestamp-aligned data set to convert all energy consumption, material quantity, and emission quantities into the same unit of measurement, ultimately integrating them into a unified data model.

[0042] For example, material procurement lists and supplier carbon emission declarations can be extracted from the enterprise resource planning system during the equipment manufacturing stage. The enterprise resource planning system is a database platform that integrates and manages enterprise resources such as procurement, production, and sales. By querying the interface, data such as steel procurement volume and carbon emission declaration documents provided by suppliers can be obtained. The carbon emission declaration documents contain emission factors in the material production process. This extraction method can ensure the integrity of the source data and lay the foundation for overall carbon footprint tracking.

[0043] In one possible implementation, electricity consumption and diesel usage records are obtained from the construction management system during the installation and commissioning phase. The construction management system is a tool for recording energy consumption during on-site operations, such as obtaining electricity meter readings and diesel generator usage logs during equipment installation. This data helps quantify the emission increases during the installation process and avoids overlooking indirect carbon sources. Specifically, fuel flow, oxygen concentration, and flue gas composition data are read in real-time from the distributed control system during daily operation. The distributed control system is an automated platform for monitoring industrial processes, collecting data such as natural gas flow meter readings and oxygen analyzer data through sensor interfaces. This real-time reading captures dynamic changes in the combustion process, improving the timeliness of assessments.

[0044] In one possible implementation, spare parts replacement logs and consumable requisition records are imported from the maintenance system during periodic overhauls. The maintenance system serves as a record database tracking equipment repairs; for example, importing logs for refractory lining replacements and lubricant requisition forms allows for the recording of additional emissions caused by maintenance, ensuring comprehensive lifecycle coverage. It's important to note that data cleaning and format conversion are performed on the acquired material procurement lists, supplier carbon emission declarations, electricity consumption records, diesel usage records, fuel flow data, oxygen concentration data, flue gas composition data, spare parts replacement logs, and consumable requisition records. Data cleaning includes removing duplicates and filling in missing values, such as cleaning duplicate entries in the procurement list and correcting outliers in fuel flow data. Format conversion involves converting formats like CSV to JSON structures. This process eliminates inconsistencies in heterogeneous data and improves integration efficiency.

[0045] One possible implementation involves uniformly converting heterogeneous formats into a pre-established standardized data structure. This standardized data structure is a template defining uniform fields such as time, quantity, and unit. For example, the kilowatt-hour field of electricity consumption records is mapped to a standard energy field. This conversion facilitates subsequent correlation and avoids data silos. Specifically, based on the standardized data structure after format conversion, timestamp alignment is performed. Timestamp alignment is achieved by synchronizing time stamps from different systems. For instance, the local time of construction records is adjusted to the UTC standard and matched with the operating data of the same equipment. This process links related records from the same equipment or the same production batch in a corresponding time dimension, forming a continuous time-series data set, which helps track the continuity of emission trends.

[0046] In one possible implementation, the timestamp-aligned dataset undergoes unit standardization, for example, converting diesel usage records in liters to standard energy equivalent joules and unifying flue gas composition from ppm to percentage. This standardization eliminates unit differences, ensuring accuracy, and ultimately integrates the data into a unified data model. This unified data model serves as a central repository for storing all carbon footprint information. This integration enables a unified carbon footprint data platform for industrial furnace oxygen-enriched combustion systems, providing a traceable basis for emissions assessment.

[0047] Step S400: Establish a refined accounting model based on emissions for each physical component. Dynamically calculate and accumulate the carbon footprint at each stage of the entire life cycle based on corresponding source data, monitoring data, and consumption records to form a complete emissions data chain for the physical component.

[0048] The industrial furnace oxygen-enriched combustion system establishes a refined emission calculation model for each component. Starting with source data such as the blast furnace carbon emission coefficient during steel smelting, fuel consumption during refractory material sintering, and the carbon emission factor from electricity generated during oxygen-enriched equipment manufacturing, the initial carbon footprint value is calculated at the equipment manufacturing stage by multiplying material mass by the unit emission intensity. During the transportation and installation stage, the incremental carbon emissions from logistics are calculated based on transportation distance, load capacity, and vehicle type. During operation, the operational carbon footprint is dynamically accumulated through real-time monitoring of fuel consumption, oxygen enrichment energy consumption, and flue gas emission concentration. During maintenance, the additional emissions resulting from the frequency of spare parts replacement and performance degradation leading to energy efficiency decline are quantified. At the end-of-life stage, the energy consumed in dismantling the equipment and the carbon emissions reduced by recycling materials are calculated, forming a complete emission data chain for each component throughout its entire lifecycle.

[0049] For each component, the carbon emission coefficient of the blast furnace during the steel smelting stage, the fuel consumption during the refractory material sintering process, and the carbon emission factor of electricity generated during the manufacturing of oxygen-enriched equipment are obtained. Unit emission intensity data is collected from the material source, and the initial carbon footprint value is determined by multiplying the material mass by the corresponding unit emission intensity. Based on the initial carbon footprint value, the incremental carbon emissions from logistics are accumulated according to transportation distance, load capacity, and transportation vehicle type. This is further accumulated by combining the construction energy consumption during the installation stage to form the cumulative carbon footprint value after installation. Using the cumulative carbon footprint value after installation as a benchmark, carbon emissions during the operation stage are dynamically accumulated by real-time monitoring of fuel consumption, oxygen enrichment energy consumption, and flue gas emission concentration. Simultaneously, the additional emissions caused by the frequency of spare parts replacement and performance degradation leading to energy efficiency decline are quantified to form the updated cumulative carbon footprint value after maintenance. Based on the updated cumulative carbon footprint value after maintenance, the energy consumed in dismantling the equipment during the scrapping stage is calculated, and the carbon emissions reduced by recycled materials are subtracted. For example, in an oxygen-enriched combustion system for industrial furnaces, the blast furnace carbon emission coefficient is obtained for each component from the steel smelting stage. This coefficient represents the carbon emissions generated per unit of steel produced by the blast furnace. The initial carbon footprint value is determined by collecting unit emission intensity data from the material source and multiplying it by the material mass. This allows for accurate tracing of source emissions, which is beneficial for identifying high-emission materials and optimizing their selection, thereby reducing the overall carbon footprint.

[0050] In one possible implementation, for fuel consumption in the refractory sintering process, the consumption of coal gas or natural gas used in the sintering furnace is considered when collecting data. A partial initial carbon footprint value is calculated by multiplying by the unit emission intensity. This helps quantify the energy consumption impact of the material processing stage and promotes the adoption of low-carbon fuels to reduce emissions during the manufacturing stage. Specifically, the carbon emission factor for electricity in oxygen-enriched equipment manufacturing is obtained from grid emission data and applied to calculate the initial carbon footprint value for equipment assembly electricity consumption. This processing integrates the carbon intensity of the electricity source and encourages the use of renewable energy in equipment manufacturing to minimize embedded carbon. For example, the incremental carbon emissions from logistics during the transportation stage are added to the initial carbon footprint value, calculated based on transportation distances such as kilometers from the factory to the site, load capacity such as component tonnage, and transportation vehicle type such as truck or train. This accurately captures emissions from the logistics stage and helps optimize transportation routes to reduce unnecessary carbon increments.

[0051] In one possible implementation, the cumulative carbon footprint after installation is further accumulated by combining energy consumption during the installation phase, such as the energy consumption of diesel generators used for welding and assembly. This accumulation ensures continuous tracking from manufacturing to deployment, which is beneficial for assessing installation efficiency and improving construction practices to reduce additional emissions. Specifically, based on the cumulative carbon footprint after installation, fuel consumption during the operation phase, such as the amount of coke burned in the furnace, is monitored in real time. Operational carbon emissions are calculated by dynamically accumulating this data. This helps to capture fluctuations in actual operation and facilitates timely adjustments to combustion parameters to improve energy efficiency. For example, oxygen enrichment energy consumption, such as the electricity usage of the air separation unit, is also monitored and dynamically accumulated to form the operational carbon footprint. This integration of multi-source data is beneficial for comprehensively assessing combustion process efficiency and reducing exhaust emissions.

[0052] In one possible implementation, the frequency of spare parts replacement during the maintenance phase, such as the number of times refractory linings are replaced annually, and the additional emissions resulting from energy efficiency decline due to performance degradation, are quantified. This quantification forms the updated cumulative carbon footprint value after the maintenance phase, revealing the impact of maintenance on the carbon footprint and contributing to extending component lifespan and reducing replacement frequency. Specifically, based on the updated cumulative carbon footprint value after the maintenance phase, the energy consumed in dismantling equipment during the end-of-life phase, such as the electricity used for cutting tools, is calculated, and the carbon emissions reduced by recycling materials, such as steel, are subtracted. This ultimately forms a complete emissions data chain. This closed-loop calculation is beneficial for promoting a circular economy and accurately assessing the carbon impact throughout the entire life cycle.

[0053] The oxygen-enriched combustion system for industrial furnaces records the material source, processing technology, and initial carbon footprint value of each component during the equipment manufacturing stage. This includes the carbon emission coefficient of the blast furnace during the steel smelting stage, the fuel consumption during the refractory sintering process, and the electricity carbon emission factor during the manufacturing of oxygen-enriched equipment, all associated with the material source and processing technology. The initial carbon footprint value is calculated by multiplying the material mass by the unit emission intensity.

[0054] For each component, the source of materials and corresponding processing technology are obtained. Carbon emission coefficients for the steel smelting stage are extracted from a pre-established blast furnace carbon emission coefficient database, corresponding fuel consumption is extracted from a refractory material sintering fuel consumption database, and corresponding electricity carbon emission factors are extracted from a database of electricity carbon emission factors for oxygen-enriched equipment manufacturing. The obtained carbon emission coefficients for the steel smelting stage, refractory material sintering fuel consumption, and electricity carbon emission factors for oxygen-enriched equipment manufacturing are multiplied by the material mass of the corresponding component to obtain the initial carbon emission component for each material. The initial carbon emission components of all materials are then summed to form the initial carbon footprint value of the component. During the equipment manufacturing stage, the component's unique identifier is associated with the material source, processing technology, and the calculated initial carbon footprint value, forming a carbon footprint data record for the component during the manufacturing stage. The associated initial carbon footprint value is stored in the data chain corresponding to the component's carbon footprint identifier for subsequent incremental carbon footprint accumulation during transportation and installation. Specifically, when obtaining the source of component materials and processing technology, the smelting information of steel from specific mining areas is first extracted from the supply chain database and matched with the blast furnace carbon emission coefficient library. This library is pre-built based on historical emission data and contains carbon emission intensity values ​​under different blast furnace types, thereby ensuring that the coefficients accurately reflect the carbon intensity of the smelting process. This can improve the accuracy of the initial carbon footprint calculation and avoid deviations caused by generalization errors.

[0055] In one embodiment, for refractory materials, the processing involves high-temperature sintering. Gas or natural gas consumption data is extracted from a fuel consumption database established through measured sintering kiln energy efficiency. Fuel consumption is calculated per unit material volume to ensure consistency with actual production, which helps quantify the carbon emission contribution of the sintering stage and promotes the reliability of life-cycle assessments. For example, for oxygen-enriched equipment, the carbon emission factor for manufacturing electricity is obtained from a regional power grid emission factor database that considers power generation structure such as the proportion of coal-fired power, thus reflecting the carbon intensity of the power source. This approach helps identify low-carbon material sources and optimize supply chain selection to reduce the overall footprint.

[0056] In one embodiment, when multiplying the extracted carbon emission coefficient by the material mass, for the steel portion, the component is obtained by multiplying the mass by the coefficient. This process ensures that each material type is calculated independently, avoiding cross-interference and improving the accuracy of subsequent accumulation. Specifically, the refractory material fuel consumption is multiplied by the mass to convert it into a carbon emission component. The consumption is based on the heat balance principle of the sintering process, i.e., fuel input minus heat loss equals effective heat utilization. This calculation reflects the energy efficiency level and improves the scientific nature of the component estimation. For example, the power factor of oxygen-enriched equipment is multiplied by the mass, and the power consumption is obtained through statistics of the power consumption in manufacturing processes such as welding and assembly. All components are accumulated to form an initial value. This accumulation method is beneficial for capturing the comprehensive emissions of multi-material composite components, ensuring that the footprint value fully covers the manufacturing stage.

[0057] When associating the unique identifier of a component with a record, the origin of the material, such as the location of the mining area, and the processing technology, such as details of continuous casting, are bound to the initial value and stored using blockchain technology. This technology ensures that the data is tamper-proof through a distributed ledger, which is beneficial for enhancing traceability and preventing the loss or forgery of manufacturing data.

[0058] In one embodiment, a manufacturing stage data record is created, which includes a timestamp and supplier verification. The timestamp marks the date the record was created, and the supplier verification is confirmed via a digital signature. This enhances data integrity and supports the auditing process. For example, an identifier such as a QR code is associated with the record for easy scanning and access, facilitating seamless integration in downstream stages such as transportation and improving the overall consistency of the carbon footprint chain.

[0059] In one embodiment, when storing the initial carbon footprint value to the data chain, a cloud database structure is used. This structure organizes data using identifiers as key-value pairs, ensuring rapid retrieval and facilitating real-time updates of transportation increments. Specifically, transportation phase increments are calculated based on distance and tool type, such as truck fuel emission factors multiplied by load mileage, and accumulated to the initial value, forming a dynamic chain. This accumulation helps capture logistical impacts and promotes end-to-end optimization. For example, construction emissions during the installation phase, such as welding power consumption, are added to the chain, ensuring that the value accumulates gradually, ultimately supporting a complete assessment and control of the carbon footprint of the oxy-fuel combustion system.

[0060] The carbon footprint increment of the industrial furnace oxygen-enriched combustion system during the transportation and installation phase is accumulated from logistics and construction. This includes calculating the logistics carbon emission increment based on transportation distance, load capacity, and vehicle type, and accumulating the carbon footprint increment by obtaining electricity consumption and diesel usage records from the construction management system.

[0061] During the transportation and installation phase, for each component of the oxy-fuel combustion system in the industrial furnace, the distance, load capacity, and specific type of transport vehicle during transportation are obtained. Using a pre-established emission factor database, the incremental carbon emissions from the logistics process are calculated, forming a preliminary logistics emission inventory. Based on this preliminary inventory, electricity consumption and diesel usage data during the installation phase are extracted from construction management records. These energy consumptions are multiplied by their corresponding carbon emission factors to obtain the incremental carbon emissions from the construction phase, which are then added to the logistics emission inventory to form a comprehensive emission inventory. The data in the comprehensive emission inventory are categorized and organized according to the unique identifier of each component. The incremental carbon emissions for each component during the transportation and installation phases are recorded separately, ensuring a one-to-one correspondence between the carbon footprint data of each component and the physical entity, generating a component-level emission detail table. Based on the component-level emission detail table, the incremental carbon footprint data from the transportation and installation phases is integrated into the full lifecycle carbon footprint record of each component for subsequent cumulative calculations during operation and maintenance phases, ensuring the completeness and traceability of the incremental carbon footprint calculation for the oxy-fuel combustion system in the transportation and installation phases. For example, during the transportation and installation phase, when acquiring the transportation distance, load capacity, and vehicle type for each component of an industrial furnace oxygen-enriched combustion system, this data can be collected in real time using a GPS tracking device. For instance, for the truck transportation of steel components from the smelter to the site, the recorded distance is hundreds of kilometers, the load capacity is tens of tons, and the vehicle is a diesel truck. The data obtained in this way helps to accurately quantify carbon emissions, avoid estimation bias, and thus improve the accuracy of carbon footprint accounting.

[0062] It should be noted that the incremental carbon emissions from logistics are calculated using a pre-established emission factor database. This database contains the unit emission intensity of different modes of transportation. For example, the emission factor for diesel trucks is based on the carbon dioxide equivalent produced by fuel combustion. The calculation process involves multiplying the distance by the load capacity and then by the emission factor to obtain incremental data, forming a preliminary logistics emission inventory. This provides a reliable basis for subsequent accumulation and ensures the continuity of overall tracking.

[0063] Specifically, when extracting electricity consumption and diesel usage data from construction management records based on the preliminary logistics emissions inventory, for example, crane operation records during the installation of oxygen-enriched equipment show electricity consumption of hundreds of kilowatt-hours and diesel usage of tens of liters, these values ​​are multiplied by the corresponding emission factors, which are the carbon intensity of the electricity source or the equivalent value of diesel combustion, to obtain the incremental carbon emissions from construction. These are then added to the inventory to form a comprehensive emissions inventory. This process is beneficial for integrating multi-source data, reducing omissions, and improving the comprehensiveness of the carbon footprint.

[0064] In one embodiment, the data for the comprehensive emission inventory is categorized and organized according to the unique identification code of each component. For example, a QR code is assigned to each refractory brick to record its transportation and installation emission values, ensuring that the data corresponds to the physical entity and generating a component-level emission detail table. This facilitates personalized tracking, avoids confusion, and improves the precision of management.

[0065] For example, when the transport and installation carbon footprint increment is integrated into the full life cycle record based on the component-level emissions schedule, such as adding the logistics and construction emissions of steel components to its chain from manufacturing to scrap for the accumulation of fuel consumption during the operation phase, this integration ensures complete and traceable accounting, helps identify high-emission links, and optimizes system design.

[0066] It should be noted that this cumulative approach can support regulatory decisions. For example, by analyzing the impact of transportation choice through detailed tables, it can encourage the use of low-emission electric vehicles and reduce the overall carbon footprint.

[0067] For example, in practical applications, for pipeline components of an oxygen-enriched combustion system, after obtaining truck transportation data and calculating the increment, the diesel fuel records for installation and welding are extracted and accumulated to ensure that the detailed list corresponds to the entity and is integrated into the life cycle record. This supports the sustainability of emissions management in multiple ways and is beneficial to the achievement of corporate compliance and environmental protection goals.

[0068] During operation, the oxygen-enriched combustion system of the industrial furnace continuously records the energy consumption carbon footprint associated with this component, including real-time reading of combustion data such as oxygen concentration, power consumption, fuel consumption, and flue gas composition from the DCS system. The system calculates the direct carbon emissions generated by fuel combustion and power consumption and accumulates the operating carbon footprint.

[0069] The distributed control system reads real-time data on oxygen concentration and power consumption from the air separation unit, as well as fuel consumption, flue gas composition, and flue gas flow rate from the oxygen-enriched combustion industrial kiln. This data is multiplied by pre-established fuel carbon emission factors and power carbon emission factors to obtain the carbon emissions per unit time. The carbon emissions per unit time are continuously accumulated according to timestamps to form a cumulative carbon footprint value for the operational phase. A unique identifier is assigned to each component to associate this cumulative carbon footprint value. Based on the cumulative carbon footprint value, and combined with real-time assessment of combustion efficiency changes in flue gas emission concentration, the carbon emissions corresponding to oxygen enrichment energy consumption are dynamically adjusted and then added back to the operational carbon footprint associated with that component. The adjusted operational carbon footprint is bound and stored with the component's unique identifier, forming a complete data chain of energy consumption carbon footprint continuously recorded by that component during operation.

[0070] For example, in an oxy-fuel combustion system for industrial furnaces, the process of reading real-time data on oxygen concentration and power consumption in the air separation unit, as well as fuel consumption, flue gas composition, and flue gas flow rate in the oxy-fuel combustion industrial furnace, from the distributed control system requires first connecting to the distributed control system via a data interface to ensure consistent data acquisition frequency and thus obtain accurate real-time parameters. Multiplying this data by pre-established carbon emission factors for electricity and fuel yields the carbon emissions per unit time. This quantifies the carbon contribution of each unit of electricity and fuel, avoiding the biases of static estimation and improving the accuracy of carbon footprint tracking.

[0071] In one possible implementation, the fuel carbon emission factor refers to the instantaneous emission calculated by multiplying the standard carbon content value of fuel types such as natural gas or coal. This provides real-time feedback, facilitating timely optimization of combustion parameters. Specifically, the electricity carbon emission factor originates from the carbon intensity of the electricity source, such as the average emission level of the power grid. The carbon emissions per unit time obtained after multiplication reflect the direct carbon impact of energy consumption, which is beneficial for identifying high-energy-consuming links. The process of continuously accumulating the carbon emissions per unit time according to timestamps to form the cumulative carbon footprint value for the operation phase relies on time-series database storage to ensure that the accumulation operation does not lose historical data. A unique identifier is assigned to each component to associate the cumulative carbon footprint value. This establishes a component-level tracking mechanism, avoids data confusion in the overall system, and thus achieves refined management.

[0072] In one possible implementation, the unique identifier could be a QR code or digital tag generated based on the component serial number. Once associated, this facilitates querying the carbon accumulation of individual components, providing data traceability and supporting subsequent auditing and optimization. The process of judging combustion efficiency changes in real time based on the accumulated carbon footprint value and flue gas emission concentration requires monitoring the ratio of carbon dioxide and carbon monoxide in the flue gas. If the ratio deviates from the standard, it indicates a decrease in efficiency. The carbon emissions corresponding to oxygen enrichment energy consumption are dynamically adjusted and then added back to the operational carbon footprint associated with that component. This approach captures dynamic variations, avoids errors caused by fixed factors, and thus improves the adaptability of carbon calculations.

[0073] Specifically, dynamic adjustments can correct energy consumption values ​​using proportional coefficients. For example, if efficiency decreases, carbon emissions can be increased. This results in a more accurate carbon footprint record, helping companies reduce overall emissions. The adjusted operational carbon footprint is then bound to a unique component identifier, creating a complete data chain of energy consumption carbon footprint continuously recorded during the component's operation. Blockchain or cloud databases ensure this binding is tamper-proof. This builds a persistent data chain, facilitating full lifecycle integration and supporting sustainable decision-making.

[0074] In one possible implementation, the data chain can be integrated with other stages, such as maintenance, after the storage is bound. This can bring about a technical effect of cross-stage consistency and ultimately strengthen the integrity of the carbon footprint.

[0075] The oxygen-enriched combustion system of the industrial furnace tracks the additional carbon emissions caused by component performance degradation during the maintenance phase. This includes importing spare parts replacement ledgers and consumable requisition records from the maintenance system to quantify the additional emissions caused by the energy efficiency decline due to spare parts replacement frequency and performance degradation.

[0076] Import spare parts replacement logs and consumable requisition records from the maintenance system, recording the replacement time, spare parts type, and related changes in operating parameters before and after the replacement for each component. Determine the component's performance degradation based on these changes, obtaining the corresponding increases in fuel consumption and oxygen enrichment energy consumption. Multiply these increases by their respective carbon emission factors to obtain the additional carbon emissions caused by performance degradation. Add these additional carbon emissions to the component's carbon footprint record during the maintenance phase, forming a complete data chain of additional emissions during the maintenance phase.

[0077] In one embodiment, the process of importing spare parts replacement ledgers and consumable requisition records from the maintenance system involves directly extracting structured data. For example, for burner components in an oxygen-enriched combustion system of an industrial furnace, the replacement time (e.g., twice a year), the type of spare parts replaced (e.g., ceramic nozzles), and the changes in associated operating parameters before and after replacement (e.g., temperature stability decreasing from 95% to 85%) can be recorded. This can accurately capture the specific impact of maintenance activities, thereby providing a reliable basis for subsequent performance evaluation and improving the accuracy of carbon footprint tracking.

[0078] In one possible implementation, in the step of determining the extent of component performance degradation based on changes in operating parameters before and after replacement, for burner components, if the fuel efficiency was 90% before replacement and dropped to 80% due to wear after replacement, the increase in fuel consumption corresponding to the degree of energy efficiency degradation, such as an additional 5% of fuel consumption per day, and the increase in oxygen enrichment energy consumption, such as an additional 10% of electricity usage, can be obtained by comparing these parameters. This method helps to quantify hidden losses, ensure more comprehensive carbon emission calculations, and thus optimize maintenance strategies to reduce unnecessary energy waste.

[0079] In one embodiment, the operation of multiplying the increase in oxygen enrichment energy consumption and the increase in fuel consumption by the corresponding carbon emission factors, such as multiplying the increase in oxygen enrichment energy consumption by the electricity carbon emission factor to obtain a portion of the additional emissions, and adding the increase in fuel consumption by the natural gas carbon emission factor to obtain another portion, thus synthesizing the additional carbon emissions caused by performance degradation, is beneficial to forming traceable emission data and supporting enterprises in making low-carbon transformation decisions.

[0080] In one possible implementation, the additional carbon emissions are added to the carbon footprint record of the component during the maintenance phase. For the entire combustion system, if the additional emissions of a single component are 50 tons of CO2 equivalent per year, the addition forms a complete data chain of additional emissions during the maintenance phase. This accumulation mechanism can connect historical records with real-time data, which is beneficial for building a full life cycle carbon footprint view, helping to identify high-emission links and promote sustainable improvement.

[0081] In one embodiment, the process from importing records to determining the attenuation magnitude is closely linked because the imported parameters before and after replacement are directly used for attenuation calculation. For example, after the burner replacement record shows parameter changes, the specific increment of energy efficiency reduction can be derived. This helps to avoid data isolation and ensures that the output of each link becomes the input of the next, thereby strengthening the logical consistency of the overall tracking.

[0082] In one possible implementation, the additional emissions after multiplying by the carbon emission factor are related to the accumulation step in that the quantified value generated by the former is directly added to the record. For example, the emissions calculated from the fuel increment are seamlessly integrated into the component's carbon footprint, thus forming a continuous data chain. This is beneficial for companies to audit their carbon reduction performance and comply with environmental standards.

[0083] The oxygen-enriched combustion system of the industrial furnace records the carbon footprint of the dismantling and recycling process during the scrapping stage, including calculating the carbon emissions reduced by the energy consumed by the dismantling equipment and the recovered materials, forming the complete emission data chain.

[0084] During the decommissioning phase of an industrial furnace oxy-fuel combustion system, the dismantling process begins by acquiring energy data related to the energy consumed during equipment dismantling. This includes the electricity, fuel, and energy consumption records of related machinery. These energy consumptions are then categorized and statistically analyzed to create an energy consumption list for the dismantling process. For each energy source in this list, the carbon emissions are calculated. Based on a pre-established energy carbon emission factor database, the consumption amount is multiplied by the corresponding factor to obtain the total carbon emissions for the dismantling phase. After dismantling, the processing of recycled materials involves acquiring data on the types and weights of the recycled materials. Combined with a pre-established carbon reduction factor table for material recycling, the carbon emission reduction resulting from the recycling process is calculated, generating carbon reduction data for the recycling stage. Finally, the total carbon emissions data from the dismantling phase and the carbon reduction data from the recycling phase are combined to generate the net carbon emissions value for the decommissioning phase. This data is then incorporated into the complete emissions data chain of the industrial furnace oxy-fuel combustion system, ensuring traceability of the carbon footprint throughout the entire process from dismantling to recycling.

[0085] For example, during the dismantling of an oxy-fuel combustion system in an industrial furnace during its decommissioning phase, data on the energy consumed by the dismantling equipment can be obtained by deploying a sensor network. These sensors monitor electricity usage and fuel consumption in real time. For instance, when dismantling an oxy-fuel combustion furnace, the electricity consumed by the electric cutting machine and the fuel consumed by the diesel generator can be recorded. By classifying and statistically analyzing this data, an energy consumption list can be formed. This helps to accurately track the details of energy use, thereby providing a reliable basis for subsequent carbon emission calculations, which is beneficial to improving the accuracy of carbon footprint assessment and supporting environmental decision-making.

[0086] In one possible implementation, the calculation of carbon emissions for each energy source in the resulting energy consumption inventory relies on a pre-established database of energy carbon emission factors. This database contains emission factors for various energy types, such as the electricity factor based on the average emission level of the power grid, and the fuel factor considering combustion efficiency. The total carbon emissions data for the dismantling phase are obtained by multiplying the consumption by the factors. For example, the total data is formed by multiplying the electricity consumption by its factors and then adding the fuel portion. The purpose of this method is to quantify hidden emissions, which is helpful in identifying high-emission links and optimizing the dismantling process to reduce the overall carbon footprint.

[0087] It should be noted that, after dismantling, the processing of recycled materials involves obtaining data on the types and weights of the materials using weighing equipment and a sorting system. This is combined with a pre-established carbon emission reduction factor table for material recycling, which lists the emission reduction potential of different materials such as steel or refractory materials. The carbon emission reduction data for the recycling process is calculated by multiplying the amount of recycled materials by the emission reduction factor. For example, when recycling steel, the reduction value is obtained by multiplying its weight by the emission reduction factor. The rationale for doing this is to acknowledge the positive impact of recycling, which helps to balance the net emissions in the end-of-life stage and encourages the recycling of materials.

[0088] For example, the process of aggregating the total carbon emission data of the dismantling stage and the carbon emission reduction data of the recycling stage to generate a net carbon emission value involves a data integration platform. This platform automatically deducts the emission reduction amount to obtain the net value and incorporates it into the complete emission data chain of the system.

[0089] In one possible implementation, the energy consumption inventory is not limited to electricity and fuel, but can be extended to the energy consumption records of mechanical equipment, such as the operating time of hydraulic presses. This expansion enhances the comprehensiveness of the inventory, supporting more refined carbon emission calculations, helping to identify potential energy-saving opportunities, and complementing recycling data to form a closed-loop assessment.

[0090] It should be noted that maintaining the pre-established energy carbon emission factor database involves periodically updating factor values ​​to reflect technological advancements, such as adjusting the power factor when the grid shifts to renewable energy. This helps maintain the timeliness of calculations, improves the dynamic accuracy of the carbon footprint at the end-of-life stage, and ensures consistency by linking with the material recycling factor table.

[0091] For example, the acquisition of data on the types and weights of recycled materials can be combined with image recognition technology to assist in classification. For instance, scanning recycled fragments can automatically identify the type of steel and weigh it to generate data. This innovation helps to accelerate the processing, and its benefits lie in improving efficiency and reducing human error, thereby enhancing the reliability of net carbon emissions values ​​and integrating them into the complete emissions data chain.

[0092] In one possible implementation, the step of generating net carbon emissions values ​​could further include a data verification mechanism, such as cross-checking the logical consistency between total emissions and emission reduction data, for example, verifying that the amount of reductions from recycling does not exceed potential emissions. This would improve data integrity, benefit the traceability of the carbon footprint throughout the end-of-life phase, and support the full lifecycle management of oxygen-enriched combustion systems in industrial furnaces.

[0093] The unique carbon footprint identifier is associated with the physical entity of the component and is used for cumulative carbon footprint tracking at each stage of the entire life cycle.

[0094] A unique carbon footprint identifier is generated for each oxygen-enriched equipment component. This identifier is permanently linked to the component through engraving or attaching RFID tags. During the manufacturing phase, the initial carbon footprint value corresponding to the material origin and processing technology is written into the database record corresponding to the unique carbon footprint identifier. During transportation and installation, the initial carbon footprint value associated with the unique carbon footprint identifier is retrieved from the database record. This value is then added to the incremental carbon emissions from logistics calculated based on transportation distance, load capacity, and vehicle type, as well as the incremental carbon emissions from construction, to form an updated cumulative carbon footprint value, which is stored in the same database record. During operation, real-time monitoring of equipment operation data retrieves the oxygen enrichment energy consumption, fuel consumption, and flue gas emission concentration associated with the component corresponding to the unique carbon footprint identifier. This data is dynamically added to the existing cumulative carbon footprint value in the database record, enabling continuous carbon footprint tracking during operation. During maintenance and scrapping, the latest cumulative carbon footprint value corresponding to the unique carbon footprint identifier is retrieved from the database record. The additional emissions from spare parts replacement and performance degradation, as well as the carbon emissions from dismantling and recycling processes, are added to form a complete carbon footprint trajectory throughout the component's entire lifecycle.

[0095] In one possible implementation, the process of generating unique carbon footprint identifiers for oxygen-enriched equipment components can be achieved by using laser engraving technology to directly mark QR codes on the component surface for permanent association. This ensures the identifiers are resistant to wear and easy to scan, allowing for the efficient writing of initial carbon footprint values ​​corresponding to material origins (e.g., steel production location) and processing techniques (e.g., forging methods) into a database during the equipment manufacturing phase. This improves data entry accuracy and facilitates subsequent tracking. For example, after retrieving the initial carbon footprint value associated with the unique carbon footprint identifier from the database during the transportation and installation phase, the calculation of cumulative logistics carbon emission increments can be based on standard emission factors (e.g., carbon emissions per kilometer from diesel trucks) multiplied by the actual transportation distance and load. Carbon emission increments generated during construction are quantified by recording the fuel consumption of on-site machinery such as cranes, forming an updated cumulative carbon footprint value, which is then stored. This approach maintains the continuity and integrity of carbon footprint data, facilitating subsequent cumulative tracking and preventing data gaps.

[0096] In one possible implementation, the process of acquiring component-related oxygen enrichment energy consumption, fuel consumption, and flue gas emission concentration through real-time monitoring of equipment operation data during the operation phase can be achieved using a sensor network installed on the furnace. These sensors collect data in real time and transmit it to a central database, dynamically accumulating it to the existing carbon footprint cumulative value. The purpose of this is to capture immediate changes during operation, and the beneficial effect is to achieve continuous tracking of the carbon footprint and support optimized energy use to reduce overall emissions. For example, during the maintenance and decommissioning phases, the latest carbon footprint cumulative value is continuously obtained from the database, and the additional emissions from spare parts replacement and performance degradation, as well as the carbon emissions from dismantling and recycling processes, are added separately. Additional emissions can be calculated by assessing the material carbon footprint corresponding to the frequency of spare parts replacement and the energy efficiency loss caused by performance degradation, while dismantling and recycling quantifies the emissions from the production of new materials reduced by the recovery of metals, forming a complete carbon footprint trajectory for the entire life cycle of the component. The rationale for this is to cover emission sources at all stages, and the beneficial effect is to provide comprehensive data to support environmental assessments and sustainable improvements.

[0097] One possible approach involves examining the association between the unique carbon footprint identifier and the physical entity of the component from multiple perspectives. For example, using heat-resistant RFID tags instead of imprints in high-temperature environments can prevent damage, thus supporting the reliability of lifecycle tracking. Another aspect is the standardized format of database records to ensure data compatibility across different stages, which facilitates cross-stage accumulation without information loss. For instance, to provide multi-directional support for incremental carbon emissions in logistics, the accuracy of increments can be verified by calculating them from different modes of transport, such as land and sea. This improves the comprehensiveness of the calculations and results in more accurate cumulative values ​​to support decision-making.

[0098] In one possible implementation, monitoring flue gas emission concentrations during operation can be cross-validated with fuel consumption data to identify abnormal emissions. This is done to enhance data reliability and, consequently, to achieve accurate and continuous carbon footprint tracking and early intervention in high-emission issues. For example, quantifying the additional emissions from performance degradation during maintenance can be supported by analyzing degradation curves from historical operating data, while the reduction in carbon emissions from recycling during the end-of-life phase can be illustrated by comparing the emissions difference between recycled materials and new materials. These multiple directions support each other, forming a consistent and complete trajectory, which comprehensively reflects the dynamic changes in the carbon footprint of components from manufacturing to end-of-life.

[0099] The carbon footprint life trajectory map is generated based on the unique carbon footprint identifier and includes the temporal and spatial dimensions of the carbon footprint increment at each stage.

[0100] Each component of the oxygen-enriched equipment is assigned a unique carbon footprint identifier, which is then linked to the physical entity of the component. During the manufacturing phase, the initial carbon footprint value corresponding to the material's origin and processing technology is recorded, forming an initial carbon footprint record containing timestamps and geographical locations. During transportation, installation, operation, maintenance, and disposal, incremental carbon footprint data is continuously collected based on the unique carbon footprint identifier. Each collected data point is appended with time and spatial dimension markers and accumulated into the record chain under the corresponding identifier. The carbon footprint increments at each stage and their corresponding time and spatial dimension markers are extracted from the record chain associated with the identifier, constructing a continuous time-series and spatial distribution data set. Based on this time-series and spatial distribution data set, a carbon footprint lifecycle map is generated, directly displaying the changing trends of carbon footprint increments at each stage in the time dimension and their distribution characteristics in the spatial dimension.

[0101] In one embodiment, the process of assigning a unique carbon footprint identifier to components of oxygen-enriched equipment can use QR codes or RFID tags as identification carriers, directly embedded in the surface of the components, thereby ensuring a permanent binding between the identifier and the physical entity. This binding prevents confusion in subsequent data collection and improves tracking accuracy. For example, for steel components, during the manufacturing stage, the material source, such as mining areas in Hebei, can be obtained from the supplier database, and the carbon emission intensity of processing techniques, such as rolling, can be recorded. By multiplying this by the material mass, an initial value is calculated, forming a record with a timestamp, such as the manufacturing date, and a geographical location, such as the factory coordinates. This helps to lock in baseline emission data from the source, providing a basis for subsequent accumulation, thereby achieving seamless integration throughout the entire life cycle.

[0102] Specifically, when collecting incremental data during the transportation and installation phase, information is read by scanning the identification code of the equipment, recording the emission increments caused by transportation distance and tool type such as truck, and adding time dimensions such as departure and arrival times and spatial dimensions such as path coordinates. This continuous collection ensures that emissions at each stage are not missed, and the data is accumulated to form a dynamically growing data structure, which is beneficial for reflecting the evolution of the component's carbon footprint in real time and avoiding assessment bias caused by data gaps.

[0103] In one embodiment, for energy consumption during the operation phase, such as the oxygen enrichment process, fuel consumption and flue gas concentration data are collected and accumulated after adding operating time and equipment location markers. This not only quantifies daily increments but also supports later analysis of component efficiency changes through chain accumulation. For example, during the maintenance phase, spare parts replacement data is collected for performance degradation, along with maintenance time and site location. After accumulation, the chain fully records additional emissions, which helps identify high-energy-consuming links and optimize maintenance strategies to reduce the overall carbon footprint.

[0104] Specifically, when extracting increments and their markers from each stage of the record chain, a data query interface is used to filter temporal and spatial information, constructing time series such as monthly emission curves and spatial distributions such as global supply chain maps. This construction process integrates scattered data into a continuous set, making it easier to visualize and track the path changes of components from manufacturing to scrapping, thereby improving the comprehensiveness of the assessment.

[0105] In one embodiment, when generating maps based on time series data, a line graph is used to display incremental trends over time, such as emissions gradually increasing from post-installation to maintenance peaks. This directly reveals the patterns of change and is beneficial for predicting future emissions and adjusting the process. For example, for spatial distribution, a heat map is used to display incremental characteristics in geographical locations, such as high emissions concentrated on long-haul routes during transportation. This helps identify regional carbon-intensive areas and guides logistics optimization to reduce the overall footprint.

[0106] Specifically, after extracting and dismantling recycling data during the end-of-life stage to construct a set, a map is generated to show the complete trajectory from the beginning to the end. This display not only visualizes the time and space records, but also supports decision-makers in adjusting system design through trend and feature analysis, reducing life cycle emissions, and achieving sustainable regulation.

[0107] The unified carbon footprint data integration platform extracts material procurement lists and supplier carbon emission declaration data from the ERP system, including material quality unit emission intensity data carried in the material procurement lists, and the supplier carbon emission declaration data associated with the source emission coefficient.

[0108] In a unified carbon footprint data integration platform, a material procurement list is obtained from the Enterprise Resource Planning (ERP) system. This list includes the procurement quantity of each material and the corresponding supplier identifier. For each material in the list, its quality data and pre-associated unit emission intensity data are recorded. Supplier carbon emission declaration data is also obtained from the ERP system. This data includes the supplier's source emission coefficient for specific materials, and the source emission coefficient is matched with the corresponding material quality data in the material procurement list using the supplier identifier. For each matched material, the material quality data is multiplied by the unit emission intensity data to obtain the first emission amount, and then multiplied by the associated source emission coefficient to obtain the second emission amount. The first and second emission amounts are added together to obtain the complete initial carbon footprint value for each material, and this complete initial carbon footprint value is stored in the data record of the corresponding equipment manufacturing stage in the unified carbon footprint data integration platform.

[0109] In one possible implementation, the process of obtaining a material procurement list from an enterprise resource planning system involves querying purchase order records stored in a database. These records detail the name of each material, the quantity purchased, and the unique identifier of the supplier. For example, in the procurement of steel materials, the list would record the code of a specific supplier for 1,000 kilograms of steel, thereby ensuring the accuracy of subsequent data association. This provides basic material information for carbon footprint calculation, avoids assessment bias caused by missing data, and improves overall traceability efficiency.

[0110] For example, in the refractory material procurement scenario, the material procurement list will further include quality data such as the total weight of each batch of materials, and pre-link unit emission intensity data. This means that the platform directly binds the emission intensity value of each kilogram of material, such as the carbon dioxide equivalent, to the list item through a built-in mapping table. This process helps to quickly quantify the initial emissions in the manufacturing stage and supports refined accounting.

[0111] In one possible implementation, the steps of obtaining supplier carbon emission declaration data from the enterprise resource planning system include extracting the declaration documents submitted by the suppliers, which detail the source emission factors for specific materials. For example, a declaration for steel may cover emission factors throughout the entire process from ore mining to smelting. These factors are then matched with supplier identifiers such as unique codes and linked to material quality data in the procurement list. This association ensures the reliability of the emission data source and provides a complementary perspective for comprehensive calculations, avoiding bias from a single data source.

[0112] For example, in supplier declaration data, the source emission coefficient represents the carbon emission intensity upstream of material production, such as the coefficient value caused by coke consumption in the blast furnace steelmaking process. Through the matching mechanism, the platform can apply this coefficient to the quality data of the corresponding material, thereby revealing hidden emissions. This helps to enhance the comprehensiveness of carbon footprint assessment and promote supply chain optimization.

[0113] In one possible implementation, the process of calculating the first part of the emissions for each matched material is to multiply the material mass data by the unit emission intensity data. For example, for a certain weight of refractory material, the mass multiplied by the preset intensity value yields the direct emissions from the manufacturing process. This calculation separates the different emission components, making it easier to sum them up to form a complete view and supporting targeted control of high-emission materials.

[0114] For example, the calculation of emissions in the second part is also based on material quality data multiplied by the source emission factor. This captures upstream indirect emissions, such as energy consumption in the raw material extraction stage. In this way, the two parts of the calculation support each other to ensure that the carbon footprint covers the chain from source to manufacturing, thereby improving the depth and accuracy of the assessment.

[0115] In one possible implementation, the process of adding the first part of emissions to the second part of emissions to obtain the complete initial carbon footprint value for each material involves a simple arithmetic operation, but emphasizes verifying data consistency before summing, such as ensuring that the unit is uniformly in tons of CO2 equivalent. The resulting initial value represents the total emissions at the material level and is stored in a dedicated record area in the equipment manufacturing stage of the platform, supporting full lifecycle tracking.

[0116] The unified carbon footprint data integration platform obtains electricity consumption and diesel usage records from the construction management system, and adds the timestamps of the electricity consumption and diesel usage records to the carbon footprint increment of the transportation and installation phase after alignment.

[0117] Electricity consumption and diesel usage records are extracted from the construction management database. For each record, its corresponding timestamp and consumption data are obtained. These records are initially organized chronologically to form a time-series dataset containing timestamps and consumption data. A timestamp alignment operation is performed on the organized time-series dataset, matching the electricity consumption and diesel usage records with the activity time range of the transportation and installation phase. If the timestamp of a record falls within that phase, it is categorized as consumption data for the transportation and installation phase, forming an aligned phase consumption list. From the aligned phase consumption list, the specific values ​​of electricity consumption and diesel usage are read. Based on a pre-established carbon emission coefficient table, each consumption item is multiplied by its corresponding emission coefficient to calculate its respective carbon footprint increment, generating a phase carbon footprint increment detail. The values ​​in the generated phase carbon footprint increment detail are summed to obtain the total carbon footprint increment data for the transportation and installation phase. This data is then integrated into a unified carbon footprint data platform for subsequent association and aggregation with carbon footprint data from other phases of the equipment's entire lifecycle.

[0118] For example, when extracting electricity consumption and diesel usage records from a construction management database, the process first involves querying log files stored in the database. Each record contains a timestamp such as 2023-01-15 08:00 and a consumption amount such as 100 kWh of electricity or 50 liters of diesel. This ensures that the data accurately captures the details of energy use in construction activities, which is beneficial for subsequent integration to avoid omissions and thus provides a complete foundation for carbon footprint calculation. For example, at an industrial furnace installation site, after extracting the records, they can be organized into a sequence dataset in chronological order, which can reflect the peak energy consumption during peak periods. This helps to identify unnecessary waste and optimize processes.

[0119] When performing timestamp alignment on the processed time series dataset, the timestamp of each record is compared with a predefined time range for the transportation and installation phase, such as from 2023-01-10 to 2023-01-20. If the timestamp, such as 2023-01-12 10:00, falls within the range, it is classified; otherwise, it is excluded. This method can accurately classify data attribution, which helps prevent cross-phase confusion and improves the reliability of carbon footprint tracking. For example, during the matching process, if the timestamp of the diesel usage record coincides with the installation activity, an aligned phase consumption list is formed. This supports subsequent calculations to avoid data deviation and lays the foundation for correlation for full life cycle analysis.

[0120] When retrieving specific figures for electricity consumption and diesel usage from the aligned phased consumption inventory, the incremental values ​​are calculated by multiplying the consumption by a pre-established carbon emission coefficient table, such as 0.5 kg CO2 equivalent per kilowatt-hour of electricity and 2.7 kg CO2 equivalent per liter of diesel. This process quantifies the actual environmental impact of energy and helps generate accurate details of the phased carbon footprint increments, facilitating auditing and reporting. For example, in the calculation, the increment for 100 kilowatt-hours of electricity is 50 kg CO2 equivalent, and for 50 liters of diesel, it is 135 kg CO2 equivalent. This helps to reveal emission hotspots during the transportation and installation phases and connects them with data from the operation phase.

[0121] For example, when summing up the values ​​in the generated stage carbon footprint increment details, the total carbon footprint increment data for the transportation and installation stage, such as 185 kg CO2 equivalent, is obtained by summing all increments, such as electricity and diesel. This data is then integrated into a unified carbon footprint data platform. This enables unified data management and facilitates the correlation and aggregation of carbon footprint data from other stages, such as equipment manufacturing or maintenance, thereby forming a complete life cycle view. For example, after integration, the platform can query the ratio of total increment to overall emissions, which supports decision-makers in optimizing energy use and ensuring the consistency of the tracking system.

[0122] The unified carbon footprint data integration platform reads combustion data such as fuel flow, oxygen concentration, and flue gas composition from the DCS system in real time. The combustion data is then dynamically accumulated into the carbon footprint during the operation phase after being standardized by format conversion.

[0123] Raw data on oxygen concentration, fuel flow rate, and flue gas composition are acquired in real time from a distributed control unit. This data is initially processed according to a pre-established format specification to ensure the integrity and consistency of the data fields. The processed data is then standardized in units, converting different sources of measurement units into a unified reference unit to ensure the accuracy of subsequent cumulative calculations. The standardized fuel flow rate, oxygen concentration, and flue gas composition data are correlated with timestamps to generate a chronologically ordered combustion data sequence, dynamically reflecting emission changes during operation. This combustion data sequence is then combined with pre-established emission calculation rules to update the total carbon footprint during operation through a progressively cumulative approach, ensuring real-time tracking of emissions during the oxygen-enriched combustion process in industrial furnaces.

[0124] For example, when acquiring raw recorded data of oxygen concentration, fuel flow and flue gas composition in real time from a distributed control device, the device is first connected through a preset interface protocol to ensure the stability and immediacy of data transmission. This allows for timely capture of fluctuations in the combustion process and avoids carbon footprint calculation errors caused by data delays.

[0125] In one possible implementation, these raw record data are initially organized according to pre-established format specifications. For example, fuel flow rate is recorded in cubic meters per hour, oxygen concentration is expressed as a percentage, and flue gas components such as carbon dioxide content are labeled as volume percentages. This ensures the integrity and consistency of data fields, thereby providing a reliable foundation for subsequent processing. The useful technical effect of doing so is to improve the compatibility of the data integration platform and reduce errors caused by inconsistent formats.

[0126] In one possible implementation, standardized data on oxygen concentration, fuel flow rate, and flue gas composition are associated with timestamps to generate a combustion data sequence arranged in chronological order. For example, sampling points are marked every minute by timestamps to form a sequence such as the change in oxygen concentration corresponding to the peak of fuel flow rate at a specific moment. This is used to dynamically reflect emission changes during the operation phase. This approach offers the advantage of real-time monitoring, helps identify peak emission periods, and optimizes combustion efficiency.

[0127] For example, the generated combustion data sequence is combined with pre-established emission calculation rules to update the total carbon footprint of the operation phase by cumulatively adding each item. For example, it is based on the fuel flow rate multiplied by the emission factor plus the correction value of the oxygen concentration adjustment, and cumulatively adding each item such as the hourly emission increment. This ensures real-time tracking of emission data during the oxygen-enriched combustion process of industrial furnaces. The role of this step is to achieve dynamic accumulation, maintain continuous updates of the carbon footprint, and thus support the accuracy of the life cycle assessment.

[0128] It should be noted that in practical applications, from acquiring raw record data to unit standardization, then to generating sequences by associating timestamps, and finally accumulating the total amount according to rules, these steps support each other. For example, the initially sorted data is directly input into the standardization process, the standardized data is used for sequence generation, and the sequence is used as the input for accumulation, forming a closed loop. This ensures that the combustion data read from the DCS system is dynamically accumulated to the carbon footprint during the operation phase after format conversion and unit standardization. The useful technical effects of doing so are enhanced data traceability, reduced human intervention, and improved automation of assessment.

[0129] In one possible implementation, considering multi-device scenarios, when acquiring data from multiple distributed control devices, preliminary sorting can unify the multi-source format, standardization processing can further coordinate unit differences, sequence generation can capture the time dynamics across devices, and cumulative updates can integrate into the overall carbon footprint. This indirectly supports the scalability of the platform. For example, in large industrial furnaces, when processing peak data, overload can be avoided to ensure stable operation. Doing so can improve the robustness of the system and enable it to adapt to complex combustion environments.

[0130] For example, in the treatment of flue gas components, the carbon dioxide and carbon monoxide contents are obtained from the original records, standardized into a unified unit after processing, and the trend is observed by correlating the timestamps, such as the concentration increasing with the increase of fuel flow. When accumulating, rules are applied to calculate the cumulative emissions. These multiple directions support each other and jointly ensure the complete chain of data from reading to accumulation. The useful technical effect of doing so is to accurately quantify emissions during the operation phase and support control decisions.

[0131] The unified carbon footprint data integration platform imports spare parts replacement ledgers and consumable requisition records from the maintenance system, including the spare parts replacement ledgers and consumable requisition records, which are then quantified into additional emissions during the maintenance phase after data cleaning.

[0132] Spare parts replacement logs and consumable requisition records are retrieved from the maintenance management system. The original records are cleaned to remove duplicates and missing values, ensuring data field integrity. The cleaned logs are then formatted into a standardized data format. These standardized logs are matched against a pre-established emission factor database. For each type of spare part and consumable, the corresponding unit emission data is determined, and the initial emission value for each replacement or requisition is calculated. Based on the initial emission value, and considering equipment runtime and performance degradation parameters during the maintenance phase, the emission data is adjusted to obtain the adjusted maintenance phase emission increment. This increment ensures that it reflects the impact of spare parts replacement and consumable use on overall energy efficiency. The adjusted maintenance phase emission increment is integrated into a unified carbon footprint data platform. For each component's maintenance record, a complete data chain is formed, from spare parts replacement to consumable use and then to emission increment, for subsequent carbon footprint assessment of the entire lifecycle of oxy-fuel combustion in industrial furnaces.

[0133] For example, the process of retrieving spare parts replacement ledgers and consumable requisition records from the maintenance management system can be implemented through interface calls. For instance, in the maintenance scenario of industrial furnaces and kilns, the system automatically extracts fields such as replacement date, spare parts model, and requisition quantity from the records. This ensures the real-time nature and accuracy of the data source, which is beneficial to the reliability of subsequent carbon footprint calculations. Data cleaning is performed on the acquired raw records to remove duplicates and missing values. For example, if multiple records for the same spare parts appear in the ledger, they are merged into a single valid entry, ensuring the integrity of the data fields. This cleaning avoids calculation bias, thereby improving the accuracy of carbon footprint assessment. The cleaned spare parts replacement ledgers and consumable requisition records are then organized into a standardized data format, such as converting them to a unified timestamp and unit format. This facilitates seamless integration with data from other systems, forming a coherent carbon emission tracking chain.

[0134] One possible implementation involves matching standardized spare parts replacement logs and consumable requisition records with a pre-established emission factor database. For each type of spare part and consumable, corresponding unit emission data is determined. For example, for refractory brick spare parts, the carbon emission factor from their production process is matched, such as 0.5 tons of CO2 equivalent per kilogram. This matching quantifies implicit emissions, which helps reveal the environmental impact of maintenance activities. Preliminary emission values ​​for each replacement or requisition are calculated, for example, by multiplying the spare part's mass by the emission factor. This calculation provides foundational data to support the cumulative assessment of the life-cycle carbon footprint, further connecting to energy consumption analysis during the operational phase.

[0135] In one possible implementation, the adjusted maintenance-phase emission increments are integrated into a unified carbon footprint data platform. For each component, maintenance records form a complete data chain from spare parts replacement to consumable usage and then to emission increments. For example, for combustion chamber components, the chain records the entire process from replacement records to increment calculations. This integration enables data traceability, is beneficial for carbon footprint assessment of the entire life cycle of oxygen-enriched combustion in industrial furnaces, and supports decision-makers in optimizing maintenance plans to reduce overall emissions.

[0136] The present invention provides an industrial furnace oxygen-enriched combustion full life cycle carbon footprint assessment and control system, comprising: a first construction module 100, an identification code establishment module 200, a second construction module 300, and a refined accounting module 400. Wherein: The first construction module 100 is used to construct a full life cycle carbon footprint data model of an industrial furnace oxygen-enriched combustion system, wherein the full life cycle includes the equipment manufacturing stage, transportation and installation stage, operation stage, maintenance stage and scrapping stage; The identification code establishment module 200 is used to establish a unique carbon footprint identification code for each physical component of the industrial furnace oxygen-enriched combustion system. The unique carbon footprint identification code is used to record and accumulate the corresponding carbon footprint increment at each stage of the entire life cycle to form the complete carbon footprint life trajectory of the physical component. The second construction module 300 is used to build a unified carbon footprint data integration platform, which obtains scattered carbon footprint-related data from multiple heterogeneous data sources, and integrates them into a unified data model through data cleaning, format conversion, timestamp alignment and unit standardization. The refined accounting module 400 is used to establish a refined accounting model based on emissions for each physical component. It dynamically calculates and accumulates the carbon footprint at each stage of the entire life cycle based on the corresponding source data, monitoring data and consumption records, forming a complete emissions data chain for the physical component.

[0137] Furthermore, the identifier code establishment module 200 includes: The extraction unit is used to extract the material purchase list and supplier carbon emission declaration data from the ERP system during the equipment manufacturing stage, calculate the initial carbon footprint value by multiplying the material quality by the unit emission intensity, and record it to the unique carbon footprint identifier. The acquisition unit is used to obtain electricity consumption and diesel usage records from the construction management system during the transportation and installation phase, calculate the incremental carbon emissions of logistics based on transportation distance, load capacity and transportation vehicle type, and accumulate them to the unique carbon footprint identifier. The reading unit is used to read oxygen concentration and power consumption data in the air separation oxygen production unit, fuel consumption, flue gas composition and flue gas flow data in the oxygen-enriched combustion industrial kiln from the DCS system in real time during the operation phase. The direct carbon emissions generated by fuel combustion and power consumption are calculated, and the operating carbon footprint is accumulated to the unique carbon footprint identifier. The import unit is used to import spare parts replacement ledgers and consumables requisition records from the maintenance system during the maintenance phase, quantify the frequency of spare parts replacement and the additional emissions caused by energy efficiency decline due to performance degradation, and accumulate them to the unique carbon footprint identifier. The calculation unit is used to calculate the energy consumption of the dismantling equipment and the reduction of carbon emissions by recycling materials during the scrapping stage, and record it to the unique carbon footprint identifier.

[0138] Furthermore, the refined accounting module 400 includes: The initial carbon footprint calculation unit is used to calculate the initial carbon footprint value by multiplying the material mass by the unit emission intensity during the equipment manufacturing stage. The carbon emission increment calculation unit is used to calculate the carbon emission increment during the transportation and installation phase based on transportation distance, load capacity, and transportation vehicle type, combined with construction energy consumption records. The carbon footprint operation unit is used to calculate the cumulative operating carbon footprint of direct carbon emissions from fuel combustion and power consumption during the operation phase by real-time monitoring of oxygen concentration and power consumption data in the air separation oxygen production unit, fuel consumption, flue gas composition and flue gas flow data in the oxygen-enriched combustion industrial kiln. Additional emissions calculation unit, used during maintenance phases to quantify the frequency of spare parts replacement and additional emissions caused by performance degradation; The emission data chain forming unit is used to calculate the energy consumed in dismantling and the reduction of carbon emissions by recycling materials during the scrapping stage, forming a complete emission data chain of the physical component from raw materials to final dismantling.

[0139] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. A method for assessing and controlling the carbon footprint of oxygen-enriched combustion throughout the entire life cycle of industrial furnaces, characterized in that, include: Construct a full life cycle carbon footprint data model for industrial furnace oxygen-enriched combustion systems, and establish standardized data acquisition interfaces and data formats. The full life cycle includes the equipment manufacturing stage, transportation and installation stage, operation stage, maintenance stage, and scrapping stage. A unique carbon footprint identifier is established for each physical component of the oxygen-enriched combustion system of the industrial furnace. The corresponding carbon footprint increment is recorded and accumulated at each stage of the entire life cycle through the unique carbon footprint identifier, forming the complete carbon footprint life trajectory of the physical component. A unified carbon footprint data integration platform is built to obtain scattered carbon footprint-related data from multiple heterogeneous data sources and integrate them into a unified data model through data cleaning, format conversion, timestamp alignment, and unit standardization. For each physical component, a refined accounting model based on emissions is established. The carbon footprint is dynamically calculated and accumulated at each stage of the entire life cycle based on corresponding source data, monitoring data, and consumption records, forming a complete emissions data chain for the physical component.

2. The method as claimed in claim 1, characterized in that, The process involves establishing a unique carbon footprint identifier for each physical component of the oxygen-enriched combustion system in the industrial furnace. This unique identifier is used to record and accumulate corresponding carbon footprint increments at each stage of the physical component's lifecycle, forming a complete carbon footprint lifecycle trajectory for that component, including: During the equipment manufacturing stage, the material procurement list and supplier carbon emission declaration data are extracted from the ERP system. The initial carbon footprint value is calculated by multiplying the material quality by the unit emission intensity and recorded to the unique carbon footprint identifier. During the transportation and installation phase, electricity consumption and diesel usage records are obtained from the construction management system. The incremental carbon emissions of logistics are calculated based on transportation distance, load capacity, and type of transportation vehicle, and then added to the unique carbon footprint identifier. During operation, the oxygen concentration and power consumption data of the air separation oxygen production unit, the fuel consumption, flue gas composition and flue gas flow data of the oxygen-enriched combustion industrial kiln are read in real time from the DCS system. The direct carbon emissions generated by fuel combustion and power consumption are calculated and uploaded to the control center. The operation carbon footprint is accumulated to the unique carbon footprint identifier code to form dynamic tracking of the carbon footprint during operation. During the maintenance phase, spare parts replacement ledgers and consumables requisition records are imported from the maintenance system to quantify the frequency of spare parts replacement and the additional emissions caused by energy efficiency decline due to performance degradation, and these are accumulated to the unique carbon footprint identifier. During the end-of-life phase, the energy consumed by dismantling equipment and the carbon emissions reduced by recycling materials are calculated and recorded in the unique carbon footprint identifier.

3. The method as described in claim 1, characterized in that, The construction of a unified carbon footprint data integration platform involves acquiring scattered carbon footprint-related data from multiple heterogeneous data sources, and integrating it into a unified data model through data cleaning, format conversion, timestamp alignment, and unit standardization. This includes: During the equipment manufacturing stage, material procurement lists and supplier carbon emission declaration data are extracted from the ERP system; During the transportation and installation phase, records of electricity consumption and diesel usage are obtained from the construction management system. During operation, the oxygen concentration and power consumption data of the air separation oxygen production unit, as well as the fuel consumption, flue gas composition and flue gas flow data of the oxygen-enriched combustion industrial kiln, are read in real time from the DCS system. During the maintenance phase, import spare parts replacement logs and consumable requisition records from the maintenance system; Redundant and abnormal data are removed through data cleaning, data structure is unified through format conversion, cross-stage data synchronization is achieved through timestamp alignment, and emission units are standardized to unify the emission dimensions, thus integrating the scattered carbon footprint-related data into a unified data model.

4. The method as described in claim 1, characterized in that, The aforementioned detailed emission calculation model is established for each physical component. At each stage of the entire life cycle, the carbon footprint is dynamically calculated and accumulated based on corresponding source data, monitoring data, and consumption records, forming a complete emission data chain for the physical component, including: Source data is obtained from the blast furnace carbon emission coefficient in the steel smelting stage, the fuel consumption in the refractory material sintering process, and the carbon emission factor of electricity generated from the manufacture of oxygen-enriched equipment. During the equipment manufacturing stage, the initial carbon footprint value is calculated by multiplying the material mass by the unit emission intensity. During the transportation and installation phase, the carbon emission increment is calculated based on the transportation distance, load capacity, and type of transportation vehicle, combined with construction energy consumption records. During operation, by reading the oxygen concentration and power consumption data in the air separation oxygen production unit, and the fuel consumption, flue gas composition and flue gas flow data in the oxygen-enriched combustion industrial kiln, the direct carbon emissions generated by fuel combustion and power consumption are calculated, and the direct carbon emissions are uploaded to the control center. The operation carbon footprint is accumulated to the unique carbon footprint identifier code to form dynamic tracking of the carbon footprint during operation. During the maintenance phase, quantify the frequency of spare parts replacement and the additional emissions caused by performance degradation; During the disposal phase, the energy consumed in dismantling and the carbon emissions reduced by recycling materials are calculated, forming a complete data chain of emissions from raw materials to final dismantling of the physical components.

5. The method as described in claim 2, characterized in that, The unique carbon footprint identifier is recorded and accumulated at each stage of the entire life cycle, including: The unique carbon footprint identifier is associated with the origin of the physical component materials and the processing technology, and the initial carbon footprint value is recorded during the equipment manufacturing stage; The unique carbon footprint identifier is associated with the incremental carbon footprint generated during the transportation and installation phases of logistics and construction. The unique carbon footprint identifier continuously records the carbon footprint of energy consumption associated with the operation phase. The unique carbon footprint identifier tracking and maintenance phase leads to component performance degradation, resulting in additional carbon emissions; The unique carbon footprint identifier records the carbon footprint of the dismantling and recycling process during the end-of-life stage.

6. The method as described in claim 3, characterized in that, The unified carbon footprint data integration platform acquires dispersed carbon footprint-related data from multiple heterogeneous data sources, including: Obtain material procurement and supplier carbon emission declaration data from the materials management system; To acquire electricity consumption and fuel usage records for energy metering systems; Acquire combustion parameters and energy consumption data for the production execution system; The equipment monitoring system reads real-time data on flue gas composition and oxygen concentration. Import spare parts replacement and consumables requisition records into the maintenance management system.

7. The method as described in claim 4, characterized in that, The process of dynamically calculating and accumulating the carbon footprint at each stage of the entire life cycle based on corresponding source data, monitoring data, and consumption records includes: Calculate the initial carbon footprint value during the equipment manufacturing stage based on source data; The carbon emission increment during the transportation and installation phase is calculated based on transportation distance, load capacity, type of transportation vehicle, and construction records. The carbon footprint during operation is calculated based on real-time monitoring data of oxygen concentration and power consumption in the air separation oxygen production unit, fuel consumption, flue gas composition and flue gas flow rate data in the oxygen-enriched combustion industrial kiln. Quantify the additional emissions during the maintenance phase based on the performance degradation caused by spare parts replacement frequency; The carbon footprint at the end-of-life stage is calculated based on energy consumption from dismantling and emission reduction from material recycling.

8. A carbon footprint assessment and control system for the entire life cycle of oxygen-enriched combustion in industrial furnaces, implementing the method described in any one of claims 1-7, characterized in that, The system includes: The first construction module is used to build a full life cycle carbon footprint data model of an industrial furnace oxygen-enriched combustion system, and to establish a standardized data acquisition interface and data format. The full life cycle includes the equipment manufacturing stage, transportation and installation stage, operation stage, maintenance stage and scrapping stage. The identification code establishment module is used to establish a unique carbon footprint identification code for each physical component of the industrial furnace oxygen-enriched combustion system. The module records and accumulates the corresponding carbon footprint increments at each stage of the entire life cycle through the unique carbon footprint identification code, forming the complete carbon footprint life trajectory of the physical component. The second building module is used to build a unified carbon footprint data integration platform. It obtains scattered carbon footprint-related data from multiple heterogeneous data sources and integrates them into a unified data model through data cleaning, format conversion, timestamp alignment and unit standardization. The refined accounting module is used to establish a refined accounting model based on emissions for each physical component. It dynamically calculates and accumulates the carbon footprint at each stage of the entire life cycle based on the corresponding source data, monitoring data and consumption records, forming a complete emissions data chain for the physical component.

9. The system as described in claim 8, characterized in that, The identifier code establishment module includes: The extraction unit is used to extract the material purchase list and supplier carbon emission declaration data from the ERP system during the equipment manufacturing stage, calculate the initial carbon footprint value by multiplying the material quality by the unit emission intensity, and record it to the unique carbon footprint identifier. The acquisition unit is used to obtain electricity consumption and diesel usage records from the construction management system during the transportation and installation phase, calculate the incremental carbon emissions of logistics based on transportation distance, load capacity and transportation vehicle type, and accumulate them to the unique carbon footprint identifier. The reading unit is used to read oxygen concentration and power consumption data in the air separation oxygen production unit, fuel consumption, flue gas composition and flue gas flow data in the oxygen-enriched combustion industrial kiln from the DCS system in real time during the operation phase. The direct carbon emissions generated by fuel combustion and power consumption are calculated, and the operating carbon footprint is accumulated to the unique carbon footprint identifier. The import unit is used to import spare parts replacement ledgers and consumables requisition records from the maintenance system during the maintenance phase, quantify the frequency of spare parts replacement and the additional emissions caused by energy efficiency decline due to performance degradation, and accumulate them to the unique carbon footprint identifier. The calculation unit is used to calculate the energy consumption of the dismantling equipment and the reduction of carbon emissions by recycling materials during the scrapping stage, and record it to the unique carbon footprint identifier.

10. The system as described in claim 8, characterized in that, The refined accounting module includes: The initial carbon footprint calculation unit is used to calculate the initial carbon footprint value by multiplying the material mass by the unit emission intensity during the equipment manufacturing stage. The carbon emission increment calculation unit is used to calculate the carbon emission increment during the transportation and installation phase based on transportation distance, load capacity, and transportation vehicle type, combined with construction energy consumption records. The carbon footprint operation unit is used to read oxygen concentration and power consumption data in the air separation oxygen production unit, fuel consumption, flue gas composition and flue gas flow data in the oxygen-enriched combustion industrial kiln from the DCS system in real time during the operation phase. It calculates the direct carbon emissions generated by fuel combustion and power consumption, uploads the direct carbon emissions to the control center, and accumulates the operation carbon footprint to the unique carbon footprint identifier code to form dynamic carbon footprint tracking during the operation phase. Additional emissions calculation unit, used during maintenance phases to quantify the frequency of spare parts replacement and additional emissions caused by performance degradation; The emission data chain forming unit is used to calculate the energy consumed in dismantling and the reduction of carbon emissions by recycling materials during the scrapping stage, forming a complete emission data chain of the physical component from raw materials to final dismantling.

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